research question about social media addiction

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Research trends in social media addiction and problematic social media use: A bibliometric analysis

Alfonso pellegrino.

1 Sasin School of Management, Chulalongkorn University, Bangkok, Thailand

Alessandro Stasi

2 Business Administration Division, Mahidol University International College, Mahidol University, Nakhon Pathom, Thailand

Veera Bhatiasevi

Associated data.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Despite their increasing ubiquity in people's lives and incredible advantages in instantly interacting with others, social media's impact on subjective well-being is a source of concern worldwide and calls for up-to-date investigations of the role social media plays in mental health. Much research has discovered how habitual social media use may lead to addiction and negatively affect adolescents' school performance, social behavior, and interpersonal relationships. The present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013–2022. Bibliometric analysis was conducted on 501 articles that were extracted from the Scopus database using the keywords social media addiction and problematic social media use. The data were then uploaded to VOSviewer software to analyze citations, co-citations, and keyword co-occurrences. Volume, growth trajectory, geographic distribution of the literature, influential authors, intellectual structure of the literature, and the most prolific publishing sources were analyzed. The bibliometric analysis presented in this paper shows that the US, the UK, and Turkey accounted for 47% of the publications in this field. Most of the studies used quantitative methods in analyzing data and therefore aimed at testing relationships between variables. In addition, the findings in this study show that most analysis were cross-sectional. Studies were performed on undergraduate students between the ages of 19–25 on the use of two social media platforms: Facebook and Instagram. Limitations as well as research directions for future studies are also discussed.

Introduction

Social media generally refers to third-party internet-based platforms that mainly focus on social interactions, community-based inputs, and content sharing among its community of users and only feature content created by their users and not that licensed from third parties ( 1 ). Social networking sites such as Facebook, Instagram, and TikTok are prominent examples of social media that allow people to stay connected in an online world regardless of geographical distance or other obstacles ( 2 , 3 ). Recent evidence suggests that social networking sites have become increasingly popular among adolescents following the strict policies implemented by many countries to counter the COVID-19 pandemic, including social distancing, “lockdowns,” and quarantine measures ( 4 ). In this new context, social media have become an essential part of everyday life, especially for children and adolescents ( 5 ). For them such media are a means of socialization that connect people together. Interestingly, social media are not only used for social communication and entertainment purposes but also for sharing opinions, learning new things, building business networks, and initiate collaborative projects ( 6 ).

Among the 7.91 billion people in the world as of 2022, 4.62 billion active social media users, and the average time individuals spent using the internet was 6 h 58 min per day with an average use of social media platforms of 2 h and 27 min ( 7 ). Despite their increasing ubiquity in people's lives and the incredible advantages they offer to instantly interact with people, an increasing number of studies have linked social media use to negative mental health consequences, such as suicidality, loneliness, and anxiety ( 8 ). Numerous sources have expressed widespread concern about the effects of social media on mental health. A 2011 report by the American Academy of Pediatrics (AAP) identifies a phenomenon known as Facebook depression which may be triggered “when preteens and teens spend a great deal of time on social media sites, such as Facebook, and then begin to exhibit classic symptoms of depression” ( 9 ). Similarly, the UK's Royal Society for Public Health (RSPH) claims that there is a clear evidence of the relationship between social media use and mental health issues based on a survey of nearly 1,500 people between the ages of 14–24 ( 10 ). According to some authors, the increase in usage frequency of social media significantly increases the risks of clinical disorders described (and diagnosed) as “Facebook depression,” “fear of missing out” (FOMO), and “social comparison orientation” (SCO) ( 11 ). Other risks include sexting ( 12 ), social media stalking ( 13 ), cyber-bullying ( 14 ), privacy breaches ( 15 ), and improper use of technology. Therefore, social media's impact on subjective well-being is a source of concern worldwide and calls for up-to-date investigations of the role social media plays with regard to mental health ( 8 ). Many studies have found that habitual social media use may lead to addiction and thus negatively affect adolescents' school performance, social behavior, and interpersonal relationships ( 16 – 18 ). As a result of addiction, the user becomes highly engaged with online activities motivated by an uncontrollable desire to browse through social media pages and “devoting so much time and effort to it that it impairs other important life areas” ( 19 ).

Given these considerations, the present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013–2022. The study presents a bibliometric overview of the leading trends with particular regard to “social media addiction” and “problematic social media use.” This is valuable as it allows for a comprehensive overview of the current state of this field of research, as well as identifies any patterns or trends that may be present. Additionally, it provides information on the geographical distribution and prolific authors in this area, which may help to inform future research endeavors.

In terms of bibliometric analysis of social media addiction research, few studies have attempted to review the existing literature in the domain extensively. Most previous bibliometric studies on social media addiction and problematic use have focused mainly on one type of screen time activity such as digital gaming or texting ( 20 ) and have been conducted with a focus on a single platform such as Facebook, Instagram, or Snapchat ( 21 , 22 ). The present study adopts a more comprehensive approach by including all social media platforms and all types of screen time activities in its analysis.

Additionally, this review aims to highlight the major themes around which the research has evolved to date and draws some guidance for future research directions. In order to meet these objectives, this work is oriented toward answering the following research questions:

• (1) What is the current status of research focusing on social media addiction?
• (2) What are the key thematic areas in social media addiction and problematic use research?
• (3) What is the intellectual structure of social media addiction as represented in the academic literature?
• (4) What are the key findings of social media addiction and problematic social media research?
• (5) What possible future research gaps can be identified in the field of social media addiction?

These research questions will be answered using bibliometric analysis of the literature on social media addiction and problematic use. This will allow for an overview of the research that has been conducted in this area, including information on the most influential authors, journals, countries of publication, and subject areas of study. Part 2 of the study will provide an examination of the intellectual structure of the extant literature in social media addiction while Part 3 will discuss the research methodology of the paper. Part 4 will discuss the findings of the study followed by a discussion under Part 5 of the paper. Finally, in Part 7, gaps in current knowledge about this field of research will be identified.

Literature review

Social media addiction research context.

Previous studies on behavioral addictions have looked at a lot of different factors that affect social media addiction focusing on personality traits. Although there is some inconsistency in the literature, numerous studies have focused on three main personality traits that may be associated with social media addiction, namely anxiety, depression, and extraversion ( 23 , 24 ).

It has been found that extraversion scores are strongly associated with increased use of social media and addiction to it ( 25 , 26 ). People with social anxiety as well as people who have psychiatric disorders often find online interactions extremely appealing ( 27 ). The available literature also reveals that the use of social media is positively associated with being female, single, and having attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), or anxiety ( 28 ).

In a study by Seidman ( 29 ), the Big Five personality traits were assessed using Saucier's ( 30 ) Mini-Markers Scale. Results indicated that neurotic individuals use social media as a safe place for expressing their personality and meet belongingness needs. People affected by neurosis tend to use online social media to stay in touch with other people and feel better about their social lives ( 31 ). Narcissism is another factor that has been examined extensively when it comes to social media, and it has been found that people who are narcissistic are more likely to become addicted to social media ( 32 ). In this case users want to be seen and get “likes” from lots of other users. Longstreet and Brooks ( 33 ) did a study on how life satisfaction depends on how much money people make. Life satisfaction was found to be negatively linked to social media addiction, according to the results. When social media addiction decreases, the level of life satisfaction rises. But results show that in lieu of true-life satisfaction people use social media as a substitute (for temporary pleasure vs. longer term happiness).

Researchers have discovered similar patterns in students who tend to rank high in shyness: they find it easier to express themselves online rather than in person ( 34 , 35 ). With the use of social media, shy individuals have the opportunity to foster better quality relationships since many of their anxiety-related concerns (e.g., social avoidance and fear of social devaluation) are significantly reduced ( 36 , 37 ).

Problematic use of social media

The amount of research on problematic use of social media has dramatically increased since the last decade. But using social media in an unhealthy manner may not be considered an addiction or a disorder as this behavior has not yet been formally categorized as such ( 38 ). Although research has shown that people who use social media in a negative way often report negative health-related conditions, most of the data that have led to such results and conclusions comprise self-reported data ( 39 ). The dimensions of excessive social media usage are not exactly known because there are not enough diagnostic criteria and not enough high-quality long-term studies available yet. This is what Zendle and Bowden-Jones ( 40 ) noted in their own research. And this is why terms like “problematic social media use” have been used to describe people who use social media in a negative way. Furthermore, if a lot of time is spent on social media, it can be hard to figure out just when it is being used in a harmful way. For instance, people easily compare their appearance to what they see on social media, and this might lead to low self-esteem if they feel they do not look as good as the people they are following. According to research in this domain, the extent to which an individual engages in photo-related activities (e.g., taking selfies, editing photos, checking other people's photos) on social media is associated with negative body image concerns. Through curated online images of peers, adolescents face challenges to their self-esteem and sense of self-worth and are increasingly isolated from face-to-face interaction.

To address this problem the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) has been used by some scholars ( 41 , 42 ). These scholars have used criteria from the DSM-V to describe one problematic social media use, internet gaming disorder, but such criteria could also be used to describe other types of social media disorders. Franchina et al. ( 43 ) and Scott and Woods ( 44 ), for example, focus their attention on individual-level factors (like fear of missing out) and family-level factors (like childhood abuse) that have been used to explain why people use social media in a harmful way. Friends-level factors have also been explored as a social well-being measurement to explain why people use social media in a malevolent way and demonstrated significant positive correlations with lower levels of friend support ( 45 ). Macro-level factors have also been suggested, such as the normalization of surveillance ( 46 ) and the ability to see what people are doing online ( 47 ). Gender and age seem to be highly associated to the ways people use social media negatively. Particularly among girls, social media use is consistently associated with mental health issues ( 41 , 48 , 49 ), an association more common among older girls than younger girls ( 46 , 48 ).

Most studies have looked at the connection between social media use and its effects (such as social media addiction) and a number of different psychosomatic disorders. In a recent study conducted by Vannucci and Ohannessian ( 50 ), the use of social media appears to have a variety of effects “on psychosocial adjustment during early adolescence, with high social media use being the most problematic.” It has been found that people who use social media in a harmful way are more likely to be depressed, anxious, have low self-esteem, be more socially isolated, have poorer sleep quality, and have more body image dissatisfaction. Furthermore, harmful social media use has been associated with unhealthy lifestyle patterns (for example, not getting enough exercise or having trouble managing daily obligations) as well as life threatening behaviors such as illicit drug use, excessive alcohol consumption and unsafe sexual practices ( 51 , 52 ).

A growing body of research investigating social media use has revealed that the extensive use of social media platforms is correlated with a reduced performance on cognitive tasks and in mental effort ( 53 ). Overall, it appears that individuals who have a problematic relationship with social media or those who use social media more frequently are more likely to develop negative health conditions.

Social media addiction and problematic use systematic reviews

Previous studies have revealed the detrimental impacts of social media addiction on users' health. A systematic review by Khan and Khan ( 20 ) has pointed out that social media addiction has a negative impact on users' mental health. For example, social media addiction can lead to stress levels rise, loneliness, and sadness ( 54 ). Anxiety is another common mental health problem associated with social media addiction. Studies have found that young adolescents who are addicted to social media are more likely to suffer from anxiety than people who are not addicted to social media ( 55 ). In addition, social media addiction can also lead to physical health problems, such as obesity and carpal tunnel syndrome a result of spending too much time on the computer ( 22 ).

Apart from the negative impacts of social media addiction on users' mental and physical health, social media addiction can also lead to other problems. For example, social media addiction can lead to financial problems. A study by Sharif and Yeoh ( 56 ) has found that people who are addicted to social media tend to spend more money than those who are not addicted to social media. In addition, social media addiction can also lead to a decline in academic performance. Students who are addicted to social media are more likely to have lower grades than those who are not addicted to social media ( 57 ).

Research methodology

Bibliometric analysis.

Merigo et al. ( 58 ) use bibliometric analysis to examine, organize, and analyze a large body of literature from a quantitative, objective perspective in order to assess patterns of research and emerging trends in a certain field. A bibliometric methodology is used to identify the current state of the academic literature, advance research. and find objective information ( 59 ). This technique allows the researchers to examine previous scientific work, comprehend advancements in prior knowledge, and identify future study opportunities.

To achieve this objective and identify the research trends in social media addiction and problematic social media use, this study employs two bibliometric methodologies: performance analysis and science mapping. Performance analysis uses a series of bibliometric indicators (e.g., number of annual publications, document type, source type, journal impact factor, languages, subject area, h-index, and countries) and aims at evaluating groups of scientific actors on a particular topic of research. VOSviewer software ( 60 ) was used to carry out the science mapping. The software is used to visualize a particular body of literature and map the bibliographic material using the co-occurrence analysis of author, index keywords, nations, and fields of publication ( 61 , 62 ).

Data collection

After picking keywords, designing the search strings, and building up a database, the authors conducted a bibliometric literature search. Scopus was utilized to gather exploration data since it is a widely used database that contains the most comprehensive view of the world's research output and provides one of the most effective search engines. If the research was to be performed using other database such as Web Of Science or Google Scholar the authors may have obtained larger number of articles however they may not have been all particularly relevant as Scopus is known to have the most widest and most relevant scholar search engine in marketing and social science. A keyword search for “social media addiction” OR “problematic social media use” yielded 553 papers, which were downloaded from Scopus. The information was gathered in March 2022, and because the Scopus database is updated on a regular basis, the results may change in the future. Next, the authors examined the titles and abstracts to see whether they were relevant to the topics treated. There were two common grounds for document exclusion. First, while several documents emphasized the negative effects of addiction in relation to the internet and digital media, they did not focus on social networking sites specifically. Similarly, addiction and problematic consumption habits were discussed in relation to social media in several studies, although only in broad terms. This left a total of 511 documents. Articles were then limited only to journal articles, conference papers, reviews, books, and only those published in English. This process excluded 10 additional documents. Then, the relevance of the remaining articles was finally checked by reading the titles, abstracts, and keywords. Documents were excluded if social networking sites were only mentioned as a background topic or very generally. This resulted in a final selection of 501 research papers, which were then subjected to bibliometric analysis (see Figure 1 ).

Preferred reporting items for systematic reviews and meta-analysis (PRISMA) flowchart showing the search procedures used in the review.

After identifying 501 Scopus files, bibliographic data related to these documents were imported into an Excel sheet where the authors' names, their affiliations, document titles, keywords, abstracts, and citation figures were analyzed. These were subsequently uploaded into VOSViewer software version 1.6.8 to begin the bibliometric review. Descriptive statistics were created to define the whole body of knowledge about social media addiction and problematic social media use. VOSViewer was used to analyze citation, co-citation, and keyword co-occurrences. According to Zupic and Cater ( 63 ), co-citation analysis measures the influence of documents, authors, and journals heavily cited and thus considered influential. Co-citation analysis has the objective of building similarities between authors, journals, and documents and is generally defined as the frequency with which two units are cited together within the reference list of a third article.

The implementation of social media addiction performance analysis was conducted according to the models recently introduced by Karjalainen et al. ( 64 ) and Pattnaik ( 65 ). Throughout the manuscript there are operational definitions of relevant terms and indicators following a standardized bibliometric approach. The cumulative academic impact (CAI) of the documents was measured by the number of times they have been cited in other scholarly works while the fine-grained academic impact (FIA) was computed according to the authors citation analysis and authors co-citation analysis within the reference lists of documents that have been specifically focused on social media addiction and problematic social media use.

Results of the study presented here include the findings on social media addiction and social media problematic use. The results are presented by the foci outlined in the study questions.

Volume, growth trajectory, and geographic distribution of the literature

After performing the Scopus-based investigation of the current literature regarding social media addiction and problematic use of social media, the authors obtained a knowledge base consisting of 501 documents comprising 455 journal articles, 27 conference papers, 15 articles reviews, 3 books and 1 conference review. The included literature was very recent. As shown in Figure 2 , publication rates started very slowly in 2013 but really took off in 2018, after which publications dramatically increased each year until a peak was reached in 2021 with 195 publications. Analyzing the literature published during the past decade reveals an exponential increase in scholarly production on social addiction and its problematic use. This might be due to the increasingly widespread introduction of social media sites in everyday life and the ubiquitous diffusion of mobile devices that have fundamentally impacted human behavior. The dip in the number of publications in 2022 is explained by the fact that by the time the review was carried out the year was not finished yet and therefore there are many articles still in press.

Annual volume of social media addiction or social media problematic use ( n = 501).

The geographical distribution trends of scholarly publications on social media addiction or problematic use of social media are highlighted in Figure 3 . The articles were assigned to a certain country according to the nationality of the university with whom the first author was affiliated with. The figure shows that the most productive countries are the USA (92), the U.K. (79), and Turkey ( 63 ), which combined produced 236 articles, equal to 47% of the entire scholarly production examined in this bibliometric analysis. Turkey has slowly evolved in various ways with the growth of the internet and social media. Anglo-American scholarly publications on problematic social media consumer behavior represent the largest research output. Yet it is interesting to observe that social networking sites studies are attracting many researchers in Asian countries, particularly China. For many Chinese people, social networking sites are a valuable opportunity to involve people in political activism in addition to simply making purchases ( 66 ).

Global dispersion of social networking sites in relation to social media addiction or social media problematic use.

Analysis of influential authors

This section analyses the high-impact authors in the Scopus-indexed knowledge base on social networking sites in relation to social media addiction or problematic use of social media. It provides valuable insights for establishing patterns of knowledge generation and dissemination of literature about social networking sites relating to addiction and problematic use.

Table 1 acknowledges the top 10 most highly cited authors with the highest total citations in the database.

Highly cited authors on social media addiction and problematic use ( n = 501).

a Total link strength indicates the number of publications in which an author occurs.

Table 1 shows that MD Griffiths (sixty-five articles), CY Lin (twenty articles), and AH Pakpour (eighteen articles) are the most productive scholars according to the number of Scopus documents examined in the area of social media addiction and its problematic use . If the criteria are changed and authors ranked according to the overall number of citations received in order to determine high-impact authors, the same three authors turn out to be the most highly cited authors. It should be noted that these highly cited authors tend to enlist several disciplines in examining social media addiction and problematic use. Griffiths, for example, focuses on behavioral addiction stemming from not only digital media usage but also from gambling and video games. Lin, on the other hand, focuses on the negative effects that the internet and digital media can have on users' mental health, and Pakpour approaches the issue from a behavioral medicine perspective.

Intellectual structure of the literature

In this part of the paper, the authors illustrate the “intellectual structure” of the social media addiction and the problematic use of social media's literature. An author co-citation analysis (ACA) was performed which is displayed as a figure that depicts the relations between highly co-cited authors. The study of co-citation assumes that strongly co-cited authors carry some form of intellectual similarity ( 67 ). Figure 4 shows the author co-citation map. Nodes represent units of analysis (in this case scholars) and network ties represent similarity connections. Nodes are sized according to the number of co-citations received—the bigger the node, the more co-citations it has. Adjacent nodes are considered intellectually similar.

Two clusters, representing the intellectual structure of the social media and its problematic use literature.

Scholars belonging to the green cluster (Mental Health and Digital Media Addiction) have extensively published on medical analysis tools and how these can be used to heal users suffering from addiction to digital media, which can range from gambling, to internet, to videogame addictions. Scholars in this school of thought focus on the negative effects on users' mental health, such as depression, anxiety, and personality disturbances. Such studies focus also on the role of screen use in the development of mental health problems and the increasing use of medical treatments to address addiction to digital media. They argue that addiction to digital media should be considered a mental health disorder and treatment options should be made available to users.

In contrast, scholars within the red cluster (Social Media Effects on Well Being and Cyberpsychology) have focused their attention on the effects of social media toward users' well-being and how social media change users' behavior, focusing particular attention on the human-machine interaction and how methods and models can help protect users' well-being. Two hundred and two authors belong to this group, the top co-cited being Andreassen (667 co-citations), Pallasen (555 co-citations), and Valkenburg (215 co-citations). These authors have extensively studied the development of addiction to social media, problem gambling, and internet addiction. They have also focused on the measurement of addiction to social media, cyberbullying, and the dark side of social media.

Most influential source title in the field of social media addiction and its problematic use

To find the preferred periodicals in the field of social media addiction and its problematic use, the authors have selected 501 articles published in 263 journals. Table 2 gives a ranked list of the top 10 journals that constitute the core publishing sources in the field of social media addiction research. In doing so, the authors analyzed the journal's impact factor, Scopus Cite Score, h-index, quartile ranking, and number of publications per year.

Top 10 most cited and more frequently mentioned documents in the field of social media addiction.

The journal Addictive Behaviors topped the list, with 700 citations and 22 publications (4.3%), followed by Computers in Human Behaviors , with 577 citations and 13 publications (2.5%), Journal of Behavioral Addictions , with 562 citations and 17 publications (3.3%), and International Journal of Mental Health and Addiction , with 502 citations and 26 publications (5.1%). Five of the 10 most productive journals in the field of social media addiction research are published by Elsevier (all Q1 rankings) while Springer and Frontiers Media published one journal each.

Documents citation analysis identified the most influential and most frequently mentioned documents in a certain scientific field. Andreassen has received the most citations among the 10 most significant papers on social media addiction, with 405 ( Table 2 ). The main objective of this type of studies was to identify the associations and the roles of different variables as predictors of social media addiction (e.g., ( 19 , 68 , 69 )). According to general addiction models, the excessive and problematic use of digital technologies is described as “being overly concerned about social media, driven by an uncontrollable motivation to log on to or use social media, and devoting so much time and effort to social media that it impairs other important life areas” ( 27 , 70 ). Furthermore, the purpose of several highly cited studies ( 31 , 71 ) was to analyse the connections between young adults' sleep quality and psychological discomfort, depression, self-esteem, and life satisfaction and the severity of internet and problematic social media use, since the health of younger generations and teenagers is of great interest this may help explain the popularity of such papers. Despite being the most recent publication Lin et al.'s work garnered more citations annually. The desire to quantify social media addiction in individuals can also help explain the popularity of studies which try to develop measurement scales ( 42 , 72 ). Some of the highest-ranked publications are devoted to either the presentation of case studies or testing relationships among psychological constructs ( 73 ).

Keyword co-occurrence analysis

The research question, “What are the key thematic areas in social media addiction literature?” was answered using keyword co-occurrence analysis. Keyword co-occurrence analysis is conducted to identify research themes and discover keywords. It mainly examines the relationships between co-occurrence keywords in a wide variety of literature ( 74 ). In this approach, the idea is to explore the frequency of specific keywords being mentioned together.

Utilizing VOSviewer, the authors conducted a keyword co-occurrence analysis to characterize and review the developing trends in the field of social media addiction. The top 10 most frequent keywords are presented in Table 3 . The results indicate that “social media addiction” is the most frequent keyword (178 occurrences), followed by “problematic social media use” (74 occurrences), “internet addiction” (51 occurrences), and “depression” (46 occurrences). As shown in the co-occurrence network ( Figure 5 ), the keywords can be grouped into two major clusters. “Problematic social media use” can be identified as the core theme of the green cluster. In the red cluster, keywords mainly identify a specific aspect of problematic social media use: social media addiction.

Frequency of occurrence of top 10 keywords.

Keywords co-occurrence map. Threshold: 5 co-occurrences.

The results of the keyword co-occurrence analysis for journal articles provide valuable perspectives and tools for understanding concepts discussed in past studies of social media usage ( 75 ). More precisely, it can be noted that there has been a large body of research on social media addiction together with other types of technological addictions, such as compulsive web surfing, internet gaming disorder, video game addiction and compulsive online shopping ( 76 – 78 ). This field of research has mainly been directed toward teenagers, middle school students, and college students and university students in order to understand the relationship between social media addiction and mental health issues such as depression, disruptions in self-perceptions, impairment of social and emotional activity, anxiety, neuroticism, and stress ( 79 – 81 ).

The findings presented in this paper show that there has been an exponential increase in scholarly publications—from two publications in 2013 to 195 publications in 2021. There were 45 publications in 2022 at the time this study was conducted. It was interesting to observe that the US, the UK, and Turkey accounted for 47% of the publications in this field even though none of these countries are in the top 15 countries in terms of active social media penetration ( 82 ) although the US has the third highest number of social media users ( 83 ). Even though China and India have the highest number of social media users ( 83 ), first and second respectively, they rank fifth and tenth in terms of publications on social media addiction or problematic use of social media. In fact, the US has almost double the number of publications in this field compared to China and almost five times compared to India. Even though East Asia, Southeast Asia, and South Asia make up the top three regions in terms of worldwide social media users ( 84 ), except for China and India there have been only a limited number of publications on social media addiction or problematic use. An explanation for that could be that there is still a lack of awareness on the negative consequences of the use of social media and the impact it has on the mental well-being of users. More research in these regions should perhaps be conducted in order to understand the problematic use and addiction of social media so preventive measures can be undertaken.

From the bibliometric analysis, it was found that most of the studies examined used quantitative methods in analyzing data and therefore aimed at testing relationships between variables. In addition, many studies were empirical, aimed at testing relationships based on direct or indirect observations of social media use. Very few studies used theories and for the most part if they did they used the technology acceptance model and social comparison theories. The findings presented in this paper show that none of the studies attempted to create or test new theories in this field, perhaps due to the lack of maturity of the literature. Moreover, neither have very many qualitative studies been conducted in this field. More qualitative research in this field should perhaps be conducted as it could explore the motivations and rationales from which certain users' behavior may arise.

The authors found that almost all the publications on social media addiction or problematic use relied on samples of undergraduate students between the ages of 19–25. The average daily time spent by users worldwide on social media applications was highest for users between the ages of 40–44, at 59.85 min per day, followed by those between the ages of 35–39, at 59.28 min per day, and those between the ages of 45–49, at 59.23 per day ( 85 ). Therefore, more studies should be conducted exploring different age groups, as users between the ages of 19–25 do not represent the entire population of social media users. Conducting studies on different age groups may yield interesting and valuable insights to the field of social media addiction. For example, it would be interesting to measure the impacts of social media use among older users aged 50 years or older who spend almost the same amount of time on social media as other groups of users (56.43 min per day) ( 85 ).

A majority of the studies tested social media addiction or problematic use based on only two social media platforms: Facebook and Instagram. Although Facebook and Instagram are ranked first and fourth in terms of most popular social networks by number of monthly users, it would be interesting to study other platforms such as YouTube, which is ranked second, and WhatsApp, which is ranked third ( 86 ). Furthermore, TikTok would also be an interesting platform to study as it has grown in popularity in recent years, evident from it being the most downloaded application in 2021, with 656 million downloads ( 87 ), and is ranked second in Q1 of 2022 ( 88 ). Moreover, most of the studies focused only on one social media platform. Comparing different social media platforms would yield interesting results because each platform is different in terms of features, algorithms, as well as recommendation engines. The purpose as well as the user behavior for using each platform is also different, therefore why users are addicted to these platforms could provide a meaningful insight into social media addiction and problematic social media use.

Lastly, most studies were cross-sectional, and not longitudinal, aiming at describing results over a certain point in time and not over a long period of time. A longitudinal study could better describe the long-term effects of social media use.

This study was conducted to review the extant literature in the field of social media and analyze the global research productivity during the period ranging from 2013 to 2022. The study presents a bibliometric overview of the leading trends with particular regard to “social media addiction” and “problematic social media use.” The authors applied science mapping to lay out a knowledge base on social media addiction and its problematic use. This represents the first large-scale analysis in this area of study.

A keyword search of “social media addiction” OR “problematic social media use” yielded 553 papers, which were downloaded from Scopus. After performing the Scopus-based investigation of the current literature regarding social media addiction and problematic use, the authors ended up with a knowledge base consisting of 501 documents comprising 455 journal articles, 27 conference papers, 15 articles reviews, 3 books, and 1 conference review.

The geographical distribution trends of scholarly publications on social media addiction or problematic use indicate that the most productive countries were the USA (92), the U.K. (79), and Turkey ( 63 ), which together produced 236 articles. Griffiths (sixty-five articles), Lin (twenty articles), and Pakpour (eighteen articles) were the most productive scholars according to the number of Scopus documents examined in the area of social media addiction and its problematic use. An author co-citation analysis (ACA) was conducted which generated a layout of social media effects on well-being and cyber psychology as well as mental health and digital media addiction in the form of two research literature clusters representing the intellectual structure of social media and its problematic use.

The preferred periodicals in the field of social media addiction and its problematic use were Addictive Behaviors , with 700 citations and 22 publications, followed by Computers in Human Behavior , with 577 citations and 13 publications, and Journal of Behavioral Addictions , with 562 citations and 17 publications. Keyword co-occurrence analysis was used to investigate the key thematic areas in the social media literature, as represented by the top three keyword phrases in terms of their frequency of occurrence, namely, “social media addiction,” “problematic social media use,” and “social media addiction.”

This research has a few limitations. The authors used science mapping to improve the comprehension of the literature base in this review. First and foremost, the authors want to emphasize that science mapping should not be utilized in place of established review procedures, but rather as a supplement. As a result, this review can be considered the initial stage, followed by substantive research syntheses that examine findings from recent research. Another constraint stems from how 'social media addiction' is defined. The authors overcame this limitation by inserting the phrase “social media addiction” OR “problematic social media use” in the search string. The exclusive focus on SCOPUS-indexed papers creates a third constraint. The SCOPUS database has a larger number of papers than does Web of Science although it does not contain all the publications in a given field.

Although the total body of literature on social media addiction is larger than what is covered in this review, the use of co-citation analyses helped to mitigate this limitation. This form of bibliometric study looks at all the publications listed in the reference list of the extracted SCOPUS database documents. As a result, a far larger dataset than the one extracted from SCOPUS initially has been analyzed.

The interpretation of co-citation maps should be mentioned as a last constraint. The reason is that the procedure is not always clear, so scholars must have a thorough comprehension of the knowledge base in order to make sense of the result of the analysis ( 63 ). This issue was addressed by the authors' expertise, but it remains somewhat subjective.

Implications

The findings of this study have implications mainly for government entities and parents. The need for regulation of social media addiction is evident when considering the various risks associated with habitual social media use. Social media addiction may lead to negative consequences for adolescents' school performance, social behavior, and interpersonal relationships. In addition, social media addiction may also lead to other risks such as sexting, social media stalking, cyber-bullying, privacy breaches, and improper use of technology. Given the seriousness of these risks, it is important to have regulations in place to protect adolescents from the harms of social media addiction.

Regulation of social media platforms

One way that regulation could help protect adolescents from the harms of social media addiction is by limiting their access to certain websites or platforms. For example, governments could restrict adolescents' access to certain websites or platforms during specific hours of the day. This would help ensure that they are not spending too much time on social media and are instead focusing on their schoolwork or other important activities.

Another way that regulation could help protect adolescents from the harms of social media addiction is by requiring companies to put warning labels on their websites or apps. These labels would warn adolescents about the potential risks associated with excessive use of social media.

Finally, regulation could also require companies to provide information about how much time each day is recommended for using their website or app. This would help adolescents make informed decisions about how much time they want to spend on social media each day. These proposed regulations would help to protect children from the dangers of social media, while also ensuring that social media companies are more transparent and accountable to their users.

Parental involvement in adolescents' social media use

Parents should be involved in their children's social media use to ensure that they are using these platforms safely and responsibly. Parents can monitor their children's online activity, set time limits for social media use, and talk to their children about the risks associated with social media addiction.

Education on responsible social media use

Adolescents need to be educated about responsible social media use so that they can enjoy the benefits of these platforms while avoiding the risks associated with addiction. Education on responsible social media use could include topics such as cyber-bullying, sexting, and privacy breaches.

Research directions for future studies

A content analysis was conducted to answer the fifth research questions “What are the potential research directions for addressing social media addiction in the future?” The study reveals that there is a lack of screening instruments and diagnostic criteria to assess social media addiction. Validated DSM-V-based instruments could shed light on the factors behind social media use disorder. Diagnostic research may be useful in order to understand social media behavioral addiction and gain deeper insights into the factors responsible for psychological stress and psychiatric disorders. In addition to cross-sectional studies, researchers should also conduct longitudinal studies and experiments to assess changes in users' behavior over time ( 20 ).

Another important area to examine is the role of engagement-based ranking and recommendation algorithms in online habit formation. More research is required to ascertain how algorithms determine which content type generates higher user engagement. A clear understanding of the way social media platforms gather content from users and amplify their preferences would lead to the development of a standardized conceptualization of social media usage patterns ( 89 ). This may provide a clearer picture of the factors that lead to problematic social media use and addiction. It has been noted that “misinformation, toxicity, and violent content are inordinately prevalent” in material reshared by users and promoted by social media algorithms ( 90 ).

Additionally, an understanding of engagement-based ranking models and recommendation algorithms is essential in order to implement appropriate public policy measures. To address the specific behavioral concerns created by social media, legislatures must craft appropriate statutes. Thus, future qualitative research to assess engagement based ranking frameworks is extremely necessary in order to provide a broader perspective on social media use and tackle key regulatory gaps. Particular emphasis must be placed on consumer awareness, algorithm bias, privacy issues, ethical platform design, and extraction and monetization of personal data ( 91 ).

From a geographical perspective, the authors have identified some main gaps in the existing knowledge base that uncover the need for further research in certain regions of the world. Accordingly, the authors suggest encouraging more studies on internet and social media addiction in underrepresented regions with high social media penetration rates such as Southeast Asia and South America. In order to draw more contributions from these countries, journals with high impact factors could also make specific calls. This would contribute to educating social media users about platform usage and implement policy changes that support the development of healthy social media practices.

The authors hope that the findings gathered here will serve to fuel interest in this topic and encourage other scholars to investigate social media addiction in other contexts on newer platforms and among wide ranges of sample populations. In light of the rising numbers of people experiencing mental health problems (e.g., depression, anxiety, food disorders, and substance addiction) in recent years, it is likely that the number of papers related to social media addiction and the range of countries covered will rise even further.

Data availability statement

Author contributions.

AP took care of bibliometric analysis and drafting the paper. VB took care of proofreading and adding value to the paper. AS took care of the interpretation of the findings. All authors contributed to the article and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

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• Open access
• Published: 13 July 2023

Conceptualising social media addiction: a longitudinal network analysis of social media addiction symptoms and their relationships with psychological distress in a community sample of adults

• Deon Tullett-Prado 1 ,
• Jo R. Doley 1 ,
• Daniel Zarate 2 ,
• Rapson Gomez 3 &
• Vasileios Stavropoulos 2 , 4  

BMC Psychiatry volume  23 , Article number:  509 ( 2023 ) Cite this article

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Problematic social media use has been identified as negatively impacting psychological and everyday functioning and has been identified as a possible behavioural addiction (social media addiction; SMA). Whether SMA can be classified as a distinct behavioural addiction has been debated within the literature, with some regarding SMA as a premature pathologisation of ordinary social media use behaviour and suggesting there is little evidence for its use as a category of clinical concern. This study aimed to understand the relationship between proposed symptoms of SMA and psychological distress and examine these over time in a longitudinal network analysis, in order better understand whether SMA warrants classification as a unique pathology unique from general distress.

N  = 462 adults ( M age  = 30.8, SD age  = 9.23, 69.3% males, 29% females, 1.9% other sex or gender) completed measures of social media addiction (Bergen Social Media Addiction Scale), and psychological distress (DASS-21) at two time points, twelve months apart. Data were analysed using network analysis (NA) to explore SMA symptoms and psychological distress. Specifically, NA allows to assess the ‘influence’ and pathways of influence of each symptom in the network both cross-sectionally at each time point, as well as over time.

SMA symptoms were found to be stable cross-sectionally over time, and were associated with, yet distinct, from, depression, anxiety and stress. The most central symptoms within the network were tolerance and mood-modification in terms of expected influence and closeness respectively. Depression symptoms appeared to have less of a formative effect on SMA symptoms than anxiety and stress.

Conclusions

Our findings support the conceptualisation of SMA as a distinct construct occurring based on an underpinning network cluster of behaviours and a distinct association between SMA symptoms and distress. Further replications of these findings, however, are needed to strengthen the evidence for SMA as a unique behavioural addiction.

Peer Review reports

Introduction

In recent years, increased attention has been paid to phenomena of excessive social media use, impacting users’ lives in a way not dissimilar to substance addiction [ 1 ]. When in this state, known as ‘Problematic Social Media Use (PSMU), one’s social media usage occupies their daily life, to the extent that their other roles and obligations maybe compromised (e.g., family, romance, employment; [ 1 , 2 ]. In that line, PSMU impact has been demonstrated by its significant associations with mood disorder symptoms, low self-esteem, disrupted sleep, reduced physical health and social impairment [ 3 , 4 ]. Given that PSMU prevalence has been estimated to vary globally between 5%-10% of the social media users’ population [ 1 , 5 , 6 ], which exceeds 80% among more developed countries, such as Australia, and has the prospective to rise [ 7 , 8 ], PSMU related mental health concerns present compelling. Despite these, a rather disproportional paucity of longitudinal research regarding the nature, causes and treatment of PSMU has been repeatedly illustrated [ 1 , 9 ]. Attending such remarks, the present study aspires to examine the structure of PSMU’s most popular conceptualisation (as inspired by the behavioural addiction model [ 2 ]), whilst concurrently assessing its relationship with depression/distress behaviours via adopting and innovative network approach.

Conceptualizing problematic social media use

When attempting to conceptualise PSMU, the most employed definitions involve the so called “behavioural addiction model” [ 1 , 9 ]. Labelled as ‘Social Media Addiction’ (SMA), this conceptualization of PSMU is characterized by a deep fixation/drive towards the use of social media that has become uncontrollable and unhealthy. This model features a number of addiction symptoms drawn from those experienced by substance and gambling addicts, with six symptoms derived from Griffiths key-components of addiction [ 10 , 11 ]. These symptoms entail salience (i.e., preoccupation with social media usage), mood modification (i.e. using Social Media to alleviate negative moods/states), tolerance (i.e. requiring more social media engagement over a period of time in order to attain the same degree of satisfaction/mood modification), withdrawal (i.e. the experience of discomfort/distress/irritability/frustration, when attempting to cease/reduce use), relapse (i.e. failed attempts to control social media usage) and conflict/social impairment (i.e. social media use interferes with, and damages, one’s social life, emotional wellbeing, educational attainment, career and/or other activities/needs; [ 12 ]).

A number of separate theories have also been put forwards, such as models describing Problematic Social Media Use in terms of dysfunctional motivations or contexts for use [ 13 , 14 ]. Similarly, various instruments have been developed to reflect conceptual variability when assessing PSMU (e.g., Social Media Disorder Scale [ 15 ]; Bergen Social Media Addiction Scale [ 11 ]). However, the SMA model, as characterized by Griffiths 6 core components of addiction has seen the most use and acceptance, with a number of studies having evidenced the manifestation of those symptoms (e.g., tolerance, relapse, conflicts [ 11 , 16 ], identified motivations and risk factors similar to addiction (e.g., brain/neurological similarities between substance and SMA addicts [ 13 , 14 , 17 ]) and developed measurement tools based on this model [ 9 , 11 , 15 , 18 ]. Based on the above, the six symptom SMA model of PSMU, as measured via the Bergen Social Media Addiction Scale (BSMAS [ 11 ]) is employed going forward in this study.

Despite this level of acceptance, this “addiction” like definition of PSMU/SMA remains the object of controversy [ 19 ]. Criticisms abound regarding the model, with some labelling it a premature pathologizing of ordinary social media use behaviours with low construct validity and little evidence for its existence [ 19 , 20 ]. For example, Huang [ 21 ] highlight positive associations between social media and physical activity, denoting that not all social media use would necessarily represent a problematic behavior. Nonetheless, the lack of clarity surrounding the links between excessive social media use symptoms and markers of impairment, such as distress has been pointed out as cause for caution [ 19 ]. For instance, it has been argued that while preoccupation behaviours may be harmful when involving substances, they don’t necessarily carry the same weight in a behavioural addiction such as SMA [ 22 ]. In addition, it is argued that links between SMA and more well recognised disorders, such as Depression, may imply that SMA is in fact a secondary symptom of pre-existing depression, and not a distinct condition itself [ 19 ]. Given that research in this area is still highly exploratory these criticisms are difficult to dispel [ 9 ]. Thus, there is a need for research clarifying the nature of SMA, its longitudinal effects, and the relative importance of each SMA proposed symptom, as well as ways in which symptoms associate risk factors/negative outcomes.

SMA and longitudinal network analysis

One avenue of addressing this need could be offered via the implementation of longitudinal network analysis [ 23 ]. Network analysis is an exploratory approach of assessing constructs, as mirroring networks of symptoms/behaviours, where a number of variables/behaviours are examined together, whilst information is simultaneously collected regarding their inter-relationships and relative influence, so as to create a graphical ‘network’ (i.e., visualization of the construct’s underpinning behaviours; [ 23 , 24 , 25 ]). This analysis allows one to examine a set of symptoms from an utterly different viewpoint than traditional latent-variable perspectives. Rather than viewing symptoms as resulting from the presence of a latent construct (SMA for example), network analysis assumes symptoms are formative. Which is to say, as causes in themselves, interacting with each other and with other risk factors/negative outcomes to compose/form the “disorder” [ 24 ]. This allows the unique relationships, known as “edges”, between all considered variables/behaviours/manifestations, called “nodes”, to be observed, in a capacity not available with traditional structural equation modelling (SEM [ 26 ]). For example, examination of the so called symptom “centrality” (i.e. relative influence of each distinct symptom on other symptoms/behaviours included in an examined network), instead of symptom severity, may enable the detection of symptoms/behaviours with the largest influence on others, and thus contribute in evaluating: a) their “central” (or more peripheral role) in defining a proposed disorder (e.g. SMA), and; b) their targeted priority in a potential intervention program [ 27 ]. This can be done in great detail with separate centrality indices providing an indication of: a) the summed associations between a symptom/behaviour and all others examined (i.e., strength; Expected Influence in the case of psychopathology); b) the degree to which a symptom serves as an intermediary between others (i.e. betweenness) and; c) how closely a symptom aligns with others (i.e., closeness [ 28 ]). Furthermore, similar centrality relationships between distinct clusters of symptoms can be examined, with the so called “bridge” (i.e. a point that connects two distinct groups of behaviours) centrality indices (i.e. bridge strength; bridge expected influence; bridge betweenness and closeness) providing indications of which symptoms bind distinct disorders, such as SMA and depression together, either serving as intermediaries between disorders and/or by being more proximal to other disorders [ 28 ].

Such detailed examination of the relationships between symptoms, and clusters of symptoms, can further serve to test the veracity of models and constructs, which is particularly important for solidifying the occurrence of SMA [ 19 ]. For example, if the symptoms/behaviours informing a model, don’t relate at all, or accumulate into tight, separate ‘clusters’, then the construct may not be valid [ 29 ]. Additionally, with testing identical construct networks across two or more timepoints, the over-time stability of a proposed network can be examined, further validating a given construct (i.e., if the SMA symptoms’ network remains stable over time, then the construct is likely experienced longitudinally similarly [ 30 ]).

Aside of considering the stability of a network over time, network analysis procedures enable attaining stability coefficients for the edge weights and centrality indicators irrespective of the population/data examined via the use of case-dropping bootstrapping to examine the potential variance in these indices (i.e. network analysis indices such as strength and/or expected influence are re-estimated based on various alternative compositions/ re-samples of the data considered [ 31 , 32 ]. Unstable indices, either population-wise or over time are invalid, and their use is generally dismissed [ 33 ]. Finally, network analysis gives one the opportunity to evaluate not only the relationships of behaviours being considered as composing a single disorder, but also to examine how these distinct disorder informing symptoms/behaviours may interact with other separate comorbid disorders (i.e. in this case SMA behaviours and depression/ anxiety [ 31 ]). This allows the examination of how these variables formatively interact with one another, as well as indicating their separate/distinct concurrent validity [ 34 ].

Indeed, the need of securing such information regarding the distinct proposed SMA symptoms and their associations with comorbid depression and/or distress behaviours experienced is reinforced by recent item response theory (IRT) and network analysis findings of responses on the Bergen Social Media Addiction Scale [ 35 , 36 ]. Stănculescu [ 35 ] identified SMA behaviours of “salience” and “withdrawal” as having the highest centrality, whilst SMA “relapse” behaviours as having the lowest centrality, in the context of the 6 SMA symptoms consisting of a single unitary cluster with strong inter-relations. However, these findings despite constituting an important step, present limited in a number of ways. Firstly, they are derived from a Romanian sample ( N  = 705), where specific cultural characteristics may apply, restricting their generalizability to different populations. Secondly, due to being cross-sectional they don’t allow the examination of the stability of the network associations over-time [ 29 , 31 , 32 ]. Thirdly, Stănculescu’s [ 35 ] examination of the SMA symptom network only took expected influence into account considering centrality and did not consider the significance of differences in the centrality of nodes. Finally, the network examined by Stănculescu [ 35 ] involved no covariates aside of the 6 SMA symptoms. Thus, the extent of differentiation of various SMA behaviours/criteria from comorbid conditions and/or their specific associations with other commonly proposed SMA risk factors and negative outcomes (e.g. depression, anxiety) could not be established [ 37 ]. To contribute to the available knowledge in the field, the present study aims to use network analysis modelling to longitudinally examine SMA symptoms in conjunction with commonly proposed comorbid excessive digital media usage conditions involving experiencing distress (i.e., depression and anxiety [ 37 , 38 , 39 ]).

Distress and SMA

Psychological distress is defined as a state of psychological suffering characterized by anxiety, depression and stress, and often serves as a general measure of mental health [ 37 , 40 ]. In this capacity, investigating the ways in which SMA and distress behaviours interact, can potentially produce a clearer understanding for how a person’s mental health could be distinctly affected by the separate symptoms of SMA and/or the vice versa (e.g., Is it SMA related preoccupation, tolerance and/or withdrawal more related to anxiety and/or depression experiences?). As distress involves some of the most well researched comorbidities of SMA (e.g., depression, anxiety), there is a wealth of prior research indicating the presence of distress-SMA interactions [ 41 , 42 ]. For instance, different aspects of social media use, such as the purpose of using social media (e.g., adaptive/maladaptive coping mechanisms [ 43 ]), their preferred social media activities, as well as behaviours of excessive social media usage have been consistently associated with an individual’s proneness/risk for depression, anxiety and stress [ 41 , 42 ]. Such links tend to be more evident in younger populations, where social media use often drives/underpins psychological distress for a proportion of users (e. g. a developing individual might feel distressed for deviating from what is presented as ideal or common by their peers online [ 44 ]). A wide variety of explanations have been put forth as potential reasons for such distress-SMA links involving: a) distressed individuals excessively utilizing social media use as a way to cope; b) the deleterious effects excessive social media use has on sleep, time management, physical activity, the development of social skills and; c) the near constant access social media provides to information of others, prompting comparisons and negative social interactions [ 42 ]. However, these, independent findings present as fragmented, the clinically relevant, over-time links/associations between specific SMA symptoms and the levels of depression, anxiety and stress one experiences remaining unclear. Such clinically important knowledge can be offered by longitudinal network analysis, which has not been yet, to the best of the authors’ knowledge, attempted concerning these variables.

The findings of such an analysis are envisaged to also have significant epidemiological utility. Given the acknowledged connection between psychological distress and SMA behaviours [ 41 , 42 ], and the noted drive of psychologically distressed individuals towards coping strategies involving escapism via social media facilitated pleasurable activities [ 44 ], it is possible-and indeed argued by some-that PSMU may not in fact represent an addiction (the SMA model) but simply be a secondary symptom of distress [ 19 ]. By examining the SMA model in conjunction with symptoms of distress, the connections between the SMA symptoms and Distress symptoms can be demystified with detail, their bridges can be identified, whilst deeper insight may be gleaned into the relationship between Distress and SMA.

The present study

Prompted by the above literature, the present study aimed to contribute to the field via innovatively, longitudinally, examining a normative, community sample of social media users, assessed across two time points, one year apart, regarding both their SMA and distress behaviours. Specifically, it assessed their responses via advanced longitudinal network analysis’ modelling, enhanced by the use of machine learning algorithms to increase knowledge regarding: a) the validity/sufficiency of the widely popular SMA conceptualization; b) persistent differential diagnosis considerations regarding SMA and distress conditions entailing depression, anxiety and stress and; c) pivotal/central behaviours considering SMA manifestations over time. Thus, the following three aims were devised: 1) To reveal/describe the network structure of the six SMA symptoms and symptoms of depression, anxiety and stress; 2) To examine potential clustering in this revealed SMA-distress network, as well as to identify any specific bridges or routes between the clusters in this network, and; 3) To examine the stability of the revealed SMA-distress network over time and across different potential sample compositions.

Participants

An online sample of adult, English speaking participants aged 18 to 64 who were familiar with social media [ N  = 462, M age  = 30.8, SD age  = 9.23, n males  = 320 (69.3%), n females  = 134, (29%), n other  = 9, (1.9%); 968 complete responses wave 1- 506 attrition between waves = 462] was assessed across two time points, 12 months apart. Acknowledging that adequate sample size rules of thumb are still explored for longitudinal network analysis [ 45 ], the current sample size well exceeds the threshold of 350 recommended for sparse networks up to 20 nodes in order to accurately estimate moderate sensitivity, high specificity and likely high edge weights correlations [ 46 ]. Furthermore, the 53.27% attrition ( N  = 506) between the two waves of data collection was studied. Specifically, attrition/retention was inserted as an independent dummy coded variable (i.e. 1 = attrition, 0 = retention between wave 1 and wave 2) to assess its associations with sociodemographic characteristics of the sample (via crosstabulation, X 2 ), as well with SMA, depression, anxiety and stress rates (via t test). There were no significant associations between social media scores at time-point 1 and 2 ( Welch’s t [953]  = 1.60, p  = 0.11, Cohen’s d  = 0.10). Moreover, older straight males showed decreased attrition rates (Age: Welch’s t [960]  = -4.05, p  < 0.01, Cohen’s d  = -0.26; Gender: χ 2 [2] = 12.4, p  < 0.01, Cramer’s V  = 0.11); however, all differences represented a small effect size. In terms of sociodemographic, variations were observed, with very significant amounts of our sample heralding from diverse backgrounds. For example, 38.1% of the sample heralded from non-white backgrounds and 30.5% of the sample was female or nonbinary. See Table 1 for the sociodemographic information of those addressing both waves and included in the current analyses.

Aside of collecting socio-demographic information the following instruments were employed for the current study:

Bergen Social Media Addiction Scale (BSMAS; [ 11 ] )

The BSMAS measures the severity of one’s experience of the six proposed SMA symptoms via an equivalent number of items that ask to which degree certain behaviours associated with these symptoms relate to one’s own life (i.e., salience, tolerance, mood modification, relapse, withdrawal and conflict [ 11 ]). The items of the BSMAS include “ You spend a lot of time thinking about social media or planning how to use it ” (salience), “You feel an urge to use social media more and more” (tolerance), “You use social media in order to forget about personal problems” (mood modification), “You have tried to cut down on the use of social media without success” (Relapse), “You become restless or troubled if you are prohibited from using social media” (withdrawal) and “You use social media so much that it has had a negative impact on your job/studies” [ 11 ]. These items are rated on a 5-point scale scored from 1 (very rarely) to 5 (very often), with higher scores indicating a greater experience of SMA Symptoms [ 11 ]. A total score ranging between 6 and 30 is comprised by the accumulation of the different items’ points reflecting overall SMA behaviors. Considering the current sample, Cronbach’s α and the McDonalds ω internal reliability indices were both 0.88 for time point one and increased to 0.90 for time point two.

Depression, Anxiety and Stress Scales-1 (DASS-21; [ 47 ] )

The DASS measures distress experiences and comprises 21 items, subdivided into three equal subscales (7 items each) addressing depression, anxiety and stress respectively [ 47 ]. Items examine distress behaviors with a 4-point likert-type scale ranging from 0 (did not apply) to 3 (applied most of the time). Total scores for each dimension are derived by the accumulation of the relevant items’ points ranging between 0–21 for the three factors. Considering time point 1, the Cronbach’s α indices for the subscales of depression, anxiety and stress were 0.94, 0.85 and 0.88 respectively and their corresponding McDonalds ω reliabilities were 0.94, 0.86 and 0.88. For time point 2, the same Cronbach α reliabilities were 0.93, 0.85 and 0.86 and their McDonalds ω reliabilities were 0.93, 0.86 and 0.86.

Approval was received from the Victoria University Human Research Ethics Committee (HRE20-169) and data for both time points was collected between 2020 and 2022. Time point 1 data ( N t1  = 968) was collected via an online survey link distributed via social media (e. g. Facebook; Instagram; Twitter), digital forums (e.g., reddit) and the Victoria University learning management system. The link first took potential participants to the Plain Language Information Statement (PLIS), which informed about the study requirements, responses’ anonymity and free of penalty withdrawal rights. After completing this step, eligible participants were asked to voluntarily provide their email address to be included in prospective data collection wave(s), and to digitally sign the study consent form (box ticking). Twelve months later (between August 2021 and August 2022), follow up emails involving an identical survey link (i.e., PLIS, email provision for the second wave, consent form and survey questions) were sent out for those interested to participate in the second data collection wave ( N t2  = 462). Participation in this study was voluntary.

Statistical analyses

A network model involving the six BSMAS symptoms and three DASS subscales was estimated for the two timepoints using the qgraph and networktools R packages [ 32 , 48 ]. Network models involve the creation of a network nodes and edges, where nodes represent considered variables/observations and edges the relationships between them [ 49 ]. Stronger relationships/edges are represented by thicker, darker lines with the distance between variables/nodes indicating their relevance/association (closer = higher relevance) and the colour indicating the direction of the relationship (Blue = positive, red = negative). This is done in the present case via the use of zero order correlations (i.e., no control for the influence of any other variables) combined with a graphical Least Absolute Shrinkage and Selection Operator algorithm (g-lasso; [ 49 ]) employed to shrink partial correlations to zero. Practically, this reduces the chance of false positives (i.e., Type 1 error), providing more precise judgements about the relationships between variables, whilst concurrently pruning excessively weak links to simplify networks [ 50 ].

Cross-sectional network stability

Once network models are estimated across time points, their respective centrality, edge weights and bridge values are assessed [ 49 ]. Centrality measures used here involve: a) degree (i.e., the number of links/edges held by each node); b) betweenness (i.e. the number of times a node lies on the shortest path between other nodes); c) closeness (i.e. the ‘closeness’ of each node to all other nodes); d) eigenvector (i.e. node centrality based not the node’s connections and additionally the centrality of the nodes they are connected with)] and; d) the ‘expected influence’ of a node for the whole network [ 51 ]. The latter accounts for negative influences/edges, promotes the overall stability in the network, and it is recommended for psychopathological networks [ 29 ]. Finally, bridge values represent the rate of nodes serving as connections between distinct network clusters and are measured via bridge expected influence indices [ 48 ].

The prerequisite for estimating these values is calculating their stability coefficients across time points. These denote the estimated maximum number of cases that can be dropped from the data to retain, with 95% probability, a correlation of at least 0.7 (default) between original network indices and those computed with less cases with an acceptable minimum probability of > 0.25 and preferably > 0.5 [ 32 ]. These were calculated using a modified version of the bootnet package with an end coefficient representing the proportion of the original sample that can be dropped before the centrality, bridge and edge weight values vary significantly [ 32 ].

Cross sectional network characteristics

Once network stability is confirmed, the networktools package estimates the centrality, edge weight and bridge indices and graphs the network. Judgements regarding differences in centrality across nodes or in the strength of edges are made using the centrality/edge difference tests via the bootnet R package [ 32 ]. These construct a confidence interval between the two regarded results, adjusted so that the lower the stability the greater the interval, with the difference deemed non-significant if the points are within it.

Stability of the network across time

To compare network stability across time points, the NetworkComparisonTest package is employed to specifically estimate their variance in terms of the global network structure, the global strength of the nodes, edges and centrality. Each of these tests is carried out in succession, with the latter two tests only being conducted by the package if the first two detected significant differences (i.e., if the networks across the two time points do not differ significantly, there is no point examining differences in more specificity; [ 52 ]). P -values less than 0.05 for these tests indicate significant differences.

Network generation and stability

Network Analyses generated two networks, one for each timepoint, depicted in Figs. 1 and 2 . Edge strengths and calculated centrality statistics for time point 1 are featured in Tables 2 and 3 , and for time point 2 in Tables 4 and 5 . Note that within the following figures, the BSMAS symptoms of salience, tolerance, mood modification, relapse, withdrawal and conflict are referred to as BSMAS_1, BSMAS_2, BSMAS_3, BSMAS_4, BSMAS_5 and BSMAS_6 respectively.

Network of the BSMAS symptoms and DASS subscales at time point 1

Network of the BSMAS symptoms and DASS subscales at time point 2

The network at time point one showed excellent stability in terms of its basic structure (edge stability coefficient = 0.75, expected influence centrality stability coefficient = 0.60) and marginal stability regarding secondary measures of centrality (closeness centrality stability coefficient = 0.13, betweenness centrality stability coefficient = 0.05). In terms of bridges between network clusters, stability ranged from acceptable (bridge expected influence stability coefficient = 0.36), to marginal (bridge betweenness stability coefficient = 0.0) to insufficient (bridge closeness stability coefficient = 0.0).

These structural network characteristics were shared with the network at time point two both in terms of basic structure (edge stability coefficient = 0.75, expected influence centrality stability coefficient = 0.60) and secondary measures of centrality (closeness centrality stability coefficient = 0.13, betweenness centrality stability coefficient = 0.05). Though the bridges between clusters featured greater stability than time point 1 (bridge expected influence stability coefficient = 0.52, bridge betweenness = 0.05, bridge closeness = 0.21).

With all necessary structural measure’s stability within acceptable limits, further analysis of the network structures and network comparison was undertaken. However, given the marginal to unacceptable stability of both closeness and betweenness as measures of centrality, it was deemed that results from these measures cannot be safely generalised, or safely used to draw inferences about the data. Thus, these measures are only considered in the following as potential indicators that may point to avenues of further investigation, unless a result of 0.0 was scored on their stability coefficient, in which case they are completely disregarded.

Network characteristics at Time Point 1

Figure  3 depicts the expected influence of all nodes at time point 1, and Fig.  4 depicts centrality difference tests determining the significance of differences in expected influence between all nodes, with black squares indicating significant differences. In terms of overall centrality, stress had the most and strongest connections with other nodes. Stress had expected influence significantly greater than the majority of nodes, with the exception of anxiety and the BSMAS symptoms of tolerance and mood modification (Items 2 & 3). These BSMAS symptoms formed a consistent plateau of centrality, significantly above the symptoms of Relapse and Withdrawal (Item 4 & 5 respectively). Depression was relatively low in centrality, with a result significantly lower than every other node except relapse and withdrawal.

Expected Influence across all nodes at time point 1

Centrality difference tests of Expected Influence at time point 1

Accordingly, Fig.  5 depicts nodes’ closeness and betweenness at time point 1, while Figs. 6 , 7 depict centrality difference tests determining the significance of differences in betweenness and closeness, with black squares indicating a significant difference. In terms of the number of times a node was on the shortest path (i.e., betweenness), there were no significant differences. In terms of the distance between nodes (i.e., closeness), BSMAS symptoms of mood modification and withdrawal displayed the greatest centrality, with each displaying significantly higher centrality in the network than the DASS subscales.

Closeness and betweenness across all nodes at time point 1

Centrality difference tests of betweenness at time point 1

Centrality difference tests of closeness at time point 1

Figure  8 depicts edge difference tests, indicating that the edges between anxiety and stress, depression and stress, and between the BSMAS symptoms of salience and tolerance were significantly stronger than those of other nodes.

Edges’ difference tests at time point 1

Bridge characteristics at Time Point 1

Figures  9 and 10 depict bridge expected influence, closeness and betweenness centralities between the BSMAS symptoms and the DASS subscales. SMA symptoms of mood modification and conflict demonstrated markedly higher expected influence connections with the DASS subscales cluster than other SMA symptoms. With regards to the DASS subscales, anxiety and stress were in a similar position, with a bridge expected influence on the BSMAS symptoms substantially greater than that of depression (see Fig.  9 ). In terms of the proximity/closeness between nodes in the two subgroups, the BSMAS symptom of mood modification (Item 3) and withdrawal (Item 5) were the most proximal to the distress subgroup, with depression serving as the closest connecting point.

Bridge Expected Influence Centrality at time point 1

Bridge Closeness Centrality at time point 1

Network characteristics at Time Point 2

Figure  11 depicts the expected influence of all nodes at time point 2, whilst Fig.  12 depicts the significance of nodes’ differences in terms of their expected influence. The highest overall centrality in terms of expected influence was demonstrated by the BSMAS symptom of tolerance (Item 2), which was closely followed by the DASS subscale of stress. As is evidenced in Fig.  12 , both stress and tolerance were significantly greater in their expected influence centrality than the other network nodes.

Expected Influence across all nodes at time point 2

Centrality difference tests of Expected Influence at time point 2

Figures  13 and 14 depict the betweenness and closeness respectively of all nodes at time point 2, whilst Figs. 15 and 16 depict centrality difference tests determining the significance of differences in betweenness and closeness respectively. No significant differences in the number of times a node was on the shortest path (i.e., betweenness) identified between the nodes, nor were there any nodes significantly higher in closeness, with the exception of withdrawal (Item 5).

Betweenness across all nodes at time point 2

Closeness across all nodes at time point 2

Centrality difference tests of betweenness at time point 2

Centrality difference tests of closeness at time point 2

Figure  17 depicts edge difference tests at time point 2. As with time point 1, the edges between anxiety and stress, depression and stress, and between the BSMAS symptoms of salience and tolerance (Items 1 & 2) were significantly stronger than those between other nodes. Additionally, the connection between the BSMAS symptoms of tolerance and mood modification (Items 2 & 3) was a significantly stronger connection than over half of those assessed.

Edges’ difference tests at time point 2

Bridge characteristics at Time Point 2

Figures  18 , 19 and 20 depict bridge centralities between the BSMAS symptoms cluster and the DASS subscales cluster at time point 2. As in time point 1, the SMA symptoms of mood modification (Item 3) and conflict (Item 6) bridged the SMA behaviours cluster to the DASS subscales cluster via the nodes of anxiety and stress. These results were displayed in both the number and strength of connections between these nodes (expected influence centrality) and the number of times these nodes were used as connecting joints in paths between other nodes in these two networks (betweenness centrality). Further, in terms of the proximal distance between nodes in the two subgroups, the BSMAS symptom of conflict was the most central symptom, with anxiety and stress being the most proximal distress experiences.

Bridge Expected Influence Centrality at time point 2

Bridge Closeness Centrality at time point 2

Bridge Betweenness Centrality at time point 2

Longitudinal network comparison

Finally, a network invariance test revealed no significant differences between the network at time point 1 and time point 2 in terms of global network invariance ( p  = 0.36) and global strength Invariance ( p  = 0.42).

The rapid expansion of social media use has generated concerns regarding the development of PSMU behaviours. These have been noted to closely resemble those displayed in substance/behavioural addictions [ 1 , 2 ]. In that line, a portion of scholars have defined these behaviour as social media addiction (SMA) and have advocated in favour of describing it via the lenses of the components model of addiction framework (i.e. salience; mood-modification; tolerance; relapse; withdrawal; losing of interest into other activities/functional impairment; [ 1 , 9 ]. Such suggestions have been criticised as accommodating the risk of pathologizing common everyday behaviours, such as the use of social media, and lacking validity due to adhering to substance abuse criteria/behaviours that may fail to correctly depict this emerging condition [ 19 , 20 ]. Additionally, there is a lack of clarity regarding the details of links between excessive use symptoms and markers of impairment, such as distress, which cause further doubts [ 19 , 20 ]. Finally, the occurrence of SMA behaviour as an independent diagnostic condition has been contested on the basis of SMA related behaviours constituting biproducts/ secondary symptoms of primarily distress conditions such as depression, anxiety and stress [ 19 , 20 ].

To address these concerns, the current research innovated via longitudinally assessing a normative cohort of adult social media users twice over a period of two years considering concurrently their SMA and depression, anxiety and stress self-reported experiences. Advanced longitudinal network analysis models, enriched via the LASSO algorithm, were calculated for both time points [ 29 , 32 ]. These aimed to firstly clarify whether SMA criteria, as described on the basis of the components model of addiction, formed indeed an underpinning network of behaviours, stable over time and across different sample compositions [ 10 ]. Answering this question would indicate that the construct is rather formative and not reflective (i.e., it is not just a conception of scholars or a sample specific construct, while it is steadily reflected the same way over time [ 19 , 20 ]).

Secondly, the analysis aimed to dispel to what extent SMA behaviours may mix/blend or closely relate to distress behaviours such as depression, anxiety and stress [ 53 ]. If the latter was to be true, then the SMA and distress components of the network would be expected to mix and not to represent distinctly different network clusters (i.e. SMA and distress related behaviours would represent different behavioural network clusters and thus should be classified independently). Thirdly, it was aimed to identify key/central/pivotal behaviours in the broader network, that should be prioritized in prevention and/or intervention for those presenting with SMA and/or comorbid depression, anxiety and stress (i.e. central nodes of the network with higher expected influence). Findings indicated that SMA behaviours/criteria, as per the components model of addiction, do constitute a formative network of symptoms, which is not sample or time specific. Furthermore, the SMA behaviours cluster was distinct to that of depression, anxiety and stress experiences across both measurements, favouring its classification as an independent diagnostic condition. Lastly, mood modification appeared to be consistently (across both time points) a central network node and has been facilitating as the main bridge primarily with distress symptoms of stress and anxiety rather than depression.

SMA and distress network

As summarized prior, results portrayed a stable overtime network cluster of SMA symptoms, which is associated yet distinct, to the distress related cluster of nodes composed by depression, anxiety and stress. These findings appear to align with the recent SMA, cross-sectional, network analysis study of Romanian data, which also supported the SMA defined behaviours of salience, tolerance, mood-modification, withdrawal, relapse and functional impairment being closely related and informing a clear cluster of nodes [ 35 ]. Therefore, the present study argues in favour of the idea of SMA operating as a formative construct, which occurs independently of the conception of scholars (i.e. does not only reflect theoretical conceptualizations [ 19 , 20 ]. This provides an indication in favour of those who support the SMA conceptualization and potentially the introduction of a distinct diagnostic category to capture the syndrome [ 35 , 36 ]. In that context, SMA behaviours related to mood-modification appeared to be central across both time points, reinforcing the idea of addictions, such as SMA, acting the problematic solution (e.g., way to either experience more positive or buffer negative emotions) of the distress generated by other problems [ 53 ]. Nevertheless, one cannot exclude the need of additional nodes, such as those likely reflecting “deception behaviours associated to the use of social media” (e.g. an individual concealing the amount of time they consume on social media usage) and/or relationship difficulties (e.g. as with other forms of addictions, a person may be marginalized within their social surrounding) to better describe the phenomenon [ 54 ]. Thus, although findings support the six, adjusted to the abuse of social media, addiction criteria operating as a distinct, SMA underpinning, formative network, the need for additional behavioural nodes to better describe the condition cannot be excluded.

Despite these, and in contrast to the results of the Stănculescu [ 35 ] Romanian study, where salience and withdrawal were identified as the most ‘central’ symptoms, the current study identified tolerance and mood-modification as the most highly central in terms of expected influence and closeness respectively. A possible explanation for this discrepancy may refer to the more rigorous methodology and wider aims applied in the current study, compared to that conducted by Stănculescu [ 35 ]. Firstly, the current analysis examined network stability across different resamples (i.e., potential population compositions) and over time (i.e. longitudinally), which was not the case in the Stănculescu [ 35 ] study. Secondly, the present study thoroughly examined centrality differences based on t-test comparisons in conjunction with the visual graph/network inspection, whilst such comparisons were not reported in the Romanian study [ 35 ]. Thirdly, centrality indices informing the present findings were referring to the extended network of SMA and distress behaviours, and not the narrower network of SMA behaviours only [ 35 ]. Thus, it is likely that whilst salience and withdrawal may be more central in the context of SMA behaviours, without taking into consideration concurrent depression, anxiety and stress behaviours; tolerance and mood modification maybe more pivotal in the broader context of SMA and distress comorbidities together. Finally, it is also likely that cultural differences between the two samples may alternate the experience of SMA between the populations, such that withdrawal and salience maybe more central for the Romanian sample [ 35 ]. Such differences inevitably invite further investigation regarding the cross-cultural invariance of the SMA network, as with other behavioural addictions related to the abuse of digital media (see gaming disorder [ 53 , 54 ]).

The current findings were also revealing considering the differential diagnosis concerns referring to SMA behaviours constituting primarily a secondary symptom of distress behaviours related to depression, anxiety and stress, rather than a distinct condition itself [ 54 ]. Specifically, network models across both time points consistently revealed two distinguishable clusters of nodes within the broader network, clearly dividing SMA and distress behaviours. Thus, although distress and SMA behaviours appeared related, they were not blended/mixed in a way that would advocate a common classification [ 41 ].

Furthermore, the current study also expands available knowledge regarding the relationship between SMA and distress, via the examination of the ‘bridging centrality’ of the various symptoms [ 54 ]. Primarily, the connections between the SMA behaviours of mood-modification and conflict, with anxiety and stress, appear to have acted as comorbidity bridges, featuring the highest expected influence bridge centrality values amongst their respective subnetworks (i.e., the number and strength of connections to other subnetworks). In addition, withdrawal symptoms served as a “go-between” in this link between subnetworks, with the highest betweenness bridge centrality (the amount of and strength of the connections between SMA and distress that used it as a go-between). Thus, these findings imply that the need to moderate one’s negative feelings via SMA, and/or the stress/anxiety related to the occurrence of functional impairments in a person’s life (e.g., conflicts with others due to SMA behaviours) could operate as the main connection points in the cyclical relationship between distress and SMA. This hypothesized process aligns with evidence relevant to other behavioural addictions [ 55 ]. Thus, one could support that stressed and anxious individuals may excessively use social media to cope with, and to modify their anxious manifestations, suffering conflicts with their real-world obligations and desires as a result of that use. The latter might induce more stress and anxiety, and perhaps even more when withdrawals ensue after failed attempts to reduce use. Further SMA and depression symptoms could follow as a result of the development of conflict/mood-modification and stress/anxiety respectively. This interpretation is reinforced by prior cross-sectional and longitudinal research in the field of addiction psychology that: a) portrays stress, as well as unhealthy coping mechanisms in response to stress, to operate as primary causes of addictions [ 56 , 57 , 58 , 59 ] and; b) proposes the need to escape from negative moods as highly associated to addictive tendencies [ 6 ]. These results may thus imply, that clinicians treating clients with comorbid SMA/distress, may wish to target these bridging symptoms in particular, in order to cut any possible bidirectional feedback loops between these disorders.

On a separate note, the depression node was found to display a seeming lack of importance in the network. Specifically, depressive behaviours were shown to possess significantly lower general centrality and bridge centrality, implying that they may not have as a formative effect on the experience of SMA symptoms, as stress and anxiety. Furthermore, depression displayed a negative association with withdrawal symptoms, the only negative association in the network. While initially this may seem to contradict prior research associating depression and social media use [ 41 ], this is not necessarily the case. Depression still displayed a positive association with the symptom of mood-modification, accommodating prior research linking addiction with the use of social media as a relief mechanism [ 6 ]. Furthermore, while at first it might seem oxymoronic that the experience of depression might associate with a reduction in SMA withdrawal symptoms, this may not be the case. It is likely that, as with other addictions, those experiencing depression are less able to attempt containing their addictive patterns, whilst when/if they do make attempts, those attempts may be less successful and thus they do not experience withdrawal [ 60 ]. Those experiencing depression have depressed mood, lack of energy and a lack of motivation all of which negate action and make it harder to quit or make an attempt to cease problematic behaviours [ 12 , 16 ]. Furthermore, a lack of direct impact of depressive experiences on SMA symptoms in the network does not imply a lack of impact overall. In the current findings, depression still displayed very strong relationships with stress and anxiety, allowing it to influence SMA via its influence on these symptoms. However, as causality associations were not directly explored in the current study, these interpretations require further additional evidence to be better supported.

Limitations and further study recommendations

Despite the relevant findings reported here, such conclusions and implications may need to be considered in the light of the several limitations of the present study. Firstly, a convenience, community, western/English speaking sample of adult social media users was collected, potentially restricting the generalization of the findings to non-western, children-adolescent and clinical populations. Secondly, findings were exclusively based on self-reported, psychometric scales and thus risks of subjectivity or self-reporting errors cannot be excluded. Therefore, considering that there is evidence of objectively measuring social media use [ 61 , 62 ] future researchers may wish to consider examining non-adult, non-western and/or clinical samples via multimethod designs entailing additionally physical actigraphy and/or digital monitoring means to further expand the available knowledge. Thirdly, this study focused exclusively on the network between PSMU and distress; however, other variables have been associated with PSMU and should be considered in future studies (e.g., fear of missing out [ 63 ]).

Conclusions and implications

Overall, the findings of the present study appear to have added important knowledge across three areas surrounding problematic social media usage. These involve the conceptualization of this debated condition, its differential diagnosis and key behavioural symptoms informing it [ 34 , 48 ]. In particular, the current findings support: a) the applicability of the SMA definition as a construct/condition naturally occurring based on an underpinning network cluster of behaviours; b) a distinct association between SMA symptoms and distress behaviours related to depression, anxiety and stress, which advocates the separate classification of SMA as a psychopathological condition and; c) the role of mood-modification drives and functional impairment/conflicts with others as the connecting/linking points with stress/anxiety behaviours in the formation of SMA behaviours. Accordingly, results pose three significant taxonomic, assessment and prevention/intervention implications. Firstly, the consideration of SMA as a distinct diagnostic category is strengthened. Secondly, assessment of comorbid stress and anxiety manifestations appears to require priority when addressing clients presenting with problematic social media usage. Thirdly, though individuals of different ages and sexes tend to use social media in different ways, and thus likely experience SMA in different fashions, the effects of age and sex on SMA symptoms and their relationship with distress was not explored. This represents an important and interesting area of future study that deserves to be examined.

Availability of data and materials

The data and materials used in this study are available in this link https://github.com/Vas08011980/SNSNETWORK/blob/main/html.Rmd

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Tullett-Prado, D., Doley, J.R., Zarate, D. et al. Conceptualising social media addiction: a longitudinal network analysis of social media addiction symptoms and their relationships with psychological distress in a community sample of adults. BMC Psychiatry 23 , 509 (2023). https://doi.org/10.1186/s12888-023-04985-5

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Research trends in social media addiction and problematic social media use: A bibliometric analysis

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• 1 Sasin School of Management, Chulalongkorn University, Bangkok, Thailand.
• 2 Business Administration Division, Mahidol University International College, Mahidol University, Nakhon Pathom, Thailand.
• PMID: 36458122
• PMCID: PMC9707397
• DOI: 10.3389/fpsyt.2022.1017506

Despite their increasing ubiquity in people's lives and incredible advantages in instantly interacting with others, social media's impact on subjective well-being is a source of concern worldwide and calls for up-to-date investigations of the role social media plays in mental health. Much research has discovered how habitual social media use may lead to addiction and negatively affect adolescents' school performance, social behavior, and interpersonal relationships. The present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013-2022. Bibliometric analysis was conducted on 501 articles that were extracted from the Scopus database using the keywords social media addiction and problematic social media use. The data were then uploaded to VOSviewer software to analyze citations, co-citations, and keyword co-occurrences. Volume, growth trajectory, geographic distribution of the literature, influential authors, intellectual structure of the literature, and the most prolific publishing sources were analyzed. The bibliometric analysis presented in this paper shows that the US, the UK, and Turkey accounted for 47% of the publications in this field. Most of the studies used quantitative methods in analyzing data and therefore aimed at testing relationships between variables. In addition, the findings in this study show that most analysis were cross-sectional. Studies were performed on undergraduate students between the ages of 19-25 on the use of two social media platforms: Facebook and Instagram. Limitations as well as research directions for future studies are also discussed.

Keywords: bibliometric analysis; problematic social media use; research trends; social media; social media addiction.

Copyright © 2022 Pellegrino, Stasi and Bhatiasevi.

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Is Social Media Addictive? Here’s What the Science Says.

A major lawsuit against Meta has placed a spotlight on our fraught relationship with online social information.

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By Matt Richtel

A group of 41 states and the District of Columbia filed suit on Tuesday against Meta , the parent company of Facebook, Instagram, WhatsApp and Messenger, contending that the company knowingly used features on its platforms to cause children to use them compulsively, even as the company said that its social media sites were safe for young people.

“Meta has harnessed powerful and unprecedented technologies to entice, engage and ultimately ensnare youth and teens,” the states said in their lawsuit filed in federal court. “Its motive is profit.”

The accusations in the lawsuit raise a deeper question about behavior: Are young people becoming addicted to social media and the internet? Here’s what the research has found.

What Makes Social Media So Compelling?

Experts who study internet use say that the magnetic allure of social media arises from the way the content plays to our neurological impulses and wiring, such that consumers find it hard to turn away from the incoming stream of information.

David Greenfield, a psychologist and founder of the Center for Internet and Technology Addiction in West Hartford, Conn., said the devices lure users with some powerful tactics. One is “intermittent reinforcement,” which creates the idea that a user could get a reward at any time. But when the reward comes is unpredictable. “Just like a slot machine,” he said. As with a slot machine, users are beckoned with lights and sounds but, even more powerful, information and reward tailored to a user’s interests and tastes.

Adults are susceptible, he noted, but young people are particularly at risk, because the brain regions that are involved in resisting temptation and reward are not nearly as developed in children and teenagers as in adults. “They’re all about impulse and not a lot about the control of that impulse,” Dr. Greenfield said of young consumers.

Moreover, he said, the adolescent brain is especially attuned to social connections, and “social media is all a perfect opportunity to connect with other people.”

Meta responded to the lawsuit by saying that it had taken many steps to support families and teenagers. “We’re disappointed that instead of working productively with companies across the industry to create clear, age-appropriate standards for the many apps teens use, the attorneys general have chosen this path,” the company said in a statement.

Does Compulsion Equal Addiction?

For many years, the scientific community typically defined addiction in relation to substances, such as drugs, and not behaviors, such as gambling or internet use. That has gradually changed. In 2013, the Diagnostic and Statistical Manual of Mental Disorders, the official reference for mental health conditions, introduced the idea of internet gaming addiction but said that more study was warranted before the condition could be formally declared.

A subsequent stud y explored broadening the definition to “internet addiction.” The author suggested further exploring diagnostic criteria and the language, noting, for instance, that terms like “problematic use” and even the word “internet” were open to broad interpretation, given the many forms the information and its delivery can take.

Dr. Michael Rich, the director of the Digital Wellness Lab at Boston Children’s Hospital, said he discouraged the use of the word “addiction” because the internet, if used effectively and with limits, was not merely useful but also essential to everyday life. “I prefer the term ‘Problematic Internet Media Use,” he said, a term that has gained currency in recent years.

Dr. Greenfield agreed that there clearly are valuable uses for the internet and that the definition of how much is too much can vary. But he said there also were clearly cases where excessive use interferes with school, sleep and other vital aspects of a healthy life. Too many young consumers “can’t put it down,” he said. “The internet is a giant hypodermic, and the content, including social media like Meta, are the psychoactive drugs.”

Matt Richtel is a health and science reporter for The Times, based in Boulder, Colo. More about Matt Richtel

A Parent’s Guide to Kids and Social Media

Does your child have an unhealthy relationship with social media? This is what problematic use could look like .

We asked experts for one practical strategy that parents can use with their kids to help mitigate the harms of social media. Here’s what they told us .

There are many tools that allow parents to monitor and set limits on their children’s screen time. Here’s what to know about them .

If you’ve already given your teen full access to social media, these three strategies can help them cut back .

Is social media addictive? Here is what the science says .

A new book argues that banning social media isn’t the answer to online safety. Instead, the author says parents should emphasize the importance of digital literacy and privacy .

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Stanford University School of Medicine blog

Addictive potential of social media, explained

The curious title of Stanford psychiatrist Anna Lembke 's book, Dopamine Nation: Finding Balance in the Age of Indulgence , pays tribute to the crucial and often destructive role that dopamine plays in modern society.

Dopamine , the main chemical involved in addiction, is secreted from certain nerve tracts in the brain when we engage in a rewarding experience such as finding food, clothing, shelter or a sexual mate. Nature designed our brains to feel pleasure when these experiences happen because they increase our odds of survival and of procreation.

But the days when our species dwelled in caves and struggled for survival are long gone. Dopamine Nation explains how living in a modern society, affluent beyond comparison by evolutionary standards, has rendered us all vulnerable to dopamine-mediated addiction . Today, the addictive substance of choice, whether we realize it or not, is often the internet and social media channels, according to Lembke, MD.

"If you're not addicted yet, it's coming soon to a website near you," Lembke joked when I talked to her about the message of Dopamine Nation , which was published in August. This Q&A is abridged from that exchange.

Why did you decide to write this book?

I wanted to tell readers what I'd learned from patients and from neuroscience about how to tackle compulsive overconsumption. Feel-good substances and behaviors increase dopamine release in the brain's reward pathways .

The brain responds to this increase by decreasing dopamine transmission -- not just back down to its natural baseline rate, but below that baseline. Repeated exposure to the same or similar stimuli ultimately creates a chronic dopamine-deficit state, wherein we're less able to experience pleasure.

What are the risk factors for addiction?

Easy access and speedy reward are two of them. Just as the hypodermic needle is the delivery mechanism for drugs like heroin, the smartphone is the modern-day hypodermic needle, delivering digital dopamine for a wired generation.

The hypodermic needle delivers a drug right into our vascular system, which in turn delivers it right to the brain, making the drug more potent. The same is true for the smartphone; with its bright colors, flashing lights and engaging alerts, it delivers images to our visual cortex that are tough to resist. And the quantity is endless. TikTok never runs out.

What makes social media particularly addictive?

We're wired to connect. It's kept us alive for millions of years in a world of scarcity and ever-present danger. Moving in tribes safeguards against predators, optimizes scarce resources and facilitates pair bonding. Our brains release dopamine when we make human connections, which incentivizes us to do it again.

But social connection has become druggified by social-media apps, making us vulnerable to compulsive overconsumption. These apps can cause the release of large amounts of dopamine into our brains' reward pathway all at once, just like heroin, or meth, or alcohol. They do that by amplifying the feel-good properties that attract humans to each other in the first place.

Then there's novelty. Dopamine is triggered by our brain's search-and-explore functions, telling us, "Hey, pay attention to this, something new has come along." Add to that the artificial intelligence algorithms that learn what we've liked before and suggest new things that are similar but not exactly the same, and we're off and running.

Further, our brains aren't equipped to process the millions of comparisons the virtual world demands. We can become overwhelmed by our inability to measure up to these "perfect" people who exist only in the Matrix . We give up trying and sink into depression, or what neuroscientists called "learned helplessness."

Upon signing off, the brain is plunged into a dopamine-deficit state as it attempts to adapt to the unnaturally high levels of dopamine social media just released. Which is why social media often feels good while we're doing it but horrible as soon as we stop.

Is there an antidote to our addiction to social media?

Yes, a timeout -- at least for a day. But a whole month is more typically the minimum amount of time we need away from our drug of choice, whether it's heroin or Instagram, to reset our dopamine reward pathways. A monthlong dopamine fast will decrease the anxiety and depression that social media can induce, and enhance our ability to enjoy other, more modest rewards again.

If and when we return to social media, we can consolidate our use to certain times of the day, avoid certain apps that suck us into the vortex and prioritize apps that connect us with real people in our real lives.

Photo by dole777

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SYSTEMATIC REVIEW article

Research trends in social media addiction and problematic social media use: a bibliometric analysis.

• 1 Sasin School of Management, Chulalongkorn University, Bangkok, Thailand
• 2 Business Administration Division, Mahidol University International College, Mahidol University, Nakhon Pathom, Thailand

Despite their increasing ubiquity in people's lives and incredible advantages in instantly interacting with others, social media's impact on subjective well-being is a source of concern worldwide and calls for up-to-date investigations of the role social media plays in mental health. Much research has discovered how habitual social media use may lead to addiction and negatively affect adolescents' school performance, social behavior, and interpersonal relationships. The present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013–2022. Bibliometric analysis was conducted on 501 articles that were extracted from the Scopus database using the keywords social media addiction and problematic social media use. The data were then uploaded to VOSviewer software to analyze citations, co-citations, and keyword co-occurrences. Volume, growth trajectory, geographic distribution of the literature, influential authors, intellectual structure of the literature, and the most prolific publishing sources were analyzed. The bibliometric analysis presented in this paper shows that the US, the UK, and Turkey accounted for 47% of the publications in this field. Most of the studies used quantitative methods in analyzing data and therefore aimed at testing relationships between variables. In addition, the findings in this study show that most analysis were cross-sectional. Studies were performed on undergraduate students between the ages of 19–25 on the use of two social media platforms: Facebook and Instagram. Limitations as well as research directions for future studies are also discussed.

Introduction

Social media generally refers to third-party internet-based platforms that mainly focus on social interactions, community-based inputs, and content sharing among its community of users and only feature content created by their users and not that licensed from third parties ( 1 ). Social networking sites such as Facebook, Instagram, and TikTok are prominent examples of social media that allow people to stay connected in an online world regardless of geographical distance or other obstacles ( 2 , 3 ). Recent evidence suggests that social networking sites have become increasingly popular among adolescents following the strict policies implemented by many countries to counter the COVID-19 pandemic, including social distancing, “lockdowns,” and quarantine measures ( 4 ). In this new context, social media have become an essential part of everyday life, especially for children and adolescents ( 5 ). For them such media are a means of socialization that connect people together. Interestingly, social media are not only used for social communication and entertainment purposes but also for sharing opinions, learning new things, building business networks, and initiate collaborative projects ( 6 ).

Among the 7.91 billion people in the world as of 2022, 4.62 billion active social media users, and the average time individuals spent using the internet was 6 h 58 min per day with an average use of social media platforms of 2 h and 27 min ( 7 ). Despite their increasing ubiquity in people's lives and the incredible advantages they offer to instantly interact with people, an increasing number of studies have linked social media use to negative mental health consequences, such as suicidality, loneliness, and anxiety ( 8 ). Numerous sources have expressed widespread concern about the effects of social media on mental health. A 2011 report by the American Academy of Pediatrics (AAP) identifies a phenomenon known as Facebook depression which may be triggered “when preteens and teens spend a great deal of time on social media sites, such as Facebook, and then begin to exhibit classic symptoms of depression” ( 9 ). Similarly, the UK's Royal Society for Public Health (RSPH) claims that there is a clear evidence of the relationship between social media use and mental health issues based on a survey of nearly 1,500 people between the ages of 14–24 ( 10 ). According to some authors, the increase in usage frequency of social media significantly increases the risks of clinical disorders described (and diagnosed) as “Facebook depression,” “fear of missing out” (FOMO), and “social comparison orientation” (SCO) ( 11 ). Other risks include sexting ( 12 ), social media stalking ( 13 ), cyber-bullying ( 14 ), privacy breaches ( 15 ), and improper use of technology. Therefore, social media's impact on subjective well-being is a source of concern worldwide and calls for up-to-date investigations of the role social media plays with regard to mental health ( 8 ). Many studies have found that habitual social media use may lead to addiction and thus negatively affect adolescents' school performance, social behavior, and interpersonal relationships ( 16 – 18 ). As a result of addiction, the user becomes highly engaged with online activities motivated by an uncontrollable desire to browse through social media pages and “devoting so much time and effort to it that it impairs other important life areas” ( 19 ).

Given these considerations, the present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013–2022. The study presents a bibliometric overview of the leading trends with particular regard to “social media addiction” and “problematic social media use.” This is valuable as it allows for a comprehensive overview of the current state of this field of research, as well as identifies any patterns or trends that may be present. Additionally, it provides information on the geographical distribution and prolific authors in this area, which may help to inform future research endeavors.

In terms of bibliometric analysis of social media addiction research, few studies have attempted to review the existing literature in the domain extensively. Most previous bibliometric studies on social media addiction and problematic use have focused mainly on one type of screen time activity such as digital gaming or texting ( 20 ) and have been conducted with a focus on a single platform such as Facebook, Instagram, or Snapchat ( 21 , 22 ). The present study adopts a more comprehensive approach by including all social media platforms and all types of screen time activities in its analysis.

Additionally, this review aims to highlight the major themes around which the research has evolved to date and draws some guidance for future research directions. In order to meet these objectives, this work is oriented toward answering the following research questions:

(1) What is the current status of research focusing on social media addiction?

(2) What are the key thematic areas in social media addiction and problematic use research?

(3) What is the intellectual structure of social media addiction as represented in the academic literature?

(4) What are the key findings of social media addiction and problematic social media research?

(5) What possible future research gaps can be identified in the field of social media addiction?

These research questions will be answered using bibliometric analysis of the literature on social media addiction and problematic use. This will allow for an overview of the research that has been conducted in this area, including information on the most influential authors, journals, countries of publication, and subject areas of study. Part 2 of the study will provide an examination of the intellectual structure of the extant literature in social media addiction while Part 3 will discuss the research methodology of the paper. Part 4 will discuss the findings of the study followed by a discussion under Part 5 of the paper. Finally, in Part 7, gaps in current knowledge about this field of research will be identified.

Literature review

Social media addiction research context.

Previous studies on behavioral addictions have looked at a lot of different factors that affect social media addiction focusing on personality traits. Although there is some inconsistency in the literature, numerous studies have focused on three main personality traits that may be associated with social media addiction, namely anxiety, depression, and extraversion ( 23 , 24 ).

It has been found that extraversion scores are strongly associated with increased use of social media and addiction to it ( 25 , 26 ). People with social anxiety as well as people who have psychiatric disorders often find online interactions extremely appealing ( 27 ). The available literature also reveals that the use of social media is positively associated with being female, single, and having attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), or anxiety ( 28 ).

In a study by Seidman ( 29 ), the Big Five personality traits were assessed using Saucier's ( 30 ) Mini-Markers Scale. Results indicated that neurotic individuals use social media as a safe place for expressing their personality and meet belongingness needs. People affected by neurosis tend to use online social media to stay in touch with other people and feel better about their social lives ( 31 ). Narcissism is another factor that has been examined extensively when it comes to social media, and it has been found that people who are narcissistic are more likely to become addicted to social media ( 32 ). In this case users want to be seen and get “likes” from lots of other users. Longstreet and Brooks ( 33 ) did a study on how life satisfaction depends on how much money people make. Life satisfaction was found to be negatively linked to social media addiction, according to the results. When social media addiction decreases, the level of life satisfaction rises. But results show that in lieu of true-life satisfaction people use social media as a substitute (for temporary pleasure vs. longer term happiness).

Researchers have discovered similar patterns in students who tend to rank high in shyness: they find it easier to express themselves online rather than in person ( 34 , 35 ). With the use of social media, shy individuals have the opportunity to foster better quality relationships since many of their anxiety-related concerns (e.g., social avoidance and fear of social devaluation) are significantly reduced ( 36 , 37 ).

Problematic use of social media

The amount of research on problematic use of social media has dramatically increased since the last decade. But using social media in an unhealthy manner may not be considered an addiction or a disorder as this behavior has not yet been formally categorized as such ( 38 ). Although research has shown that people who use social media in a negative way often report negative health-related conditions, most of the data that have led to such results and conclusions comprise self-reported data ( 39 ). The dimensions of excessive social media usage are not exactly known because there are not enough diagnostic criteria and not enough high-quality long-term studies available yet. This is what Zendle and Bowden-Jones ( 40 ) noted in their own research. And this is why terms like “problematic social media use” have been used to describe people who use social media in a negative way. Furthermore, if a lot of time is spent on social media, it can be hard to figure out just when it is being used in a harmful way. For instance, people easily compare their appearance to what they see on social media, and this might lead to low self-esteem if they feel they do not look as good as the people they are following. According to research in this domain, the extent to which an individual engages in photo-related activities (e.g., taking selfies, editing photos, checking other people's photos) on social media is associated with negative body image concerns. Through curated online images of peers, adolescents face challenges to their self-esteem and sense of self-worth and are increasingly isolated from face-to-face interaction.

To address this problem the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) has been used by some scholars ( 41 , 42 ). These scholars have used criteria from the DSM-V to describe one problematic social media use, internet gaming disorder, but such criteria could also be used to describe other types of social media disorders. Franchina et al. ( 43 ) and Scott and Woods ( 44 ), for example, focus their attention on individual-level factors (like fear of missing out) and family-level factors (like childhood abuse) that have been used to explain why people use social media in a harmful way. Friends-level factors have also been explored as a social well-being measurement to explain why people use social media in a malevolent way and demonstrated significant positive correlations with lower levels of friend support ( 45 ). Macro-level factors have also been suggested, such as the normalization of surveillance ( 46 ) and the ability to see what people are doing online ( 47 ). Gender and age seem to be highly associated to the ways people use social media negatively. Particularly among girls, social media use is consistently associated with mental health issues ( 41 , 48 , 49 ), an association more common among older girls than younger girls ( 46 , 48 ).

Most studies have looked at the connection between social media use and its effects (such as social media addiction) and a number of different psychosomatic disorders. In a recent study conducted by Vannucci and Ohannessian ( 50 ), the use of social media appears to have a variety of effects “on psychosocial adjustment during early adolescence, with high social media use being the most problematic.” It has been found that people who use social media in a harmful way are more likely to be depressed, anxious, have low self-esteem, be more socially isolated, have poorer sleep quality, and have more body image dissatisfaction. Furthermore, harmful social media use has been associated with unhealthy lifestyle patterns (for example, not getting enough exercise or having trouble managing daily obligations) as well as life threatening behaviors such as illicit drug use, excessive alcohol consumption and unsafe sexual practices ( 51 , 52 ).

A growing body of research investigating social media use has revealed that the extensive use of social media platforms is correlated with a reduced performance on cognitive tasks and in mental effort ( 53 ). Overall, it appears that individuals who have a problematic relationship with social media or those who use social media more frequently are more likely to develop negative health conditions.

Social media addiction and problematic use systematic reviews

Previous studies have revealed the detrimental impacts of social media addiction on users' health. A systematic review by Khan and Khan ( 20 ) has pointed out that social media addiction has a negative impact on users' mental health. For example, social media addiction can lead to stress levels rise, loneliness, and sadness ( 54 ). Anxiety is another common mental health problem associated with social media addiction. Studies have found that young adolescents who are addicted to social media are more likely to suffer from anxiety than people who are not addicted to social media ( 55 ). In addition, social media addiction can also lead to physical health problems, such as obesity and carpal tunnel syndrome a result of spending too much time on the computer ( 22 ).

Apart from the negative impacts of social media addiction on users' mental and physical health, social media addiction can also lead to other problems. For example, social media addiction can lead to financial problems. A study by Sharif and Yeoh ( 56 ) has found that people who are addicted to social media tend to spend more money than those who are not addicted to social media. In addition, social media addiction can also lead to a decline in academic performance. Students who are addicted to social media are more likely to have lower grades than those who are not addicted to social media ( 57 ).

Research methodology

Bibliometric analysis.

Merigo et al. ( 58 ) use bibliometric analysis to examine, organize, and analyze a large body of literature from a quantitative, objective perspective in order to assess patterns of research and emerging trends in a certain field. A bibliometric methodology is used to identify the current state of the academic literature, advance research. and find objective information ( 59 ). This technique allows the researchers to examine previous scientific work, comprehend advancements in prior knowledge, and identify future study opportunities.

To achieve this objective and identify the research trends in social media addiction and problematic social media use, this study employs two bibliometric methodologies: performance analysis and science mapping. Performance analysis uses a series of bibliometric indicators (e.g., number of annual publications, document type, source type, journal impact factor, languages, subject area, h-index, and countries) and aims at evaluating groups of scientific actors on a particular topic of research. VOSviewer software ( 60 ) was used to carry out the science mapping. The software is used to visualize a particular body of literature and map the bibliographic material using the co-occurrence analysis of author, index keywords, nations, and fields of publication ( 61 , 62 ).

Data collection

After picking keywords, designing the search strings, and building up a database, the authors conducted a bibliometric literature search. Scopus was utilized to gather exploration data since it is a widely used database that contains the most comprehensive view of the world's research output and provides one of the most effective search engines. If the research was to be performed using other database such as Web Of Science or Google Scholar the authors may have obtained larger number of articles however they may not have been all particularly relevant as Scopus is known to have the most widest and most relevant scholar search engine in marketing and social science. A keyword search for “social media addiction” OR “problematic social media use” yielded 553 papers, which were downloaded from Scopus. The information was gathered in March 2022, and because the Scopus database is updated on a regular basis, the results may change in the future. Next, the authors examined the titles and abstracts to see whether they were relevant to the topics treated. There were two common grounds for document exclusion. First, while several documents emphasized the negative effects of addiction in relation to the internet and digital media, they did not focus on social networking sites specifically. Similarly, addiction and problematic consumption habits were discussed in relation to social media in several studies, although only in broad terms. This left a total of 511 documents. Articles were then limited only to journal articles, conference papers, reviews, books, and only those published in English. This process excluded 10 additional documents. Then, the relevance of the remaining articles was finally checked by reading the titles, abstracts, and keywords. Documents were excluded if social networking sites were only mentioned as a background topic or very generally. This resulted in a final selection of 501 research papers, which were then subjected to bibliometric analysis (see Figure 1 ).

Figure 1 . Preferred reporting items for systematic reviews and meta-analysis (PRISMA) flowchart showing the search procedures used in the review.

After identifying 501 Scopus files, bibliographic data related to these documents were imported into an Excel sheet where the authors' names, their affiliations, document titles, keywords, abstracts, and citation figures were analyzed. These were subsequently uploaded into VOSViewer software version 1.6.8 to begin the bibliometric review. Descriptive statistics were created to define the whole body of knowledge about social media addiction and problematic social media use. VOSViewer was used to analyze citation, co-citation, and keyword co-occurrences. According to Zupic and Cater ( 63 ), co-citation analysis measures the influence of documents, authors, and journals heavily cited and thus considered influential. Co-citation analysis has the objective of building similarities between authors, journals, and documents and is generally defined as the frequency with which two units are cited together within the reference list of a third article.

The implementation of social media addiction performance analysis was conducted according to the models recently introduced by Karjalainen et al. ( 64 ) and Pattnaik ( 65 ). Throughout the manuscript there are operational definitions of relevant terms and indicators following a standardized bibliometric approach. The cumulative academic impact (CAI) of the documents was measured by the number of times they have been cited in other scholarly works while the fine-grained academic impact (FIA) was computed according to the authors citation analysis and authors co-citation analysis within the reference lists of documents that have been specifically focused on social media addiction and problematic social media use.

Results of the study presented here include the findings on social media addiction and social media problematic use. The results are presented by the foci outlined in the study questions.

Volume, growth trajectory, and geographic distribution of the literature

After performing the Scopus-based investigation of the current literature regarding social media addiction and problematic use of social media, the authors obtained a knowledge base consisting of 501 documents comprising 455 journal articles, 27 conference papers, 15 articles reviews, 3 books and 1 conference review. The included literature was very recent. As shown in Figure 2 , publication rates started very slowly in 2013 but really took off in 2018, after which publications dramatically increased each year until a peak was reached in 2021 with 195 publications. Analyzing the literature published during the past decade reveals an exponential increase in scholarly production on social addiction and its problematic use. This might be due to the increasingly widespread introduction of social media sites in everyday life and the ubiquitous diffusion of mobile devices that have fundamentally impacted human behavior. The dip in the number of publications in 2022 is explained by the fact that by the time the review was carried out the year was not finished yet and therefore there are many articles still in press.

Figure 2 . Annual volume of social media addiction or social media problematic use ( n = 501).

The geographical distribution trends of scholarly publications on social media addiction or problematic use of social media are highlighted in Figure 3 . The articles were assigned to a certain country according to the nationality of the university with whom the first author was affiliated with. The figure shows that the most productive countries are the USA (92), the U.K. (79), and Turkey ( 63 ), which combined produced 236 articles, equal to 47% of the entire scholarly production examined in this bibliometric analysis. Turkey has slowly evolved in various ways with the growth of the internet and social media. Anglo-American scholarly publications on problematic social media consumer behavior represent the largest research output. Yet it is interesting to observe that social networking sites studies are attracting many researchers in Asian countries, particularly China. For many Chinese people, social networking sites are a valuable opportunity to involve people in political activism in addition to simply making purchases ( 66 ).

Figure 3 . Global dispersion of social networking sites in relation to social media addiction or social media problematic use.

Analysis of influential authors

This section analyses the high-impact authors in the Scopus-indexed knowledge base on social networking sites in relation to social media addiction or problematic use of social media. It provides valuable insights for establishing patterns of knowledge generation and dissemination of literature about social networking sites relating to addiction and problematic use.

Table 1 acknowledges the top 10 most highly cited authors with the highest total citations in the database.

Table 1 . Highly cited authors on social media addiction and problematic use ( n = 501).

Table 1 shows that MD Griffiths (sixty-five articles), CY Lin (twenty articles), and AH Pakpour (eighteen articles) are the most productive scholars according to the number of Scopus documents examined in the area of social media addiction and its problematic use . If the criteria are changed and authors ranked according to the overall number of citations received in order to determine high-impact authors, the same three authors turn out to be the most highly cited authors. It should be noted that these highly cited authors tend to enlist several disciplines in examining social media addiction and problematic use. Griffiths, for example, focuses on behavioral addiction stemming from not only digital media usage but also from gambling and video games. Lin, on the other hand, focuses on the negative effects that the internet and digital media can have on users' mental health, and Pakpour approaches the issue from a behavioral medicine perspective.

Intellectual structure of the literature

In this part of the paper, the authors illustrate the “intellectual structure” of the social media addiction and the problematic use of social media's literature. An author co-citation analysis (ACA) was performed which is displayed as a figure that depicts the relations between highly co-cited authors. The study of co-citation assumes that strongly co-cited authors carry some form of intellectual similarity ( 67 ). Figure 4 shows the author co-citation map. Nodes represent units of analysis (in this case scholars) and network ties represent similarity connections. Nodes are sized according to the number of co-citations received—the bigger the node, the more co-citations it has. Adjacent nodes are considered intellectually similar.

Figure 4 . Two clusters, representing the intellectual structure of the social media and its problematic use literature.

Scholars belonging to the green cluster (Mental Health and Digital Media Addiction) have extensively published on medical analysis tools and how these can be used to heal users suffering from addiction to digital media, which can range from gambling, to internet, to videogame addictions. Scholars in this school of thought focus on the negative effects on users' mental health, such as depression, anxiety, and personality disturbances. Such studies focus also on the role of screen use in the development of mental health problems and the increasing use of medical treatments to address addiction to digital media. They argue that addiction to digital media should be considered a mental health disorder and treatment options should be made available to users.

In contrast, scholars within the red cluster (Social Media Effects on Well Being and Cyberpsychology) have focused their attention on the effects of social media toward users' well-being and how social media change users' behavior, focusing particular attention on the human-machine interaction and how methods and models can help protect users' well-being. Two hundred and two authors belong to this group, the top co-cited being Andreassen (667 co-citations), Pallasen (555 co-citations), and Valkenburg (215 co-citations). These authors have extensively studied the development of addiction to social media, problem gambling, and internet addiction. They have also focused on the measurement of addiction to social media, cyberbullying, and the dark side of social media.

Most influential source title in the field of social media addiction and its problematic use

To find the preferred periodicals in the field of social media addiction and its problematic use, the authors have selected 501 articles published in 263 journals. Table 2 gives a ranked list of the top 10 journals that constitute the core publishing sources in the field of social media addiction research. In doing so, the authors analyzed the journal's impact factor, Scopus Cite Score, h-index, quartile ranking, and number of publications per year.

Table 2 . Top 10 most cited and more frequently mentioned documents in the field of social media addiction.

The journal Addictive Behaviors topped the list, with 700 citations and 22 publications (4.3%), followed by Computers in Human Behaviors , with 577 citations and 13 publications (2.5%), Journal of Behavioral Addictions , with 562 citations and 17 publications (3.3%), and International Journal of Mental Health and Addiction , with 502 citations and 26 publications (5.1%). Five of the 10 most productive journals in the field of social media addiction research are published by Elsevier (all Q1 rankings) while Springer and Frontiers Media published one journal each.

Documents citation analysis identified the most influential and most frequently mentioned documents in a certain scientific field. Andreassen has received the most citations among the 10 most significant papers on social media addiction, with 405 ( Table 2 ). The main objective of this type of studies was to identify the associations and the roles of different variables as predictors of social media addiction (e.g., ( 19 , 68 , 69 )). According to general addiction models, the excessive and problematic use of digital technologies is described as “being overly concerned about social media, driven by an uncontrollable motivation to log on to or use social media, and devoting so much time and effort to social media that it impairs other important life areas” ( 27 , 70 ). Furthermore, the purpose of several highly cited studies ( 31 , 71 ) was to analyse the connections between young adults' sleep quality and psychological discomfort, depression, self-esteem, and life satisfaction and the severity of internet and problematic social media use, since the health of younger generations and teenagers is of great interest this may help explain the popularity of such papers. Despite being the most recent publication Lin et al.'s work garnered more citations annually. The desire to quantify social media addiction in individuals can also help explain the popularity of studies which try to develop measurement scales ( 42 , 72 ). Some of the highest-ranked publications are devoted to either the presentation of case studies or testing relationships among psychological constructs ( 73 ).

Keyword co-occurrence analysis

The research question, “What are the key thematic areas in social media addiction literature?” was answered using keyword co-occurrence analysis. Keyword co-occurrence analysis is conducted to identify research themes and discover keywords. It mainly examines the relationships between co-occurrence keywords in a wide variety of literature ( 74 ). In this approach, the idea is to explore the frequency of specific keywords being mentioned together.

Utilizing VOSviewer, the authors conducted a keyword co-occurrence analysis to characterize and review the developing trends in the field of social media addiction. The top 10 most frequent keywords are presented in Table 3 . The results indicate that “social media addiction” is the most frequent keyword (178 occurrences), followed by “problematic social media use” (74 occurrences), “internet addiction” (51 occurrences), and “depression” (46 occurrences). As shown in the co-occurrence network ( Figure 5 ), the keywords can be grouped into two major clusters. “Problematic social media use” can be identified as the core theme of the green cluster. In the red cluster, keywords mainly identify a specific aspect of problematic social media use: social media addiction.

Table 3 . Frequency of occurrence of top 10 keywords.

Figure 5 . Keywords co-occurrence map. Threshold: 5 co-occurrences.

The results of the keyword co-occurrence analysis for journal articles provide valuable perspectives and tools for understanding concepts discussed in past studies of social media usage ( 75 ). More precisely, it can be noted that there has been a large body of research on social media addiction together with other types of technological addictions, such as compulsive web surfing, internet gaming disorder, video game addiction and compulsive online shopping ( 76 – 78 ). This field of research has mainly been directed toward teenagers, middle school students, and college students and university students in order to understand the relationship between social media addiction and mental health issues such as depression, disruptions in self-perceptions, impairment of social and emotional activity, anxiety, neuroticism, and stress ( 79 – 81 ).

The findings presented in this paper show that there has been an exponential increase in scholarly publications—from two publications in 2013 to 195 publications in 2021. There were 45 publications in 2022 at the time this study was conducted. It was interesting to observe that the US, the UK, and Turkey accounted for 47% of the publications in this field even though none of these countries are in the top 15 countries in terms of active social media penetration ( 82 ) although the US has the third highest number of social media users ( 83 ). Even though China and India have the highest number of social media users ( 83 ), first and second respectively, they rank fifth and tenth in terms of publications on social media addiction or problematic use of social media. In fact, the US has almost double the number of publications in this field compared to China and almost five times compared to India. Even though East Asia, Southeast Asia, and South Asia make up the top three regions in terms of worldwide social media users ( 84 ), except for China and India there have been only a limited number of publications on social media addiction or problematic use. An explanation for that could be that there is still a lack of awareness on the negative consequences of the use of social media and the impact it has on the mental well-being of users. More research in these regions should perhaps be conducted in order to understand the problematic use and addiction of social media so preventive measures can be undertaken.

From the bibliometric analysis, it was found that most of the studies examined used quantitative methods in analyzing data and therefore aimed at testing relationships between variables. In addition, many studies were empirical, aimed at testing relationships based on direct or indirect observations of social media use. Very few studies used theories and for the most part if they did they used the technology acceptance model and social comparison theories. The findings presented in this paper show that none of the studies attempted to create or test new theories in this field, perhaps due to the lack of maturity of the literature. Moreover, neither have very many qualitative studies been conducted in this field. More qualitative research in this field should perhaps be conducted as it could explore the motivations and rationales from which certain users' behavior may arise.

The authors found that almost all the publications on social media addiction or problematic use relied on samples of undergraduate students between the ages of 19–25. The average daily time spent by users worldwide on social media applications was highest for users between the ages of 40–44, at 59.85 min per day, followed by those between the ages of 35–39, at 59.28 min per day, and those between the ages of 45–49, at 59.23 per day ( 85 ). Therefore, more studies should be conducted exploring different age groups, as users between the ages of 19–25 do not represent the entire population of social media users. Conducting studies on different age groups may yield interesting and valuable insights to the field of social media addiction. For example, it would be interesting to measure the impacts of social media use among older users aged 50 years or older who spend almost the same amount of time on social media as other groups of users (56.43 min per day) ( 85 ).

A majority of the studies tested social media addiction or problematic use based on only two social media platforms: Facebook and Instagram. Although Facebook and Instagram are ranked first and fourth in terms of most popular social networks by number of monthly users, it would be interesting to study other platforms such as YouTube, which is ranked second, and WhatsApp, which is ranked third ( 86 ). Furthermore, TikTok would also be an interesting platform to study as it has grown in popularity in recent years, evident from it being the most downloaded application in 2021, with 656 million downloads ( 87 ), and is ranked second in Q1 of 2022 ( 88 ). Moreover, most of the studies focused only on one social media platform. Comparing different social media platforms would yield interesting results because each platform is different in terms of features, algorithms, as well as recommendation engines. The purpose as well as the user behavior for using each platform is also different, therefore why users are addicted to these platforms could provide a meaningful insight into social media addiction and problematic social media use.

Lastly, most studies were cross-sectional, and not longitudinal, aiming at describing results over a certain point in time and not over a long period of time. A longitudinal study could better describe the long-term effects of social media use.

This study was conducted to review the extant literature in the field of social media and analyze the global research productivity during the period ranging from 2013 to 2022. The study presents a bibliometric overview of the leading trends with particular regard to “social media addiction” and “problematic social media use.” The authors applied science mapping to lay out a knowledge base on social media addiction and its problematic use. This represents the first large-scale analysis in this area of study.

A keyword search of “social media addiction” OR “problematic social media use” yielded 553 papers, which were downloaded from Scopus. After performing the Scopus-based investigation of the current literature regarding social media addiction and problematic use, the authors ended up with a knowledge base consisting of 501 documents comprising 455 journal articles, 27 conference papers, 15 articles reviews, 3 books, and 1 conference review.

The geographical distribution trends of scholarly publications on social media addiction or problematic use indicate that the most productive countries were the USA (92), the U.K. (79), and Turkey ( 63 ), which together produced 236 articles. Griffiths (sixty-five articles), Lin (twenty articles), and Pakpour (eighteen articles) were the most productive scholars according to the number of Scopus documents examined in the area of social media addiction and its problematic use. An author co-citation analysis (ACA) was conducted which generated a layout of social media effects on well-being and cyber psychology as well as mental health and digital media addiction in the form of two research literature clusters representing the intellectual structure of social media and its problematic use.

The preferred periodicals in the field of social media addiction and its problematic use were Addictive Behaviors , with 700 citations and 22 publications, followed by Computers in Human Behavior , with 577 citations and 13 publications, and Journal of Behavioral Addictions , with 562 citations and 17 publications. Keyword co-occurrence analysis was used to investigate the key thematic areas in the social media literature, as represented by the top three keyword phrases in terms of their frequency of occurrence, namely, “social media addiction,” “problematic social media use,” and “social media addiction.”

This research has a few limitations. The authors used science mapping to improve the comprehension of the literature base in this review. First and foremost, the authors want to emphasize that science mapping should not be utilized in place of established review procedures, but rather as a supplement. As a result, this review can be considered the initial stage, followed by substantive research syntheses that examine findings from recent research. Another constraint stems from how 'social media addiction' is defined. The authors overcame this limitation by inserting the phrase “social media addiction” OR “problematic social media use” in the search string. The exclusive focus on SCOPUS-indexed papers creates a third constraint. The SCOPUS database has a larger number of papers than does Web of Science although it does not contain all the publications in a given field.

Although the total body of literature on social media addiction is larger than what is covered in this review, the use of co-citation analyses helped to mitigate this limitation. This form of bibliometric study looks at all the publications listed in the reference list of the extracted SCOPUS database documents. As a result, a far larger dataset than the one extracted from SCOPUS initially has been analyzed.

The interpretation of co-citation maps should be mentioned as a last constraint. The reason is that the procedure is not always clear, so scholars must have a thorough comprehension of the knowledge base in order to make sense of the result of the analysis ( 63 ). This issue was addressed by the authors' expertise, but it remains somewhat subjective.

Implications

The findings of this study have implications mainly for government entities and parents. The need for regulation of social media addiction is evident when considering the various risks associated with habitual social media use. Social media addiction may lead to negative consequences for adolescents' school performance, social behavior, and interpersonal relationships. In addition, social media addiction may also lead to other risks such as sexting, social media stalking, cyber-bullying, privacy breaches, and improper use of technology. Given the seriousness of these risks, it is important to have regulations in place to protect adolescents from the harms of social media addiction.

Regulation of social media platforms

One way that regulation could help protect adolescents from the harms of social media addiction is by limiting their access to certain websites or platforms. For example, governments could restrict adolescents' access to certain websites or platforms during specific hours of the day. This would help ensure that they are not spending too much time on social media and are instead focusing on their schoolwork or other important activities.

Another way that regulation could help protect adolescents from the harms of social media addiction is by requiring companies to put warning labels on their websites or apps. These labels would warn adolescents about the potential risks associated with excessive use of social media.

Finally, regulation could also require companies to provide information about how much time each day is recommended for using their website or app. This would help adolescents make informed decisions about how much time they want to spend on social media each day. These proposed regulations would help to protect children from the dangers of social media, while also ensuring that social media companies are more transparent and accountable to their users.

Parental involvement in adolescents' social media use

Parents should be involved in their children's social media use to ensure that they are using these platforms safely and responsibly. Parents can monitor their children's online activity, set time limits for social media use, and talk to their children about the risks associated with social media addiction.

Education on responsible social media use

Adolescents need to be educated about responsible social media use so that they can enjoy the benefits of these platforms while avoiding the risks associated with addiction. Education on responsible social media use could include topics such as cyber-bullying, sexting, and privacy breaches.

Research directions for future studies

A content analysis was conducted to answer the fifth research questions “What are the potential research directions for addressing social media addiction in the future?” The study reveals that there is a lack of screening instruments and diagnostic criteria to assess social media addiction. Validated DSM-V-based instruments could shed light on the factors behind social media use disorder. Diagnostic research may be useful in order to understand social media behavioral addiction and gain deeper insights into the factors responsible for psychological stress and psychiatric disorders. In addition to cross-sectional studies, researchers should also conduct longitudinal studies and experiments to assess changes in users' behavior over time ( 20 ).

Another important area to examine is the role of engagement-based ranking and recommendation algorithms in online habit formation. More research is required to ascertain how algorithms determine which content type generates higher user engagement. A clear understanding of the way social media platforms gather content from users and amplify their preferences would lead to the development of a standardized conceptualization of social media usage patterns ( 89 ). This may provide a clearer picture of the factors that lead to problematic social media use and addiction. It has been noted that “misinformation, toxicity, and violent content are inordinately prevalent” in material reshared by users and promoted by social media algorithms ( 90 ).

Additionally, an understanding of engagement-based ranking models and recommendation algorithms is essential in order to implement appropriate public policy measures. To address the specific behavioral concerns created by social media, legislatures must craft appropriate statutes. Thus, future qualitative research to assess engagement based ranking frameworks is extremely necessary in order to provide a broader perspective on social media use and tackle key regulatory gaps. Particular emphasis must be placed on consumer awareness, algorithm bias, privacy issues, ethical platform design, and extraction and monetization of personal data ( 91 ).

From a geographical perspective, the authors have identified some main gaps in the existing knowledge base that uncover the need for further research in certain regions of the world. Accordingly, the authors suggest encouraging more studies on internet and social media addiction in underrepresented regions with high social media penetration rates such as Southeast Asia and South America. In order to draw more contributions from these countries, journals with high impact factors could also make specific calls. This would contribute to educating social media users about platform usage and implement policy changes that support the development of healthy social media practices.

The authors hope that the findings gathered here will serve to fuel interest in this topic and encourage other scholars to investigate social media addiction in other contexts on newer platforms and among wide ranges of sample populations. In light of the rising numbers of people experiencing mental health problems (e.g., depression, anxiety, food disorders, and substance addiction) in recent years, it is likely that the number of papers related to social media addiction and the range of countries covered will rise even further.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Author contributions

AP took care of bibliometric analysis and drafting the paper. VB took care of proofreading and adding value to the paper. AS took care of the interpretation of the findings. All authors contributed to the article and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: bibliometric analysis, social media, social media addiction, problematic social media use, research trends

Citation: Pellegrino A, Stasi A and Bhatiasevi V (2022) Research trends in social media addiction and problematic social media use: A bibliometric analysis. Front. Psychiatry 13:1017506. doi: 10.3389/fpsyt.2022.1017506

Received: 12 August 2022; Accepted: 24 October 2022; Published: 10 November 2022.

Reviewed by:

Copyright © 2022 Pellegrino, Stasi and Bhatiasevi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Alfonso Pellegrino, alfonso.pellegrino@sasin.edu ; Veera Bhatiasevi, veera.bhatiasevi@mahidol.ac.th

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Social Media Addiction in High School Students: A Cross-Sectional Study Examining Its Relationship with Sleep Quality and Psychological Problems

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• Volume 14 , pages 2265–2283, ( 2021 )

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• Adem Sümen   ORCID: orcid.org/0000-0002-8876-400X 1 &
• Derya Evgin 2  

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The aim of this study was to examine the relationship of social media addiction with sleep quality and psychological problems in high school students. The study is a cross-sectional, correlational type. The study was conducted with 1,274 students receiving education in a district located in the western region of Turkey. For the collection of the data, a Descriptive Information Form, the Social Media Addiction Scale for Adolescents (SMASA), the Strengths and Difficulties Questionnaire (SDQ), the Sleep Quality Scale (SQS) and the Sleep Variables Questionnaire (SVQ) were used. Among the high school students who participated in the research, 49.3% stated that they had been using social media for 1–3 years, 53.9% reported that they spent 1–3 h per day on social media, and 42.8% stated that they placed their telephone under their pillow or beside their bed while sleeping. Students’ mean scores were 16.59 ± 6.79 (range: 9–45) for the SMASA, 16.54 ± 4.27 (range: 0–40) for total difficulties, and 14.18 ± 1.56 (range: 7–21) for the SQS, while their sleep efficiency value was 97.9%. According to the research model, difficulties experienced by high school students increase their social media addiction, while they decrease prosocial behaviours. Social media addiction in high school students decreases students’ sleep efficiency (p < 0.05). It is considered important to conduct further public health studies for children and adolescents related to the risks caused by the excessive use of technology, the consequences of social media addiction, measures to protect psychological health, sleep programmes and the importance of sleep quality.

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1 Introduction

Together with the very rapid digitalization in our age, the use of social media is increasing in our country and in the world (Ersöz & Kahraman, 2020 ; Singh et al., 2020 ). According to the Digital 2021: Global Overview Report, the time spent on social media has increased 1.5 times in the last 5 years. The most widely used social networks are listed as: Facebook, YouTube, WhatsApp, FB Messenger, Instagram, WeChat, TikTok and QQ (DataReportal, 2021a ). As for Turkey, the use of social media has increased by 11.1% in the past year, and YouTube, Instagram, WhatsApp, Facebook, Twitter and FB Messenger are the most frequently used social networks (DataReportal, 2021b ). When the way of dealing with social media addiction is examined, it can be said that nowadays, social media addiction has ceased to be an ordinary problem and become a disease associated with a global epidemic. People all over the world can show excessive interest in social media and spend a great deal of time using social media. For this reason, social media has a negative effect on the lives of millions of people in the world (Andreassen, 2015 ; Singh et al., 2020 ).

In a study by Drahošová and Balco ( 2017 ), in which they investigated the advantages and disadvantages of social media use, 97.7% of participants stated that the advantages of using social media were communication and the exchange of information, while 72.2% stated that the biggest disadvantage was internet addiction. It is known that among users, especially the younger age group faces the risk of addiction. Although social media is regarded as a new area of socialization and that this situation is an advantage (Savcı & Aysan, 2017 ), it is also reported that social media has a negative effect on interpersonal relationships (Çalışır, 2015 ), psychological health (Chen et al., 2020 ) and private life (Acılar & Mersin, 2015 ), increases levels of depression (Haand & Shuwang, 2020 ), and leads to social media addiction. Indeed, it has been determined that in the case of adolescent users, excessive levels of use are associated with paranoid thoughts, phobic anxiety and feelings of anger and hostility (Bilgin, 2018 ). Moreover, an increase in periods of social media use can cause a reduction in sleep quality (Eroğlu & Yıldırım, 2017 ). Poor sleep quality can lead to daytime sleepiness in students and to negative effects on their performance, school achievement, activities and energy (Güneş et al., 2018 ).

Due to the coronavirus pandemic, the switch to the distance education process was made in line with the restrictions implemented for protecting public health. The extension of periods spent at home by adolescents has led to long periods of exposure to screens, a restriction of outdoor activities, a reduction in peer interactions, unhealthy sleep patterns, and increases in stress and anxiety levels (Liu et al., 2021 ; Wang et al., 2020 ). Based on this, the aim of this study is to examine the relationship of social media addiction with sleep quality and psychological problems in high school students.

2.1 Study Design

This is a cross-sectional, correlational type of research. In this study, which was conducted in order to determine the relationship of social media addiction with sleep quality and psychological problems in high school students, a path analysis study was made in line with the examined literature and the aim, and the theoretical model is shown in Fig.  1 . The model consists of four hypotheses, and the correlations between the variables in these hypotheses are included in the model.

H 1 : Difficulties experienced by high school students (emotional problems, conduct problems, attention deficit and hyperactivity, and peer problems) increase social media addiction.

H 2 : Prosocial behaviours in high school students decrease social media addiction.

H 3 : Social media addiction in high school students increases poor sleep quality.

H 4 : Social media addiction in high school students decreases sleep efficiency.

Path diagram of the research model. SMASA: Social Media Addiction Scale for Adolescents, SQS: Sleep Quality Scale

2.2 Participants

The study was conducted in 15 high schools affiliated to a District National Education Directorate in the south of Turkey. A total of 4,602 students are registered at these high schools in the 2020–2021 academic year. Since education at the schools is carried out in the form of distance education within the scope of the COVID-19 measures, the research was carried out online via the District National Education Directorate and the school principals. The study was completed between 01–30 December 2020 with a total of 1,274 people with the aim of reaching all students. Students registered at high school and volunteering to participate in the study were included in the research. A 99% error rate and 3.07% confidence interval originating from the sample number of the research were found.

2.3 Data Collection Tools

A Descriptive Information Form prepared by the researchers by examining the literature, the Social Media Addiction Scale for Adolescents, the Strengths and Difficulties Questionnaire, the Sleep Quality Scale, and the Sleep Variables Questionnaire were used for data collection.

Descriptive Information Form

This was prepared in line with the literature, and consists of questions related to adolescents’ socio-demographic characteristics, school achievement, family, friend relationships, sleep status, and extent of using social media. School achievement and relationship levels were classified as “good”, “average” or “poor” depending on the students’ own statements.

Social Media Addiction Scale for Adolescents (SMASA)

This scale was developed by Özgenel et al. ( 2019 ) with the aim of determining adolescents’ levels of social media addiction. The scale consists of a single factor and includes nine items. The highest score that can be obtained from the five-point Likert-type scale is 45, while the lowest score is 9. It can be said that adolescents’ social media addiction is greater as scores obtained in the scale increase, while as scores decrease, their level of addiction is lower. The Cronbach alpha internal consistency reliability coefficient of the scale is 0.904. In this study, however, the Cronbach alpha value was found to be 0.880.

Strengths and Difficulties Questionnaire (SDQ)

Developed by Goodman ( 1997 ), this scale is extensively used all over the world to examine children’s and adolescents’ psychological and behavioural problems. The scale was adapted to Turkish by Güvenir et al. ( 2008 ). Consisting of a total of 25 questions, the scale is scored with a three-point Likert-type rating, and the questions are scored as “0”, “1” and “2” according to their degree of accuracy. The scale includes subscales of emotional problems, conduct problems, attention deficit and hyperactivity, peer problems, and prosocial behaviours, each containing five questions. Although each subscale can be evaluated in itself, the total of the first four subscales gives a total difficulty score. While high scores for prosocial behaviours reflect an individual’s strengths in the social domain, high scores in the other four domains indicate that the problem areas are severe. The Cronbach alpha internal consistency reliability coefficient of the scale is 0.73, while in this study, the Cronbach alpha value was found to be 0.776.

Sleep Quality Scale and Sleep Variables Questionnaire (SQS-SVQ)

This scale was developed by Meijer and van den Wittenboer ( 2004 ), and the Turkish validity and reliability study was carried out by Önder et al. ( 2016 ). Seven scale items that measure sleep quality and eight questionnaire items that identify parental control, total sleep time, midpoint of sleep, and sleep efficiency are included in the SQS-SVQ. Each of the SQS items have three categories scored from 1 to 3. Scores that can be obtained from the scale range between 7 and 21. A high score obtained from the scale indicates poor sleep quality, while a low score indicates good sleep quality. Among the SVQ items, however, only sleep efficiency was calculated and used. The Cronbach alpha internal consistency reliability coefficient of the scale is 0.72. In this study, however, the Cronbach alpha value was calculated as 0.714.

2.4 Data Collection

The data were collected by using an online web-based questionnaire via Google Forms. The questionnaire was sent to the students through social media networks via the District National Education Directorate and the school principals. Before beginning the study, the study aim and method were explained to the students and their families, and it was stated that the data would be used only for scientific purposes, that the data would be kept confidential, that the study would be conducted based on the principle of voluntariness, and that participants were free to take part in the research or not. After the students who agreed to take part in the study had confirmed that they were volunteers in an electronic environment, they began to reply to the questions. It took an average of 15–20 min to respond to the questionnaires. A total of 1,366 students filled in the form. When the forms were examined after the study, 92 forms were not evaluated due to missing data. Therefore, the data collection process was completed with 1,274 students.

2.5 Data Evaluation

The statistical analyses of the data were made using the SPSS Statistics Base V 23 version of Statistical Package for the Social Sciences and AMOS 21.0 software. For evaluating the data of the study, descriptive statistical methods (frequency, percentage, mean and standard deviation) were used; to test the differences between groups, t-test for independent variables and one-way variance analysis were performed; for comparisons between groups, the post-hoc Bonferroni and Tukey tests for multiple comparisons were utilised. In the research, the path analysis method was applied to test the hypotheses of the model created to determine the relationship of social media addiction with psychological problems and sleep quality. The results were evaluated at a 95% confidence interval and at p < 0.05, p < 0.01 and p < 0.001 significance levels.

2.6 Ethical Aspect of the Research

To be able to conduct the research, institutional permission was obtained from Antalya Provincial Directorate of Education (date: 25/09.2020, No: E.13536854), while ethical approval was obtained from Akdeniz University Clinical Research Ethics Committee (date: 19/02/2020, No: KAEK-174). Meetings were held with school principals of all the schools, and the research aim, content and method were explained to them. Participants’ consent was obtained by making an announcement about the study on the first page of the online link of the data collection tools.

Among the high school students participating in the research, 70.0% were girls, and their average age was 15.36 ± 1.22. Approximately half of the students were studying in first grade (45.4%), while over half of them (61.9%) stated that their school achievement level was average. The majority of students reported that they had good relationships with their mothers (85.2%), fathers (77.1%), siblings (72.2%) and friends (77.5%). It was revealed that 75.1% of students decided when to go to bed themselves, 65.6% did not turn off their telephones while sleeping, 44.6% kept their telephones away from the bed, and 42.8% placed their telephones under their pillow or beside their bed. The majority of students stated that they had been using social media for 1–3 years (49.3%), and that they spent 1–3 h per day on social media (53.9%), while 35.9% checked their social media as soon as a notification came. 10.3% of students considered themselves to be social media addicts, while 72.7% believed that society was addicted to social media (Table 1 ).

The high school students’ mean SMASA score was determined to be 16.59 ± 6.79. For the SDQ, their mean score for total difficulties was calculated as 16.54 ± 4.27. Among the SDQ subscales, the highest mean score was for prosocial behaviours with 7.94 ± 1.88, while the lowest was for conduct problems with 2.23 ± 1.49. The total SQS mean score was calculated as 14.18 ± 1.56, while the sleep efficiency value was calculated as 97.9% (Fig.  2 ).

Participants’ SMASA, SQS-SVQ and SDQ total and subscale mean scores (n: 1274)

Mean SMASA scores of female students (p < 0.001), students with poor school achievement (p < 0.001), students who had poor relationships with their mothers (p < 0.001), fathers (p < 0.001), siblings (p < 0.001) and friends (p < 0.05), whose parents decided on their bedtime (p < 0.05), who did not turn off their telephones while sleeping (p < 0.001), who had been using social media for more than seven years (p < 0.001), who spent more than seven hours on social media per day (p < 0.001), who checked their social media notifications at every spare moment (p < 0.001), and who considered themselves (p < 0.001) and society (p < 0.001) to be social media addicts were found to be higher. Female students (p < 0.05), students who had poor relationships with their mothers (p < 0.01) and siblings (p < 0.05), and those who did not turn off their telephones while sleeping (p < 0.01) were determined to have higher mean SQS scores. It was revealed that female students (p < 0.001), students with poor school achievement (p < 0.001), students who had poor relationships with their mothers (p < 0.001), fathers (p < 0.001), siblings (p < 0.001) and friends (p < 0.001), who had used social media for more than seven years (p < 0.005), who spent more than seven hours on social media per day (p < 0.001), who checked their social media notifications at every spare moment (p < 0.001), and who considered themselves (p < 0.001) and society (p < 0.001) to be social media addicts had higher mean SDQ scores (Table 1 ).

In the study, a positive correlation of students’ mean SMASA scores with SDQ-conduct problems, SDQ-attention deficit, SDQ-emotional problems, SDQ-peer problems, SDQ-total difficulties index and total SQS mean scores was found, while a negative correlation was found with SDQ-prosocial behaviours and SVQ-sleep efficiency mean scores (p < 0.01) (Table 2 ).

The standardised estimates related to the research model drawn within the scope of the study are given in Table 3 . According to the research model, difficulties experienced by high school students have a positive effect on social media addiction (β = 0.293), while prosocial behaviours have a negative effect on social media addiction (β = -0.159) (p < 0.05). Social media addiction in high school students has a negative effect on sleep efficiency (β = -0.094, p < 0.05). As a result of the path analysis, it was determined that the goodness-of-fit indices of the model had acceptable values and that model-data fit was achieved (İlhan & Çetin, 2014 ; Kline, 2011 ). Accordingly, hypotheses H 1 , H 2 ve H 4 relating to the model were accepted, while hypothesis H 3 was not accepted (Table 3 ).

4 Discussion

Social media use by individuals has steadily increased in recent years (Dong et al., 2020 ; Fernandes et al., 2020 ; Kashif & Aziz-Ur-Rehman, 2020 ; Lemenager et al., 2021 ). Especially young people increasingly use social media and the internet, which is an easily and rapidly accessible means of mass communication, frequently for academic and other purposes. These tools are not merely a source of information, their use is also sought for other purposes such as social interaction, games and entertainment (Singh & Barmola, 2015 ). The decrease seen in individuals’ interaction in social life and the increase in the time they spend at home due to the COVID-19 pandemic have increased the use of online communication tools (Benke et al., 2020 ; King et al., 2020 ; Oliviero et al., 2021 ). The steady increase in internet and social media addiction among young people in recent years has already been reported (Fernandes et al., 2020 ; Kashif & Aziz-Ur-Rehman, 2020 ; Orben et al., 2020 ; Scott et al., 2019 ). However, in this study, it was seen that high school students’ mean social media addiction scores (16.59 ± 6.79) were below average.

In the Addiction Prevention Training Programme of Turkey implemented by Green Crescent ( 2017 ), certain criteria were defined concerning the case of whether or not high school students’ are addicted to social media. Accordingly, it is stated that if social media is the first choice that comes to mind in cases of boredom, if it takes precedence over real life, if it leads to disruption of daily life and negligence of responsibilities, if it takes up an excessive amount of time and creates anxiety when it cannot be accessed, if the need is felt to constantly share things, then adolescents may be addicted to social media. The majority of students included in the scope of the study stated that they had been using social media for 1–3 years (49.3%), and that they spent 1–3 h on social media per day (53.9%), while 35.9% checked their social media whenever a notification came. Therefore, it can be said that students taking part in the study were at risk of social media use disorder. However, another important finding of the study is that while one in ten students regarded themselves as social media addicts, around three-quarters of them considered that society was addicted to social media. This situation in fact shows that the students had awareness regarding social media addiction, but that they did not accept addiction for themselves. In a study conducted by Fernandes et al. ( 2020 ) on adolescents in India, Malaysia, Mexico and Great Britain, it was found that during the pandemic, periods of social media use, playing online games, and watching video content increased significantly compared to before the pandemic. In other conducted studies, it is also seen that the period spent on social media has increased during the pandemic compared to before the pandemic (71.4%) (Lemenager et al., 2021 ), and that people frequently spend their free time on social media during the pandemic (67%) (Kashif & Aziz-Ur-Rehman, 2020 ).

In the study, it was revealed that social media addiction scores were higher in students who had poor relationships with their mothers, fathers, siblings and friends. Social media prevents adolescents from forming close personal relationships with their families and immediate environment. Social media use disorder also causes weak family and friend relationships in adolescents (Moreno & Uhls, 2019 ). Numerous problems emerge due to the misuse of social media. In the study, it was determined that mean SQS scores were higher in students who had poor relationships with their mothers and siblings, and those who did not switch off their telephones while sleeping. It has been found that adolescents with high levels of problematic internet use and of social media use suffer from depression, loneliness, lower sleep quality and high anxiety levels (Bányai et al., 2017 ; Alonzo et al., 2020 ; Fernandes et al., 2020 ; Orben et al., 2020 ). In some studies, a statistically significant correlation between social media use and adolescent sleep patterns, especially delayed sleep onset, has been determined (Alimoradi et al., 2019 ; Gradisar et al., 2013 ; Scott et al., 2019 ). In the study, students’ total sleep quality mean score (14.18 ± 1.56) was revealed to be poor, and their sleep efficiency value was calculated as 97.9%. This shows that the adolescents included in the sample were unable to sleep efficiently and that their sleep quality was low. This situation may be the result of changes in sleep habits of adolescents due to remaining at home because of the coronavirus pandemic. Similarly, in a study carried out in Italy, it was determined that as a result of the isolation measures taken against the coronavirus, a big delay in children’ sleeping/waking schedules and an increase in sleep disorders occurred in all age groups (Oliviero et al., 2021 ). In another study, it was revealed that problems occurred in adolescents during the pandemic, such as delay in falling asleep, reduction in length of sleep, respiratory impairment during sleep, and sleepiness during the day, and that sleep routines were disrupted (Becker & Gregory, 2020 ). The problem of lack of sleep is very common in adolescents, and is an important public health problem that needs intervention in several aspects, such as mental health, obesity and academic performance (Owens, 2014 ; Sampasa-Kanyinga et al., 2020 ).

In the study, the high school students’ mean total difficulties score in the SDQ was calculated as medium level (16.54 ± 4.27). Among the SDQ subscales, the highest mean score was found to be for prosocial behaviours, while the lowest was for conduct problems. The high level of prosocial behaviours and low level of conduct problems in the sample group indicates that the research group were able to cope with difficulties. A negative correlation was found between SDQ-prosocial behaviours and SVQ-sleep efficiency mean scores in the study. This situation can be interpreted to say that social media use can lead to lack of sleep in students, and that students’ prosocial behaviours can decrease. Pandemic adolescents showed higher levels of other problems and a more problematic social media usage than peers before the pandemic (Muzi et al., 2021 ). Moreover, significant increases are seen in individuals’ rates of problematic internet use and of social media use due to the pandemic, and it is stated that this situation creates negative effects in terms of individuals’ psychological health (Baltacı et al., 2021 ; Oliviero et al., 2021 ). In a qualitative study conducted by Baltacı et al., ( 2020 ), it was stated that students experienced difficulties in controlling their internet use during the pandemic, and that since they were unable to control this, they experienced negative emotions and regarded themselves as internet addicts due to this situation.

Evidence suggests that problematic use of gaming, the internet, and social media among adolescents is on the rise, affecting multiple psycho-emotional domains. Moreover, excessive use of digital activities and smartphones may result in multiple mental and physical problems, such as behavioural addiction, cognitive impairment, and emotional distress (Ophir et al., 2020 ). It was found that as students’ mean social media scores increased, their mean scores for attention deficit, conduct problems, emotional problems, peer problems and total difficulties index also increased. In addition, it has been determined that the difficulties experienced by high school students (emotional problems, conduct problems, attention deficit and hyperactivity, and peer problems) increase social media addiction (H 1 ). It is emphasized that spending a long time on the Internet increases the possibility of exposure to risks and pathological tendencies, and that the time spent using social media is harmful to mental health (Alonzo et al., 2020 ; Coyne et al., 2020 ; Stockdale & Coyne, 2020 ; Twigg et al., 2020 ). It is known that during the pandemic, missing the daily routines that school brings and absence of time spent with peers causes adolescents to experience a great number of problems. These problems can be listed as increase in monotonous time spent at home, disrupted sleep habits, increased exposure to screens, intensive internet use, increased eating habits, decreased physical activity, increased attention and concentration problems, loss of academic achievement due to reduced motivation, increased domestic conflicts, inability to cope with negative emotions such as aggression, boredom, anger and anxiety, increased emotional activity, and deterioration of emotion regulation skills (Ghosh et al., 2020 ; Lee, 2020 ; Oliviero et al., 2021 ). In support of the literature, in this study, too, it was seen that especially during these difficult times that we have been going through, the high school students’ social relationships were weakened, their school achievement decreased, the frequency and length of their social media use increased, and there was an increase in the psychological problems and social media addiction that they experienced. This situation reveals that adolescents are at risk biopsychosocially in terms of healthy development and acquiring identity, and with regard to other risks (cyber violence, obesity, loneliness, depression, anxiety, etc.) that the digital environment will bring (Orben et al., 2020 ). Especially the greater amount of time that adolescents spend using social media has increased the negative effects on adolescents’ general health and wellbeing, including sleep (Dong et al., 2020 ).

Another important result of the study is the finding that prosocial behaviors reduce social media addiction in high school students (H 2 ). Some studies showed that there were short comings in social skills associated with social interactions and internet and social media addiction (Chua et al., 2020 ; Dalvi-Esfahani et al., 2021 ). While the effective use of the internet creates an opportunity for the adolescent, its excessive use may negatively affect the adolescent's physical, psychological, social and cognitive development (Hou et al., 2019 ). A study found that depression, bullying, loneliness, and sleep quality are among the most common health problems that arise from social media use (Royal Society for Public Health, 2020 ). Kurulan araştırma modelinde, sosyal medya bağımlılığının lise öğrencilerinde kötü uyku kalitesini etkilemediği (H 3 ) fakat uyku verimliliğini (H 4 ) azalttığı sonucuna varılmıştır. There are studies showing that social media addiction is positively associated with poor sleep quality (Alfaya et al., 2021 ; Ho, 2021 ; Tandon et al., 2020 ; Wong et al., 2020 ). According to Garett et al. ( 2018 ), using social media for longer periods of time and spending more time with social media causes the quality of sleep of users to decrease. Wong et al. ( 2020 ) determined that both the severity of internet gaming disorder and social media addiction were positively related to psychological distress and sleep disorder. In a study on social media use, sleep quality, and well-being in 467 adolescents, it was found that social media use was associated with poor sleep, anxiety, depression, and low self-esteem. Poor sleep was most strongly associated with nighttime social media use (Woods & Scott, 2016 ). It is important for the development of a healthy generation to educate adolescents about conscious social media and smart phone use and to emphasize the importance of sleep habits (Gıca, 2020 ).

5 Conclusions

According to the results obtained in the study, the students’ scores for social media addiction and psychological problems were found to be below average, while their sleep quality scores were negatively above. Although it is known that sleep is very important for adolescent health, it was determined that increased social media addiction in the students in the sample group increased the potential for the emergence of health and sleep problems. It should be borne in mind that the social distancing, recommendations to stay at home, and distance education implemented due to the pandemic can lead to greater flexibility in sleeping and waking times, and can cause an increase in the use of technology for long periods and in social media addiction. It was seen that social media addiction in students was positively correlated with conduct and emotional problems, attention deficit/hyperactivity, peer problems and poor sleep quality, and negatively correlated with prosocial behaviours and sleep efficiency. Based on this, school health nurses should plan and implement appropriate intervention methods in collaboration with other healthcare personnel (psychologists, school counsellors, social workers, etc.). Enabling high school students’ access to the correct information sources, open and transparent sharing of information, planning daily routines at home such as meals, sleep and homework, increasing physical activities, expanding intelligent internet use that will support personal and social development, enabling adolescents’ return to the peer and school environment by creating safe school environments in as short a time as possible, creating alternative means and support groups for peer interaction by reducing isolation and loneliness, and appropriate therapeutic interventions such as sleep education and interventions can be listed among these measures and precautions.

Data Availability

The data that support the fndings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors are grateful to all the high school students for their cooperation in this study.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Sümen, A., Evgin, D. Social Media Addiction in High School Students: A Cross-Sectional Study Examining Its Relationship with Sleep Quality and Psychological Problems. Child Ind Res 14 , 2265–2283 (2021). https://doi.org/10.1007/s12187-021-09838-9

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Statistics on Social Media Addiction

In This Article

Scrolling through social media is pretty common, especially for younger generations. However, it is possible to become dependent on it for online affirmation and grow a full-blown addiction to it.

Many people are becoming addicted to social media, seeking constant connection and validation in today's digital age. As the number of social media users continues to skyrocket, so does social media addiction, leading to a host of negative consequences that extend far beyond the screen.

In this article, we will take a deep dive into the latest statistics surrounding social media addiction, shedding light on its global reach, its impact on mental health, and the demographic trends that are shaping this growing epidemic.

The Global Epidemic

The scale of social media addiction on a global level is nothing short of astounding.

• A staggering 210 million people worldwide suffer from social media addiction, representing approximately 4% to 5% of all social media users globally.
• In the United States alone, an estimated 10% of social media users are addicted, amounting to 33.19 million Americans based on 2021 population data.
• During the COVID-19 pandemic, social media use increased by an alarming 21% globally, highlighting how social distancing measures and lockdowns may have fueled a greater reliance on digital platforms for social interaction.

The Toll on Mental Health

The impact of social media addiction on mental health is both profound and deeply concerning, particularly among younger generations.

• Social media addiction is strongly linked to heightened rates of anxiety, depression, and poor sleep quality, with increased usage directly correlating to a greater risk of these mental health issues.
• The feature that wreaks the most havoc on mental well-being is the pursuit of likes, comments, and followers, indicating that the quest for validation and social esteem through social media can lead to a vicious cycle of depression and anxiety.
• Perhaps most disturbing of all, suicide rates among teens have surged in the age of social media, with a staggering 22% of high schoolers reporting serious thoughts of suicide and 10% actually attempting suicide in the past year alone.

Demographic Divides

While social media addiction affects individuals across all age groups, certain demographics are particularly vulnerable.

• Young adults and teenagers bear the brunt of social media addiction, with a staggering 90% of people aged 18 to 29 using social media and 15% of those aged 23 to 38 admitting to being addicted.
• More than half of Generation Z and Millennial users confess to feeling addicted to social media, underscoring the generational divide in social media dependence.
• College students are hit especially hard, with a shocking 56% reporting social media addiction, suggesting that the pressures and stressors of higher education may fuel problematic usage patterns.

The Path Forward

While the statistics surrounding social media addiction are undeniably grim, there is hope for those struggling with this issue. Recovery is possible through a comprehensive approach that combines behavioral therapies, support groups, and lifestyle modifications.

• Cognitive Behavioral Therapy (CBT) has emerged as a highly effective treatment for social media addiction, helping individuals identify triggers and develop healthy coping mechanisms
• Support groups like Internet and Technology Addicts Anonymous (ITAA) offer a safe and supportive space for those battling addiction to connect with others who understand their struggles
• Practical strategies such as digital detoxes, setting clear boundaries around social media use, cultivating offline hobbies, and taking regular breaks can all contribute to a more balanced relationship with technology

Online Therapy Can Help

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The latest statistics on social media addiction are a sobering reminder of the pervasive and deeply troubling nature of this issue. With millions of people worldwide grappling with the negative consequences of excessive social media use, from crippling anxiety and depression to an increased risk of suicide, it is clear that we are facing a global crisis.

As we navigate an increasingly digital world, we must remain vigilant about the potential dangers of social media addiction and take proactive steps to promote healthier habits and support those who are struggling.

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• Why Call an Addiction Hotline?
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Despite equivocal evidence, risks such as cyberbullying and exposure to inappropriate content have sparked a global debate about possible links between social-media use and deteriorating adolescent mental health (see C. L. Odgers Nature 628 , 29–30; 2024 ). Arguments also continue about whether social-media use is addictive, and what responsibility the industry bears for creating immersive platforms that result in prolonged time spent online ( C. Montag and J. D. Elhai Curr. Addiction Rep. 10 , 610–616; 2023 ).

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University of Utah announces major funding for new addiction treatment research

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Patricia Brandt Manager, Public Relations and Communications, Huntsman Mental Health Institute University of Utah Health Email: Patricia.Brandt @hsc.utah.edu

Salt Lake City (April 10, 2024) - Worldwide, someone dies from drug or alcohol addiction every four minutes. Now, researchers at Huntsman Mental Health Institute at the University of Utah have been selected by Wellcome Leap to research a new treatment for substance use disorder as part of a $50 million commitment to develop innovative treatments.

Brian J. Mickey, MD, PhD, professor of psychiatry at Huntsman Mental Health Institute (pictured top left), will lead the team of investigators with expertise in psychiatry, biomedical engineering, neuroscience, radiology, and social work to research a new, noninvasive treatment for addiction. Co-principal investigators include Jan Kubanek, PhD , (pictured top center), and Taylor Webb, PhD (pictured top right); co-investigators include (from left to right) Eric Garland, PhD, LCSW ; Rana Jawish, MD ; Vincent Koppelmans, PhD ; and Tom Riis, PhD.

The research will be funded by the Untangling Addiction program, which is a $50 million program founded by Wellcome Leap , to develop scalable measures to assess addiction susceptibility, quantify the risks stemming from addiction, and develop innovative treatments.  

“Substance use disorder is a significant global health problem, and yet the treatment options are limited,” Mickey said.  “We’re developing a non-invasive intervention for preventing and treating addiction, chronic pain, and depression. This funding will help us validate and generate the data to support the next critical step: an efficacy trial to determine the effectiveness of the intervention.”

Mickey’s team will use a novel ultrasound-based device to modulate deep brain regions and behaviors associated with opioid addiction. The goal will be to ultimately develop this approach into an individually targeted therapeutic intervention for a range of addictions. “Addictions are brain illnesses that have enormous negative impact on individuals, families, and society,” Mickey said. “A major reason that addictions have been difficult to prevent—and treat—is that they are driven by dysfunction of deep brain regions that are challenging to access. Many psychiatric problems such as depression, anxiety, and addiction are caused by malfunction of brain circuits. This project is an example of our mission to understand how these neural circuits are dysregulated and to develop novel, circuit-targeted interventions that return the brain to a healthy state.”

"We are proud to bring Wellcome Leap's innovative problem-solving and funding approach to our research enterprise at the University of Utah," said Taylor Randall, President , University of Utah. "To have our mental health researchers contributing to pioneering work on addiction treatment reaffirms our commitment to improving lives through discovery."

“What makes research like this so impactful is that it brings together a variety of disciplines to help solve complex problems in mental health,” said Mark Hyman Rapaport, MD , CEO of Huntsman Mental Health Institute. “This is particularly timely news given the groundbreaking of a new translational research building on campus focused on mental health and the brain. Our nation is in a mental health crisis, but there is hope if we can think differently and work together to change this trajectory.”

About Huntsman Mental Health Institute

Huntsman Mental Health Institute at University of Utah Health brings together 75 years of patient care, research, and education into one of the nation's leading academic medical centers focused on mental health. Nestled in the campus of University of Utah, Huntsman Mental Health Institute serves the community with 1,600 faculty and staff in 20 locations providing inpatient and outpatient services for youth, teens, and adults as well as a comprehensive crisis care model which includes the nationally recognized SafeUT app and the 988 Crisis hotline for Utah. Our mission is to advance mental health knowledge, hope, and healing for all. Learn more at:  HMHI.utah.edu  and join the conversation on  Instagram ,  Facebook ,  TikTok ,  X  and  LinkedIn .

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