Key PointsQuestion
What are the patterns of nonsocial and social cognitive functioning in adults with autism spectrum disorder?
Findings
In this systematic review and meta-analysis of 75 studies comprising 3361 individuals with autism spectrum disorder and 5344 neurotypical adults, those with autism spectrum disorder showed the greatest impairments in theory of mind and emotion perception and processing, followed by processing speed and verbal learning and memory.
Meaning
The severity of impairments across domains of nonsocial and social cognition in adults with autism spectrum disorder identified highlight key intervention targets and suggest significant implications for clinical practice.
Importance
Many studies have investigated impairments in cognitive domains in adults with autism spectrum disorder (ASD). Yet, to date, a comprehensive overview on the patterns of cognitive functioning is lacking.
Objective
To provide an overview of nonsocial and social cognitive functioning in various domains in adults with ASD, allowing for comparison of the severity of deficits between different domains.
Data Sources
A literature search performed in an academic medical setting was conducted using PubMed, PsycINFO, Embase, and Medline databases with the combination of the following free-text and Medical Subject Headings where applicable: [cogniti* OR neurocogniti* OR neuropsycholog* OR executive function* OR IQ OR intelligence quotient OR social cognition OR emotion perception OR affect perception OR emotion recognition OR attribution OR ToM OR mentalising OR mentalizing OR prosody OR social knowledge OR mind reading OR social cue OR social judgment] AND [autis* OR ASD OR Asperger OR Asperger’s OR PDD OR pervasive developmental disorder]. The search was further limited to studies published between 1980 (first inclusion of autism diagnosis in the DSM-III) and July 2018.
Study Selection
Studies included were published as a primary peer-reviewed research article in English, included individuals with ASD 16 years or older, and assessed at least 1 domain of neurocognitive functioning or social cognition using standard measures.
Data Extraction and Synthesis
Of 9892 articles identified and screened, 75 met the inclusion criteria for the systematic review and meta-analysis.
Main Outcomes and Measures
Hedges g effect sizes were computed, and random-effects models were used for all analyses. Moderators of between-study variability in effect sizes were assessed using meta-regressions.
Results
The systematic review and meta-analysis included 75 studies, with a combined sample of 3361 individuals with ASD (mean [SD] age, 32.0 [9.3] years; 75.9% male) and 5344 neurotypical adults (mean [SD] age, 32.3 [9.1] years; 70.1% male). Adults with ASD showed large impairments in theory of mind (g = −1.09; 95% CI, −1.25 to −0.92; number of studies = 39) and emotion perception and processing (g = −0.80; 95% CI, −1.04 to −0.55; n = 18), followed by medium impairments in processing speed (g = −0.61; 95% CI, −0.83 to −0.38; n = 21) and verbal learning and memory (g = −0.55; 95% CI, −0.86 to −0.25; n = 12). The least altered cognitive domains were attention and vigilance (g = −0.30; 95% CI, −0.81 to 0.21; n = 5) and working memory (g = −0.23; 95% CI, −0.47 to 0.01; n = 19). Meta-regressions confirmed robustness of the results.
Conclusions and Relevance
Results of this systematic review and meta-analysis suggest that adults with ASD show impairments in social cognitive domains and in specific nonsocial cognitive domains. These findings contribute to the understanding of the patterns of cognitive functioning in adults with ASD and may assist in the identification of targets for cognitive interventions.
Autism spectrum disorder (ASD) is characterized by persistent deficits in social communication and social interaction, along with restricted, repetitive patterns of behavior, interests, or activities (per the Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition] [DSM-5]).1 In addition to genetic and neurobiological factors, these behavioral patterns are suggested to be primarily underpinned by impairments in nonsocial and social cognition,2-4 which are also direct contributors to individuals’ poor adaptive functioning.2 Autism spectrum disorder alters functioning in many domains throughout an individual’s life span (eg, unemployment, social relationships, and quality of life2,5). However, despite similar ASD prevalence rates of 1% among children and adults6 and clear challenges that persist into adulthood, research and treatment efforts have been largely dedicated to children.7 The identification of treatment targets for adults with ASD and development of successful treatment strategies for this population have been recognized as priority areas for research by the Special Interest Group at the International Meeting for Autism Research.8
A critical question that has remained largely unaddressed concerns the identification of cognitive domains that are most severely impaired in adults with an ASD diagnosis. This lack of knowledge is surprising considering the importance of cognitive skills (eg, attention) relative to the early detection and recognition of ASD.9 Existing research has largely focused on impairments in the following 2 key cognitive domains: (1) the inability to attribute mental states, beliefs, intents, and so forth to oneself and others to understand their actions, also referred to as theory of mind,4 and (2) impairments in executive dysfunction (eg, planning, cognitive flexibility, and inhibition).10,11 However, a wider range of cognitive domains appears to be altered, including working memory,12,13 processing speed,14 attention,15 and verbal learning.16
Despite huge efforts of individual studies to increase the understanding of the cognitive deficits in adults with ASD, sample sizes were often small,17-19 yielding inconsistent findings.20 Moreover, most studies have focused on a single cognitive domain,16,21,22 and methods of assessment used vary across studies.14,23 Therefore, answering this important clinical question requires a comprehensive overview of the literature. By aggregating all available literature, it is possible to directly compare the relative severity of impairments across various cognitive domains. A greater understanding of the cognitive performance of adults with ASD can inform cognitive theories24 and may provide insight on the progression of ASD symptoms into adulthood. The lack of such information limits treatment development in this area.20
The present systematic review and meta-analysis aimed to systematically map the severity of impairments across domains of nonsocial and social cognitive functioning in adults with ASD compared with the neurotypical adult population. To help explain any variability between studies, potential moderators of impairments observed in these individuals were evaluated. A detailed evaluation and comparison of nonsocial and social cognitive deficits in adults with ASD will advance knowledge about the expression of ASD in later life and may help pinpoint targets for nonsocial and social cognitive intervention.
This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline recommendations.25 A literature search performed in an academic medical setting was conducted using PubMed, PsycINFO, Embase, and MEDLINE databases with the combination of the following free-text and Medical Subject Headings where applicable: [cogniti* OR neurocogniti* OR neuropsycholog* OR executive function* OR IQ OR intelligence quotient OR social cognition OR emotion perception OR affect perception OR emotion recognition OR attribution OR ToM OR mentalising OR mentalizing OR prosody OR social knowledge OR mind reading OR social cue OR social judgment] AND [autis* OR ASD OR Asperger OR Asperger’s OR PDD OR pervasive developmental disorder]. The search was further limited to studies published between 1980 (first inclusion of autism diagnosis in the DSM-III) and July 2018, among individuals 16 years or older.
Studies were included if they fit 5 criteria. First, they had to be published as a primary peer-reviewed research article in English. Second, they had to include individuals with ASD 16 years or older (confirmed diagnosis with either the DSM, International Classification of Diseases [ICD], or another valid diagnostic measure) (complete measures are listed in Table 1 and Table 2). Third, they had to assess at least 1 domain of nonsocial or social cognition using standard measures. Fourth, they had to provide sufficient information to allow for effect size calculations (eg, mean [SD] for the ASD group and the neurotypical control group). Fifth, an age- and IQ-matched neurotypical control group had to be included.
After initial screening of the abstracts, studies were excluded for 3 reasons. First, studies were excluded if the sample included a nonclinical population (eg, with autistic-like traits). Second, studies were excluded if participants were initially seen with comorbidity of any neurological conditions altering cognition (eg, epilepsy). Third, studies were excluded if no data on any of the specified cognitive domains were available (if only total IQ was reported, the study was excluded).
In total, 9892 potentially eligible articles were identified (Figure 1). After the first screening of titles (stage 1), 7488 articles were reviewed by their abstracts (stage 2). Stage 2 yielded 1268 articles for full-text reviews (stage 3). Thirty percent of the stage 1 yield were double screened by 2 of us (T.V. and A.K.F./E.V.), with Cohen κ interrater reliability values of 0.95 and 0.98, respectively, which represents an excellent strength of agreement.92 Consensus decisions were made on the inclusion of any inconsistently screened articles (included by one reviewer and excluded by the other). Five articles did not report the mean scores on the measures of interest and/or reported the means in figures only (for which the exact numbers could not be extracted). Missing data could not be obtained after contacting the authors. The resulting 76 studies that met all the inclusion criteria are listed in Table 1 and Table 2. All included domains with associated measures and parameters (ie, the measure outcomes) are listed in Table 3.
The following key domains of nonsocial cognition were included: (1) reasoning and problem solving, (2) processing speed, (3) attention and vigilance, (4) working memory, (5) visual learning and memory, (6) verbal learning and memory, (7) verbal comprehension, and (8) verbal fluency. Social cognition was categorized into the following 3 domains: (1) theory of mind, (2) emotion perception and processing, and (3) social perception and knowledge. The overview of domains followed the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) consensus,93 which aimed for more standardized cognitive research in schizophrenia but has previously been adopted for the ASD population.14
Ten meta-analyses were carried out, including domains of nonsocial and social cognition for which at least 3 independent studies were found. The social perception and knowledge domain was reported by only 2 studies and hence was omitted from further analysis. Because one of the included studies only reported outcomes on this domain, the present meta-analysis consisted of 75 studies.
When studies did not provide a total mean score on a particular measure but reported subscores (eg, individual emotions presented separately), data were pooled into an overall mean score. Similarly, when studies reported the mean scores per subgroup (eg, by sex or by diagnosis [Asperger syndrome and high-functioning autism]), data were pooled into an overall mean score. In cases where higher mean scores on cognitive measures corresponded to worse (and not better) performance, effect sizes were reversed. If a study provided more than 1 outcome within the same cognitive domain, the measures were aggregated by computing the mean effect size (and standard error) based on the assumption that the correlation is in the region of 1 between the measures.94 In case of overlapping samples from 2 or more articles reporting outcomes for the same domain, only the largest sample was considered. Meta-analyses were completed using a random-effects model (DerSimonian-Laird estimate), which assumes a distribution of true effect sizes and aims to evaluate the mean of this distribution. When assigning weights to estimate the effect size, the within-studies and between-studies sampling errors are considered.95 All analyses were carried out using statistical software (Stata/MP 15.0; StataCorp LP96).
For each of these individual meta-analyses, we reported the number of studies, total sample size for the ASD group and the neurotypical control group, the mean effect size (Hedges g) with 95% CI, P value, and the results from the Cochran Q test for heterogeneity (Figure 2). The magnitude of Hedges g may be interpreted using Cohen d97 effect sizes convention, described as 0.20 for small, 0.50 for medium, and 0.80 for large. The Cochran Q test acquired for each of the domains represents the weighted sum of squared differences between individual study effects and the pooled effect across studies. The I2 statistic refers to the percentage of variability in point estimates that is due to between-study heterogeneity rather than sampling error.98 A value of 0 suggests the absence of heterogeneity, in which case the random-effects model is simplified to a fixed-effects model. To assess risk of publication bias, the funnel plots for each cognitive domain were examined for asymmetry and then formally evaluated with Egger test. If publication bias was found, the trim-and-fill method was applied,99 providing effect sizes adjusted for publication bias.
The moderators selected include variables that might alter the observed association between impairments in nonsocial or social cognition and ASD. The sample selection and its characteristics (ie, age, sex, and IQ) can moderate the cognitive performance due to differential developmental trajectories observed for ASD100 and neurotypical individuals.101 Similarly, the assessment methods (eg, what is the response mode required) can have an effect on the cognitive performance.100 Because these variables vary between studies, the findings are difficult to interpret without the inclusion of these moderators in the meta-regression model.
Eight moderators were considered. First was the mean age, previously shown to be associated with the cognitive performance in adults with ASD.102 Second was sex, building on reports on sex-related cognitive profiles.103 Third, diagnostic classification was included due to potential sampling bias and was categorized as diagnosis made using the DSM/ICD, Autism Diagnostic Observation Schedule (ADOS)/Autism Diagnostic Interview Revised (ADI-R)/Autism Spectrum Quotient Questionnaire (AQ)/Diagnostic Interview for Social and Communication Disorders (DISCO), or DSM/ICD plus ADOS/ADI-R/AQ/DISCO.104,105 Fourth was the mean number of years of education.106 Fifth, IQ differences were explored with the following 2 different approaches: (1) we created a variable that indicated whether a significant IQ difference was observed between the study groups (yes or no) and (2) we examined the mean IQ of a study sample because evidence suggests that intelligence may act as a moderator of cognitive presentation.107,108 Sixth was assessment tool format (computer vs traditional administration) and the response mode (verbal vs motor), previously shown to have significant effect on the measure outcomes.100 Seventh was country. Eighth was year of publication.
All moderators were included in the meta-regression model if information was available for a sufficient number of studies (≥4). We also aimed to include the ADOS total score; however, we could not do so due to a lack of data. Considering the number of statistical tests in meta-regressions, a conservative statistical significance (2-sided P < .01) was adopted.
In total, 9892 potentially eligible articles were identified. Most of the 75 included studies were conducted in Europe (50 [66.7%]), followed by studies from the United States and Canada (16 [21.3%]). The sample sizes varied greatly, ranging from 18 participants69 to 3907 participants (including neurotypical adults),28 with 66 studies (88.0%) using samples between 20 and 100 participants. The overall database included a combined sample of 3361 individuals with ASD (mean [SD] age of samples across studies, 32.0 [9.3] years; range, 19.6-63.6 years; 75.9% male) and 5344 neurotypical adults (mean [SD] age of samples across studies, 32.3 [9.1] years; range, 18.8-63.7 years; 70.1% male). The combined mean (SD) IQ across studies was 108.2 (9.1) for the ASD group and 109.8 (7.7) for neurotypical adults.
The meta-analyses showed consistent impairments in individuals with ASD across all nonsocial cognitive domains compared with neurotypical controls (Figure 2). The largest impairments were observed for processing speed (g = −0.61; 95% CI, −0.83 to −0.38; n = 21; P < .001), followed by verbal learning and memory (g = −0.55; 95% CI, −0.86 to −0.25; n = 12; P < .001) and reasoning and problem solving (g = −0.51; 95% CI, −0.74 to −0.28; n = 22; P < .001). The least altered domains were attention and vigilance (g = −0.30; 95% CI, −0.81 to 0.21; n = 5; P = .09) and working memory (g = −0.23; 95% CI, −0.47 to 0.01; n = 19; P = .06). There was no heterogeneity across studies on processing speed (Q = 13.42, P = .86) or reasoning and problem solving (Q = 8.83, P = .99), but there was significant variation in studies for verbal learning and memory (Q = 34.76, P < .001). The review of the funnel plots identified outliers on domains of processing speed (1 outlier), working memory (3 outliers), visual learning and memory (2 outliers), and verbal learning and memory (2 outliers). After the removal of these outliers, the magnitude of the effect sizes remained similar (the eAppendix in the Supplement contains the results after the removal of outliers). The only significant Egger test result was found for visual learning and memory. A trim-and-fill analysis did not result in imputation of any studies, and the effect size remained the same.
The greatest impairments in the ASD group compared with the neurotypical control group were found in theory of mind (g = −1.09; 95% CI, −1.25 to −0.92; number of studies = 39; P < .001) and emotion perception and processing (g = −0.80; 95% CI, −1.04 to −0.55; n = 18; P < .001) (Figure 2). The removal of 4 outliers identified by funnel plot inspection for theory of mind and the removal of 1 outlier for emotion perception and processing did not change the magnitude of the effect sizes. Egger test results were found to be significant for both domains, indicating the existence of reporting bias. However, trim-and-fill analyses did not change any of the results.
Meta-regressions showed that included moderators did not account for the heterogeneity between studies. Heterogeneity was not altered by the mean age (β range = −0.01 to 0.13, P range = .06 to .97), sex (β range = −0.01 to 0.35, P range = .06 to .88), diagnostic classification (β range = −0.41 to 0.45, P range = .08 to .84), IQ differences (β range = −0.01 to 1.65, P range = .19 to .99), the mean IQ of the study sample (β range = −0.08 to 0.21, P range = .09 to .99), assessment tool format (β range = −1.32 to 0.20, P range = .02 to .87), the response mode (β range = 0.07 to 1.63, P range = .03 to .95), country (β range = −0.20 to 1.10, P range = .23 to .86), or year of publication (β range = −1.23 to 0.61, P range = .12 to .94).
To our knowledge, this the first systematic review and meta-analysis that has investigated the patterns of nonsocial and social cognitive functioning in adults with ASD, allowing for comparison of relative cognitive strengths and weaknesses in the adult ASD population. The meta-analyses included 75 studies, with combined samples of 3361 individuals with ASD and 5344 neurotypical adults. Relative to neurotypical adults, the ASD group showed impairments across all domains of nonsocial and social cognitive functioning, with the largest deficits in social cognition (theory of mind g = −1.09 and emotion perception and processing g = −0.80) (Figure 2). Among domains of nonsocial cognition, the largest magnitude of impairment was found for processing speed (g = −0.61), followed by verbal learning and memory (g = −0.55) and reasoning and problem solving (g = −0.51). The review highlighted working memory (g = −0.23) and attention and vigilance (g = −0.30) as the least altered cognitive domains in adults with ASD. The moderators considered in the present analysis (mean age, sex, IQ, and country, among others) did not change the magnitude of the effect sizes observed.
The present findings help improve our understanding of the patterns of cognitive impairments in adults with ASD. While our results confirm key impairments in social cognition,109-111 they also highlight important challenges in nonsocial cognitive processing in ASD in the absence of overall intellectual disability. The most striking impairments in nonsocial cognition were evident in processing speed.
Dominant theories suggest that ASD is a disorder of the “social brain network” mediating social motivational and social cognitive processes, such as face processing, mental state understanding, and empathy.112 However, the findings of our systematic review and meta-analysis add support to the idea that ASD is not characterized by one “primary” cognitive deficit but instead by impairments in a selective range of “higher-order” cognitive abilities.113 This assumption is in agreement with the “multiple-deficit” theory,24 which proposes that autism may be a complex of cognitive disorders and that individuals may be affected differentially in various (possibly independent) cognitive domains. It is possible that certain subgroups experience deficits in multiple domains, while others only show impairments in a single area.
We were unable to examine the association between nonsocial and social cognitive impairments because most studies included in the present meta-analysis exclusively focused on nonsocial or social cognition. To disentangle this association and to increase our understanding of the cognitive mechanisms of ASD, future studies need to consider both domains.
Our findings have important implications for cognitive interventions in ASD. Current interventions in adults with ASD are primarily focused on improving individual adaptive social skills or social cognition114-116 (mainly theory of mind114,117), with an overall aim of improving social functioning.118 Our results support interventions that also include nonsocial cognitive domains. Promising findings from a randomized clinical trial by Eack et al119 suggest that cognitive enhancement therapy120 results in significant levels of improvement in nonsocial and social cognition. Cognitive enhancement therapy was initially designed for patients with schizophrenia,120 and the key targets of that intervention are the areas our systematic review and analysis showed to be most impaired (ie, processing speed and emotion perception and processing). Although now defined as distinct neurodevelopmental disorders, ASD and schizophrenia both share clinical and cognitive features,121 with the largest impairments in speed of processing (g = −1.03 for schizophrenia), verbal memory (g = −1.03 for schizophrenia), and executive functioning (g = −0.74 for schizophrenia).122 The broad profile of cognitive deficits in adults with ASD seems to be similar to that of individuals with schizophrenia but less severe (except in working memory, which is largely intact in ASD but not in schizophrenia122). This implies that cognitive training strategies shown to be effective across a range of cognitive domains in schizophrenia123,124 could also be adopted for the adult ASD population. More research should focus on the evaluation of effectiveness of cognitive remediation for adults with ASD.
Our systematic review and meta-analysis focused on cross-sectional studies in adults only. To our knowledge, only a single meta-analysis100 and a single systemic review125 have evaluated nonsocial cognitive deficits in children and adolescents with ASD, tapping into domains of executive functioning, working memory, and verbal fluency. When comparing these findings with the results of the present meta-analysis, we notice different profiles for specific cognitive impairments. Compared with childhood and adolescence studies, impairments in working memory100 and verbal fluency100,125 appear to become less pronounced in adulthood. In contrast, cognitive deficits in mental flexibility and response inhibition100 seem to be large in adults compared with children and adolescents diagnosed as having ASD. These findings may indicate that the pattern of cognitive development is domain specific, with development of some cognitive skills (eg, verbal fluency) delayed initially but eventually catching up to neurotypically developing controls; yet, for other domains (eg, mental flexibility), there might be a lasting developmental lag (as seen in other conditions).126 However, longitudinal studies are needed to unravel the trajectories of nonsocial and social cognitive functioning in ASD, as well as their association with functional and clinical outcomes in daily life.
Limitations and Recommendations
Our findings have to be considered in light of certain limitations. First, the domain-specific meta-analyses would have benefited from a larger number of studies (and larger sample sizes).127 Also, our meta-analyses rely exclusively on English-language peer-reviewed studies, which do not represent possible available evidence in other cultural or language areas. However, more recent data showed no systematic bias from the use of language restrictions in systematic review–based meta-analyses.128 Second, there was heterogeneity in samples regarding the diagnostic criteria used to identify individuals with ASD. However, diagnostic classification, which was included as a potential moderator in the regression models, had no association with the results. Third, some studies included individuals with higher-functioning ASD only, while others used more mixed samples (although still within the normal IQ range). Fourth, the severity of symptoms (measured by the ADOS or equivalent instruments) was rarely reported; therefore, potential cognitive variability within ASD could not be evaluated. However, a recent meta-analysis100 examining effect sizes of executive functioning between different ASD diagnostic classifications failed to find any differences. Another study129 found no association between different cognitive profiles and autism severity in all core domains. Fifth, there was some heterogeneity in types of cognitive measures used; for example, some studies worked with adapted and/or translated versions or different editions, which could have altered the outcomes. Yet, only studies using standard cognitive assessments were included in our systematic review and meta-analysis, and adapted or translated versions have been validated for the population for which they were being used. Sixth, comorbid symptoms are often found in ASD, including depression, anxiety, and attention-deficit/hyperactivity disorder (ADHD), among others.53 These comorbidities were not taken into account in the studies included herein. However, 32 of 75 included studies (42.7%) reported “other psychiatric disorder and/or neurological disorder” to be part of their exclusion criteria. It has been suggested that ADHD in children with ASD might be associated with distinct patterns of cognitive impairment.130 However, despite high comorbidity of ASD and ADHD,131 the 2 diagnoses could not be given simultaneously until the DSM-5 publication.132 Therefore, the cognitive impairments in ASD may be partly altered by comorbid ADHD. A systematic investigation is required to raise awareness about potential cognitive profiles associated with ADHD in ASD.
This systematic review and meta-analysis of impairments in nonsocial cognitive functioning and social cognition among adults with ASD showed that, despite having an intact IQ, there are medium to large deficits observed in 4 key domains of nonsocial and social cognition (theory of mind, emotion perception and processing, processing speed, and verbal learning and memory). While our findings support the key social cognitive theories of ASD, they also stress deficits in nonsocial cognitive areas. These results highlight the importance of a broader approach to our study of cognition and to our understanding of potential cognitive mechanisms underlying symptoms and treatment outcomes.
Accepted for Publication: September 19, 2018.
Corresponding Author: Tjasa Velikonja, PhD, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, PO Box 1230, New York, NY 10029 (tjasa.velikonja@mssm.edu).
Published Online: January 2, 2019. doi:10.1001/jamapsychiatry.2018.3645
Author Contributions: Dr Velikonja had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: All authors.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: All authors.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Velikonja.
Supervision: Fett, Velthorst.
Conflict of Interest Disclosures: Dr Velikonja reported receiving support from The Seaver Foundation and reported being a Seaver postdoctoral research fellow. Dr Fett reported receiving support from the Netherlands Organisation for Scientific Research (NWO) grant 451-13-035 and reported receiving a 2015 National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) Young Investigator Award from the Brain and Behavior Foundation. Dr Velthorst reported receiving support from the Netherlands Organisation for Scientific Research (NWO) grant 916-15-005 and The Seaver Foundation and reported being a Seaver faculty scholar.
Additional Contributions: Lauren Smith, BA, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, assisted with English-language editing and proofreading. No compensation was received.
1.American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th ed. Arlington, VA: American Psychiatric Association; 2013.
8.Nicholas
DB, Hodgetts
S, Zwaigenbaum
L,
et al. Research needs and priorities for transition and employment in autism: considerations reflected in a “Special Interest Group” at the International Meeting for Autism Research.
Autism Res. 2017;10(1):15-24. doi:
10.1002/aur.1683PubMedGoogle ScholarCrossref 11.Pugliese
CE, Anthony
L, Strang
JF, Dudley
K, Wallace
GL, Kenworthy
L. Increasing adaptive behavior skill deficits from childhood to adolescence in autism spectrum disorder: role of executive function.
J Autism Dev Disord. 2015;45(6):1579-1587. doi:
10.1007/s10803-014-2309-1PubMedGoogle ScholarCrossref 22.Baron-Cohen
S, Wheelwright
S, Hill
J, Raste
Y, Plumb
I. The “Reading the Mind in the Eyes” Test revised version: a study with normal adults, and adults with Asperger syndrome or high-functioning autism.
J Child Psychol Psychiatry. 2001;42(2):241-251. doi:
10.1111/1469-7610.00715PubMedGoogle ScholarCrossref 23.Golan
O, Baron-Cohen
S, Hill
JJ, Rutherford
MD. The “Reading the Mind in the Voice” test–revised: a study of complex emotion recognition in adults with and without autism spectrum conditions.
J Autism Dev Disord. 2007;37(6):1096-1106. doi:
10.1007/s10803-006-0252-5PubMedGoogle ScholarCrossref 33.Bramham
J, Ambery
F, Young
S,
et al. Executive functioning differences between adults with attention deficit hyperactivity disorder and autistic spectrum disorder in initiation, planning and strategy formation.
Autism. 2009;13(3):245-264. doi:
10.1177/1362361309103790PubMedGoogle ScholarCrossref 46.Globerson
E, Amir
N, Kishon-Rabin
L, Golan
O. Prosody recognition in adults with high-functioning autism spectrum disorders: from psychoacoustics to cognition.
Autism Res. 2015;8(2):153-163. doi:
10.1002/aur.1432PubMedGoogle ScholarCrossref 56.Kuschner
ES, Bodner
KE, Minshew
NJ. Local vs. global approaches to reproducing the Rey Osterrieth Complex Figure by children, adolescents, and adults with high-functioning autism.
Autism Res. 2009;2(6):348-358.
PubMedGoogle Scholar 64.Mathewson
KJ, Drmic
IE, Jetha
MK,
et al. Behavioral and cardiac responses to emotional Stroop in adults with autism spectrum disorders: influence of medication.
Autism Res. 2011;4(2):98-108. doi:
10.1002/aur.176PubMedGoogle ScholarCrossref 65.Mayer
JL, Heaton
PF. Age and sensory processing abnormalities predict declines in encoding and recall of temporally manipulated speech in high-functioning adults with ASD.
Autism Res. 2014;7(1):40-49. doi:
10.1002/aur.1333PubMedGoogle ScholarCrossref 66.Murray
K, Johnston
K, Cunnane
H,
et al. A new test of advanced theory of mind: the “Strange Stories Film task” captures social processing differences in adults with autism spectrum disorders.
Autism Res. 2017;10(6):1120-1132. doi:
10.1002/aur.1744PubMedGoogle ScholarCrossref 67.Nakahachi
T, Iwase
M, Takahashi
H,
et al. Discrepancy of performance among working memory–related tasks in autism spectrum disorders was caused by task characteristics, apart from working memory, which could interfere with task execution.
Psychiatry Clin Neurosci. 2006;60(3):312-318. doi:
10.1111/j.1440-1819.2006.01507.xPubMedGoogle ScholarCrossref 68.Otsuka
S, Uono
S, Yoshimura
S, Zhao
S, Toichi
M. Emotion perception mediates the predictive relationship between verbal ability and functional outcome in high-functioning adults with autism spectrum disorder.
J Autism Dev Disord. 2017;47(4):1166-1182. doi:
10.1007/s10803-017-3036-1PubMedGoogle ScholarCrossref 79.Spek
AA, Scholte
EM, Van Berckelaer-Onnes
IA. Local information processing in adults with high functioning autism and Asperger syndrome: the usefulness of neuropsychological tests and self-reports.
J Autism Dev Disord. 2011;41(7):859-869. doi:
10.1007/s10803-010-1106-8PubMedGoogle ScholarCrossref 87.White
SJ, Coniston
D, Rogers
R, Frith
U. Developing the Frith-Happé animations: a quick and objective test of Theory of Mind for adults with autism.
Autism Res. 2011;4(2):149-154. doi:
10.1002/aur.174PubMedGoogle ScholarCrossref 88.Williams
DM, Jarrold
C, Grainger
C, Lind
SE. Diminished time-based, but undiminished event-based, prospective memory among intellectually high-functioning adults with autism spectrum disorder: relation to working memory ability.
Neuropsychology. 2014;28(1):30-42. doi:
10.1037/neu0000008PubMedGoogle ScholarCrossref 91.Zwickel
J, White
SJ, Coniston
D, Senju
A, Frith
U. Exploring the building blocks of social cognition: spontaneous agency perception and visual perspective taking in autism.
Soc Cogn Affect Neurosci. 2011;6(5):564-571. doi:
10.1093/scan/nsq088PubMedGoogle ScholarCrossref 96. Stata Statistical Software. Version MP 15.0. College Station, TX: StataCorp LP; 2017.
97.Cohen
J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Erlbaum; 1988.
100.Demetriou
EA, Lampit A, Quintana DS,
et al. Autism spectrum disorders: a meta-analysis of executive function.
Mol Psychiatry. 2018;23(5):1198-1204.
PubMedGoogle Scholar 102.Braden
BB, Smith
CJ, Thompson
A,
et al. Executive function and functional and structural brain differences in middle-age adults with autism spectrum disorder.
Autism Res. 2017;10(12):1945-1959. doi:
10.1002/aur.1842PubMedGoogle ScholarCrossref 110.Frith
U. Autism: Explaining the Enigma. 2nd ed. Oxford, United Kingdom: Blackwell Publishing; 2003.
111.Baron-Cohen
S. Mindblindness: An Essay on Autism and Theory of Mind. Cambridge, MA: MIT Press; 1995.
113.Minshew
NJ, Goldstein
G, Siegel
DJ. Neuropsychologic functioning in autism: profile of a complex information processing disorder.
J Int Neuropsychol Soc. 1997;3(4):303-316.
PubMedGoogle Scholar 117.Bölte
S, Feineis-Matthews
S, Leber
S, Dierks
T, Hubl
D, Poustka
F. The development and evaluation of a computer-based program to test and to teach the recognition of facial affect.
Int J Circumpolar Health. 2002;61(suppl 2):61-68. doi:
10.3402/ijch.v61i0.17503PubMedGoogle ScholarCrossref 118.Klin
A, Saulnier
CA, Sparrow
SS, Cicchetti
DV, Volkmar
FR, Lord
C. Social and communication abilities and disabilities in higher functioning individuals with autism spectrum disorders: the Vineland and the ADOS.
J Autism Dev Disord. 2007;37(4):748-759. doi:
10.1007/s10803-006-0229-4PubMedGoogle ScholarCrossref 119.Eack
SM, Hogarty
SS, Greenwald
DP,
et al. Cognitive enhancement therapy for adult autism spectrum disorder: results of an 18-month randomized clinical trial.
Autism Res. 2018;11(3):519-530. doi:
10.1002/aur.1913PubMedGoogle ScholarCrossref 120.Hogarty
GE, Greenwald
DP. Cognitive Enhancement Therapy: The Training Manual. Pittsburgh, PA: University of Pittsburgh Medical Center; 2006.
121.Stone
WS, Iguchi
L. Do apparent overlaps between schizophrenia and autistic spectrum disorders reflect superficial similarities or etiological commonalities?
N Am J Med Sci (Boston). 2011;4(3):124-133. doi:
10.7156/v4i3p124PubMedGoogle ScholarCrossref 125.Magiati
I, Tay
XW, Howlin
P. Cognitive, language, social and behavioural outcomes in adults with autism spectrum disorders: a systematic review of longitudinal follow-up studies in adulthood.
Clin Psychol Rev. 2014;34(1):73-86. doi:
10.1016/j.cpr.2013.11.002PubMedGoogle ScholarCrossref 128.Morrison
A, Polisena
J, Husereau
D,
et al. The effect of English-language restriction on systematic review–based meta-analyses: a systematic review of empirical studies.
Int J Technol Assess Health Care. 2012;28(2):138-144. doi:
10.1017/S0266462312000086PubMedGoogle ScholarCrossref 131.Yoshida
Y, Uchiyama
T. The clinical necessity for assessing attention deficit/hyperactivity disorder (AD/HD) symptoms in children with high-functioning pervasive developmental disorder (PDD).
Eur Child Adolesc Psychiatry. 2004;13(5):307-314. doi:
10.1007/s00787-004-0391-1PubMedGoogle ScholarCrossref