DSM-5 Autism Spectrum Disorder Research Articles

Autism spectrum disorder in ICD-11-a critical reflection of its possible impact on clinical practice and research.

This perspective article compares and contrasts the conceptualization of Autism Spectrum Disorder (ASD) in ICD-11 and DSM-5. By guiding the user through the ICD-11 text, it is argued that, in contrast to DSM-5, ICD-11 allows a high variety in symptom combinations, which results in an operationalization of ASD that is in favor of an extreme diverse picture, yet possibly at the expense of precision, including unforeseeable effects on clinical practice, care, and research. The clinical utility is questionable as this conceptualization can hardly be differentiated from other mental disorders and autism-like traits. It moves away from an observable, behavioral, and neurodevelopmental disorder to a disorder of inner experience that can hardly be measured objectively. It contains many vague and subjective concepts that lead to non-falsifiable diagnoses. This bears a large danger of false positive diagnoses, of further increased prevalence rates, limitations of access to ASD-specific services and of increasing the non-specificity of treatments. For research, the hypothesis is that the specificity of ASD will be reduced and this will additional increase the already high heterogeneity with the effect that replication of studies will be hampered. This could limit our understanding of etiology and biological pathways of ASD and bears the risk that precision medicine, i.e., a targeted approach for individual treatment strategies based on precise diagnostic markers, is more far from becoming reality. Thus, a more precise, quantitative description and more objective measurement of symptoms are suggested that define the clinical ASD phenotype. Identification of core ASD subtypes/endophenotypes and a precise description of symptoms is the necessary next step to advance diagnostic classification systems. Therefore, employing a more finely grained, objective, clinical symptom characterization which is more relatable to neurobehavioral concepts is of central significance.

The Analysis of the Differences between On-screen Portrayals and Realistic Characters of Autism Spectrum Disorder - Take the Example of The Good Doctor in the U.S.

Autism spectrum disorder (ASD) is a prevalent mental disease, but most people do not have enough interaction with individuals on the autism spectrum; they may learn about it through other resources like movies and television shows. Therefore, it is essential to ensure the veracity of ASD character portrayals on screen. Many previous researchers have analyzed the details of the representation of ASD in popular culture, but academic articles focusing only on a particular TV series are scarce. Thus, this research aims to analyze the differences between on-screen portrayals and realistic characters of ASD from the case study of The Good Doctor, which is popular in many countries. This study first records the specifics of ASD portrayals in this television series, then compares them to the DSM-5 criteria for ASD, determines whether these depictions can influence people's understanding, and concludes with suggestions for the depiction of ASD characters in film and TV. The results show that in The Good Doctor, ASD characters frequently tend to be highlighted savant skills and simultaneously represent the four symptoms of the second diagnostic criteria for ASD in DSM-5; besides, specific plot strands like unfortunate experiences tend to be set up. Therefore, to solve these problems, autistic characters can be included in some long-running and popular TV series to influence the public's views sustainably. More incidental ASD characters could also be encouraged to appear on screen to provide various characteristics of ASD. Besides, competent educators can also assist people in viewing these dramas in educational settings.

Male and Female Toddlers with DSM-5 Autism Spectrum Disorder have Similar Developmental Profiles and Core Autism Symptoms.

Compare developmental profiles and core ASD symptom manifestation between male and female toddlers with DSM-5 ASD. Retrospective record review of 500 toddlers (79% male) at time of ASD diagnosis. There were no differences in developmental functioning between males and females. When adjusting for multiple comparisons, sex differences were only noted for sensory seeking behavior occurring at a higher frequency in females. Overall, there were no significant differences in demographic characteristics, developmental functioning, or manifestation of core ASD symptoms between males versus female toddlers at the time of DSM-5 ASD diagnosis.

Heterogeneity thwarts autism explanatory power: A proposal for endophenotypes.

Many researchers now believe that autism heterogeneity is likely to include many disorders, but most research is based on samples defined by the DSM-5 Autism Spectrum Disorder (ASD) criteria. However, individuals diagnosed with autism have complex and varied biological causes for their symptoms. Therefore, autism is not a unitary biological entity. And although autism is significantly different from typical development, autism is not a unitary clinical disorder because diagnosed individuals vary in symptom patterns, comorbidities, biomarkers, and gene variants. The DSM-5 ASD criteria were designed to reduce heterogeneity, and there have been many other efforts to reduce autism heterogeneity including using more stringent clinical criteria, dividing autism into low and high functioning groups, creating subgroups, and by studying larger samples. However, to date these efforts have not been successful. Heterogeneity is extensive and remains unexplained, and no autism pathophysiology has been discovered. Most importantly, heterogeneity has hindered the explanatory power of the autism diagnosis to discover drug regimens and effective behavioral treatments. The paper proposes that possible transdiagnostic endophenotypes may reduce autism heterogeneity. Searching for transdiagnostic endophenotypes requires exploring autism symptoms outside of the framework of the DSM-5 autism diagnosis. This paper proposes that researchers relax diagnostic criteria to increase the range of phenotypes to support the search for transdiagnostic endophenotypes. The paper proposes possible candidates for transdiagnostic endophenotypes. These candidates are taken from DSM-5 ASD criteria, from concepts that have resulted from researched theories, and from symptoms that are the result of subtyping. The paper then sketches a possible basis for a future transdiagnostic endophenotypes screening tool that includes symptoms of autism and other neurodevelopmental disorders.

The Optimal Cut-Off Point for Thai Diagnostic Autism Scale and Probability Prediction of Autism Spectrum Disorder Diagnosis in Suspected Children.

The Thai Diagnostic Autism Scale (TDAS) was developed to diagnose autism spectrum disorder (ASD) under the context and characteristics of the Thai population. Although the tool has an excellent agreement, the interpretation of diagnostic results needs to rely on the optimal cut-off point to maximize efficiency and clarity. This study aims to find an optimal cut-off point for TDAS in the diagnosis of ASD and to compare its agreement with the DSM-5 ASD criteria. This study was conducted on 156 children aged 12–48 months old who were suspected of having ASD and had enrolled from hospitals in the four regions of Thailand in 2017–2018. The optimal cut-off point for TDAS was considered by using receiver operating characteristic (ROC) curves according to the DSM-5 ASD criteria. The areas under the curve (AUCs) for TDAS and ADOS-2 were also compared. Multivariable logistic regression was performed to create a predictive model for the probability of ASD. The AUC of TDAS was significantly higher than that of ADOS-2 (0.8748 vs. 0.7993; p = 0.033). The optimal cut-off point for TDAS was ≥20 points (accuracy = 82.05%, sensitivity = 82.86%, and specificity = 80.93%). Our findings show that TDAS with a cut-off point can yield higher diagnostic accuracy than ADOS-2 and TDAS domain. Diagnosis by using this cut-off point could be useful in practical assessments.

Diagnostic evaluation of patients referred by family physicians with the suspicion of autism spectrum disorder

Current evidence shows that early interventions in children with autism spectrum disorder (ASD) are more efficient and associated with better long-term outcomes. This also highlights the need for early recognition of children with ASD symptoms by family physicians and referral to child psychiatrists. This study aimed to evaluate how family physicians’ knowledge about ASD is reflected in clinical practice by making a diagnostic evaluation of the cases referred with suspected ASD. The study included 149 cases that family physicians referred to child psychiatrists regarding the assessment for ASD. Diagnostic evaluation of the subjects was carried out using the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) criteria. Childhood Autism Rating Scale (CARS) and Autism Behavior Checklist (ABC) were used in the evaluation process. Denver II developmental screening inventory was used to evaluate all subjects under six. The mean age of all participants was 39.1 (±13.2) months, and in ASD cases, it was 34.6 (±7.8) months. Of all referred cases, 72,5% were diagnosed according to the DSM-5 criteria. The most common diagnoses were global developmental delay (28.9%), language disorder (15.4%), ASD (15.4%), and attention deficit hyperactivity disorder (8.7%), respectively. The most common reason for referral specified on the consultation note was delayed speech, with a rate of 87.2%. In addition, 148 (99.3%) of the symptoms noted on the referral note were clustered within the DSM-5 ASD A criteria and 19 (12.8%) within the ASD B criteria. Developmental delay was more prominent in cases with ASD when compared to those with global developmental delay and language disorder. The most common diagnosis was a global developmental delay in referred cases, and only some of the symptoms seen in ASD from the referral notes of family physicians stood out as the reason for referral. These results underline the necessity of continuing ASD training for family physicians.

Defining in Detail and Evaluating Reliability of DSM-5 Criteria for Autism Spectrum Disorder (ASD) Among Children.

This paper describes a process to define a comprehensive list of exemplars for seven core Diagnostic and Statistical Manual (DSM) diagnostic criteria for autism spectrum disorder (ASD), and report on interrater reliability in applying these exemplars to determine ASD case classification. Clinicians completed an iterative process to map specific exemplars from the CDC Autism and Developmental Disabilities Monitoring (ADDM) Network criteria for ASD surveillance, DSM-5 text, and diagnostic assessments to each of the core DSM-5 ASD criteria. Clinicians applied the diagnostic exemplars to child behavioral descriptions in existing evaluation records to establish initial reliability standards and then for blinded clinician review in one site (phase 1) and for two ADDM Network surveillance years (phase 2). Interrater reliability for each of the DSM-5 diagnostic categories and overall ASD classification was high (defined as very good .60-.79 to excellent ≥ .80 Kappa values) across sex, race/ethnicity, and cognitive levels for both phases. Classification of DSM-5 ASD by mapping specific exemplars from evaluation records by a diverse group of clinician raters is feasible and reliable. This framework provides confidence in the consistency of prevalence classifications of ASD and may be further applied to improve consistency of ASD diagnoses in clinical settings.

Using latent profile analysis to evaluate the utility of a DSM-5 symptom checklist in screening children for autism spectrum disorder

Objective: Currently available screening measures for Autism Spectrum Disorder (ASD) typically do not reflect DSM-5 diagnostic criteria and generally have weak positive predictive values. These factors result in missed opportunities for early intervention, delays in diagnosis, and contribute to inefficient usage of healthcare resources by inadequately discerning those in need of comprehensive assessment. This study examined a DSM-5 ASD symptom checklist to determine whether parent-report response patterns could accurately identify which children received an ASD diagnosis. Method: Data were examined from 376 ASD evaluations in a three-year period. Latent profile analysis was used to determine if subgroups could be identified according to parent response patterns, and network analysis was implemented to examine the relationship among DSM-5 ASD criteria within each latent profile. Results: A four-profile model was best supported based on fit indices and high probability classifications. The model was largely a product of how parents responded regarding their child’s sensory behavior and minimally reflected other symptomatology. Subsequent network analyses by profile indicated weak coherence among DSM-5 symptoms within all profiles. Overall, direct assessment of DSM-5 criteria based on parent report did not add diagnostic value beyond that reflected in base rates. Conclusions: Although continued refinement of ASD screening tools is needed to improve accuracy of referrals for evaluations and reduce wait time for diagnosis, this study continues to support the need for behavioral observation and formal assessment by trained clinicians. Continued development of sensitive and specific screening tools, likely with embedded behavioral and/or objective observation, is needed.

CONSTRUCT VALIDITY OF INDONESIAN LANGUAGE VERSION OF CHILDHOOD AUTISM RATING SCALE™ SECOND EDITION

Combination of The Childhood Autism Rating Scale™ Second Edition - Standard Clinical Tool (CARS2-ST) with criteria for autism spectrum disorder (ASD) based on Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) is thought to improve diagnostic process. To meet diagnostic needs, localized, Indonesian-translated version of CARS2-ST is developed. Therefore, assessment of construct validity of the Indonesian-language translated CARS2-ST must be performed. A cross-sectional study was conducted in Child Development Center in Surabaya, Indonesia from August to December 2019. Diagnosis of ASD then performed by using CARS2-ST and DSM-5 criteria. To assess construct validity, principal components analysis and Kaiser-varimax rotation was performed for CARS2-ST in order to determine factors. DSM-5 criteria for ASD was used to compare scale.There were 201 children aged 2 - 6 years old with reported speech and behavior problems. Sixty-six children were diagnosed for ASD. Factor analysis using Kaiser-varimax rotation indicates a significant two factors: social communication and interaction factor and restrictive stereotyped behaviors and sensory factor sensitivites. The factors satisfyingly reflects the criteria for ASD in DSM-5.Construct validity of Indonesian-translated version of CARS2-ST is confirmed, as shown by its correspondence with DSM-5 criteria for diagnosing . This study supports the continued relevance of the Indonesian CARS2-ST in ASD assessment.

Identifying Subgroups of Toddlers with DSM-5 Autism Spectrum Disorder Based on Core Symptoms.

The objective of this study was to identify subgroups of toddlers with DSM-5 ASD based on core ASD symptoms using a person-based analytical framework. This is a retrospective study of 500 toddlers (mean age 26months, 79% male) with DSM-5 ASD. Data were analyzed using latent class analyses in which profiles were formed based on ASD symptomatology. Social communication (SC) symptoms favored a three-class solution, while restricted/repetitive behaviors (RRBs) favored a two-class solution. Classes with higher consistency of SC deficits were younger, with lower developmental functioning. The class with more RRBs was older, with higher functioning. If confirmed in other populations, these classes may more precisely characterize subgroups within the heterogeneous group of toddlers at time of ASD diagnosis.

DSM-5 criteria for autism spectrum disorder maximizes diagnostic sensitivity and specificity in preschool children.

The criteria for autism spectrum disorder (ASD) were revised in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM). The objective of this study was to compare the sensitivity and specificity of DSM-IV-Text Revision (DSM-IV-TR) and DSM-5 definitions of ASD in a community-based sample of preschool children. Children between 2 and 5years of age were enrolled in the Study to Explore Early Development-Phase 2 (SEED2) and received a comprehensive developmental evaluation. The clinician(s) who evaluated the child completed two diagnostic checklists that indicated the presence and severity of DSM-IV-TR and DSM-5 criteria. Definitions for DSM-5 ASD, DSM-IV-TR autistic disorder, and DSM-IV-TR Pervasive Developmental Disorder Not Otherwise Specified (PDD-NOS) were created from the diagnostic checklists. 773 children met SEED2 criteria for ASD and 288 met criteria for another developmental disorder (DD). Agreement between DSM-5 and DSM-IV-TR definitions of ASD were good for autistic disorder (0.78) and moderate for PDD-NOS (0.57 and 0.59). Children who met DSM-IV-TR autistic disorder but not DSM-5 ASD (n = 71) were more likely to have mild ASD symptoms, or symptoms accounted for by another disorder. Children who met PDD-NOS but not DSM-5 ASD (n = 66), or vice versa (n = 120) were less likely to have intellectual disability and more likely to be female. Sensitivity and specificity were best balanced with DSM-5 ASD criteria (0.95 and 0.78, respectively). The DSM-5 definition of ASD maximizes diagnostic sensitivity and specificity in the SEED2 sample. These findings support the DSM-5 conceptualization of ASD in preschool children.

Exploration of the DSM-5’s Autism Spectrum Disorder Severity Level Specifier and Prediction of Autism Severity

ABSTRACTWith the publication of DSM-5, clinical assessment of Autism Spectrum Disorder (ASD) has begun to follow a new dimensional framework which includes new severity specifiers. Little research has explored these severity ratings in comparison to other previously established severity indicators (e.g. ADOS-2 calibrated severity score). The current study compared parent and teacher ratings using the BASC-2 for 43 children and adolescents diagnosed with DSM-5 ASD, to contribute novel information to the BASC literature and to explore the new DSM-5 severity ratings. Linear regression analyses were conducted to determine the extent to which the DSM-5 Social Communication and Restrictive/Repetitive Behavior Severity Ratings (clinician-rated) predicted autism severity based on ADOS-2 calibrated severity scores. Furthermore, linear regressions were conducted to explore whether teacher ratings on the BASC-2 enhance parent ratings. Implications of these preliminary results for the assessment of children and adolescents with ASD are suggested.

Autism Spectrum Disorder Diagnosis in Diagnostic and Statistical Manual of Mental Disorders-5 Compared to Diagnostic and Statistical Manual of Mental Disorders-IV.

Objectives:The objective of this study was to investigate the concordance of Diagnostic and Statistical Manual of Mental Disorders (DSM-IV and DSM-5) diagnostic criteria for autism spectrum disorder (ASD).Methods:We retrospectively reviewed the medical records of 170 subjects (age range: 3–23, 140 boys) with developmental delay or social deficit from January 2011 to July 2016 at the Department of Psychiatry of Asan Medical Center. The Autism Diagnostic Interview-Revised (ADI-R), the Autism Diagnostic Observation Schedule (ADOS), and intelligence tests were performed for each subject. Diagnosis was reviewed and confirmed for each subject with DSM-IV Pervasive Developmental Disorder (PDD) and DSM-5 ASD criteria, respectively.Results:Fifty-eight of 145 subjects (34.1%) who were previously diagnosed as having PDD in DSM-IV did not meet DSM-5 ASD criteria. Among them, 28 (48.3%) had Asperger’s disorder based on DSM-IV. Most algorithm scores on ADOS and all algorithm scores on ADI-R were highest in subjects who met both DSM-IV PDD criteria and DSM-5 ASD criteria (the Convergent group), followed by subjects with a DSM-IV PDD diagnosis who did not have a DSM-5 ASD diagnosis (the Divergent group), and subjects who did not meet either DSM-IV PDD or DSM-5 ASD criteria (the non-PDD group). Intelligence quotient was lower in the Convergent group than in the Divergent group.Conclusion:The results of our study suggest that ASD prevalence estimates could be lower under DSM-5 than DSM-IV diagnostic criteria. Further prospective study on the impact of new DSM-5 ASD diagnoses in Koreans with ASD is needed.

Correlates of DSM-5 Autism Spectrum Disorder Levels of Support Ratings in a Clinical Sample.

The DSM-5 features level of support ratings for social communication (SC) and restrictive and repetitive behaviors (RRB) for individuals with autism spectrum disorder (ASD). We contrasted cognitive, adaptive, and autism severity scores across SC and RRB groups for 158 individuals with ASD diagnosed in a developmental disabilities clinic. Roughly 46% of individuals were identified by licensed psychologists' clinical judgement as needing Level 2 SC support and 49% were identified as needing Level 2 RRB support. No individuals were rated as needing a combination of Level 1/Level 3 supports across domains. MANOVA and direct discriminant analysis revealed that both SC and RRB groups showed a graded pattern of higher adaptation/lower autism severity to lower adaptation/higher autism severity from Level 1 to Level 3.

Prevalence of DSM-5 Autism Spectrum Disorder Among School-Based Children Aged 3-12Years in Shanghai, China.

We estimated the prevalence of ASD in a population-based sample comprising children aged 3-12years (N = 74,252) in Shanghai. This included a high-risk group sampled from special education schools and a low-risk group randomly sampled from general schools. First, we asked parents and then teachers to complete the Social Communication Questionnaire for participating children. Children who screened positive based on both parental and teachers' reports were comprehensively assessed. ASD was identified based on DSM-5 criteria. We identified 711 children as being at-risk for ASD, of which 203 were identified as ASD cases. The prevalence of ASD was 8.3 per 10,000, which is likely an underestimate, given that 81.6% of the children diagnosed with ASD had IQs below 40. This is the first report on the prevalence of ASD according to DSM-5 in China.

Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm

DSM-5 Autism Spectrum Disorder (ASD) comprises a set of neurodevelopmental disorders characterized by deficits in social communication and interaction and repetitive behaviors or restricted interests, and may both affect and be affected by multiple cognitive mechanisms. This study attempts to identify and characterize cognitive subtypes within the ASD population using our Functional Random Forest (FRF) machine learning classification model. This model trained a traditional random forest model on measures from seven tasks that reflect multiple levels of information processing. 47 ASD diagnosed and 58 typically developing (TD) children between the ages of 9 and 13 participated in this study. Our RF model was 72.7% accurate, with 80.7% specificity and 63.1% sensitivity. Using the random forest model, the FRF then measures the proximity of each subject to every other subject, generating a distance matrix between participants. This matrix is then used in a community detection algorithm to identify subgroups within the ASD and TD groups, and revealed 3 ASD and 4 TD putative subgroups with unique behavioral profiles. We then examined differences in functional brain systems between diagnostic groups and putative subgroups using resting-state functional connectivity magnetic resonance imaging (rsfcMRI). Chi-square tests revealed a significantly greater number of between group differences (p < .05) within the cingulo-opercular, visual, and default systems as well as differences in inter-system connections in the somato-motor, dorsal attention, and subcortical systems. Many of these differences were primarily driven by specific subgroups suggesting that our method could potentially parse the variation in brain mechanisms affected by ASD.

Evaluating social (pragmatic) communication disorder.

Social (pragmatic) communication disorder (SPCD) is a new diagnosis introduced by DSM-5, characterised by problems with verbal and nonverbal social communication. It is currently unclear whether SPCD is a valid diagnostic category, because little is known about the characteristics of those who meet its criteria. We sought to identify and describe cases of SPCD, to contribute to debates about its validity. We investigated whether the symptoms of SPCD cluster together to form a coherent syndrome that is distinct from autism spectrum disorder (ASD) in terms of its core and associated features. Participants were young people (N=1,081, age range=4-18years) who had attended a specialist social communication disorders clinic for children with fluent language and normal-range intelligence. Standardised parent-report data were collected using the Developmental, Dimensional and Diagnostic Interview (3Di), Child Communication Checklist (CCC) and Strengths and Difficulties Questionnaire (SDQ). An algorithm was designed using 3Di and CCC items to implement DSM-5 SPCD criteria. Eighty-eight young people met our criteria for SPCD, with 801 meeting DSM-5 ASD criteria and the remaining 192 having neither SPCD nor ASD ('clinical comparison group'). The core symptoms of SPCD co-occurred to a moderate degree (average interitem correlation=.22). SPCD cases had autistic social difficulties that were intermediate between ASD and the clinical comparison group. SPCD was associated with high rates of nonautistic psychopathology, with 63.5% scoring in the abnormal range of the SDQ's Total Problems scale. We did not find evidence that SPCD is qualitatively distinct from ASD. Rather, it appears to lie on the borderlands of the autism spectrum, describing those with autistic traits that fall just below the threshold for an ASD diagnosis. SPCD may have clinical utility for identifying people with autistic traits that are insufficiently severe for ASD diagnosis, but who nevertheless require support.

Underestimation of autism spectrum disorders according to DSM-5 criteria: A pilot study

IntroductionRecent studies on autism concern the number of individuals diagnosed with pervasive developmental disorder (PDD) according to DSM-IV-TR who may no longer qualify for diagnoses under the new DSM-5 autism spectrum disorder (ASD). ASD is diagnosed using the impairments in two dimensions:– the social and communication dimension;– the restricted and repetitive interests and behaviors (RRIB) dimension whereas PDD is diagnosed using impairments in three dimensions.All the studies indicate between 50 and 75% of individuals will maintain diagnoses.ObjectivesThe aim of the study is to quantify how many individuals with previous PDD diagnoses under DSM-IV-TR criteria would maintain a diagnosis of ASD under DSM-5 criteria.MethodsOur sample consists of 23 cases (21 males, 2 female) related to the treatment Centre “Una breccia nel muro” of Rome and Salerno. All the cases previous received a PDD diagnose according to DSM-IV TR criteria. The mean age of cases was 7.7 years. All the cases were diagnosed by our team according to DSM-5 criteria, clinicians also used to make diagnoses: the Autism Diagnostic Observation Schedule-2, the Autism Diagnostic Interview-Revised.ResultsEighty-seven percent of cases with PDD were classified as ASD using DSM-5 criteria. Thirteen percent of cases, that previous received an Asperger diagnose, did not meet the ASD criteria (Fig. 1).ConclusionsDSM-5 criteria may easily exclude cases with high functioning from ASD because they tend to be atypical for ASD according to this study.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Identifying High Ability Children with DSM-5 Autism Spectrum or Social Communication Disorder: Performance on Autism Diagnostic Instruments.

This study was a replication of Mazefsky et al.'s (Journal of Autism and Developmental Disabilities 43:1236-1242, 2013) investigation among a sample of 45 high ability children and adolescents diagnosed with ASD under DSM-IV-TR. Items from the ADOS and ADI-R were mapped onto DSM-5 diagnostic criteria for ASD and SCD to determine whether participants would meet either diagnosis under DSM-5. If the ADOS were administered alone, 62% of individuals diagnosed with ASD would no longer meet criteria under DSM-5; however, when the ADI-R and ADOS scores were combined, 100% of individuals would continue to meet ASD diagnosis. The ADOS was determined to be an insufficient measure for SCD due to the small number of algorithm items measuring SCD diagnostic criteria, suggesting the development of SCD measures is required.

A Meta-analysis of DSM-5 Autism Diagnoses in Relation to DSM-IV and DSM-IV-TR

This appears to be the first meta-analysis study which has incorporated articles on the percentage of people with a Diagnostic and Statistical Manual of Mental Disorders-Forth Edition (DSM-IV) autism spectrum disorder (ASD) diagnosis receiving a Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) ASD diagnosis and articles on the percentage of people with a Diagnostic and Statistical Manual of Mental Disorders-Forth Edition-Text Revision (DSM-IV-TR) ASD diagnosis receiving a DSM-5 ASD diagnosis. Our meta-analysis measured the percentage of people with an ASD diagnosis from the DSM-IV or DSM-IV-TR obtaining an ASD diagnosis from the DSM-5. All 24 studies identified indicated a reduction in the number of people with a DSM-IV or DSM-IV-TR ASD diagnosis being eligible for a DSM-5 ASD diagnosis, a 35 and 37 % reduction respectfully. Our meta-analysis also showed that those with a DSM-IV-TR or DSM-IV diagnosis of PDD-NOS were the least likely to qualify for a DSM-5 ASD diagnosis at 26 and 47 % followed by 55 and 19 %, respectfully of people with Asperger syndrome, and 80 and 87 %, respectfully of people with an autism diagnosis.