psychological disorders research paper

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What is a mental disorder? An exemplar-focused approach

Dan j. stein.

1 SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa

Andrea C. Palk

2 Department of Philosophy, Stellenbosch University, Stellenbosch, South Africa

Kenneth S. Kendler

3 Virginia Institute of Psychiatric and Behavioral Genetics and Departments of Psychiatry, and Human and Molecular Genetics, School of Medicine/Virginia Commonwealth University, VA, USA

The question of ‘what is a mental disorder?’ is central to the philosophy of psychiatry, and has crucial practical implications for psychiatric nosology. Rather than approaching the problem in terms of abstractions, we review a series of exemplars – real-world examples of problematic cases that emerged during work on and immediately after DSM-5, with the aim of developing practical guidelines for addressing future proposals. We consider cases where (1) there is harm but no clear dysfunction, (2) there is dysfunction but no clear harm, and (3) there is possible dysfunction and/or harm, but this is controversial for various reasons. We found no specific criteria to determine whether future proposals for new entities should be accepted or rejected; any such proposal will need to be assessed on its particular merits, using practical judgment. Nevertheless, several suggestions for the field emerged. First, while harm is useful for defining mental disorder, some proposed entities may require careful consideration of individual v. societal harm, as well as of societal accommodation. Second, while dysfunction is useful for defining mental disorder, the field would benefit from more sharply defined indicators of dysfunction. Third, it would be useful to incorporate evidence of diagnostic validity and clinical utility into the definition of mental disorder, and to further clarify the type and extent of data needed to support such judgments.

Introduction

The question of ‘what is a mental disorder?’ is foundational in philosophy of psychiatry, and also has enormous practical importance for clinicians and patients. This question has therefore been addressed in successive revisions of the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (DSM). Given ongoing work on the revision of DSM-5, it is timely to ask this question again.

Many previous attempts have applied a conceptual approach to the definition of mental disorder. These have produced limited progress, particularly in assisting with decisions about specific conditions. Thus, it may be useful to try a different approach to this critical problem. Rather than focusing on abstractions, we review a series of exemplars – real-world examples of problematic cases that emerged during work on and immediately after DSM-5. From these cases, we hoped to extract practical guidelines for considering future proposals for the inclusion of entities in the nosology.

What is a mental disorder?

The question of ‘what is a mental disorder’, is crucial, in part, because the real possibility exists of erroneously classifying various kinds of social deviance or behavioral variation as ‘disorder’, when they are better conceptualized using other categories, such as ‘non-pathological individual differences’, ‘lifestyle choice’, or ‘crime’. A paradigmatic example from DSM is that of homosexuality, which was conceptualized in DSM-I as a disorder, (American Psychiatric Association, 1952 ) but by DSM-5 was no longer mentioned (American Psychiatric Association, 2013 ; Drescher, 2015 ).

Many authors have emphasized that what counts as a disease or disorder changes over time and across place, and have accused medicine and psychiatry of failing to recognize how idioms of distress are shaped by culture (Kirmayer, 2005 ; Kleinman, 1988 ). Others have accused the DSM of over-medicalizing (Frances, 2014 ; Horwitz, 2007 ; Szasz, 2007 ). These criticisms are driven by disagreements about the advantages and disadvantages of the medicalization of putative mental conditions. Central to these debates is the degree to which our disorders can be best understood as independent biological entities (naturalism/objectivism) or value-laden social constructs (normativism/constructivism) (Agich, 1983 ; Boorse, 1975 ; Fulford, 2001 ; Nordenfelt, 2007 ; Sadler, 2005 ; Stein, 2008 ; Zachar & Kendler, 2017 ).

Prior proposals have attempted to move beyond the polarities of naturalism and constructivism. Zachar suggested that mental disorders are ‘practical kinds’ (Zachar, 2002 ), shifting the issue from whether disorder categories reference scientific entities, to how effectively they facilitate particular scientific or clinical goals (Zachar & Kendler, 2017 ). In influential work, Wakefield defined mental disorders as ‘harmful dysfunctions’, and depicted dysfunction in evolutionary terms (Wakefield, 1992 ).

A strong form of realism holds that, just as the periodic table depicts the properties of molecular entities, so a medical or psychiatric nosology can carve nature at its joints – as a series of ‘natural kinds’ (Kendler, 2016 ; Stein, 2008 ). Softer forms of realism, likely more appropriate for conceptualizing mental disorders, regard exemplars like biological species as more appropriate for psychiatric disorders as the boundaries between different species are fuzzy, and not amenable to depiction in tabular format (Kendler, 2016 ; Stein, 2008 ).

We find aspects of both pragmatic approaches and Wakefield's characterization helpful, and use them as a framework for organizing our exemplars. More specifically, in reviewing real-world cases relevant to DSM-5 we will rely on the notions of ‘harm’ and of ‘dysfunction’. Harm may be indexed by the presence of distress and impairment, while dysfunction may be inferred when psychobiological mechanisms produce symptoms and associated harm. Nevertheless, as our exemplars will demonstrate, judgments about harm and dysfunction entail a range of additional complex considerations.

DSM definitions of mental disorder

DSM has responded to these debates in its definitions of mental disorders. Thus DSM-III emphasizes, for example, that clinicians should not misclassify or label a cultural expression of distress or political deviance as a disease (American Psychiatric Association, 1980 ). Subsequent editions of DSM have emphasized that the boundaries of mental disorders are fuzzy ( Table 1 ) (American Psychiatric Association, 2000 , 2013 ).

DSM-IV definition of mental disorder

During the development of DSM-5, along with others, we attempted to further clarify the DSM criteria for a mental disorder ( Table 2 ) (Stein et al., 2010 ). While our proposal differs modestly from the later DSM-5 wording ( Table 3 ), three differences are relevant here. First, while the DSM-5 definition refers to dysfunction in ‘psychological, biological, or developmental processes,’ we prefer ‘psychobiological’, to emphasize that psychology and biology are intertwined constructs that encompass development, as well as other life-course constructs.

DSM-V proposal for the definition of mental/psychiatric disorder

DSM-5 definition of mental disorder

Second, our proposal suggested that the consequences of a mental disorder are clinically significant distress or disability (B). The DSM-5 wording indicates that mental disorders are usually associated with significant distress or impairment. The word ‘usually’ may be technically accurate, in that on rare occasions, a mental disorder is listed in DSM-5, and there is no ‘clinical criterion’ (First & Wakefield, 2013 ). However, given that psychiatric symptoms are often on a continuum with normality, the clinical criterion is one key way of providing a relatively valid and reliable marker of underlying dysfunction, so lessening the risk of false positives and over-medicalization (Cooper, 2013 ). Other ways in which clinical criteria can validly and reliably point to underlying dysfunction include descriptions of symptom severity, excessiveness, frequency, and duration (First & Wakefield, 2013 ).

Third, our proposal made reference to considerations of diagnostic validity and clinical utility. This explicitly emphasizes that decisions about proposals for new entities must address empirical data. Certainly, data on diagnostic validity and clinical utility of proposed entities were carefully assessed during the DSM-5 revision process.

Examining different exemplars

We now turn to a number of test-cases that emerged during DSM-5. While conceptual work is crucial, it is important to examine its conclusions in the context of specific empirical examples, which may then produce greater clarity on the underlying conceptual issues.

We explore, in turn, several different types of cases, categorized along the following lines: (1) entities associated with harm, but for which there is limited evidence of underlying dysfunction, (2) entities involving dysfunction but without strong evidence that they produce harm, and (3) entities involving possible harm and dysfunction, and thus possibly indicative of a disorder, but which are controversial for various reasons. While the third category deals explicitly with controversial cases, controversy is present in all three categories.

Harm but no clear psychobiological dysfunction

A number of conditions are associated with harm to individuals and/or society, but are not considered disorders because they lack evidence of underlying psychobiological dysfunction. Entities that fall under this rubric include unwanted physical, mental, or behavioral changes (e.g. those that accompany aging), more enduring traits that entail suffering or produce negative impacts but are not considered disorders (e.g. laziness), and behavior that is more appropriately classified as culturally or socially deviant rather than as a mental disorder (e.g. racism). The appropriate responses to distress or impairment associated with these entities would generally be regarded as emanating from moral, cultural, or social domains, rather than from the domain of health. Closer examination of specific exemplars suggests, however, that judgments of whether or not an entity should be included in the nosology reflect a number of different considerations ( Table 4 ).

Key considerations regarding the inclusion of putative entities in the nosology

Aging is associated with a range of negative sequelae. Furthermore, there is a growing understanding of the specific psychobiological mechanisms that lead to symptoms associated with aging and these harms, bolstering the claim that aging involves dysfunction (De Grey, 2007 ). That said, a range of causal mechanisms presumably underly the spectrum of aging from premature aging (e.g. progeria) to typical senescence. Indeed, a view that emphasizes the normality of aging may concede that physicians counsel individuals on a range of measures to sustain health and curb aging but call into question the inclusion of mild neurocognitive disorder in DSM-5. The concern is that this risks pathologizing minor forgetfulness associated with the aging process, particularly given the lack of treatment and the potentially harmful effects of receiving such a diagnosis (Rattan, 2014 ). That said, the more future medical interventions for mild neurocognitive disorder target mechanisms relevant to premature aging, and are shown efficacious and cost-effective, the more useful such a diagnosis will, arguably, be. Thus, judgments about the inclusion of entities in the nosology may, in part, reflect the existence, efficacy, and cost-efficiency of health interventions.

Time-limited and non-incapacitating anxiety associated with threat (e.g. a possible job loss), and suffering associated with loss (e.g. death of a parent), may be experienced as unwelcome, and clinicians may play a useful role in helping to alleviate them. Nevertheless, anxiety and sadness in the face of threat and loss are generally considered to be appropriate, rather than dysfunctional, responses. During the development of DSM-5, there was considerable debate about the removal of the bereavement exclusion criteria from the diagnosis of major depression (Zachar, First, & Kendler, 2017 ). The removal of this clause is consistent with the fact that depressions that are precipitated by a range of other common stressors (e.g. romantic rejection; serious medical problems) were not excluded. While critics argued that this decision reflected over-medicalization, a counter-argument is that it is important to ensure that diagnostic criteria allow appropriate diagnosis and treatment of depression in the context of bereavement (Prigerson, Boelen, Xu, Smith, & Maciejewski, 2021 ). Thus, judgments about thresholds for a putative disorder in the nosology may require consideration of epistemic values such as the internal consistency of criteria.

Racism is a phenomenon that has been associated with great harm and suffering (Schmitt, Branscombe, Postmes, & Garcia, 2014 ). While extreme racism may be a symptom of psychopathology, and there is some evidence of an association between, for example, racism and certain personality types (Adorno, 1969 ), there is little evidence that racism, in general, is the result of underlying psychobiological dysfunction. Rather, there is relatively widespread consensus that racist beliefs and behavior are largely a product of socialization and culture. We would therefore argue that racism is not a disorder; it is a phenomenon that, while sanctioned in some cultures in the past, is now a form of social deviance that should be addressed by a range of different social and educational interventions. Thus, judgments about the inclusion of an entity in the nosology may require rigorous reflection on cultural and social values.

Similar logic would hold for a range of other socially deviant or problematic behaviors (Aristotle, 1985 ), including those redolent of the seven deadly sins of laziness, gluttony, acquisitiveness, aggression, lust, jealousy, and pride. Prima facie, these are more appropriately understood and responded to in moral or socio-cultural terms rather than with health interventions. That said, psychotherapy may usefully target such behaviors or traits, and public health may usefully advocate for healthy eating and sexual behaviors. Furthermore, this matter is complicated by the fact that when clearly excessive, such traits can point to underlying psychobiological dysfunction; indeed, symptoms such as apathy, hyperphagia, hoarding, violence, hypersexuality, obsessional jealousy, and grandiosity may be indicative of a psychiatric disorder, and are appropriately listed in the DSM-5 glossary. Thus, judgments about the inclusion of a disorder in the nosology are based, in part, on evidence of clear excessiveness of behaviors/traits, and associated features that point to dysfunction.

Psychobiological dysfunction but no clear harm

In this category, we include various conditions for which there is some evidence of underlying psychobiological dysfunction, even if this is not fully understood. Conditions in this category may have been regarded as harmful, in the sense of disadvantageous, or socially deviant, in the past, but this view has been contested due to social change. While conditions in this category may point to differences rather than disorder, individuals with these conditions may still experience disadvantage and suffering. It may therefore be crucial to ensure support and treatment for those who seek it. Again, a closer examination of specific exemplars suggests that judgments of whether or not an entity should be included in the nosology reflect a number of different considerations ( Table 4 ).

The notion of disability has been extensively challenged by rights-based advocacy groups and organizations that have focused on promoting inclusivity, equality, and respect (Charlton, 1998 ). A paradigmatic example is deafness, which although not a psychiatric entity, is nevertheless useful as a point of departure for further discussion of analogous behavioral conditions where the presence of harm is contested. Deafness is the result of underlying alterations in structures and mechanisms of hearing, consistent with dysfunction. Moreover, given the challenges of participating in a hearing society, deafness has been widely viewed as disadvantageous, and characterized as a medical condition. However, this has been challenged by the view that deafness itself is not intrinsically harmful; rather, it is societal responses, or lack of response in terms of ensuring adequate accommodation, that produces harm. A view of deafness as a disability has been replaced with a view of deafness as a cultural identity (Padden & Humphries, 2005 ). This identity is referred to as Deaf, rather than deaf, which refers simply to hearing loss. While there have been rare, but controversial, cases of Deaf parents wishing to utilize preimplantation genetic diagnosis to select for deafness, many members of the Deaf community, given the choice of having children with or without hearing, opt for the former (Camporesi, 2010 ; Wallis, 2020 ).

Deaf culture has some parallels with groups that are open about their unusual psychological behaviors or traits, but who argue that these are not associated with harm. It turns out, for example, that hearing voice is prevalent in the general population, and that these experiences may not necessarily be indicative of a serious mental disorder (Maijer, Begemann, Palmen, Leucht, & Sommer, 2018 ). In the absence of harm, it is difficult to argue for the medicalization of such experiences, and there are now support groups for those with these experiences (Longden, 2017 ). That said, hearing voices may be a symptom of a range of mental disorders, other than psychotic disorders, and there is evidence from community surveys that such symptoms are associated with significant disability, which is unlikely to be simply a reflection of lack of social accommodation (Navarro-Mateu et al., 2017 ; Pierre, 2010 ). Thus, judgments about whether or not an entity should be included in the nosology require nuanced assessment of the extent of harm, as reflected in distress and impairment.

Autistic spectrum disorder (ASD) which is associated with alterations in structures and mechanisms underlying behavior (Van Rooij et al., 2018 ), has traditionally been viewed as a harmful condition. However, there is a contrary position, which may be particularly relevant to milder cases of ASD. In this view, the positive attributes associated with ASD (e.g. high levels of creativity and mathematical ability) are emphasized and neurodiversity is celebrated, shifting the onus onto neuro-typical society to accommodate neuro-atypical persons (Glannon, 2007 ). However, despite the growing prevalence of persons with ASD who choose to see themselves as situated on a spectrum of normal variation, there are many individuals and families who seek health interventions or advocate for more scientific research to cure or prevent ASD (Walsh, Elsabbagh, Bolton, & Singh, 2011 ). These disagreements are perhaps indicative of the heterogeneous and dimensional nature of both ASD and its impact; in severe cases care rather than accommodation is required. Thus, judgments about whether or not an entity should be included in the nosology require careful assessment of the extent to which social accommodation is possible.

A similar set of issues emerges for gender identity disorder (GID) or transsexualism, which were removed from DSM-5 and ICD-11 and replaced by gender dysphoria (GD) and gender incongruence, respectively. These latter categories address cases in which there is significant distress due to conflicts between assigned and identified gender. In the case of GD, there is some preliminary evidence of neuroanatomical differences between transgender and cisgender persons which may arguably indicate underlying dysfunction (Burke, Manzouri, & Savic, 2017 ). Moreover, there is also some evidence of harmfulness, for example, a high risk of suicide (Garcia-Vega, Camero, Fernandez, & Villaverde, 2018 ). This could be sufficient for inclusion in our third category, however, we mention GD here because, despite the evidence that distress is intrinsic to the condition, it has also been argued that this distress is a product of stigmatization and social rejection. The shift from social rejection to acceptance of homosexuality, has bolstered this argument for some. On the other hand, from a clinical utility perspective, the inclusion of GD in the nosology is precisely important for ensuring medical and psychiatric care for individuals with this condition who request such care. Judgments about whether or not an entity should be included in the nosology may require careful balancing of the advantages and disadvantages of medicalization (Parens, 2013 ).

Possible harm and psychobiological dysfunction, but controversial

In the third category, we include conditions for which there is some evidence of underlying psychobiological dysfunction and actual or potential harm, but which are controversial for various reasons. First, the controversy may be attributed to a lack of certainty about whether or not a condition does, in fact, reflect underlying psychobiological dysfunction, or whether inclusion would represent over-medicalization. Second, the controversy could arise due to the fact that harm, in the sense of clinically significant distress or impairment, may be present only as a risk, which may not be actualized, so that inclusion of the condition may lead to overdiagnosis. Concerns about medicalization and overdiagnosis both reflect a critical stance towards the expansion of disorder constructs (Hofmann, 2016 ). Third, a condition may be indicative of disorder but considered controversial, in the sense of inappropriate for inclusion in the nosology, due to various pragmatic concerns. This could include a risk of misuse in legal contexts or negative implications for public health. These kinds of pragmatic considerations shift the focus from whether or not a condition is a disorder to whether or not a particular disorder belongs in a diagnostic manual ( Table 4 ).

Medicalization concerns

Compulsive sexual behavior disorder was rejected for DSM-5 but is included in ICD-11 as an impulse control disorder (Grant & Chamberlain, 2016 ). There is a growing evidence base on this disorder. Still, hypersexuality is not necessarily pathological, and there is currently little direct evidence that those who present clinically for the treatment of compulsive sexual behavior have underlying psychobiological dysfunction. Thus, such dysfunction needs to be inferred on the basis of clinical criteria such as severity and duration of symptoms (Kafka, 2010 ). As noted earlier, psychiatry should be wary of medicalizing conditions redolent of the seven sins, focusing rather on advocating for healthy sexual behavior. At the same time, psychiatry clearly has a role when hypersexuality reflects an underlying medical or psychiatric disorder, and it may well have a role when symptoms are truly excessive and associated with a great deal of distress and impairment. For example, it is not clear whether a person who compulsively watches pornography, but is able to limit viewing to the privacy of the home, has a disorder. While personal relationships may be negatively impacted, such a person can be described as functioning, as long as there is control over the behavior. We would be more inclined to regard a person who cannot limit viewing of pornography to a particular time of day or place and feels compelled to watch it while at work, with risk of job loss, as having a disorder. Judgments about whether or not an entity should be included in the nosology may require careful assessment of the degree of loss of control, and related impairment, particularly in the case of compulsive or addictive behaviors.

Internet gaming disorder was included in DSM-5 as a condition for further study, and gaming disorder is included as a mental disorder in ICD-11 (Billieux, Flayelle, Rumpf, & Stein, 2019 ). There is some evidence of underlying alterations in psychobiological structures and mechanisms in gambling disorder, which is included in both nosologies, but less evidence that this is the case in gaming disorder. Behavioral addictions are controversial partly because they raise questions as to whether underlying alterations in structures or mechanisms are sufficient to explain the behavior (which may be viewed as a lifestyle choice rather than as a loss of control). Proposals for new behavioral addictions such as gaming disorder also face the difficulty that there is simply less evidence for newly emergent conditions. Similarly, the brain disease model of substance use disorders has been critiqued (Hammer et al., 2013 ). Still, there is a strong argument that substance use disorders are mental disorders, with evidence of alterations in a range of psychobiological processes that are associated with loss of control, and that can be targeted by health interventions.

Overdiagnosis concerns

Attenuated psychosis syndrome (APS), which is associated both with evidence of psychobiological dysfunction and potential harm in the case of conversion, was included in DSM-5 as a condition for further study (Tsuang et al., 2013 ). APS elicits concerns about overdiagnosis, mainly due to the possibility that interventions for individuals who meet the criteria may cause harm (Zachar, First, & Kendler, 2020 ). There are some parallels between APS and other risk-syndromes such as hypercholesterolaemia or hypertension. Once it was clear that high levels of cholesterol were risky, these were defined as pathological. With the introduction of statins, and evidence that these agents lowered risks, thresholds for diagnosis were lowered; with the introduction of generic statins, and great cost-efficiencies, such thresholds were further decreased. It is possible that an analogous perspective may be useful in defining thresholds for anxiety disorders and depression. However, in the case of APS, there are arguably insufficient data demonstrating risk if untreated, as well as insufficient data demonstrating safety, efficacy, and cost-efficiency of interventions. Moreover, medical risk-syndromes may differ from the risk associated with a psychotic disorder due to the high levels of stigmatization associated with the latter. Nevertheless, it is possible that the issue of whether, and when, to intervene in the case of evidence of psychiatric risk will become increasingly pertinent given the potential for identifying predictive biomarkers – for example, from molecular genetics research (Palk, Dalvie, de Vries, Martin, & Stein, 2019 ).

Suicidal behavior disorder is included in DSM-5 as a condition for further study. Clearly, it is important for clinicians to be aware of suicidal behavior, and this is often an important target of treatment. On the other hand, suicidal behavior may be due to a range of different mental disorders, reflecting a range of different kinds of dysfunction. Furthermore, suicidal behavior is not always associated with a mental disorder; there is a compelling argument that in particular medical circumstances, it is understandable and appropriate for patients to make a decision to end their lives. Suicide can also arise as a form of political protest or a culturally sanctioned response to shame. Judgments about diagnostic validity may be complex, including consideration of a range of different empirical data of varying quality. This point is also exemplified by other entities included in DSM-5 as conditions for further study, namely persistent complex bereavement disorder, depressive episodes with short-duration hypomania, caffeine use disorder, non-suicidal self-injury, and neurobehavioral disorder associated with prenatal alcohol exposure (American Psychiatric Association, 2013 ).

Pragmatic concerns

Simple (type) schizophrenia (SS) or simple deteriorative disorder has long been controversial (Serra-Mestres et al., 2000 ). It has not been included in the nosology since DSM-III (although it was included in DSM-IV as a condition for further study), and while it was in ICD-10 it is not in ICD-11. There is indeed some evidence that simple schizophrenia is a rare deteriorative disorder characterized by nonspecific negative symptoms and an absence of psychotic symptoms. However, while previous iterations of DSM contained schizophrenia sub-types, these were appropriately removed due to a lack of diagnostic validity and reliability, and evidence that schizophrenia is a spectrum disorder (Serra-Mestres et al., 2000 ; Whitwell, Bramham, & Moriarty, 2018 ). Nevertheless, the fact that there continue to be patients who present with these kinds of deteriorative symptoms has been used to support claims that the diagnosis remains relevant (Whitwell et al., 2018 ). This exemplar illustrates that there is a distinction between judgments regarding whether a condition is a mental disorder, and judgments regarding whether it should be included in the nosology.

Paraphilic coercive disorder (PCD) was considered, but ultimately rejected, for inclusion in DSM-5 (Stern, 2010 ). PCD illustrates issues at the boundary between the medical and legal systems, and highlights disagreements about the nature of psychopathology and moral responsibility. There is inconclusive evidence of underlying psychobiological dysfunction or of harm to the individual (other than that following legal transgression) (Knight, 2010 ). However, more relevant here is the real risk of the PCD diagnosis being misused in legal contexts to either inappropriately exculpate a rapist, or to detain persons indefinitely, if deemed to be at risk of sexual reoffending (Wakefield, 2011 ). The debates surrounding PCD highlight how pragmatic considerations inform decisions about nosology. Such considerations include maintaining societal trust in the integrity of psychiatric diagnosis and protecting the reputation of the profession, as well as anticipating potentially harmful consequences of including certain constructs as disorders.

Importantly, as social mores change, so too may considerations about the cost-benefit of including particular entities in the nosology. Premenstrual dysphoric disorder (PMDD), formerly known as late luteal phase dysphoric disorder, is well described in the psychiatric literature. There is clear evidence that specific psychobiological mechanisms are altered in those with this condition, and that those with this condition may benefit from medical treatments (Epperson et al., 2012 ). Still, this entity was not included in DSM-IV, as concerns were raised that the diagnosis would impact negatively on women, confirming stereotypes that they had less ability to fulfil professional obligations (Zachar & Kendler, 2015 ). In DSM-5, perhaps partly because of advances in our understanding of and treatment of PMDD, and perhaps partly because of continued advances in gender parity, PMDD was included in the manual. Judgments about the inclusion of entities in the nosology may need to weigh up responsibilities to patients v. responsibilities to society as a whole.

Taken together, these exemplars may help shed light on key conceptual issues involved in including a proposed entity in the classification.

One set of conceptual issues surround the notion of ‘harm’. Harm refers to suffering or disadvantage associated with a particular condition, and is operationalized with the ‘clinical criterion’ of DSM-5 using the phrase ‘significant distress and/or impairment’. It has often been emphasized, including by DSM-5, that this criterion is ‘fuzzy’, and also that not all distress/impairment points to a mental disorder. However, our exemplars indicate a number of additional complexities.

First, decisions about the introduction of new entities into the nosology need to balance the harm to the individual with harm to society. This is seen in the discussion of PCD and PMDD. The introduction of PCD has significant potential for societal harm, and the proposal to introduce this disorder was rejected. While there were concerns about such harm for PMDD, societal changes have significantly mitigated these concerns, and the proposal to introduce this disorder was accepted. Furthermore, putative PCDs are relatively rare and PMDD relatively common, so the possibility of clinical benefit to those affected is greater for the latter (Hartlage, Breaux, & Yonkers, 2014 ; Robinson & Ismail, 2015 ; Thornton, 2010 ; Wollert, 2011 ). Second, there may be significant debate about the extent to which harm is due to the failure of society to accommodate differences. This is seen in debates around the inclusion of homosexual and gender dysphoria in the nosology. In the former case, exclusion was agreed upon, while in the latter case inclusion was advocated.

While the concept of ‘harm’ is a useful one for defining mental disorder, when new entities are proposed in the future, it will be important to consider, for some of them, more sharply, the issue of individual v. societal harm, as well as the issue of societal accommodation. Notably, our exemplars seem to indicate that profiles of harm may change over time as societies change. Although this is seen in only a very small number of exemplars, this means that we cannot provide future decision-makers with algorithmic advice about what proposal to accept or reject across the board. Just as the clinical criterion requires careful clinical judgment, so in the case of these disorders, decisions will require careful practical judgment, that weighs up a range of relevant considerations.

The second set of conceptual issues is those concerning the notion of ‘dysfunction’. In some medical disorders there is persuasive evidence of biological dysfunction (e.g. in progeria and in schizophrenia, neurogenetic mechanisms are causally linked to distressing and impairing symptoms). However, in many mental conditions, causal mechanisms are poorly understood, and psychobiological dysfunction is inferred on the basis of crude markers such as the severity of symptoms and the extent of associated distress and impairment (e.g. in mild cognitive impairment and in social anxiety disorder). Furthermore, our exemplars point to additional considerations.

In particular, in some cases of putative mental disorder, even though there are symptoms, as well as associated distress and impairment, there are still reasons to doubt the presence of underlying psychobiological dysfunction. First, the symptoms may simply reflect apparently normal processes, such as memory loss with age, or bereavement symptoms after a loss. Second, the symptoms may represent an understandable response to particular circumstances, other than those in Table 3 , criterion C. Suicidal ideation, for example, may be reasonable under certain circumstances. Thus, judgments about dysfunction, again, require careful practical judgment, weighing up a range of relevant considerations.

While the concept of ‘dysfunction’ is a useful one for conceptualizing mental disorders, when new entities are proposed in the future, it would be ideal to have more sharply defined indicators of dysfunction. Symptom severity, excessiveness, and duration may be helpful in indexing dysfunction (e.g. pointing to hypersexuality, or obsessional jealousy), but they are rough indicators that run the risk of relying on a statistical definition of dysfunction. At the same time, it is notable how rarely molecular evidence, per se , is able to index dysfunction; crucially, biological difference does not point to dysfunction .

The third set of conceptual issues relates to the type and extent of data required to reach conclusions about harm and dysfunction. In our proposed DSM-5 definition of mental disorder, we emphasized the importance of evidence for diagnostic validity and clinical utility. Diagnostic validity is supported, in part, by data that point to the involvement of specific etiological mechanisms; such data support assertions that psychobiological dysfunction is present and can be addressed by health interventions. Clinical utility is supported, in part, by data indicating that clinical assessment and intervention will be helpful; such data support assertions that harm is present and can be diminished. These issues are not listed in the DSM-5 text defining mental disorders, but our exemplars suggest that they are useful considerations.

Thus, across different proposals for disorders, there have been differences in the type and extent of data that support diagnostic validity and clinical utility. This is apparent in discussions of behavioral addictions, APS, and simple type schizophrenia. In behavioral addictions, some entities (e.g. gambling) have a great deal of data supporting diagnostic validity and clinical utility, while others (e.g. gaming) have fewer supporting data. In the case of simple type schizophrenia there are insufficient data to demonstrate diagnostic validity, and in the case of APS, there are insufficient data to demonstrate clinical utility.

It is notable that most discussions of the definition of mental disorders focus on conceptual issues and are therefore quite different from a data-oriented approach to the validation of entities, once they are considered to be disorders. It may be useful to incorporate explicitly the importance of a validation-oriented approach into conceptual discussions. Some in the field expect that once internet gaming gathers more high-quality validity and utility data, it too will be accepted as a disorder. Our view is that the field should recognize the potential importance of evidence of diagnostic validity and clinical utility in the definition of a mental disorder, and that future revisions further clarify the type and extent of data needed to support such judgments.

In summary, this paper has taken an exemplar-based approach to the question of defining mental disorders. We had hoped to extract a set of practical guidelines that future nosologists could draw on when discussing proposals for new entities. The conceptual issues that emerge from our exemplars are, however, complex, indicating that any future proposal will need to be assessed on its particular merits, using practical judgment. Nevertheless, several proposals for the field emerged. First, while harm is useful for defining mental disorder, some proposed entities may require careful consideration of individual v. societal harm, as well as of societal accommodation. Second, while dysfunction is useful for conceptualizing mental disorders, the field would benefit from developing more sharply defined indicators of dysfunction. Third, it would be useful to incorporate evidence of diagnostic validity and clinical utility into the definition of a mental disorder and to further clarify the type and extent of data needed to support such judgments.

Financial support

This research received no specific grant from any funding agency, commercial or not-for-profit sectors. However, Dan J Stein is funded by the South African Medical Research Council.

Conflict of interest

Dan J Stein has received support from Johnson & Johnson, Lundbeck, Servier, and Takeda for work unrelated to the topic of this manuscript, Andrea C Palk and Kenneth S Kendler have no conflicts of interest.

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• Published: 26 January 2022

Putting the “mental” back in “mental disorders”: a perspective from research on fear and anxiety

• Vincent Taschereau-Dumouchel   ORCID: orcid.org/0000-0002-9245-7934 1 , 2 ,
• Matthias Michel   ORCID: orcid.org/0000-0002-5780-5702 3 ,
• Hakwan Lau   ORCID: orcid.org/0000-0001-8433-4232 4 ,
• Stefan G. Hofmann   ORCID: orcid.org/0000-0002-3548-9681 5 , 6 &
• Joseph E. LeDoux   ORCID: orcid.org/0000-0001-8518-132X 7 , 8  

Molecular Psychiatry volume  27 ,  pages 1322–1330 ( 2022 ) Cite this article

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Mental health problems often involve clusters of symptoms that include subjective (conscious) experiences as well as behavioral and/or physiological responses. Because the bodily responses are readily measured objectively, these have come to be emphasized when developing treatments and assessing their effectiveness. On the other hand, the subjective experience of the patient reported during a clinical interview is often viewed as a weak correlate of psychopathology. To the extent that subjective symptoms are related to the underlying problem, it is often assumed that they will be taken care of if the more objective behavioral and physiological symptoms are properly treated. Decades of research on anxiety disorders, however, show that behavioral and physiological symptoms do not correlate as strongly with subjective experiences as is typically assumed. Further, the treatments developed using more objective symptoms as a marker of psychopathology have mostly been disappointing in effectiveness. Given that “mental” disorders are named for, and defined by, their subjective mental qualities, it is perhaps not surprising, in retrospect, that treatments that have sidelined mental qualities have not been especially effective. These negative attitudes about subjective experience took root in psychiatry and allied fields decades ago when there were few avenues for scientifically studying subjective experience. Today, however, cognitive neuroscience research on consciousness is thriving, and offers a viable and novel scientific approach that could help achieve a deeper understanding of mental disorders and their treatment.

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Introduction

Problems related to fear and anxiety are among the most prevalent forms of mental illnesses [ 1 ] and have been the subject of much research in animals [ 2 , 3 , 4 , 5 , 6 , 7 , 8 ] and humans [ 9 , 10 ]. The success of this pre-clinical research has substantially influenced modern clinical interventions [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. Yet, treatments remain less satisfactory than patients and therapists would like [ 20 , 21 , 22 , 23 , 24 ]. We propose here that one factor, more than all others, has contributed to this state of affairs: the systematic marginalization of the subjective experience of patients as a research topic and treatment target.

Modern theories of emotion started in the late nineteenth century with Charles Darwin [ 25 ] and William James [ 26 ]. Both emphasized subjective experience but in different ways. For Darwin the mental state of emotion caused behavioral and physiological responses in the body, while for James the body responses defined the mental state. Contemporary theories of human emotions, including fear and anxiety, still emphasize the relation between subjective experience, overt behavior, and physiological changes [ 26 , 27 ]. But the subjective component, typically assessed via verbal report, has been viewed as no more important than the others, and, in fact, has often been least valued by scientists. This bias has its roots in the early twentieth century when behaviorists, because of free-wheeling attribution of mental states as causes of human and animal behavior [ 28 , 29 ], shunned subjective experience as a scientific construct [ 30 ]. The trend continued in the middle of the century, when physiological psychologists, mostly from behaviorist backgrounds, began studying brain mechanisms of overt behavior in animals using the methods of behaviorism and embracing its disdain for anything mental [ 31 , 32 , 33 , 34 ]. Although cognitive science was emerging as a new approach to the mind around this time, it treated the mind as a system that processes information rather than one that generates subjective experiences [ 35 ].

Throughout much of the first half of the twentieth century, the subjective mind was nevertheless alive and well in psychiatry, which was dominated by the psychoanalytic approach initiated by Sigmund Freud. But clinical psychologists in the 1950s and 60s began designing new therapies based on behavioral principles [ 36 , 37 ]. And biologically oriented psychiatrists were searching for medicinal treatments, often through behaviorist-inspired studies of animals [ 38 , 39 , 40 ]. Proponents of these approaches were motivated, in part, by a desire to distance themselves from Freud’s legacy. While they had cause to desire a fresh start, rather than simply distancing themselves from Freud’s view of the mind, they dismissed the central role of subjective mental states in mental illness.

During this same time, the cognitive approach to therapy was also emerging in the hands of Albert Ellis [ 41 ] and Aaron Beck [ 42 ], both of whom were initially trained as psychoanalysts. Their twist was to change the focus of subjective distress from unresolved unconscious conflict to maladaptive beliefs and automatic thoughts. However, over the subsequent years, the popularity of the medical model of psychiatry came to be the standard of how to evaluate therapeutic outcomes, and even cognitive approaches began to treat subjective experience as just another factor that contributed to the “disease”. As a result, the tendency to marginalize subjective experience is the norm rather than the exception in the field, despite the fact that the way a patient feels subjectively is a major factor that leads them to seek help, and also shapes their evaluation of whether the treatment has been effective.

Clinicians, of course, have always wanted their patients to feel better as a result of their therapies. But because of the inconsistencies they observed in the self-report of patients during clinical interviews, self-report acquired a bad reputation. As we will see, this was supported by research that questioned the reliability of self-report. But in throwing the baby out with the bathwater, important, empirically useful aspects of self-report were ignored. As therapy became more evidence-based, and insurers demanded objective treatment targets to evaluate treatment success, the scientific merit of self-reports was further marginalized (as reflected in the NIMH RDoC initiative [ 43 , 44 ]).

In this paper, we propose that the marginalization of subjective experience in modern psychology, neuroscience, and psychiatry made it inevitable that the treatments developed and implemented would be less effective than desirable. Specifically, we suggest that treatments designed to target easily measurable behavioral and physiological manifestations, while useful for treating behavioral and physiological symptoms, are problematic as an approach to improving subjective well-being.

We will use fear to make our case, and will argue that, contrary to long-standing and current trends, subjective fear is not just another factor in the emotion fear; it is what the emotion fear is [ 3 , 22 , 45 ]. We believe that the acceptance of this view would allow a deeper understanding of the relation of adaptive to pathological fear and anxiety, and pave the way for new, more effective, approaches for the treatment of prevalent and troubling conditions involving these mental states.

Before laying out our arguments, it is important to point out that fear and anxiety, though related, are different states (see [ 3 ]). Nevertheless, because these terms have often been used interchangeably in the historical literature, we use the terms interchangeably when referring to historical points.

The disease model of fear and anxiety

Early nosological systems emphasized deep-seated psychodynamic conflicts as the latent causes of dysfunction in multiple mental illnesses. Today, the American Psychiatric Association [ 46 , p. 20] defines mental disorders, including anxiety disorders, as “a syndrome characterized by clinically significant disturbance in an individual’s cognition, emotion regulation, or behavior that reflects a dysfunction in the psychological, biological, or developmental processes underlying mental functioning”. Contemporary classification systems, such as the International Classification of Disease (ICD-11) and the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), explain “dysfunction” by adopting a medical illness model that assumes that symptoms reflect latent disease entities. In this perspective, anxiety disorders are a consequence of abnormal brain circuits, neurotransmitters, genes, and/or other biological abnormalities [ 43 ]. It is assumed that pharmacological and/or psychological interventions can be effective treatments because they correct such pathophysiological conditions.

This medical perspective gave rise to the commonly used approach of evaluating the involvement of pharmaceutical and other biological targets using behavioral tests in animals before conducting clinical trials in humans. It was assumed that interventions that proved effective and safe in pre-clinical studies could then be tested in human patients. Because animals lack the ability to give verbal self-reports of their inner feelings, behavioral and physiological responses could be used as proxies for subjective experience.

But contrary to the predictions of the medical model, decades of research have failed to discover new, efficacious pharmacological treatments [ 20 , 21 , 47 , 48 , 49 ]. As a result, the pharmaceutical industry has been eliminating or reducing efforts in psychiatric drug discovery [ 23 , 24 , 50 ]. According to Steven Hyman [ 51 ], former director of the National Institute of Mental Health, the failure of the pharmaceutical industry in the area of psychiatric research is leading to a global healthcare crisis since psychiatric illness is the world’s leading cause of disability, and is resulting in enormous societal burden.

Why has this effort failed? We believe that it was, in fact, doomed from the start by its commitment to a simplistic view of human suffering [ 52 ]. Specifically, the medical model of fear depends too heavily on the assumption that all three aspects of fear (subjective, behavioral, physiological) have a common origin—a fear circuit—in the brain. For instance, the DSM-5 describes fear as including “surges of autonomic arousal necessary for fight or flight, thoughts of immediate danger, and escape behaviors” ([ 46 ], p. 189). This view posits that all three aspects are manifestations of the same underlying circuits. Since we humans are assumed to have inherited our “fear circuits” from our mammalian ancestors, interventions that are effective at normalizing behavioral and physiological proxies in rats and mice should be effective in treating fear and anxiety disorders. To the extent that subjective feelings are also troubling, treating the fear circuit should address those, since fear, like behavioral and physiological responses, is a product of the fear circuit. As noted above, we do not share this view and suggest that subjective and objective responses be addressed separately.

Terminological confusion in the study of “fear”

Fear has received more scientific attention than any other emotion. But there have been two conflicting approaches. The first started with Darwin, who defined emotions like fear as “states of mind” that we have inherited from our mammalian ancestors by virtue of having inherited some feature of their nervous system [ 25 ]. This meshed well with the emphasis on consciousness by both animal and human psychologists in the late nineteenth century [ 53 ]. The second approach began in the early twentieth century when the “behaviorists“ called out psychologists for their rampant and often unjustified use of consciousness as explanation of behavior.

The behaviorists dominated psychology for the next several decades. Consequently, the vast majority of researchers in animal psychology from the 1920s into the 1960s, and even into the 1970s, were either behaviorists, or trained by behaviorists. Despite their disdain for the use of subjective states to explain behavior, behaviorists nevertheless retained the use of subjective state terms (e.g., fear, hunger) to describe the motivations underlying behavior. These researchers did not typically mean that a subjective state of fear or hunger was responsible for avoidance of danger or approach to food [ 54 , 55 ]. Instead, these terms were said to refer to hypothetical intervening variables that connected stimuli with responses [ 56 ]. For example, fear was a functional relation between a dangerous or threatening stimulus and a protective (defensive) response [ 57 , 58 , 59 ].

Meanwhile, biologists studying behavior worked more in the tradition of Darwin. One group, the ethologists, opposed the behaviorist lack of concern with species differences in behavior, but tended to side with them regarding subjective experience [ 60 ]. Another group, physiologists, studied the brain mechanisms of emotional behavior. The well-known work of Cannon, Bard, Hess, Kluver, and Bucy revealed the role of the hypothalamus and temporal lobe in aggressive and defensive behaviors (see [ 2 ]). These researchers were unconstrained by behaviorism and some freely treated the emotional behaviors they studied as indicators of subjective feelings of rage or fear.

In the 1950s some behaviorists became physiological psychologists. That is, their intervening variables became physiological states in brain areas. This move was inspired by the work of the physiologists mentioned above. But physiological psychologists mostly remained true to their behaviorist legacy, treating the physiological factors they studied as non-subjective motivational states, at least initially.

The leading behavioral approach for studying “fear” in animal psychology from the 1940s through the 1970s was Mowrer’s [ 61 , 62 , 63 , 64 ] avoidance procedure ([ 65 , 66 ] For a review, see [ 67 ]). Mowrer proposed that rats are motivated to avoid aversive stimuli (electric shocks) by “fear.” Behaviors that led to successful escape from, and later avoidance of, the aversive stimulus were reinforced by “fear” reduction. An important finding was that early in training heart rate rises, but then once the avoidance response is well-established the rate normalizes [ 65 , 66 , 68 ]. This was interpreted to mean that “fear” leads to the elevation of heart rate. Successful avoidance is then accompanied by a reduction of “fear,” and a decrease in heart rate follows [ 69 ].

Behaviorists like Mowrer treated fear as an intervening variable [ 57 , 64 ]. What did this mean? The natural assumption among behaviorists at the time was that fear was a non-subjective state that controls behavior. But as behaviorism became a less dominant force in psychology, even some behaviorists began to speak about “fear” as if they meant subjective fear, using expressions like “frightened rats” or “rats frozen in fear” [ 65 , 70 ]. Often within a single paper “fear” seemed to refer to a non-subjective state in some sentences, while in others it seemed to imply that the animals were subjectively afraid. This was likely as much about ideology as about how difficult it is to refrain from reverting to the use of an everyday vernacular term for a mental state in a non-mental state way.

Some two decades after starting the field, Mowrer clarified his position, noting that rats freeze and avoid “by-cause of” fear; for him, in other words, “fear” always meant conscious fear [ 71 ]. Though one could have read this between the lines that he penned over the years, the field seems to have been blinded to what he was really saying by their ideology.

Mowrer’s work not only impacted research on animal behavior but also came to be the way that fear was viewed by clinicians. From the beginning, Mowrer was interested in avoidance learning in animals as a tool for understanding pathological human anxiety [ 63 ]. At that time, Freud’s psychoanalytic approach was the dominant clinical approach, and Mowrer proposed that principles of behavioral learning could improve clinical treatments [ 72 ]. Subsequently, Mowrer’s colleague, Neal Miller, continued this effort, writing a book called Personality and Psychotherapy with the psychoanalyst John Dollard [ 73 ]. But by then psychoanalysis was on the wane, and these efforts, rather than broadening the scope of psychoanalytic treatment, paved the way for the emergence of behavior therapy [ 36 ], and then cognitive-behavioral therapy [ 41 , 74 ]. Mowrer’s two-factor theory continues to be cited in contemporary clinical understanding of anxiety [ 75 , 76 , 77 ].

The terminology of fear became even more confusing in the 1970s with the revival of the Darwinian approach adopted by psychological researchers in guise of basic emotions theory [ 78 , 79 , 80 , 81 ]. Fear, in this perspective, was an innate emotion inherited from mammalian ancestors in the form of a neural “affect program“ or “emotion operating system.” Jaak Panksepp [ 80 , 81 ], for example, used evidence implicating the amygdala and periaqueductal gray regions of the brain in the defensive behaviors of rats as the basis for postulating that homologous emotion operating systems underlies, not just behavioral and physiological responses, but also the subjective experience of fear in rats and humans alike.

Many working on the circuits underlying defensive behavior in the behaviorist-oriented physiological psychology tradition at this time did not bother to address the issue of what fear meant, since conscious fear was a non-starter, and they just assumed it was a non-subjective physiological amygdala state. Nevertheless, when discussing the implications of behavioral studies in animals for understanding fear and anxiety as clinical problems, they often talked about fear in the colloquial way.

Because the colloquial way is the way most people, including lay people, journalists, and most scientists not in the fear field, think about fear, the public conversation about fear circuits was about conscious fear. The result was that the idea of the amygdala as the seat of fearful feelings in the brain became a cultural meme, one that also implied that drugs or other treatments that target the amygdala could make people less fearful and anxious [ 18 , 82 , 83 ].

Lang’s three-systems model of fear

As a result of the inconsistent use of the term “fear” in the 40s and 50s, some researchers in the 1960s began to wrestle anew with fear as a scientific construct. The work of Peter Lang was particularly important.

Lang noted a number of instances in the literature which showed that subjective fear experiences (as measured by verbal reports) did not correlate well with objective and measurable behavioral responses (e.g., avoidance behavior) and physiological changes (e.g., in heart rate) [ 84 , 85 , 86 ]. Accordingly, he was critical of the importance that some clinicians placed on subjective states over behavior and physiology.

Under the lingering influence of behaviorism and the growing influence of the new cognitive movement in psychology, Lang proposed that verbal behavior should be repurposed. Rather than using it as a way to assess intangible subjective experiences, it should be used to track more tangible cognitive processes. Treatment could then be focused on altering verbal behavior, which would, in turn, reflect changes in the underlying cognitive processes, much like the way that treatments that change overt behavior or physiological arousal do so because they change underlying processes.

Expressing his scientific distaste for subjective experience, Lang noted: “whether seen as causes or consequences, feelings are beyond the pale of direct scientific inquiry” ([ 87 ], 124). Fear, he said, “is not some hard phenomenal lump that lives inside people” [ 87 ]. Instead, it is a response expressed in three response systems: verbal (cognitive), overt motor, and somatic. The responses corresponding with these were self-report for the cognitive system, behavior (especially avoidance behavior) for the overt motor system, and physiological changes for the somatic system. Therapy, he argued, should focus on changing the specific response systems, since each contributes separately to the overall intensity of fear.

Discordance and desynchrony

Lang’s, “three-system model” stimulated much clinical research and theorizing [ 88 , 89 , 90 , 91 , 92 , 93 , 94 ]. While his views had their greatest impact on clinical research, they also affected basic research in psychology and neuroscience.

One problem was that Lang’s terminology (cognitive, overt motor, and somatic responses) was a bit unclear. For example, “somatic” is more typically used to refer to skeletal-motor responses underlying overt behavior than to visceral autonomic responses (e.g. [ 95 ]). As we proceed we will, therefore, use a more straightforward set of terms: self-report, behavioral, and physiological responses. By “self-report” we specifically mean verbal reports resulting from conscious fear experiences. Such reports can be interpreted as indicating that the person is having, or has had, a subjective experience of fear in the presence of a threatening stimulus or situation. By “physiological responses” we mean increases in skin conductance, heart rate or other visceral changes in the body in response to threatening stimuli or situations. By “behavioral responses” we mean threat-elicited reactions (freezing, flight), as well as threat-motivated instrumental behaviors (avoidance), expressed in the presence of threatening stimuli or situations [ 96 ].

We will use this terminology to discuss two kinds of discrepancies in this literature. The lack of concordance between the three measures of “fear” at a given time is referred to as discordance [ 90 ]. There are many examples of discordance in the literature [ 97 ]. For instance, in the presence of threat, patients have reported high levels of subjective fear, and yet demonstrate normal or even low levels of physiological threat responses (e.g. heart rate or skin conductance measures), while others show the opposite pattern [ 89 , 98 , 99 , 100 , 101 , 102 ]. Other forms of discordance have been observed following pharmacological interventions [ 103 ]. Medications, such as beta-blockers, for example, can dampen the hyperreactivity of the autonomic nervous system (e.g. heart rate acceleration) or behavior (e.g., trembling hands, fidgeting) in the presence of actual or perceived threats without necessarily affecting the subjective experience of anxiety [ 104 ].

Discordance is distinguished from the phenomenon of desynchrony. The latter refers to variations in the levels of the three measures over time. For example, a patient undergoing behavioral therapy for exaggerated fear or anxiety may first show signs of reduced behavioral and physiological symptoms, and gradually demonstrate changes in self-reports of fear later on. This was reported by Lang in early clinical trials [ 105 ]. Another example pertains to the desynchrony between avoidance behaviors and subjective fear. For instance, the presentation of aversive stimuli often generates both avoidance behaviors and subjective reports of fear. But, successful avoidance will typically lead to a decrease in fear reports while avoidance behaviors can persist over extended periods of time [ 106 ].

Cases of discordance and desynchrony emphasize that behavioral and physiological responses that are sometimes correlated with subjective fear should not necessarily be interpreted as indicating that the person is consciously experiencing subjective feelings of fear per se [ 54 , 55 , 107 ]. In fact, for the sake of clarity, if nothing else, we maintain that the mental state term “fear” should be reserved for the mental state, and behavioral and physiological responses should be referred to as “threat” or “defense“ responses.

Considerable confusion in the discordance and desynchrony literature has also resulted from a failure to recognize that in threatening situations a variety of behaviors can result [ 96 ]. Species-typical (innate) reactions (e.g. freezing behavior) are automatically elicited by unlearned or conditioned stimuli, while instrumental responses (e.g. avoidance) are acquired by their consequences and are emitted in appropriate situations. Species-typical reactions to unlearned or conditioned stimuli have reliable physiological correlates that are “wired in” as part of the “defense reaction” [ 108 ], but most avoidance and other instrumental responses do not, since these can be achieved in many ways [ 109 ]. This may account for the poor correlation often observed between physiological measures and avoidance behavior [ 106 ]. Furthermore, instrumental avoidance responses, though often treated as a single class of response, can be due to habit learning, goal-directed action learning, or cognitive deliberation, each of which involves different neural circuits [ 96 , 110 ]. Future studies should adopt a more subtle approach to behavioral measures.

Conceptual challenges

Given that discordance and desynchrony between responses occur, the key question is whether self-report, behavior, and physiology should be interpreted as indicating the existence of different psychological constructs, or whether they should be interpreted as indications of a single multi-faceted underlying construct. This is an issue of construct validity [ 111 ].

Construct validation is typically achieved by establishing robust correlations between the results of different tests purporting to measure the same construct. If measures of self-report, physiological activity, and behavioral responses were systematically correlated, it would be relatively straightforward to interpret them as collectively reflecting a single underlying construct. However, studies have typically found that self-report shares only a modest part of its variance with other measures [ 112 ], with the most optimistic estimates indicating about 27–28% of shared variance [ 113 ].

There are two main views regarding the interpretation of discordance and desynchrony in this literature (for an in-depth discussion of these in relation to construct validity in “fear” studies, see [ 114 ]). The first attempts to salvage a singular fear construct, despite the existence of discordance and desynchrony, by arguing that self-report, behavior, and physiology are each indicators of the same underlying construct (fear), but that they differ in the degree of accuracy with which they reflect the construct. The second posits that the three factors are independent, but interacting, constructs.

Those who favor the first view maintain that using self-reports to assess fear in effect amounts to using an inaccurate measurement procedure. For instance, Fanselow and Pennington (2018) [ 82 , p. 27] argue that the amygdala is a “fear generator” that controls all three response types, but that the most reliable measures are the behavioral and physiological outputs. They write that “the additional machinery needed to generate subjective report probably adds additional noise, rendering it… a less pure and objective measure of fear.” In this view, cases of discordance and desynchrony are explained away as being due to the fact that self-reports are the least accurate of the three measures of fear [ 58 , 82 , 115 ]. According to Fanselow and Pennington (2018), emphasizing the subjective experience of fear will “push us back well over a century to what was truly the dark ages of psychiatry” (p. 28).

In contrast, those who favor the second view posit that cases of discordance and desynchrony indicate the existence of separate factors. For example, LeDoux and colleagues [ 21 , 116 , 117 , 118 ] argue that while behavioral and physiological responses elicited by threats are products of the amygdala, subjective fear reflects a cognitive interpretation that one is in a situation of potential or actual psychological or physical harm. Such an approach is hardly a fringe idea, as cognitive theories are leading explanations of emotions [ 119 , 120 , 121 ]. Recently, the higher-order theory (HOT) of consciousness (see Box  1 ; [ 122 ]), which is usually discussed in relation to visual perception, has been extended as a novel cognitive account of fear and other emotions [ 116 , 123 , 124 ]. According to HOT, consciousness arises when higher-order cognitive structures monitor or meta-represent lower-order information (see Fig.  1 ). A simple version of the higher-order account would be that signals resulting from the consequences of the behavioral and physiological responses generated by the amygdala in the brain and body are re-represented and contribute to the experience of fear. But the model also includes emotion schema and self-schema, as well as meta-representations of semantic and episodic memories. These representations result in a mental model of the dangerous situation, which can fully account for the subjective experience of fear, even in situations where the amygdala activity and body feedback are absent. That this is necessary is clearly indicated by discordance and desynchrony between subjective fear and body arousal. Antonio Damasio [ 125 ] similarly noticed this and proposed “as if body loops” that simulate brain and body activity when these are absent.

Threatening stimuli often lead to subjective fear via the higher-order circuit, and trigger bodily reactions (behavioral and physiological responses) via the defensive survival circuit, in parallel. This higher-order model can account for situations where subjective and objective responses are discordant or desynchronous. For instance, blocking physiological reactions (X1) dissociates them from conditioned or forecasted actions and/or conscious experiences, while blocking physiological reactions (X2) dissociates those from behavior reactions and/or conscious experience. Similar logic applies to X3 and X4. ANS autonomic nervous system.

The controversy surrounding the two perspectives is in part fueled by the long and complex history of subjective reports [ 29 , 126 ]. For instance, some social psychologists have suggested that self-reports about the causes of our own actions are often mistaken [ 127 , 128 ]. The use of self-reports has also been criticized in other disciplines, such as sociology [ 129 ], thus indicating that humans sometimes exhibit surprisingly poor capacities for self-knowledge (for a review, see [ 130 ]). This evidence could be interpreted as suggesting that subjective reports are systematically inaccurate, and are, therefore, unreliable scientific tools.

However, alleged cases of unreliability are not cases in which subjects report about ongoing conscious experiences, but instead are typically cases in which participants report about the causes of their behaviors [ 128 ], or about long-standing psychological attitudes such as their beliefs [ 130 ]. Aside from pathological cases (e.g. Anton’s syndrome), or malicious deceit, there is no significant body of empirical evidence to support a general dismissal of subjective reports about conscious experiences such as perceptual experiences, fear or anxiety [ 131 , 132 ]. As a matter of fact, a wide variety of experiments in fields, such as perceptual psychology [ 133 ], and even more germane, the scientific study of emotions [ 134 ], rely on experimentally controlled subjective reports about what the subject experiences.

According to Borsboom et al.’s [ 135 , p. 1061] definition of validity, “a test is valid for measuring an attribute if and only if (a) the attribute exists and (b) variations in the attribute causally produce variations in the outcomes of the measurement procedure”. Given that self-reports can be interpreted as resulting from variations in metacognitions (cognitive re-representations) that are directly antecedent to the experience of fear, it follows that self-reports are valid indicators of fear experience. On the other hand, since behavior and physiology can sometimes dissociate from the feeling of fear, interpreting them as reliable indicators of fear, if we follow Borsboom, is invalid, though not necessarily useless.

These observations are in line with the second interpretation of discordance and desynchrony in fear research discussed above. As such, we hold that behavior and physiology, on the one hand, result from threat detection and the activity of defense mechanisms, while self-report, on the other hand, results from the metacognitions upon which subjective experience is based. It follows that self-report, which reflects these metacognitions as well (Fig.  1 ), is the only valid indicator of fear as a subjective experience.

Box 1 First-order theories vs higher-order theories

In consciousness science, one core topic of disagreement pertains to the origin of consciousness in the brain. Here, when we say consciousness, we refer to what is sometimes called phenomenal consciousness, that is the qualitative or phenomenal “feel” of experiences. For example, looking at a sunset has a subjective character that can be described in terms of “what it feels like”. This is different from what can be called states of consciousness which are studied, for instance, in minimally conscious patients or sleep. While undoubtedly important, especially for clinical practices, the study of states of consciousness does not directly address the question of how the brain generates this subjective “feel” of things.

While many theories of phenomenal consciousness make vastly different predictions from one another [ 156 ], they can be broadly divided in two categories. First-order theories, such as recurrent processing theory [ 157 , 158 , 159 , 160 ], posit that consciousness originates in brain regions specialized in the processing of a given type of information (for instance, visual or auditory cortices). As we saw in the main text, some authors have suggested that the amygdala might be such a first-order structure in the subjective experience of fear [ 81 , 82 , 161 ]. Another first-order theory, the global neuronal workspace theory, posits that the activity within first-order structures becomes conscious when it is made available to other brain regions through a global broadcasting mechanism.

On the contrary, higher-order theories suggest that these first-order structures may not be sufficient for the information to become conscious [ 122 , 162 , 163 ]. They posit that some additional cognitive processes in other regions may be needed in order to monitor the information. In this perspective, subjective experience arises from a mechanism closely related to metacognition, which also involves the monitoring of one’s own cognitive and sensory processing [ 164 ]. As such, the information represented in first-order structures should remain unconscious if no higher-order processing is involved. With respect to fear, this view posits that the amygdala non-consciously controls defensive behavioral and physiological responses to threats, but that higher-order processes are required in order to generate the subjective experience to the same threatening stimulus [ 54 , 55 , 107 , 116 , 163 ]. In this view, the re-representation of the first-order information (often termed as meta-representation) is a non-conscious antecedent to consciousness. We suggest that treatment strategies that target both the subjective (conscious experience) and objective (behavioral and physiological responses) will be more effective than approaches that primarily focus on objective responses. We also suggest that measures of discordance and desynchrony can provide additional indicators of treatment progress.

Clinical pragmatism

In addition to its scientific merits, our view of the subjective fear construct is consistent with the way patients express their concerns in clinical settings, and is often what they care most about. From a clinical perspective, a problem usually only reaches the level of clinical significance if it is associated with significant subjective distress and/or interferes with the person’s life. Without the subjective experience of distress, it is very difficult to conclude that an individual suffers from an emotional disorder. This is why subjective distress is a core feature of the definition of an emotional disorder (e.g., in the DSM-5). From this perspective, self-report is the most direct measure of the patient’s problem and treatment efficacy. Thus, whether implicit or explicit, the subjective experience of the patient has been the focal point of all mental disorders, especially emotional disorders.

At the same time, self-report data rarely determine the clinical status directly. Instead, the patient’s subjective report is filtered and interpreted by a clinician to derive a clinical assessment. This is in part because clinicians have long recognized that relying only on self-report in their clinical assessment presents some limitations. As we discussed in the “Conceptual challenges” section, self-report about recalled causes of past behaviors [ 128 ] or about beliefs [ 130 ] can sometimes be misleading. Such observations, together with the influence of the behaviorist movement, fueled a general trend in psychiatry research to look for objective (behavioral and physiological) markers of pathology. For instance, although the Research Domain Criteria initiative (RDoC) of the NIMH (the National Institute of Mental Health in the United States) [ 43 , 44 ] purports to recognize the importance of human psychology, its view of self-report is ambivalent at best: “experiential claims represent a kind of “folk” psychology of the self that should [not be] assumed veridical.” It also acknowledges that these claims should not be “simply discounted” [ 44 , p. 292]. As such, the ultimate goal in psychiatry research in modern times has chiefly been to identify biological markers of mental disorders, akin to other medical diseases.

Some have resisted this trend and advocated for the importance of subjective reports [ 136 , 137 , 138 ]. For instance, Edna Foa [ 139 ], a leading clinical researcher, noted that self-report generates “valid measures of key constructs, some of which cannot be measured in any other way, and sometimes are the best measure of the construct of interest”. Similarly, we [ 3 , 21 , 55 ] and others [ 45 ] argued that emotions are first and foremost subjective experiences. As a result, self-report should play a significantly more prominent role in clinical practice. It can be collected through clinical interviews, daily diaries, in vivo exposure, computerized tasks, or using virtual reality approaches. And given that we now have better understanding of the various factors that affect the validity and reliability of self-report, we can work toward improving clinical tools, paving the way for more rigorous and valid assessments of subjective experience in clinical practice.

By distinguishing between physiological, behavioral, and self-report measures, fear and anxiety research can use valid and reliable procedures for addressing each of those constructs when needed. For instance, unlike physiological responses, subjective ratings during an extinction procedure (i.e., expectancy of the unconditioned stimulus) are predictive of post-exposure affective ratings, a clinically meaningful measure associated with the relapse of fear [ 140 ]. Importantly, this association was observed even though subjective ratings were also correlated with physiological responses at various stages of the experiment. Furthermore, another line of evidence comes from a recent meta-analysis indicating that psychotherapy and pharmacotherapy may have very different effects in the brain [ 141 ]. More precisely, the results suggest that psychotherapy might target cognitive processes and schema in the prefrontal cortex while antidepressant medication might primarily affect the amygdala and basal ganglia. As we saw above, there are reasons to believe that objective measures may primarily originate from the defensive survival circuit that includes the amygdala while the subjective experience is likely generated by the higher-order circuit that includes the prefrontal cortex [ 141 , 142 , 143 ]. As such, these examples highlight the added values of considering the three constructs separately as they each provide distinct information and may require different treatment strategies.

Furthermore, by studying how discordance and desynchrony between the three measures naturally occur it may be possible to tailor therapies to the individual needs of patients [ 21 , 144 , 145 , 146 ]. This idea was notably put forward some time ago by Rachman [ 89 ] and Michelson [ 100 ] who suggested that behavioral therapy may be particularly effective if a patient has exaggerated behavioral or physiological responses, but low levels of self-reported fear. Such “tailored” approach must however be used with caution as treating exclusively the objective response systems may lead the subjective system to relapse, and vice versa [ 21 ].

Early reports also revealed gender differences in discordance and desynchrony [ 147 ]. In some situations, men showed lower self-reported levels of negative emotions compared to women even when their physiological responses were high [ 148 ]. As one can imagine, effects like these may well be modulated by age and cultural factors. If we can track what the systematic factors modulating the effects on discordance are, this may help establish that discordance is a real, meaningful phenomenon, and not just due to the noisiness of individual measures. Additionally, such findings may help achieve a better understanding of underlying mechanisms.

Once individuals are identified as having higher degrees of discordance and/or desynchrony, it would be possible to examine how their brain’s structure and physiology might be associated with such variations. In Taschereau-Dumouchel et al. (2020) [ 142 ] we identified brain regions that are specifically important for decoding self-report vs physiological responses to threat. Studying the connectivity between these different regions—as assessed by structural imaging based on diffusion, or resting-state fMRI data—may also predict individual differences in discordance and desynchrony [ 145 , 146 ]. Similarly, machine-learning algorithms trained to predict self-report, physiology and behavior [ 142 , 149 ] could also help us reveal the brain mechanisms associated with discordance and desynchrony. Studying such individual differences in brain processes might therefore help us better understand how discordance and desynchrony are associated with pathological conditions.

As such, distinguishing between the three measures might have great clinical benefits. At the same time, we should not lose sight of the fact that they are related constructs, in part because they are consequences of the same external stimulus. And although the brain processes underlying each are separate, they interact.

Moving forward

To this day, the role of subjective experience in leading theories of emotions remains marginalized. Basic emotions theorists have tended to emphasize the facial expression of emotions, and to a lesser extent, autonomic responses to a greater degree than subjective experiences [ 79 , 150 ]. Cognitive appraisal theorists give more weight to subjective experience than basic emotions theories, but they typically treat it as one component among several that collectively constitute an emotion [ 151 ]. Cognitive construction theories, on the other hand, respect the centrality of subjective experience, and treat it as a conceptualized byproduct of valence and arousal [ 152 ]. Our higher-order theory is, in some sense, constructionist and conceptual in nature, but it has a broader view of the non-conscious precursors [ 107 , 116 , 118 , 123 , 145 , 153 ] and it highlights the idea that the conscious experience is the emotion (also see [ 45 ]).

Considering the marginalized role of subjective experience in emotion research, and the fact that objective measures of physiology and behavior are relatively poor indicators of subjective suffering, we [ 3 , 21 , 55 ] and others [ 45 ], have felt compelled to raise concerns. In some related fields, this issue has long been taken seriously. For instance, in the study of pain, self-report is the traditional gold standard in part due to well-known cases of discordance (see [ 154 ]), not unlike those we emphasized. But research on many mental health disorders has unfortunately not generally benefited from a similar epiphany. With discussions about other disorders also emerging [ 155 ], we think that the time is right for a change.

Progress in the scientific study of consciousness, and recent work applying this knowledge to explore emotional consciousness, opens the door for a new beginning for designing treatments that will hopefully better target subjective aspects of mental disorders. To succeed, though, this will require a reassessment of some of the implicit assumptions of the behaviorist and medical model legacies, both of which linger as sources of unconscious inferences that guide research and theory. However, we are confident that the approach we tout will lead to new interventions, including personalized ones, capable of tackling mental health disorders in a more complete fashion.

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SGH receives financial support from the Alexander von Humboldt Foundation and the James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition—Special Initiative. HL received financial support from the US National Institute of Mental Health (R61MH113772) and The Templeton World Charity Foundation (RA537-01). JELD receives financial support from the National Institute of Drug Abuse, The Templeton World Charity Foundation, New York University, and private donors. VT-D received the financial support from the Canadian Institute of Health Research (CIHR).

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Taschereau-Dumouchel, V., Michel, M., Lau, H. et al. Putting the “mental” back in “mental disorders”: a perspective from research on fear and anxiety. Mol Psychiatry 27 , 1322–1330 (2022). https://doi.org/10.1038/s41380-021-01395-5

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Advances in Understanding and Treating Mood Disorders

• Ned H. Kalin , M.D.

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Mood disorders, primarily major depression and bipolar disorder, are among the most debilitating psychiatric illnesses. Although significant progress has been made, there is much to be learned about their pathophysiology and much to be improved upon regarding their treatment. It is important to acknowledge that considerable work in the past has enhanced our understanding and treatment of mood disorders as evidenced by currently available effective treatments, which range from specific psychotherapies to psychopharmacology to neuromodulation. Still, many of our patients fail to fully respond to treatment or stay chronically ill.

Significant advances have been made in relation to the neurobiology underlying emotion, cognition, and behavior, and multitudes of studies have been performed in clinically ill populations; however, we are still far away from applying most of these findings to the clinical setting. From neuroimaging studies, we have developed a reasonable understanding of the circuity underlying negative emotion, reward, fear, anxiety, cognition, and behavior and have characterized various abnormalities in task and “resting-state” brain function in populations of patients with depression and bipolar disorder. Replicability of many of these findings, especially those in patient populations, has become an issue. Genetic studies are identifying structural genetic variants associated with the likelihood of developing mood disorders. However, the effect size of the influence of any one single-nucleotide polymorphism is quite small, and as with most psychiatric illness, we are understanding that many genes interact to increase susceptibility or provide protection. The use of polygenic risk scores appears to be an effective way to capture the complex genetics of these disorders, and over time this approach has potential to inform clinical care. Environmental factors also play a prominent role in the expression of mood disorders: advances are being made at the molecular level in understanding how environmental events are epigenetically programmed to result in altered gene expression that is informative for understanding the gene-by-environment interactions relevant to mood disorders. Most in the field believe that new effective treatment development depends on elucidating a fundamental understanding of mood disorder–related alterations in specific neural circuits and the molecules within these circuits. In addition, the use of machine learning to capitalize on combining critical components of large data sets (i.e., genetic, epigenetic, circuit function, and environmental events) holds promise for personalized psychiatric treatment approaches.

This issue of the Journal is devoted to providing our readership with a better understanding of where the field is in relation to our understanding and treatment of mood disorders, as well as introducing our readers to new promising findings. The centerpiece of this issue is a broad overview on depression by Dr. Charles Nemeroff, chair of the Department of Psychiatry and Behavioral Sciences at the University of Texas Dell Medical School in Austin. In his insightful and thought-provoking overview ( 1 ), Dr. Nemeroff provides his perspective on how we can conceptualize and integrate the multitude of findings and issues relevant to understanding the heterogeneity of depression, diagnostic criteria, mechanisms associated with depression-related pathophysiology, and insights into current and future treatments. This overview is followed by a comprehensive review focused on the use of hormonal treatment strategies for major depression ( 2 ). Dysregulated hormonal systems (e.g., pituitary-adrenal, thyroid, and gonadal) have long been associated with mood alterations and have been a focus of a vast number of studies investigating the potential role of specific hormonal systems in the pathophysiology and treatment of depression. This review, a product of the APA Council of Research Task Force on Novel Biomarkers and Treatments, synthesizes findings from the existing literature to provide clinicians and researchers with a resource for the evidence underlying hormonal treatment strategies. I particularly want to acknowledge the two co-first authors of this review, Dr. Jennifer Dwyer and Dr. Awais Aftab, who at the time were trainee members on the research council. I had the privilege of working closely with Drs. Dwyer and Aftab on this review and personally thank them for their insights and considerable efforts, which they relate in further detail in this month’s AJP Audio podcast episode.

This issue of the Journal also presents original research articles that address topics related to the treatment of bipolar disorder, the use of a new transcranial magnetic stimulation (TMS) strategy for treatment of refractory depression, and the effects of gender-affirming interventions on the treatment of mood and anxiety disorders in transgender individuals.

Using data from the National Ambulatory Medical Care Survey from 1997 to 2016, Rhee et al. ( 3 ) statistically characterize 20-year trends in the pharmacological treatment of bipolar disorder. Although it is probably not a surprise to somewhat older practitioners who have lived these changes, an important finding from this study is documenting the dramatic increase in the use of second-generation antipsychotics with the co-occurrence of a large reduction in the use of traditional mood stabilizers, such as lithium or valproic acid. The authors also report a considerable decrease in the use of psychotherapy, which may be problematic given the considerable psychosocial issues faced by patients with bipolar disorder. Dr. Michael Thase, from the University of Pennsylvania and an expert in the development and evaluation of new treatments for mood disorders, contributes an editorial that provides further historical context for these changes in treatment as well as the implications of these changes ( 4 ).

In another article, the Stanford group presents extremely promising data toward improving TMS methods for treatment-resistant depression ( 5 ). Capitalizing on intermittent theta-burst stimulation (iTBS), which is approved for the treatment of depression, Cole and coworkers report findings from an open-label trial of 22 patients who underwent an intensive iTBS treatment over the course of 5 consecutive days. Importantly, this early study used resting-state functional connectivity MRI to individualize the treatment target region within the left dorsolateral prefrontal cortex, such that stimulation was placed over the area that was most negatively correlated with the functional MRI signal in the subgenual anterior cingulate cortex (sgACC). This targeting strategy was used as the sgACC is a neural hub that receives the confluence of prefrontal cortical and subcortical information that is relevant to emotion and mood regulation, as well as to depression. One important outcome of the study is the demonstration that this intensive theta-burst treatment protocol was safe for patients. Treatment efficacy was rapid, with a remarkable remission rate of approximately 90%. Drs. Carpenter and Philip, from the Brown Department of Psychiatry and Human Behavior and experts in TMS neuromodulation, provide an editorial emphasizing the exciting treatment prospects supported by the data from this study (6). They also discuss these findings in relation to existing TMS treatment strategies and study design issues, including the small sample size and open-label nature of the study.

Also in this issue, along with an accompanying editorial by Dr. Sven Mueller from Ghent University ( 7 ), is an article that addresses the very important concern regarding the mental well-being of transgender individuals, specifically the effects of gender-affirming treatments on their mental health ( 8 ). In their article, Bränström and Pachankis use Swedish registries to assess mental health visits and outcomes after hormonal and surgical gender-affirming interventions. Compared with the general population, the results demonstrate that transgender individuals had higher numbers of clinical visits for the treatment of depression and anxiety prior to the interventions. The authors initially concluded, and presented in their article, that gender-affirming surgery, and not hormonal treatment, was associated with a subsequent reduction in the need for mental health intervention. However, when the article was initially available online, concerns were raised by some of our readers regarding the conclusions. Based on these concerns, we solicited secondary reviews of the article, including statistical consultation that recommended additional analyses. Among these analyses, the authors compared matched groups of gender identity patients who did and did not receive gender-affirming surgery, which resulted in the revised conclusion that gender-affirming surgery did not provide an advantage in relation to mental health outcomes. A robust discussion of this issue, and other methodologic and interpretive concerns, can be found in the numerous accompanying letters to the editor ( 9 – 15 ), published along with Bränström and Pachankis’ response to these letters ( 16 ) and a note from myself regarding the corrections and the process the Journal followed to vet the concerns that were raised ( 17 ). In addition to a published erratum notice, the Bränström and Pachankis article now includes an addendum referring to this postpublication discussion.

Two articles in this issue address environmental influences on mental health and depression, though in very different ways. One article examines the effects of air pollution on increasing hospital admissions for depression in China, and another article focuses on mechanisms involved in the intergenerational transmission of the effects of trauma. In their article, Gu et al. ( 18 ) present information building on earlier work that draws an association between short-term ambient air pollutant concentration and hospital admissions for depression. Using daily assessments of air pollutant concentrations across 75 cities and admission data from more than 111,000 hospitals, the authors found that from 2013 to 2017, increasing exposure to fine particles (<2.5 μm) and inhalable particles (<10 μm) was associated with increased rates of hospitalization. This association was demonstrated to be present within 7 days of increasing pollutant exposure, and the effects appeared to be particularly strong for nitrogen dioxide. It should be emphasized that in interpreting these findings, there are important methodologic issues that the authors discuss in the limitations paragraph of the article’s Discussion section. Furthermore, these findings represent associational data, which do not address causality. Nonetheless, the authors speculate on the possibility that pollutant-induced oxidative stress and inflammation may be underlying factors that could mediate this interesting and troubling association with depression.

Moving from an epidemiological level of analysis toward a molecular one, the article in this issue by Bierer et al. ( 19 ) characterizes epigenetic changes associated with the intergenerational transfer of traumatic experiences. This article focuses on the FKBP5 gene, which makes a protein that regulates glucocorticoid receptor responsivity. In addition, variation in the FKBP5 gene has been shown to be associated with posttraumatic stress disorder. This article speaks to how traumatic experiences in parents prior to conception may influence the biology and behavior of their offspring. Specifically, the authors replicate and extend an earlier finding in which they demonstrated reduced methylation at a specific site of the FKBP5 gene when measured in blood from the offspring of mothers who survived the Holocaust. The authors show that this effect was strongest in the offspring of mothers who were exposed to the Holocaust at younger ages and that reduced methylation of this site on the FKBP5 gene was associated with lower levels of anxiety and higher levels of basal cortisol levels. Because of the association between reduced anxiety and decreased FKBP5 methylation, the authors speculate that this epigenetic alteration may serve to protect offspring from the influences of stress exposure. The article also provides a helpful, in-depth discussion of the function of the FKBP5 gene and its protein and how this gene may be causally related to the effects of trauma and to pituitary-adrenal function. The present finding, which is an important replication of earlier work, along with other numerous relevant discoveries involving the FKBP5 gene, supports further serious attention to FKBP5 as a risk factor and mediator of stress-related psychopathology.

The disruption of hedonic processes is a cardinal feature of depression, and it is well established that depression is associated with alterations in the activation of reward-related circuits. The article by Rappaport and coauthors ( 20 ) addresses depression at a neural systems level of analysis by focusing on reward-related circuitry and development. This circuitry is complex and brain-wide, including regions such as brainstem dopaminergic nuclei, the ventral and dorsal striatum (i.e., the nucleus accumbens and caudate, respectively), the prefrontal cortex, and limbic structures (e.g., the amygdala, hypothalamus, and hippocampus). In the study presented here, the researchers used a monetary reward task to examine activation of reward-related neural circuitry in adolescents in relation to current symptoms of depression as well as in relation to their lifetime history of depression. The sample used is unique in that prospective assessments of symptoms began at between 3 and 5 years of age. The findings demonstrate the importance of examining both the state and “trait-like” aspects of depression, as the data revealed different patterns of neural alterations in relation to current symptoms compared with an individual’s life history of depression. Specifically, current depression was characterized by blunted activation of the nucleus accumbens when anticipating reward, whereas a cumulative history of depression involved a blunted response across a broader network of cortical and striatal regions. These findings are intriguing and potentially very important. Above and beyond the specific findings, the analytic strategy used in this study emphasizes the value of parsing current symptoms from illness history when characterizing the biology of our patients. The findings suggest that different mechanisms, even within the same general circuitry, may be at play in relation to understanding current symptoms in contrast to longer-term vulnerabilities. The developmental nature of this study is also highly important, as the findings shed light on the earliest manifestations of depression and its potential cumulative effects over development on neural circuit dysfunction. In her accompanying editorial ( 21 ), Dr. Erika Forbes, an expert in mechanisms underlying adolescent depression, highlights the importance of neurodevelopmental research while reviewing and discussing the relevance of these new findings.

In conclusion, this issue presents an in-depth view into important clinical and research issues relevant to mood disorders. The overview on depression presents our readership with where we are in the field and the challenges we face in improving outcomes for patients with depression. The review on the use of hormonal treatments and the articles on treatment trends in bipolar disorder and on gender-affirming interventions in transgender individuals provide information that is immediately applicable to clinical practice. Other exciting findings reveal insights into alterations in reward processing in adolescents with depression, an understanding of how environmental influences affect the risk for developing stress-related psychopathology, and groundbreaking new neuromodulation strategies that may significantly impact treatment outcomes in patients with treatment-resistant depression. It is my hope that this issue of the Journal will enthuse, and provide optimism to, readers about the potential for further advances that will benefit our patients suffering from mood disorders.

Disclosures of Editors’ financial relationships appear in the April 2020 issue of the Journal .

1 Nemeroff CB : The state of our understanding of the pathophysiology and optimal treatment of depression: glass half full or half empty? Am J Psychiatry 2020 ; 177:671–685 Link ,  Google Scholar

2 Dwyer JB, Aftab A, Widge A, et al. : Hormonal treatments for major depressive disorder: state of the art . Am J Psychiatry 2020 ; 177:686–705 Link ,  Google Scholar

3 Rhee TG, Olfson M, Nierenberg AA, et al. : 20-year trends in the pharmacologic treatment of bipolar disorder by psychiatrists in outpatient care settings . Am J Psychiatry 2020 ; 177:706–715 Link ,  Google Scholar

4 Thase ME : Charting sea changes in outpatient pharmacotherapy of bipolar disorder (editorial). Am J Psychiatry 2020 ; 177:651–653 Abstract ,  Google Scholar

5 Cole EJ, Stimpson KH, Bentzley BS, et al. : Stanford Accelerated Intelligent Neuromodulation Therapy for treatment-resistant depression . Am J Psychiatry 2020 ; 177:716–726 Link ,  Google Scholar

6 Carpenter LL, Philip NS : The future is now? Rapid advances by brain stimulation innovation (editorial). Am J Psychiatry 2020 ; 177:654–656 Abstract ,  Google Scholar

7 Mueller SC : Mental health treatment utilization in transgender persons: what we know and what we don’t know (editorial). Am J Psychiatry 2020 ; 177:657–659 Abstract ,  Google Scholar

8 Bränström R, Pachankis JE : Reduction in mental health treatment utilization among transgender individuals after gender-affirming surgeries: a total population study . Am J Psychiatry 2020 ; 177:727–734 Abstract ,  Google Scholar

9 Anckarsäter H, Gillberg C : Methodological shortcomings undercut statement in support of gender-affirming surgery (letter). Am J Psychiatry 2020 ; 177:764–765 Abstract ,  Google Scholar

10 Van Mol A, Laidlaw MK, Grossman M, et al. : Gender-affirmation surgery conclusion lacks evidence (letter). Am J Psychiatry 2020 ; 177:765–766 Abstract ,  Google Scholar

11 Curtis D : Study of transgender patients: conclusions are not supported by findings (letter). Am J Psychiatry 2020 ; 177:766 Abstract ,  Google Scholar

12 Malone WJ, Roman S : Calling into question whether gender-affirming surgery relieves psychological distress (letter). Am J Psychiatry 2020 ; 177:766–767 Abstract ,  Google Scholar

13 Landén M : The effect of gender-affirming treatment on psychiatric morbidity is still undecided (letter). Am J Psychiatry 2020 ; 177:767–768 Abstract ,  Google Scholar

14 Wold A : Gender-corrective surgery promoting mental health in persons with gender dysphoria not supported by data presented in article (letter). Am J Psychiatry 2020 ; 177:768 Abstract ,  Google Scholar

15 Ring A, Malone WJ : Confounding effects on mental health observations after sex reassignment surgery (letter). Am J Psychiatry 2020 ; 177:768–769 Abstract ,  Google Scholar

16 Bränström R, Pachankis JE : Toward rigorous methodologies for strengthening causal inference in the association between gender-affirming care and transgender individuals’ mental health: response to letters (letter). Am J Psychiatry 2020 ; 177:769–772 Abstract ,  Google Scholar

17 Kalin NH : Reassessing mental health treatment utilization reduction in transgender individuals after gender-affirming surgeries: a comment by the editor on the process (letter). Am J Psychiatry 2020 ; 177:764 Abstract ,  Google Scholar

18 Gu X, Guo T, Si Y, et al. : Association between ambient air pollution and daily hospital admissions for depression in 75 Chinese cities . Am J Psychiatry 2020 ; 177:735–743 Link ,  Google Scholar

19 Bierer LM, Bader HN, Daskalakis NP, et al. : Intergenerational effects of maternal Holocaust exposure on FKBP5 methylation . Am J Psychiatry 2020 ; 177:744–753 Link ,  Google Scholar

20 Rappaport BI, Kandala S, Luby JL, et al. : Brain reward system dysfunction in adolescence: current, cumulative, and developmental periods of depression . Am J Psychiatry 2020 ; 177:754–763 Link ,  Google Scholar

21 Forbes EE : Chasing the Holy Grail: developmentally informed research on frontostriatal reward circuitry in depression (editorial). Am J Psychiatry 2020 ; 177:660–662 Abstract ,  Google Scholar

• Cited by None

• Second-Generation Antipsychotics
• Bipolar and Related Disorders
• Depressive Disorders
• Environmental Risk Factors
• Inflammation
• Transgender (LGBT) Issues
• Neurostimulation
• Pharmacotherapy

• Research article
• Open access
• Published: 29 March 2021

Factors contributing to psychological distress in the working population, with a special reference to gender difference

• Satu Viertiö   ORCID: orcid.org/0000-0002-8894-2056 1 , 2 ,
• Olli Kiviruusu 1 , 2 ,
• Maarit Piirtola 3 ,
• Jaakko Kaprio 3 , 4 ,
• Tellervo Korhonen 3 ,
• Mauri Marttunen 1 , 2 &
• Jaana Suvisaari 1  

BMC Public Health volume  21 , Article number:  611 ( 2021 ) Cite this article

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Psychological distress refers to non-specific symptoms of stress, anxiety and depression, and it is more common in women. Our aim was to investigate factors contributing to psychological distress in the working population, with a special reference to gender differences.

We used questionnaire data from the nationally representative Finnish Regional Health and Well-being Study (ATH) collected in the years 2012–2016 (target population participants aged 20 +, n  = 96,668, response rate 53%), restricting the current analysis to those persons who were working full-time and under 65 of age ( n  = 34,468). Psychological distress was assessed using the Mental Health Inventory-5 (MHI-5) (cut-off value <=52). We studied the following factors potentially associated with psychological distress: sociodemographic factors, living alone, having children under18 years of age, lifestyle-related factors, social support, helping others outside of the home and work-related factors. We used logistic regression analysis to examine association between having work-family conflict with the likelihood for psychological distress. We first performed the models separately for men and women. Then interaction by gender was tested in the combined data for those independent variables where gender differences appeared probable in the analyses conducted separately for men and women.

Women reported more psychological distress than men (11.0% vs. 8.8%, respectively, p  < 0.0001). Loneliness, job dissatisfaction and family-work conflict were associated with the largest risk of psychological distress. Having children, active participation, being able to successfully combine work and family roles, and social support were found to be protective factors. A significant interaction with gender was found in only two variables: ignoring family due to being absorbed in one’s work was associated with distress in women (OR 1.30 (95% CI 1.00–1.70), and mental strain of work in men (OR 2.71 (95% CI 1.66–4.41).

Conclusions

Satisfying work, family life and being able to successfully combine the two are important sources of psychological well-being for both genders in the working population.

Peer Review reports

Psychological distress refers to non-specific symptoms of stress, anxiety and depression. High levels of psychological distress are indicative of impaired mental health and may reflect common mental disorders, like depressive and anxiety disorders [ 1 ]. It is commonly measured with self-report rating scales like the General Health Questionnaire [ 2 ] or MHI-5, derived from the RAND-36 questionnaire [ 3 ]. As psychological distress also predicts sickness absences and work disability among the working-age population [ 4 , 5 ], it is important to understand the factors that contribute to psychological distress among those who are working.

According to previous studies, women in the Western world are more prone to psychological distress, depression and anxiety than men [ 6 , 7 , 8 , 9 ]. Proposed explanations for the gender difference include biological, psychological and social risk factors [ 10 , 11 ]. Social factors involve, e.g. different societal roles and expectations for men and women. The roles at work and in the family as well as the challenges in combining them may be one factor contributing to gender differences [ 12 , 13 , 14 ]. However, the combination may also create more content and satisfaction in life, including with respect to possible gender differences [ 15 ].

Work-to-family conflict, family-to-work conflict and work-family enrichment load

Contradictions between work and family, a work-family conflict involves two separate, but related domains. One is work-to-family conflict, also called work-family interference or work interference with family, which occurs when participation in family life is made more difficult by work-related demands [ 16 ]. Family-to-work conflict, also called family-work interference or family interference with work, occurs when family life interferes with work [ 17 ]. In contrast, work-to-family enrichment means that the experiences at work improve one’s performance and satisfaction within the family [ 15 , 18 ]. Role accumulation theory claims that multiple roles and meaningful content in life create a positive conception of oneself [ 19 ].

Work-family conflict has been found to be more common in women, although the gender difference in European countries is currently small [ 20 ]. Women still perform most of the domestic work in families [ 21 ]. Both having children and providing informal care to elderly relatives may increase the experience of work-family conflict [ 20 ]. One negative consequence of work-family conflict suggested by previous research is that women may reduce their contribution in work domain and that in turn may hinder career advancement [ 13 ]. According to European statistics, when the time spent travelling between home and the workplace and doing unpaid work are taken into account, women work on average 64 h a week compared to 53 h for men. Women spend on average 26 h taking care of children and elderly relatives, whereas men spend only 9 h [ 22 ]. It seems that especially during parenting, women have more problems in coordinating work and family life [ 17 , 23 , 24 ].

According to a 2010 European Social Survey, mothers and higher educated employees report the highest rates of work-family conflict [ 25 ]. Highly educated parents tend to experience more work-family conflict than less educated parents because of longer working days and greater difficulty in separating work from leisure time. A work position where an individual has much authority and responsibility to make decisions, has been found to increase the risk of psychological distress [ 26 ].

Other work-related factors

According to a meta-analysis [ 27 ], a low level of job satisfaction is associated with a higher risk of psychological distress, burnout, anxiety and depression. Significant gender differences in job satisfaction have not been found, although women are less likely to work in managerial jobs and their salary is commonly lower [ 28 , 29 , 30 ].

Mental and physical work strain may affect mental health. Mental strain is common in human service work, but while working in these professions may increase the risk of emotional exhaustion and psychological distress, it may also provide meaning in work [ 31 ]. Physical work strain has been found to have a stronger effect on mental health in men than in women [ 32 ].

Social support, loneliness and other social environmental factors

Perceived social support refers to a person’s sense that emotional or practical support is available from others when needed. A lack of social support from one’s partner and close relatives, parents and friends is a risk factor for psychological distress [ 33 ]. There are indications that it operates in different ways for men and women [ 34 ], such as the fact that emotional support is more protective against depression for women than for men [ 33 ]. Women benefit from support more than men in both work and family contexts [ 35 ] and have more supportive networks than men do [ 36 ]. In contrast, women seem to receive less support from their spouses than men do from theirs [ 37 ].

Social support, especially emotional support, is often related to leisure-time activities, such as hobbies or cultural activities, and women tend to gain more benefit from social participation than men [ 33 , 38 ]. It seems that leisure-time activities are associated with better mental health, especially when they include social contacts, and this is true particularly for men [ 39 ].

Emotional loneliness is the absence of someone to turn to in times of need, while social loneliness is the absence of a social network [ 40 ]. Loneliness, which women report experiencing more commonly than men in the general population, co-occurs with mental disorders and psychological distress [ 41 , 42 ], and its association is partly independent of perceived social support [ 43 ]. Accordingly, emotional loneliness is more strongly associated with distress and mental disorders than social loneliness [ 42 ]. Among college students, loneliness has a greater impact on women’s mental health than it does on men’s [ 44 ], but differences between genders have not been found among community dwelling adults [ 45 ].

Marital status appears to be a significant feature in loneliness. Marriage, compared to widowhood and divorce, has been found to be associated with better mental well-being in both genders [ 46 , 47 ], while becoming widowed has more long-term effects among men than among women [ 48 ]. Living alone has mostly been associated with a greater risk of experiencing mental health problems [ 49 ], in some studies particularly among men [ 50 ], and men especially experience greater mortality rates from mental disorders than do women [ 51 ]. However, findings, especially among elderly people, have also shown that living alone is not associated with reduced emotional well-being [ 52 ] or psychological distress [ 53 ].

Studies on parenting and mental health have mainly focused on how parental stress and depression affects children [ 54 ] and a depressed parent’s behaviour as a parent [ 55 ]. Parenthood itself as a risk or protective factor has been studied less often. Some studies have found that parenthood is associated with less mental health problems [ 56 , 57 ], whereas no association between mental health and parenthood has been found when different types of family statuses, like single parenthood and divorce or living alone, have been taken into account [ 58 ].

Other factors

Harmful lifestyle factors, like smoking and heavy alcohol intake, have been found to be associated with an increased risk for depressive symptoms [ 59 , 60 , 61 , 62 ]. Cigarette smoking is more common in lower socioeconomic groups and among people with mental disorders or psychological distress [ 63 , 64 , 65 ]. Moreover, the association between smoking and psychological distress appears to have become stronger in recent decades.

Financial difficulties have been found to be a risk factor for reduced mental health [ 66 , 67 ]. It is not just poverty that causes psychological distress, but also the stigma associated with receiving public assistance [ 68 ]. The risk of suffering common mental disorders, e.g. depression and anxiety disorders, among men and women appears different when viewed by income category; women’s risk is greater than men’s risk in all other categories except the lowest one, [ 69 ], whereas financial difficulties in covering household costs seem to have equal negative effects on mental health both in men and women [ 70 , 71 ].

Informal caregiving, e.g. helping elderly parents, may increase psychological distress, and a recent study has found this to be true for women but not for men [ 72 ]. However, other studies have not found an association between informal caregiving and mental health [ 73 ].

Aims of the study

There is a growing concern in Finland related to increasing rates and widening gender gap in sickness absences and disability pensions related to mental disorders [ 74 , 75 ] Therefore, it is important to study factors contributing to psychological distress in the working population and to identify factors that may relate to these gender differences.

The aim of the current study was to investigate factors contributing to psychological distress among those working full-time, with a special reference to gender differences. A large and representative general population-based survey sample was used, and variables were chosen in the regression models so that they would cover the most important domains that potentially influence psychological distress. Our hypothesis was that factors related to work, family and conflicts in their coordination would be particularly relevant for gender differences associated with psychological distress in the general population.

Design and population

The Regional Health, Wellbeing and Service Use Study (ATH) was set out to provide regional (regions or municipalities) information for monitoring on factors affecting health, wellbeing and service use in Finland. Several questions derived from the study are used as national indicators and reported in the Sotkanet portal (sotkanet.fi). Sotkanet portal provides demographic indicators across Finland and Europe on health, welfare and functioning of the service-system. The survey was targeted at the population of Finland aged 20 years or over, implemented annually from 2010 to 2016. Since 2017, the survey has been called Finsote and its content has changed slightly. A stratified random sampling design, described in detail by Härkänen et al. [ 76 ], was used, and the sampling was done without replacement. The sample was drawn from the Finnish Population Register. Participants were informed about the purposes of the survey, as well as about data security. In the selection phase of the new sample, there is the exclusion of persons who have been included into the samples of the ATH survey in previous years. Inverse probability weighting was used to account for missing data [ 76 ]. Data used in the present study are from nationally representative samples collected in the years 2012–2016 ( n  = 96,668). In the present analyses, we used answers from participants aged 65 years or younger and who were working full-time ( n  = 34,468) (Fig.  1 ). The respondents returned the questionnaire either by mail or online, and it was possible to answer in four languages: Finnish, Swedish, Russian and English. ATH study was approved by the Coordinating Ethics Committee of Finnish Institute for Health and Welfare (THL) in 2010 (approval number THL107/6.01.00/2010).

Flow chart of the sample sizes and response rates to the Finnish Regional Health and Well-being Study and participants in the present study

The questionnaire was designed by a group of scientists and specialists at the Finnish Institute for Health and Welfare with members from Finnish Institute of Occupational Health, the Social Insurance Institution of Finland and Institute of Criminology and Legal Policy. The writers of the article chose the questions into the current study from the original ATH study questionnaire and they are found as an additional file .

Psychological distress was assessed using the MHI-5 [ 3 , 5 ]. MHI-5 is derived from the RAND-36 questionnaire [ 3 ], which is a widely used self-report instrument to measure health-related quality of life. It includes eight concepts: physical functioning, bodily pain, role limitations due to physical health problems, role limitations due to personal or emotional problems, emotional well-being, social functioning, energy/fatigue, and general health perceptions [ 3 ]. The MHI-5 consists of five questions: ‘How much of the time during the last month have you: 1) been a very nervous person, 2) felt downhearted and blue, 3) felt calm and peaceful, 4) felt so down in the dumps that nothing could cheer you up and 5) been a happy person? The six possible responses to the questions were scored between 1 and 6. Items 3 and 5 ask about positive feelings and their scoring was done in reverse. All scores were then converted to fit a range from 0 to 100, with low scores indicating more psychological distress.

There is not one established cut-off point for measuring clinically significant psychological distress by MHI-5 [ 1 ]. We used the cut-off of 52 points, derived from the Eurobarometer survey in 2002 [ 77 ], in which Finland participated as well. The same cut-off score has been used throughout the history of the ATH study. ATH started regionally already in 2009. Cronbach’s alpha, which is a measure of internal consistency, was 0.85.

The variables chosen as potential risk or protective factors for psychological distress are presented in Table  1 ; the table format is adapted from Abbas et al. [ 78 ].

Work-related variables

Potential work-family conflict was assessed using the following question: ‘Are the following statements about home and work accurate for you?’ The respondents were then asked to agree or disagree with six statements. One statement was considered protective: ‘I have more energy to be with the children when I also go to work’. Another statement was considered neutral: ‘When I come home, I stop thinking about my work’. Work interference with family was assessed via three statements: ‘I feel I am neglecting domestic issues because of my work’, ‘I sometimes ignore my family when I am wholly absorbed in my work’ and ‘I feel inadequacy as a parent’. Family interference with work was assessed with the statement ‘I often find it difficult to concentrate on my work because of domestic issues’. The answers were divided into two classes: agree and disagree/cannot say.

Job satisfaction was measured using the following question: ‘How satisfied are you with your present work?’ The responses were divided into four categories: extremely satisfied, fairly satisfied, neither satisfied nor dissatisfied, and fairly/extremely dissatisfied. We merged classes 4 and 5 due to too few observations. Mental and physical strain of one’s work was measured using the following question: ‘What is/was you most recent job like (physically and mentally)?’ Answers were divided into three categories: low strain (light, fairly light), moderate strain (a bit or quite strenuous) and high strain (very strenuous).

Questions related to job satisfaction and strain and work-family and family-work conflict are from the Finnish Quality of Work Life Surveys 1977–2008 [ 79 ].

Sociodemographic and other non-work-related variables

The age of the participants was divided into three categories: 20–34 years, 35–49 years and 50–65 years. Education was likewise divided into three categories: less or equal to 12 years, 13–16 years and 17 years or more. Marital status was categorised as married/cohabiting, separated/divorced/widowed and single. Having children under 18 years of age was divided into a yes or no category. Living alone was likewise categorised based on a response of yes or no. All the participants in the analyses had a full-time job.

Those who reported that they smoke on a daily basis were classified as smokers, others as non-smokers. Alcohol consumption was assessed using the Alcohol Use Disorders Identification Test (AUDIT-C) [ 80 ], which included the following questions: ‘How often do you have a drink containing alcohol?’, ‘How many standard drinks of alcohol do you have on a typical day when you are drinking?’, ‘How often do you have 5 or more drinks on one occasion?’. A total score of six or more for men and five or more for women indicated at-risk drinking.

Subjectively experienced loneliness was divided into two categories: never/seldom/sometimes and often/all the time. Participation in leisure-time activities, such as hobby groups, societies and so forth, was categorised as regular or never/sometimes. Helping parents, children or other people outside the home regularly was defined as occurring at least once or twice a month.

Whether or not respondents received practical support when needed was identified using the following question: ‘Who will provide practical help when you need it?’ For emotional support, the question was worded as follows: ‘Who do you believe truly cares about you, whatever may happen?’. Possible helpers or carers were partner, other next of kin, close friend, close colleague, close neighbours and other persons in close proximity to you. The answers were divided into three categories: no one helps or cares, 1–2 persons help or care, and 3–6 persons help or care. Financial problems were assessed with the question ‘How difficult or easy is it to cover your living costs?’. The responses were divided into two categories: very difficult/fairly difficult and fairly easy/very easy.

Statistical analysis

Analyses were conducted using the SAS Enterprise Guide 7.1 [ 81 ] and SUDAAN Release 11.0.3 [ 82 ]. Weights were used to take into account the sampling design and non-participation, so that the results would be representative of the Finnish working-age population. We calculated the distribution of sociodemographic variables, other non-work-related variables and work-related variables for both genders. Gender differences in the categorical variables were tested using the two-tailed χ2 test. Next we calculated the prevalence of psychological distress in both genders according to the levels of the study variables.

We used logistic regression analysis to examine association between having family-to-work or work-to-family conflict with the likelihood for psychological distress (cut-off value of MHI-5 < =52). Dependent variable in the model was psychological distress (yes/ no) measured with MHI-5 and independent variables, i.e. sociodemographic factors, other non-work-related factors and work-related factors were included in the model simultaneously. We first performed the models separately for men and women. Then interaction by gender was tested in the combined data for those independent variables where gender differences appeared probable in the analyses conducted separately for men and women.

Characteristics of study variables in men and women

Characteristics of the study variables are presented in Table  2 for men and women separately. Women reported more distress than men did, and with most of the other variables also exhibited a statistically significant gender difference. We found no gender difference for the variables living alone, having school-age children or being active in societies and hobby groups. Men and women differed in all but one work-family conflict: ‘I have more energy to be with the children when I also go to work’.

Associations of study variables with psychological distress by gender

Cross-tabulation of different variables with psychological distress in men and women are presented in Table  3 . Most of the independent variables were associated with psychological distress, but with some gender differences. Education was associated with psychological distress only in women, with less education being associated with more distress. Helping a parent or a child outside of a person’s own household was associated with less distress, but statistically significantly only in men helping a parent and in women helping a child. Helping somebody other than one’s own child or parent was associated with more distress, but statistically significantly only in women.

Separate multivariable logistic regression analyses for men and women

Work-family conflicts were similarly either protective or risk factors in both genders (Table  4 ). Only one domain, ‘I sometimes ignore my family when I am wholly absorbed in my work’, was associated with psychological distress in women, but not in men. The most distressing domain in both genders was family-to-work conflict, ‘I often find it difficult to concentrate on my work because of domestic issues’, while the second most distressing was ‘I feel inadequacy as a parent’.

Being fairly or extremely dissatisfied with work had the strongest association with on psychological distress measure in both genders. The high mental strain of one’s work had a statistically significant association with psychological distress only in men, whereas the physical strain of one’s work was not associated with distress in either gender.

Of the other variables considered, loneliness was strongly associated with psychological distress among both genders. Smoking and difficulties in covering household costs were also similarly associated with psychological distress in both genders. With respect to other not work-related factors, having minor children and actively participating in hobby groups and societies were associated with lower odds, while feeling inadequacy as a parent was associated with higher odds for psychological distress.

Having someone to give practical help (among men) or emotional support (among women) when needed were both associated with lower odds of psychological distress, especially when several supporters were available. Helping others outside the home was not associated with psychological distress.

Combined logistic regression analysis to test for gender interactions

In the logistic regression models conducted separately for men and women, gender difference in the strength of the associations with psychological distress appeared possible in the following variables: having children under 18 years old, at-risk drinking, active participation, receiving practical help from others, receiving emotional support from others, mental strain of work and ignoring family when wholly absorbed in one’s work. We included these variables in the logistic regression model pooled together across gender to test if they exhibited statistically significant gender interaction.

We found significant interaction by gender in two variables. The interaction term ‘gender and mental strain’ proved significant (F value 3.86, p  = 0.0212), indicating that mental strain was associated with psychological distress in men (see Table 4 ). The interaction term ‘gender and ignoring family due to being absorbed in one’s work’ also proved significant (F value 4.16, p  = 0.0414), indicating that ignoring family due to being absorbed in one’s work was associated with psychological distress in women.

In this cross-sectional, nationally representative study sample of the working population, we found that several factors related to work and balancing work and family life are associated with psychological distress. Furthermore, these associations were mostly similar among women and men. Earlier studies have yielded mixed evidence regarding gender differences based on work-family conflicts [ 24 ].

Psychological distress is quite common problem. In the current study, 11% of women and 8.8% of men in the working population had psychological distress. In the most recent national FinSote Survey from years 2017–2018, where participants were over 19 years with no upper age limit, the prevalence of psychological distress among women was 11.9% and among men 11.2% [ 83 ], suggesting that people who are employed full-time may experience slightly less psychological distress than the rest of the population. In large surveys made in the United States, 15.1% reported moderate psychological distress and 3.1% severe distress over the 2001–2012 period [ 84 ]. Because of the different rating scales and cut-off scores used in previous studies, the reported prevalence figures of psychological distress are not directly comparable between countries. With the cut-off score used in the current study, some underlying mood or anxiety disorder is very probable [ 1 ].

Family-to-work conflict has previously been found to be less common than work-to-family conflict [ 85 ], but in our study family-to-work conflict was more strongly associated with psychological distress than work-to-family conflict. The only gender difference was found in sometimes ignoring family when wholly absorbed in one’s work, which was associated with psychological distress only in women. This suggests that an engaging job may cause psychological distress via work-to-family conflict among women [ 86 ]. Difficulty in concentrating on work because of domestic issues showed the strongest association with psychological distress, but it could also imply that the participants were experiencing distressing family-related challenges at the time.

We also found evidence of work-to-family enrichment: those who responded that they have more energy to be with their children when they also go to work had less psychological distress [ 15 ]. Also, participants who reported that they stop thinking about their work when they come home had less distress, suggesting that a successful combination of work and family life protects a person from psychological distress. Inadequacy as a parent was associated with psychological distress independently of gender. Prior studies have reported that about half of employed parents feel they do not spend enough time with their children, and such a time deficit is associated with psychological distress [ 87 ].

Interestingly, mental strain of one’s work was a risk for psychological distress in men but not in women. The link between the mental demands of one’s work and psychological distress or mental disorder has been observed both in cross-sectional and in longitudinal studies [ 87 , 88 , 89 , 90 ]. Emotional exhaustion is more common in emotionally demanding jobs, such as in police work or among physicians and other professionals working in healthcare, and effective preventive interventions are available [ 91 ]. Most previous studies have not found any gender difference in how the psychological or emotional demands of one’s work affect mental health, but one previous study found that they may have a mediating effect between low income and psychological distress in men [ 92 ].

Consistent with prior studies [ 27 , 93 ], our findings showed that job dissatisfaction was strongly associated with psychological distress. We did not find any gender difference in terms of job dissatisfaction, which is consistent with earlier studies [ 29 , 94 ]. In a meta-analysis on the health effects of job dissatisfaction, the strongest correlation between job dissatisfaction and mental health problems was with burnout [ 27 ]. Burnout is a chronic stress syndrome characterised by exhaustion, cynicism and a lack of professional efficacy [ 95 ], and it may be an important mediator in the observed association between job dissatisfaction and psychological distress.

Loneliness was, similar to job dissatisfaction, the most significant factor increasing the odds of psychological distress, and at the same magnitude, in both genders. Women reported feelings of loneliness more often than men, as has been found earlier [ 41 ], but the association with psychological distress was equal in both genders. Previous studies have shown that loneliness is a significant risk factor for depression [ 96 ] and other common mental disorders [ 43 ] as well as for suicidal ideation and suicide attempts [ 97 ]. Furthermore, loneliness is associated with an increased risk of many health problems [ 97 ], and it has been increasingly seen as an important public health problem [ 98 ]. Our finding supports this view and encourages experts to implement specific interventions to reduce loneliness [ 99 ].

Various aspects related to social networks and social support were associated with having less psychological distress. Having minor children, being active in hobby groups, and receiving social support when needed were all associated with less psychological distress. Previous studies have found that social participation in activities is especially beneficial for women [ 33 , 38 ], whereas men and women benefit differently from emotional support [ 33 , 34 , 35 ]. However, while the analyses conducted separately among men and women suggested that there might be gender differences in these aspects of social networks and support, we did not observe any significant interaction in the analysis. It is also noteworthy that helping others outside the home was not associated with psychological distress.

Previous studies [ 66 , 68 , 70 ] have likewise found that financial difficulties constitute a notable risk factor for psychological distress. Consistent with a large body of previous research, smoking [ 59 , 100 , 101 ] and at-risk drinking [ 102 , 103 ] were associated with more psychological distress; however, their effect was less prominent than that of social and work-related factors in our study.

After considering a wide range of work-related, family-related and social factors, well-known risk factors like marital status and living alone did not have an association with psychological distress. This is consistent with a previous study that found that loneliness is a mediator between living alone and distress [ 104 ].

Strengths and limitations

The major strength of the present study is the large study sample representative of the adult working-age population in Finland. It was possible for participants to respond in several languages spoken by sizeable minorities within Finland, which further improved the representativeness. The Finnish version of MHI-5 has been shown to have construct validity [ 105 ].

The major limitation is that our study is cross-sectional. Therefore, we could not assess the direction or causality of the associations. Furthermore, data were obtained using self-report questionnaire and therefore we did not get detailed information e.g. about mental disorders. Self-reporting bias, such as social desirability bias and recall bias, could affect the results [ 106 ]. We did not have information about job demands, job control or other features related to work. Low response rate is a common phenomenon in survey studies today, and so it was in our study as well, especially for the youngest age group. However, we used inverse probability weighting to account for missing data, which has been shown to remove a relatively large proportion of the bias related to the low response rate in the current study sample [ 76 ]. In addition, we did not have information on all factors potentially related to gender differences in mental health. For example, intimate partner violence is strongly associated with psychological distress, and women experience it more often than men [ 107 ].

The results may not be generalizable to countries where there is more gender inequality. According to the European Institute for Gender Equality, Finland ranked the fourth in the European Union on the Gender Equality Index [ 108 ]. The gender gap in full-time equivalent employment rate and duration of working life is much smaller in Finland than in European countries on average, although there is still a gender gap in mean monthly earnings. There is a gender gap in caring for children, grandchildren or older people and in housework in Finland, but it is smaller than the European average. Women in Finland have higher level of education than men, and in our current parliament there are almost as many women as men [ 108 ]. In the Global Gender Gap report, Finland ranked the third [ 109 ]. Therefore, it is probable that in another country where gender inequality is more widespread or the culture is less individualistic, these results would be different [ 110 ].

Satisfying work, family life and being able to successfully combine both are important sources of psychological well-being in the working population, both among men and women. Of all studied variables, loneliness and being dissatisfied with work were most strongly associated with psychological distress. The detrimental effect of loneliness on mental health has become apparent during the COVID-19 pandemic [ 111 ] and should receive more attention in mental health policies and promotion. The strong association between dissatisfaction with work and psychological distress is likely bidirectional, and underscores the need to improve workplace mental health literacy and the availability of mental health interventions [ 112 ].

Availability of data and materials

The data that support the findings of this study are not publicly available. The data, from which all personal data have been eliminated, may be disclosed for research purposes by FinData in return for a research proposal and an approved user authorisation application.

Abbreviations

Finnish Regional Health and Well-being Study

Mental Health Inventory-5

The Alcohol Use Disorders Identification Test

Confidence interval

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Academy of Finland (grant No. 312073 to JK, grant No. 309119 to TK and grant No. 309117 to MM). The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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All authors contributed to the study conception and design. The statistical analysis plan was designed by SV and JS, and material preparation and statistical analysis was done by SV. The first draft of the manuscript was written by SV, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Viertiö, S., Kiviruusu, O., Piirtola, M. et al. Factors contributing to psychological distress in the working population, with a special reference to gender difference. BMC Public Health 21 , 611 (2021). https://doi.org/10.1186/s12889-021-10560-y

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E-collection: Public Mental Health

Mental health and mental disorder in the european journal of public health.

Jutta Lindert President of the EUPHA Section on Public Mental Health 

Mental Health and mental disorder including suicide and suicidal behavior have been a neglected issue in Public Health for many years. Yet, mental disorders rank among the disorders which contribute enormous suffering for affected persons and their families, high burden of disability adjusted life years (DALYS), and high economic and societal direct and indirect costs. People with severe mental illness have increased risk for premature mortality and thus a shorter life expectancy ( Ösby U ).

The fact that mental disorders are the leading causes of the burden of disease make research in mental disorders and policies to promote mental health a Public Health priority, worldwide. More knowledge on the scope and extent of mental health and mental disorders, the relationship between mental health and mental disorder and the determinants of mental health and mental disorder is highly needed.  As examples of determinants a variety of determinants of mental disorders (e.g., economic, social factors, relationship factors, factors related to the physical environment) have been identified. Economic factors such as relative deprivation ( Gunnarsdóttir H ), social factors such as social adversities ( Rajaleid K ) and working related factors, relationship factors such as violence and victimization, and factors related to the physical environment have been identified.

Social adversities over the life course have not only short term but also long-term effects on mental health and social adversities in adolescence predict trajectories of internalized mental ill-health symptoms. Working related factors related to mental disorders are employment status ( Katikireddi S ), working conditions ( Kouvonen A ), and employment history ( von Bonsdorff MB ). In the study from the Netherlands by von Bonsdorf discontinuous employment during mid-career was associated with poorer self-reported physical and mental functioning around the age of retirement. Herewith the long term effects of exposures to social adversities such as financial stress and interrupted employment histories were highlighted. Many studies have investigated how unemployment history influences health, less attention has been paid to the reverse causal direction; how health may influence the risk of employment history and the risk of becoming unemployed. However, an interrupted employment history might be both an indicator for mental disorders and a determinant of mental disorders as people with poor mental and physical health are at increased risk of job loss. ( Kaspersen SL )

Additionally, and importantly, studies investigated relationship factors and mental disorders and mental health. Relationships might include relationships between individuals, groups and communities. A study by Palm et al. showed the significant impact violence and abuse has on women`s mental health. In this study young women visiting youth health centers in Sweden answered a questionnaire constructed from standardized instruments addressing violence victimization (emotional, physical, sexual and family violence), socio-demographics, substance use and physical and mental health ( Palm A ). Yet the relationships between violence and health need further investigation, might it be the impact of war on mental health ( Lindert J ) or the impact of family relationships, physical abuse and early adversities, gun violence, domestic violence, bullying and cyber-bullying? 

Besides economic, social or relationship factors environment related factors may have a significant contribution for mental health, such as exposure to asbestos. The results obtained in the Asbestos-Related Diseases Cohort (ARDCO) study confirm that environment related factors need to be investigated and linked to the field of Public Mental Health. ( Mounchetrou Njoya I ).

Yet the relationships of mental health and mental disorders need further investigation. However, we need more longitudinal population based studies on trajectories of mental disorders, determinants and mechanisms of mental health and mental disorders and how positive trajectories of mental health can be supported. If we want to promote mental health, reduce mental disorders and improve Public Mental Health, we need to produce studies with data from more countries ( Bøe T ). Studies published in the EJPH on mental disorder and mental health trajectories are good examples and will allow us not only to better understand variations between and within countries but mental disorders' trajectories and develop effective and cost-effective interventions.

Financial difficulties in childhood and adult depression in Europe Tormod Bøe, Mirza Balaj, Terje A. Eikemo, Courtney L. McNamara, Erling F. Solheim Eur J Public Health (2017) 27 (suppl_1): 96-101.

Suicide mortality in Belgium at the beginning of the 21st century: differences according to migrant background Mariska Bauwelinck, Patrick Deboosere, Didier Willaert, Hadewijch Vandenheede Eur J Public Health (2017) 27 (1): 111-111

Relative deprivation in the Nordic countries-child mental health problems in relation to parental financial stress  Hrafnhildur Gunnarsdóttir, Gunnel Hensing, Lene Povlsen, Max Petzold Eur J Public Health (2016) 26 (2): 277-282

Health and unemployment: 14 years of follow-up on job loss in the Norwegian HUNT Study Silje L Kaspersen, Kristine Pape, Gunnhild Å. Vie, Solveig O. Ose, Steinar Krokstad, David Gunnell, Johan H. Bjørngaard  Eur J Public Health (2016) 26 (2): 312-317. 

Employment status and income as potential mediators of educational inequalities in population mental health Srinivasa Vittal Katikireddi, Claire L. Niedzwiedz CL, Frank Popham Eur J Public Health (2016) 26 (5): 814-816

Changes in psychosocial and physical working conditions and common mental disorders  Anne Kouvonen, Minna Mänty, Tea Lallukka, Eero Lahelma, Ossi Rahkonen Eur J Public Health (2016). pii: ckw019. [Epub ahead of print])

Refugees mental health-A public mental health challenge Jutta Lindert, Mauro G. Carta, Ingo Schäfer, Richard F. Mollica Eur J Public Health (2016) 26 (3): 374-375

Anxious and depressive symptoms in the French Asbestos Related Diseases Cohort: risk factors and self-perception of risk Ibrahim Mounchetrou Njoya, Christophe Paris, Jerome Dinet, Amadine Luc, Joelle Lighezzolo-Alnot, Jean-Claude Pairon, Isabelle Thaon Eur J Public Health (2017) 27 (2): 359-366

Mortality trends in cardiovascular causes in schizophrenia, bipolar and unipolar mood disorder in Sweden 1987-2010 Urban Ösby, Jeanette Westman, Jonas Hällgren, Mika Gissler Eur J Public Health (2016) 26 (5): 867-871

Violence victimisation-a watershed for young women's mental and physical health Anna Palm, Ingela Danielsson, Alkistis Skalkidou, Niclas Olofsson, Ulf Högberg  Eur J Public Health (2016) 26 (5): 861-867

Social adversities in adolescence predict unfavourable trajectories of internalized mental health symptoms until middle age: results from the Northern Swedish Cohort  Kristiina Rajaleid, Tapio Nummi, Hugo Westerlund, Pekka Virtanen, Per E. Gustafsson, Anne Hammarström Eur J Public Health (2016) 26 (1): 23-29

Mid-career work patterns and physical and mental functioning at age 60-64: evidence from the 1946 British birth cohort Mikaela B. von Bonsdorff, Diana Kuh, Monika E. von Bonsdorff, Rachel Cooper Eur J Public Health (2016) 26 (3): 486-491

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Open Access

Peer-reviewed

Research Article

Discovering Relations Between Mind, Brain, and Mental Disorders Using Topic Mapping

* E-mail: [email protected]

Affiliation Imaging Research Center and Departments of Psychology and Neurobiology, University of Texas, Austin, Texas, United States of America

Affiliation NASA Ames Research Center, Mountain View, California, United States of America

Affiliation Department of Electrical and Computer Engineering, University of Texas, Austin, Texas, United States of America

Affiliation Department of Psychology, Colorado University, Boulder, Colorado, United States of America

• Russell A. Poldrack, 
• Jeanette A. Mumford, 
• Tom Schonberg, 
• Donald Kalar, 
• Bishal Barman, 
• Tal Yarkoni

• Published: October 11, 2012
• https://doi.org/10.1371/journal.pcbi.1002707
• Reader Comments

Neuroimaging research has largely focused on the identification of associations between brain activation and specific mental functions. Here we show that data mining techniques applied to a large database of neuroimaging results can be used to identify the conceptual structure of mental functions and their mapping to brain systems. This analysis confirms many current ideas regarding the neural organization of cognition, but also provides some new insights into the roles of particular brain systems in mental function. We further show that the same methods can be used to identify the relations between mental disorders. Finally, we show that these two approaches can be combined to empirically identify novel relations between mental disorders and mental functions via their common involvement of particular brain networks. This approach has the potential to discover novel endophenotypes for neuropsychiatric disorders and to better characterize the structure of these disorders and the relations between them.

Author Summary

One of the major challenges of neuroscience research is to integrate the results of the large number of published research studies in order to better understand how psychological functions are mapped onto brain systems. In this research, we take advantage of a large database of neuroimaging studies, along with text mining methods, to extract information about the topics that are found in the brain imaging literature and their mapping onto reported brain activation data. We also show that this method can be used to identify new relations between psychological functions and mental disorders, through their shared brain activity patterns. This work provides a new way to discover the underlying structure that relates brain function and mental processes.

Citation: Poldrack RA, Mumford JA, Schonberg T, Kalar D, Barman B, Yarkoni T (2012) Discovering Relations Between Mind, Brain, and Mental Disorders Using Topic Mapping. PLoS Comput Biol 8(10): e1002707. https://doi.org/10.1371/journal.pcbi.1002707

Editor: Olaf Sporns, Indiana University, United States of America

Received: May 14, 2012; Accepted: August 2, 2012; Published: October 11, 2012

Copyright: © Poldrack et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was supported by NIH grant RO1MH082795 (to RAP) and F32NR012081 (to TY) and by the Texas Emerging Technology Fund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Competing interests: The authors have declared that no competing interests exist.

Introduction

The search for clues regarding the underlying causes of mental disorders has led to the notion that these disorders may be best understood in terms of a set of underlying psychological and/or neural mechanisms that stand between genes and environment on the one hand and psychiatric diagnoses on the other hand. Such intermediate phenotypes, or “endophenotypes”, may provide the traction that has eluded research using diagnostic categories as primary phenotypes [1] , [2] . They may also provide the means to better understand the structure the underlying psychological dimensions that appear to underlie overlapping categories of mental disorders [3] , [4] .

The identification of endophenotypes requires an understanding the basic structure of mental functions and their associated brain networks. For more than 30 years, cognitive neuroscientists have used neuroimaging methods (including EEG/MEG, PET, and fMRI) in an attempt to address this question. This work has led to a large body of knowledge about associations between specific psychological processes or tasks and activity in brain regions or networks. However, this knowledge has not led to a commensurate improvement in our understanding of the basic mental operations that may be subserved by particular brain systems. Instead, diverse literatures often assign widely varying functions to the same networks. A prime example is the anterior cingulate cortex, which has been associated with such widespread functions as conflict monitoring, error processing, pain, and interoceptive awareness. In order to understand the unique functions that are subserved by brain regions or networks, a different approach is necessary; namely, we need to analyze data obtained across a broad range of mental domains and understand how these domains are organized with regard to neural function and structure.

The identification of basic operations can be understood statistically as a problem of latent structure identification; that is, what are the latent underlying mental functions and brain networks that give rise to to the broad range of observed behaviors and patterns of brain activity and neuropsychiatric disorders? The focus within cognitive neuroscience on establishing associations between activation and specific hypothesized processes has hindered the ability to identify such latent structures. However, within the fields of machine learning and text mining, a number of powerful approaches have been developed to estimate the latent structure that generates observed data, assuming that large enough datasets are available. In the present work, we take advantage of one class of such generative models to develop a new approach to identifying the underlying latent structure of mental processing and the associated brain functions, which we refer to as “topic mapping”. We examine the latent conceptual structure of the fMRI literature by mining the full text from a large text corpus comprising more than 5,800 articles from the neuroimaging literature, and model the relation between these topics and associated brain activation using automated methods for extracting activation coordinates from published papers. This analysis uncovers conceptual structure and activation patterns consistent with those observed in previous neuroimaging meta-analyses, which provides confirmation of the approach, while also providing some novel suggestions regarding structure/function relationships. We then use this approach to identify the topical structure of terms related neuropsychiatric diseases, and use multivariate methods to identify relations between these the mental and disorder domains based on common brain activation patterns. This approach provides an empirical means of discovering novel endophenotypes that may underlie mental disorders, as well providing new insights into the relations between diagnostic categories.

Within the fields of information retrieval and computer science, research into document retrieval has led to the development of a set of techniques for estimating the latent structure underlying a set of documents. Early work in this area treated documents as vectors in a high-dimensional space, and used matrix decomposition techniques such as singular value decomposition to identify the latent semantic structure of the documents [5] . More recently, researchers in this domain have developed approaches that are based on generative models of documents. One popular approach, known generically as “topic models” [6] , treats each document as a mixture of a small number of underlying “topics”, each of which is associated with a distribution over words. Generating a document via this model involves sampling a topic and then sampling over words within the chosen topic; using Bayesian estimation techniques, it is possible to invert this model and estimate the topic and word distributions given a set of documents. The particular topic modeling technique that we employ here, known as latent Dirichlet allocation (LDA: [7] ), has been shown to be highly effective at extracting the structure of large text corpuses. For example [8] , used this approach to characterize the topical structure of science by analyzing 10 years of abstracts from PNAS , showing that it was able to accurately extract the conceptual structure of this domain.

We characterized the latent structure of the cognitive neuroscience literature by applying latent Dirichlet allocation to a corpus of 5,809 articles (using an expanded version of the corpus developed in [9] ), which were selected on the basis of reporting fMRI activation in a standardized coordinate format. An overview of the entire data processing workflow is presented in Figure 1 . This technique estimates a number of underlying latent “topics” that generate the observed text, where each topic is defined by a distribution over words. The dimensionality (i.e., number of topics) is estimated using a cross-validation approach; the documents are randomly split into 8 sets, and for each set a topic model is trained on the remaining data and then used to estimate the empirical likelihood of the held-out documents [10] . Plots of the empirical likelihood of left-out documents as a function of the number of topics are shown in Figure 2 , and histograms of the number of documents per topic and number of topics per document are shown in figure 3 .

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https://doi.org/10.1371/journal.pcbi.1002707.g003

Initial application of LDA to the full-text corpus identified a number of topics that were related to mental function, but also many topics related to methodological or linguistic aspects of the documents. Because we were specifically interested in estimating the conceptual structure of mental processes, we examined each document in the corpus and identified each occurrence of any of the 605 terms (both single words and phrases) that are present as mental concepts in the Cognitive Atlas ( http://www.cognitiveatlas.org ); the topic model was then estimated using this limited word set (treating each word or phrase as a single-word token). The Cognitive Atlas is a curated collaborative ontology that aims to describe mental functions, and contains terms spanning across nearly all domains of psychological function [11] . The cross-validation analysis identified 130 as the optimal number of topics for this dataset. Examples of these topics are shown in Figure 4 , and the full list is presented in Table S1 . In large part these topics are consistent with the topics that are the focus of research in the cognitive neuroscience literature. The topics with the highest number of associated documents were those related to very common features of neuroimaging tasks such as movement (topic 20), emotion (topic 93), audition (topic 74), attention (topic 43), and working memory (topic 61). Each of these was associated with more than 400 documents in the corpus. At the other end of the spectrum were more focused topics that loaded on fewer than 200 documents, such as topic 121 (regret,surprise), topic 71 (narrative, discourse), and topic 108 (empathy, pain). The results of this analysis suggest that topic modeling applied to the limited term set of mental functions can successfully extract the conceptual structure of psychological processes at multiple levels within the current text corpus.

https://doi.org/10.1371/journal.pcbi.1002707.g004

In order to further examine the effects of topic dimensionality, we compared the results obtained across several values for the number of topics (10,50, 100, and 250). We chose the term “language” and identified all topics for each model in which that term occurred in the top five terms. We then examined the correlation in the loading vector across documents for each set of levels, in order to identify the hierarchical graph relating topics across levels (see Figure 5 ). This analysis showed that increasing the topic dimensionality resulted in finer-grained topics; for example, with 10 topics there was a single matching topic that included “meaning”, “reading”, and “comprehension”, whereas each of these was split into a separate set of topics in the 50-topic model, and further subdivided as the dimensionality increased. This suggests that although the cross validation resulted in a particular “best” dimensionality, in reality there is relevant information at many different levels which differs in grain size.

All topics with “language in their top 5 terms were first identified from the results for topic models fit to the data at 10, 50, 100, and 250 topics. At each level, each topic is linked to the topic at the previous level with which it had the highest correlation in its document loadings. The values on each edge reflect the correlation in the topic loading vector across documents between the two levels.

https://doi.org/10.1371/journal.pcbi.1002707.g005

Topic mapping

While concordance with the existing literature is reassuring, the true promise of this approach is in its ability to uncover novel associations between functions and activation, and the topic mapping analysis did in fact identify some unexpected associations, particularly when looking at negative associations. Two interesting examples are evident in Figure 4 . First, topic 61 was associated with the bilateral fronto-parietal network usually associated with working memory, but it also exhibited strong and focused negative association in the right amygdala; this means that the amygdala was significantly less likely to be activated in studies that loaded on this topic relative to those that did not. This is particularly interesting in light of further exploration of the literature using the PubBrain tool ( http://www.pubbrain.org ) which identified a number of studies that have noted amygdala activation in association with working memory tasks (cf. [13] ). Another example is topic 71 (associated with auditory processing) which was negatively associated with activation in a broad set of regions previously implicated in emotional function, such as orbitofrontal cortex, striatum, and amygdala. Whether such negative associations reflect truly negative relations in activation between these networks or reflect features of the tasks used in these domains remains to be determined, but such unexpected associations could suggest novel hypotheses about relations between specific brain networks. These are only two examples of potential novel discoveries using Topic Mapping.; future studies will be needed to systematically examine all possible new findings emerging from the usage of this tool.

Mapping the neural basis of neuropsychiatric disorders

Based on the results from the foregoing analyses, we then examined whether it was possible to obtain new insights about the organization of brain disorders using the topic mapping approach developed above. We estimated a set of topics using only terms related to brain disorders, based on a lexicon of mental disorders terms derived from the NIFSTD Dysfunction ontology [14] along with the DSM-IV. The optimal dimensionality of 60 based on cross-validation was found to produce multiple topics with exactly the same word distribution, so we used the largest number of topics yielding a unique set of word distributions across topics, which was 29 topics. Examples of these topics and the associated topic maps are presented in Figure 6 .

Topics are ordered in terms of the number of documents loading on the topic; color maps reflect the correlation coefficient between topic loading and activation across documents. The images are presented in radiological convention (i.e., left-right reversed).

https://doi.org/10.1371/journal.pcbi.1002707.g006

The results of this analysis are largely consistent with results from prior meta-analyses and known functional anatomy of the various disorders, but are novel in highlighting relations between some of the disorders. For example, Topic 7 demonstrates the relations between bipolar disorder, schizophrenia, and mood disorders, with activation centered on the medial prefrontal cortex, basal ganglia, and amygdala. Topic 8 highlights relations between obesity and eating disorders and drug abuse, with activation in the ventral striatum and ventromedial prefrontal cortex. Topic 14 demonstrates relations between a set of externalizing disorders (drug abuse, conduct disorder, alcoholism, antisocial personality disorder, and cannabis related disorder) with activation focused in the striatum, amygdala, orbitofrontal cortex, and dorsal prefrontal cortex. Conversely, Topic 25 demonstrates relations between a set of internalizing disorders (anxiety disorder, panic disorder, phobia, obsessive compulsive disorder, agoraphobia, and post traumatic stress disorder), with a very similar pattern of activation, though notably weaker in the striatum. One striking result of these analyses is the similarity of the patterns of brain activity associated with the mention of all of these different disorders. This could arise either from the fact that this particular set of limbic brain systems is the seat of all major psychiatric disorders, or the fact that these disorders are commonly mentioned in relation to tasks or cognitive domains that happen to preferentially engage these brain systems.

We further characterized the relations between different disorder concepts in their associated neural activations by clustering the disorder topics based on their associated brain activation patterns using hierarchical clustering. The results of this analysis are shown in Figure 7 . The results show the degree to which the neural patterns associated with the use of particular sets of mental disorder terms exhibit a consistent systematic structure. The clustering breaks into four large groups, comprising language disorders, mood/anxiety disorders and drug abuse, psychotic disorders, and autism and memory disorders. What is particularly interesting is that, although none of the topic maps associated with the term “schizophrenia” showed strong activation, the fact that they cluster together in this analysis suggests that they are nonetheless similar in the patterns of activation that are reported in the associated papers; however, this could also reflect the fact that a relatively small number of tasks is used in the literature, and thus any concordance could be driven by overlap of tasks that are commonly mentioned in the context of schizophrenia. Despite such limitations, these results provide further confirmation that the present analysis, while largely based on studies involving healthy adults, can nonetheless accurately characterize the neural basis of mental disorders as described in the literature.

Euclidean distance was used as the distance metric for clustering, and hierarchical clustering was performed using Ward's method. The colored blocks show the four major groupings obtained by cutting the tree at a height of 2.0. Abbreviations: APH: aphasia, DLX:dyslexia, SLI: specific language impairment, DA: drug abuse, AD:Alzheimer's disease, DEP:depressive disorder, MDD:major depressive disorder, ANX:anxiety disorder, PAN: panic disorder, BPD: bipolar disorder, CD: conduct disorder, GAM: gambling, MD: mood disorder, PD: Parkinson's disease, OCD: obsessive compulsive disorder, PHO: phobia, EAT: eating disorder, SZ: schizophrenia, OBE: obesity, COC: cocaine related disorder, PSY: psychotic disorder, PAR: paranoid disorder, SZTY: schizotypal personality disorder, TIC: tic disorder, ALC: alcoholism, ALX: alexia, ADD: attention deficit disorder, AMN: amnesia, AUT: autism, ASP: Asperger syndrome.

https://doi.org/10.1371/journal.pcbi.1002707.g007

Empirical discovery of endophenotypes

https://doi.org/10.1371/journal.pcbi.1002707.t001

The first canonical variate (#0) demonstrated associations between a number of both internalizing and externalizing disorders (anxiety, depression, obesity, gambling) which were centered around the involvement of emotional processes (such as mood and fear) and reward-related decision processes. Another canonical variate (#1) was focused on memory processes, and identified a cluster of disorders including classical memory disorders (amnesia and Alzheimer's disease) as well as schizophrenia. Another (#2) focused on language processes and was associated with activity in left prefrontal, temporal, and parietal regions.

The results of the CCA analysis provide a potential new window into the complex psychological and neural underpinnings of schizophrenia and its relation to other psychiatric disorders. Across different canonical variates, schizophrenia is related to mood and decision making processes (components 0 and 3), memory processes (component 5), and social perception (component 10). These could potentially relate to different aspects of schizophrenic symptomatology, such as the distinctions between positive versus negative symptoms or between cognitive versus affective impairments. Further, they provide novel potential targets for genetic association studies, which have struggled to identify meaningful and replicable associations between schizophrenic symptoms or endophenotypes and genetic polymorphisms (cf. [16] ).

We also performed CCA directly using topic-document loading vectors, in order to determine whether the results differed from CCA computed on neural loading vectors; the results are presented in Table 2 . The results of this analysis are quite concordant with the foregoing analyses based on activation patterns, but one noticeable difference between the two analyses is that the activation-based CCA analysis appeared to cluster disorders more broadly, whereas many of the components found in the text-based analysis had only a single disorder. This may reflect the fact that disorders are less neurally distinct than is suggested by what is written by authors, but could also reflect greater noise in the neural data; further work will be necessary to better understand the unique contributions of activation-based and text-based analyses.

https://doi.org/10.1371/journal.pcbi.1002707.t002

It is clear that neuroimaging can provide important evidence regarding the functional organization of the brain, but one of the most fundamental questions in cognitive neuroscience has been whether it can provide any new insights into psychological function [17] – [19] . The results presented here demonstrate how large databases of neuroimaging data can provide new insights into the structure of psychological processes, by laying bare their relations within a similarity space defined by neural function. The present results highlight the importance of “discovery science” approaches that take advantage of modern statistical techniques to characterize large, high-dimensional datasets (cf. [20] ). Just as the fields of molecular biology and genomics have been revolutionized by this approach [21] , we propose that the hypothesis-generating approach supported by data mining tools can serve as a powerful complement to more standard hypothesis-testing approaches [22] .

There is growing recognition that the diagnostic categories used in psychiatry are not reflective of sharp parallel biological distinctions; instead, a growing body of behavioral, genetic, and neuroimaging data suggest that these different disorders fall along a set of underlying continuous dimensions which likely relate to particular basic psychological processes [3] , [4] . The results presented here are consistent with that viewpoint, and further show how endophenotypes for groups of disorders can be empirically discovered via data mining, even if those disorders were not the primary aims of the studies being mined. This approach would likely be even more powerful using databases that were focused on imaging data from studies of patients. In addition, this approach has the potential to characterize the genetic architecture of these disorders through mining of genetic association data; unfortunately, genetic terms are not sufficiently frequent in the Neurosynth database to support robust mapping of relationships to genes, but future analyses using enhanced databases has the potential to discover additional relations between neurocognitive components and genetic contributions.

The present work is limited by several features of the data that were used in the analyses. The first limitation arises from the fact that we rely upon the presence of particular terms in the text, rather than on manual annotation of the relevance of those terms. Thus, obvious issues such as polysemy (e.g., the multiple senses of the term “working memory”) and negation can be problematic, though these issues could potentially be addressed using more powerful natural language processing. A second limitation arises from the meta-analytic nature of the activation data used in the analyses, which are reconstructed from a very sparse representation of the original data. A third limitation is that the activation maps are associated only with complete documents, not with specific terms within the document, and this coarseness undoubtedly adds a significant amount of noise to the modeling results. These limitations necessitate caution in drawing strong conclusions from the results reported here. At the same time, the concordance of many of the results with previous analyses using different datasets and analysis approaches suggests that these limitations have not greatly undermined the power of the technique. We propose that the approach outlined here is likely to be most useful for inspiring novel hypotheses rather than for confirming existing hypotheses, which means that any such results will be just the first step in a research program that must also include hypothesis-driven experimentation.

Another potential limitation of the present work is that the fact that a number of the parameters in the analyses were set arbitrarily. While the dimensionality of the topic models was determined using an automated method, there remain parameter settings (such as smoothness of the word and topic distributions) that must be chosen arbitrarily (in our case, we chose them based on previously published results). The results of the topic model are quite robust; for example, we saw very similar results when performing the topic models on the original set of 4,393 papers from the earlier paper by Yarkoni et al. compared to the results from the corpus of 5,809 papers. It is also evident from Figure 5 that there is strong continuity in topics across different dimensionalities, with single topics at lower dimensionalities splitting into multiple finer-grained topics at higher dimensionalities. We have chosen model parameters that appear to give sensible results relative to prior findings, but the possibility remains that different parameterizations or analysis approaches could lead to different outcomes; future research will need to explore this question in more detail. We would also note that some of these limitations may be offset by the fact that the analyses presented here are almost fully automated, which removes many possible opportunities for research bias to affect the results.

The present work follows and extends other recent work that has aimed to mine the relations between mental function and brain function using coordinate-based meta-analyses. Smith et al. [23] analyzed the BrainMap database (which is similar to the database used here, but is created via manual annotation and thus has lower coverage but greater specificity and accuracy than the Neurosynth database). This work showed that independent components analysis applied to the meta-analytic data was able to identify networks very similar to those observed in resting-state fMRI time series, and that these could be related to specific aspects of psychological function via the annotations in the BrainMap database. Laird et al [24] extended this by showing that behavioral functions could be clustered together based on these meta-analytic maps. The present work further extends those previous studies by showing that the structure of the psychological domain can be identified in an unsupervised manner using topic modeling across both cognitive function and mental disorder domains, and that these can further be used to identify potential endophenotypes that share common neural patterns across these two domains. Visual examination of the ICA components presented in the Smith and Laird papers shows substantial overlap with the topic maps identified in the present study. In future work, we hope to directly compare the topic mapping results with the maps identified in those papers, to further characterize the utility of each approach.

In summary, we have shown how large neuroimaging and text databases can be used to identify novel relations between brain, mind, and mental disorders. The approach developed here has the potential to enable new discoveries about the neural and cognitive bases of neuropsychiatric disorders, and to provide empirically-driven functional characterizations of patterns of brain activation. The results also highlight the importance of the availability of large open datasets in cognitive neuroscience to enable discovery-based science as a complement to hypothesis-driven research.

Materials and Methods

Code to implement all of the analyses reported here, along with all of the auxiliary files, are available at https://github.com/poldrack/LatentStructure .

Data extraction

The full text from the Neurosynth corpus was used for the text mining analyses. The sources of these data as well as the process for automated extraction of activation coordinates are described in detail in [9] .

Peak image creation

Synthetic activation peak images were created from the extracted activation coordinates by placing a sphere (10 mm radius) at each activation location, at 3 mm resolution using the MNI305 template. Activations detected to be in Talairach space were first converted to MNI305 coordinates using the Lancaster transform [25] .

Topic modeling

We ran two topic modeling analyses using limited sets of terms to obtain focused topics in specific domains. In the first, we used 605 mental concept terms from the Cognitive Atlas database mentioned previously. In the second, we used a set of 55 terms describing mental disorders; these were obtained by taking the NIFSTD Dysfunction ontology and removing all terms not relevant to psychiatric disorders, and then adding a set of missing terms that described additional disorders listed in the DSM-IV. In each case, we processed the full text corpus and created restricted documents containing only terms that were present in the respective term list (along with synonyms, which were mapped back to the base term), and then performed topic modeling on those restricted documents. The median number of terms per document after filtering was 127 for cognitive terms and 3 for disease terms.

For each dataset, the optimal number of topics was determined by performing a grid search across a range of dimensionality values (from 10 to 250 in steps of 10). Each document set was split into 8 random sets of documents, and 8 separate models were trained, in each case leaving out one subset of documents. The empirical likelihood of the left-out documents was then estimated using an importance sampling method as implemented in MALLET [10] .

In order to identify the hierarchical relations between topics across different dimensionalities (as shown in Figure 5 ), the topic models from the first crossvalidation fold for each level (10, 50, 100, and 250 topics) were used; because 1/8 of the data were excluded as test data, these models were thus trained on a total of 5082 documents (using the same documents across all different dimensionalities). Hierarchical relations between levels were identified by computing the correlation between the document loading vectors for each lower-level topic and all higher-level topics, and then assigning the link according to the maximum correlation.

Disorder clustering

Disorders were clustered using hierarchical clustering (Ward's method) applied to the Euclidean distance matrix computed across voxels for the disorder-based topic maps (Pearson r values).

Canonical correlation analysis

Supporting Information

Complete list of topics identified through application of latent Dirichlet allocation to the text corpus filtered for Cognitive Atlas terms. The top 5 words shown for each topic are those which had the highest loading for that topic across documents. The number of documents that loaded on each topic is also listed.

https://doi.org/10.1371/journal.pcbi.1002707.s001

Complete list of topics identified through application of latent Dirichlet allocation to the text corpus filtered for mental disorder terms. The top 5 words shown for each topic are those which had the highest loading for that topic across documents. The number of documents that loaded on each topic is also listed.

https://doi.org/10.1371/journal.pcbi.1002707.s002

Acknowledgments

Thanks to Robert Bilder, Eliza Congdon, Steve Hanson, Oluwasanmi Koyejo, Jonathan Pillow, and Fred Sabb for helpful comments on a draft of this paper and to Daniela Witten for assistance with the R PMA package.

Author Contributions

Conceived and designed the experiments: RAP TS DK BB TY. Performed the experiments: RAP TY. Analyzed the data: RAP JAM TY. Contributed reagents/materials/analysis tools: RAP JAM DK BB TY. Wrote the paper: RAP JAM TS TY.

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• Published: 01 February 2022

Researching the researchers: psychological distress and psychosocial stressors according to career stage in mental health researchers

• Nicole T. M. Hill 1 , 2 , 3 ,
• Eleanor Bailey 4 , 5 ,
• Ruth Benson 6 , 7 ,
• Grace Cully 6 , 7 ,
• Olivia J. Kirtley 8 ,
• Rosemary Purcell 4 , 5 ,
• Simon Rice 4 , 5 ,
• Jo Robinson 4 , 5 &
• Courtney C. Walton 4 , 5  

BMC Psychology volume  10 , Article number:  19 ( 2022 ) Cite this article

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Although there are many benefits associated with working in academia, this career path often involves structural and organisational stressors that can be detrimental to wellbeing and increase susceptibility to psychological distress and mental ill health. This exploratory study examines experiences of work-related psychosocial stressors, psychological distress, and mental health diagnoses among mental health researchers.

This international cross-sectional study involved 207 mental health researchers who were post-graduate students or employed in research institutes or university settings. Work-related psychosocial stressors were measured by the Copenhagen Psychosocial Questionnaire III (COPSOQ III). Psychological distress was assessed using the Depression-Anxiety-Stress Scale-21 (DASS-21). Thoughts of suicide was assessed using an adaptation of the Patient Health Questionnaire-9 (PHQ-9). History of mental health diagnoses was assessed through a custom questionnaire. Pearson’s chi-square test of independence was used to compare mental health diagnoses and suicidal ideation across career stages. The association between work-related psychosocial stressors and psychological distress was conducted using multivariate linear regression controlling for key demographic, employment-related and mental health factors.

Differences in ‘demands at work’ and the ‘work-life balance’ domain were lowest among support staff ( p  = 0.01). Overall, 13.4% of respondents met the threshold for severe psychological distress, which was significantly higher in students compared to participants from other career stages ( p  = 0.01). Among the subgroup of participants who responded to the question on mental health diagnoses and suicidal ideation ( n  = 152), 54% reported a life-time mental health diagnosis and 23.7% reported suicidal ideation since their academic career commencement. After controlling for key covariates, the association between the ‘interpersonal relations and leadership’ domain and psychological distress was attenuated by the mental health covariates included in model 3 ( β  = −0.23, p  = 0.07). The association between the remaining work-related psychosocial stressors and psychological distress remained significant.

Conclusions

Despite working in the same environment, research support staff report experiencing significantly less psychosocial stressors compared to postgraduate students, early-middle career researchers and senior researchers. Future research that targets key modifiable stressors associated with psychological distress including work organization and job content, and work-life balance could improve the overall mental health and wellbeing of mental health researchers.

Peer Review reports

Introduction

The mental health and wellbeing of academic staff and students at higher education institutions (including universities) has become a prominent concern in the research community [ 1 , 2 ]. Although there are many benefits and privileges associated with working in academia including knowledge gain, personal fulfilment, flexibility, and comparatively high salaries at senior levels, this career path often involves a range of structural and organisational stressors that may potentially compromise well-being and increase stress. Examples of academic-specific stressors identified in previous studies include being regularly evaluated and ‘benchmarked’ against output metrics, cyclical competition for funding (including salary support), job insecurity and uncertainty, and balancing multiple roles (teacher, mentor, researcher, writer, reviewer, manager, and administrator) [ 2 , 3 , 4 , 5 ]. These work commitments regularly interfere with personal life [ 5 , 6 ] and have been shown in previous meta-analyses to be associated with increased psychological distress, and poor mental health outcomes such as depression and anxiety and suicidal ideation across occupations [ 7 , 8 , 9 ].

In response to increased international scrutiny of the academic work culture, several reports have been produced that highlight key work-place stressors experienced by researchers in academic settings [ 3 , 10 , 11 ]. For example, a report published by Wellcome Trust in the United Kingdom [ 3 ] highlighted concerns about career uncertainty and longevity, including a culture of long working hours, and continually changing goalposts with overwhelming and unrealistic expectations on productivity. Furthermore, a third of participants (34%) described accessing support from a mental health professional for depression or anxiety since working in academia [ 3 ]. This proportion was higher for females (38%) and non-binary respondents (66%), than males (25%). However, estimates of symptom prevalence and severity using validated clinical scales (e.g. DASS21) [ 12 ] were not collected nor was the association between symptom severity and work-related psychosocial stressors investigated.

To date, much of what is known about the mental health of academics stems from studies conducted among graduate student populations [ 13 , 14 ]. However, it is often unclear what proportion of these samples conduct research, with many enrolled in applied study (e.g., medical training) that may not generalise to academics in research roles. Using the Generalized Anxiety Disorder Scale and Patient Health Questionnaire, Evans and colleagues [ 13 ] showed graduate research students were more than six times more likely to report experiencing symptoms of mental ill health including anxiety or depression than the general population, with rates of 39% and 41% respectively scoring in the ‘moderate’ or ‘severe’ range. Furthermore, psychosocial work-related factors such as poor work-life balance and poor mentoring relationships were revealed as being more common in those with a mental health disorder. Another study examined psychological distress [ 15 ] using the General Health Questionnaire, as well as job satisfaction, in a large sample of Australian university staff and found that 43% of academic staff scored above the cut-off [ 6 ], indicating increased risk of a possible mental health disorder [ 6 , 16 ]. Together these findings suggest that the severity of psychological distress among academics, relative to the general population, may be related to modifiable work-related psychosocial stressors. Given psychological distress is characterised by depressive and anxiety symptoms, and is an indicator of mental ill health conditions such as depression and anxiety disorders [ 17 ] research that seeks to identify the association between work-related stresses and psychological distress may have upstream benefits that reduce the progression of a later mental health diagnosis.

Though there is now a growing concern about the mental health of researchers, particularly in early stages of their careers, the majority of work to date has focussed on assessment of stress, environmental factors, or relied on non-clinical instruments to measure researchers’ mental health [ 18 ]. Additionally, differences in psychological distress and mental health outcomes that are experienced at different career stages (e.g., postgraduate students versus senior researchers) has not been investigated. This gap in evidence is noteworthy since different modifiable work-related stressors may be more or less prevalent at different career stages. Given the link between job stress and the prospective development of psychological distress, mental ill health (e.g., depression and anxiety) and organisational productivity (e.g., sickness, absence rates, and workers compensation claims) [ 19 ], understanding the burden of psychological distress and mental ill health, including suicidal ideation, and work-related psychosocial stressors across different career stages has important implications for employees, as well as occupational health, safety regulators, insurers, unions and employers [ 20 ].

The current study was undertaken as part of the International Association for Suicide Prevention taskforce on emotional health and wellbeing. It is exploratory in nature, with the aim of investigating the work-related psychosocial stressors experienced by mental health researchers across different career stages, the prevalence of psychological distress and mental ill health, and the association between work-related psychosocial stressors and psychological distress within this population. In doing so, we seek to expand on the existing evidence-base in order to better identify the possible modifiable work-related psychosocial stressors that impact mental health researchers and identify possible opportunities for intervention and prevention of psychological distress and mental ill health among mental health researchers.

Material and methods

Data and sampling.

This exploratory cross-sectional study used data from an online survey examining the association between work-related psychosocial stressors and psychological distress in an international sample of specific to mental health researchers. The study was approved by the University of Melbourne Human Research Ethics Committee (ID 1954670). All methods were performed in accordance with the relevant guidelines and regulations and all participants provided informed consent. The survey was available between 28 October 2019 and 1 March 2020. Participants were recruited via a number of targeted strategies including the email distribution lists of universities and mental health organisations, together with advertisements on the social media platform, Twitter. Recipients were invited to share the link to the study to their potentially eligible colleagues.

Eligible participants included those who were: (1) employed (full time, part time or casually) by a university or research institution (including research assistants, project managers, lecturers, and other academic staff), or; (2) enrolled as a postgraduate student (full-time or part-time Master’s or Ph.D. candidate), and; (3) the person’s main field of research related to mental health (e.g., psychology, psychiatry, social work). There were no restrictions on geographic location. All participants were screened against the eligibility criteria using an automatic skip-logic algorithm embedded within Qualtrics survey platform [ 21 ]. Participants who did not meet the eligibility criteria were not permitted to proceed to the study survey. The survey was formatted so that participants could not complete the survey more than once. Participation was anonymous and participants were not provided any incentive for taking part in the research.

A total of 357 participants provided consent, of whom 207 completed both the Copenhagen Psychosocial Questionnaire III (COPSOQ III) [ 22 ] and the Depression Anxiety and Stress Scale (DASS-21), representing 57.2% of the initial sample. Additional exploratory analyses were conducted on a subsample of 152 participants who answered questions about their history of mental health diagnoses.

Sociodemographic and work-related characteristics

Sociodemographic variables were assessed in a customised survey developed for the purpose of this study and included age, gender (male/female/other), relationship status (entered as a binary variable indicating the presence or absence of a relationship/spouse), dependents (e.g., children including biological and step-children; entered as binary variable representing the presence or absence of dependents), employment status (casual, full-time, part-time), type of work contract (fixed term/permanent) and clinical (e.g., registered psychologist or doctor) status (yes/no). Participants were classified according to their self-reported career stage. Participants who were employed as a research assistant or project officer were combined into a single category representing support staff. Participants who were enrolled in a Postgraduate degree (PhD or Master’s degree) were categorised as students. Participants who were employed at postdoctoral level or as a lecturer, were categorised as EMCRs. Lastly, senior researchers were participants who were employed as associate professor or above.

Work-related psychosocial stressors

Work-related psychosocial exposures were assessed using the COPSOQ III [ 22 ]. The COPSOQ III was selected because it has been validated in over 14 countries worldwide [ 23 ] and assesses relevant dimensions (e.g., work-life balance) that have been identified as key work-related psychosocial stressors experienced by academics in research settings [ 3 , 5 ]. Questionnaire items were obtained from the COPSOQ III middle and core items [ 24 ]. The questionnaire used in this study comprised 60 items, encompassing 25 psychosocial dimensions and five domains (Table 1 ) [ 22 ]. Each item is rated on a 5-point Likert scale. All items were transformed to a value ranging between zero (minimum value) to 100 (maximum value) with lower scores representing the lowest probable exposure (never/hardly ever) and 100 representing the highest probable exposure (always or to a very large extent). Higher scores indicated positive outcomes for the work organization and job content, interpersonal relations and leadership, social capital, and general health domains. Whereas higher scores indicated negative outcomes for the demands at work and work-life balance domains. Mean values were summarised according to the five core domains established previously in a previous international validation study that showed acceptable to good reliability with a Cronbach α > 0.7 [ 22 ] and good construct validity [ 25 ]. No adaption was made for this study.

General psychological distress

General psychological distress was assessed using the DASS-21 [ 12 ], a self-report measures of depression, anxiety and stress. The DASS-21 is an internationally validated instrument for measuring psychological distress [ 26 ] and has been shown as a valid and reliable tool for predicting the development of a possible mental health disorder in clinical settings [ 27 ]. Participants were asked to score each item on a 4-point Likert scale from 0 (did not apply to me at all) to 3 (applied to me very much). Total scores were computed by adding each item and multiplying the score by a factor 2 [ 12 ]. Total scores for the DASS-21 [ 12 ] range between zero and 120. Cut-off scores of 60 were labelled high distress [ 12 ]. Good inter-rater reliability, test–retest reliability, and validity of the DASS-21 have been reported previously in both clinical and non-clinical populations [ 28 , 29 , 30 ].

Self-reported diagnosed psychological disorder

Self-reported history of diagnosed mental ill health was assessed using two questions developed specifically for this study: (1) Prior to beginning your research career (including your Ph.D.), have you ever been diagnosed with a psychological disorder? (2) Since beginning your research career (including your PhD), have you ever been diagnosed with a psychological disorder? Participants were provided with the response options ‘yes’, ‘no’, and ‘I have not been diagnosed, but I probably could have been’.

Suicidal ideation

Self-reported suicidal ideation was assessed using three questions adapted from item 9 in the Patient Health Questionnaire-9 (PHQ-9; 31). Item 9 in the PHQ-9 [ 31 ] evaluates the frequency of suicidal ideation over the preceding two weeks and has been used as a single scale in studies reporting the prevalence of suicidal ideation [ 32 , 33 ] and has shown to be a valid measure of suicidal ideation in studies comparting results with those from detailed clinical interviews [ 34 , 35 , 36 ]. In the present study, participants were asked: (1) Over the past two weeks, how often have you been bothered by thoughts that you would be better off dead, or thoughts of hurting yourself in some way? Response options were: Not at all, more than half the days, nearly every day and several days. Items were collapsed into a binary variable representing the presence (consisting of the responses: “more than half the days”, “nearly every day” and “several days” or absence (consisting of the response: “not at all”) of suicidal ideation for each item. Additionally, participants were asked: (2) Over the past year, have you experienced thoughts that you would be better off dead, or thoughts of hurting yourself in some way? and (3) Since beginning your research career (including during your Ph.D.), have you ever experienced thoughts that you would be better off dead, or thoughts of hurting yourself in some way? Participants responded ‘yes’ or ‘no’, indicating the presence or absence of suicidal ideation.

Descriptive analysis was conducted to determine the sociodemographic characteristics of the study participants and their history of mental health diagnoses, suicidal ideation, work-related psychosocial exposures and psychological distress. Pearson’s chi-square test of independence was used to compare mental health diagnoses and suicidal ideation across career stages (research support staff, postgraduate students, EMCRs, and senior researchers). Group comparisons of work-related psychosocial exposures, DASS-21 [ 12 ] psychological distress and related sub-scores were conducted using ANOVA. Multiple pairwise comparisons were performed using the Tukey post hoc test, stratified by career stage.

Multivariate linear regression models [ 37 ] were used to estimate the association between the five work-related psychosocial stressor domains and psychological distress, controlling for age, sex, career stage, employment type (fulltime, part-time, casual) and the presence of a mental health policy at work (yes, no, unsure) lifetime mental health-diagnoses (present, absent), suicidal ideation in the past two-weeks (present, absent) for the subsample of 152 participants with complete data. In model 1 the association between work-related psychosocial stressors and psychological distress was adjusted by age and sex (male, female). Model 2 was adjusted for age, sex career stage, hours of employment, employment type, and the presence of a mental health policy at work. Model 3 was adjusted for the covariates included in Model 1 and 2 as well as lifetime mental health diagnosis and suicidal ideation in the past 2 weeks. Coefficients of linear regression ( β ) are calculated and displayed along with their 95% confidence intervals. To identify differences across models we compared coefficients and confidence intervals to examine whether the models were statistically different. All analyses were conducted in R v 4.1.2.

Sociodemographic and employment characteristics

Among the 357 participants who provided consent, 207 participants completed the full COPSOQ III [22). survey and DASS-21 [ 12 ]; a completion rate of 57.2%. Participants were from Australia (63.7%), Europe (29.9%), North America (5.3%), and South East Asia (< 1%). Most participants were female (82.1%) and over half (56.5%) were aged 18–34 years. Table 2 displays the sociodemographic and employment characteristics of participants according to career stage. The largest group of participants were postgraduate students (34.3%), followed by EMCRs (28.5%), senior researchers (20.3%), with research support staff constituting the smallest group (16.9%). One third (31%) of participants reported the presence of a mental health policy at their research institution, however relatively few had read the policy or were aware of its contents (15%).

Work-related psychosocial exposures

Table 3 shows the work-related psychosocial exposures according to career stage for the five work-related COPSOQ III [ 22 ] domains (see Table 1 ). Differences between career stages were observed for the domains: ‘demands at work’, ‘work-life balance (termed hereafter as work-life balance) ‘social capital’ and ‘health and wellbeing.’ Tukey’s post-hoc analysis revealed that the differences in the ‘demands at work domain’ were driven by lower (i.e., better) scores among research support staff relative to other career stages ( p  < 0.001 for postgraduate students, EMCRs and senior researchers, respectively). A similar trend was observed for the ‘work-life balance’ domain ( p  < 0.001 for postgraduate students; p  = 0.002 for EMCRs and p  = 0.04 for senior researchers). Differences in social capital were driven by higher scores among research support staff compared to senior researchers ( p  = 0.004). Lastly, differences in health and wellbeing were driven by higher scores in research support staff compared to postgraduate students ( p  = 0.003) and in senior researchers compared to students ( p  = 0.03).

Figures 1 , 2 and 3 show sub-scores for depression, anxiety, stress, and total psychological distress measured by the DASS-21 [ 12 ], stratified by career stage. Post-hoc comparisons revealed postgraduate students reported experiencing significantly greater anxiety and stress, and total psychological distress compared to research support staff ( p  = 0.01), EMCRs ( p  = 0.01) and senior researchers ( p  = 0.01; Table 4 ). A total of 27 (13.4%) participants reported DASS-21 [ 12 ] scores ≥ 60, indicating severe distress. Severe distress was most frequently reported among postgraduate students ( n  = 16), followed by research support staff ( n  = 4), EMCRs ( n  = 3) and senior researchers ( n  = 4). Fisher’s exact test revealed these differences were statistically significant ( p  = 0.02).

DASS-21 depression subscores by career stage

DASS-21 anxiety subscores by career stage

DASS-21 stress subscores by career stage

Self-reported history of mental health diagnoses and suicidal ideation

Of the 152 participants who responded to the question on self-reported mental health diagnoses, over half (54.6%) had received a mental health diagnosis at some point during their lives and a further 46 (30.1%) reported a suspected mental health disorder (i.e., did not receive a diagnosis but thought they should have; Table 5 ). The proportion of participants who had a diagnosed mental health disorder prior to their academic career was over one-third (37.5%), while just under one-third (31.6%) of participants received a psychological diagnosis since commencing their academic career. Senior researchers were significantly less likely to report having received a mental health diagnoses prior to their career in academia, compared to research support staff, postgraduate students, and EMCRs. Of the 80 (52.0%) participants who reported suicidal ideation since embarking on their academic career, 36 (17.4%) reported experiencing suicidal ideation in the past fortnight and 69 (33.3%) reported experiencing suicidal ideation in the past year. All measures of suicidal ideation were comparable across career stages.

Association between work-related psychosocial stressors and psychological distress

Table 6 shows the results of the regression models examining the relationship between work-related psychosocial exposures and psychological distress. A comparison of the confidence intervals for each of the models included in the analysis did not reveal statistically meaningful differences. After adjusting for all covariates, the association between ‘interpersonal relations and leadership’ and psychological distress was attenuated by the mental health covariates included in model 3 ( β  = −0.23, p  = 0.07). The association between the remaining work-related psychosocial domains and psychological distress remained significant. Based on the standardised β coefficients from the fully adjusted model (model 3), the strongest associations were observed for ‘work organisation and job content’ ( β  = −0.27, p  < 0.001) and ‘work-life balance’ ( β  = 0.23, p  = 0.01) domains. The weakest association was observed in the social capital dimension ( β  = −0.10, p  = 0.03).

Post-hoc power analysis

The post-hoc power analysis revealed that with 4 groups, a medium effect size 0.3, and a power of 0.8, the recommended sample size for the ANOVA was 44 for each group. The estimated power for the regression analysis was 0.9, based on 152 participants, 8 covariates, and a medium effect size of 0.3.

This study sought to describe the psychological distress, mental health and work-related psychosocial stressors experienced by mental health researchers according to their career stage and to identify the association between general psychological distress and work-related psychosocial stressors within the academic settings. Results of the regression analysis provide some insight into the potential modifiable work-related stressors associated with psychological distress among mental health researchers. For example, the strongest associations between psychological distress and work-related psychosocial stressors occurred in the ‘work organization and job contents’ and ‘work-life balance’ domains. The ‘work organization and job contents’ domain include factors such as influence at work, possibilities for development and control over working time, whereas the ‘work-life balance’ domain comprises commitment to the workplace, work engagement, job insecurity, insecurity over working conditions (e.g., office and desk space availability), quality of work, job satisfaction, and work-life-conflict. The current findings corroborate and extend on those reported in a previous survey involving 4,267 researchers in the UK that showed long-working hours, competing demands which reduce capacity to conduct research, and lack of job security as key concerns faced by academics [ 3 ]. Our study extends these findings by showing that after controlling for demographic, employment, and mental health factors, the same work-related psychosocial stressors are associated with increased psychological distress.

Results of the descriptive analysis of mental health and suicidal ideation outcomes revealed that over half of participants had either received a mental health diagnosis in their lifetime or had a suspected mental health diagnosis, compared to approximately 18% to 36% reported in previous studies in the general population [ 38 , 39 ]. Moreover one-third of participants had received a mental health diagnosis since commencing their academic careers. Similarly, rates of suicidal ideation were reported among 52% of participants, compared to approximately 10% reported in a previous cross-sectional study of suicidal ideation in the general population [ 40 ]. Taken together, these findings suggest that many mental health researchers have lived experience of mental ill health themselves, and that the work-place environment remains an important setting for primary and secondary prevention of mental-ill health.

This study showed that rates of self-reported mental health diagnoses and suicidal ideation were comparable across career stages for those in employment and the post-hoc power analysis demonstrated that these findings are unlikely to be driven by power limitations. However, postgraduate students reported notably higher scores for psychological distress, as well as anxiety, depression, and stress sub-scores, compared to research support staff, EMCRs and senior researchers. Potential explanations include financial strains experienced by many postgraduate students, which may include the need to also engage in paid employment leading to multiple role commitments [ 41 ]. Another possibility is that postgraduate students may face greater uncertainty regarding future employment [ 14 , 41 ]. Indeed, previous studies have shown that although the number of PhD graduates from science, technology engineering and mathematics has increased substantially over the past 20-years [ 42 ], the number of post-graduate research positions has remained constant, resulting in fewer job prospects among recent graduates [ 43 ]. Due to missing data on mental health outcomes it was not feasible to investigate the association between work-related psychosocial stressors and self-reported mental health diagnoses. However previous meta-analytic evidence across occupation groups found factors such as effort-reward imbalance and job insecurity were associated with a 1.81 and 1.91 increased odds of suicidal ideation [ 8 ], whereas factors such as long working hours and job insecurity were associated with 1.31–1.77 increased odds of developing an anxiety disorder [ 8 ].

It is noteworthy that senior researchers in this study were also significantly less likely to have received a mental health diagnosis prior to their career in academia compared to postgraduate students and EMCRs. On the one hand, it is possible that mental health researchers who stay in academia and transition to senior roles with tenure are those who are less likely to face ongoing work-related stressors that may contribute to their risk of psychological distress or mental ill health [ 44 ]. It is also possible that students and EMCRs experience significant differences in career pressure and funding success decline that senior researchers did not experience, to the same extent [ 45 ].

It has been argued that key structural changes within University institutions such as the marketisation of university education; increased competition between institutions; changes to higher education consumption patterns; the commodification of education; and the growth of managerialism is associated with negative work culture and reduced mental health and wellbeing in recent decades [ 5 ]. These structural changes have corresponded with increased student numbers, more demanding students, increased teaching demands, and a shift towards metrics-based performance management [ 5 ]. Similar findings were reported in the recent Wellcome trust report into academic work-place culture which identified the tendency for risk aversion and short termism among research institutions, manifested by short term contracts, job insecurity, increased competition to secure limited funding as significant concerns among academic researchers [ 3 ]. Moving forward, it is imperative that academic institutions reflect on the impact that structural barriers have on the workplace culture among academics and invest in strategies that have the potential to mitigate the adverse effects associated with psychological distress and wellbeing.

Despite the current recommendations, changes to the institutional structures require time and strategic investment, both of which are unlikely to occur rapidly. Thus it is important that the sector consider interventions that can be implemented in the interim, to bridge the gap between existing work-related psychosocial stressors and wellbeing among academics. Whilst evidence regarding the effectiveness of interventions targeting mental ill health in the workforce is limited, previous studies have shown that screening employees for mental ill health symptoms, proactive outreach, and providing opportunities for therapeutic counselling in the workplace, is both cost effective and associated with improved individual mental health outcomes and workplace productivity [ 46 , 47 ]. Furthermore, secondary interventions such as stress management, coping, resilience training, mindfulness-based stress reduction, problem solving, physical activity and cognitive behavioural therapy have been efficacious at increasing productivity and reducing distress in other occupational settings [ 48 , 49 , 50 , 51 , 52 ]. Given less than half of participants in the current study indicated having knowledge of a mental health and wellbeing policy or strategy at their place of employment, an important next-step forward for research institutions is to assess for the presence or absence of mental health and wellbeing policies within the workplace. This includes ensuring that mental health researchers have both access to and knowledge of help-seeking pathways at their institution or place of employment [ 53 ] and having policies in place that facilitate employees return to work following an episode of mental ill health [ 54 ]. Importantly these policies should include proactive strategies to reduce stigmatizing attitudes and cultures of non-disclosure that have been shown to impact individuals help-seeking behaviours in the workplace [ 55 ].

Lastly, data reported in the present study were collected prior to the onset of the COVID-19 pandemic. Factors such as social-distancing restrictions and the transition from office-based to home-based work environments have been linked to disruptions in productivity across disciplines [ 56 ]. As such, it is likely that the psychosocial stressors experienced by mental health researchers, such as those involving the work-life balance have increased as a result of COVID-19 restrictions. These effects may be particularly pronounced among specific groups, such as academics with young dependents [ 57 , 58 ] as well as postgraduate students who may have experienced significant disruptions in their social support networks whilst working remotely during their studies. Moving forward, future research that examines the impact of the COVID-19 pandemic on the mental health of mental health researchers and academics, more generally, should be prioritised so that decision makers within research institutions can embed timely and appropriate primary and secondary harm minimization strategies, accordingly.

Limitations

Limitations exist within this study. First, the majority of the sample were from western countries including Australia, UK and USA, with less than 1% from South East Asia and surrounding geographies. Significant cultural differences may exist in geographic regions not captured by the present survey and remain an important consideration for future studies. Second, the present study was limited to the 57% of participants who had completed the COPSOQ III [ 22 ] questionnaire and selection bias arising from missing data, particularly on suicide ideation outcomes, meant that it was not possible to investigate the association between mental health outcomes and work-related psychosocial stressors such as job insecurity and suicidal ideation, which have been reported in previous workplace studies [ 59 ]. Because attrition was greater than 40% it was not considered methodologically valid to use statistical adjustments such as multiple imputation on missing data [ 60 ]. For this reason the results of the present study should be interpreted in the context of generating hypotheses for future research [ 60 ].

Third, participants included in this study were self-selected and did not represent a random sample, nor did we sample participants for maximum variation. Furthermore, since participants were recruited via multiple email distribution links and via social media, it was not possible to identify the number of people who were contacted or reached, nor was it possible to calculate rates of refusal. This limitation is means that the study findings may be prone to selection bias and should be interpreted accordingly.

Lastly, previous studies have shown that occupation-based surveys may be susceptible to response biases reflecting higher rates of psychological distress compared to outcomes reported in population-based surveys [ 61 ]. This is considered to be a reflection of employees being consciously or unconsciously more inclined to vent their frustrations at their current work [ 61 ]. However, Winefield, Gillespie [ 6 ] found evidence to suggest that respondents to a university-based survey on stress and psychological distress were neither more nor less likely to display bias in their response based on their current distress. Given the current sample comprises mental health researchers who, by virtue of the academic and mental health training, may be more aware of response biases compared to the general population, we do not expect the results on general psychological distress to be significantly impacted by individual response biases. Nonetheless, as with any self-reported outcomes, results of the present study should be interpreted with caution.

Over half of mental health researchers have experienced mental ill health during their lives and this figure is greater than those reported in the general population and this warrants concerted efforts to validate these findings against larger, representative samples within academia. Despite working in the same environment, research support staff experience significantly less psychosocial stressors compared to postgraduate students, early-middle career researchers and senior researchers. In contrast, students are significantly more likely to experience mental ill health and suicidal ideation relative to mental health researchers at different career stages. Future research that targets the modifiable stressors at each career stage, including key systemic issues linked to work organization and job content and those that impact work-life balance has the potential to improve the overall mental health and wellbeing of mental health researchers and that these differences ought to be reflected in mental health and wellbeing policy and practice within research institutions.

Availability of data and materials

The dataset used and analysed during the current study available from the corresponding author on reasonable request.

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NTMH is funded by a Forrest Research Foundation Prospect Fellowship. GC is funded by the European Council: 101018325, EU 3rd Health Programme and the Health Research Board, Ireland: EIA-2019-005. OJK is supported by a Senior Postdoctoral Fellowship from Research Foundation Flanders (FWO 1257821 N). SR is funded by a Career Development Fellowship from the National Health and Medical Research Council of Australia (GNT1158881), and a Dame Kate Campbell Fellowship from the Faculty of Medicine, Dentistry and Health Sciences at The University of Melbourne. JR is funded by a Career Development Fellowship from the National Health and Medical Research Council of Australia (APP1142348) and the University of Melbourne Dame Kate Campbell Fellowship. CCW is supported by a McKenzie Postdoctoral Research Fellowship at the University of Melbourne (MCK2020292).

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Hill, N.T.M., Bailey, E., Benson, R. et al. Researching the researchers: psychological distress and psychosocial stressors according to career stage in mental health researchers. BMC Psychol 10 , 19 (2022). https://doi.org/10.1186/s40359-022-00728-5

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Factors predicting long-term weight maintenance in anorexia nervosa: a systematic review

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Eating disorder recovery is a poorly defined concept, with large variations among researchers’ definitions. Weight maintenance is a key aspect of recovery that remains relatively underexplored in the literature. Understanding the role of weight maintenance may help guide the development of treatments. This paper aims to address this by (1) investigating the factors predicting long-term weight maintenance in anorexia nervosa (AN) patients; (2) exploring differences in predictive factors between adolescent and adult populations; and (3) exploring how weight maintenance is conceptualised in the literature. Methods: We conducted a systematic review following PRISMA guidelines to address our research questions. Five databases were searched and filtered according to our exclusion criteria.

From the search, 1059 studies were yielded, and 13 studies were included for review. A range of weight, biological and psychological factors were found to predict weight maintenance among these papers. BMI at admission and discharge from inpatient treatment was the most common predictor among the papers. Few studies investigated biological factors and mixed evidence was found for psychological factors. We found no observable differences between adult and adolescent populations. Finally, weight maintenance was defined and measured differently across studies.

This review’s findings can help contribute to a well-rounded understanding of weight maintenance, and ultimately, of recovery. This can help support clinicians in tailoring interventions to improve long-term outcomes in AN. Future research should aim to replicate studies to better understand the relationship between the factors identified and weight maintenance.

Systematic review.

Avoid common mistakes on your manuscript.

Introduction

Eating disorders are severe mental health conditions that negatively impact an individual’s physical, psychological and social functioning [ 1 ]. The prevalence and severity of eating disorder presentations have increased significantly over the last few years, with hospital admissions in the UK increasing by 84% in the last five years [ 2 ]. The recent COVID-19 pandemic further contributed, in part, to this increase, whereby individuals with eating disorders faced significant challenges such as increased social isolation, a reduced sense of control, and limited access to healthcare services [ 3 , 4 ]. Taken together, these pressures have meant that eating disorder services have struggled to meet demand and healthcare providers face the ongoing need to develop and adapt treatments accordingly.

Clinicians have highlighted concerns around long-term outcomes for patients following eating disorder treatment, in particular relapse. For example, relapse rates of 31% have been reported in anorexia nervosa (AN) [ 5 ], highlighting the importance of understanding contributing factors. Studies have explored possible mechanisms behind AN relapse and have found a wide range of possible factors. Frostad et al. [ 6 ] found BMI at discharge was a significant predictor of relapse in adults and adolescents. This lies in contrast to other studies that have found factors such as weight and shape concerns [ 5 ] having the binge–purge subtype of AN, having more motivation to recover at different points in treatment, and the severity of pre-treatment checking behaviour [ 7 ] to be significant predictors of relapse. Whilst these findings may support the adaptations of future treatments, a drawback of focusing on relapse is the heavy emphasis on preventing negative outcomes, rather than promoting positive change. These are two separate facets of long-term AN outcomes, and a substantial focus on preventing relapse may disempower an individual in their journey.

The promotion of positive outcomes in AN can be viewed through a recovery-focused lens. Numerous factors have been identified as predictors of recovery or positive outcomes, including personality traits [ 8 , 9 ], family relations [ 10 ], impulsivity [ 9 ], selflessness [ 11 ], and self-esteem [ 12 , 13 ]. As the aim for patients, families and clinicians is full recovery from AN, this has led to a comprehensive literature base on factors impacting AN recovery, and subsequently, a vast landscape of possible definitions of recovery [ 14 ]. Many researchers have attempted to operationalise ‘recovery’, with a widely accepted modern view that this should include a combination of biological, physical, and cognitive constructs [ 15 ], as well as measures of psychological and social wellbeing [ 16 ]. However, the concept of recovery remains somewhat abstract due to the variability in the individual’s experience and the personal nature of recovery for each person, which together have led to difficulties with measuring recovery, its predictors and with producing replicable studies [ 8 ].

An important aspect of recovery is weight maintenance, which refers to the sustained management of weight within a healthy range over time. Underweight individuals with AN have a twofold challenge when it comes to weight: weight gain and weight maintenance. Research has investigated factors that contribute to weight gain in various clinical settings [ 17 , 18 ]. Byrne et al. [ 17 ] found that parental self-efficacy was a significant predictor of weight gain for adolescents undergoing family-based treatment for AN. Nyman-Carlsson et al. [ 18 ] investigated pre-treatment factors predicting weight gain in a sample of young adult women and found that different predictors were significant depending on the type of treatment received. These factors included levels of emotion dysregulation and deficits in one’s ability to understand and cope with emotions. Research has also demonstrated early weight gain during treatment is a strong predictor of overall weight gain, as well as full recovery [ 19 , 20 ]. Whilst studies have investigated weight gain, there is little research on factors that impact weight maintenance. This is surprising given weight maintenance is a primary aim of AN treatments. Furthermore, research has found that weight maintenance is an essential part of full recovery outcomes [ 21 , 22 ]; for example, Rigaud et al. [ 22 ] found in a sample of adult inpatients with AN that more years spent relapse-free increased the probability of reaching full recovery with each year.

Better understanding the factors that impact weight maintenance can provide a focus on the positive aspects of AN trajectories and may support services to sustain existing improvement, including maximising current successful aspects of treatment. Furthermore, this perspective would allow us to focus on weight as an important aspect of positive change, whilst acknowledging that there are other relevant factors within recovery. This specific focus prevents researchers from becoming lost in an abstract world of ‘recovery’. In this context, recovery lacks a clear conceptualisation due to the wide number of relevant factors and its personal nature. Investigating weight maintenance in more depth can contribute to establishing a better understanding of recovery, and at the same time, the specificity of weight maintenance may allow findings to be more effectively applied in clinical settings.

This study reviews the current literature on factors associated with long-term weight maintenance in AN specifically, rather than eating disorders as a whole, given the heterogeneity of eating disorders and the likelihood of different factors affecting weight maintenance. Long-term weight maintenance is considered as defined by the papers included in the review and its definition will be further discussed in this paper.

This study further aims to investigate whether any identified factors vary between adult and adolescent populations. AN impacts adolescents and adults differently due to differences across developmental stages; for example, younger patients may have poorer medical outcomes as compared with adults [ 23 ]. Furthermore, therapeutic approaches differ according to age [ 24 ]. It is therefore possible that the factors maintaining long-term weight maintenance may also differ for each population. Another important reason to investigate differences between adults and adolescents is their differences in treatment outcome. Despite poorer morbidity, research suggests that adolescents have overall better outcomes after treatment for their eating disorder, and that the effect of factors such as early weight gain is larger for children than for adults [ 25 , 26 ]. This suggests that it is important to investigate patterns in factors that predict aspects of recovery, such as weight maintenance, as this may help explain overall differences in recovery rates for each group.

This paper aims to answer the following questions:

What are the factors associated with long-term weight maintenance following weight restoration in AN?

What are the similarities and differences in the factors associated with long-term weight maintenance between adult and adolescent AN populations?

How is long-term weight maintenance conceptualised in AN literature?

Search strategy

A systematic search of the literature was conducted by one reviewer, following PRISMA guidelines, between February and August 2022 using PubMed, MEDLINE, PsycINFO, Cochrane Library and Wiley Online Library. A pre-defined list of search terms was used to generate the literature search, including a combination of: “eating disorders”; “long term weight restoration”; “long term weight maintenance”; “anorexia nervosa”; “weight maintenance” and “restrictive eating disorder”.

Eligibility criteria and selection process

Due to the lack of available studies in this research area, no limits were placed on the patient demographics, type of intervention or study design. Studies were excluded using the following primary criteria:

Measuring weight maintenance after weight loss, in obesity and binge eating populations;

Examining factors that predict poor outcomes;

Examining factors that predict global outcomes, including psychological improvement; and

Measuring factors that predict long-term improvements in weight as a continuous variable.

Inclusion criteria included:

Studies measuring factors associated with and/or predicting weight maintenance in AN populations; and

English language studies.

For the purpose of this paper, studies met the condition of weight maintenance if they identified a weight or weight range to be sustained over a period of time. No limits were placed on the defined length of time required for a participant’s weight to be considered maintained, and patterns in these definitions will be discussed in the results.

The reviewer screened abstracts and retrieved full-texts of appropriate studies using the eligibility criteria above. Reference lists of reports that were assessed for eligibility were also searched for any appropriate studies. Reference lists were searched at this point in the retrieval process as the reports retrieved thus far were likely to be the most appropriate and may refer to other studies that contribute to their reports on weight maintenance. Figure  1 outlines the selection process for the studies included in this review, including full exclusion criteria. The third author was consulted regarding any studies that required further consultation to determine if they met inclusion or exclusion criteria.

PRISMA 2020 flow diagram

A data extraction sheet was used by two reviewers to independently gather data on study purpose and design, intervention details, participant characteristics, definition of weight maintenance, any other measures and results/outcomes were sought from the retrieved full-text studies. These studies were then examined by the third author for clarification on study details and outcomes where needed.

The quality of the included studies was evaluated using the Quality Assessment Tool (QAT) [ 25 ].

The initial search yielded 1059 studies which were then screened for eligibility. Eighty-eight studies remained, and their abstracts were reviewed, with any papers that did not investigate factors associated with weight maintenance in AN being excluded at this stage. Thirteen studies remained, and the full texts were retrieved and assessed for eligibility. In addition, the reference lists of these 13 studies were reviewed, alongside any papers that had cited them, yielding a total of 21 additional studies. Combined, this resulted in the retrieval of full-texts for 34 studies. Twenty-one studies were excluded because they met the exclusion criteria, resulting in 13 studies for review in this paper. The process of selecting studies for review, following PRISMA guidelines, is depicted in Fig.  1 .

Sample characteristics of all included studies, as well as results from the quality assessment, are presented in Table  1 . All studies examined factors that influence long-term weight maintenance in individuals with AN as part of their research, although some studies did not investigate this as a primary aim. All the included studies were published between 2007 – 2021. In all 13 studies, the samples consisted of patients who had been admitted to inpatient or day patient programmes [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 ] and in 6 of these studies, patients had been discharged to outpatient programmes [ 26 , 27 , 28 , 29 , 30 , 38 ].

The mean age of participants across all studies ranged from 14.40 to 32.55 years. Data from studies show that the average weight maintenance rate for the participants ranged from 32.10% to 62.50%. Six studies included only adults [ 26 , 28 , 33 , 35 , 37 , 38 ], two studies included only adolescents [ 29 , 32 ], and five studies included both adults and adolescents [ 27 , 30 , 31 , 34 , 36 ]. The combined sample size across all the studies was 1689. Significant findings and p-values from the included papers are presented in Table  2 .

Definition of weight maintenance

There was a range of weight maintenance definitions across the studies, with different definitions for both adult and adolescent samples. Eleven studies used a measure of between BMI ≥18 and 19.5 [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 35 , 36 , 37 ], whilst Forman [ 34 ] used > 85% median BMI (%mBMI).

All studies took measures at three or more time points: admission, discharge and one or more follow-up points. Follow-up ranged from 6 months to 5 years. Six studies provided measures of weight between discharge and follow-up to ensure weight maintenance was sustained during the given time period [ 27 , 28 , 30 , 31 , 35 , 38 ]. From these, two studies used only in-person measures [ 27 , 30 ], two studies used only online/phone measures [ 31 , 35 ], and two studies used a combination of both [ 28 , 38 ]. Furthermore, three studies defined the time in weight maintenance needed for a patient to be considered in ‘maintenance’, specifying a requirement ranging from 4 to 8 consecutive weeks [ 27 , 28 , 30 ].

After reviewing the included articles, our findings can be grouped into three themes: BMI/weight variables; biological markers; and psychological markers.

Weight variables—BMI

Overall, BMI was most commonly investigated as a predictor of weight maintenance across the studies [ 26 , 29 , 30 , 31 , 32 , 35 , 37 ].

The most common finding was that BMI at discharge from inpatient treatment significantly predicted weight maintenance at follow-up [ 26 , 30 , 31 , 35 , 37 ]. Kaplan [ 30 ] found that women with a higher BMI at discharge from intensive treatment (inpatient or day patient) were more likely to maintain their weight at 6- and 12-month follow-up. El Ghoch [ 26 ] found discharge BMI significantly predicted weight maintenance at 12-month follow-up in a sample of inpatient women. Redgrave [ 37 ] also found similar results using a more stringent measure of maintenance (BMI ≥ 19 kg/m 2 ) at 6-month follow-up, and two studies found similar findings at longer term follow-up, namely up to 5 years [ 31 , 35 ]. These five studies reported that participants had a discharge BMI between 19.0 ± 3.3 kg/m 2 and 20.3 ± 0.5 kg/m 2 .

Alternatively, only two studies found that a higher BMI at admission to inpatient treatment significantly predicted weight maintenance up to 1-year follow-up [ 29 , 31 ]. Castro-Fornieles [ 29 ] found that admission BMI predicted weight maintenance at 9-month follow-up. Glasofer [ 31 ] found that BMI at admission predicted weight maintenance at 18.5 kg/m 2 , but not at a more stringent cut off at 19.5 kg/m 2 , whereas discharge BMI predicted maintenance in both maintenance at 18.5 kg/m 2 and at 19.5 kg/m 2 . These studies reported a BMI at admission between 15.5 ± 1.4 kg/m 2 and 16.0 ± 1.86 kg/m 2 .

However, not all studies found BMI to be a significant predictor. Boehm [ 32 ] used a different measure of BMI and found that increases in BMI standard deviation scores did not significantly predict weight maintenance at follow-up, which was a mean of 3.7 years after the start of inpatient treatment.

Other weight variables

Some studies investigated the predictive value of other weight-related variables on long-term weight maintenance. Forman [ 34 ] found that %MBMI was a significant predictor of weight maintenance at 1-year follow-up in a sample of adolescents and young adults, such that for each 5% increase in baseline %MBMI, patients were 1.69 times more likely to reach weight maintenance.

Uniacke [ 27 ] investigated the impact of weight suppression using data from Kaplan’s [ 30 ] study. Weight suppression refers to the difference between a person’s previous highest weight and their current weight [ 40 ]. Whilst previous research has found that weight suppression predicts weight gain outcomes [ 40 ], Uniacke [ 27 ] found neither weight suppression, nor the interaction between weight suppression and BMI (measured at start of outpatient treatment), significantly predicted weight maintenance at follow-up.

One study investigated the predictive value of early weight gain on long-term outcomes. Kaplan [ 30 ] found that the rate of weight change, namely a lower rate of weekly weight loss, in the first 28 days of outpatient CBT treatment was a significant predictor of weight maintenance.

Biological markers

Three studies investigated the impact of biological factors related to weight [ 26 , 28 , 38 ]. Two studies found that body fat percentage, measured using a whole-body DXA scan and MRI imaging, did not significantly predict weight maintenance at 12-month follow-up [ 26 , 38 ]. However, Kim [ 28 ] found that both body fat percentage and higher levels of leptin (fat-adjusted) pre-discharge from inpatient treatment, measured using whole-body MRI imaging, significantly predicted weight maintenance at 12-month follow-up.

Psychological markers

The identified studies in this paper investigated a range of psychological markers with mixed findings. Some studies found significant findings for predictors related to motivation and belief in oneself to change [ 29 , 36 ]. Castro-Fornieles [ 29 ] found that readiness to recover significantly predicted weight maintenance at 9-month follow-up in a sample of adolescents. Cooper [ 36 ] found that normative eating self-efficacy at admission was significantly associated with long-term weight maintenance, with participants 4.65 times more likely to have maintained weight at 6-month follow-up for each one-unit increase in normative eating self-efficacy scores from admission to follow-up.

Three studies investigated the impact of body image concern components on weight maintenance outcomes namely: ‘fear of weight gain’, ‘preoccupation with weight or shape’, ‘feeling fat’, body image distortion, and body image self-efficacy [ 32 , 33 , 36 ]. Calugi [ 33 ] explored a range of variables, measured by using items taken from the Eating Disorder Examination 12.0D at the end of treatment, and found that lower scores for ‘fear of weight gain’ at baseline were associated with a higher likelihood of maintaining weight at 6- and 12-month follow-up in a sample of young women. Calugi [ 33 ] also found that lower scores of ‘preoccupation with shape or weight’, and ‘feeling fat’ predicted weight maintenance at 6-month follow-up, but not at 12-month follow-up. However, the authors did not include significance values in their findings therefore it is unclear whether these measures are significant predictors. In contrast, Boehm [ 32 ] investigated a separate facet of body image, specifically perceptual body image distortion, referring to the accuracy of comparison between one’s perceived and actual body size [ 41 ], and found this did not significantly predict weight maintenance, although it was a significant predictor of long-term global outcome (including psychological outcomes). In line with this, Cooper [ 36 ] found that improvements in body dissatisfaction and body image self-efficacy from admission to follow-up, namely the belief in oneself to complete everyday tasks without being held back by body image concerns [ 42 ], did not significantly predict long-term weight maintenance either.

Other studies found that psychological variables, including anxiety symptoms, depression symptoms, eating disorder psychopathology, expectations for recovery, personality traits and quality of life did not significantly predict long-term weight maintenance [ 30 , 35 , 36 ].

Difference between adult and adolescent samples

The studies were reviewed to examine whether any predictors differentiated the adult and adolescent patient groups. None of the studies with both adolescent and adult samples analysed differences in predictors between these two groups. Studies looking at biological markers used only adult samples. Otherwise, there were no observable patterns in the data to suggest that any variable has been found to predict weight maintenance more consistently in adult or adolescent samples.

The overarching aim of this review was to explore the factors predicting long-term weight maintenance in adults and adolescents with AN, and then compare any differences between adults and adolescents. Another aim was to evaluate how weight maintenance is defined and measured among these papers. A literature review was conducted following the PRISMA framework, resulting in 13 studies. The review identified a range of weight, biological and psychological factors investigated in relation to weight maintenance, but also found that the concept of weight maintenance varied among the studies.

BMI at admission and discharge

The most common significant finding across studies was that BMI at admission and discharge from inpatient treatment significantly predicted weight maintenance across both adult and adolescent samples.

Our finding that admission BMI predicts weight maintenance is mirrored in the literature on recovery, as admission BMI has been found to significantly predict treatment outcome and recovery [ 43 , 44 ]. However, we found that BMI at discharge from treatment was a more common significant predictor of weight maintenance than admission BMI among the included studies. This finding is important as there is little research on the predictive value of discharge BMI in the recovery and relapse literature. A possible reason for this finding is that patients with a higher discharge BMI would have a wider margin for some weight loss to remain in the ‘maintenance’ category as compared to those with a lower discharge BMI, making maintenance easier from a weight perspective. It is also possible that higher BMI at discharge correlates with increased cognitive function recovery, which is linked to increased cognitive flexibility [ 45 ]. This may support individuals in their efforts to maintain their weight after treatment, although further research is needed to investigate these relationships.

Research on recovery has investigated changes in BMI during inpatient treatment, rather than BMI before or after treatment, and found that larger changes in BMI between admission and discharge were a significant predictor of remission at follow-up, whereas admission BMI was not a significant predictor [ 46 ]. It would be interesting to investigate this construct further in relation to long-term weight maintenance, in order to better understand the predictive value and relationships between admission BMI, discharge BMI and weight gain during treatment.

Some papers included in this review investigated the predictive value of other weight-related variables, such as weight suppression and rate of weight change in treatment [ 27 , 28 ]. Whilst some findings are significant, given that there has been little replication of any significant findings on these weight variables, future research is needed.

Biological factors

This review also identified studies that investigated biological factors predicting weight maintenance, namely body fat and leptin levels. Whilst studies investigating body fat found this was not a significant predictor of weight maintenance [ 26 , 38 ], one study found that body fat percentage and leptin levels at discharge significantly predicted weight maintenance at follow-up [ 28 ]. This may correlate with our finding that discharge BMI predicts weight maintenance, as identified in this review. Given the relationship between body fat percentage and leptin levels with a person’s weight for height, these findings may be linked [ 6 ].

Psychological factors

The present study found a range of psychological factors affecting weight maintenance among the literature. Some studies found that factors related to self-efficacy and motivation to change significantly predicted weight maintenance [ 36 , 39 ]. Research suggests that increased self-efficacy predicts end-of-treatment outcomes in eating disorder populations [ 12 , 47 ], and it is possible that this may help to support individuals with AN in maintaining their weight after treatment, helping them cope with difficulties and challenges they may face during this process [ 48 ]. However, the other studies looking at body image constructs in this review found mixed results [ 32 , 33 , 36 ]. Research suggests that psychological factors tend to take longer than physical factors to improve [ 49 ], and body image disturbance is suggested to shift in the later stages of recovery [ 12 ]. This may explain these inconsistent findings in the present review, though this should be interpreted with caution.

Adult vs adolescent samples

Our second aim was to explore whether there were any differences between adult and adolescent samples in factors that predict weight maintenance. We found no observable patterns in results from the included studies between age groups. This may be due to the limited number of studies in this review, which will have impacted our ability to observe patterns; it would be important for future research to investigate this further. An understanding of the role of different factors in weight maintenance may help clinicians to tailor interventions according to age group, as adolescents and adults face different challenges when overcoming eating disorders. [ 50 ].

Conceptualisation of weight maintenance

We found that many studies used different definitions of weight maintenance, including different weight cut-offs and time periods required for weight restoration to be considered maintenance. This makes it difficult to compare findings across studies because different factors may have varying predictive value. For example, one study using a different measure of BMI, namely BMI-SDS, found this did not predict weight maintenance [ 32 ], which may suggest that the measurements used may impact findings. Further, one study with a notably longer-term follow-up period [ 32 ] had non-significant findings regarding a range of variables. This highlights the need for more consistent measurements and follow-up periods, to gain a better understanding of predictive variables in weight maintenance.

Despite this, many studies used the weight criterion from the Morgan–Russell scale [ 51 ]. These studies also included menstrual recovery as part of their weight maintenance definition. This dilutes the definition of weight maintenance, which cannot be used across wider samples, including men.

Furthermore, most studies took one measure of weight at follow-up and used a weight cut off to establish whether participants had maintained their weight throughout this time period, instead of taking multiple measurements to ascertain sustained weight maintenance. This approach does not necessarily represent a true measure of ‘maintenance’, as it is possible that participants may have lost weight in between follow-up measures.

Taken together, there is a lack of consensus between researchers in the definition of weight maintenance, as well as a need for more robust and consistent measurement methods. We hope this paper stimulates the debate. It is important to improve this before trying to explore more complex concepts, such as recovery.

Strengths and limits

This study gives voice to the lack of clarity around the concept of eating disorders recovery, alongside the impact that this could have on treatment. To our knowledge this is the first systematic review on papers looking at factors affecting weight maintenance.

The present study has several limitations. Findings should be treated with caution given the small number of available studies, as well as the heterogeneity in their design, intervention and follow-up durations. The differences make it difficult to make comparisons between studies and find patterns in results, highlighting the need for a common definition of weight maintenance across studies [ 45 ]. We included studies that included menstruation as part of their criteria. It is possible that this may have skewed findings, for having an additional criterion for maintenance may reduce the likelihood that certain predictors are found significant, or alternatively, other factors may hold more importance. In addition, most studies had primarily white female samples, particularly so in the studies that included menstruation resumption as part of their criteria. Men and non-white samples are more likely to have poorer outcomes [ 44 ], therefore significant predictors identified in this review may not apply to those populations.

Implications

Future research must focus on developing a clear concept of weight maintenance as it pertains to the eating disorders and particularly AN. Research and common clinical observation suggests that weight maintenance is the first step to full psychological recovery [ 19 ]. In addition, there lacks a clear consensus on the definitions of recovery and relapse, and better understanding weight maintenance may help contribute to rectifying this. Understanding the factors that predict weight maintenance can help clinicians adapt existing treatments to focus on targeting these factors, with the aim of supporting patients to maintain their weight after treatment and work towards full recovery.

Avenues that may be explored by future research include replicating studies looking at BMI throughout treatment, in order to increase reliability in the findings around weight variables. Future research should also investigate further the relationship between body image and long-term weight maintenance, given this review’s mixed findings.

The present study aimed to scope the literature on the factors predicting weight maintenance after acknowledging that this is a critical factor for recovery, and the inconsistent findings and definitions of recovery.

The current literature on weight maintenance suggests that a higher BMI at admission and discharge are the strongest predictors of long-term weight maintenance. Mixed findings have been found for biological and psychological factors. It is important for readers to interpret these findings with care, and to combine this with a wider understanding of what is important for AN patients, rather than using these results in isolation to promote a purely medical model of recovery. The findings provide important implications for future research as they highlight the need for a common definition of weight maintenance, as well as the need to compare differences between adult and adolescent samples so we can ensure that treatments are tailored to their individual needs. Further research should aim to develop a clear definition of weight maintenance and investigate predictive factors, including how BMI and weight gain processes account for weight maintenance, and elucidate the role of psychological processes in weight maintenance.

What is already known on this subject?

There exists extensive research on eating disorder recovery, but there are different views on how this should be defined and measured. Several factors have been suggested to predict long-term recovery, yet the recovery landscape remains unclear due to the lack of consensus on the definition of recovery and on the factors deemed to predict recovery.

What this study adds?

This study adds an understanding of how weight maintenance is conceptualised in eating disorder research and an initial understanding of factors predicting weight maintenance, upon which future research can build.

Data availability

The datasets used in this study are available from the corresponding author on reasonable request.

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Maurel, L., MacKean, M. & Lacey, J.H. Factors predicting long-term weight maintenance in anorexia nervosa: a systematic review. Eat Weight Disord 29 , 24 (2024). https://doi.org/10.1007/s40519-024-01649-5

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Psychiatric and medical comorbidities of eating disorders: findings from a rapid review of the literature

• Ashlea Hambleton 1 ,
• Genevieve Pepin 2 ,
• Anvi Le 3 ,
• Danielle Maloney 1 , 4 ,
• National Eating Disorder Research Consortium ,
• Stephen Touyz 1 , 4 &
• Sarah Maguire 1 , 4  

Journal of Eating Disorders volume  10 , Article number:  132 ( 2022 ) Cite this article

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Eating disorders (EDs) are potentially severe, complex, and life-threatening illnesses. The mortality rate of EDs is significantly elevated compared to other psychiatric conditions, primarily due to medical complications and suicide. The current rapid review aimed to summarise the literature and identify gaps in knowledge relating to any psychiatric and medical comorbidities of eating disorders.

This paper forms part of a rapid review) series scoping the evidence base for the field of EDs, conducted to inform the Australian National Eating Disorders Research and Translation Strategy 2021–2031, funded and released by the Australian Government. ScienceDirect, PubMed and Ovid/Medline were searched for English-language studies focused on the psychiatric and medical comorbidities of EDs, published between 2009 and 2021. High-level evidence such as meta-analyses, large population studies and Randomised Control Trials were prioritised.

A total of 202 studies were included in this review, with 58% pertaining to psychiatric comorbidities and 42% to medical comorbidities. For EDs in general, the most prevalent psychiatric comorbidities were anxiety (up to 62%), mood (up to 54%) and substance use and post-traumatic stress disorders (similar comorbidity rates up to 27%). The review also noted associations between specific EDs and non-suicidal self-injury, personality disorders, and neurodevelopmental disorders. EDs were complicated by medical comorbidities across the neuroendocrine, skeletal, nutritional, gastrointestinal, dental, and reproductive systems. Medical comorbidities can precede, occur alongside or emerge as a complication of the ED.

Conclusions

This review provides a thorough overview of the comorbid psychiatric and medical conditions co-occurring with EDs. High psychiatric and medical comorbidity rates were observed in people with EDs, with comorbidities contributing to increased ED symptom severity, maintenance of some ED behaviours, and poorer functioning as well as treatment outcomes. Early identification and management of psychiatric and medical comorbidities in people with an ED may improve response to treatment and overall outcomes.

Plain English Summary

The mortality rate of eating disorders is significantly elevated compared to other psychiatric conditions, primarily due to medical complications and suicide. Further, individuals with eating disorders often meet the diagnostic criteria of at least one comorbid psychiatric or medical disorder, that is, the individual simultaneously experiences both an ED and at least one other condition. This has significant consequences for researchers and health care providers – medical and psychiatric comorbidities impact ED symptoms and treatment effectiveness. The current review is part of a larger Rapid Review series conducted to inform the development of Australia’s National Eating Disorders Research and Translation Strategy 2021–2031. A Rapid Review is designed to comprehensively summarise a body of literature in a short timeframe, often to guide policymaking and address urgent health concerns. The Rapid Review synthesises the current evidence base and identifies gaps in eating disorder research and care. This paper gives a critical overview of the scientific literature relating to the psychiatric and medical comorbidities of eating disorders. It covers recent literature regarding psychiatric comorbidities including anxiety disorders, mood disorders, substance use disorders, trauma and personality disorders and neurodevelopmental disorders. Further, the review discusses the impact and associations between EDs and medical comorbidities, some of which precede the eating disorder, occur alongside, or as a consequence of the eating disorder.

Introduction

Eating Disorders (EDs) are often severe, complex, life-threatening illnesses with significant physiological and psychiatric impacts. EDs impact individuals across the entire lifespan, affecting all age groups (although most often they emerge in childhood and adolescence), genders, socioeconomic groups and cultures [ 1 ]. EDs have some of the highest mortality rates of all psychiatric illnesses and carry a significant personal, interpersonal, social and economic burdens [ 2 , 3 ].

Adding to the innate complexity of EDs, it is not uncommon for people living with an ED to experience associated problems such as psychological, social, and functional limitations [ 2 ] in addition to psychiatric and medical comorbidities [ 4 , 5 , 6 ]. Comorbidity is defined as conditions or illnesses that occur concurrently to the ED. Evidence suggests that between 55 and 95% of people diagnosed with an ED will also experience a comorbid psychiatric disorder in their lifetime [ 4 , 6 ]. Identifying psychiatric comorbidities is essential because of their potential impact on the severity of ED symptomatology, the individual’s distress and treatment effectiveness [ 7 , 8 ].

The mortality rate of EDs is significantly higher than the general population, with the highest occurring in Anorexia Nervosa (AN) due to impacts on the cardiovascular system [ 9 ] and suicide. [ 10 ] Mortality rates are also heightened in Bulimia Nervosa (BN) and Other Specified Feeding and Eating Disorder (OSFED) [ 11 ]. Suicide rates are elevated across the ED spectrum, and higher rates are observed in patients with a comorbid psychiatric disorder [ 10 , 12 ]. Of concern, the proportion of people with an ED not accessing treatment is estimated to be as high as 75% [ 13 ], potentially a consequence of comorbidities which impact on motivation, the ability to schedule appointments or require clinical prioritisation (i.e., self-harm or suicidal behaviours) [ 14 ]. Further, for many of those diagnosed with an ED who access treatment, recovery is a lengthy process. A longitudinal study found approximately two-thirds of participants with AN or BN had recovered by 22 years follow-up [ 15 ]. Although recovery occurred earlier for those with BN, illness duration was lengthy for both groups with quality of life and physical health impacts [ 15 ]. Further, less is known regarding the illness trajectory for those who do not receive treatment.

Medical comorbidities associated with EDs can range from mild to severe and life-threatening, with complications observed across all body systems, including the cardiac, metabolic and gastrointestinal, and reproductive systems [ 5 ]. These comorbidities and complications can place people at increased risk of medical instability and death [ 5 ]. Therefore, understanding how co-occurring medical comorbidities and complications impact EDs is critical to treatment and recovery.

In addition to ED-associated medical comorbidities, EDs often present alongside other psychiatric conditions. Psychiatric comorbidities in people with EDs are associated with higher health system costs, emergency department presentations and admissions [ 16 ]. Comorbidities may precede the onset of the ED, be co-occurring, or result from symptoms and behaviours associated with the ED [ 17 , 18 ]. Individuals with an ED, their carers and care providers often face a complex and important dilemma; the individual with an ED requires treatment for their ED but also for their psychiatric comorbidities, and it can be difficult for treatment providers to determine which is the clinical priority [ 19 ]. This is further complicated by the fact that EDs and comorbidities may have a reciprocal relationship, whereby the presence of one impact the pathology, treatment and outcomes of the other.

The current Rapid Review (RR) forms part of a series of reviews commissioned by the Australian Federal Government to inform the Australian National Eating Disorders Research and Translation Strategy 2021–2031 [ 20 ]. In response to the impact of psychiatric and medical comorbidities on outcomes, this rapid review summarises the recent literature on the nature and implications of psychiatric and medical comorbidities associated with EDs.

The Australian Government Commonwealth Department of Health funded the InsideOut Institute for Eating Disorders (IOI) to develop the Australian Eating Disorders Research and Translation Strategy 2021–2031 [ 20 ] under the Psych Services for Hard to Reach Groups initiative (ID 4-8MSSLE). The strategy was developed in partnership with state and national stakeholders including clinicians, service providers, researchers, and experts by lived experience (both consumers and families/carers). Developed through a two-year national consultation and collaboration process, the strategy provides the roadmap to establishing EDs as a national research priority and is the first disorder-specific strategy to be developed in consultation with the National Mental Health Commission. To inform the strategy, IOI commissioned Healthcare Management Advisors (HMA) to conduct a series of RRs to assess all available peer-reviewed literature on all DSM-5 listed EDs.

A RR Protocol [ 21 ] was utilised to allow swift synthesis of the evidence in order to guide public policy and decision-making [ 22 ]. This approach has been adopted by several leading health organisations including the World Health Organisation [ 17 ] and the Canadian Agency for Drugs and Technologies in Health Rapid Response Service [ 18 ], to build a strong evidence base in a timely and accelerated manner, without compromising quality. A RR is not designed to be as comprehensive as a systematic review—it is purposive rather than exhaustive and provides actionable evidence to guide health policy [ 23 ].

The RR is a narrative synthesis adhering to the PRISMA guidelines [ 24 ]. It is divided by topic area and presented as a series of papers. Three research databases were searched: ScienceDirect, PubMed and Ovid/Medline. To establish a broad understanding of the progress made in the field of EDs, and to capture the largest evidence base from the past 12 years (originally 2009–2019, but expanded to include the preceding two years), the eligibility criteria for included studies were kept broad. Therefore, included studies were published between 2009 and 2021, written in English, and conducted within Western healthcare systems or health systems comparable to Australia in terms of structure and resourcing. The initial search and review process was conducted by three reviewers between 5 December 2019 and 16 January 2020. The re-run for the years 2020–2021 was conducted by two reviewers at the end of May 2021.

The RR had a translational research focus with the objective of identifying evidence relevant to developing optimal care pathways. Searches therefore used a Population, Intervention, Comparison, Outcome (PICO) approach to identify literature relating to population impact, prevention and early intervention, treatment, and long-term outcomes. Purposive sampling focused on high-level evidence studies encompassing meta-analyses; systematic reviews; moderately sized randomised controlled studies (RCTs) (n > 50); moderately sized controlled-cohort studies (n > 50); and population studies (n > 500). However, the diagnoses ARFID and UFED necessitated less stringent eligibility criteria due to a paucity of published articles. As these diagnoses are newly captured in the DSM-5 (released in 2013, within the allocated search timeframe), the evidence base is still emerging, and few studies have been conducted. Thus, smaller studies (n =  ≤ 20) and narrative reviews were also considered and included. Grey literature, such as clinical or practice guidelines, protocol papers (without results) and Masters’ theses or dissertations, were excluded. Other sources (which may not be replicable when applying the current methodology) included the personal libraries of authors, yielding two additional studies (see Additional file 1 ). This extra step was conducted in line with the PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews [ 25 ].

Full methodological details including eligibility criteria, search strategy and terms and data analysis are published in a separate protocol paper, which included a total of 1320 studies [ 26 ] (see Additional file 1 : Fig. S1 for PRISMA flow diagram). Data from included studies relating to psychiatric and medical comorbidities of EDs were synthesised and are presented in the current review. No further analyses were conducted.

The search included articles published in the period January 2009 to May 2021. The RR identified 202 studies for inclusion. Of these, 58% related to psychiatric comorbidities (n = 117) and 42% to medical comorbidities (n = 85). A full list of the studies included in this review and information about population, aims and results can be found in Additional file 2 : Tables S3, S4. Results are subdivided into two categories: (1) psychiatric comorbidities and (2) medical complications. Tables 1 and 2 provide high-level summaries of the results.

Psychiatric comorbidities

The study of psychiatric comorbidities can assist with developing models of ED aetiology, conceptualising psychopathology and has relevance for treatment development and outcomes. Given that common psychological factors are observed across psychiatric disorders [ 87 ], it is not surprising that there are high prevalence rates of co-occurring psychiatric conditions with EDs. Comorbidity rates of EDs and other psychiatric conditions are elevated further in ethnic/racial minority groups [ 88 ]. When looking at the evidence from studies conducted with children and young people, one study of children with ARFID found that 53% of the population had a lifetime comorbid psychiatric disorder [ 89 ]. It emerged from the RR that research regarding psychiatric comorbidities generally focussed on the prevalence rates of comorbidities among certain ED subgroups, with some also exploring implications for treatment and ED psychopathology.

Anxiety disorders

Research indicates that EDs and anxiety disorders frequently co-occur [ 8 , 27 ]. The high prevalence rates of anxiety disorders in the general population are also observed in people with EDs; with a large population study finding anxiety disorders were the most frequently comorbid conditions reported [ 8 ]. In a study of women presenting for ED treatment, 65% also met the criteria for at least one comorbid anxiety disorder [ 28 ]. Of note, 69% of those endorsing the comorbidity also reported that the anxiety disorder preceded the onset of the ED [ 28 ]. Another study explored anxiety across individuals with an ED categorised by three weight ranges (individuals whose weight is in the ‘healthy weight’ range, individuals in the ‘overweight’ range and individuals in the ‘obese’ range). While anxiety was elevated across all groups, the authors did note that individuals in the overweight group reported significantly higher rates of anxiety than individuals within the healthy weight group [ 90 ]. One study that explored temperamental factors provided some insight into factors that may mediate this association; anxiety sensitivity (a predictor of anxiety disorders) was associated with greater ED severity among individuals in a residential ED treatment facility [ 29 ]. Further, this association was mediated by a tendency to engage in experiential avoidance—the authors noting that individuals with greater ED symptoms were more likely to avoid distressing experiences [ 29 ].

Generalised anxiety disorder (GAD)

Studies have noted the potential genetic links between EDs and GAD, noting that the presence of one significantly increases the likelihood of the other [ 8 , 30 ]. Further, there appears to be a relationship between the severity of ED behaviours and the co-occurrence of GAD, with comorbidity more likely when fasting and excessive exercise are present, as well as a lower BMI [ 30 ]. The authors noted the particularly pernicious comorbidity of EDs (specifically AN) and GAD may be amplified by the jointly anxiolytic and weight loss effects of food restriction and excessive exercise [ 30 ].

Social anxiety

A meta-analysis of 12 studies found higher rates of social anxiety across all ED diagnoses, with patients with BN demonstrating the highest rate of comorbidity at 84.5%, followed by both BED and AN-BP both at 75% [ 31 ]. High levels of social anxiety were also associated with more severe ED psychopathology [ 31 ] and higher body weight [ 91 ]. This particular comorbidity may also impact on access to treatment for the ED; a large follow-up study of adolescents found that self-reported social phobia predicted not seeking treatment for BN symptoms [ 32 ]. Interestingly, two studies noted that anxiety symptoms improved following psychological treatments that targeted ED symptoms, possibly due to a shared symptom profile [ 29 , 31 ].

Obsessive–compulsive disorder

Similarities between the symptoms of Obsessive–Compulsive Disorder (OCD) and EDs, such as cognitive rigidity, obsessiveness, detail focus, perfectionism and compulsive routines have long been reported in the literature [ 34 ]. Given the symptom overlap, a meta-analysis sought to clarify the lifetime and current (that is, a current diagnosis at the time of data collection) comorbidity rates of OCD and EDs, noting the lifetime comorbidity rate was 18% and current comorbidity rate was 15% [ 33 ]. However, the authors noted that this prevalence may double over longer periods of observation, with some follow-up data demonstrating comorbidity rates of 33% [ 33 ]. Prevalence rates of OCD seemed to be highest among people with AN (lifetime = 19% and current = 14%) compared to other ED subtypes. In addition to the symptom crossover, this RR found evidence of a complex relationship between OCD and EDs, including a potential association between OCD and greater ED severity [ 34 ].

Network analysis found that doubts about simple everyday things and repeating things over and over bridged between ED and OCD symptoms. Further, a pathway was observed between restricting and checking compulsions and food rigidity as well as binge eating and hoarding. However, as the data was cross-sectional, directional inferences could not be made [ 36 ]. An earlier study explored how changes in OCD symptoms impact ED symptoms among an inpatient sample [ 35 ]. As was hypothesised, decreases in OCD symptoms accounted for significant variance in decreases in ED symptoms, and this effect was strongest among ED patients with comorbid OCD. The study also found that irrespective of whether patients had comorbid OCD or not, when ED symptoms improved, so did symptoms of OCD [ 35 ]. The authors concluded that perhaps there is a reciprocal relationship between OCD and ED symptoms, whereby symptoms of both conditions interact in a synergistic, bidirectional manner, meaning that improvement in one domain can lead to improvement in another [ 35 ]. These findings were somewhat supported in a study by Simpson and colleagues (2013), which found exposure and response prevention (a specialised OCD treatment) resulted in a significant reduction in OCD severity, as was expected, and an improvement in ED symptoms. In their study, individuals with BN showed more improvement than those with AN–nevertheless, BMI still increased among those underweight [ 92 ].

Mood disorders

Depression and major depressive disorder (mdd).

This RR also found high levels of comorbidity between major depression and EDs. A longitudinal study of disordered eating behaviours among adolescents found that disordered eating behaviours and depressive symptoms developed concurrently [ 37 ]. Among the sample, over half the adolescent sample had a depressive disorder. Prevalence rates were similar for AN (51.5%) and BN (54%) [ 37 ]. The study also explored the neurological predictors of comorbid depression in individuals with EDs, noting that lower grey matter volumes in the medial orbitofrontal, dorsomedial, and dorsolateral prefrontal cortices predicted the concurrent development of purging and depressive symptoms [ 37 ]. The results suggested that alterations in frontal brain circuits were part of a neural aetiology common to EDs and depression [ 37 ].

This RR found much support for a strong relationship between depression and ED symptomatology. In a study of patients with AN, comorbid MDD was associated with a greater AN symptom severity [ 93 ], and this relationship between the symptoms of MDD and AN was bidirectional in a study of adolescents undergoing treatment for AN, whereby dietary restraint predicted increased guilt and hostility (symptoms of low mood) and fear predicted further food restriction [ 94 ]. Further studies noted the association between BN, BED and NES, with a higher prevalence of depression and more significant depression symptoms [ 95 , 96 , 97 ]. However, other studies have failed to find support for this association–for example, a Swedish twin study found no association between NES and other mental health disorders [ 98 ].

The impact of the relationship between depression and EDs on treatment outcomes was variable across the studies identified by the RR. One study noted the impact of depression on attrition; patients with BN and comorbid depression attending a university clinic had the highest rates of treatment drop-out [ 99 ]. However, in a sample of patients with AN, the comorbidity of depression (or lack of) did not impact treatment outcome and the severity of depression was not associated with changes in ED symptoms [ 100 ]. This finding was supported in another study of inpatients with AN; pre-treatment depression level did not predict treatment outcome or BMI [ 101 ].

Bipolar disorders

Notable comorbidity rates between bipolar disorders (BD) and EDs were reported in the literature reviewed, however evidence about the frequency of this association was mixed. Studies noted comorbidity rates of BD and EDs ranging between 1.9% to as high as 35.8% [ 38 , 39 , 40 ]. In order to better understand the nature of comorbidity, a recent systematic review and meta-analysis found BD (including bipolar 1 disorder and bipolar 2 disorder) and ED comorbidity varied across different ED diagnostic groups (BED—12.5%, BN—7.4%, AN—3.8%) [ 102 ]. However, the authors noted the scant longitudinal studies available, particularly in paediatric samples. An analysis of comorbidity within a sample of patients with BD identified that 27% of participants also met criteria for an ED; 15% had BN, 12% had BED, and 0.2% had AN [ 103 ]. Two other studies noted considerable comorbidity rates of BD; 18.6% for binge eating [ 104 ] and 8.8% for NES [ 105 ]. Some studies suggested the co-occurrence of BD and EDs were seen most in people with AN-BP, BN and BED—all of which share a binge and/or purge symptom profile [ 38 , 106 ]. Specifically, BED and BN were the most common co-occurring EDs with BD [ 40 ], however, these EDs are also the most prevalent in the population. Therefore, it is unclear if this finding is reflective of the increased prevalence of BN and BED, or if it reflects a shared underlying psychopathology between BD and these EDs [ 40 ].

Comorbid ED-BD patients appear to experience increased ED symptom severity, poorer daily and neuropsychological functioning than patients with only a ED or BD diagnosis [ 107 ]. In an effort to understand which shared features in ED-BD relate to quality of life, one study assessed an adult sample with BD [ 108 ]. Binge eating, restriction, overevaluation of weight and shape, purging and driven exercise were associated with poorer clinical outcomes, quality of life and mood regulation [ 108 ]. Additionally, a study of patients undergoing treatment for BD noted patients with a comorbid ED had significantly poorer clinical outcomes and higher scores of depression [ 109 ]. Further, quality of life was significantly lower among patients with comorbid ED-BD [ 109 ]. The comorbidity of ED and BD has implications for intervention and clinical management, as at least one study observed higher rates of alcohol abuse and suicidality among patients with comorbid ED and BD compared to those with BD only [ 40 ].

Personality disorders

This RR identified limited research regarding the comorbidity between personality disorders (PD) and EDs. A meta-analysis sought to summarise the proportion of comorbid PDs among patients with AN and BN [ 41 ]. There was a heightened association between any type of ED and PDs, and this was significantly different to the general population. For specific PDs, the proportions of paranoid, borderline, avoidant, dependant and obsessive–compulsive PD were significantly higher in EDs than in the general population. For both AN and BN, Cluster C PDs (avoidant, dependant and obsessive–compulsive) were most frequent. The authors noted that the specific comorbidity between specific EDs and PDs appears to be associated with common traits—constriction/perfectionism and rigidity is present in both AN and obsessive–compulsive PD (which had a heightened association), as was the case with impulsivity, a characteristic of both BN and borderline PD [ 41 ]. This symptom association was also observed in a study of adolescents admitted to an ED inpatient unit whereby a significant interaction between binge-purge EDs (AN-BP and BN), childhood emotional abuse (a risk factor for PD) and borderline personality style was found [ 110 ].

This comorbidity may be associated with greater patient distress and have implications for patient outcomes [ 41 , 42 ]. Data from a nine-year observational study of individuals with BN reported that comorbidity with a PD was strongly associated with elevated mortality risk [ 111 ]. In terms of treatment outcomes, an RCT compared the one- and three-year treatment outcomes of four subgroups of women with BN, defined by PD complexity; no comorbid PD (health control), personality difficulties, simple PD and complex PD [ 112 ]. At pre-treatment, the complex PD group had greater ED psychopathology than the other three groups. Despite this initial difference, there were no differences in outcomes between groups at one-year and three-year follow up [ 112 ]. The authors suggested this result could be due to the targeting of the shared symptoms of BN and PD by the intervention delivered in this study, and that as ED symptoms improve, so do PD symptoms [ 112 ]. Suggesting that beyond symptom overlap, perhaps some symptoms attributed to the PD are better explained by the ED. This was consistent with Brietzke and colleagues’ (2011) recommendation that for individuals with ED and a comorbid PD, treatment approaches should target both conditions where possible [ 113 ].

Substance use disorders

Comorbid substance use disorders (SUDs) are also often noted in the literature as an issue that complicates treatment and outcomes of EDs [ 114 ]. A meta-analysis reported the lifetime prevalence of EDs and comorbid SUD was 27.9%, [ 43 ] with a lifetime prevalence of comorbid illicit drug use of 17.2% for AN and 18.6% for BN [ 115 ]. Alcohol, caffeine and tobacco were the most frequently reported comorbidities [ 43 ]. Further analysis of SUDs by substance type in a population-based twin sample indicated that the lifetime prevalence of an alcohol use disorder among individuals with AN was 22.4% [ 115 ]. For BN, the prevalence rate was slightly higher at 24.0% [ 115 ].

The comorbidity of SUD is considered far more common among individuals with binge/purge type EDs, evidenced by a meta-analysis finding higher rates of comorbid SUD among patients with AN-BP and BN than AN-R [ 44 ]. This trend was also observed in population data [ 116 ]. Further, a multi-site study found that patients with BN had higher rates of comorbid SUD than patients with AN, BED and Eating Disorder Not Otherwise Specific (EDNOS) (utilised DSM-IV criteria) [ 117 ]. Behaviourally, there was an association between higher frequencies of binge/purge behaviours with high rates of substance use [ 117 ]. The higher risk of substance abuse among patients with binge/purge symptomology was also associated with younger age of binge eating onset [ 118 ]. A study explored whether BN and ED subtypes with binge/purge symptoms predicted adverse outcomes and found that adolescent girls with purging disorder were significantly more likely to use drugs or frequently binge drink [ 119 ]. This association was again observed in a network analysis of college students, whereby there was an association between binge drinking and increased ED cognitions [ 120 ].

Psychosis and schizophrenia

The RR identified a small body of literature with mixed results regarding the comorbidity of ED and psychosis-spectrum symptoms. A study of patients with schizophrenia found that 12% of participants met full diagnostic criteria for NES, with a further 10% meeting partial criteria [ 45 ]. Miotto and colleagues’ (2010) study noted higher rates of paranoid ideation and psychotic symptoms in ED patients than those observed in healthy controls [ 121 ]. However, the authors concluded that these symptoms were better explained by the participant's ED diagnosis than a psychotic disorder [ 121 ]. At a large population level, an English national survey noted associations between psychotic-like experiences and uncontrolled eating, food dominance and potential EDs [ 122 ]. In particular, these associations were stronger in males [ 122 ]. However, the true comorbidity between psychotic disorders and ED remains unclear and further research is needed.

Body dysmorphic disorder

While body image disturbances common to AN, BN and BED are primarily related to weight and shape concerns, individuals with body dysmorphic disorder (BDD) have additional concerns regarding other aspects of their appearance, such as facial features and skin blemishes [ 46 , 123 ]. AN and BDD share similar psychopathology and both have a peak onset period in adolescence, although BDD development typically precedes AN [ 46 ]. The prevalence rates of BDD among individuals with AN are variable. In one clinical sample of female AN patients, 26% met BDD diagnostic criteria [ 124 ]. However, much higher rates were observed in another clinical sample of adults with AN, where 62% of patients reported clinically significant 'dysmorphic concern' [ 125 ].

As the RR has found with other mental health comorbidities, BDD contributes to greater symptom severity in individuals with AN, making the disorder more difficult to treat. However, some research suggested that improved long-term outcomes from treatments for AN are associated with the integration of strategies that address dysmorphic concerns [ 124 , 126 ]. However, there remains little research on the similarities, differences and co-occurrence of BDD and AN, and with even less research on the cooccurrence of BDD and other EDs.

Neurodevelopmental disorders

Attention deficit hyperactivity disorder

Several studies noted the comorbidity between Attention Deficit Hyperactivity Disorder (ADHD) and EDs. A systematic review found moderate evidence for a positive association between ADHD and disordered eating, particularly between overeating and ADHD [ 47 ]. The impulsivity symptoms of ADHD were particularly associated with BN for all genders, and weaker evidence was found for the association between hyperactivity and restrictive EDs (AN and ARFID) for males, but not females [ 47 ]. Another meta-analysis reported a two-fold increased risk of ADHD in individuals with an ED [ 48 ] and studies have noted particularly strong associations between ADHD and BN [ 49 , 50 ]. In a cohort of adults with a diagnosis of an ED, 31.3% had a 'possible' ADHD [ 127 ]. Another study considered sex differences; women with ADHD had a significantly higher lifetime prevalence of both AN and BN than women without ADHD [ 128 ]. Further, the comorbidity rates for BED were considerably higher among individuals with ADHD for both genders [ 128 ].

Further evidence for a significant association between ADHD and EDs was reported in a population study of children [ 51 ]. Results revealed that children with ADHD were more like to experience an ED or binge, purge, or restrictive behaviours above clinical threshold [ 51 ]. Another study of children with ADHD considered gender differences; boys with ADHD had a greater risk of binge eating than girls [ 129 ]. However, the study found no significant difference in AN's prevalence between ADHD and non-ADHD groups. Further, among patients attending an ED specialist clinic, those with comorbid ADHD symptoms had poorer outcomes at one-year follow-up [ 130 ].

Autism spectrum disorder

There is evidence of heightened prevalence rates of autism spectrum disorder (ASD) among individuals with EDs. A systematic review found an average prevalence of ASD with EDs of 22.9% compared with 2% observed in the general population [ 52 ]. With regards to AN, several studies have found symptoms of ASD to be frequently exhibited by patients with AN [ 53 , 54 ]. An assessment of common phenomena between ARFID and ASD in children found a shared symptom profile of eating difficulties, behavioural problems and sensory hypersensitivity beyond what is observed in typically developing children (the control group) [ 55 ]. While research in this area is developing, the findings indicated these comorbidities would likely have implications for the treatment and management of both conditions [ 55 ].

Post traumatic stress disorder

Many individuals with EDs report historical traumatic experiences, and for a proportion of the population, symptoms of post traumatic stress disorder (PTSD). A broad range of prevalence rates between PTSD and EDs have been reported; between 16.1–22.7% for AN, 32.4–66.2% for BN and 24.02–31.6% for BED [ 56 ]. A review noted self-criticism, low self-worth, guilt, shame, depression, anxiety, emotion dysregulation, anger and impulsivity were linked to the association between EDs and trauma [ 57 ]. It was suggested that for individuals with trauma/PTSD, EDs might have a functional role to manage PTSD symptoms and reduce negative affect [ 57 ]. Further, some ED behaviours such as restriction, binge eating, and purging may be used to avoid hyperarousal, in turn maintaining the association between EDs and PTSD [ 57 ].

Few studies have explored the impact of comorbid PTSD on ED treatment outcomes. A study of inpatients admitted to a residential ED treatment service investigated whether PTSD diagnosis at admission was associated with symptom changes [ 56 ]. Cognitive and behavioural symptoms related to the ED had decreased at discharge, however, they increased again at six-month follow up. In contrast, while PTSD diagnosis was associated with higher baseline ED symptoms, it was not related to symptom change throughout treatment or treatment dropout [ 56 ]. Given previous research identified that PTSD and EDs tend to relate to more complex courses of illness, greater rates of drop out and poorer outcomes, a study by Brewerton and colleagues [ 131 ], explored the presence of EDs in patients with PTSD admitted to a residential setting. Results showed that patients with PTSD had significantly higher scores of ED psychopathology, as well as depression, anxiety and quality of life. [ 131 ]. Further, those with PTSD had a greater tendency for binge-type EDs.

Suicidality

Suicide is one of the leading causes of death for individuals with EDs [ 58 ]. In a longitudinal study of adolescents, almost one quarter had attempted suicide, and 65% reported suicidal ideation within the past 6 months [ 37 ]. EDs are a significant risk factor for suicide, with some evidence suggesting a genetic association between suicide risk and EDs [ 59 , 60 ]. This association was supported in the analysis of Swedish population registry data, which found that individuals with a sibling with an ED had an increased risk of suicide attempts with an odds ratio of 1.4 (relative cohort n  = 1,680,658) [ 61 ]. For suicide attempts, this study found an even higher odds ratio of 5.28 (relative cohort n  = 2,268,786) for individuals with an ED and 5.39 (relative cohort n  = 1,919,114) for death by suicide [ 61 ]. A comparison of individuals with AN and BN indicated that risk for suicide attempts was higher for those with BN compared to AN [ 61 ]. However, the opposite was true for death by suicide; which was higher in AN compared to BN [ 61 ]. This result is consistent with the findings of a meta-analysis—the incidence of suicide was higher among patients with AN compared to those with BN or BED [ 62 ].

The higher incidence of suicide in adults with AN [ 132 ] is potentially explained by the findings from Guillaume and colleagues (2011), which suggested that comparative to BN, AN patients are more likely to have more serious suicide attempts resulting in a higher risk of death [ 133 ]. However, death by suicide remains a significant risk for both diagnoses. As an example, Udo and colleagues (2019) study reported that suicide attempts were more common in those with an AN-BP subtype (44.1%) than AN-R (15.7%), or BN (31.4%) [ 134 ]. Further, in a large cohort of transgender college students with EDs, rates of past-year suicidal ideation (a significant risk factor for suicide attempts) was 75.2%, and suicide attempts were 74.8%, significantly higher than cisgender students with EDs and transgender students without EDs [ 135 ]. The RR found that the risk of suicidal ideation and behaviour was associated with ED diagnosis and the presence of other comorbidities. Among a community-based sample of female college students diagnosed with an ED, 25.6% reported suicidal ideation, and this was positively correlated with depression, anxiety and purging [ 136 ]. In support of this evidence, Sagiv and Gvion (2020) proposed a dual pathway model of risk of suicide attempt in individuals with ED, which implicates trait impulsivity and comorbid depression [ 137 ]. In two large transdiagnostic ED patient samples, suicidal ideation was associated with different aspects of self-image between ED diagnoses. For example, suicidal ideation was associated with higher levels of self-blame among individuals with BED, while among patients with AN and OSFED, increased suicidal ideation was associated with a lack of self-love [ 138 , 139 ].

Anorexia nervosa

Amongst adults with AN, higher rates of suicide have been reported amongst those with a binge-purge subtype (25%) than restrictive subtype (8.65%) [ 58 , 140 ]. Further, comorbid depression and prolonged starvation were strongly associated with elevated suicide attempts for both subtypes [ 58 , 140 ]. In another study, the risk of attempted suicide was associated with depression, but it was moderated by hospital treatment [ 93 ]. Further, suicidal ideation was related to depression. A significant 'acquired' suicide risk in individuals with AN has been identified by Selby et al. (2010) through an increased tolerance for pain and discomfort resultant from repeated exposure to painful restricting and purging behaviours [ 141 ].

Bulimia nervosa

Further research among individuals diagnosed with BN found an increased level of suicide risk [ 142 ]. Results from an extensive study of women with BN indicated that the lifetime prevalence of suicide attempts in this cohort was 26.9% [ 143 ]. In one study of individuals diagnosed with severe BN, 60% of deaths were attributed to suicide [ 144 ]. The mean age at the time of death was 29.6 years, and predictive factors included previous suicide attempts and low BMI. Further, in a sample of children and adolescents aged 7 to 18 years, higher rates of suicidal ideation were associated with BN, self-induced vomiting and a history of trauma [ 12 ].

A large population-based study of adolescents and adults explored the frequency and correlates of suicidal ideation and attempts in those who met the criteria for BN [ 145 ]. Suicidal ideation was highest in adolescents with BN (53%), followed by BED (34.4%), other non-ED psychopathology (21.3%) or no psychopathology (3.8%). A similar trend was observed for suicide plans and attempts [ 145 ]. However, for adults, suicidality was more prevalent in the BN group compared to no psychopathology, but not statistically different to the AN, BED or other psychopathology groups [ 145 ].

Consistent with Crow and colleagues’ (2014) results, in a sample of women with BN, depression had the strongest association with lifetime suicide attempts [ 146 ]. There were also associations between identity problems, cognitive dysregulation, anxiousness, insecure attachment and lifetime suicide attempts among the sample. Depression was the most pertinent association, suggesting that potential comorbid depression should be a focus of assessment and treatment among individuals with BN due to the elevated suicide risk for this group [ 146 ]. Insecure attachment is associated with childhood trauma, and a systematic review found that suicide attempts in women with BN were significantly associated with childhood abuse and familial history of EDs [ 58 ].

Binge eating disorder

The RR found mixed evidence for the association between suicidal behaviour and BED. A meta-analysis found no suicides for patients with BED [ 62 ]. However, evidence from two separate large national surveys found that a significant proportion of individuals who had a suicide attempt also had a diagnosis of BED [ 134 , 147 ].

Non-suicidal self injury

Non-suicidal self-injury (NSSI), broadly defined, is the intentional harm inflicted to one’s body without intent to die [ 148 ]. Recognising NSSI is often a precursor for suicidal ideation and behaviour [ 149 ], together with the already heightened mortality rate for EDs, several studies have examined the association between EDs and NSSI. Up to one-third of patients with EDs report NSSI at some stage in their lifetime, with over one quarter having engaged in NSSI within the previous year [ 63 ]. Similarly, a cohort study [ 148 ] found elevated rates of historical NSSI amongst patients with DSM-IV EDs; specifically EDNOS (49%), BN (41%) and AN (26%). In a Spanish sample of ED patients, the most prevalent form of NSSI was banging (64.6%) and cutting (56.9%) [ 63 ].

Further research has explored the individual factors associated with heightened rates of NSSI. Higher levels of impulsivity among patients with EDs have been associated with concomitant NSSI [ 64 ]. This was demonstrated in a longitudinal study of female students, whereby NSSI preceded purging, marking it a potential risk factor for ED onset [ 65 ]. In a study of a large clinical sample of patients with EDs and co-occurring NSSI, significantly higher levels of emotional reactivity were observed [ 150 ]. The highest levels of emotional reactivity were reported by individuals with a diagnosis of BN, who were also more likely to engage in NSSI than those with AN [ 150 ]. In Olatunji and colleagues’ (2015) cohort study, NSSI was used to regulate difficult emotions, much like other ED behaviours. NSSI functioning as a means to manage negative affect associated with EDs was further supported by Muehlenkamp and colleagues’ [ 66 ] study exploring the risk factors in inpatients admitted for an ED. The authors found significant differences in the prevalence of NSSI across ED diagnoses, although patients with binge/purge subtype EDs were more likely to engage in poly-NSSI (multiple types of NSSI). Consistent with these findings, a study of patients admitted to an ED inpatient unit found that 45% of patients displayed at least one type of NSSI [ 151 ]. The function of NSSI among ED patients was explored in two studies, one noting that avoiding or suppressing negative feelings was the most frequently reported reason for NSSI [ 151 ]. The other analysed a series of interviews and self-report questionnaires and found patients with ED and comorbid Borderline Personality Disorder (BPD) engaged in NSSI as a means of emotion regulation [ 152 ].

Medical comorbidities

The impact of EDs on physical health and the consequential medical comorbidities has been a focus of research. Many studies reported medical comorbidities resulting from prolonged malnutrition, as well as excessive exercise, binging and purging behaviours.

Cardiovascular complications

As discussed above, although suicide is a significant contributor to the mortality rate of EDs, physical and medical complications remain the primary cause of death, particularly in AN, with a high proportion of deaths thought to result from cardiovascular complications [ 153 ]. AN has attracted the most research focus given its increased risk of cardiac failure due to severe malnutrition, dehydration and electrolyte imbalances [ 67 ].

Cardiovascular complications in AN can be divided by conduction, structural and ischemic diseases. A review found that up to 87% of patients experience cardiovascular compromise shortly following onset of AN [ 153 ]. Within conduction disease, bradycardia and QT prolongation occur at a high frequency, largely due to low body weight and resultant decreased venous return to the heart. Whereas, atrioventricular block and ventricular arrhythmia are more rare [ 153 ]. Various structural cardiomyopathies are observed in AN, such as low left ventricular mass index (occurs frequently), mitral prolapse and percardial effusion (occurs moderately). Ischemic diseases such as dyslipidemia or acute myocardial infarction are more rare.

Another review identified cardiopulmonary abnormalities that are frequently observed in AN; mitral valve prolapse occurred in 25% of patients, sinus bradycardia was the most common arrhythmia, and pericardial effusion prevalence rates ranged from 15 to 30%. [ 68 ] Sudden cardiac death is thought to occur due to increased QT interval dispersion and heart rate variability. [ 68 ] A review of an inpatient database in a large retrospective cohort study found that coronary artery disease (CAD) was lower in AN patients than the general population (4.4% and 18.4%, respectively). Consistent with trends in the general population, the risk of cardiac arrest, arrhythmias and heart failure was higher in males with AN than females with AN [ 69 ].

Given that individuals with AN have compromised biology, may avoid medical care, and have higher rates of substance use, research has examined cancer incidence and prognosis among individuals with AN. A retrospective study noted higher mortality from melanoma, cancers of genital organs and cancers of unspecified sites among individuals with AN, however, there was no statistically significant difference compared to the general population [ 70 ]. No further studies of cancer in EDs were identified.

Gastrointestinal disorders

The gastrointestinal (GI) system plays a pivotal role in the development, maintenance, and treatment outcomes for EDs, with changes and implications present throughout the GI tract. More than 90% of AN patients report fullness, early satiety, abdominal distention, pain and nausea [ 68 ]. Although it is well understood that GI system complaints are complicated and exacerbated by malnutrition, purging and binge eating [ 154 , 155 ], the actual cause of the increased prevalence of GI disorders and their contribution to ED maintenance remain poorly understood.

To this end, a review aimed to determine the GI symptoms reported in two restrictive disorders (AN and ARFID), as well as the physiologic changes as a result of malnutrition and function of low body weight and the contribution of GI diseases to the disordered eating observed in AN and ARFID [ 156 ]. The review found mixed evidence regarding whether GI issues were increased in patients with AN and ARFID. This was partly due to the relatively limited amount of research in this area and mixed results across the literature. The review noted that patients with AN and ARFID reported a higher frequency of symptoms of gastroparesis. Further, there was evidence for a bidirectional relationship between AN and functional gastrointestinal disorders (FGIDs) contributing to ongoing disordered eating. The review found that GI symptoms observed in EDs develop due to (1) poorly treated medical conditions with GI-predominant symptoms, (2) the physiological and anatomical changes that develop due to malnutrition or (3) FGIDs.

There was a high rate of comorbidity (93%) between ED and FGIDs, including oesophageal, bowel and anorectal disorders, in a patient sample with AN, BN and EDNOS [ 157 ]. A retrospective study investigating increased rates of oesophageal cancer in individuals with a history of EDs could not conclude that risk was associated with purging over other confounding factors such as alcohol abuse and smoking [ 158 ].

Given that gut peptides like ghrelin, cholecystokinin (CCK), peptide tyrosine (PYY) and glucagon-like peptide 1 (GLP-1) are known to influence food intake, attention has focussed on the dysregulation of gut peptide signalling in EDs [ 159 ]. A review aimed to discuss how these peptides or the signals triggered by their release are dysregulated in EDs and whether they are normalised following weight restoration or weight loss (in the case of people with higher body weight) [ 159 ]. The results were inconsistent, with significant variability in peptide dysregulation observed across EDs [ 159 ]. A systematic review and meta-analysis explored whether ghrelin is increased in restrictive AN. The review found that all forms of ghrelin were raised in AN’s acute state during fasting [ 160 ]. In addition, the data did not support differences in ghrelin levels between AN subtypes [ 160 ]. Another study examined levels of orexigenic ghrelin and anorexigenic peptide YY (PYY) in young females with ARFID, AN and healthy controls (HC) [ 161 ]. Results demonstrated that fasting and postprandial ghrelin were lower in ARFID than AN, but there was no difference between ARFID and AN for fasting and postprandial PYY [ 161 ].

Oesophageal and gastrointestinal dysfunction have been observed in patients with AN and complicate nutritional and refeeding interventions [ 155 ]. Findings from a systematic review indicated that structural changes that occurred in the GI tract of patients with AN impacted their ability to swallow and absorb nutrients [ 162 ]. Interestingly, no differences in the severity of gastrointestinal symptoms were observed between AN-R and AN-BP subtypes [ 155 ].

A systematic review of thirteen studies aimed to identify the most effective treatment approaches for GI disorders and AN [ 163 ]. An improvement in at least one or more GI symptoms was reported in 11 of the 13 studies, with all studies including nutritional rehabilitation, and half also included concurrent psychological treatment [ 163 ]. Emerging evidence on ED comorbidity with chronic GI disorders suggested that EDs are often misdiagnosed in children and adolescents due to the crossover of symptoms. Therefore, clinicians treating children and adolescents for GI dysfunction should be aware of potential EDs and conduct appropriate screening [ 164 ]. There has been an emerging focus on the role of the gut microbiome in the regulation of core ED symptoms and psychophysiology. Increased attention is being paid to how the macronutrient composition of nutritional rehabilitation should be considered to maximise treatment outcomes. A review found that high fibre consumption in addition to prebiotic and probiotic supplementation helped balance the gut microbiome and maintained the results of refeeding [ 165 ].

Bone health

The RR found evidence for bone loss/poor bone mineral density (BMD) and EDs, particularly in AN. The high rates of bone resorption observed in patients with AN is a consequence of chronic malnutrition leading to osteoporosis (weak and brittle bones), increased fracture risk and scoliosis [ 166 ]. The negative impacts of bone loss are more pronounced in individuals with early-onset AN when the skeleton is still developing [ 67 ] and among those who have very low BMI [ 71 ], with comorbidity rates as high as 46.9% [ 71 ]. However, lowered BMD was also observed among patients with BN [ 72 ].

A review [ 167 ] explored the prevalence and differences in pathophysiology of osteoporosis and fractures in patients with AN-R and AN-BP. AN-R patients had a higher prevalence of osteoporosis, and AN-BP patients had a higher prevalence of osteopenia (loss of BMD) [ 167 ]. Further, the authors noted the significant increase in fracture risk that starts at disease onset and lasts throughout AN, with some evidence that risk remains increased beyond remission and recovery [ 167 ]. Findings from a longitudinal study of female patients with a history of adolescent AN found long-term bone thinning at five and ten-year follow-up despite these patients achieving weight restoration [ 168 ].

Given this, treatment to increase BMD in individuals with AN has been the objective of many pharmacotherapy trials, mainly investigating the efficacy of hormone replacement [ 169 , 170 ]. Treatments include oestrogen and oral contraceptives [ 169 , 170 , 171 , 172 ]; bisphosphonates [ 169 , 173 ]; other hormonal treatment [ 174 , 175 , 176 , 177 ] and vitamin D [ 178 ]. However, the outcomes of these studies were mixed.

Refeeding syndrome

Nutritional rehabilitation of severely malnourished individuals is central to routine care and medical stabilisation of patients with EDs [ 179 ]. Within inpatient treatment settings, reversing severe malnutrition is achieved using oral, or nasogastric tube feeding. However, following a period of starvation, initiating/commencing feeding has been associated with ‘refeeding syndrome’ (RFS), a potentially fatal electrolyte imbalance caused by the body's response to introducing nutritional restoration [ 180 , 181 ]. The studies identified in the RR focused predominantly on restrictive EDs/on this population group—results regarding RFS risk were mixed [ 73 ].

A retrospective cohort study of inpatients diagnosed with AN with a very low BMI implemented a nasogastric feeding routine with vitamin, potassium and phosphate supplementation [ 182 ]. All patients achieved a significant increase in body weight. None developed RFS [ 182 ], suggesting that even with extreme undernutrition, cautious feeding within a specialised unit can be done safely without RFS. For adults with AN, aminotransferases are often high upon admission, however are normalised following four weeks of enteral feeding [ 183 , 184 ]. Further, the RR identified several studies demonstrating the provision of a higher caloric diet at intake to adolescents with AN led to faster recoveries and fewer days in the hospital with no observed increased risk for RFS [ 75 , 76 , 77 ]. These findings were also noted in a study of adults with AN [ 179 ].

However, the prevalence of RFS among inpatients is highly variable, with one systematic review noting rates ranging from 0 to 62% [ 74 ]. This variability was largely a reflection of the different definitions of RFS used across the literature [ 74 ]. A retrospective review of medical records of patients with AN admitted to Intensive Care Units (ICUs) aimed to evaluate complications, particularly RFS, that occurred during the ICU stay and the impact of these complications on treatment outcomes [ 185 ]. Of the 68 patients (62 female), seven developed RFS (10.3%) [ 185 ].

Although easily detectable and treatable, hypophosphatemia (a low serum phosphate concentration) may lead to RFS which is the term used to describe severe fluid and electrolyte shifts that can occur when nutrition support is introduced after a period of starvation. Untreated hypophosphatemia may lead to characteristic signs of the RFS such as respiratory failure, heart failure, and seizures [ 76 , 179 , 186 , 187 , 188 ]. A retrospective case–control study of inpatients with severe AN identified [ 189 ]. A retrospective study of AN and atypical AN patients undergoing refeeding found that the risk of hypophosphatemia was associated with a higher level of total weight loss and recent weight loss rather than the patient’s weight at admission [ 190 ]. The safe and effective use of prophylactic phosphate supplementation during refeeding was supported by the results from Agostino and colleagues’ chart review study [ 191 ], where 90% of inpatients received supplementation during admission.

Higher calorie refeeding approaches are considered safe in most cases, however the steps necessitated to monitor health status are costly to health services [ 192 ]. The most cost-effective approach would likely involve prophylactic electrolyte supplementation in addition to high calorie refeeding, which would decrease the need for daily laboratory monitoring as well as shortening hospital stays [ 75 , 191 , 192 ]. A systematic review noted that much of the research regarding refeeding, particularly in children and young people, has been limited by small sample sizes, single-site studies and heterogeneous designs [ 181 ]. Further, the differing definitions of RFS, recovery, remission and outcomes leading to variable results. While RFS appears safe for many people requiring feeding, the risk and benefits of it are unclear [ 193 ] due to the limited research on this topic. Following current clinical practice guidelines on the safe introduction of nutrition is recommended.

Metabolic syndrome

Metabolic syndrome refers to a group of factors that increase risks for heart disease, diabetes, stroke and other related conditions [ 194 ]. Metabolic syndrome is conceptualised as five key criteria; (1) elevated waist circumference, (2) elevated triglyceride levels, (3) reduced HDL-C, (4) elevated blood pressure and (5) elevated fasting glucose. The binge eating behaviours exhibited in BN, BED and NES have been linked to the higher rates of metabolic syndrome observed in these ED patients [ 78 , 195 ].

An analysis of population data of medical comorbidities with BED noted the strongest associations were with diabetes and circulatory systems, likely indexing components of metabolic syndrome [ 196 ]. While type 1 diabetes is considered a risk factor for ED development, both BN and BED have increased risk for type 2 diabetes [ 78 ]. A 16-year observation study found that the risk of type 2 diabetes was significantly increased in male patients with BED compared to the community controls [ 78 ]. By the end of the observation period, 33% of patients with BED had developed type 2 diabetes compared to 1.7% of the control group. The prevalence of type 2 diabetes among patients with BN was also slightly elevated at 4.4% [ 78 ]. Importantly, the authors were not able to control for BMI in this study. In another study, BED was the most prevalent ED in a cohort of type 2 diabetes patients [ 197 ]. Conversely, the prevalence of AN among patients with type 2 diabetes is significantly lower, with a review of national data reporting comorbidity rates to be 0.06% [ 198 ].

Metabolic dysfunction was observed in a relatively large sample of individuals with NES, including metabolic syndrome and type 2 diabetes, with women reporting slightly higher rates (13%) than men (11%) [ 199 ]. In another group of adults with type 2 diabetes, 7% met the diagnostic criteria for NES [ 200 ]. These findings suggested a need for increased monitoring and treatment of type 2 diabetes in individuals with EDs, particularly BED and NES. Another study found BED had a significant impact on metabolic abnormalities, including elevated cholesterol and poor glycaemic control [ 201 ].

The RR identified one intervention study, which examined an intervention to address medical comorbidities associated with BN and BED [ 195 ]. The study compared cognitive behaviour therapy (CBT) to an exercise and nutrition intervention to increase physical fitness, decrease body fat percentage and reduce the risk for metabolic syndrome. While the exercise intervention improved participants' physical fitness and body composition, neither group reduced cardiovascular risk at one-year follow-up [ 195 ].

Oral health

Purging behaviour, particularly self-induced vomiting, has been associated with several oral health and gastrointestinal dysfunctions in patients with EDs. A case–control study of ED patients with binge/purge symptomology found that despite ED patients reporting an increased concern for dental issues and engaging in more frequent brushing, their oral health was poorer than controls. [ 79 ] Further, a systematic review and meta-analysis aimed to explore whether EDs increase the risk of tooth erosion [ 80 ]. The analysis found that patients with EDs had more risk of dental erosion, especially among those who self-induced vomiting [ 80 ]. These findings were also found in a large cohort study, where the increased risk for BN was associated with higher rates of dental erosion but not dental cavities [ 81 ].

However, a systematic review of 10 studies suggested that poor oral health may be common among ED patients irrespective of whether self-induced vomiting forms part of their psychopathology [ 202 ]. One study reported that AN-R patients had poorer oral health outcomes and tooth decay than BN patients [ 203 ]. Two studies identified associations between NES and poor oral health, including higher rates of missing teeth, periodontal disease [ 204 , 205 ]. Another study of a group of patients with AN, BN and EDNOS, demonstrated the impact of ED behaviours on dental soft tissue, whereby 94% of patients had oral mucosal lesions, and 3% were found to have dental erosion [ 206 ].

Vitamin deficiencies

The prolonged periods of starvation, food restriction (of caloric intake and/or food groups), purging and excessive exercise observed across the ED spectrum have detrimental impacts on micronutrient balances [ 207 ]. The impact of prolonged vitamin deficiencies in early-onset EDs can also impair brain development, substantially reducing neurocognitive function in some younger patients even after weight restoration [ 82 ]. Common micronutrient deficiencies include calcium, fat soluble vitamins, essential fatty acids selenium, zinc and B vitamins [ 183 ]. One included study looked at prevalence rates of cerebral atrophy and neurological conditions, specifically Wernicke's encephalopathy in EDs and found that these neurological conditions were very rare in people with EDs [ 208 ].

Cognitive functioning

The literature included in RR regarding the cognitive changes in ED patients with AN following weight gain was sparse. It appears that some cognitive functions affected by EDs recover following nutritional restoration, whereas others persist. Cognitive functions, such as flexibility, central coherence, decision making, attention, processing speed and memory, are hypothesised to be impacted by, and influence the maintenance of EDs. A systematic review explored whether cognitive functions improved in AN following weight gain [ 83 ]. Weight gain appeared to be associated with improved processing speed in children and adolescents. However, no improvement was observed in cognitive flexibility following weight gain. Further, the results for adults were inconclusive [ 83 ].

Reproductive health

Infertility and higher rates of poor reproductive health are strongly associated with EDs, including miscarriages, induced abortions, obstetric complications, and poorer birth outcomes [ 84 , 85 ]. Although amenorrhea is a known consequence of AN, oligomenorrhea (irregular periods) was common among individuals with BN and BED [ 86 ]. A twin study found women diagnosed with BN and BED were also more likely to have poly cystic ovarian syndrome (PCOS), leading to menstrual irregularities [ 209 ]. The prevalence of lifetime amenorrhea in this sample was 10.4%, and lifetime oligomenorrhea was 33.7%. An epidemiological study explored the association of premenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD) in women with BN and BED and found prevalence rates as high as 42.4% for PMS and 4.2% for PMDD [ 210 ].

Given the increased rates of menstrual irregularities and issues, questions have been raised regarding whether this complication is reversed or improves with recovery. A review of five studies monitoring reproductive functions during recovery over a 6- to 18-year follow up period [ 211 ] noted no significant difference between the pooled odds of childbirth rates between the AN and general population—demonstrating that if patients undergo treatment for AN, achieve weight restoration, and continue to maintain wellness, reproductive functions can renormalise [ 211 ].

An observational study of women with AN, BN or EDNOS found higher rates of low birth rate, pre-term deliveries, caesarean deliveries, and intrauterine growth restrictions [ 84 ]. Increased caesarean delivery was also observed in a large cohort of women diagnosed with BED [ 212 ]. However, these women had higher birth weight babies [ 212 ]. Further, women with comorbid ED and epilepsy were found to have an increased risk of pregnancy-related comorbidities, including preeclampsia (gestational hypertension and signs of damage to the liver and kidneys ) , gestational diabetes and perinatal depression [ 213 ].

The results from this review identified that the symptomology and outcomes of EDs are impacted by both psychiatric and medical factors. Further, EDs have a mortality rate substantially higher than the general population, with a significant proportion of those who die from an ED dying by suicide or as a result of severe medical complications.

This RR noted high rates of psychiatric and medical comorbidities in people with EDs, with comorbidities contributing to increased ED symptom severity, maintenance of some ED behaviours, compromised functioning, and adverse treatment outcomes. Evidence suggested that early identification and management of psychiatric and medical comorbidities in people with an ED may improve response to treatment and outcomes [ 29 , 35 , 83 ].

EDs and other psychiatric conditions often shared symptoms and high levels of psychopathology crossover were noted. The most prevalent psychiatric comorbidities were anxiety disorders, mood disorders and substance use disorders [ 8 , 100 , 119 ]. perhaps unsurprising given the prevalence of these illnesses in the general population. Of concern is the elevated suicide rate noted across the ED spectrum, the highest observed in AN [ 58 , 140 , 149 ]. For people with AN, suicide attempts were mostly associated with comorbid mood and anxiety disorders [ 136 ]. The review noted elevated rates of NSSI were particularly associated with binge/purge subtype EDs [ 150 ], impulsivity and emotional dysregulation (again, an example of psychopathological overlap).

With regards to PDs, studies were limited to EDs with binge-purge symptomology. Of those included, the presence of a comorbid personality disorder and ED was associated with childhood trauma [ 110 ] and elevated mortality risk [ 111 ]. There appeared to be a link between the clinical characteristics of the ED (e.g., impulsivity, rigidity) and the comorbid PD (cluster B PDs were more associated with BN/BED and cluster C PDs were more associated with AN). There was mixed (albeit limited) evidence regarding the comorbidity between EDs and psychosis and schizophrenia, with some studies noting an association between EDs and psychotic experiences [ 45 ]. Specifically, there was an association between psychotic experiences and uncontrolled eating and food dominance, which were stronger in males [ 122 ]. In addition, the review noted the association between EDs and neurodevelopmental disorders-specifically ADHD—was associated with features of BN and ASD was more prevalent among individuals with AN [ 53 , 54 ] and ARFID [ 55 ].

EDs are complicated by medical comorbidities across the neuroendocrine, skeletal, nutritional, gastrointestinal, dental, and reproductive systems that can occur alongside, or result from the ED. The RR noted mixed evidence regarding the effectiveness and safety of enteral feeding [ 180 , 181 ], with some studies noting that RFS could be safely managed with supplementation [ 191 ]. Research also described the impacts of restrictive EDs on BMD and binge eating behaviour on metabolic disorders [ 78 , 195 ]. Purging behaviours, particularly self-induced vomiting [ 79 ], were found to increase the risk of tooth erosion [ 81 ] and damage to soft tissue within the gastrointestinal tract [ 206 ]. Further, EDs were associated with a range of reproductive health issues in women, including infertility and birth complications [ 84 ].

Whilst the RR achieved its aim of synthesising a broad scope of literature, the absence of particular ED diagnoses and other key research gaps are worth noting. A large portion of the studies identified focused on AN, for both psychiatric and medical comorbidities. This reflects the stark lack of research exploring the comorbidities for ARFID, NES, and OSFED compared to that seen with AN, BN and BED. There were no studies identified exploring the psychiatric and medical comorbidities of Pica. These gaps could in part be due to the timeline utilised in the RR search strategy, which included the transition from DSM-IV to DSM-5. The update in the DSM had significant implications for psychiatric diagnosis, with the addition of new disorders (such as Autism Spectrum Disorder and various Depressive Disorders), reorganisation (for example, moving OCD and PTSD out of anxiety disorders and into newly defined chapters) and changes in diagnostic criteria (including for AN and BN, and establishing BED as a discrete disorder). Although current understanding suggests EDs are more prevalent in females, research is increasingly demonstrating that males are not immune to ED symptoms, and the RR highlighted the disproportionate lack of male subjects included in recent ED research, particularly in the domain of psychiatric and medical comorbidities.

As the RR was broad in scope and policy-driven in intent, limitations as a result of this methodology ought to be considered. The RR only considered ‘Western’ studies, leading to the potential of important pieces of work not being included in the synthesis. In the interest of achieving a rapid synthesis, grey literature, qualitative and theoretical works, case studies or implementation research were not included, risking a loss of nuance in developing fields, such as the association and prevalence of complex/developmental trauma with EDs (most research on this comorbidity focuses on PTSD, not complex or developmental trauma) or body image dissatisfaction among different gender groups. No studies regarding the association between dissociative disorders and EDs were included in the review. However, dissociation can co-occur with EDs, particularly AN-BP and among those with a trauma history [ 214 ]. Future studies would benefit from exploring this association further, particularly as trauma becomes more recognised as a risk factor for ED development.

The review was not designed to be an exhaustive summary of all medical comorbidities. Thus, some areas of medical comorbidity may not be included, or there may be variability in the level of detail included (such as, limited studies regarding the association between cancer and EDs). Studies that explored the association between other autoimmune disorders (such as Type 1 Diabetes, Crohn’s disease, Addison’s disease, ulcerative colitis, and coeliac disease) and EDs [ 215 , 216 ] were not included. Future reviews and research should examine the associations between autoimmune disorders and the subsequent increased risk of EDs, and likewise, the association between EDs and the subsequent risk of autoimmune disorders.

An important challenge for future research is to explore the impact of comorbidity on ED identification, development and treatment processes and outcomes. Insights could be gained from exploring shared psychiatric symptomology (i.e., ARFID and ASD, BN/BED and personality disorders, and food addiction). Particularly in disorders where the psychiatric comorbidity appears to precede the ED diagnosis (as may be the case in anxiety disorders [ 28 ]) and the unique physiological complications of these EDs (e.g., the impact of ARFID on childhood development and growth). Further, treatment outcomes would benefit from future research exploring the nature of the proposed reciprocal nature between EDs and comorbidities, particularly in those instances where there is significant shared psychopathology, or the presence of ED symptoms appears to exacerbate the symptoms of the other condition—and vice versa.

The majority of research regarding the newly introduced EDs has focused on understanding their aetiology, psychopathology, and what treatments demonstrate efficacy. Further, some areas included in the review had limited included studies, for example cancer and EDs. Thus, in addition to the already discussed need for further review regarding the association between EDs and autoimmune disorders, future research should explore the nature and prevalence of comorbidity between cancers and EDs. There was variability regarding the balance of child/adolescent and adult studies across the various comorbidities. Some comorbidities are heavily researched in child and adolescent populations (such as refeeding syndrome) and others there is stark child and adolescent inclusion, with included studies only looking at adult samples. Future studies should also address specific comorbidities as they apply to groups underrepresented in current research. This includes but is not limited to gender, sexual and racial minorities, whereby prevalence rates of psychiatric comorbidities are elevated. [ 88 ] In addition, future research would benefit from considering the nature of psychiatric and medical comorbidity for subthreshold and subclinical EDs, particularly as it pertains to an opportunity to identify EDs early within certain comorbidities where ED risk is heightened.

This review has identified the psychiatric and medical comorbidities of EDs, for which there is a substantial level of literature, as well as other areas requiring further investigation. EDs are associated with a myriad of psychiatric and medical comorbidities which have significant impacts on the symptomology and outcomes of an already difficult to treat, and burdensome illness.

Availability of data and materials

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Abbreviations

Anorexia nervosa—restricting type

Anorexia nervosa—binge-purge type

Avoidant restrictive food intake disorder

Body mass index

Borderline personality disorder

Diagnostic and statistical manual of mental disorders, 5th edition

Eating disorder

Generalised anxiety disorder

International classification of diseases, 11th edition

Major depressive disorder

Night eating syndrome

Other specified feeding or eating disorder

Post-traumatic stress disorder

Rapid review

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Acknowledgements

The authors would like to thank and acknowledge the hard work of Healthcare Management Advisors (HMA) who were commissioned to undertake the Rapid Review. Additionally, the authors would like to thank all members of the consortium and consultation committees for their advice, input, and considerations during the development process. Further, a special thank you to the carers, consumers and lived experience consultants that provided input to the development of the Rapid Review and wider national Eating Disorders Research & Translation Strategy. Finally, thank you to the Australian Government—Department of Health for their support of the current project.

National Eating Disorder Research Consortium: Phillip Aouad, Sarah Barakat, Robert Boakes, Leah Brennan, Emma Bryant, Susan Byrne, Belinda Caldwell, Shannon Calvert, Bronny Carroll, David Castle, Ian Caterson, Belinda Chelius, Lyn Chiem, Simon Clarke, Janet Conti, Lexi Crouch, Genevieve Dammery, Natasha Dzajkovski, Jasmine Fardouly, Carmen Felicia, John Feneley, Amber-Marie Firriolo, Nasim Foroughi, Mathew Fuller-Tyszkiewicz, Anthea Fursland, Veronica Gonzalez-Arce, Bethanie Gouldthorp, Kelly Griffin, Scott Griffiths, Ashlea Hambleton, Amy Hannigan, Mel Hart, Susan Hart, Phillipa Hay, Ian Hickie, Francis Kay-Lambkin, Ross King, Michael Kohn, Eyza Koreshe, Isabel Krug, Anvi Le, Jake Linardon, Randall Long, Amanda Long, Sloane Madden, Sarah Maguire, Danielle Maloney, Peta Marks, Sian McLean, Thy Meddick, Jane Miskovic-Wheatley, Deborah Mitchison, Richard O’Kearney, Shu Hwa Ong, Roger Paterson, Susan Paxton, Melissa Pehlivan, Genevieve Pepin, Andrea Phillipou, Judith Piccone, Rebecca Pinkus, Bronwyn Raykos, Paul Rhodes, Elizabeth Rieger, Sarah Rodan, Karen Rockett, Janice Russell, Haley Russell, Fiona Salter, Susan Sawyer, Beth Shelton, Urvashnee Singh, Sophie Smith, Evelyn Smith, Karen Spielman, Sarah Squire, Juliette Thomson, Marika Tiggemann, Stephen Touyz, Ranjani Utpala, Lenny Vartanian, Andrew Wallis, Warren Ward, Sarah Wells, Eleanor Wertheim, Simon Wilksch & Michelle Williams

The RR was in-part funded by the Australian Government Department of Health in partnership with other national and jurisdictional stakeholders. As the organisation responsible for overseeing the National Eating Disorder Research & Translation Strategy, InsideOut Institute commissioned Healthcare Management Advisors to undertake the RR as part of a larger, ongoing, project. Role of Funder: The funder was not directly involved in informing the development of the current review.

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DM, PM, ST and SM oversaw the Rapid Review process; AL carried out and wrote the initial review; AH and GP wrote the first manuscript; all authors edited and approved the final manuscript.

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ST receives royalties from Hogrefe and Huber, McGraw Hill and Taylor and Francis for published books/book chapters. He has received honoraria from the Takeda Group of Companies for consultative work, public speaking engagements and commissioned reports. He has chaired their Clinical Advisory Committee for Binge Eating Disorder. He is the Editor in Chief of the Journal of Eating Disorders. ST is a committee member of the National Eating Disorders Collaboration as well as the Technical Advisory Group for Eating Disorders. AL undertook work on this RR while employed by HMA. A/Prof Sarah Maguire is a guest editor of the special issue “Improving the future by understanding the present: evidence reviews for the field of eating disorders.”

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Studies included in the Rapid Review.

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Hambleton, A., Pepin, G., Le, A. et al. Psychiatric and medical comorbidities of eating disorders: findings from a rapid review of the literature. J Eat Disord 10 , 132 (2022). https://doi.org/10.1186/s40337-022-00654-2

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Published on 9.4.2024 in Vol 26 (2024)

Moderating Effect of Coping Strategies on the Association Between the Infodemic-Driven Overuse of Health Care Services and Cyberchondria and Anxiety: Partial Least Squares Structural Equation Modeling Study

Authors of this article:

Original Paper

• Richard Huan Xu 1 , PhD   ; 
• Caiyun Chen 2 , PhD  

1 Department of Rehabilitation Sciences, Faculty of Health and Social Sciences, Hong Kong Polytechnic University, Hung Hom, China (Hong Kong)

2 Nanjing Academy of Administration, Nanjing, China

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Richard Huan Xu, PhD

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Faculty of Health and Social Sciences

Hong Kong Polytechnic University

11 Yuk Choi Rd

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Phone: 852 27664199

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Background: The COVID-19 pandemic has led to a substantial increase in health information, which has, in turn, caused a significant rise in cyberchondria and anxiety among individuals who search for web-based medical information. To cope with this information overload and safeguard their mental well-being, individuals may adopt various strategies. However, the effectiveness of these strategies in mitigating the negative effects of information overload and promoting overall well-being remains uncertain.

Objective: This study aimed to investigate the moderating effect of coping strategies on the relationship between the infodemic-driven misuse of health care and depression and cyberchondria. The findings could add a new dimension to our understanding of the psychological impacts of the infodemic, especially in the context of a global health crisis, and the moderating effect of different coping strategies on the relationship between the overuse of health care and cyberchondria and anxiety.

Methods: The data used in this study were obtained from a cross-sectional web-based survey. A professional survey company was contracted to collect the data using its web-based panel. The survey was completed by Chinese individuals aged 18 years or older without cognitive problems. Model parameters of the relationships between infodemic-driven overuse of health care, cyberchondria, and anxiety were analyzed using bootstrapped partial least squares structural equation modeling. Additionally, the moderating effects of coping strategies on the aforementioned relationships were also examined.

Results: A total of 986 respondents completed the web-based survey. The mean scores of the Generalized Anxiety Disorder-7 and Cyberchondria Severity Scale-12 were 8.4 (SD 3.8) and 39.7 (SD 7.5), respectively. The mean score of problem-focused coping was higher than those of emotion- and avoidant-focused coping. There was a significantly positive relationship between a high level of infodemic and increased overuse of health care (bootstrapped mean 0.21, SD 0.03; 95% CI 0.1581-0.271). The overuse of health care resulted in more severe cyberchondria (bootstrapped mean 0.107, SD 0.032) and higher anxiety levels (bootstrapped mean 0.282, SD 0.032) in all the models. Emotion (bootstrapped mean 0.02, SD 0.008 and 0.037, SD 0.015)- and avoidant (bootstrapped mean 0.026, SD 0.009 and 0.049, SD 0.016)-focused coping strategies significantly moderated the relationship between the overuse of health care and cyberchondria and that between the overuse of health care and anxiety, respectively. Regarding the problem-based model, the moderating effect was significant for the relationship between the overuse of health care and anxiety (bootstrapped mean 0.007, SD 0.011; 95% CI 0.005-0.027).

Conclusions: This study provides empirical evidence about the impact of coping strategies on the relationship between infodemic-related overuse of health care services and cyberchondria and anxiety. Future research can build on the findings of this study to further explore these relationships and develop and test interventions aimed at mitigating the negative impact of the infodemic on mental health.

Introduction

Covid-19–related mental health problems.

In today’s technologically advancing society, widespread and rapid digitization has led to a substantial increase in the use of social media and the internet. This, in turn, has facilitated the rapid dissemination of all types of information. Although this can be beneficial in filling information gaps quickly, it has its drawbacks. A prominent drawback is the amplification of harmful messages, which can have negative effects on individuals [ 1 , 2 ]. The World Health Organization (WHO) acknowledged the presence of an infodemic during the COVID-19 pandemic and subsequent responses. WHO defines an infodemic as an excessive amount of information, including both accurate and inaccurate content [ 3 ]. This abundance of information makes it difficult for individuals to distinguish reliable sources from unreliable sources and to find trustworthy guidance when they need it.

Excessive use of health care services can have adverse effects on individuals and the overall sustainability of health care systems. Although challenges associated with the overuse of health care services were evident before the COVID-19 pandemic [ 4 , 5 ], the urgent need for sustainable health care systems was exacerbated by the pandemic. Because large portions of the population were instructed to self-isolate at home and had limited access to health care professionals during the pandemic, the internet became the primary source of information for numerous individuals seeking answers to health-related questions. However, the abundance of web-based information, including both true and false content, can leave individuals feeling overwhelmed and struggling to make informed choices. This information overload can lead to depression because individuals bombarded with conflicting messages may feel unsure of what to believe [ 6 - 10 ].

Besides depression, cyberchondria has also emerged as a significant public health challenge since the onset of the COVID-19 pandemic. This refers to the repeated and excessive search for health-related information on the internet, leading to a significant increase in distress or anxiety [ 11 ]. Although the global emergency caused by the COVID-19 pandemic is over, telehealth remains a growing trend. An increasing number of studies have indicated that telehealth can improve health care access, outcomes, and affordability by offering a bridge to care and an opportunity to reinvent web-based care models [ 12 ]. However, increasing internet exposure increases the risk of cyberchondria, especially under conditions of uncertainty and increased risk, due to the large volume of information it contains. Thus, it is crucial to understand how to provide support and guidance to help people adopt appropriate strategies for using web-based resources safely in the context of an infodemic.

Current Research on the COVID-19–Related Infodemic

The harms of infodemic are well documented. An Italian study suggested developing early warning signals for an infodemic, which can provide important cues for implementing effective communication strategies to mitigate misinformation [ 13 ]. Other studies have shown that successful use of coping strategies can help individuals manage stressful events and reduce negative emotions during a pandemic. For example, Yang [ 14 ] found a positive correlation between emotion-focused coping and cyberbullying and depression during the COVID-19 pandemic. A large-scale UK study indicated that supportive coping was associated with a faster decrease in depression and anxiety symptoms [ 15 ]. Shigeto et al [ 16 ] emphasized the importance of training young adults to develop resilience, flexibility, and specific coping skills to offset the psychological effects of significant lifestyle changes resulting from pandemics or other health crises in the future. A recent study used machine learning technology to enhance the accuracy and efficiency of automated fact-checking and infodemic risk management at a strategic level [ 17 ]. However, the impact of coping strategies on the relationship among the infodemic, cyberchondria, and anxiety at an individual level during the COVID-19 pandemic is still unknown.

Importance of Coping Strategies

The ability of individuals to discern and adopt appropriate coping strategies can have a profound impact on their mental health, particularly in relation to conditions such as depression and anxiety. The ability to select and implement coping strategies is not uniform across all individuals, and these differences can significantly influence the trajectory of their mental health outcomes. For some, the ability to effectively choose and implement coping strategies can serve as a protective factor, mitigating the severity of the symptoms of depression or anxiety and promoting overall health and well-being. Conversely, for others, inability or difficulty in selecting and implementing effective coping strategies can exacerbate mental health conditions, leading to increased severity of depression and anxiety. This, in turn, can have detrimental effects on individuals’ overall health and well-being. Therefore, understanding the factors that influence individuals’ ability to select and implement effective coping strategies is of paramount importance in the field of mental health research and intervention [ 18 ].

Research has demonstrated the importance of appropriate coping mechanisms in managing mental health problems. Coping strategies, which are essential for dealing with stress or challenging situations, can be categorized into 3 primary types: emotion focused, problem focused, and avoidant focused [ 19 ]. Emotion-focused strategies are centered around managing and regulating emotions. They serve as a means to cope with stress or difficult situations. These strategies might involve seeking emotional support from others, using relaxation techniques, or practicing mindfulness. In contrast, problem-focused strategies actively address the problem or stressor. These strategies might encompass problem-solving, devising a plan of action, or seeking information and resources to effectively tackle the situation. Avoidant-focused strategies involve evading or distancing oneself from the stressor or problem. These strategies might include denial, distraction, or engaging in activities to escape or avoid contemplating the issue [ 18 ]. The effectiveness of different coping strategies can vary depending on the situation. Individuals often use different or a combination of strategies, tailoring their approach to their circumstances.

Coping Strategies in the COVID-19–Related Infodemic

From a social perspective, this study underscores the importance of mental health in the context of public health emergencies such as the COVID-19 pandemic. It highlights the need for society to recognize and address the mental health burden that such emergencies can place on individuals, particularly in relation to the phenomenon of cyberchondria, which is the unfounded escalation of concerns about common symptoms based on reviews of web-based literature and resources.

Practically, this study provides valuable insights for policy makers and practitioners. It emphasizes the need for the development of effective coping strategies and programs to manage the negative impact of an overload of misinformation and disinformation on mental health. This is particularly relevant in the digital age, where individuals have access to a plethora of information, not all of which is accurate or reliable. Policy makers and practitioners can use the findings of this study to design interventions that not only provide accurate information but also equip individuals with the skills to distinguish reliable sources from unreliable sources and to cope with the anxiety that misinformation can cause. From a research standpoint, this study fills a gap in the literature by assessing the impact of the infodemic on cyberchondria and the moderating effect of coping strategies in this relationship. It opens up new avenues of research into the complex interplay among public health emergencies, infodemic, cyberchondria, and coping strategies. Future research could build on the findings of this study to further explore these relationships and develop and test interventions aimed at mitigating the negative impact of infodemic on mental health.

Objective of the Study

Currently, the association between the overuse of health care services and mental health problems in the context of an infodemic remains unclear, as is the moderating effect of different coping strategies on this association. Thus, this study investigated the moderating effect of coping strategies on the relationship between the infodemic-driven misuse of health care and depression and cyberchondria.

Hypotheses of the Study

The study used a hypothesis-driven format. Specifically, there are five hypotheses: (1) a positive relationship exists between infodemic and the misuse of health care, (2) a positive relationship exists between the misuse of health care and depressive disorders, (3) a positive relationship exists between the misuse of health care and cyberchondria, (4) coping strategies mitigate the negative effect of the misuse of health care on depression, and (5) coping strategies mitigate the negative effect of the misuse of health care on cyberchondria. Hypotheses 2-5 are separately evaluated for the three types of coping strategies: problem focused (H2.1), emotion focused (H2.2), and avoidant focused (H2.3).

Study Design and Sample Size

The data used in this study were obtained from a cross-sectional and web-based survey conducted between April and May 2023 in China.

There is no gold standard for sample estimation in partial least squares structural equation modeling (PLS-SEM). Following Hair et al [ 20 ], we set the significance level at 5% and the minimum path coefficients to between 0.05 and 0.1. Based on these criteria, a minimum sample size of 619 was determined.

Data Source and Collection

A professional surveying company, WenJuanXing, was invited to collect the data through its web-based panel. The panel of WenJuanXing consists of 2.6 million members, with an average of over 1 million questionnaire respondents daily. At the beginning of the project, a survey manager collaborated with the research team to screen and recruit participants using the company’s internal social network platform. All of the eligible panel members received a survey invitation, and a voluntary response sampling method was used. The survey manager checked the data quality using WenJuanXing’s artificial intelligence data quality control system to ensure that respondents met our inclusion criteria and provided valid responses, thus ensuring a high level of data accuracy and integrity. The inclusion criteria were (1) aged older than 18 years, (2) able to understand and read Chinese, and (3) agreed to provide informed consent. All eligible respondents were invited to participate in a web-based survey. The first section of the survey was the informed consent, which the participants were required to read and agree to before proceeding. All the participants who agreed to participate in the survey were asked to complete six questionnaires covering (1) demographics and socioeconomic status, (2) COVID-19 information–related questions, (3) a cyberchondria questionnaire, (4) an eHealth literacy questionnaire, (5) an anxiety questionnaire, and (6) a coping strategy questionnaire. The English translations of the questionnaires are presented in Multimedia Appendix 1 . To ensure data quality, we collaborated with the survey company and implemented various indicators. We monitored completion time, excluding responses that took less than 6 minutes. We also tracked ID addresses, ensuring that each ID address could only complete the questionnaire once. To minimize random errors, we used an artificial intelligence formula developed by the survey company to identify and filter any response patterns that appeared to be generated in parallel.

Ethical Considerations

The study protocol and informed consent process were approved by the institutional review board of the Hong Kong Polytechnic University (HSEARS20230502006). Informed consent was collected from all participants. The survey was conducted anonymously, and no personally identifiable information was collected. No compensation was provided by the research team.

Instruments

Cyberchondria severity scale-12.

The Cyberchondria Severity Scale-12 (CSS-12), derived from the 33-item CSS, was used to measure the severity of cyberchondria. The CSS-12 exhibited equally good psychometric properties as the original version and has been validated in Chinese populations [ 21 ]. The CSS-12 items are scored on a Likert-type scale ranging from 1=“never” to 5=“always,” giving total scores ranging from 12 to 60. A higher score indicates a higher severity of suspected cyberchondria. The psychometric properties of the Chinese version of the CSS-12 were reported by Peng et al [ 22 ].

Generalized Anxiety Disorder Assessment

The Generalized Anxiety Disorder Assessment-7 (GAD-7) was used to screen for generalized anxiety disorder and related anxiety disorders [ 23 ]. This scale consists of 7 items designed to assess the frequency of anxiety symptoms during the 2 weeks preceding the survey. The GAD-7 score is calculated by assigning scores of 0, 1, 2, and 3 to the response categories of “not at all,” “several days,” “more than half the days,” and “nearly every day,” respectively. The scores of the 7 questions are then summed, giving a total ranging from 0 to 21, with higher scores indicating a higher severity of anxiety disorders. Many studies have reported the psychometric properties of the GAD-7 in Chinese populations, such as that conducted by Sun et al [ 24 ].

Coping Orientation to Problems Experienced Inventory

The Coping Orientation to Problems Experienced Inventory (Brief-COPE) is a 28-item self-report questionnaire used to measure effective and ineffective strategies for coping with a stressful life event [ 25 ]. The Brief-COPE assesses how a person deals with stressors in their daily life. The questionnaire measures 3 coping strategy dimensions: problem focused, emotion focused, and avoidant focused [ 26 ]. Each item is rated on a 4-point scale. The scores for the 3 overarching coping styles are calculated as average scores. This is done by dividing the sum of the item scores by the number of items. These average scores indicate the extent to which the respondent engages in each coping style. A higher score indicates that the respondent does not have many coping skills. The Chinese version of the Brief-COPE and its psychometric properties in Chinese populations were reported by Wang et al [ 27 ].

Infodemic- and Misinformation-Driven Overuse of Health Care Services

The COVID-19–related infodemic and misinformation-driven medical misbehavior were assessed using 2 self-developed items. The first item was “Do you believe there is an excessive amount of information regarding the COVID virus and vaccine on a daily basis?” The second item was “Has misinformation or disinformation about COVID-19 led you to engage in the overuse of health care services (eg, frequently visiting the doctor/psychiatrist or buying unnecessary medicine)?” The respondents were required to indicate their response to these 2 questions by selecting 1 of 2 options presented dichotomously: yes or no.

Statistical Analysis

Descriptive statistics were used to describe the participants’ background characteristics. Continuous variables (eg, age) were calculated as means and SDs. Categorical variables (eg, sex) were calculated as frequencies and proportions. The Pearson correlation coefficient ( r ) was used to examine the association between measures, where  r ≥0.3 and  r ≥0.5 indicated moderate and large effects, respectively [ 28 , 29 ].

In this study, we used PLS-SEM to estimate the research model parameters, as it works efficiently with small samples and complex models. Compared with covariance-based structural equation modeling, PLS-SEM has several advantages, such as the ability to handle non-normal data and small samples [ 30 ]. Unlike covariance-based structural equation modeling, which focuses on confirming theories, PLS-SEM is a causal-predictive approach that explains variance in the model’s dependent variables [ 31 ]. To improve the model fit, we used the bootstrapping method with 10,000 replications to obtain the estimates of the mean coefficients and 95% CIs [ 32 ]. Composite reliability rho_a (>0.7), composite reliability rho_c (>0.7), and average variance extracted (>0.5) were used to examine the model performance.

PLS-SEM encompasses measurement models that define the relationship between constructs (instruments) and indicator variables and a structural model. The structural model used in this study is presented in Figure 1 . We hypothesized that the infodemic significantly affects misinformation-driven medical misbehavior, resulting in cyberchondria and high anxiety levels. Furthermore, we speculated that coping strategies significantly modify this relationship. To test these hypotheses, we used 3 models that used the full sample to separately investigate the moderating effect of the 3 types of coping strategies (problem focused, emotion focused, and avoidant focused). We analyzed the data and estimated the PLS-SEM parameters using the “SEMinR” package in R (R Foundation for Statistical Computing). A P value of ≤.05 was considered statistically significant.

Background Characteristics of Participants

A total of 986 respondents completed the web-based survey and provided valid responses, resulting in a response rate of 84%. Among the participants, 51.7% (n=510) were female, approximately 95% (n=933) had completed tertiary education or above, and 71.2% (n=702) resided in urban areas. The participants’ background characteristics are listed in Table 1 .

a A currency exchange rate of 7.23 CNY=US $1 applies.

Mean Scores and Frequency of Responses

The mean score of the GAD-7 was 8.4 (SD 3.8), while the mean score of the CSS-12 was 39.7 (SD 7.5). Problem-focused coping had a higher mean score than emotion- and avoidant-focused coping. Respondents with active employment reported statistically significantly higher mean scores on the GAD and avoidant-focused coping subscale compared to those with nonactive employment. A higher proportion of respondents with chronic diseases experienced an infodemic and exhibited the overuse of health care services relative to those without chronic diseases ( Table 2 ). The correlations between all of the measures are presented in Multimedia Appendix 2 .

a GAD-7: Generalized Anxiety Disorder Assessment-7.

b CSS-12: Cyberchondria Severity Scale-12.

c COPE: Coping Orientation to Problems Experienced Inventory.

g P <.001.

Measurement Models

Tables 3 - 5 present the performance of the measurement models for the 3 coping strategies. The values of rho_C and rho_A were above 0.7, indicating acceptable construct reliability. All 3 constructs had Cronbach α values exceeding the cutoff of 0.7, indicating adequate reliability. Table 2 presents the models’ convergent validity. All the bootstrapped item loadings exceeded 0.3 and were significant at <.05 for the problem- and avoidant-focused models. However, for cyberchondria and the Brief-COPE, none of the average variance extracted values were above 0.5, indicating unsatisfactory model convergent validity.

a AVE: average variance extracted.

b GAD-7: Generalized Anxiety Disorder-7.

d HC: health care.

b GAD-7: Generalized Anxiety Disorder.

Structural Models

The structural model analysis involved estimating path coefficients for the conceptual model. We performed PLS-SEM on the research model 3 times to estimate path coefficients for the models with different coping strategies. We found that H1 was supported. A significant and positive relationship was observed between a high level of infodemic exposure and increased overuse of health care services (coefficient=0.212, 95% CI 0.151-0.271). In addition, the overuse of health care services was correlated with more severe cyberchondria and higher anxiety levels in all the 3 models, supporting H2 and H3. The effect of the overuse of health care services on cyberchondria was larger than its effect on anxiety. All these relationships were statistically significant ( Tables 3 - 5 ).

Moderating Effects

In our moderation analyses ( Figure 2 and Tables 6 and 7 ), we found that emotion- and avoidant-focused coping strategies significantly moderated the relationship between the overuse of health care services and cyberchondria and that between the overuse of health care services and anxiety, respectively, supporting H5 and H6. For the problem-based model (H4), the moderating effect was not significant for the relationship between the overuse of health care services and cyberchondria (coefficient=0.002, 95% CI −0.011 to 0.006), indicating that H4.1 was not supported. Compared with the direct effects on the relationship between the overuse of health care services and cyberchondria or anxiety, a strong ability to cope with difficulties can effectively mitigate the negative effects of the infodemic-driven overuse of health care services on cyberchondria and anxiety.

a HC: health care.

b GAD: Generalized Anxiety Disorder Assessment.

b CS: coping strategy.

c GAD: Generalized Anxiety Disorder Assessment.

Principal Findings

We performed a series of PLS-SEM analyses to examine the relationships between the infodemic-driven overuse of health care services and cyberchondria and anxiety and determine the moderating effects of 3 types of coping strategies on these relationships. We observed that the individuals who were exposed to an overload of COVID-19–related information were more likely to seek and use extra and unnecessary health care services during the pandemic. Such behavior may lead to a considerable wastage of health resources that are particularly limited during a public health crisis. Although some studies have indicated that during the COVID-19 pandemic individuals with increasing mental health symptoms rarely used mental health services [ 33 - 35 ], we found that the overuse of health care services may contribute to higher levels of depression and cyberchondria during a pandemic. This finding has never been reported before. However, we did not differentiate between the types of health care services, either physical or mental, that the individuals overused during the pandemic. This limitation may affect the implications of our findings for policy making purposes.

Comparisons With Previous Studies

We observed that enhanced coping strategies can mitigate the adverse effects of overusing health care on depression and cyberchondria. Studies have confirmed the association between pandemics and depression, have identified several sources of depression [ 6 , 7 , 10 , 36 , 37 ], and have determined the relationship between depression and cyberchondria [ 38 ]. However, few studies have investigated the relationship between depression or cyberchondria and the infodemic-driven overuse of health care services. Our findings demonstrate that the adverse effects of the pandemic are diverse and require the investigation of individuals’ health from multiple perspectives (ie, infodemic in health communication, the use of health care in health service research, and depression in psychiatry). These effects might not be immediately apparent, but they are all linked to each other and collectively cause harm. Thus, policy makers should develop a comprehensive and cost-effective strategy to address the potential adverse effects of pandemics on people’s health and well-being and better prepare for the next public health crisis.

This study offers new insights into the role of coping strategies in mediating the relationship between health care overuse and depression or cyberchondria during the COVID-19 pandemic. Overall, individuals with strong coping abilities were more likely to report lower levels of depression or cyberchondria than those with weak coping abilities. However, the moderating effects of different coping strategies varied slightly. We discovered that problem-focused coping strategies resulted in lower levels of depression and cyberchondria than avoidant-focused coping strategies. Additionally, emotion-focused coping strategies led to lower levels of depression than the other 2 types of coping strategies. These findings partially align with previous studies. For instance, Li [ 39 ] demonstrated that using both problem-focused and emotion-focused coping strategies was beneficial for psychological well-being. However, previous studies have reported mixed findings. For example, AlHadi et al [ 40 ] indicated that emotion-focused coping strategies were associated with increased depression, anxiety, and sleep disorders in the Saudi Arabian population. Few studies have examined the effect of avoidant-focused coping strategies. In this study, we found that respondents who reported living with chronic diseases exhibited a higher ability to use avoidant-focused coping. This finding is partially consistent with a previous study that found a positive relationship between avoidance-focused coping strategies and mental health in women with heart disease [ 41 ]. Individuals with medical conditions are more likely to adopt avoidant coping strategies. Firouzbakht et al [ 42 ] explained that avoidance is an effective strategy for handling short-term stress and is more likely to be adopted by certain patient groups.

We found that individuals who favor emotion-focused coping strategies to overcome difficulties are able to effectively mitigate the adverse effects of excessive health care use on depression and cyberchondria relative to those who opt for the other 2 coping strategies. This finding is not entirely surprising or unexpected. It is, in fact, quite reasonable when one considers that scholars and researchers in the field have previously indicated that people have a tendency to adopt emotion-focused strategies, especially when they find themselves in situations that are uncontrollable or unpredictable, such as the ongoing global pandemic [ 43 ]. Some studies have found that age can have a significant impact on an individual’s coping strategy preferences. For instance, younger adults were more likely to use emotion-focused coping strategies during the acute phase of the SARS outbreak, whereas older adults used this particular strategy several months after the outbreak had initially occurred [ 44 ]. This suggests that the coping strategies adopted by individuals can vary greatly depending on their age and the stage of the crisis they are experiencing. However, in the context of this study, we did not observe any significant differences in the coping strategy preferences of the different age groups. This could be due to a variety of factors, but a possible explanation is that our model incorporated the COVID-19 infodemic. In this context, it is understandable that providing emotional support might be more important than providing real solutions. This is particularly true in the current digital age, where the internet offers unlimited information sources for people to explore, which can often lead to information overload and increased anxiety. Therefore, emotion-focused coping strategies could be more beneficial in helping individuals navigate the sea of information and manage their emotional responses effectively.

In this study, we used self-developed items to measure the infodemic and overuse of health care services. While this approach allowed us to collect data that were directly related to the research questions, it may have introduced some potential issues. First, self-developed items may have less validity and reliability than standardized questionnaires. This could affect the accuracy of measurements and the validity of findings. Second, using self-developed items may limit comparability with other studies that use standardized questionnaires. Standardized questionnaires allow for easy comparison across studies and populations. The lack of a common metric may make it challenging to compare the findings of this study to other studies or to aggregate them in future meta-analyses. Finally, self-developed items may be more susceptible to response bias. They may not have considered factors like social desirability bias or acquiescence bias as standardized questionnaires do. This could have skewed the responses and affected the accuracy of the findings. Despite these limitations, the study’s findings provide valuable insights and pave the way for future research in this area.

Main Contributions of This Study

The importance of preparedness, prevention, and emergency response to infodemiology is highly encouraged by the WHO [ 45 ]. This study makes a significant contribution by exploring and empirically evaluating the relationship between the infodemic, the overuse of health care services, cyberchondria, and anxiety in the context of the COVID-19 pandemic. It provides empirical evidence supporting the assertion that a high level of infodemic can lead to the increased overuse of health care services, resulting in more severe cyberchondria and heightened anxiety levels. This finding adds a new dimension to our understanding of the psychological impacts of the infodemic, especially in the context of a global public health crisis. Additionally, this study highlights that adopting appropriate coping strategies can potentially reduce the severity of cyberchondria and anxiety, even among people facing high levels of the infodemic and the overuse of health care services.

Future Research

The study’s findings emphasize the importance of coping strategies in reducing the negative effects of the infodemic and the excessive use of health care. Future research could focus on developing and testing interventions to improve coping skills, such as cognitive-behavioral, mindfulness-based, or psychoeducational approaches. Additionally, other factors like social support, personality traits, or health literacy may moderate the relationship between infodemic, health care overuse, cyberchondria, and anxiety. Future research could further explore these variables. This study’s findings may not apply to all populations, so future research could investigate these relationships in different groups, including those with pre-existing mental health conditions, health care professionals, or diverse cultural contexts. By pursuing these future directions, researchers could build on this study’s findings, thereby enhancing our understanding of the psychological impact of infodemic and developing effective interventions.

Limitations

This study has several limitations that need to be addressed. A primary limitation is that the data were cross-sectional and self-reporting, which can introduce several biases. Social desirability bias may occur when respondents provide answers they believe are socially acceptable rather than truthful. Recall bias may also be present, as the respondents were asked to recall experiences from months or even a year ago. The data are also prone to response bias, as respondents may agree or disagree with statements regardless of their content. These biases may have affected the accuracy of the findings. In the future, we will try to collect data at multiple time points to reduce the biases and identify changes over time. Second, the data used in this analysis were obtained from a web-based survey, which excluded individuals who are not familiar with web-based surveys or do not have access to the internet. This could have resulted in selection bias. Additionally, due to the nature of the web-based survey, the demographic information of our sample was highly skewed. The majority of the respondents were young and highly educated and were frequent internet users who may have experienced more infodemic effects than older and less educated individuals. This may have affected the reliability of our findings. A quota sampling method could be used in future studies to improve the representativeness of the sample. Third, the study was conducted in China; thus, it is important to consider the unique context of China when interpreting the results. It is necessary to conduct further research in different cultural and regional contexts to determine the generalizability of the results. Finally, the evaluation of health care service overuse and strength of the infodemic relied on 2 self-developed items, which may have affected the measurement properties and limited the reliability of our findings. The development of standardized questionnaires to measure the infodemic and the overuse of health care services during a pandemic would be a valuable contribution to future research in this field.

Conclusions

This study is the first to demonstrate a significant correlation between the infodemic-driven overuse of health care services and high levels of depression and cyberchondria in the Chinese population during the COVID-19 pandemic. We find that 3 types of coping strategies can effectively mitigate the adverse effects of infodemic-driven health care overuse on depression and cyberchondria. Among them, emotion-focused coping strategies have stronger moderating effects than the other 2 types of coping strategies. These findings provide empirical evidence that can guide policy makers in developing strategies to reduce cyberchondria, provide accurate information about public health crises, and promote adaptive coping strategies to effectively manage future public health crises.

Data Availability

The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Authors' Contributions

RHX contributed to developing the study concept and design, data analysis and interpretation, software, writing the original draft, and review and editing. CC contributed to data collection, software, and review and editing. Both authors approved the submitted version.

Conflicts of Interest

None declared.

English-translated questionnaire.

Correlations between measures.

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Abbreviations

Edited by G Eysenbach, T de Azevedo Cardoso; submitted 05.10.23; peer-reviewed by K Wang, J Chen, CN Hang, E Vashishtha, D Liu; comments to author 06.11.23; revised version received 14.11.23; accepted 22.03.24; published 09.04.24.

©Richard Huan Xu, Caiyun Chen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 09.04.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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The Implications of COVID-19 for Mental Health and Substance Use

Nirmita Panchal , Heather Saunders , Robin Rudowitz , and Cynthia Cox Published: Mar 20, 2023

Note: This brief was updated on March 20, 2023 to incorporate the latest available data. Concerns about mental health and substance use remain elevated three years after the onset of the COVID-19 pandemic, with 90% of U.S. adults believing that the country is facing a mental health crisis, according to a recent KFF/CNN survey. The pandemic has affected the public’s mental health and well-being in a variety of ways, including through isolation and loneliness, job loss and financial instability, and illness and grief.

Over the course of the pandemic, many adults reported symptoms consistent with anxiety and depression, with approximately four in ten adults reporting these symptoms by early 2021, before declining to approximately three in ten adults as the pandemic continued (Figure 1). Additionally, drug overdose deaths have sharply increased – largely due to fentanyl – and after a brief period of decline, suicide deaths are once again on the rise. These negative mental health and substance use outcomes have disproportionately affected some populations, particularly communities of color and youth. As the end of the declaration of the public health emergency nears – on May 11, 2023 – many people continue to grapple with worsened mental health and well-being and face barriers to care.

This brief explores mental health and substance use during, and prior to, the COVID-19 pandemic. We highlight populations that were more likely to experience worse mental health and substance use outcomes during the pandemic and discuss some innovations in the delivery of services. We analyze and present findings using the most recent data available at the time of this publication – including the Household Pulse Survey and the CDC WONDER database . Key takeaways include:

• Symptoms of anxiety and depression increased during the pandemic and are more pronounced among individuals experiencing household job loss, young adults, and women. Adolescent females have also experienced increased feelings of hopelessness and sadness compared to their male peers.
• Deaths due to drug overdose increased sharply across the total population coinciding with the pandemic – and more than doubled among adolescents. Drug overdose death rates are highest among American Indian and Alaska Native people and Black people.
• Alcohol-induced death rates increased substantially during the pandemic, with rates increasing the fastest among people of color and people living in rural areas.
• After briefly decreasing, suicide deaths are on the rise again as of 2021. From 2019 to 2021, many communities of color experienced a larger growth in suicide death rates compared to their White counterparts. Additionally, self-harm and suicidal ideation has increased faster among adolescent females compared to their male peers.
• Several changes have been implemented in the delivery of mental health and substance use services since the onset of the pandemic, including the utilization of telehealth, steps to improve access to treatment for opioid use disorders, expansion of school-based mental health care, and the rollout of the 988 crisis line. As the public health emergency declaration comes to an end, it is possible that some of these changes will be interrupted.

Prevalence of Mental Illness and Substance Use During the Pandemic

Anxiety and depression.

The pandemic was associated with a high prevalence of anxiety and depression symptoms in adults. Research suggests that these symptoms increased during the pandemic, but the extent of this increase is unclear . 1 Throughout the pandemic, symptoms of anxiety and depression have been more pronounced among several populations.

For example, individuals experiencing household job loss were more likely than their counterparts to report symptoms of anxiety and/or depression (53% vs. 30%) in February 2023 (Figure 2). Job loss and unemployment – which have long been associated with adverse mental health outcomes – increased substantially early on in the pandemic .

Fifty percent of young adults (ages 18-24) reported anxiety and depression symptoms in 2023, making them more likely than older adults to experience mental health symptoms (Figure 2). Young adults have experienced a number of pandemic-related consequences – such as closures of universities, transitioning to remote work, and loss of income or employment – that may contribute to poor mental health. Additionally, young adults in college settings may encounter increased difficulty accessing treatment .

Symptoms of anxiety and/or depression were also elevated among women (36%) compared to men (28%) in February 2023 (Figure 2). Even before the pandemic, women were  more likely  than men to report mental health disorders, including serious mental illness.

Concerns about youth mental health further increased with the onset of the pandemic and the recent uptick in gun violence . In a recent KFF/CNN survey , roughly half of parents (47%) said the pandemic had a negative impact on their child’s mental health, including 17% who said it had a “major negative impact”. Poor mental health has been more pronounced among adolescent females in particular. As shown in Figure 3, the gap in the share of adolescent females and males reporting feelings of hopelessness and sadness – symptoms indicative of depressive disorder – widened from 2019 (47% vs. 27%, respectively) to 2021 (57% vs. 29%, respectively). Many female adolescents also reported adverse experiences in 2021, which can negatively impact mental health.

Substance use and deaths

The pandemic has coincided with an increase in substance use and increased death rates due to substances. In 2021, there were over  106,600 deaths  due to drug overdose in the U.S. – the highest on record. This spike in deaths has primarily been driven by substances laced with synthetic opioids, including illicitly manufactured fentanyl .

Further, the overall drug overdose death rate rose by 50% during the pandemic (Figure 4), but varied across states . While drug overdose death rates increased across all racial and ethnic groups, the increases were larger for people of color compared to White people. White people continue to account for the largest share of deaths due to drug overdose per year, but  people of color  are accounting for a growing share of these deaths over time. In 2021, the highest drug overdose death rates were among American Indian Alaska Native (AIAN) people (56.6 per 100,000), Black people (44.2 per 100,000), and White people (36.8 per 100,000) (Figure 4). Differences in drug overdose deaths by sex were also exacerbated during the pandemic. As shown in Figure 4, the gap in the drug overdose death rates between males and females increased from 2019 (29.6 vs. 13.7 per 100,000, respectively) to 2021 (45.1 vs. 19.6 per 100,000, respectively).

Research suggests that substance use among adolescents has declined, yet drug overdose deaths have sharply increased among this population, primarily due to fentanyl-laced substances . Among adolescents, drug overdose deaths have more than doubled from 2019 (282 deaths) to 2021 (637 deaths) following a period of relative stability. 2 Male, Black, and Hispanic youth have experienced the highest increases in deaths due to drug overdose.

During the pandemic, excessive drinking increased along with alcohol-induced deaths. Alcohol-induced death rates increased by 38% during the pandemic, with rates the highest and increasing the fastest among AIAN people. AIAN people died of alcohol-induced causes at a rate of 91.7 per 100,000 in 2021, six times more than the next highest group – Hispanic people at a rate of 13.6. Black people also experienced significant increases in alcohol-induced deaths during COVID, with rates increasing more than 45% (Figure 5). Both rural and metropolitan areas experienced an increase in alcohol-induced deaths during the pandemic, but rural areas saw the largest increase (46% increase compared to 36%).

Suicidal ideation and deaths

Concerns about suicidal ideation and suicide deaths have also grown during the pandemic. Notably, self-harm and suicidal ideation has increased among adolescent females. Thirty percent of adolescent females seriously considered attempting suicide in 2021 compared to 14% of their male peers (Figure 6). Other analyses found that as the pandemic progressed, emergency department visits for  suicide attempts  increased among adolescents, primarily driven by females.

Suicide deaths in the U.S. began to increase in 2021 after briefly slowing in 2019 and 2020 , although some research suggests that some  suicides  may be misclassified as drug overdose deaths since it can be difficult to determine whether drug overdoses are  intentional . From 2019 to 2021, many communities of color experienced a larger growth in suicide death rates compared to their White counterparts. 3 In 2021, suicide deaths by firearm accounted for more than half ( 55% ) of all suicides in the U.S., but varied greatly across states .

The pandemic has also raised concerns about mental illness, suicide, and substance use among other populations. Essential workers and people with chronic health conditions may have experienced worsened mental health due to increased risk of contracting or becoming severely ill from COVID-19. Many of these individuals, particularly those with chronic conditions , were already at-risk of experiencing poor mental health outcomes prior to the pandemic. LBGT+ people have historically faced mental health problems at higher rates than their non-LGBT+ peers. The pandemic has continued to negatively impact LBGT+ people’s mental health in disproportionate ways. In addition, people experiencing prolonged COVID-19 symptoms, or long COVID , may be more likely to develop new mental health conditions or to experience worsening of existing ones.

Changes in the Delivery of Mental Health and Substance Use Disorder Services

Leading up to the pandemic, many people faced barriers accessing mental health and substance use disorder services for reasons including costs, not knowing where to obtain care, limited provider options, and low rates of insurance acceptance. Young adults, Black adults, men, and uninsured people were less likely to receive services compared to their peers.

In recent years, access to care barriers may have worsened due to pandemic disruptions and closures, workforce shortages, and increased demand for services. In response to growing need, some policies and strategies were implemented to address access challenges, such as growth of telehealth, improved access to opioid use disorder treatment, the expansion of school-based mental health services, and the rollout of 988; however, challenges remain.

The delivery of mental health and substance use disorder services via telehealth grew sharply during the pandemic. By 2021, nearly 40% of all mental health and substance use disorder outpatient visits were delivered through telehealth. These behavioral health services via telehealth have also been more utilized in rural areas than urban areas during the pandemic. This underscores the role telehealth can play in improving access to behavioral health services in rural areas, which often face additional provider and resource shortages . Further, community health centers – which serve low-income and medically underserved communities, including communities of color and those in rural areas – experienced a large increase in behavioral health visits in 2021, largely driven by telehealth. During the pandemic, many state Medicaid programs expanded coverage of behavioral health telehealth services. This includes broadening the range of behavioral health services offered virtually and allowing for more provider types to be reimbursed for telehealth services. Many  state  Medicaid programs reported that telehealth has helped maintain and expand access to behavioral services during the pandemic. Some private payers have also  improved  coverage for mental health and substance use services by removing pre-pandemic telehealth coverage restrictions. Although telehealth can broaden access to care, in-person care may be necessary or preferred for some or for those experiencing challenges with technology and digital literacy.

As opioid-related overdose deaths have sharply increased, measures to improve access to treatment have been implemented. Following the onset of the pandemic , the federal government allowed for new  flexibilities  in opioid use disorder (OUD) treatment to ease access barriers, for example allowing for take-home methadone doses and covering telehealth treatment, and the Biden administration has  proposed  making these flexibilities permanent. Further, the 2023  Consolidated Appropriations Act   eliminated  the X-waiver requirement for prescribing buprenorphine, which substantially increases the number of providers who are authorized to prescribe buprenorphine to treat OUD. Voluntary guidelines for providers have also been issued to help reduce opioid overprescribing and misuse. At the same time, the Drug Enforcement Agency recently proposed returning to previous rules that required in-person visits before prescribing controlled substances to patients via telehealth, though there are some exceptions.

In response to growing mental health concerns among youth, integration of mental health services in school-based settings became a priority. Recent legislation aims to expand mental health care in schools – a setting that is easily accessible by children and adolescents. Specifically, legislation provides funding to expand and train mental health providers in schools; implement suicide, drug, and violence prevention programs; and provide trauma support services, among others. Further, recognizing Medicaid’s importance  in covering and financing behavioral health care for  children , CMS is now required to provide updated guidance on how to support and expand school-based behavioral health services. The recently passed Consolidated Appropriations Act (CAA) continues to build on prior pandemic-era legislation that promotes access to behavioral health care for children. For example, to ensure more stable coverage for low-income children the CAA requires states to provide 12 months of continuous eligibility for children in Medicaid and CHIP.

An easy-to-remember number for the suicide and behavioral health crisis hotline, 988, was launched in 2022 . On July 16, 2022, the  federally mandated   crisis number ,  988 , became available to all  landline and cell phone users , providing a single three-digit number to access a network of over 200 local and state funded crisis centers where those in need may receive crisis counseling, resources and referrals. After 988 implementation, national answer rates increased alongside increases in call volume. Long-term sustainable funding of local 988 crisis call centers remains uncertain in many states. In addition to 988, some states are developing behavioral health crisis response systems, such as mobile crisis or crisis stabilization units, which will enable a specialized behavioral health response for behavioral health crises that require intervention. The  CAA included provisions aimed at strengthening and evaluating 988 and the developing behavioral health crisis continuum.

Despite steps taken to improve the delivery of mental health and substance use services, challenges remain. Provider workforce challenges are widespread, with nearly half of the U.S. population ( 47% ) living in a mental health workforce shortage area . Shortages may contribute to access challenges and contribute to increases in psychiatric boarding in emergency rooms. Additionally, provider network directories are often outdated, further contributing to access challenges. While recent legislation has taken steps in response – including funding for at least 100 new psychiatry residency positions, grants for mental health peer support providers, and improvements to provider directories through the CAA – these are relatively small measures in the face of big access challenges. The lack of a diverse mental health care workforce may contribute to limited mental health treatment among people of color. Separately, even with insurance coverage, individuals with mental health needs face challenges accessing care. While Medicaid enrollees have limited out-of-pocket costs there is variation in who is eligible and the range of services covered across states . Additionally, the end of Medicaid’s continuous enrollment provision – on March 31, 2023 – could result in millions of disenrollments over the next year which could disrupt access to behavioral health services. Among private insurance enrollees, enrollees, with mental illness face high out-of-pocket costs; and these costs vary substantially across states . While most adults with mental illness have private insurance, rates of mental illness and substance use disorders are most prevalent among nonelderly adults with Medicaid.

Looking Ahead

Although steps have been taken to address negative mental health impacts stemming from the pandemic, mental health and substance use concerns remain elevated. Heightened racism and increasing gun violence may also contribute to poor mental health outcomes. Further, negative mental health impacts have been more pronounced among several populations, including communities of color, young adults and children – populations which have historically experienced increased barriers to care. Additionally, despite renewed discussions and new federal grants for state parity enforcement under the CAA, challenges with mental health parity persist – including lack of clarity on specific protections, low compliance rates, and slow federal enforcement. Finally, the COVID-19 public health emergency will end in May 2023, which may at least partially unravel steps taken toward delivering mental health services via telehealth and improving access to substance use disorder services.

History has shown that the mental health impact of disasters outlasts the physical impact, suggesting today’s elevated mental health needs will continue well beyond the coronavirus outbreak itself. As we emerge from the COVID-19 pandemic and the federal public health emergency draws to an end, it will be important to consider how the increased need for mental health and substance use services may persist long term, even as new cases and deaths due to COVID-19 hopefully subside.

This work was supported in part by Well Being Trust. KFF maintains full editorial control over all of its policy analysis, polling, and journalism activities.

The Household Pulse Survey (HPS) is a rapid response survey that has provided real-time data during the pandemic and includes a 4-item Patient Health Questionnaire (PHQ-4) anxiety and depression screening scale. In order to understand how the prevalence of anxiety and depression may have shifted in the adult population during the onset of the pandemic, mental health estimates from HPS were compared against pre-pandemic data from the National Health Interview Survey, which also includes the 4-item PHQ scale. However, recent research finds that these comparisons may not be reliable given lower response rates and over estimation in HPS; and are no longer included in this brief.

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KFF analysis of Centers for Disease Control and Prevention, Wide-ranging Online Data for Epidemiologic Research (WONDER). Accessed at: https://wonder.cdc.gov/mcd-icd10-expanded.html

• Mental Health
• Coronavirus (COVID-19)
• Affordable Care Act
• Access to Care
• Adolescents
• Tracking Poll
• Race/Ethnicity

news release

• Latest Federal Data Show That Young People Are More Likely Than Older Adults to Be Experiencing Symptoms of Anxiety or Depression

Also of Interest

• Medicaid Coverage of Behavioral Health Services in 2022: Findings from a Survey of State Medicaid Programs
• Mental Health and Substance Use State Fact Sheets
• Mental Health and Substance Use Considerations Among Children During the COVID-19 Pandemic
• Mental Health Impact of the COVID-19 Pandemic: An Update
• Mental Illnesses May Soon Be the Most Common Pre-Existing Conditions
• State Data on Mental Health and Substance Abuse
• April 2022 Web Event: The Future of Mental Health Coverage & Access
• Medicaid Behavioral Health Services: Data Collection

• COVID-19 and your mental health

Worries and anxiety about COVID-19 can be overwhelming. Learn ways to cope as COVID-19 spreads.

At the start of the COVID-19 pandemic, life for many people changed very quickly. Worry and concern were natural partners of all that change — getting used to new routines, loneliness and financial pressure, among other issues. Information overload, rumor and misinformation didn't help.

Worldwide surveys done in 2020 and 2021 found higher than typical levels of stress, insomnia, anxiety and depression. By 2022, levels had lowered but were still higher than before 2020.

Though feelings of distress about COVID-19 may come and go, they are still an issue for many people. You aren't alone if you feel distress due to COVID-19. And you're not alone if you've coped with the stress in less than healthy ways, such as substance use.

But healthier self-care choices can help you cope with COVID-19 or any other challenge you may face.

And knowing when to get help can be the most essential self-care action of all.

Recognize what's typical and what's not

Stress and worry are common during a crisis. But something like the COVID-19 pandemic can push people beyond their ability to cope.

In surveys, the most common symptoms reported were trouble sleeping and feeling anxiety or nervous. The number of people noting those symptoms went up and down in surveys given over time. Depression and loneliness were less common than nervousness or sleep problems, but more consistent across surveys given over time. Among adults, use of drugs, alcohol and other intoxicating substances has increased over time as well.

The first step is to notice how often you feel helpless, sad, angry, irritable, hopeless, anxious or afraid. Some people may feel numb.

Keep track of how often you have trouble focusing on daily tasks or doing routine chores. Are there things that you used to enjoy doing that you stopped doing because of how you feel? Note any big changes in appetite, any substance use, body aches and pains, and problems with sleep.

These feelings may come and go over time. But if these feelings don't go away or make it hard to do your daily tasks, it's time to ask for help.

Get help when you need it

If you're feeling suicidal or thinking of hurting yourself, seek help.

• Contact your healthcare professional or a mental health professional.
• Contact a suicide hotline. In the U.S., call or text 988 to reach the 988 Suicide & Crisis Lifeline , available 24 hours a day, seven days a week. Or use the Lifeline Chat . Services are free and confidential.

If you are worried about yourself or someone else, contact your healthcare professional or mental health professional. Some may be able to see you in person or talk over the phone or online.

You also can reach out to a friend or loved one. Someone in your faith community also could help.

And you may be able to get counseling or a mental health appointment through an employer's employee assistance program.

Another option is information and treatment options from groups such as:

• National Alliance on Mental Illness (NAMI).
• Substance Abuse and Mental Health Services Administration (SAMHSA).
• Anxiety and Depression Association of America.

Self-care tips

Some people may use unhealthy ways to cope with anxiety around COVID-19. These unhealthy choices may include things such as misuse of medicines or legal drugs and use of illegal drugs. Unhealthy coping choices also can be things such as sleeping too much or too little, or overeating. It also can include avoiding other people and focusing on only one soothing thing, such as work, television or gaming.

Unhealthy coping methods can worsen mental and physical health. And that is particularly true if you're trying to manage or recover from COVID-19.

Self-care actions can help you restore a healthy balance in your life. They can lessen everyday stress or significant anxiety linked to events such as the COVID-19 pandemic. Self-care actions give your body and mind a chance to heal from the problems long-term stress can cause.

Take care of your body

Healthy self-care tips start with the basics. Give your body what it needs and avoid what it doesn't need. Some tips are:

• Get the right amount of sleep for you. A regular sleep schedule, when you go to bed and get up at similar times each day, can help avoid sleep problems.
• Move your body. Regular physical activity and exercise can help reduce anxiety and improve mood. Any activity you can do regularly is a good choice. That may be a scheduled workout, a walk or even dancing to your favorite music.
• Choose healthy food and drinks. Foods that are high in nutrients, such as protein, vitamins and minerals are healthy choices. Avoid food or drink with added sugar, fat or salt.
• Avoid tobacco, alcohol and drugs. If you smoke tobacco or if you vape, you're already at higher risk of lung disease. Because COVID-19 affects the lungs, your risk increases even more. Using alcohol to manage how you feel can make matters worse and reduce your coping skills. Avoid taking illegal drugs or misusing prescriptions to manage your feelings.

Take care of your mind

Healthy coping actions for your brain start with deciding how much news and social media is right for you. Staying informed, especially during a pandemic, helps you make the best choices but do it carefully.

Set aside a specific amount of time to find information in the news or on social media, stay limited to that time, and choose reliable sources. For example, give yourself up to 20 or 30 minutes a day of news and social media. That amount keeps people informed but not overwhelmed.

For COVID-19, consider reliable health sources. Examples are the U.S. Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO).

Other healthy self-care tips are:

• Relax and recharge. Many people benefit from relaxation exercises such as mindfulness, deep breathing, meditation and yoga. Find an activity that helps you relax and try to do it every day at least for a short time. Fitting time in for hobbies or activities you enjoy can help manage feelings of stress too.
• Stick to your health routine. If you see a healthcare professional for mental health services, keep up with your appointments. And stay up to date with all your wellness tests and screenings.
• Stay in touch and connect with others. Family, friends and your community are part of a healthy mental outlook. Together, you form a healthy support network for concerns or challenges. Social interactions, over time, are linked to a healthier and longer life.

Avoid stigma and discrimination

Stigma can make people feel isolated and even abandoned. They may feel sad, hurt and angry when people in their community avoid them for fear of getting COVID-19. People who have experienced stigma related to COVID-19 include people of Asian descent, health care workers and people with COVID-19.

Treating people differently because of their medical condition, called medical discrimination, isn't new to the COVID-19 pandemic. Stigma has long been a problem for people with various conditions such as Hansen's disease (leprosy), HIV, diabetes and many mental illnesses.

People who experience stigma may be left out or shunned, treated differently, or denied job and school options. They also may be targets of verbal, emotional and physical abuse.

Communication can help end stigma or discrimination. You can address stigma when you:

• Get to know people as more than just an illness. Using respectful language can go a long way toward making people comfortable talking about a health issue.
• Get the facts about COVID-19 or other medical issues from reputable sources such as the CDC and WHO.
• Speak up if you hear or see myths about an illness or people with an illness.

COVID-19 and health

The virus that causes COVID-19 is still a concern for many people. By recognizing when to get help and taking time for your health, life challenges such as COVID-19 can be managed.

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• Sawchuk CN (expert opinion). Mayo Clinic. March 25, 2024.

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