Rethinking “gold standards” and “best practices” in the assessment of autism

A Systematic Review on Autism and Hyperserotonemia: State-of-the-Art, Limitations, and Future Directions

Hyperserotonemia is one of the most studied endophenotypes in autism spectrum disorder (ASD), but there are still no unequivocal results about its causes or biological and behavioral outcomes. This systematic review summarizes the studies investigating the relationship between blood serotonin (5-HT) levels and ASD, comparing diagnostic tools, analytical methods, and clinical outcomes. A literature search on peripheral 5-HT levels and ASD was conducted. In total, 1104 publications were screened, of which 113 entered the present systematic review. Of these, 59 articles reported hyperserotonemia in subjects with ASD, and 26 presented correlations between 5-HT levels and ASD-core clinical outcomes. The 5-HT levels are increased in about half, and correlations between hyperserotonemia and clinical outcomes are detected in a quarter of the studies. The present research highlights a large amount of heterogeneity in this field, ranging from the characterization of ASD and control groups to diagnostic and clinical assessments, from blood sampling procedures to analytical methods, allowing us to delineate critical topics for future studies.

Diagnostic Utility of Parent Ratings on the Behavior Assessment System for Children-Third Edition in Children who are Deaf and Hard of Hearing and Diagnosed with Autism Spectrum Disorder

Between 1 to 2 of every 1,000 children are born deaf or hard of hearing (DHH) and, of those, 30-50% have additional disabilities, including Autism Spectrum Disorder (ASD). Most measures assessing ASD characteristics rely on some degree of behavioral response to sound (e.g., responding to name, listening response), and may not be appropriate for use with children who are DHH. Further, ASD specific measures do not provide information on a child's functional abilities across developmental domains. We conducted a cross-sectional analysis comparing mean T-scores on a standardized multidimensional measure, the Behavior Assessment System for Children, Third Edition, Parent Rating Scale (BASC-3 PRS), across three groups matched for age and sex: children who are DHH and diagnosed with ASD (DHH + ASD; n = 16); children who are DHH without ASD (DHH-ASD; n = 16); and children who are typically hearing with ASD (H + ASD; n = 16). Analyses revealed statistically significant differences across scales of Attention Problems, Atypicality, Withdrawal, Behavioral Symptoms Index, Social Skills, Leadership, Functional Communication, Activities of Daily Living, Adaptive Skills, Autism Probability Indices, and Developmental Social Disorders. Pairwise comparisons showed DHH + ASD and H + ASD mean T-scores were statistically similar and distinct from DHH-ASD mean T-scores on all these scales except for Withdrawal, Leadership, Functional Communication, and Activities of Daily Living, where pairwise comparisons varied. The findings add to the literature on ASD and DHH children and call for further exploration of the BASC-3 as a tool for both evaluation of ASD and the development of individualized treatment plans in this unique population.

A Scoping Review of Diagnosis of Autism Spectrum Disorder in Primary Care

INTRODUCTION

This scoping review was performed to collect, examine, and present literature on interventions promoting the diagnosis of Autism Spectrum Disorder (ASD) in U.S. primary health care settings.

METHOD

The literature searched was from 2011-2022, in the English language, in PubMed, CINAHL, Psych INFO, Cochrane, and Web of Science, for persons with autism or ASD aged ≤ 18 years.

RESULTS

Six studies met the search criteria, including a quality improvement project, a feasibility study, a pilot study, and three primary care provider (PCP) intervention trials. Measured outcomes included: accuracy of diagnosis (n = 4), practice change maintenance (n = 3), time to diagnosis (n = 2), specialty clinic appointment wait time (n = 1), PCP comfort making ASD diagnosis (n = 1), and increased ASD diagnosis (n = 1).

DISCUSSION

Results inform future implementation of PCP ASD diagnosis for the most obvious cases of ASD and research evaluating PCP training, using longitudinal measures of PCP knowledge of ASD and intention to diagnose.

Identifying neurodevelopmental disabilities from nationalised preschool health check

OBJECTIVE

Models of psychometric screening to identify individuals with neurodevelopmental disabilities (NDDs) have had limited success. In Aotearoa/New Zealand, routine developmental surveillance of preschool children is undertaken using the Before School Check (B4SC), which includes psychometric and physical health screening instruments. This study aimed to determine whether combining multiple screening measures could improve the prediction of NDDs.

METHODS

Linked administrative health data were used to identify NDDs, including attention deficit hyperactivity disorder, autism spectrum disorder and intellectual disability, within a multi-year national cohort of children who undertook the B4SC. Cox proportional hazards models, with different combinations of potential predictors, were used to predict onset of a NDD. Harrell's c-statistic for composite models were compared with a model representing recommended cutoff psychometric scores for referral in New Zealand.

RESULTS

Data were examined for 287,754 children, and NDDs were identified in 10,953 (3.8%). The best-performing composite model combining the Strengths and Difficulties Questionnaire, the Parental Evaluation of Developmental Status, vision screening and biological sex had 'excellent' predictive power (C-statistic: 0.83) compared with existing referral pathways which had 'poor' predictive power (C-statistic: 0.68). In addition, the composite model was able to improve the sensitivity of NDD diagnosis detection by 13% without any reduction in specificity.

CONCLUSIONS

Combination of B4SC screening measures using composite modelling could lead to significantly improved identification of preschool children with NDDs when compared with surveillance that rely on individual psychometric test results alone. This may optimise access to academic, personal and family support for children with NDDs.

Increased delay from initial concern to diagnosis of autism spectrum disorder and associated health care resource utilization and cost among children aged younger than 6 years in the United States

BACKGROUND: Prolonged delays between first caregiver concern and autism spectrum disorder (ASD) diagnosis have been reported, but associations between length of time to diagnosis (TTD) and health care resource utilization (HCRU) and costs have not been studied in a large sample of children with ASD. OBJECTIVE: To address these informational gaps in the ASD diagnostic pathway. METHODS: This retrospective, observational, single cohort analysis of Optum's administrative claims data from January 1, 2011, to December 31, 2020, included commercially insured children who had 2 or more claims for an ASD diagnosis (earliest diagnosis designated as the index date), were between the ages of older than 1.5 years and 6 years or younger at index date, and were continuously enrolled for up to 48 months before and for 12 months after the index date. Two cohorts (between the ages of older than 1.5 years and 3 years or younger and between the ages of older than 3 years and 6 years or younger at ASD diagnosis) were divided into shorter (less than median) and longer (greater than or equal to median) TTD around each cohort median TTD calculated from the first documented ASD-related concern to the earliest ASD diagnosis, because TTD may vary by age at diagnosis. This exploratory analysis compared all-cause and ASD-related HCRU and costs during a 12-month period preceding ASD diagnosis among children with shorter vs longer TTD. RESULTS: 8,954 children met selection criteria: 4,205 aged 3 years or younger and 4,749 aged older than 3 years at diagnosis, with median TTD of 9.5 and 22.1 months, respectively. In the year preceding ASD diagnosis, children with longer TTD in both age cohorts experienced a greater number of all-cause and ASD-related health care visits compared with those with shorter TTD (mean and median number of office or home visits were approximately 1.5- and 2-fold greater in longer vs shorter TTD groups; P < 0.0001). The mean all-cause medical cost per child in the year preceding ASD diagnosis was approximately 2-fold higher for those with longer vs shorter TTD ($5,268 vs $2,525 in the younger and $5,570 vs $2,265 in the older cohort; P < 0.0001 for both). Mean ASD-related costs were also higher across age cohorts for those with longer vs shorter TTD ($2,355 vs $859 in the younger and $2,351 vs $1,144 in the older cohort; P < 0.0001 for both). CONCLUSIONS: In the year prior to diagnosis, children with longer TTD experienced more frequent health care visits and greater cost burden in their diagnostic journey compared with children with shorter TTD. Novel diagnostic approaches that could accelerate TTD may reduce costs and HCRU for commercially insured children. DISCLOSURES: This study was funded by Cognoa, Inc. Optum received funding from Cognoa to conduct this study. Dr Salomon is an employee and holds stock options of Cognoa, Inc. Dr Campbell was an employee of Cognoa, Inc., at the time this study was conducted. Dr Duhig was an employee of Cognoa, Inc., at the time the study was conducted and holds stock options. Dr Vu, Ms Kruse, Mr Gaur, and Ms Gupta are employees and/or stockholders of Optum. Dr Tibrewal was an employee of Optum at the time the research for this study was conducted. Dr Taraman is an employee and holds stock options of Cognoa, Inc., receives consulting fees from Cognito Therapeutics, volunteers as a board member of the American Academy of Pediatrics California and Orange County Chapter, is a paid advisor for MI10 LLC, and owns stock options of NTX, Inc., and HandzIn.

Challenging Case: Leveraging Community Partnerships to Address Barriers to Care for Students with Autism

CASE

Sam is an 11-year-old young boy with autism spectrum disorder (ASD), unspecified anxiety disorder, and attention-deficit/hyperactivity disorder, combined presentation. He was initially diagnosed with ASD at 6 years of age after evaluation by a developmental-behavioral (DB) pediatrician. He presents to the DB pediatrics clinic to reestablish care. He established care with psychiatry 5 months ago after his school referred him to a hospital-school-community telepartnership bridge program following statements of self-harm and numerous concerns with his behavior, including elopement.Sam currently receives special education support under the classifications of "Emotional Disturbance" and "Speech Impairment." His parents report significant challenges with having his medical diagnosis of autism recognized by the school, which has impeded him receiving educational support as a student with autism. This has resulted in Sam being penalized for challenging behaviors related to his neurodevelopmental disorder. He is not currently making meaningful progress in the school setting. Sam currently demonstrates avoidance, physical and verbal aggression, and difficulty adapting to change across settings. In addition to difficulties advocating for more individualized support at school, Sam has never received applied behavior analysis (ABA) therapy because of challenges obtaining insurance approval. There are no additional barriers to accessing care, such as language, geographic, or socioeconomic factors.Sam's visit to reestablish care with DB pediatrics consisted of an individual clinician evaluation model. The Childhood Autism Rating Scale, Second Edition, (CARS-2) and Vineland Adaptive Behavior Scales, Third Edition (Vineland-3), were administered, and Sam continued to meet DSM-5 criteria for ASD following re-evaluation. A new referral for ABA therapy was submitted. Shortly afterward, his family received an insurance denial letter specifying that additional developmental testing was needed before ABA therapy would be approved. His clinician called the insurance company to appeal this decision but was unsuccessful. Sam was then seen by the DB pediatrics embedded psychologist, who completed additional testing, including assessment of cognitive functioning, administration of the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), and autism-specific rating scales. This process led to further delays in access to ABA services. Throughout this process, the parents reported feeling helpless and frustrated given the barriers faced in receiving appropriate services. What are your next steps to advocate for supports through the school and insurance company?

Clinician Diagnostic Certainty and the Role of the Autism Diagnostic Observation Schedule in Autism Spectrum Disorder Diagnosis in Young Children

Importance

Autism spectrum disorder (ASD) affects 1 in 44 children. The Autism Diagnostic Observation Schedule (ADOS) is a semi-structured observation developed for use in research but is considered a component of gold standard clinical diagnosis. The ADOS adds time and cost to diagnostic assessments.

Objective

To evaluate consistency between clinical diagnosis (index ASD diagnosis) and diagnosis incorporating the ADOS (reference standard ASD diagnosis) and to examine clinician and child factors that predict consistency between index diagnoses and reference standard diagnoses.

Design, Setting, and Participants

This prospective diagnostic study was conducted between May 2019 and February 2020. Developmental-behavioral pediatricians (DBPs) made a diagnosis based on clinical assessment (index ASD diagnosis). The ADOS was then administered, after which the DBP made a second diagnosis (reference standard ASD diagnosis). DBPs self-reported diagnostic certainty at the time of the index diagnoses and reference standard diagnoses. The study took place at 8 sites (7 US and 1 European) that provided subspecialty assessments for children with concerns for ASD. Participants included children aged 18 months to 5 years, 11 months, without a prior ASD diagnosis, consecutively referred for possible ASD. Among 648 eligible children, 23 refused, 376 enrolled, and 349 completed the study. All 40 eligible DBPs participated.

Exposures

ADOS administered to all child participants.

Main Outcomes and Measures

Index diagnoses and reference standard diagnoses of ASD (yes/no).

Results

Among the 349 children (279 [79.7%] male; mean [SD] age, 39.9 [13.4] months), index diagnoses and reference standard diagnoses were consistent for 314 (90%) (ASD = 250; not ASD = 64) and changed for 35. Clinician diagnostic certainty was the most sensitive and specific predictor of diagnostic consistency (area under curve = 0.860; P < .001). In a multilevel logistic regression, no child or clinician factors improved prediction of diagnostic consistency based solely on clinician diagnostic certainty at time of index diagnosis.

Conclusions and Relevance

In this prospective diagnostic study, clinical diagnoses of ASD by DBPs with vs without the ADOS were consistent in 90.0% of cases. Clinician diagnostic certainty predicted consistency of index diagnoses and reference standard diagnoses. This study suggests that the ADOS is generally not required for diagnosis of ASD in young children by DBPs and that DBPs can identify children for whom the ADOS may be needed.

A data driven machine learning approach to differentiate between autism spectrum disorder and attention-deficit/hyperactivity disorder based on the best-practice diagnostic instruments for autism

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are two frequently co-occurring neurodevelopmental conditions that share certain symptomatology, including social difficulties. This presents practitioners with challenging (differential) diagnostic considerations, particularly in clinically more complex cases with co-occurring ASD and ADHD. Therefore, the primary aim of the current study was to apply a data-driven machine learning approach (support vector machine) to determine whether and which items from the best-practice clinical instruments for diagnosing ASD (ADOS, ADI-R) would best differentiate between four groups of individuals referred to specialized ASD clinics (i.e., ASD, ADHD, ASD + ADHD, ND = no diagnosis). We found that a subset of five features from both ADOS (clinical observation) and ADI-R (parental interview) reliably differentiated between ASD groups (ASD & ASD + ADHD) and non-ASD groups (ADHD & ND), and these features corresponded to the social-communication but also restrictive and repetitive behavior domains. In conclusion, the results of the current study support the idea that detecting ASD in individuals with suspected signs of the diagnosis, including those with co-occurring ADHD, is possible with considerably fewer items relative to the original ADOS/2 and ADI-R algorithms (i.e., 92% item reduction) while preserving relatively high diagnostic accuracy. Clinical implications and study limitations are discussed.

Responding to Autism in Low and Middle Income Countries (LMIC): What to Do and What Not to Do

Autism is a spectrum disorder that occurs globally with increasing numbers of children and adults being identified with this condition. Although rates are higher in more affluent nations, the bulk of people with autism reside in Low and Middle Income Countries (LMICs). However, most do not have access to timely and appropriate support. The types of services delivered in high income countries are often ill-suited to the needs and resources of LMICs. Rather alternative forms of provision need to be devised. In common with other public health initiatives, these should be family-focused and community based, with suitably qualified and experienced leaders who in turn train and supervise a cadre of knowledgeable support workers drawn from local communities and cultures. As well as providing personalized, home-based guidance to people with autism and to their primary carers, regular group-based advocacy and training activities are undertaken in partnership with available mainstream services such as schools and social services. The principles and operations of these new forms of services are described in this paper albeit with an acknowledgment of their limitations. In recent decades, the cost-effectiveness of these approaches have been demonstrated with other chronic illnesses and disabling conditions in LMICs but their extension to autism has barely begun. More affluent countries are being forced to adopt similar strategies in response to the increased numbers of people identified with autism. A transformation in research strategies is essential to building better international support for persons with autism.

The utility of the autism-spectrum quotient to screen for autism spectrum disorder in adults with attention deficit/hyperactivity disorder

The co-occurrence of attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) has been reported to be highly prevalent in adults. However, very few studies have assessed the usefulness of screening instruments to detect this co-occurrence, particularly when screening for ASD in the context of ADHD. Our study aimed at assessing the utility of the autism-spectrum quotient (AQ) as a screening tool of ASD in a sample of 153 adults referred for ADHD assessment. Our results showed that the AQ is of limited use in this context as its positive predictive value was low (47%). Particularly, the more severe the attentional deficits the more likely individuals with ADHD were to be misclassified as having a co-occurring ASD based on the AQ. However, the "imagination" subscale of the AQ was able to discriminate those who met ASD criteria from those who did not, suggesting that targeting imagination impairments might be useful when assessing for the ADHD+ASD co-occurrence in clinical settings.

Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder

Autism spectrum disorder (ASD) can be reliably diagnosed at 18 months, yet significant diagnostic delays persist in the United States. This double-blinded, multi-site, prospective, active comparator cohort study tested the accuracy of an artificial intelligence-based Software as a Medical Device designed to aid primary care healthcare providers (HCPs) in diagnosing ASD. The Device combines behavioral features from three distinct inputs (a caregiver questionnaire, analysis of two short home videos, and an HCP questionnaire) in a gradient boosted decision tree machine learning algorithm to produce either an ASD positive, ASD negative, or indeterminate output. This study compared Device outputs to diagnostic agreement by two or more independent specialists in a cohort of 18-72-month-olds with developmental delay concerns (425 study completers, 36% female, 29% ASD prevalence). Device output PPV for all study completers was 80.8% (95% confidence intervals (CI), 70.3%-88.8%) and NPV was 98.3% (90.6%-100%). For the 31.8% of participants who received a determinate output (ASD positive or negative) Device sensitivity was 98.4% (91.6%-100%) and specificity was 78.9% (67.6%-87.7%). The Device's indeterminate output acts as a risk control measure when inputs are insufficiently granular to make a determinate recommendation with confidence. If this risk control measure were removed, the sensitivity for all study completers would fall to 51.6% (63/122) (95% CI 42.4%, 60.8%), and specificity would fall to 18.5% (56/303) (95% CI 14.3%, 23.3%). Among participants for whom the Device abstained from providing a result, specialists identified that 91% had one or more complex neurodevelopmental disorders. No significant differences in Device performance were found across participants' sex, race/ethnicity, income, or education level. For nearly a third of this primary care sample, the Device enabled timely diagnostic evaluation with a high degree of accuracy. The Device shows promise to significantly increase the number of children able to be diagnosed with ASD in a primary care setting, potentially facilitating earlier intervention and more efficient use of specialist resources.

The Psychometric Properties of the Gilliam Autism Rating Scale (GARS-3) with Kurdish Samples of Children with Developmental Disabilities

There is marked variation internationally in the prevalence of children identified as having autism spectrum disorders (ASD). In part, this may reflect a shortage of screening tools for the early identification of children with ASD in many countries. This study aimed to evaluate the Kurdish translation of the Gilliam autism rating scale-third edition (GARS-3), a scale commonly used in Western countries that evaluates six domains related to the ASD definition from the Diagnostic and Statistical Manual of Mental Disorders (DSM) 5, notably Restricted/Repetitive Behavior, deficits in Social interaction and Social Communication, as well as differences in Cognitive Style, Maladaptive Speech, and Emotional Response. GARS-3 assessments were completed through interviews with parents of 735 children, 442 (53%) of whom were diagnosed with ASD. 165 (22%) with an intellectual disability, 49 (7%) with communication disorders, and 133 (18%) typically developing children. The reliability, construct, and the predictive validity of the scale was assessed, and the scores suggestive of a child having ASD were identified. The factor structure was broadly replicated, especially on items relating to social interaction and social communication. The cutoffs for the total scores that were indicative of possible ASD had a high degree of specificity and sensitivity in distinguishing children with ASD from typically developing peers. Some children with I.D. and communication disorders may also score above the threshold, and further assessments should be sought to confirm the presence of autistic traits. Although GARS-3 could be recommended for use in Kurdistan and possibly similar cultures, further prospective research is needed to confirm a diagnosis of assessment with children who score above and below the cutoff scores identified in this study. Moreover, the development of normative data drawn from Kurdish samples of children would be advantageous, although ambitious, given the lack of diagnostic services in many low- and middle-income countries.

Feasibility and impact of integrating an artificial intelligence-based autism spectrum disorder diagnosis aid into the primary care ECHO Autism STAT Model: protocol for a prospective observational study (Preprint)

Background

The Extension for Community Health Outcomes (ECHO) Autism Program trains clinicians to screen, diagnose, and care for children with autism spectrum disorder (ASD) in primary care settings. This study will assess the feasibility and impact of integrating an artificial intelligence (AI)–based ASD diagnosis aid (the device) into the existing ECHO Autism Screening Tool for Autism in Toddlers and Young Children (STAT) diagnosis model. The prescription-only Software as a Medical Device, designed for use in children aged 18 to 72 months at risk for developmental delay, produces ASD diagnostic recommendations after analyzing behavioral features from 3 distinct inputs: a caregiver questionnaire, 2 short home videos analyzed by trained video analysts, and a health care provider questionnaire. The device is not a stand-alone diagnostic and should be used in conjunction with clinical judgment.

Objective

This study aims to assess the feasibility and impact of integrating an AI-based ASD diagnosis aid into the ECHO Autism STAT diagnosis model. The time from initial ECHO Autism clinician concern to ASD diagnosis is the primary end point. Secondary end points include the time from initial caregiver concern to ASD diagnosis, time from diagnosis to treatment initiation, and clinician and caregiver experience of device use as part of the ASD diagnostic journey.

Methods

Research participants for this prospective observational study will be patients suspected of having ASD (aged 18-72 months) and their caregivers and up to 15 trained ECHO Autism clinicians recruited by the ECHO Autism Communities research team from across rural and suburban areas of the United States. Clinicians will provide routine clinical care and conduct best practice ECHO Autism diagnostic evaluations in addition to prescribing the device. Outcome data will be collected via a combination of electronic questionnaires, reviews of standard clinical care records, and analysis of device outputs. The expected study duration is no more than 12 months. The study was approved by the institutional review board of the University of Missouri-Columbia (institutional review board–assigned project number 2075722).

Results

Participant recruitment began in April 2022. As of June 2022, a total of 41 participants have been enrolled.

Conclusions

This prospective observational study will be the first to evaluate the use of a novel AI-based ASD diagnosis aid as part of a real-world primary care diagnostic pathway. If device integration into primary care proves feasible and efficacious, prolonged delays between the first ASD concern and eventual diagnosis may be reduced. Streamlining primary care ASD diagnosis could potentially reduce the strain on specialty services and allow a greater proportion of children to commence early intervention during a critical neurodevelopmental window.

Trial Registration

ClinicalTrials.gov NCT05223374; https://clinicaltrials.gov/ct2/show/NCT05223374

International Registered Report Identifier (IRRID)

PRR1-10.2196/37576

Visual working memory performance is intact across development in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with atypical visual processing and deficits in working memory (WM). Visual WM performance typically improves between childhood and adulthood, but such improvement may be atypical in ASD. To better understand how visual WM develops, we used a well-established change detection task across multiple visual features. We examined visual WM for color, shape, and pattern in children, adolescents, and adults with and without ASD. VWM capacity and performance for all visual features improved across age similarly for both the TD and ASD groups. While performance was better on set size 4 trials than set size 8 trials for color, shape, and no change trials, such an effect was not evident for pattern change trials. Overall, the present findings suggest that VWM for different visual features may be intact across development in ASD. The ability to hold multiple objects in mind (WM) improves across typical development, but it remains unclear whether such improvement occurs in ASD. We found that developmental improvements in WM for different types of object details (e.g., color, shape, and pattern) is generally similar for both ASD and typical development.

Suspected feigning of autism in adults: a clinician survey, indications and proposed guidelines

Purpose

This paper aims to provide a discussion and summary of a clinician survey exploring the experiences of suspected feigned autism.

Design/methodology/approach

This study is an online survey targeting a range of autism professionals, with varying levels of experience, working in different clinical settings.

Findings

Approximately half of the professionals who completed the survey reported experiencing situations of suspected feigning of adult autism across a range of clinical contexts and with various motivations. In terms of best indications of potential feigning, most clinicians reported “textbook” self-descriptions of problem behaviours with vague examples, as well as inconsistent presenting problems and mismatch with any known developmental history. Approximately half of clinicians expressed the view that autism was more difficult to feign than a psychiatric disorder and had experienced situations involving differences in professional opinion as to an individual autism diagnosis.

Research limitations/implications

The survey is limited by a potential sample bias and no information regarding the clinical characteristics of those suspected to have feigned autism. However, these initial findings offer further questions for future research to pursue.

Originality/value

As an initial examination of practicing clinicians’ experiences of suspected feigned autism, the survey highlights the complexities of an autism diagnosis and suggests feigning is a potential clinical scenario. Some guidance as to when to suspect possible feigned autism is also offered, as well as a provisional assessment protocol.

Survey of training experiences and clinical practice in assessment for autism spectrum disorder by neuropsychologists

OBJECTIVE

The primary purpose of this study is to better understand current practices in the assessment of autism spectrum disorder (ASD) by neuropsychologists.

METHODS

A 21-item survey regarding ASD assessment beliefs and practices was sent via email through neuropsychology listservs. The survey was accessed by 445 licensed psychologists who identified as neuropsychologists. A total of 367 surveys were deemed usable for data analysis. Descriptive statistics were used to characterize the full sample. Exploratory analyses were conducted between groups of interest, including primary population served (pediatric, adult, or lifespan), primary practice setting (medical center vs. private practice) and years in practice (< 5 years, 5 to 14 years, or 15+ years).

RESULTS

Respondents were well-distributed across age range, years in practice, primary practice setting, and primary practice location. Almost all respondents (most of whom self-identified as pediatric-focused clinicians) believe that neuropsychologists should be able to competently rule in or out ASD and most received training in ASD assessment. Approximately 40% of respondents endorsed wanting more training in ASD assessment to increase their competence and confidence in making this differential diagnosis. Minimal differences in ASD beliefs and assessment practices were seen across years of practice or primary practice setting. Pediatric and lifespan clinicians had similar experience with ASD assessment practices, and both generally differed from adult clinicians.

CONCLUSIONS

Our findings suggest many respondents desire further specialty ASD training for neuropsychologists. Additionally, the large majority of respondents indicated that future neuropsychologists should receive training in ASD assessment during graduate school, internship and/or post-doctoral fellowship.