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  • Published: 18 May 2020

Clinical Characteristics of Developmentally Delayed Children based on Interdisciplinary Evaluation

  • S. W. Kim 1 ,
  • H. R. Jeon 1 ,
  • H. J. Jung 2 ,
  • J. A. Kim 2 ,
  • J.-E. Song 3 &
  • J. Kim   ORCID: orcid.org/0000-0003-4693-8400 4  

Scientific Reports volume  10 , Article number:  8148 ( 2020 ) Cite this article

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  • Autism spectrum disorders
  • Risk factors

The aim of this study is to examine the clinical characteristics of children suspected to have neurodevelopmental disorders and to present features that could be helpful diagnostic clues at the clinical assessment stage. All children who visited the interdisciplinary clinic for developmental problems from May 2001 to December 2014 were eligible for this study. Medical records of the children were reviewed. A total of 1,877 children were enrolled in this study. Most children were classified into four major diagnostic groups: global developmental delay (GDD), autism spectrum disorder (ASD), developmental language disorder (DLD) and motor delay (MD). GDD was the most common (43.9%), and boys were significantly more predominant than girls in all groups. When evaluating the predictive power of numerous risk factors, the probability of GDD was lower than the probability of ASD among boys, while the probability of GDD increased as independent walking age increased. Compared with GDD and DLD, the probability of GDD was increased when there was neonatal history or when the independent walking age was late. Comparison of ASD and DLD showed that the probability of ASD decreased when a maternal history was present, whereas the probability of ASD increased with male gender. To conclude, the present study revealed the clinical features of children with various neurodevelopmental disorders. These results are expected to be helpful for more effectively flagging children with potential neurodevelopmental disorders in the clinical setting.

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Introduction

Developmental disabilities caused by dysfunction of the central nervous system, including the brain, are called neurodevelopmental disorders, and children with neurodevelopmental disorders have difficulties in various fields including physical, linguistic, behavior and learning 1 . According to a previous study conducted in the United States, 5–17% of children suffer from developmental disabilities, and recent trends have shown a gradual increase 2 . Limitations due to neurodevelopmental disorders might continue throughout life, and individuals with these disorders may require special services, health care and support 3 . These factors cause enormous social costs to a country as well as economic and psychological burdens for the families of children with developmental disabilities 4 .

The cause of neurodevelopmental disorders varies, and it is difficult to distinguish between children with neurodevelopmental disorders and typically developing children in early infancy. Even if the neurodevelopmental disorder is caused by nonprogressive factors, the clinical phenotype may change over time as the central nervous system matures 5 . Therefore, children’s symptoms are different according to their age and severity, and the necessary interventions will vary accordingly. As a result, the diagnosis of a neurodevelopmental disorder can vary greatly depending on the clinician’s perspective, and the treatment or intervention or social support offered may differ according to diagnosis. The time at which an expert is consulted varies widely from newborn to school-aged 6 . As shown in previous studies 7 , 8 , intervention during the period when the brain is developing rapidly can minimize disabilities and reduce the gap in developmental delay; as such, it is important to start precise intervention early. Neurodevelopmental disorders express various features, and the degree of influence by developmental domain varies from case to case. Because of the multi-morbidity feature, attempting to intervene by focusing on only one problem can lead to not only overlooking other accompanying problems but also a problem of inefficient use of limited intervention resources.

To compensate for difficulties in dealing with the complexity of neurodevelopmental disorders, an interdisciplinary clinic named the Developmental Delay Clinic (DDC) has been operating in our hospital. In this clinic, three specialists (a pediatric neurologist, pediatric physiatrist and pediatric psychologist) work together to provide comprehensive diagnoses and intervention plans. The three specialists, depending on area of expertise, each examine children, prescribe necessary tests, share and discuss the results of physical and neurological examinations and various tests and produce a precise diagnosis with a balanced intervention plan for each child. In this study, the authors aimed to identify meaningful factors for diagnosis and to determine if it is possible to distinguish major neurodevelopmental disorders at the clinical assessment stage.

Children who visited the DDC in our hospital with complaints of any developmental problems from May 2001 to December 2014 were included in this study. The total number of subjects was 1,877. Approval to perform this retrospective study was obtained from our Institutional Review Board (IRB) and research ethics committee (National Health Insurance Medical Center, NHIMC 2015-09-016). The need for informed consent was formally waived by the IRB and research ethics committee. All methods were performed in accordance with relevant guidelines and regulations.

All patients who visited the DDC for the first time had a history taken, and data were gathered according to the prescribed protocol. Data such as birth history, prenatal history, family history and other medical history were collected from a paper questionnaire. Birth history included intrauterine period and birth weight. Prenatal history included fetal distress, problems related to amniotic fluid or placenta, intrauterine growth retardation (IUGR), and fetal movement abnormality. Events such as fetal apnea, meconium aspiration and neonatal seizures were considered in the neonatal history. Postnatal history included infections such as sepsis, infantile spasm, and febrile convulsion. The presence of family history, such as language delay, autism spectrum disorder, and intellectual disability, and maternal history during the pregnancy period, such as anxiety or insomnia, depression, smoking and drinking, were also assessed in the survey.

After assessing histories through the questionnaire, the three specialists examined the child and prescribed necessary tests according to protocol. The diagnostic protocol was composed of two categories: required tests applied to all children and selective tests applied to some patients who needed those tests, based on each specialist’s judgment 9 (Fig.  1 , Supplementary 1).

figure 1

Diagnostic protocol for children visited developmental delay clinic.

The diagnosis was determined by discussion among the three specialists in reference to each child’s clinical findings and standardized developmental assessment results. The diagnoses were divided into two categories: either a phenomenological diagnosis based on the child’s current condition or an etiological diagnosis based on the pathophysiology of the condition. All these phenomenological diagnoses were classified into four major groups according to the child’s main features: global developmental delay (GDD), autism spectrum disorder (ASD), developmental language disorder (DLD) and motor delay (MD). The GDD group included diagnoses such as GDD and intellectual disability. GDD refers to children with significant delays in more than two of the following developmental domains: gross motor/fine motor, speech/language, intelligence, social interaction and self-care. In general, children under five years of age who met the requirements were diagnosed with GDD, while older children who could be examined using a reliable and formal intelligence test were diagnosed with intellectual disability 10 . Diagnoses such as reactive attachment disorder and social communication disorder were included in the ASD group. Those in the ASD group were diagnosed based on diagnostic criteria from the Diagnostic and Statistical Manual of Mental Disorders, 4 th edition (DSM-IV) 11 . However, since it has been updated from DSM-IV to DSM-V, the term ASD is used in this paper to prevent confusion. MD was defined as significant impairment of gross and/or fine-motor function compared with other developmental domains. Cerebral palsy and developmental coordination disorder were included in this group. DLD was defined as significant impairment of speech and language ability compared with other developmental domains. In this context, “significant” meant more than two standard deviations below the average value for the same age 10 . Etiological diagnoses included chromosomal and genetic anomalies, myopathy, and metabolic disease, among others.

Statistical analysis

SAS ver. 9.2 (SAS Institute, Cary, NC, USA) was used for statistical analysis. The results of the survey were obtained using the Kruskal-Wallis test with Bonferroni correction and logistic regression analysis. The level of significance was set at p < 0.05.

A total of 1,877 children were enrolled in this study. When divided into classes according to major phenomenological diagnosis, GDD accounted for the largest number, with 824 children (43.9%), followed by ASD with 430 (22.9%), DLD with 389 (20.7%) and MD with 72 (3.8%). Only 16 children (0.9%) were finally diagnosed as developing normally after all tests and examinations were given. Boys were more predominant than girls, with 1,316 (70.1%) and 561 (29.9%), respectively (p < 0.05). The age at which children visited the DDC ranged from 2 months to 192 months, and the average age was 50.9 ± 30.0 months. The corrected age was used for preterm children until they reached two years old. Two hundred thirty-four children (12.5%) out of the total could be diagnosed with an etiological diagnosis. Among these, hypoxic ischemic encephalopathy accounted for the largest number, with 58 children (24.8%), followed by chromosomal and/or genetic abnormalities with 53 children (22.6%) and congenital anomalies of the brain with 33 children (14.0%). Among the children who underwent a brain MRI, abnormal findings were mostly found in MD with 27.8%, which was significantly higher than ASD and DLD (p < 0.05) (Table  1 ).

With respect to preterm birth (gestational age less than 37 weeks), the history of preterm birth was the most prevalent in MD (29.2%), which was significantly higher than that in GDD (12.5%), ASD (10.9%) and DLD (8.7%) (p < 0.05). A history of low birth weight (LBW, birth weight less than 2,500 grams) was most common in MD (44.4%), which was significantly higher than that in ASD (20.9%) and DLD (25.4%) (p < 0.05) but not GDD (32.5%) (p = 0.426). Prenatal histories were most prevalent in MD (5.6%), which was significantly higher than in ASD and DLD (p < 0.05). Neonatal histories were also most prevalent in MD (29.2%), which was significantly higher than in the other three groups (p < 0.05). GDD and MD had a significantly higher prevalence of postnatal history compared with ASD and DLD (p < 0.05), but the difference between GDD and MD was not significant. Among family histories, language delay was the most common across all diagnosis groups, but the prevalence of having a family history did not differ significantly among the groups (p = 0.445). With regard to maternal histories, a maternal history of having anxiety or insomnia was the most common type in GDD, ASD and DLD, but drugs or drinking alcohol were the most common in MD. The percentage of cases with a maternal history did not differ significantly across the groups (p = 0.294) (Table  2 ).

Among the various risk factors mentioned above, logistic regression analysis performed to compare the groups and to determine if certain risk factors contributed to being diagnosed with GDD, ASD and DLD. When comparing GDD with ASD, the risk of having GDD decreased with boys and the presence of family history, while the risk increased with the presence of neonatal, postnatal and maternal history, later independent walking age (a representation of delayed motor milestone) and abnormal findings in the brain MRI. After controlling for confounders, gender and independent walking age showed significant between-group differences. When comparing GDD with DLD, the risk of having GDD was lower in boys and with the presence of a family history, while the risk increased with presence of the prenatal, neonatal and postnatal history, later independent walking age and abnormal findings in the brain MRI. After controlling for confounders, neonatal history and independent walking age showed significant between-group differences. When comparing ASD with DLD, the risk of having ASD was higher in boys, while the risk decreased with the presence of maternal history. The results were the same after controlling for confounders (Table  3 , Fig.  2 ).

figure 2

Distinctive clinical features among different diagnosis.

When receiver operating characteristic (ROC) curve analysis was performed to confirm the predictive power of these models, the model comparison of GDD vs. ASD and the model comparison of GDD vs. DLD showed good predictive power, while the model comparison of ASD vs. DLD had poor predictive power. Hosmer and Lemeshow’s Goodness-of-Fit Test revealed that all three logistic regression models were fit to predict the risk factors (Table  4 ).

The prevalence of developmental disabilities has risen in recent years with increases in high-risk pregnancies such as aged pregnancy, improved survival of high-risk infants due to medical technology advancement, and improved awareness and diagnosis of developmental disabilities 2 . The goal of early intervention for children with developmental disabilities is to prevent or minimize delays in all developmental domains, and early intervention allows children to achieve developmental milestones through the provision of enriched environments. Additionally, such interventions help caregivers cope efficiently with their children in daily life 12 . As seen in this study, the symptoms of children with neurodevelopmental disorders are very diverse, and the timing and symptoms of caregivers’ perception of something wrong in their children also vary. In addition, during the brain development period, one developmental domain affects the development of other domains, thus indicating multi-morbidity features. Proper intervention is important, but intervention is not always necessary. In some cases, it is more important to educate parents and modify the home environment than to use special resources. To effectively use limited resources, it is important to accurately diagnose neurodevelopmental disorders, which represent a multi-morbidity feature.

Among the patients who visited the DDC during the past 14 years, boys outnumbered girls in all diagnostic groups, which is consistent with previous studies 2 , 13 . Regarding etiological diagnosis, hypoxic ischemic encephalopathy was the most prevalent, followed by chromosomal and genetic abnormalities and congenital anomalies of the brain. These three factors accounted for 61.5% of the total etiologic causes. This outcome is similar to that of a study conducted by Shevell et al . 14 indicating that four causes, i.e., the three causes mentioned above plus poisoning, accounted for 68.9% of total cases with a known etiological basis. There were no children with poisoning in the present study, which could be due to differences in socio-cultural backgrounds. However, more attention to antenatal poisoning might be needed, based on the recent increase in poisoning cases in Korea 15 .

In cases of preterm birth and LBW, which are known as the strongest risk factors for developmental disabilities 16 , a history of preterm birth was significantly more common in MD than in GDD, ASD and DLD. In contrast, a history of LBW was not significantly different between MD and GDD. It could be posited that the risk of GDD increased in cases of small for gestational age even in full-term births. Arcangeli et al . 17 reported that compared with children of appropriate size for their gestational age, children who had a history of being small for their gestational age or who had fetal growth retardation, even in full-term births, showed lower neurodevelopmental scores. Takeuchi et al . 18 reported that being small for gestational age is a risk factor for developmental disabilities, even in full-term babies. These results were consistent with the present study, and more attentive follow-up regarding developmental course is needed for children with a history of being small for gestational age.

Kumar et al . 19 reported that the prevalence of neurodevelopmental disorders was higher in groups having family histories of neurodevelopmental disorders, such as epilepsy, GDD, MD, vision or hearing defects, compared with groups without such histories. Among the types of family histories, a history of language delay was seen the most in all diagnostic groups in this study. This finding could be explained by several factors: language delay is often present in various neurodevelopmental disorders, and the recognition and diagnosis of various neurodevelopmental disorders has improved in recent years, but this was not the case before. It may have been diagnosed as language delay 13 . In addition, it is possible that ASD has been diagnosed as other diseases, such as GDD or language delay, due to negative social perception of the diagnosis in Korea. Several studies have previously revealed that delay in one developmental domain often correlates with delay in other domains. Rechetnikov et al . 20 stated that there was a correlation between motor impairment and speech and language disorder. Wang et al . 21 reported that motor skill and communication skill were correlated with each other and that the motor skill of a one-and-a-half-year-old could predict the communication skill of a three-year-old. Language delay was predominant among the chief complaints of children who visited the DDC, but their final diagnosis was not limited to DLD. Shevell et al . 22 reported that approximately three-quarters of children who were diagnosed with DLD before their fifth birthday showed some limitation of not only language but also communication, motor skill and social function at an early school age. Overall, the physicians would carefully assess all of the developmental domains, even if the chief complaints of parents were language delay, and would also give them a proper intervention plan focusing on the other domains.

This study has a few limitations. First, it is a single-center study, and most of the included children were from a metropolitan area in the Northern Gyeonggi territory. Second, children suspected to have cerebral palsy often visited the outpatient clinic of the rehabilitation department instead of the DDC for their initial evaluation, so the proportion of children with cerebral palsy was low in this study. Third, although the diagnosis may change over time, the study was conducted based on the initial diagnosis. Nevertheless, this study is meaningful in that it is the first study to present a probabilistic model in the clinical evaluation of children with suspected neurodevelopmental disorders. Several papers on the diagnosis of neurodevelopmental disorders that suggest diagnostic steps for GDD and ASD have been published thus far 23 , 24 , 25 , 26 , 27 . However, in contrast to the present study, there were no articles suggesting probabilistic models that included comprehensive history taking and clinical diagnosis. Additionally, most previous studies were confined to one diagnosis, such as cerebral palsy or intellectual disabilities, whereas this study represents the many children who visited interdisciplinary clinics for 14 years with various chief complaints about development.

In conclusion, the present study revealed the clinical characteristics of children who have developmental problems. In this study, we present a feature that can aid diagnosis in the stage of clinical evaluation for children with suspected neurodevelopmental disorders. These results are expected to be helpful for more effectively identifying children with potential neurodevelopmental disorders in the clinical setting.

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S.W., H.J. and J.-E. conceived of the presented concept and revised the article. J.K. and H.R. developed the theory, interpreted of data and drafted the article. J.A. collected and analyzed the data and drafted the article. All authors discussed the results and contributed to the final manuscript and had complete access to the study data that support the publication. All authors read and approved the final manuscript.

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Kim, S.W., Jeon, H.R., Jung, H.J. et al. Clinical Characteristics of Developmentally Delayed Children based on Interdisciplinary Evaluation. Sci Rep 10 , 8148 (2020). https://doi.org/10.1038/s41598-020-64875-8

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Global developmental delay and intellectual disability are relatively common pediatric conditions. This report describes the recommended clinical genetics diagnostic approach. The report is based on a review of published reports, most consisting of medium to large case series of diagnostic tests used, and the proportion of those that led to a diagnosis in such patients. Chromosome microarray is designated as a first-line test and replaces the standard karyotype and fluorescent in situ hybridization subtelomere tests for the child with intellectual disability of unknown etiology. Fragile X testing remains an important first-line test. The importance of considering testing for inborn errors of metabolism in this population is supported by a recent systematic review of the literature and several case series recently published. The role of brain MRI remains important in certain patients. There is also a discussion of the emerging literature on the use of whole-exome sequencing as a diagnostic test in this population. Finally, the importance of intentional comanagement among families, the medical home, and the clinical genetics specialty clinic is discussed.

The purpose of this clinical report of the American Academy of Pediatrics (AAP) is to describe an optimal medical genetics evaluation of the child with intellectual disability (ID) or global developmental delays (GDDs). The intention is to assist the medical home in preparing families properly for the medical genetics evaluation process. This report addresses the advances in diagnosis and treatment of children with intellectual disabilities since the publication of the original AAP clinical report in 2006 1 and provides current guidance for the medical genetics evaluation. One intention is to inform primary care providers in the setting of the medical home so that they and families are knowledgeable about the purpose and process of the genetics evaluation. This report will emphasize advances in genetic diagnosis while updating information regarding the appropriate evaluation for inborn errors of metabolism and the role of imaging in this context. The reader is referred to the 2006 clinical report for background information that remains relevant, including the roles of the medical home or pediatric primary care provider.

This clinical report will not address the importance of developmental screening in the medical home, nor will it address the diagnostic evaluation of the child with an autism spectrum disorder who happens to have ID as a co-occurring disability. (For AAP guidance related to Autism Spectrum Disorders, see Johnson and Myers. 2 )

For both pediatric primary care providers and families, there are specific benefits to establishing an etiologic diagnosis ( Table 1 ): clarification of etiology; provision of prognosis or expected clinical course; discussion of genetic mechanism(s) and recurrence risks; refined treatment options; the avoidance of unnecessary and redundant diagnostic tests; information regarding treatment, symptom management, or surveillance for known complications; provision of condition-specific family support; access to research treatment protocols; and the opportunity for comanagement of patients, as appropriate, in the context of a medical home to ensure the best health, social, and health care services satisfaction outcomes for the child and family. The presence of an accurate etiologic diagnosis along with a knowledgeable, experienced, expert clinician is one factor in improving the psychosocial outcomes for children and with intellectual disabilities and their families. 3 , – 5 Although perhaps difficult to measure, this “healing touch” contributes to the general well-being of the family. “As physicians we have experience with other children who have the same disorder, access to management programs, knowledge of the prognosis, awareness of research on understanding the disease and many other elements that when shared with the parents will give them a feeling that some control is possible.” 5  

The Purposes of the Comprehensive Medical Genetics Evaluation of the Young Child With GDD or ID

Makela et al 6 studied, in depth, 20 families of children with ID with and without an etiologic diagnosis and found that these families had specific stated needs and feelings about what a genetic diagnosis offers:

Validation: a diagnosis established that the problem (ID) was credible, which empowered them to advocate for their child.

Information: a diagnosis was felt to help guide expectations and management immediately and provide hope for treatment or cure in future.

Procuring services: the diagnosis assisted families in obtaining desired services, particularly in schools.

Support: families expressed the need for emotional companionship that a specific diagnosis (or “similar challenges”) assisted in accessing.

Need to know: families widely differed in their “need to know” a specific diagnosis, ranging from strong to indifferent.

Prenatal testing: families varied in their emotions, thoughts, and actions regarding prenatal genetic diagnosis.

For some families in the Makela et al 6 study, the clinical diagnosis of autism, for example, was sufficient and often more useful than “a rare but specific etiological diagnosis.” These authors report that “all of the families would have preferred to have an [etiologic] diagnosis, if given the option,” particularly early in the course of the symptoms.

As was true of the 2006 clinical report, this clinical report will not address the etiologic evaluation of young children who are diagnosed with cerebral palsy, autism, or a single-domain developmental delay (gross motor delay or specific language impairment). 1 Some children will present both with GDD and clinical features of autism. In such cases, the judgment of the clinical geneticist will be important in determining the evaluation of the child depending on the primary neurodevelopmental diagnosis. It is recognized that the determination that an infant or young child has a cognitive disability can be a matter of clinical judgment, and it is important for the pediatrician and consulting clinical geneticist to discuss this before deciding on the best approach to the diagnostic evaluation.” 1  

ID is a developmental disability presenting in infancy or the early childhood years, although in some cases, it cannot be diagnosed until the child is older than ∼5 years of age, when standardized measures of developmental skills become more reliable and valid. The American Association on Intellectual and Developmental Disability defines ID by using measures of 3 domains: intelligence (IQ), adaptive behavior, and systems of supports afforded the individual. 7 Thus, one cannot rely solely on the measure of IQ to define ID. More recently, the term ID has been suggested to replace “mental retardation.” 7 , 8 For the purposes of this clinical report, the American Association on Intellectual and Developmental Disability definition is used: “Intellectual disability is a disability characterized by significant limitations both in intellectual functioning and in adaptive behavior as expressed in conceptual, social and practical adaptive skills. The disability originates before age 18 years.” 7 The prevalence of ID is estimated to be between 1% and 3%. Lifetime costs (direct and indirect) to support individuals with ID are large, estimated to be an average of approximately $1 million per person. 9  

Identifying the type of developmental delay is an important preliminary step, because typing influences the path of investigation later undertaken. GDD is defined as a significant delay in 2 or more developmental domains, including gross or fine motor, speech/language, cognitive, social/personal, and activities of daily living and is thought to predict a future diagnosis of ID. 10 Such delays require accurate documentation by using norm-referenced and age-appropriate standardized measures of development administered by experienced developmental specialists. The term GDD is reserved for younger children (ie, typically younger than 5 years), whereas the term ID is usually applied to older children for whom IQ testing is valid and reliable. Children with GDD are those who present with delays in the attainment of developmental milestones at the expected age; this implies deficits in learning and adaptation, which suggests that the delays are significant and predict later ID. However, delays in development, especially those that are mild, may be transient and lack predictive reliability for ID or other developmental disabilities. For the purposes of this report, children with delays in a single developmental domain (for example, isolated mild speech delay) should not be considered appropriate candidates for the comprehensive genetic evaluation process set forth here. The prevalence of GDD is estimated to be 1% to 3%, similar to that of ID.

Schaefer and Bodensteiner 11 wrote that a specific diagnosis is that which “can be translated into useful clinical information for the family, including providing information about prognosis, recurrence risks, and preferred modes of available therapy.” For example, agenesis of the corpus callosum is considered a sign and not a diagnosis, whereas the autosomal-recessive Acrocallosal syndrome (agenesis of the corpus callosum and polydactyly) is a clinical diagnosis. Van Karnebeek et al 12 defined etiologic diagnosis as “sufficient literature evidence…to make a causal relationship of the disorder with mental retardation likely, and if it met the Schaefer-Bodensteiner definition.” This clinical report will use this Van Karnebeek modification of the Schaefer–Bodensteiner definition and, thus, includes the etiology (genetic mutation or genomic abnormality) as an essential element to the definition of a diagnosis.

Recommendations are best when established from considerable empirical evidence on the quality, yield, and usefulness of the various diagnostic investigations appropriate to the clinical situation. The evidence for this clinical report is largely based on many small- or medium-size case series and on expert opinion. The report is based on a review of the literature by the authors.

Significant changes in genetic diagnosis in the last several years have made the 2006 clinical report out-of-date. First, the chromosome microarray (CMA) is now considered a first-line clinical diagnostic test for children who present with GDD/ID of unknown cause. Second, this report highlights a renewed emphasis on the identification of “treatable” causes of GDD/ID with the recommendation to consider screening for inborn errors of metabolism in all patients with unknown etiology for GDD/ID. 13  

Nevertheless, the approach to the patient remains familiar to pediatric primary care providers and includes the child’s medical history (including prenatal and birth histories); the family history, which includes construction and analysis of a pedigree of 3 generations or more; the physical and neurologic examinations emphasizing the examination for minor anomalies (the “dysmorphology examination”); and the examination for neurologic or behavioral signs that might suggest a specific recognizable syndrome or diagnosis. After the clinical genetic evaluation, judicious use of laboratory tests, imaging, and other consultations on the basis of best evidence are important in establishing the diagnosis and for care planning.

CMA now should be considered a first-tier diagnostic test in all children with GDD/ID for whom the causal diagnosis is not known. G-banded karyotyping historically has been the standard first-tier test for detection of genetic imbalance in patients with GDD/ID for more than 35 years. CMA is now the standard for diagnosis of patients with GDD/ID, as well as other conditions, such as autism spectrum disorders or multiple congenital anomalies. 14 , – 24 The G-banded karyotype allows a cytogeneticist to visualize and analyze chromosomes for chromosomal rearrangements, including chromosomal gains (duplications) and losses (deletions). CMA performs a similar function, but at a much “higher resolution,” for genomic imbalances, thus increasing the sensitivity substantially. In their recent review of the CMA literature, Vissers et al 25 report the diagnostic rate of CMA to be at least twice that of the standard karyotype. CMA, as used in this clinical report, encompasses all current types of array-based genomic copy number analyses, including array-based comparative genomic hybridization and single-nucleotide polymorphism arrays (see Miller et al 15 for a review of array types). With these techniques, a patient’s genome is examined for detection of gains or losses of genome material, including those too small to be detectable by standard G-banded chromosome studies. 26 , 27 CMA replaces the standard karyotype (“chromosomes”) and fluorescent in situ hybridization (FISH) testing for patients presenting with GDD/ID of unknown cause. The standard karyotype and certain FISH tests remain important to diagnostic testing but now only in limited clinical situations (see Manning and Hudgins 14 ) in which a specific condition is suspected (eg, Down syndrome or Williams syndrome). The discussion of CMA does not include whole-genome sequencing, exome sequencing, or “next-generation” genome sequencing; these are discussed in the “emerging technologies” section of this report.

Twenty-eight case series have been published addressing the rate of diagnosis by CMA of patients presenting with GDD/ID. 28 The studies vary by subject criteria and type of microarray technique and reflect rapid changes in technology over recent years. Nevertheless, the diagnostic yield for all current CMA is estimated at 12% for patients with GDD/ID. 14 , – 29 CMA is the single most efficient diagnostic test, after the history and examination by a specialist in GDD/ID.

CMA techniques or “platforms” vary. Generally, CMA compares DNA content from 2 differentially labeled genomes: the patient and a control. In the early techniques, 2 genomes were cohybridized, typically onto a glass microscope slide on which cloned or synthesized control DNA fragments had been immobilized. Arrays have been built with a variety of DNA substrates that may include oligonucleotides, complementary DNAs, or bacterial artificial chromosomes. The arrays might be whole-genome arrays, which are designed to cover the entire genome, or targeted arrays, which target known pathologic loci, the telomeres, and pericentromeric regions. Some laboratories offer chromosome-specific arrays (eg, for nonsyndromic X-linked ID [XLID]). 30 The primary advantage of CMA over the standard karyotype or later FISH techniques is the ability of CMA to detect DNA copy changes simultaneously at multiple loci in a genome in one “experiment” or test. The copy number change (or copy number variant [CNV]) may include deletions, duplications, or amplifications at any locus, as long as that region is represented on the array. CMA, independent of whether it is “whole genome” or “targeted” and what type of DNA substrate (single-nucleotide polymorphisms, 31 oligonucleotides, complementary DNAs, or bacterial artificial chromosomes), 32 identifies deletions and/or duplications of chromosome material with a high degree of sensitivity in a more efficient manner than FISH techniques. Two main factors define the resolution of CMA: (1) the size of the nucleic acid targets; and (2) the density of coverage over the genome. The smaller the size of the nucleic acid targets and the more contiguous the targets on the native chromosome are, the higher the resolution is. As with the standard karyotype, one result of the CMA test can be “of uncertain significance,” (ie, expert interpretation is required, because some deletions or duplications may not be clearly pathogenic or benign). Miller et al 15 describe an effort to develop an international consortium of laboratories to address questions surrounding array-based testing interpretation. This International Standard Cytogenomic Array Consortium 15 ( www.iscaconsortium.org ) is investigating the feasibility of establishing a standardized, universal system of reporting and cataloging CMA results, both pathologic and benign, to provide the physician with the most accurate and up-to-date information.

It is important for the primary care pediatrician to work closely with the clinical geneticist and the diagnostic laboratory when interpreting CMA test results, particularly when “variants of unknown significance” are identified. In general, CNVs are assigned the following interpretations: (1) pathogenic (ie, abnormal, well-established syndromes, de novo variants, and large changes); (2) variants of unknown significance; and (3) likely benign. 15 These interpretations are not essentially different than those seen in the standard G-banded karyotype. It is important to note that not all commercial health plans in the United States include this testing as a covered benefit when ordered by the primary care pediatrician; others do not cover it even when ordered by the medical geneticist. Typically, the medical genetics team has knowledge and experience in matters of payment for testing.

The literature does not stratify the diagnostic rates of CMA by severity of disability. In addition, there is substantial literature supporting the multiple factors (eg, social, environmental, economic, genetic) that contribute to mild disability. 33 Consequently, it remains within the judgment of the medical geneticist as to whether it is warranted to test the patient with mild (and familial) ID for pathogenic CNVs. In their review, Vissers et al 25 reported on several recurrent deletion or duplication syndromes with mild disability and commented on the variable penetrance of the more common CNV conditions, such as 1q21.1 microdeletion, 1q21.1 microduplication, 3q29 microduplication, and 12q14 microdeletion. Some of these are also inherited. Consequently, among families with more than one member with disability, it remains challenging for the medical geneticist to know for which patient with GDD/ID CMA testing is not warranted.

Recent efforts to evaluate reporting of CNVs among clinical laboratories indicate variability of interpretation because of platform variability in sensitivity. 34 , 35 Thus, the interpretation of CMA test abnormal results and variants of unknown significance, and the subsequent counseling of families should be performed in all cases by a medical geneticist and certified genetic counselor in collaboration with the reference laboratory and platform used. Test variability is resolving as a result of international collaborations. 36 With large data sets, the functional impact (or lack thereof) of very rare CNVs is better understood. Still, there will continue to be rare or unique CNVs for which interpretation remain ambiguous. The medical geneticist is best equipped to interpret such information to families and the medical home.

Since the 2006 AAP clinical report, several additional reports have been published regarding metabolic testing for a cause of ID. 13 , 37 , – 40 The percentage of patients with identifiable metabolic disorders as cause of the ID ranges from 1% to 5% in these reports, a range similar to those studies included in the 2006 clinical report. Likewise, these newer published case series varied by site, age range of patients, time frame, study protocol, and results. However, they do bring renewed focus to treatable metabolic disorders. 13 Furthermore, some of the disorders identified are not included currently in any newborn screening blood spot panels. Although the prevalence of inherited metabolic conditions is relatively low (0% to 5% in these studies), the potential for improved outcomes after diagnosis and treatment is high. 41  

In 2005, Van Karnebeek et al 40 reported on a comprehensive genetic diagnostic evaluation of 281 consecutive patients referred to an academic center in the Netherlands. All patients were subjected to a protocol for evaluation and studies were performed for all patients with an initially unrecognized cause of mental retardation and included urinary screen for amino acids, organic acids, oligosaccharides, acid mucopolysaccharides, and uric acid; plasma concentrations of total cholesterol and diene sterols of 7- and 8-dehydrocholesterol to identify defects in the distal cholesterol pathway; and a serum test to screen for congenital disorders of glycosylation (test names such as “carbohydrate-deficient transferrin”). In individual patients, other searches were performed as deemed necessary depending on results of earlier studies. This approach identified 7 (4.6%) subjects with “certain or probable” metabolic disorders among those who completed the metabolic screening ( n = 216). None of the 176 screening tests for plasma amino acids and urine organic acids was abnormal. Four children (1.4%) with congenital disorders of glycosylation were identified by serum sialotransferrins, 2 children had abnormal serum cholesterol and 7-dehydrocholesterol concentrations suggestive of Smith-Lemli-Opitz syndrome, 2 had evidence of a mitochondrial disorder, 1 had evidence of a peroxisomal disorder, and 1 had abnormal cerebrospinal fluid biogenic amine concentrations. These authors concluded that “screening for glycosylation defects proved useful, whereas the yield of organic acid and amino acid screening was negligible.”

In a similar study from the Netherlands done more recently, Engbers et al 39 reported on metabolic testing that was performed in 433 children whose GDD/ID remained unexplained after genetic/metabolic testing, which included a standard karyotype; urine screen for amino acids, organic acids, mucopolysaccharides, oligosaccharides, uric acid, sialic acid, purines, and pyrimidines; and plasma for amino acids, acylcarnitines, and sialotransferrins. Screenings were repeated, and additional testing, including cerebrospinal fluid studies, was guided by clinical suspicion. Metabolic disorders were identified and confirmed in 12 of these patients (2.7%), including 3 with mitochondrial disorders; 2 with creatine transporter disorders; 2 with short-chain acyl-coenzyme A dehydrogenase deficiency; and 1 each with Sanfilippo IIIa, a peroxisomal disorder; a congenital disorder of glycosylation; 5-methyltetrahydrofolate reductase deficiency; and deficiency of the GLUT1 glucose transporter.

Other studies have focused on the prevalence of disorders of creatine synthesis and transport. Lion-François et al 37 reported on 188 children referred over a period of 18 months with “unexplained mild to severe mental retardation, normal karyotype, and absence of fragile X syndrome” who were prospectively screened for congenital creatine deficiency syndromes. Children were from diverse ethnic backgrounds. Children with “polymalformative syndromes” were excluded. There were 114 boys (61%) and 74 girls (39%) studied. Creatine metabolism was evaluated by using creatine/creatinine and guanidinoacetate (GAA)-to-creatine ratios on a spot urine screen. Diagnosis was further confirmed by using brain proton magnetic resonance spectroscopy and mutation screening by DNA sequence analysis in either the SLC6A8 (creatine transporter defect) or the GAMT genes. This resulted in a diagnosis in 5 boys (2.7% of all; 4.4% of boys). No affected girls were identified among the 74 studied. All 5 boys also were late to walk, and 3 had “autistic features.” The authors concluded that all patients with undiagnosed ID have urine screened for creatine-to-creatinine ratio and GAA-to-creatine ratio. Similarly, Caldeira Arauja et al 38 studied 180 adults with ID institutionalized in Portugal, screening them for congenital creatine deficiency syndromes. Their protocol involved screening all subjects for urine and plasma uric acid and creatinine. Patients with an increased urinary uric acid-to-creatinine ratio and/or decreased creatinine were subjected to the analysis of GAA. GAMT activity was measured in lymphocytes and followed by GAMT gene analysis. This resulted in identifying 5 individuals (2.8%) from 2 families with GAMT deficiency. A larger but less selective study of 1600 unrelated male and female children with GDD/ID and/or autism found that 34 (2.1%) had abnormal urine creatine-to-creatinine ratios, although only 10 (0.6%) had abnormal repeat tests and only 3 (0.2%) were found to have an SLC6A8 mutation. 42 Clark et al 43 identified SLC6A8 mutations in 0.5% of 478 unrelated boys with unexplained GDD/ID.

Recently, van Karnebeek and Stockler reported 13 , 42 on a systematic literature review of metabolic disorders “presenting with intellectual disability as a major feature.” The authors identified 81 treatable genetic metabolic disorders presenting with ID as a major feature. Of these disorders, 50 conditions (62%) were identified by routinely available tests ( Tables 2 and 3 ). Therapeutic modalities with proven effect included diet, cofactor/vitamin supplements, substrate inhibition, enzyme replacement, and hematopoietic stem cell transplant. The effect on outcome (IQ, developmental performance, behavior, epilepsy, and neuroimaging) varied from improvement to halting or slowing neurocognitive regression. The authors emphasized the approach as one that potentially has significant impact on patient outcomes: “This approach revisits current paradigms for the diagnostic evaluation of ID. It implies treatability as the premise in the etiologic work-up and applies evidence-based medicine to rare diseases.” Van Karnebeek and Stockler 13 , 42 reported on 130 patients with ID who were “tested” per this metabolic protocol; of these, 6 (4.6%) had confirmed treatable inborn errors of metabolism and another 5 (3.8%) had “probable” treatable inborn error of metabolism.

Metabolic Screening Tests

See Fig 1 .

Serum lead, thyroid function studies not included as “metabolic tests” and to be ordered per clinician judgment.

Metabolic Conditions Identified by Tests Listed

Adapted from van Karnebeek and Stockler. 41  

Acylcarn, acylcarnitine profile; CPS, carbamyl phosphate synthetase; GA, glutaric acidemia; HHH, hyperornithinemia-hyperammonemia-homocitrullinuria; HMG-CoA, 3-hydroxy-3-methylglutaryl-coenzyme A; MHBD, 2-methyl-3-hydroxybutyryl CoA dehydrogenase; MMA, methylmalonic acidemia; MTHFR, methylenetetrahydrofolate reductase; NAGS, N-acetylglutamate synthase; OTC, ornithine transcarbamylase; PAA, plasma amino acids; PDH, pyruvate dehydrogenase; P-HCY, plasma homocysteine; PKU; phenylketonuria; PPA, propionic acid; SCOT, succinyl-CoA:3-ketoacid CoA transferase; SSADH, succinic semialdehyde dehydrogenase; UGAA/creat; urine guanidino acid/creatine metabolites; UMPS, urine mucopolysaccharides qualitative screen (glycosaminoglycans); UOA, urine organic acids; UOGS, urine oligosaccharides; UPP, urine purines and pyrimidines.

Late-onset form of condition listed; some conditions are identified by more than 1 metabolic test.

This literature supports the need to consider screening children presenting with GDD/ID for treatable metabolic conditions. Many metabolic screening tests are readily available to the medical home and/or local hospital laboratory service. Furthermore, the costs for these metabolic screening tests are relatively low.

For patients in whom a diagnosis is suspected, diagnostic molecular genetic testing is required to confirm the diagnosis so that proper health care is implemented and so that reliable genetic counseling can be provided. For patients with a clinical diagnosis of a Mendelian disorder that is certain, molecular genetic diagnostic testing usually is not required to establish the diagnosis but may be useful for health care planning. However, for carrier testing or for genetic counseling of family members, it is often essential to know the specific gene mutation in the proband.

For patients with GDD/ID for whom the diagnosis is not known, molecular genetic diagnostic testing is necessary, under certain circumstances, which is discussed in the next section.

There is an approximate 40% excess of boys in all studies of prevalence and incidence of ID. 44 , 45 Part of this distortion of the gender ratio is attributable to X-linked genetic disorders. 46 Consequently, genetic testing for X-linked genes in boys with GDD/ID is often warranted, particularly in patients whose pedigree is suggestive of an X-linked condition. In addition, for several reasons, research in X-linked genes that cause ID is advanced over autosomal genes, 46 , 47 thus accelerating the clinical capacity to diagnose XLID over autosomal forms.

Most common of these is fragile X syndrome, although the prevalence of all other X-linked genes involved in ID far exceeds that of fragile X syndrome alone. 46 Fragile X testing should be performed in all boys and girls with GDD/ID of unknown cause. Of boys with GDD/ID of uncertain cause, 2% to 3% will have fragile X syndrome (full mutation of FMR1 , >200 CGG repeats), as will 1% to 2% of girls (full mutation). 48  

Stevenson and Schwartz 49 suggest 2 clinical categories for those with XLID: syndromal and nonsyndromal. Syndromal refers to patients in whom physical or neurologic signs suggest a specific diagnosis; nonsyndromal refers to those with no signs or symptoms to guide the diagnostic process. Using this classification has practical applicability, because the pediatric primary care provider can establish a specific XLID syndrome on the basis of clinical findings. In contrast, nonsyndromal conditions can only be distinguished on the basis of the knowledge of their causative gene. 50 In excess of 215 XLID conditions have been recorded, and >90 XLID genes have been identified. 46 , 50  

To address male patients with GDD/ID and X-linked inheritance, there are molecular genetic diagnostic “panels” of X-linked genes available clinically. These panels examine many genes in 1 “test sample.” The problem for the clinical evaluation is in which patient to use which test panel, because there is no literature on head-to-head performance of test panels, and the test panels differ somewhat by genes included, test methods used, and the rate of a true pathogenic genetic diagnosis. Nevertheless, the imperative for the diagnostic evaluation remains the same for families and physicians, and there is a place for such testing in the clinical evaluation of children with GDD/ID. For patients with an X-linked pedigree, genetic testing using one of the panels is clinically indicated. The clinical geneticist is best suited to guide this genetic testing of patients with possible XLID. For patients with “syndromal” XLID (eg, Coffin-Lowry syndrome), a single gene test rather than a gene panel is indicated. Whereas those patients with “nonsyndromal” presentation might best be assessed by using a multigene panel comprising many of the more common nonsyndromal XLID genes. The expected rate of the diagnosis may be high. Stevenson and Schwartz 46 reported, for example, on 113 cases of nonspecific ID testing using a 9-gene panel of whom 9 (14.2%) had pathogenic mutations identified. de Brouwer et al 51 reported on 600 families with multiple boys with GDD/ID and normal karyotype and FMR1 testing. Among those families with “an obligate female carrier” (defined by pedigree analysis and linkage studies), a specific gene mutation was identified in 42%. In addition, in those families with more than 2 boys with ID and no obligate female carrier or without linkage to the X chromosome, 17% of the ID cases could be explained by X-linked gene mutations. This very large study suggested that testing of individual boys for X-linked gene mutations is warranted.

Recently, clinical laboratories have begun offering “high-density” X-CMAs to assess for pathogenic CNVs (see previous discussion regarding microarrays) specifically for patients with XLID. Wibley et al 30 (2010) reported on CNVs in 251 families with evidence of XLID who were investigated by array comparative genomic hybridization on a high-density oligonucleotide X-chromosome array platform. They identified pathogenic CNVs in 10% of families. The high-density arrays for XLID are appropriate in those patients with syndromal or nonsyndromal XLID. The expected diagnostic rate remains uncertain, although many pathogenic segmental duplications are reported (for a catalog of X-linked mutations and CNVs, see http://www.ggc.org/research/molecular-studies/xlid.html ).

Whole exome sequencing and whole-genome sequencing are emerging testing technologies for patients with nonspecific XLID. Recently, Tarpey et al 52 have reported the results of the large-scale systematic resequencing of the coding X chromosome to identify novel genes underlying XLID. Gene coding sequences of 718 X-chromosome genes were screened via Sanger sequencing technology in probands from 208 families with probable XLID. This resequencing screen contributed to the identification of 9 novel XLID-associated genes but identified pathogenic sequence variants in only 35 of 208 (17%) of the cohort families. This figure likely underestimates the general contribution of sequence variants to XLID given the subjects were selected from a pool that had had previous clinical and molecular genetic screening. 30  

Table 4 lists some common XLID conditions. In cases in which the diagnosis is not certain, molecular genetic testing of patients for the specific gene is indicated, even if the pedigree does not indicate other affected boys (ie, cannot confirm X-linked inheritance). 46  

Common Recognizable XLID Syndromes

Reproduced with permission from Stevenson and Schwartz. 46  

Rett syndrome is an X-linked condition that affects girls and results from MECP2 gene mutations primarily (at least 1 other gene has been determined causal in some patients with typical and atypical Rett syndrome: CDKL5) . Girls with mutations in the MECP2 gene do not always present clinically with classic Rett syndrome. Several large case series have examined the rate of pathogenic MECP2 mutations in girls and boys with ID. The proportion of MECP2 mutations in these series ranged from 0% to 4.4% with the average of 1.5% among girls with moderate to severe ID. 53 , – 62   MECP2 mutations in boys present with severe neonatal encephalopathy and not with GDD/ID.

Currently, the literature does not indicate consensus on the role that neuroimaging, either by computed tomography (CT) or MRI, can play in the evaluation of children with GDD/ID. Current recommendations range from performing brain imaging on all patients with GDD/ID, 63 to performing it only on those with indications on clinical examination, 12 to being considered as a second-line investigation to be undertaken when features in addition to GDD are detected either on history or physical examination. The finding of a brain abnormality or anomaly on neuroimaging may lead to the recognition of a specific cause of an individual child’s developmental delay/ID in the same way that a dysmorphologic examination might lead to the inference of a particular clinical diagnosis. However, like other major or minor anomalies noted on physical examination, abnormalities on neuroimaging typically are not sufficient for determining the cause of the developmental delay/ID; the underlying precise, and presumably frequently genetic in origin, cause of the brain anomaly is often left unknown. Thus, although a central nervous system (CNS) anomaly (often also called a “CNS dysgenesis”) is a useful finding and indeed may be considered, according to the definition of Schaefer and Bodensteiner, 11 a useful “diagnosis.” However, it is frequently not an etiologic or syndromic diagnosis. This distinction is not always made in the literature on the utility of neuroimaging in the evaluation of children with developmental delay/ID. The lack of a consistent use of this distinction has led to confusion regarding this particular issue.

Early studies on the use of CT in the evaluation of children with idiopathic ID 64 indicated a low diagnostic yield for the nonspecific finding of “cerebral atrophy,” which did not contribute to clarifying the precise cause of the ID. 65 Later studies that used MRI to detect CNS abnormalities suggested that MRI was more sensitive than CT, with an increased diagnostic yield. 10 , 66 The rate of abnormalities actually detected on imaging varies widely in the literature as a result of many factors, such as subject selection and the method of imaging used (ie, CT or MRI). Schaefer and Bodensteiner, 63 in their literature review, found reported ranges of abnormalities from 9% to 80% of those patients studied. Shevell et al 10 reported a similar range of finding in their review. For example, in 3 studies totaling 329 children with developmental delay in which CT was used in almost all patients and MRI was used in but a small sample, a specific cause was determined in 31.4%, 67 27%, 68 and 30% 69 of the children. In their systematic review of the literature, van Karnebeek et al 12 reported on 9 studies that used MRI in children with ID. The mean rate of abnormalities found was 30%, with a range of 6.2% to 48.7%. These investigators noted that more abnormalities were found in children with moderate to profound ID versus those with borderline to mild ID (mean yield of 30% and 21.2%, respectively). These authors also noted that none of the studies reported on the value of the absence of any neurologic abnormality for a diagnostic workup and concluded that “the value for finding abnormalities or the absence of abnormalities must be higher” than the 30% mean rate implied.

If neuroimaging is performed in only selected cases, such as children with an abnormal head circumference or an abnormal focal neurologic finding, the rate of abnormalities detected is increased further than when used on a screening basis in children with a normal neurologic examination except for the documentation of developmental delay. Shevell et al 68 reported that the percentage of abnormalities were 13.9% if neuroimaging was performed on a “screening basis” but increased to 41.2% if performed on “an indicated basis.” Griffiths et al 70 highlighted that the overall risk of having a specific structural abnormality found on MRI scanning was 28% if neurologic symptoms and signs other than developmental delay were present, but if the developmental delay was isolated, the yield was reduced to 7.5%. In a series of 109 children, Verbruggen et al 71 reported an etiologic yield on MRI of 9%. They noted that all of these children had neurologic signs or an abnormal head circumference. In their practice parameter, the American Academy of Neurology and the Child Neurology Society 10 discussed other studies on smaller numbers of patients who showed similar results, which led to their recommendation that “neuroimaging is a recommended part of the diagnostic evaluation,” particularly should there be abnormal findings on examination (ie, microcephaly, macrocephaly, focal motor findings, pyramidal signs, extrapyramidal signs) and that MRI is preferable to CT. However, the authors of the American College of Medical Genetics Consensus Conference Report 10 stated that neuroimaging by CT or MRI in normocephalic patients without focal neurologic signs should not be considered a “standard of practice” or mandatory and believed that decisions regarding “cranial imaging will need to follow (not precede) a thorough assessment of the patient and the clinical presentation.” In contrast, van Karnebeek et al 12 found that MRI alone leads to an etiologic diagnosis in a much lower percentage of patients studied. They cited Kjos et al, 72 who reported diagnoses in 3.9% of patients who had no known cause for their ID and who did not manifest either a progressive or degenerative course in terms of their neurologic symptomatology. Bouhadiba et al 73 reported diagnoses in 0.9% of patients with neurologic symptoms, and in 4 additional studies, no etiologic or syndromic diagnosis on the basis of neuroimaging alone was found. 65 , 69 , 74 , 75 The authors of 3 studies reported the results on unselected patients; Majnemer and Shevell 67 reported a diagnosis by this typed unselected investigation in 0.2%, Stromme 76 reported a diagnosis in 1.4% of patients, and van Karnebeek et al 40 reported a diagnosis in 2.2% of patients.

Although a considerable evolution has occurred over the past 2 decades in neuroimaging techniques and modalities, for the most part with the exception of proton magnetic resonance spectroscopy, this has not been applied or reported in the clinical situation of developmental delay/ID in childhood. Proton resonance spectroscopy provides a noninvasive mechanism of measuring brain metabolites, such as lactate, using technical modifications to MRI. Martin et al 77 did not detect any differences in brain metabolite concentrations among stratifications of GDD/ID into mild, moderate, and severe levels. Furthermore, they did not detect any significant differences in brain metabolite concentration between children with GDD/ID and age-matched typically developing control children. Thus, these authors concluded that proton resonance spectroscopy “has little information concerning cause of unexplained DD.” Similarly, the studies by Martin et al 77 and Verbruggen et al 71 did not reveal that proton magnetic resonance spectroscopy was particularly useful in the determination of an underlying etiologic diagnosis in children with unexplained developmental delay/ID.

All of these findings suggest that abnormal findings on MRI are seen in ∼30% of children with developmental delay/ID. However, only in a fraction of these children does MRI lead to an etiologic or syndromic diagnosis. The precise value of a negative MRI result in leading to a diagnosis has not yet been studied in detail. In addition, MRI in the young child with developmental delay/ID invariably requires sedation or, in some cases, anesthesia to immobilize the child to accomplish the imaging study. This need, however, is decreasing with faster acquisition times provided by more modern imaging technology. Although the risk of sedation or anesthesia is small, it still merits consideration within the decision calculus for practitioners and the child’s family. 63 , 78 , 79 Thus, although MRI is often useful in the evaluation of the child with developmental delay/ID, at present, it cannot be definitively recommended as a mandatory study, and it certainly has higher diagnostic yields when concurrent neurologic indications exist derived from a careful physical examination of the child (ie, microcephaly, microcephaly, seizures, or focal motor findings).

The following is the recommended medical genetic diagnostic evaluation flow process for a new patient with GDD/ID. All patients with ID, irrespective of degree of disability, merit a comprehensive medical evaluation coordinated by the medical home in conjunction with the medical genetics specialist. What follows is the clinical genetics evaluation ( Fig 1 ):

FIGURE 1. Diagnostic process and care planning. Metabolic test 1: blood homocysteine, acylcarnitine profile, amino acids; and, urine organic acids, glycosaminoglycans, oligosaccharides, purines, pyrimidines, GAA/creatine metabolites. Metabolic test 2 based on clinical signs and symptoms. FH, family history; MH, medical history; NE, neurologic examination; PE, physical and dysmorphology examination.

Diagnostic process and care planning. Metabolic test 1: blood homocysteine, acylcarnitine profile, amino acids; and, urine organic acids, glycosaminoglycans, oligosaccharides, purines, pyrimidines, GAA/creatine metabolites. Metabolic test 2 based on clinical signs and symptoms. FH, family history; MH, medical history; NE, neurologic examination; PE, physical and dysmorphology examination.

Complete medical history; 3-generation family history; and physical, dysmorphologic, and neurologic examinations.

If the specific diagnosis is certain, inform the family and the medical home, providing informational resources for both; set in place an explicit shared health care plan 80 with the medical home and family, including role definitions; provide sources of information and support to the family; provide genetic counseling services by a certified genetic counselor; and discuss treatment and prognosis. Confirm the clinical diagnosis with the appropriate genetic testing, as warranted by clinical circumstances.

If a specific diagnosis is suspected, arrange for the appropriate diagnostic studies to confirm including single-gene tests or chromosomal microarray test.

If diagnosis is unknown and no clinical diagnosis is strongly suspected, begin the stepwise evaluation process:

Chromosomal microarray should be performed in all.

Specific metabolic testing should be considered and should include serum total homocysteine, acyl-carnitine profile, amino acids; and urine organic acids, glycosaminoglycans, oligosaccharides, purines, pyrimidines, GAA/creatine metabolites.

Fragile X genetic testing should be performed in all.

If no diagnosis is established:

Male gender and family history suggestive X-linkage, complete XLID panel that contains genes causal of nonsyndromic XLID and complete high-density X-CMA. Consider X-inactivation skewing in the mother of the proband.

Female gender: complete MECP2 deletion, duplication, and sequencing study.

If microcephaly, macrocephaly, or abnormal findings on neurologic examination (focal motor findings, pyramidal signs, extrapyramidal signs, intractable epilepsy, or focal seizures), perform brain MRI.

If brain MRI findings are negative or normal, review status of diagnostic evaluation with family and medical home.

Consider referrals to other specialists, signs of inborn errors of metabolism for which screening has not yet been performed, etc.

If no further studies appear warranted, develop a plan with the family and medical home for needed services for child and family; also develop a plan for diagnostic reevaluation.

Health care systems, processes, and outcomes vary geographically, and not all of what is recommended in this clinical report is easily accessible in all regions of the United States. 21 , 81 , – 84 Consequently, local factors affect the process of evaluation and care. These arrangements are largely by local custom or design. In some areas, there may be quick access and intimate coordination between the medical home and medical genetics specialist, but in other regions, access may be constrained by distance or by decreased capacity, making for long wait times for appointments. Some general pediatricians have the ability to interpret the results of genetic testing that they may order. In addition, children with GDD or ID are often referred by pediatricians to developmental pediatricians, child neurologists, or other subspecialists. It is appropriate for some elements of the medical genetic evaluation to be performed by physicians other than medical geneticists if they have the ability to interpret the test results and provide appropriate counseling to the families. In such circumstances, the diagnostic evaluation process can be designed to address local particularities. The medical home is responsible for referrals of the family and child to the appropriate special education or early developmental services professional for individualized services. In addition, the medical home can begin the process of the diagnostic evaluation if access is a problem and in coordination with colleagues in medical genetics. 80 , 85 What follows is a suggested process for the evaluation by the medical home and the medical genetics specialist and only applies where access is a problem; any such process is better established with local particularities in mind:

Medical home completes the medical evaluation, determines that GDD/ID is present, counsels family, refers to educational services, completes a 3-generation family history, and completes the physical examination and addresses the following questions:

Does the child have abnormalities on the dysmorphologic examination?

If no or uncertain, obtain microarray, perform fragile X testing, and consider the metabolic testing listed previously. Confirm that newborn screening was completed and reported negative. Refer to medical genetics while testing is pending.

If yes, send case summary and clinical photo to medical genetics center for review for syndrome identification. If diagnosis is suspected, arrange for expedited medical genetics referral and hold all testing listed above. Medical geneticist to arrange visit with genetic counselor for testing for suspected condition.

Does the child have microcephaly, macrocephaly, or abnormal neurologic examination (listed above)? If “yes,” measure parental head circumferences and review the family history for affected and unaffected members. If normal head circumferences in both parents and negative family history, obtain brain MRI and refer to medical genetics.

Does child also have features of autism, cerebral palsy, epilepsy, or sensory disorders (deafness, blindness)? This protocol does not address these patients; manage and refer as per local circumstances.

As above are arranged and completed and negative, refer to medical genetics and hold on additional diagnostic testing until consultation completed. Continue with current medical home family support services and health care.

Should a diagnosis be established, the medical home, medical geneticist, and family might then agree to a care plan with explicit roles and responsibilities of all.

Should a diagnosis not be established by medical genetics consultation, the medical home, family, and medical geneticist can then agree on the frequency and timing of diagnostic reevaluation while providing the family and child services needed.

Several research reports have cited whole-exome sequencing and whole-genome sequencing in patients with known clinical syndromes for whom the causative gene was unknown. These research reports identified the causative genes in patients with rare syndromes (eg, Miller syndrome, 86 Charcot-Marie-Tooth disease, 87 and a child with severe inflammatory bowel disease 88 ). Applying similar whole-genome sequencing of a family of 4 with 1 affected individual, Roach et al 86 identified the genes for Miller syndrome and primary ciliary dyskinesia. The ability to do whole-genome sequencing and interpretation at an acceptable price is on the horizon. 87 , 89 The use of exome or whole-genome sequencing challenges the field of medical genetics in ways not yet fully understood. When a child presents with ID and whole-genome sequencing is applied, one will identify mutations that are unrelated to the question being addressed, in this case “What is the cause of the child’s intellectual disability?” One assumes that this will include mutations that families do not want to have (eg, adult-onset disorders for which no treatment now exists). This is a sea change for the field of medical genetics, and the implications of this new technology have not been fully explored. In addition, ethical issues regarding validity of new tests, uncertainty, and use of resources will need to be addressed as these technologies become available for clinical use. 90 , 91  

The medical genetic diagnostic evaluation of the child with GDD/ID is best accomplished in collaboration with the medical home and family by using this clinical report to guide the process. The manner in which the elements of this clinical protocol are applied is subject to local circumstances, as well as the decision-making by the involved pediatric primary care provider and family. The goals and the process of the diagnostic evaluation are unchanged: to improve the health and well-being of those with GDD/ID. It is important to emphasize the new role of the genomic microarray as a first-line test, as well as the renewal of efforts to identify the child with an inborn error of metabolism. The future use of whole-genome sequencing offers promise and challenges needing to be addressed before regular implementation in the clinic.

John B. Moeschler, MD, MS, FAAP, FACMG

Michael Shevell, MDCM, FRCP

Robert A. Saul, MD, FAAP, Chairperson

Emily Chen, MD, PhD, FAAP

Debra L. Freedenberg, MD, FAAP

Rizwan Hamid, MD, FAAP

Marilyn C. Jones, MD, FAAP

Joan M. Stoler, MD, FAAP

Beth Anne Tarini, MD, MS, FAAP

Stephen R. Braddock, MD

Katrina M. Dipple, MD, PhD – American College of Medical Genetics

Melissa A. Parisi, MD, PhD – Eunice Kennedy Shriver National Institute of Child Health and Human Development

Nancy Rose, MD – American College of Obstetricians and Gynecologists

Joan A. Scott, MS, CGC – Health Resources and Services Administration, Maternal and Child Health Bureau

Stuart K. Shapira, MD, PhD – Centers for Disease Control and Prevention

American Academy of Pediatrics

chromosome microarray

central nervous system

copy number variant

computed tomography

fluorescent in situ hybridization

guanidinoacetate

global developmental delay

intellectual disability

X-linked intellectual disability

This document is copyrighted and is property of the American Academy of Pediatrics and its Board of Directors. All authors have filed conflict of interest statements with the American Academy of Pediatrics. Any conflicts have been resolved through a process approved by the Board of Directors. The American Academy of Pediatrics has neither solicited nor accepted any commercial involvement in the development of the content of this publication.

The guidance in this report does not indicate an exclusive course of treatment or serve as a standard of medical care. Variations, taking into account individual circumstances, may be appropriate.

All clinical reports from the American Academy of Pediatrics automatically expire 5 years after publication unless reaffirmed, revised, or retired at or before that time.

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Case study: child with global developmental delay

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  • 1 Department of Nursing, New York City College of Technology, New York, USA. [email protected]
  • PMID: 20646091
  • DOI: 10.1111/j.1744-618X.2010.01159.x

Purpose: This case study focused on the care of a child with global developmental delay.

Data sources: Data were obtained through the author's clinical practice in long-term care pediatric rehabilitation and literature sources.

Data synthesis: NANDA-International Classifications, the Nursing Interventions Classification (NIC), and Nursing Outcomes Classification (NOC) were used to identify the appropriate nursing diagnosis, nursing interventions, and patient outcomes.

Conclusions: This case study provides the pertinent nursing diagnoses, interventions, and outcomes for a child with global developmental delay. The interdisciplinary team approach and family involvement is addressed.

Implications for nursing: Use of NANDA, NIC, and NOC outcomes constructs for enhancing the care of a child with global developmental delay.

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Article Contents

Introduction, child development, developmental disability, early intervention for children with developmental disabilities, case studies of eci for children with developmental disabilities, the case for action, author's contributions, acknowledgements, competing interests, ethical approval.

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Early intervention for children with developmental disabilities in low and middle-income countries – the case for action

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Tracey Smythe, Maria Zuurmond, Cally J Tann, Melissa Gladstone, Hannah Kuper, Early intervention for children with developmental disabilities in low and middle-income countries – the case for action, International Health , Volume 13, Issue 3, May 2021, Pages 222–231, https://doi.org/10.1093/inthealth/ihaa044

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In the last two decades, the global community has made significant progress in saving the lives of children <5 y of age. However, these advances are failing to help all children to thrive, especially children with disabilities. Most early child development research has focussed on the impact of biological and psychosocial factors on the developing brain and the effect of early intervention on child development. Yet studies typically exclude children with disabilities, so relatively little is known about which interventions are effective for this high-risk group. In this article we provide an overview of child development and developmental disabilities. We describe family-centred care interventions that aim to provide optimal stimulation for development in a safe, stable and nurturing environment. We make the case for improving opportunities for children with developmental disabilities to achieve their full potential and thrive, including through inclusive early childhood development intervention. Finally, we call for the global research community to adopt a systematic approach for better evidence for and implementation of early interventions for children with developmental disabilities in low-resource settings.

Substantial global progress has been made in reducing child deaths since 1990 and the mortality rate of children <5 y of age has decreased in all world regions. However, non-communicable morbidities and disabilities have not been addressed to the same extent. This review discusses the urgency of taking actions to narrow the inequality gap in early childhood developmental care, especially for the 53 million children <5 y of age living with disabilities and developmental disorders such as epilepsy, intellectual disability, sensory impairments, autism spectrum disorder and attention deficit hyperactivity disorder. 1 A focus on supporting children with disabilities to thrive during their early years is important, as this period is critical for maximising their development. Furthermore, under the United Nations Convention of Rights for a Child and the United Nations Convention of the Rights of Persons with Disabilities, governments are duty-bound to provide early years services that are inclusive of and available to all children. 2 , 3 This article will describe child development and developmental disabilities and make the case for which equitable early childhood development (ECD) interventions may be optimal for helping children with developmental disabilities to achieve their potential.

Early childhood is a period of great opportunity for optimum brain growth, but it is also a period of vulnerability. Development in language, cognition, motor and socio-emotional domains occurs rapidly in these first years. These areas of development do not operate or develop in isolation, but enable each other and mutually interact as the child learns to become more independent. For instance, as a child learns to see, she will increasingly reach for and play with objects and thereby develop motor skills and coordination. Biological, psychosocial 4 , 5 and environmental factors also crucially affect the structure and functioning of the brain as it is developing. 6 For example, if a child experiences adequate nutrition and is provided with opportunities to play, she may progressively explore her environment and interact with her caregiver and by doing so, reinforce her psychosocial development. Furthermore, the time period when these factors influence brain growth are critically important, as there are particular early windows of opportunity that if not harnessed, may prevent optimal brain development and lifelong well-being. 7

It is increasingly apparent that optimal early child development has lifetime beneficial consequences for educational achievement, adult productivity and population health. 8–10 Conversely, exposure to biological and psychosocial risks negatively affects the developing brain and compromises the development of children. 5 Many structural factors determine these early child circumstances. These factors include a lack of nurturing care (nutrition, stimulation, good health) in the early years, as well as inadequate cognitive and psychosocial stimulation. 5 , 11 Children <5 y of age in low- and middle-income countries (LMICs) may be particularly at risk of poor development due to poor health and nutrition. 7

Child development can be encouraged through intervention in early childhood. 11 A number of mutually important elements are needed for maximising children's development. These include supporting responsive relationships, reducing sources of stress in the lives of children and families, building executive function and self-regulation skills and reinforcing contexts in which learning is most achievable across all developmental domains. 12 , 13 ECD interventions work to improve development through integrating family support, health, nutrition and educational services and providing direct learning experiences to young children and families. 14

The strategic focus of the World health Organization (WHO), United Nations Children's Fund (UNICEF) and World Bank ‘Nurturing Care Framework’ is therefore timely. 15–17 This action plan provides a framework for helping children survive and thrive through five strategic actions—lead and invest, focus on families and their communities, strengthen services, monitor progress and use data and innovate—and thereby aims to transform health and human potential. We know that urgent action is necessary to improve early childhood outcomes and ensure that all children reach their full potential as adults. Children with developmental disabilities must be included in this agenda, as they are a marginalised group with additional and specific needs and will otherwise be left behind.

Developmental delay and developmental disability are two distinct concepts. Developmental delay is often defined as a deviation from normative milestones; this may be in terms of delayed cognitive, language, motor and/or socio-emotional development. 18 The term developmental disabilities covers a range of childhood conditions and is used differently across different settings and cultures. 19 In this article we define developmental disability as a heterogeneous group of conditions that can impact on the development of children's function (e.g. sensory, cognitive, physical), with a very wide range of effects. 20 Developmental disability is the most common cause of childhood disability, with an estimated 53 million children <5 y of age living with developmental disabilities globally. 21 This estimate is based on only six conditions (epilepsy, intellectual disability, vision loss, hearing loss, autism and attention deficit hyperactivity disorder) and on present reporting of these conditions. It is likely therefore that the true number of children with developmental disability is much higher than this estimate, particularly if a broader age range is considered.

The majority of children with developmental disabilities live in LMICs, 21 and the prevalence is higher among families with high levels of poverty and low education. 27 However, there remain data gaps for the prevalence, epidemiology and causes of developmental disabilities in LMICs. 28 One reason for the uncertainty in the estimates is that identification of children with or at risk of developmental delay requires assessment using valid developmental evaluation tools to measure ECD 29 (Box 1 ), and these facilities are often not available in LMICs.

Identification of children with developmental disabilities

The impacts of developmental disabilities extend far beyond functional abilities. Children with developmental disabilities and their families are at high risk of social exclusion, exclusion from education and even stigma and violence. 30 Furthermore, looking after a child with developmental disabilities potentially places an enormous strain on families, and caregivers experience high levels of stress, anxiety, depression, physical exhaustion, stigma and discrimination. 31 This further increases the risk of mental ill health and social isolation in caregivers. A recent systematic review found caregivers of children with intellectual and developmental disabilities, when compared with caregivers of children without intellectual and developmental disabilities, experienced elevated levels of depressive symptoms (31% vs 7%, respectively) and anxiety symptoms (31% vs 14%, respectively). 32 There are also substantial costs to childhood disability, both the cost of additional services and resources required by the child and the lost income from parents who are caring for their child. Consequently, childhood disability may exacerbate poverty. 33 , 34 However, there is generally a lack of available services and support for children with disabilities and their families, especially in LMICs, which further compound these risks.

Evidence is limited, but growing, on the effectiveness of ECD interventions for children at risk of and with developmental delays, particularly in LMICs. 35 Indeed, many programmes and studies actively exclude children with developmental disabilities, as additional considerations may be required, and children with developmental disabilities may be unable to show progress when using developmental progress as the primary outcome 9 , 36–38 (Box 2 ).

Inclusion of children with developmental disabilities in clinical trials

Consequently, risks to delayed development are compounded for children with developmental disabilities, as they potentially receive less stimulation and fewer learning opportunities through other health service or care routes. 39 Exclusion of children with developmental disabilities from ECD thus perpetuates an already fragile cycle of development. We know that early childhood developmental intervention for these children is imperative, but we cannot inform planning and delivery of inclusive services for all children without better research in this area. For example, there are gaps in evidence-based approaches to monitoring and evaluation of ECD projects in LMICs, such as challenges in measurement of outcomes in routine programmes, which limit comparative understanding of impact, and in defining and monitoring quality and coverage. 25

Early identification of children with developmental disabilities, as well as early childhood intervention (ECI), improves children's opportunities to maximise their developmental potential and functioning as well as their quality of life and social participation. 40 , 41 Early identification and intervention are two distinct complementary strands; timely identification of children with developmental disabilities is required for early intervention, which strengthens the cumulative process of development, helping children acquire new skills and behaviours to reinforce and strengthen learning. In addition, some ECIs may have wider benefits for caregivers, such as through establishing support, thus helping build their knowledge, confidence and coping strategies, 32 with positive impacts for their mental health. However, data are lacking from LMICs and there is a paucity of implementation evidence to guide policymakers and donors. 33

ECI for children with disabilities can comprise a range of coordinated multidisciplinary services and can take many forms, including hospital- or clinic-based care, school-based programmes, parenting and community support and home-based childhood therapies. In high-resource settings, we know that family-centred interventions are more likely to result in the greatest satisfaction with services and improve psychosocial well-being for the child and caregiver. 42 With regards to impact, a systematic review of ECIs for children at risk of cerebral palsy demonstrated improved cognitive outcomes up to preschool age and improved motor outcomes during infancy, although variability in interventions limited the identification of which interventions are most effective. 43 Nevertheless, without such ECIs in LMICs, years lived with disability will be more than 3.3 million. 1

There are broadly two approaches to providing ECI for children with developmental disabilities, including children with disabilities in mainstream ECD interventions and targeted intervention programmes for children with disabilities. These approaches take many different forms, as they are used to support children and families with different needs. For example, universal programmes in the UK, such as the five mandated health visits for young children, are offered to all families. In contrast, targeted programmes, such as the Disabled Children's Outreach Service (DCOS), are aimed specifically at vulnerable families of children with a disability where the children are at higher risk of poor outcomes in later life. 44

While both inclusive and targeted efforts for children with disabilities at the level of early childhood centres have increased, 45 weak country health systems and conflict settings are major impediments to delivering high-quality services. 46 There remains a need for inclusive approaches for children with developmental disabilities in mainstream services, as well as within specialist ECIs. This means that the role of families can be particularly crucial to fill existing gaps in service availability.

A number of case studies have been identified for ECI for children with developmental disabilities. The following have been selected for description, as they illustrate different approaches for children with different developmental disabilities in several LMIC settings.

The WHO has developed Caregiver Skills Training (CST) for caregivers of children with intellectual disabilities. 47 , 48 The CST consists of nine group sessions and three home visits. The programme teaches strategies to promote communication and learning and address challenging behaviours. However, sustainable and scalable quality delivery of the group format by a lay facilitator remains a challenge due to limited integration in health systems. 49 Evidence of effectiveness is currently lacking, but randomised controlled trials are under way in Pakistan (Family Networks [FaNs] for Children with Developmental Disorders and Delays 50 ) and Italy, with future trials planned in China, Ethiopia and Kenya. 51

Interventions that aim to provide contextualised psychological support to caregivers of children with intellectual disabilities include ‘Titukulane’, a community group intervention that aims to reduce mental health problems among the parents of affected children. 52 This community-based intervention consists of eight modules that have been developed and piloted to help parents cope with the challenging role of caring for a child with intellectual disabilities.

Learning through Everyday Activities with Parents (LEAP-CP) is a family-centred intervention delivered peer to peer at home during 30 weekly 2h visits that aims to improve the mobility of children with cerebral palsy. 53 Visits include therapeutic modules (goal-directed active motor and cognitive strategies and LEAP-CP games) and parent education. Randomised controlled trials are currently under way in India. 54 The trial also provides nutrition and health support to all families in the study, which may influence the findings.

The London School of Hygiene & Tropical Medicine (UK) has developed three caregiver group interventions under the ‘Ubuntu’ umbrella (resources available from www.ubuntu-hub.org ). The interventions consist of 10 sessions, the content of which includes information about essential care practices, such as feeding, positioning, communication and play, offered through a local support group format. ‘Getting to know cerebral palsy’ was developed as a resource to empower families using a participatory approach at the community level. 31 , 55 The ABAaNA Early Intervention Programme (EIP) was developed in response to a recognised need to support families of very young children (<2 y) with an evolving developmental disability. 56 ‘Juntos’ was developed for children with congenital Zika syndrome and their families in Latin America and integrates a strengthened component on caregiver emotional well-being, arguably fundamental to a child's early development. 57–60

Interventions for children with autism spectrum disorder include PASS, a parent-mediated intervention for autism spectrum disorder in India and Pakistan. 61 The intervention uses video feedback methods to address parent–child interaction and was adapted for delivery by non-specialist workers. As PASS is focused on improving a child's social communication, common mental health comorbidities such as sleep difficulties will be important to integrate into wider intervention programmes.

These examples provide good case studies of diverse interventions for different children with developmental disabilities in different low-resource settings. These case studies indicate that in LMICs, the gap in meeting the holistic needs of children with developmental disabilities may be addressed through the use of community-based group interventions facilitated by trained and supervised health or peer support workers. Commonality is the focus on caregiver involvement, which is critical, particularly where there are few health services. Yet formal evaluation of their effectiveness and cost-effectiveness is lacking, in addition to limited implementation with education and social welfare, which hampers scaling of these services.

The number of children with developmental disabilities is large and the impacts on the child and family are extensive. There are valuable lessons learned from case studies, yet there remains insufficient progress in ECI for children with developmental disabilities and unmet needs are widespread. The causes of this gap are complex and diverse. An important reason is that in many settings health services are often fragile, poorly coordinated and overstrained, with concerns about the availability and quality of healthcare workers capable of delivering the intervention. Health systems gaps are particularly important in fragile states, including those affected by war and famine, as they experience many competing pressing needs. Furthermore, the policy agenda supporting a focus on children with developmental disabilities is weak internationally and nationally in many cases, limiting the priority given to this issue and the availability of funding for developing services. Ensuring inclusive education is a clear responsibility for United Nations member states under international treaties and Sustainable Development Goal 4, to ‘ensure inclusive, equitable quality education for all’. However, investing in inclusion prior to schooling is not mandated and consequently becomes optional. Cultural challenges also exist, such as widespread stigma and discrimination around children with disabilities and their families. 62 Finally, the evidence base on needs for and effectiveness of services is currently weak and needs to be strengthened. Enhancing environments that provide equal opportunities for children with developmental disabilities for ECI therefore requires a systems approach with global collaboration.

Accordingly, priorities for future research to ensure that all young children reach their development potential include assessment of the effect of interventions for children with developmental disability and their families in different low-resource settings. Further identification of barriers to accessing general services (e.g. primary healthcare) as well as specialist services is also required, as poverty remains a major issue for affected families in LMICs. Furthermore, studies that identify how to maximise the reach and cost-effectiveness of ECD interventions for children with developmental disabilities are warranted. Evaluation of how these interventions can be embedded within health systems are needed to strengthen the service delivery strategies. Global collaboration in these efforts are required in research, and critical steps include providing best evidence on practices to improve knowledge and skills at local levels to avoid children with developmental disabilities being turned away from existing services and evidence of ‘what works’ to provide sustainable, inclusive ECD interventions with impact in resource-constrained settings. We call for international research communities, including funders, to adopt a systematic approach for better evidence.

ECD interventions are aimed at improving the development of children. However, children with developmental disabilities are often excluded from these programmes, even though they have the greatest need for support. There is still a dearth of research about what interventions are effective in improving outcomes for this marginalised group and an even greater lack of evidence on cost-effectiveness and what can be successfully implemented at scale. A two-pronged approach is likely to be optimal, encouraging the inclusion of children with disabilities in mainstream ECD programmes, while also offering targeted approaches, most likely through caregivers. We call for global collaboration among international research communities, including funders, to adopt a systematic approach to strengthening the available evidence base of interventions for children with developmental disabilities and their families. We call for greater attention for this marginalised group, to prioritise public policies and hold governments accountable to ensure that multisectoral services centred around the child and his/her family are provided during this crucial time. This will contribute to ensuring that all children have an early foundation for optimal development, a key factor in equitable long-term health.

HK conceived the study. TS carried out the analysis and interpretation of case study data. TS and HK drafted the manuscript. MZ, CJT, MG and HK critically revised the manuscript for intellectual content. All authors read and approved the final manuscript. TS and HK are guarantors of the paper. The data underlying this article are available in the article and in its online supplementary material.

This work was supported by the Wellcome Trust and Department for International Development (grant 206719/Z/17/Z to HK). The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.

MG is a member of expert panels for the WHO and UNICEF on measurement of childhood development and disability. This research paper was undertaken outside and separate from these duties.

Not required.

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  • Published: 09 June 2023

Screen time and speech and language delay in children aged 12–48 months in UAE: a case–control study

  • Salwa Salem Al Hosani   ORCID: orcid.org/0000-0003-2323-0768 1 ,
  • Ebtihal Ahmed Darwish 2 ,
  • Sona Ayanikalath 3 ,
  • Ruqaya Saeed AlMazroei 4 ,
  • Radwha Saeed AlMaashari 4 &
  • Amer Tareq Wedyan 5  

Middle East Current Psychiatry volume  30 , Article number:  47 ( 2023 ) Cite this article

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To identify impact of screen time on speech and language development in preschool children. There has been an alarming increase in the use of electronic devices among preschool children despite their potential adverse effects on childhood development during this crucial time of rapid brain development. Prior research has identified the potential risk and benefits of traditional screen media such as television and video. Our findings will help your readers understand the potential impact of screen time between traditional and new technologies. The case–control study included 227 new patients with language delay and 227 normal children, aged 12–48 months male and female. Language delay was diagnosed by reviewing language milestones and Receptive-Expressive Emergent Language Test (RELT). Television viewing variables and child/parental characteristics between both groups were interviewed. Odds ratio was used to establish whether screen time using either electronic devices (smartphones and tablets) or TV viewing has an effect on speech and language development. Chi-square test was used to establish the association between categorical variable 95%. A P -value less than 0.05 was considered to be statistically significant.

A total of 90.3% of those who have speech and language developmental delay use electronic devices. Odd ratio is found to be statistically significant.

The factors that predict language delays include use of and early onset of using an electronic device at 12–24 months of age. The factors that were less likely associated with language delays are watching TV and the mother’s education level.

Introduction

Language development begins in utero, and the first cry after birth is considered the first means of communicating needs that an infant has. The amount of caregiver response will draw the attachment relationship for normal social and emotional development. However, speech and language development milestones are a sensitive and critical period when language is rapidly acquired and environmental stimulation and linguistic input from caregivers aid language acquisition. We live in a digital era, and exposure to visual and verbal media stimulation encompasses language development, and the rapid advances in device manufacturing and diversity of devices and applications have led to a dramatic increase in the possession and the use of portable devices.

Screen time is the time spent using a device such as a computer, television, iPad, or mobile device. Exposure to digital media in the last decade is increasing considering the advancement in technologies. Since the 1970, the age at which the child first begin to exposed and interact with media screen has been lowered from 4 years to 4 months making children born as digital naïve [ 1 ].

Exposure to digital media is increasing and has led to concerns about the impact on child development. There has been an increasing interest in the link between media viewing and language development. Therefore, it is important to understand the relationship between screen time use and the language development of preschool children.

Furthermore, the American Academy of Pediatrics (AAP) guidelines stated that children below the age of 2 years should not have any screen exposure, and screen time of 3 h per day is considered excessive among children aged 2–5 years [ 2 ].

Excessive screen media use according to the recommendation of WHO was defined as follows: children aged 0–12 months exposed to media devices or children aged 2–7 years exposed to screen media use more than 1 h/day. Furthermore, UK guidelines set out by the National Institute for Clinical Excellence (NICE) recommend no more than 2 h of leisure screen time per day for children of any age.

However, families continue to exceed the hours of viewing recommended by the American Academy of Paediatrics (AAP). Gupta et al. have highlighted in a review that there is a high prevalence of excessive screen time among under-five5 children in the high- and middle-income countries. There are several health impacts of excessive screen time including emotional, sleep, and behavioral issues impairing the growth and cognitive development of under-5 children [ 3 ].

Systematic review by Chao Li et al. confirms that excessive screen time, mainly engaging in more than 2 h of daily screen time, has various health indicators in physical, behavioral, and psychosocial aspects [ 4 ].

The consequences of excessive screen time have garnered considerable attention in research, health, and public debate over the past decade [ 5 ]. This has led to an increasing interest by pediatric societies in the link between media viewing and language development. Therefore, understanding the relationship between screen time and language development of preschool children is important within child health and development.

Nathanson et al. found that TV viewing has a positive effect on the linguistic and cognitive development of children [ 6 ]. There have also been reports that it has a harmful effect on cognitive abilities, including attention and reading [ 6 , 7 , 8 , 9 , 10 , 11 ].

Zimmerman et al. have reported positive parental perception of screen time might explain early exposure to screen. Parents believed that screening media (e.g., television, DVD, video), if appropriately used, is educational and useful to their child’s brain development [ 12 ]. Dutch et al. published a longitudinal study of 119 Hispanic toddlers and found that families overwhelmingly believed (84%) that baby DVD and educational TV shows have a positive effect on their children’s learning [ 13 ].

Kabali also found that most children had their own tablet by age 4, which is a remarkable uptake of technology considering that in 2013, ownership of mobile devices among children aged 0 to 8 years was in the single digits nationwide [ 14 ].

Chonchaiya and Pruksananonda found that children who started watching television at lesser than 12 months of age and watched television more than 2 h per day were approximately six times more likely to have language delays [ 15 ]. Population-based studies continue to show negative impact between excessive television viewing in early childhood (0–2) years and cognitive development [ 16 , 17 , 18 ], language development [ 12 , 19 ], and social/emotional delays [ 20 , 21 , 22 , 23 ]. These delays are likely secondary to decreases in parent-child interactions when the television is on, as well as decreased family functioning in households with high media use [ 24 ].

Nathanson et al. found an earlier age of media use onset, and greater cumulative hours of media use are all significant independent predictors of poor executive functioning in preschoolers [ 6 ].

However, there have also even been reports that there is no significant correlation between TV watching time and the linguistic ability of Thai infants and toddlers [ 25 ]. Therefore, further studying the impact of TV viewing is needed.

Epidemiological studies that can represent the general population are required. We live in a digital era where electronic devices are quickly becoming the preferred media choice for children because of their screen size, mobility, and ability to stream content and interactive capability [ 14 ]. Hence, it is important to study the impact of early adoption and use of those devices on children development.

However, research on screen time using other electronic devices and speech and language delay has lagged behind the adoption of these technologies. This study, as far as we know, is the first study to identify the impact of screen time including TV, smartphones, and tablets on speech language development in children aged 12–48 months in UAE.

This study addresses three elements in studying the association between screen time and delayed language development: (a) both TV viewing and other electronic devices (smartphone and tablets), (b) age of first exposure to the screen, and (c) association with other variables including parent’s education, the onset of using electronic devices, child ownership of devices, the onset of TV viewing, TV viewing hours per day, and the child and parent interactions.

Study design

This is a case-control study comparing the screen time use in children with speech and language delays to that of typically developing children.

Participants

From January 2018 to January 2019, children, aged between 12 and 48 months old with language delay who came for the first time to pediatric clinic were assessed by clinical history taking, and performing physical examination, head circumference measurement, observation of child’s play, language, cognitive ability, sociability, repetitive, hyperactive behavior, joint attention, and hearing screening were performed by developmental pediatricians. We excluded participants who had language delay due to ASD, known genetics causes, hearing problems, cerebral palsy, neurological disorder, and global developmental delay. Therefore, 227 new patients with language delay were included in the study. A child and adolescent psychiatrist and speech and language pathologist interviewed caregivers during the next visit in order to complete the data. Parental consent was obtained from all participants.

Cases were age and gender matched with 227 typically developing children control subjects who were recruited from the Well Baby Clinic in Ambulatory Health Services.

The questionnaire consisted of questions about the child age and gender, parents martial status, education level and mother employment, child screen time (age child first starts watching TV and using electronic devices, number of hours spend in screen time (TV viewing/electronic devices), child favorite program/apps, and lastly parent–child quality time spent (questionnaire in Appendix).

Diagnosis of delayed language development

Children were diagnosed with language delays based on the Receptive-Expressive Emergent Language Test and early signs of language and speech disorders. A delay of 25% or greater by age 16–24 months is considered important. For example, a 24-month-old child who functions as a typical 18 month old is considered to have a clinically important language delay [ 26 ].

Data analysis

Data were analyzed using SPSS 21.0. Categorical data are expressed as the frequency with the corresponding percentage. A chi-squared test established the difference between categorical variables. An odds ratio established whether the screen playtime using either an iPad or watching TV (exposure) affects speech and language development. A P -value of less than 0.05 is considered statistically significant for all tests.

Odds ratio analyses compared the probability that children with and without language delay had been exposed to the risk factors defined above. To determine the relationship between all significant risk variables, categorical data were expressed as the frequency with the corresponding percentage. For all binary risk variables, odds ratios were estimated using unconditional logistic regression. Each run of this statistical analysis provided a chi-squared test result. Multivariate logistic regression modeling was performed to determine the relationship between all significant risk variables and language development. Given the large number of variables, the analyses were adjusted for multiple comparisons by multivariate logistic regression modeling. Adjusted odds ratios and their corresponding 95% confidence intervals were calculated from the logistic regression model.

Our sample included 277 children who had language delays and 277 controls with normal language development. Both groups were age and gender matched. In our sample, 37.0% of the children were younger than 24 months of age, 36.1% were 24 months old or older, and 26.9% were 37 months old or older. There was a relatively high proportion of males (54.2%) in both the case and control groups. The distribution of UAE nationals (37.9%), non-UAE national Arabs (28.6%), and non-UAE national non-Arabs (33.5%) was consistent in the control group. However, this distribution was uneven in the case group ( P -value < 0.001): 49.3% of the subjects were UAE nationals, 35.2% non-UAE national Arabs, and 15.4% were non-UAE national non-Arabs. Married parents accounted for 99.6% of the control group compared to 93.8% of the cases. Divorced/separated/widowed parents were more common among cases than controls (6.2% vs. 0.4%), a statistically significant difference ( P -value < 0.001). Table 1 shows the sociodemographic data of the case and control groups.

Table 2 shows the number and percentage of individual factors in the case and control groups, along with the binary logic regression and crude odds ratio and the corresponding confidence interval. Significant differences existed between the two language groups when the confidence intervals for the odds ratios did not include an odds ratio of 1.0.

The following factors are significantly correlated (statistically and clinically) with language delay among children: those who use a device [ OR 6.82 (4.09–11.40), P -value < 0.001], early onset of using electronic devices (12–24 months) ( OR 8.22 (1.71–39.55), P -value = 0.009), and fewer TV viewing hours per day, at 3 to 4 h and 5 to 8 h ( OR 2.67 (1.65–4.32), P -value < 0.001) and ( OR 4.93 (1.90–12.79), P = 0.001), respectively. The following factors were protective against developing a speech and language delay: mother’s education level of master’s degree or PhD ( OR 0.1 (0.01–0.93), P -value = 0.043) and watching TV ( OR 0.32 (0.21–0.49), P < 0.001).

Although spending time with children was not found to be a significant factor in reducing speech delays, spending 1 to 4 h a day with children protects against speech delays [for 1 to 2 h, OR = 0.379 (0.21–0.67), P = 0.001; for 3 to 4 h, OR = 0.355 (0.20–0.62), P < 0.001]. No significant association was found between the father’s education level and possession of a device.

Table 3 shows multiple logistic regression with an adjusted odds ratio and the 95% confidence interval. The factors that could predict a language delay include owning a device, early onset of using electronic devices, and total TV viewing hours per day. Children who own a device are at an increased risk of language development problems ( OR = 3.94 (1.97–7.84), P -value < 0.001). The late-onset use of electronic devices (at 25–36 months of age) has a positive influence on language development compared to early-onset use (at 12–24 months of age) ( OR = 0.32 (0.13–0.82), P -value = 0.017). Children who watch 3 to 4 h of television per day are at increased risk of language problems ( OR = 3.21, 95% CI = 1.66–6.17, P -value < 0.001).

Prior studies have noted the importance of decreasing screen time. To date, most of the studies on children’s screen time have focused on the traditional screen media, such as television and video. In fact, television has dominated screen time studies for the past decade. However, a focus on portable electronic media is needed in light of the pervasive increase in access and the use of modern mobile devices. This study addresses three elements in studying the association between screen time use and delayed language development: (a) both TV viewing and other electronic devices (smartphone and tablets), (b) age of first exposure to screens, and (c) association with other variables, including parent’s education, the onset of using electronic devices, child ownership of devices, the onset of TV viewing, TV viewing hours per day, and child-parent interactions.

Our data indicate that those who use electronic devices have a higher risk of delayed speech and language development ( OR  = 6.83). These results agree with other studies [ 18 , 19 ].

Dutch et al. found in both cross-sectional and longitudinal analyses that children who watched more than 2 h of television per day had increased odds of low communication scores [ 19 ]. In a longitudinal analysis of 259 mother-infant dyads participating in a long-term study related to early child development with unadjusted and adjusted analyses, Tomopoulos et al. found that the duration of media exposure at age 6 months was associated with lower cognitive development at age 14 months (unadjusted: r = −0.17, P < 0.01; adjusted: β = −0.15, P = 0.02) and lower language development ( r = −0.16, P < 0.01; β = −0.16, P < 0.01) [ 18 ].

We found that 90.3% of those who have speech and language development delay use electronic devices. A recent study (van den Heuvel et al.) found a significant association between mobile device use and parent-reported expressive speech delay in 18-month-old children. Each additional 30-min increase in daily mobile media device use was associated with an increased odds of parent-reported expressive speech delay ( OR 2.33, 95% confidence interval, 1.25–4.82). No relationship was observed between mobile media device use and other parent-reported communication delays [ 27 ].

TV viewing and speech and language developmental delay have very contradictory results; this study found that TV viewing is reducing the risk for speech and language developmental delay ( OR = 0.32): 40.5% of children who had speech and language developmental delays do not watch TV. However, previous research showed no association between time spent on television viewing (≥ 2 h per day) and delayed language development at 2 years old [ 25 ]. Other work found similar results in a prospective cohort study: Television viewing in infancy does not seem to be associated with language or visual motor skills at 3 years of age [ 17 ]. However, such conclusions must be taken cautiously because many other studies found a high association [ 12 , 13 , 15 , 16 , 18 , 24 , 28 ].

The results on age at first screen exposure are surprising in light of the mounting evidence on the lack of benefits and potentially negative impact of media exposure in young children.

Our study found that 88.3% of children who were younger than 24 months old were first exposed to screen, which agrees with prior work [ 24 , 27 , 28 , 29 , 30 ]. A possible explanation for the early age of exposure might be a positive parental perception of screen time. This is beyond the scope of our study, but other work assessed parental perceptions on TV viewing and found positive parental perceptions on television viewing toward children’s development [ 25 ].

One interesting finding is in the area of child ownership of the devices. However, this study did not find an association between owning a device and developmental language delay: 63.9% of children in the case group who use electronic devices have their own device versus 70.2% in the control group. This result is consistent with the literature [ 14 ]: the number of households who own tablets doubled since 2013, reflecting the pervasive nature of digital technology.

This study has been unable to demonstrate whether gender variables are associated with speech and language developmental delay. Chonchaiya and Pruksananonda found that boys were more likely to have language delays ( OR = 3.98) [ 27 ]. Ruangdaraganon et al. also found a similar association between male gender and delayed language development ( OR = 6.9; 95% CI = 1.5–31.3) [ 25 ].

This study found a positive influence on language development for mothers with a master’s degree or PhD ( OR = 0.10), but no association was found with the father’s education level. This result seems to be consistent with other research [ 30 ] showing that children of high school graduates were more than twice as likely as children of college graduates to watch more television than AAP recommended ( OR = 2.3; 95% CI = 1.4–3.9, P = 0.002). However, Chonchaiya and Pruksananonda found that the father’s education (≤ at primary school level) was strongly correlated to predict language delays in children ( OR = 4.91) [ 15 ].

Limitations

Its retrospective design is a limitation of this case-control study. There might be interviewer bias and limitations in the human recall. There was also a lack of measures to determine other important variables, including temperament, interactive activity, and parenting style.

Despite these limitations, however, our study has several strengths. It is the first study to identify the impact of screen time including TV, smartphones, and tablets on speech language development in children aged 12–48 months in UAE. This contribution is important, given the sample size from a diverse multiethnic population, which might improve the generalizability of our findings.

Future direction

A longitudinal prospective study is needed to examine the impact of screen time on speech and language development in children and for better understanding of the possible causality.

The main goal of this study was to determine the impact of screen time via electronic devices or television on speech and language development and the factors that predict language delays. Overall, this study supports the notion that there is a relationship between early onset before the age of 2 years and high frequency of screen time and delayed language in preschool children. The factors that predict speech and language delay are using a device and early onset of the electronic device. However, the factors found to less likely associated with speech and language delay are watching TV and the mother having a master’s degree or PhD.

Availability of data and materials

Data available on request from the authors.

Abbreviations

Receptive-Expressive Emergent Language Test

American Academy of Pediatrics

National Institute for Clinical Excellence

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Al Hosani, S.S., Darwish, E.A., Ayanikalath, S. et al. Screen time and speech and language delay in children aged 12–48 months in UAE: a case–control study. Middle East Curr Psychiatry 30 , 47 (2023). https://doi.org/10.1186/s43045-023-00318-0

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Original research article, association between interruption of intervention and language performance in young children with language delay—a cohort study during covid-19 pandemic.

case study of a child with developmental delay

  • 1 Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Taoyuan, Taiwan
  • 2 Department of Physical Medicine and Rehabiltiation, New Taipei City Municipal Tucheng Hospital, Chang Gung Memorial Hospital, Tucheng branch, New Taipei City, Taiwan

Introduction: To assess the association between a three-month interruption of language intervention programs and the language performance of children with language delay during the COVID-19 pandemic, and to identify which children are more vulnerable to such interruptions.

Materials and methods: This is a retrospective study involving 33 children with language delay who experienced a three-month suspension of language interventions due to the COVID-19 pandemic. We collected their demographic data and language performance scores from the Comprehensive Developmental Inventory for Infants and Toddlers—Diagnostic test (CDIIT-DT) at four different time points. The scores were analyzed using a Wilcoxon Signed Ranks test.

Results: The median scores of language comprehension and overall language ability showed a decreasing trend during the interruption period. However, resuming interventions post-interruption showed a statistically significant increase in all language domains. Children in the borderline delay group (CDIIT-DT DQ scores between 71 and 85) were more likely to experience a decline in their language abilities during the interruption.

Discussion: This is the first study to reveal a decreasing trend in language performance during interruption periods, and highlighting the significance of post-interruption language interventions in facilitating improvements. Furthermore, our study brings attention to the heightened vulnerability of children exhibiting borderline language delay in overall language ability tests when faced with interruptions in language interventions.

1. Introduction

Language delay, a condition in which children fail to meet the expected developmental milestones for their age group in terms of language comprehension and/or expression ( 1 , 2 ), is common in young children, affecting approximately 5% to 12% of those between the ages of 2 and 5 ( 3 , 4 ). Early identification and intervention can prevent language delay from interfering with formal education and behavioral adjustment ( 5 ). There have been numerous studies conducted to identify risk factors, predictors, and prevalence of language disorders in children ( 3 , 6 – 10 ). Additionally, there is a considerable body of research focused on interventions for children with language delay ( 11 – 13 ). Some studies have reported outcome predictors specifically related to children with delayed expressive language ( 14 , 15 ). However, it is worth noting that there are currently no studies investigating the influence of interrupting interventions on these children. Ethical considerations have made it impractical to interrupt interventions for children with language delay for research purposes. During the COVID-19 pandemic, Taiwan suspended non-emergency medical treatments, including language interventions for three months. This event provided a unique opportunity to study this topic. Our study aimed to explore the relationship between intervention interruptions and language performance in young children with language delay, and to identify which groups of children are more vulnerable to such interruptions.

2. Materials and methods

2.1. patient inclusion.

This retrospective study analyzed 33 children who were diagnosed with language delay or borderline language delay using the Comprehensive Developmental Inventory for Infants and Toddlers—Diagnostic test (CDIIT-DT) ( 16 – 20 ) and underwent language intervention programs at New Taipei City Hospital Tu Cheng Branch between June 2020 and August 2022. All these children experienced a three-month interruption of the program from April 2021 to July 2021 due to a sharp surge in Covid-19 cases in Taiwan.

2.2. Data collection

We collected general data from each study child with language delay, including date of birth, gender, gestational age, birth weight, medical history, family history, multilingual speaking, parents' education level, main caregiver, siblings' condition, early childhood education condition, and other developmental delay conditions. We used the CDIIT-DT to evaluate the language performance of each study child. Raw scores were collected from three subdomains (language comprehension, language expression, and overall language ability) at four different time points: T1—the first assessment before interventions, T2—the last assessment before the three-month interruption, T3—the first assessment after the three-month interruption, and T4—the last assessment obtained from patients' medical records.

2.3. Comprehensive developmental inventory for infants and toddlers (CDIIT)

The CDIIT was created by a multidisciplinary team in Taiwan in 1995 to evaluate the developmental levels of infants and toddlers between 3 and 71 months old, encompassing seven age groups. The CDIIT includes both a diagnostic test (CDIIT-DT) and a screening test (CDIIT-ST). These components are used to assess five developmental areas: motor skills, language skills, cognition, social skills, and self-care skills.

The CDIIT utilizes age-related norms established for the Taiwan population, with a mean score of 100 and a standard deviation of 15. It has been shown to exhibit good reliability and validity in previous studies. The CDIIT is generally supported as a norm-referenced test for evaluating developmental changes of children with developmental delay and outcome measures of pediatric intervention programs ( 16 – 19 ).

2.4. Language intervention programs in Taiwan

In Taiwan, young children are taken to pediatric rehabilitation clinics when there is a suspicion of developmental delay. Caregivers or kindergarten teachers usually notice these delays. If a physician clinically assesses children and identifies a language delay, they are referred to a speech-language pathologist for diagnostic tests. Once the reports confirm a language developmental delay, language intervention programs begin for them once per week.

In the Physical Medicine and Rehabilitation Department of New Taipei City Hospital Tu Cheng Hospital, a single pediatric speech-language pathologist utilized CDIIT-DT to track the language performance of children with language delay during intervention programs every three to six months. The intervention programs were discontinued when the CDIIT-DT indicated that the language delay was no longer present. Subsequently, every six months to a year, the speech-language pathologist utilized CDIIT-ST to track the language development of this children until they reached the age of six.

2.5. Statistical analysis

In this study, we transformed the raw scores into developmental quotient (DQ) scores and utilized the Wilcoxon Signed Ranks test (significance level: p  < 0.05) to analyze the differences between various time points. The “W” test statistic in the Wilcoxon Signed Ranks test represents the sum of ranks computed from the absolute differences between paired observations, facilitating the assessment of significant variations between these paired measurements.

To further investigate the CDIIT score regression following intervention interruption, we segregated the children into two groups based on this specific criterion. To examine the potential correlations between each variable and CDIIT score regression, univariate logistic regression and multivariate logistic regression were employed (significance level: p  < 0.05). Moreover, for the construction of a prediction model, we applied machine learning algorithms, including KNN, decision tree, and random forest. All analyses were conducted using Python 3, capitalizing on its extensive libraries, and figures were generated using both Python 3 and Prism 9 software.

With regard to ethical considerations, the study was reviewed and approved by the Institutional Review Board of Chang Gung Memorial Hospital, with a waiver of informed consent granted for the use of de-identified data from routine clinical care, ensuring ethical compliance. This study followed the STROBE reporting guideline.

3.1. Findings on language comprehension, expression, and overall language ability

Of all the children studied, 19 were male and 14 were female. Characteristics of Study Participants were presented in the Table 1 . The median scores of language comprehension, language expression, and overall language ability at different time points are presented in Table 2 . Our findings showed that the scores for language comprehension were consistently higher than those for language expression across all time points. Compared with T3, there were statistically significant increases of scores at T4 among all three domains: language comprehension ( W  = 315, p  = 0.0001), language expression ( W  = 140, p  = 0.04), and overall language ability ( W  = 228, p  = 0.001).

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Table 1 . Characteristics of study participants and comparison of Two groups based on regression Status after intervention interruption.

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Table 2 . Median CDIIT-DT scores and significance levels at different timepoints across language comprehension, expression, and ability domains.

3.2. Trends in CDIIT-DT DQ scores and the impact of intervention interruption

Figure 1 illustrates the trends in CDIIT-DT DQ scores over time for the domains of language comprehension, language expression, and overall language ability. Comprising the three line charts, the trend of language comprehension aligns consistently and synchronously with the overall language ability. The median scores of the two domains, language comprehension and overall language ability, showed a decreasing trend during the interruption. Moreover, resuming the intervention after the interruption showed a statistically significant increase in all language domains.

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Figure 1 . Trends in CDIIT-DT DQ scores over time. T1: the first assessment before interventions, T2: the last assessment before the 3-month interruption, T3: the first assessment after the 3-month interruption, T4: the last assessment obtained from patients’ medical records. The plot shows the median and interquartile range of CDIIT-DT DQ scores at each timepoint.

3.3. Analysis of individual variable contributions to CDIIT-DT DQ score regression in children with language delay following intervention interruption

To identify key variables that might contribute to CDIIT score regression following intervention interruption, we conducted both univariate logistic regression and multivariate logistic regression analyses. However, none of the variables exhibited statistical significance. The p -values obtained from the univariate logistic regression analysis are detailed in Table 1 .

3.4. Identifying vulnerable groups: language ability scores and therapy interruption

To identify which group were more vulnerable to speech therapy interruption, we divided studied children based on their CDIIT-DT DQ scores at T2. We used 15 points as an interval to group these children. We observed a group of children with overall language ability scores ranging from 71 to 85 (borderline delay) at T2. Out of the 15 children in this group, 10 showed a decline in scores between T2 and T3, while 2 maintained stable scores ( Figure 2 ).

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Figure 2 . Scatter plot of CDIIT-DT DQ scores and T3-T2 score differences. X-axis: CDIIT-DT DQ score (interval: 10 points), Y-axis: T3-T2 score difference, T2 score: score evaluated at last assessment before the 3-month interruption, T3 score: score evaluated at first assessment after the 3-month of interruption. The red dots represent cases where the CDIIT-DT DQ score at T3 is lower than the score at T2, while the blue dots indicate cases where the CDIIT-DT DQ score at T3 is higher than or equal to the score at T2.

3.5. Constructing a prediction model for CDIIT-DT DQ score regression following intervention interruption

While no key variable was identified as contributing to CDIIT score regression after intervention interruption, we endeavored to construct a prediction model utilizing all available variables. By employing machine learning algorithms such as KNN, decision tree, and random forest, we sought to find the most effective predictive approach. The random forest algorithm emerged as the most accurate, achieving a 70% accuracy rate and an area under the ROC curve of 0.720 ( Figure 3 ).

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Figure 3 . Receiver operating characteristic (ROC) curve of random forest algorithm for predicting CDIIT-DT score regression after intervention interruption. The ROC curve illustrates the performance of the Random Forest algorithm in predicting CDIIT-DT score regression after intervention interruption. The Area Under the ROC Curve (AUROC) was calculated to be 0.720, indicating a moderate level of predictive accuracy.

4. Discussion

This study is the first to examine the effects of interrupting language intervention programs on children with language delay, which occurred during the COVID-19 outbreak in Taiwan in 2021. The unique circumstances presented by the pandemic provided an opportunity to investigate this topic. While it is unlikely that similar situations will arise in the future, the findings of this study remain valuable in understanding the consequences of unexpected disruptions in healthcare services. Despite the numerous studies conducted during the global COVID-19 pandemic focusing on strategies and alternative language intervention methods, such as telepractice speech therapy ( 21 – 23 ), little is known about the specific impact of pandemic-induced intervention interruption on children with language delays. Hackenberg et al. reported a high psychosocial burden experienced by parents of children with speech and language disorders due to therapy pause during the Covid-19 pandemic; however, the effects on their children's speech and language abilities were not addressed ( 24 ).

Regarding the relationship between intervention interruption and language performance in children with language delays, our findings indicated a decreasing trend during the interruption period, while post-interruption language interventions were significantly associated with performance improvements. These findings can provide clinicians and parents with an overview of language performance trends following rehabilitation interruption and encourage them to pursue post-interruption interventions. In addition, Hackenberg el. reported parents of children with speech and language disorders had more fears and worries about their children's development ( 24 ). In a clinical setting, our study can alleviate parents' psychosocial burden and increase parental compliance and confidence in resuming intervention post-interruption.

Children with developmental delay typically demonstrate stronger language comprehension abilities relative to their language expression skills ( 25 ). This observation aligns with our results, which showed that the mean CDIIT-DT scores for language comprehension consistently exceeded those for language expression at all evaluated time points. More notably, language comprehension scores exhibited greater sensitivity to the impact of continuity and discontinuity in rehabilitation programs compared to language expression scores. In our study, the slopes in the line chart depicting language abilities closely paralleled those for language comprehension ( Figure 1 ). These results reinforce the substantial role that language comprehension plays in the speech and language abilities of children. Earlier studies have likewise reported that language comprehension could serve as a reliable predictor of language expression outcomes ( 3 ). Therefore, assessing language comprehension is not just crucial for differential diagnosis, but also invaluable for evaluating outcomes in children with speech and language disorders.

To further enhance language comprehension in children with developmental delay, several strategies can be employed ( 26 ). These include Enhanced Milieu Teaching (EMT), a conversation-based therapy technique that uses the child's interests as opportunities to model and prompt language use in everyday contexts. Parent-based Video Home Training, where parents are trained in attachment, referencing, relevance, and connectivity of language, can also be beneficial. Techniques such as pausing and expanding in shared book reading and in everyday situations can be used to encourage children to choose or initiate a topic of interest to them. Interactive book reading with expository books and language facilitation strategies can also be employed to focus children's attention on the expository structure and help them construct responses to questions. It is possible that tailoring post-interruption intervention strategies to enhance comprehension could expedite improvements in expressive abilities in overall language abilities.

Our study is also the first to identify which groups of children are more vulnerable to interruptions in language interventions. Our results revealed that among the children with overall language ability scores ranging from 71 to 85 at T2, 10 out of the 15 children in this group exhibited a decline in scores between T2 and T3. Similar results were observed in the language comprehension test ( Figure 2 ). In clinical practice, parents often assume that their child is approaching age-appropriate milestones, overlooking the importance of language intervention during the borderline delay phase. However, our study highlights the particular importance of maintaining ongoing language intervention during this phase, as discontinuation poses a high risk of score regression. Further research is necessary to corroborate this finding, which would provide clinicians and parents with a better understanding of the optimal timing for ceasing interventions.

Although this study is the only one examining young children with language delay who experience interruptions in language intervention programs, there were some limitations to this study. The most notable constraint is the small sample size, which may have curtailed the statistical power of our analyses and led to an absence of statistically significant findings in both univariate and multivariate logistic regression. This small sample size could explain our inability to detect meaningful differences. Nevertheless, our application of a machine learning algorithm enabled us to predict CDIIT score regression after intervention interruption with an accuracy of 70%. We anticipate that expanding the database for model training could enhance this accuracy further. It is essential to note that our findings are preliminary and derived from a small, heterogeneous sample. These initial results emphasize the need for larger and more diverse studies to corroborate and solidify our conclusions.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Institutional Review Board of Chang Gung Memorial Hospital. The studies were conducted in accordance with the local legislation and institutional requirements. The Ethics Committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants’ legal guardians/next of kin because The use of de-identified data from routine clinical care, ensuring ethical compliance.

Author contributions

Conceptualization, Methodology, Data curation, Formal analysis, Investigation, Writing – original draft, Visualization: S-CH. Supervision: AM-KW. All author contributed to the article and approved the submitted version.

Acknowledgments

The authors gratefully acknowledge the valuable contributions of Heng-An Yeh and Guan-Ting Huang in data extraction. Heng-An Yeh and Guan-Ting Huang, both holding degrees in SLP, are affiliated with the Department of Physical Medicine and Rehabiltiation, New Taipei City Municipal Tucheng Hospital, Chang Gung Memorial Hospital, Tucheng branch, New Taipei City, Taiwan.

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: developmental language delay, language therapy, disruption of language intervention, language ability, COVID-19

Citation: Hsu S-C and Wong AM-K (2023) Association between interruption of intervention and language performance in young children with language delay—a cohort study during COVID-19 pandemic. Front. Pediatr. 11:1240354. doi: 10.3389/fped.2023.1240354

Received: 14 June 2023; Accepted: 17 August 2023; Published: 15 September 2023.

Reviewed by:

© 2023 Hsu and Wong. 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: Alice May-Kuen Wong [email protected]

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  • v.176(1); 2002 Jan

Evidence-Based Case Reviews

Investigation of children with “developmental delay”, louise hartley.

1 Dubowitz Neuromuscular Centre Hammersmith Hospital Campus Du Cane Rd London W12 0NN UK

Alison Salt

2 Neurodisability Service Institute of Child Health Mecklenburgh Square London WC1N 2AP

Jon Dorling

3 Jenny Lind Children's Department Norfolk and Norwich Hospital Brunswick Rd Norwich NR1 3SR UK

Paul Gringras

4 Imperial College of Science, Technology and Medicine London, UK

A 7-year-old boy is referred to you with concerns about developmental delay. On assessment, he is found to have moderate mental retardation (IQ of 50) but no remarkable physical findings. His parents are considering having another child, and they wonder what caused the retardation in their first child and whether it is likely to recur in future offspring.

Developmental delay is a common problem in pediatrics, with an estimated population prevalence as high as 10%. 1 , 2 , 3 , 4 The etiology includes various genetic and environmental processes, with the most common causes being Down syndrome and the fragile X chromosome. The proportion of children with severe mental retardation found to have an organic cause is reported as 55% to 57%. 5 , 6 , 7 No consensus exists on the choice of investigations for developmental delay, with clinicians using a wide variety of investigations. 8 The example we give in this article is intended to illustrate the process used to evaluate developmental delay in a variety of circumstances, recognizing that the specifics will vary according to the clinical situation.

This scenario raises many clinical questions. You wish to use an evidence-based approach, so you frame your questions to maximize the yield from searching and look first for high-quality systematic reviews and evidence-based practice guidelines to answer your questions. However, because most systematic reviews address issues of therapy, no reviews or guidelines are found that address your questions, which are mostly related to the probability of particular causes of developmental delay. You go to MEDLINE and EMBASE searches to try to answer these questions ( box 1 ).

Focusing a literature search

You want to know the best estimate for the prevalence of fragile X chromosome in the general population and the best estimate for the prevalence of fragile X chromosome among children with learning disabilities. From the 133 articles found in your search, 10 described population-based studies of the prevalence of fragile X chromosome that were performed since the cloning of the fragile X mental retardation gene ( FMR1 ) in 1991. Of the 10 studies, only 2 meet most of the criteria for high-quality prevalence studies ( box 2 ).

Criteria for appraising the quality of prevalence studies

You decide to start with the study of Murray et al because it was limited to boys, used a population-based sample, and tested only those aged 18 years or younger. 9 Neither the case definition for mental retardation nor the distribution of IQs in the population is stated in the study, and the low prevalence of fragile X chromosome suggests that this is a relatively lower risk group (higher IQ) than that used in other studies. Only 70% of children with specia educational needs were tested, and no information is available about nonresponders. Because the prevalence estimate of fragile X chromosome from this study would be affected if children with the chromosome were less or more likely to participate, you try varying the prevalence in the nonparticipating group to half or double that of the participating group. This gives a prevalence range for the overall population of between 1 in 3,990 and 1 in 6,171, which is reassuring because these numbers overlap with estimates from other studies identified by your search (de Vries et al, 10 1/6,045; and Turner et al, 11 1/5,000). Applying the same assumptions to the population of learning disabled boys in this study gives a range of 1 in 162 to 1 in 250 (0.6%-0.4%).

In the study by de Vries et al, the learning-disabled group was stratified into mild and moderate-to-severe learning difficulty. 10 Unfortunately, the authors excluded those who already had a diagnosis of fragile X; these cases must be included for accurate prevalence figures. If the prevalence of fragile X chromosome among the nonresponders is similar to that among the responders, then adding those known to have fragile X and new diagnoses to the numerator gives an estimated prevalence of fragile X chromosome for mild mental retardation of 1 in 50, with 1 in 40 for moderate to severe mental retardation. In your 7-year-old child who has moderate intellectual impairment, you estimate the probability of his having the fragile X syndrome as somewhere between 1 in 40 and 1 in 250. You would, therefore, need to test between 40 and 250 children to find 1 child with the fragile X chromosome.

You next consider the usefulness of dysmorphic features in ruling in or ruling out the diagnosis of fragile X syndrome. A search nets 33 articles regarding dysmorphic features in those with the fragile X chromosome. From the abstracts, two articles were found that used a combination of physical and behavioral features to select who, among a group of mentally retarded children, has the highest probability of testing positive for the fragile X chromosome, using molecular testing for the FMR1 gene. 10 , 12

The article by Giangreco et al refines previously defined checklists of phenotypic characteristics associated with the fragile X chromosome into a six-item checklist with a scoring system, shown in table 1 . 12

Phenotypic characteristics associated with fragile X: checklist and scoring system *

In this study, a score of 5 or more of a maximum of 12 was found to identify all children who had the fragile X chromosome. Using the identification of these features as a “diagnostic test” for fragile X chromosome, with molecular testing as the gold standard, you use the guidelines on assessing diagnostic and screening tests summarized in box 3 . 13

Criteria for appraising studies of diagnostic tests

In this retrospective study, the molecular polymerase chain reaction (PCR) technique was used in all patients, but the authors do not state whether those applying the diagnostic test were blind to the (PCR-defined) fragile X status of the patients. If the assessors already knew the “answer,” the potential for biased assessment is high. The scoring system is clear; however, some of the physical features, such as long face and large or prominent ears, are subjective, and no objective measurements are given. Some of the behavioral characteristics may also be open to interpretation. The provision of genetic testing at the time of the study may have been unique to this study or this location; if so, this could have attracted a highly selected group of children, and the results may not be generalizable. Because the clinical features of fragile X syndrome are well known to clinicians, and all children were referred for testing, the children referred are likely to have had a high prevalence of the chromosome. The data necessary for calculating likelihood ratios (LRs) presented in the article are shown in table 2 .

Calculation of likelihood ratios

In this study, a negative result (those with a score <5) will effectively rule out a diagnosis of the fragile X chromosome because it is a highly sensitive test. That is, children with a low score on the clinical assessment are unlikely to have the chromosome. However, the calculated LR of a positive test in this study is 2.5. In general, LRs between 2 and 5 generate only small changes in probability. Indeed, if the pretest probability is 3.5%, then a positive test increases the probability of having the fragile X chromosome to only 8.2%.

de Vries et al studied a prospectively collected sample with examiners blind to the fragile X result 10 using a similar scoring system: the phenotypic criteria described by Laing et al. 14 Scores were divided into three groups: low risk, when dysmorphic features suggested another diagnosis; medium risk, in the absence of dysmorphic features; and high risk, in the presence of fragile X chromosome characteristics. This sample contained many adults in whom the phenotype is more characteristic than in children. Despite this, the outcome was impressive. None of the low- or medium-scoring males had the fragile X chromosome, with all those who had the chromosome scoring in the high range. Of course, this did not mean that all of the high scorers had the syndrome. The LR for a high score was 10, and the LR for a low or medium score was 0. The high LR for a positive test confirms your suspicion that the patients in their group showed more distinct features. This indicates how test performance, including LRs, can vary when a test is applied to different groups.

Although neither of these studies is ideal, both show that children who do not have the fragile X chromosome can be correctly identified clinically (decreasing the number of molecular tests that are done) and that having clinically identified features increases the likelihood of a positive genetic test but does not confirm the diagnosis. If our group were similar to that described by Murray et al, with a prevalence of 0.4% (the lowest possible estimate of prevalence), and the diagnostic test performed in the same way as described by Giangreco et al, with an LR of 2.5, the posttest probability of having the fragile X chromosome would have increased from 0.5% to 1.0%. 9 , 12 However, the high sensitivity of the test suggests that instead of testing 250 children before finding 1 child with the fragile X chromosome, you could exclude 150 of those children (60%) from testing with minimal risk of missing a case. de Vries et al suggest that in a group with moderate or severe mental retardation, a higher prevalence may be expected (the highest estimate being 3.3%). 10 Excluding those with a known diagnosis from the denominator gives an estimated prevalence of about 4%, so the posttest probability is, therefore, increased to 10%. Under these circumstances, for every 24 children at risk, 14 could be excluded from testing, and 1 of the remaining 10 would have the fragile X chromosome.

You wonder about the benefit to the parents of knowing their son's diagnosis but are not able to find randomized trials or cohort studies directly relating to the diagnosis of fragile X chromosome. A table is found that provides a framework with the different values associated with making a diagnosis in children with developmental delay ( table 3 ).

Considerations for genetic diagnostic testing in developmentally delayed children *

Resolution of the scenario You are now able to estimate the probability of the patient's having the fragile X chromosome as somewhere between 1 in 40 and 1 in 250 and would, therefore, need to test between 40 and 250 children to find 1 child with the chromosome abnormality. If this child has a score of less than 5 for the features described by Giancreco et al, you feel confident in ruling out the chromosome abnormality and not proceeding to molecular testing. 12 Because there is no well-established treatment option, the direct benefit to the patient of making a diagnosis is marginal. However, the use of this clinical diagnostic test avoids subjecting some children to an unnecessary blood test and spares some parents the anxiety of awaiting the results, as well as the unnecessary expenditure. In addition, the resolution of diagnostic uncertainty can provide much relief and stop further investigations for a cause of developmental delay. As more information on the prognosis of this condition becomes available, parents and patients may benefit from this knowledge. Also, for the parents and relatives, the identification of female carriers may allow an informed choice regarding at-risk pregnancies.

Within the limitations of current evidence, some information is now available on the range of the possible prevalence of the fragile X chromosome in different groups, and some understanding of how specific features of the fragile X syndrome may influence your decision making. The decisions that are made depend on the group from which the child comes and the values that the tester and the parents put on having a diagnosis versus the disadvantages of unnecessary testing. In this article, we provide a model for thinking through the issues involved in the investigation of developmental delay and a way of incorporating evidence into this process. We have chosen a common example to illustrate the process, that of fragile X syndrome, the second most common cause of mental retardation after Down syndrome. The prevalence of a particular disorder in different patient groups will influence the outcome of any diagnostic investigations. This method is generalizable to other causes of developmental delay.

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Down syndrome is one of the more common causes of developmental delay

Hattie Young/Science Photo Library

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Fragile X syndrome: the benefits of testing include diagnostic certainty. (Courtesy of the Fragile X Society, www.fraxa.org )

Competing interests: None declared

This article was edited by Virginia A Moyer of the Department of Pediatrics, University of Texas Medical Center at Houston. Articles in this series are based on chapters from Moyer VA, Elliott EJ, Davis RL, et al, eds. Evidence-Based Pediatrics and Child Health . London: BMJ Books; 2000.

Summary points In a 7-year-old child who has moderate intellectual impairment:

  • The likely prior probability of having fragile X syndrome is between 1 in 40 and 1 in 250 (ie, to find 1 child with the fragile X chromosome, between 40 and 250 children would need to be tested)
  • Currently available evidence shows that when a scoring system based on physical and behavioral features is used, a diagnosis of fragile X syndrome can be confidently ruled out in those with low scores
  • Decisions that are made about testing will depend on the population from which the child comes and the values that the tester and the parents put on having a diagnosis versus the disadvantages of unnecessary testing
  • The benefits of using this “clinical diagnostic test” include preventing children from being subjected to an unnecessary blood test, sparing parents the anxiety of awaiting the results, and reducing the cost of investigation
  • The benefits of testing for the fragile X chromosome include the resolution of diagnostic uncertainty, the prevention of further investigations, and the identification of female carriers

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