The objectivity of the Autism Diagnostic Observation Schedule (ADOS) in naturalistic clinical settings

Objective Measurement of Social Gaze and Smile Behaviors in Children with Suspected Autism Spectrum Disorder During Administration of the Autism Diagnostic Observation Schedule, 2nd Edition

Best practice for the assessment of autism spectrum disorder (ASD) symptom severity relies on clinician ratings of the Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2), but the association of these ratings with objective measures of children's social gaze and smiling is unknown. Sixty-six preschool-age children (49 boys, M = 39.97 months, SD = 10.58) with suspected ASD (61 confirmed ASD) were administered the ADOS-2 and provided social affect calibrated severity scores (SA CSS). Children's social gaze and smiling during the ADOS-2, captured with a camera contained in eyeglasses worn by the examiner and parent, were obtained via a computer vision processing pipeline. Children who gazed more at their parents (p = .04) and whose gaze at their parents involved more smiling (p = .02) received lower social affect severity scores, indicating fewer social affect symptoms, adjusted R2 = .15, p = .003.

An Internal Consistency Reliability Study of the Catalyst Datafinch Applied Behavior Analysis Data Collection Application With Autistic Individuals

Introduction Many psychometric studies have scrutinized the dependability of different instruments for evaluating and treating autism using applied behavior analysis (ABA). However, there has been no exploration into the psychometric attributes of the Catalyst Datafinch Applied Behavior Analysis Data Collection Application, namely, internal consistency reliability measures. Materials and methods  Four datasets were extracted (n=100, 98, 103, and 62) from published studies at The Oxford Center, Brighton, MI, ranging from March 19, 2023, through January 8, 2024, using Catalyst Datafinch as the data collection tool. All data were gathered by Board Certified Behavior Analysts (BCBAs) and behavioral technicians and designed to replicate how practitioners collect traditional paper and pencil data. SPSS Statistics (v. 29.0) computed internal consistency reliability measures, including Cronbach's alpha, inter-item, split-half, and interclass correlation coefficients. Results  Dataset #1: Cronbach's alpha was 0.916 with seven items, indicating excellent reliability. Cronbach's split-half reliability for Part 1 was 0.777, indicating good reliability, and for Part 2 was 0.972, indicating excellent reliability. Guttman split-half coefficient was 0.817, indicating good reliability. Inter-item correlation coefficients ranged from 0.474 to 0.970. The average measures interclass correlation (ICC) was 0.916, indicating excellent reliability. Single measures (ICC) reliability was 0.609, indicating acceptable reliability. Dataset #2: Cronbach's alpha was 0.954 with three items, indicating excellent reliability. Cronbach's split-half reliability for Part 1 was 0.912, indicating excellent reliability, and for Part 2 was 0.975, indicating excellent reliability. Guttman split-half coefficient was 0.917, indicating excellent reliability. Inter-item correlation coefficients ranged from 0.827 to 0.977. Average measures (ICC) was 0.954, indicating excellent reliability. Single measures (ICC) reliability was 0.875, indicating good reliability. Dataset #3: Cronbach's alpha was 0.974 with three items, indicating excellent reliability. Cronbach's split-half reliability for Part 1 was 0.978, indicating excellent reliability. Split-half reliability for Part 2 was 0.970, indicating excellent reliability. Guttman split-half coefficient was 0.935, indicating excellent reliability. Inter-item correlation coefficients ranged from 0.931 to 0.972. The average measures (ICC) was 0.974, indicating excellent reliability. Single measures (ICC) reliability was 0.926, indicating excellent reliability. Dataset #4: Cronbach's alpha was 0.980 with 12 items, indicating excellent reliability. Cronbach's split-half reliability for Part 1 was 0.973, indicating excellent reliability. Split-half reliability for Part 2 was 0.996, indicating excellent reliability. Guttman split-half coefficient was 0.838, indicating good reliability. Inter-item correlation coefficients ranged from 0.692 to 0.999. The average measures (ICC) was 0.980, indicating excellent reliability. Single measures (ICC) reliability was 0.804, indicating good reliability. Conclusions These results suggest that Catalyst Datafinch demonstrates high internal consistency reliability when used with individuals with autism. This indicates that the application is reliable for collecting and analyzing behavioral data in this population. The ratings ranged from good to excellent, indicating a high consistency in the measurements.

Telehealth assessment of autism in preschoolers using the TELE-ASD-PEDS: A pilot clinical investigation

PURPOSE

Appropriate early intervention is beneficial but dependent on accurate and timely diagnoses. This has been affected by long waiting lists for face-to-face clinical services, in part due to pandemic lockdowns, with telehealth introduced in many services to continue clinical services. This pilot clinical study investigated the feasibility of integrating a specially-designed telepractice autism assessment tool into a tertiary diagnostic service.

METHOD

Eighteen boys (2;4-5;1) participated in the study. Assessment was undertaken as per standard practice (parent interview, questionnaires, review of reports), with an additional telepractice assessment, included in place of face-to-face assessment, to provide clinicians with an observation of the children's communication, behaviours, and interests. Ten parents provided feedback via semi-structured interviews.

RESULT

The TELE-ASD-PEDS was a feasible assessment tool in terms of administration, clinical experience, and information gained through the assessment process. Parents reported mostly positive experiences of the TELE-ASD-PEDS and made suggestions for improvements for future use of this tool.

CONCLUSION

It is possible to obtain useful information about a child's autism-specific behaviours using the activities in the TELE-ASD-PEDS. This information can be combined with clinical history from parents using the DSM-5 framework to provide a gold standard assessment for autism.

Symptom similarities and differences in social interaction between autistic children and adolescents with and without ADHD

Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) are two often co-occurring neurodevelopmental conditions. Nevertheless, there is limited research about symptom differences between ASD and ASD + ADHD groups. This study examined differences in social interaction and communication between children and adolescents with ASD and with ASD + ADHD. A total of 112 participants were identified from two clinical trials. Fifty-six children and adolescents with ASD aged 8–17 years were matched for age, gender and general intelligence quotient with fifty-six children and adolescents with ASD + ADHD. Group differences in scores on the Autism Diagnostic Observation Schedule were analysed. Our results showed that participants with ASD and with ASD + ADHD had similar profiles of social communication interaction challenges and restricted behaviour. However, items assessing gestures: Conventional, Instrumental or Informational Gestures and Empathic or Emotional gestures showed significant differences between the groups suggesting that the ASD + ADHD group used descriptive gestures to communicate to a greater extent than the ASD group. These findings suggest that children and adolescents in both groups have similar difficulties in social communication and interaction with observed differences in the use of gestures. Possible reasons and implications for the differences in the use of gestures are discussed.

Individual differences in computational psychiatry: a review of current challenges

Bringing precision to the understanding and treatment of mental disorders requires instruments for studying clinically relevant individual differences. One promising approach is the development of computational assays: integrating computational models with cognitive tasks to infer latent patient-specific disease processes in brain computations. While recent years have seen many methodological advancements in computational modelling and many cross-sectional patient studies, much less attention has been paid to basic psychometric properties (reliability and construct validity) of the computational measures provided by the assays. In this review, we assess the extent of this issue by examining emerging empirical evidence. We find that many computational measures suffer from poor psychometric properties, which poses a risk of invalidating previous findings and undermining ongoing research efforts using computational assays to study individual (and even group) differences. We provide recommendations for how to address these problems and, crucially, embed them within a broader perspective on key developments that are needed for translating computational assays to clinical practice.

The relationship between camouflaging and mental health in autistic children and adolescents

Camouflaging involves the masking of autistic traits in social situations. While camouflaging may function as a potential barrier to the early diagnosis of autism, minimal research into camouflaging in autistic young people has been conducted. It is also important to evaluate the impact of camouflaging on the mental health of autistic children and adolescents. This study evaluated camouflaging in a sample of 359 female and 374 male autistic children and adolescents (4-17 years, 48.9% females). Findings indicated that camouflaging was a significant predictor of internalizing (i.e., anxiety, depression, somatic complaints) symptoms, when controlling for age, gender, and IQ. We also found evidence for some gender differences in camouflaging. Parents endorsed more autistic traits for females compared with males, whereas there were no differences in autistic traits across sex in the clinician-administered assessment. There was also evidence for a relationship between age and camouflaging, with adolescents showing a larger discrepancy between parent and clinician reported autistic traits. This has implications for clinical assessment and future research and is important for understanding how best to support the mental health of autistic children and adolescents.

Agreement between parents' and clinical researchers' ratings of behavioral problems in children with fragile X syndrome and chromosome 15 imprinting disorders

BACKGROUND

Despite the increasing number of clinical trials involving children with neurodevelopmental disorders, appropriate and objective outcome measures for behavioral symptoms are still required.

AIM

This study assessed the agreement between parents' and clinical researchers' ratings of behavioral problem severity in children with fragile X syndrome (FXS) and chromosome 15 imprinting disorders.

METHODS AND PROCEDURES

The cohort comprised 123 children (64% males), aged 3-17 years, with FXS (n = 79), Prader-Willi (PWS; n = 19), Angelman (AS; n = 15), and Chromosome 15q duplication (n = 10) syndromes. Specific items from the Autism Diagnostic Observation Schedule-Second Edition and Aberrant Behavior Checklist-Community Edition mapping to corresponding behavioral domains were selected ad-hoc, to assess behavioral problems.

OUTCOMES AND RESULTS

Inter-rater agreement for the cohort was slight for self-injury (Intraclass Correlation Coefficient (ICC) = 0.12), fair for tantrums/aggression (0.24) and mannerisms/stereotypies (0.25), and moderate for hyperactivity (0.48). When stratified by diagnosis, ICC ranged from poor (0; self-injury, AS and PWS) to substantial (0.48; hyperactivity, females with FXS).

CONCLUSIONS AND IMPLICATIONS

The high level of inter-rater disagreement across most domains suggests that parents' and researchers' assessments led to discrepant appraisal of behavioral problem severity. These findings have implications for treatment targets and outcome measure selection in clinical trials, supporting a multi-informant approach.

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.

Detecting autism from picture book narratives using deep neural utterance embeddings

BACKGROUND

Deficits in the ability to use language in social contexts, including storytelling skills, are observed across the autism spectrum. Development in machine-learning approaches may contribute to clinical psychology and psychiatry, given its potential to support decisions concerning the diagnosis and treatment of psychiatric conditions and disorders.

AIMS

To evaluate the usefulness of deep neural networks for detecting autism spectrum disorder (ASD) from textual utterances, specifically from narrations produced by individuals with ASD.

METHODS & PROCEDURES

We examined two text encoders: Embeddings from Language Models (ELMo) and Universal Sentence Encoder (USE), and three classification algorithms: XGBoost, support vector machines, and dense neural network layer. We aimed to classify 25 participants with ASD and 25 participants with typical development (TD) based on their narrations produced during the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) picture book task. The results of computational approaches were compared with the results of standardized testing and classifications made by two psychiatrists (raters). The raters were asked to read utterances produced by a participant (without an examiner's statements and additional information) and assign a participant to one of the two groups: ASD or with typical development (TD).

OUTCOMES & RESULTS

The computer-based models had higher sensitivity, specificity, positive predictive values and negative predictive values than the raters, and lower than the two standardized instruments: ADOS-2 and Social Communication Questionnaire (SCQ).

CONCLUSIONS & IMPLICATIONS

Our findings lay the groundwork for future studies involving deep neural network-based text representation models as tools for augmenting the ASD diagnosis or screening. Both ELMo and USE text encoders provided promising specificities, sensitivities, positive predictive values and negative predictive values. Our results indicate the usefulness of page-level embeddings for utterance representation in ADOS-2 picture book task.

WHAT THIS PAPER ADDS

What is already known on this subject Deficits in the use of language in social contexts, and narrative ability in particular, are observed across the autism spectrum. Most research on narrative skills has applied hand-coding methods. Hitherto, machine-learning methods were used mostly for image recognition problems and data from screening questionnaires for ASD classification. Detection of mental and developmental disorders from textual input is an emerging field for machine and deep-learning methods. What this paper adds to existing knowledge This study explored the ability of several types of deep neural network-based text representation models to detect ASD. Both ELMo and USE provided the most promising values of specificity, sensitivity, positive predictive values and negative predictive values. What are the potential or actual clinical implications of this work? Competitive accuracy, repeatability, speed and ease of operation are all advantages of computerized methods. They allow for objective and quantitative assessment of narrative ability and complex language skills. Deep neural network-based text representation models could in the future support clinicians and augment the decision-making process related to ASD diagnosis, screening and intervention planning.

Autism Diagnostic Assessments With Children, Adolescents, and Adults Prior to and During the COVID-19 Pandemic: A Cross-Sectional Survey of Professionals

Background

Access to timely high quality autism diagnostic assessments has traditionally been patchy; many individuals wait months, if not years, for an appointment. The onset of the COVID-19 pandemic has likely impacted autism diagnostic services. This study investigated professionals' experiences of, and thoughts about: (1) how autism diagnostic assessments were conducted before the pandemic; (2) adaptations to service provision because of the pandemic; and (3) challenges, risks, advantages and opportunities associated with autism assessments conducted via online platforms (telehealth).

Method

Fifty-two professionals, based in different autism diagnostic services and working with children, adolescents and/or adults, completed an online cross-sectional survey in August and September 2020. This comprised demographic questions (about professionals' roles and experiences), and closed and open questions about service provision and telehealth autism assessments.

Results

There was substantial variation in how autism assessments were conducted prior to and during the pandemic; for example, in relation to the number of professionals involved in the assessment and types of structured, semi-structured and unstructured measures used to conduct this. Fifty-two percent of participants (n = 27) reported some service disruption (e.g., full closure, substantial reduction in provision, and/or pausing of in person appointments). Waiting times for assessment had become longer for 58% of services (n = 30), due to pandemic-related disruption. Six themes emerged from thematic analysis of open responses: (1) the autism diagnostic pathway, pre-pandemic; (2) initial impact of the pandemic on service delivery; (3) conducting autism assessments during the pandemic; (4) working remotely; (5) improving service design and delivery; and (6) post-diagnostic support. Views about the accessibility, validity, and reliability of conducting telehealth autism assessments were polarized. Some participants considered this efficient, flexible, and adequate; others viewed this as unethical and inappropriate. What constitutes good practice in telehealth autism assessments remains unclear, but there is a general openness to using this method (potentially in a hybrid telehealth-in person model), provided rigor and standardization are enhanced.

Conclusions

The pandemic has potentially compounded existing bottlenecks to the autism diagnostic pathway. Future research should seek to improve timeliness, standardization, accessibility and robustness of this pathway, and the validity and reliability of telehealth autism assessments.

Objective measurement of vocalizations in the assessment of autism spectrum disorder symptoms in preschool age children

Assessment of autism spectrum disorder (ASD) relies on expert clinician observation and judgment, but objective measurement tools have the potential to provide additional information on ASD symptom severity. Diagnostic evaluations for ASD typically include the autism diagnostic observation schedule (ADOS-2), a semi-structured assessment composed of a series of social presses. The current study examined associations between concurrent objective features of child vocalizations during the ADOS-2 and examiner-rated autism symptom severity. The sample included 66 children (49 male; M = 40 months, SD = 10.58) evaluated in a university-based clinic, 61 of whom received an ASD diagnosis. Research reliable administration of the ADOS-2 provided social affect (SA) and restricted and repetitive behavior (RRB) calibrated severity scores (CSS). Audio was recorded from examiner-worn eyeglasses during the ADOS-2 and child and adult speech were differentiated with LENA SP Hub. PRAAT was used to ascertain acoustic features of the audio signal, specifically the mean fundamental vocal frequency (F0) of LENA-identified child speech-like vocalizations (those with phonemic content), child cry vocalizations, and adult speech. Sphinx-4 was employed to estimate child and adult phonological features indexed by the average consonant and vowel count per vocalization. More than a quarter of the variance in ADOS-2 RRB CSS was predicted by the combination of child phoneme count per vocalization and child vocalization F0. Findings indicate that both acoustic and phonological features of child vocalizations are associated with expert clinician ratings of autism symptom severity. LAY SUMMARY: Determination of the severity of autism spectrum disorder is based in part on expert (but subjective) clinician observations during the ADOS-2. Two characteristics of child vocalizations-a smaller number of speech-like sounds per vocalization and higher pitched vocalizations (including cries)-were associated with greater autism symptom severity. The results suggest that objectively ascertained characteristics of children's vocalizations capture variance in children's restricted and repetitive behaviors that are reflected in clinician severity indices.

Analysis of Race and Sex Bias in the Autism Diagnostic Observation Schedule (ADOS-2)

IMPORTANCE

There are long-standing disparities in the prevalence of autism spectrum disorder (ASD) across race and sex. Surprisingly, few studies have examined whether these disparities arise partially out of systematic biases in the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), the reference standard measure of ASD.

OBJECTIVE

To examine differential item functioning (DIF) of ADOS-2 items across sex and race.

DESIGN, SETTING, AND PARTICIPANTS

This is a cross-sectional study of children who were evaluated for ASD between 2014 and 2020 at a specialty outpatient clinic located in the Mid-Atlantic region of the US. Data were analyzed from July 2021 to February 2022.

EXPOSURES

Child race (Black/African American vs White) and sex (female vs male).

MAIN OUTCOMES AND MEASURES

Item-level biases across ADOS-2 harmonized algorithm items, including social affect (SA; 10 items) and repetitive/restricted behaviors (RRBs; 4 items), were evaluated across 3 modules. Measurement bias was identified by examining DIF and differential test functioning (DTF), within a graded response, item response theory framework. Statistical significance was determined by a likelihood ratio χ2 test, and a series of metrics was used to examine the magnitude of DIF and DTF.

RESULTS

A total of 6269 children (mean [SD] age, 6.77 [3.27] years; 1619 Black/African American [25.9%], 3151 White [50.3%], and 4970 male [79.4%]), were included in this study. Overall, 16 of 140 ADOS-2 diagnostic items (11%) had a significant DIF. For race, 8 items had a significant DIF, 6 of which involved SA. No single item showed DIF consistently across all modules. Most items with DIF had greater difficulty and poorer discrimination in Black/African American children compared with White children. For sex, 5 items showed significant DIF. DIF was split across SA and RRB. However, hand mannerisms evidenced DIF across all 5 algorithms, with generally greater difficulty. The magnitude of DIF was only moderate to large for 2 items: hand mannerisms (among female children) and repetitive interests (among Black/African American children). The overall estimated effect of DIF on total DTF was not large.

CONCLUSIONS AND RELEVANCE

These findings suggest that the ADOS-2 does not have widespread systematic measurement bias across race or sex. However, the findings raise some concerns around underdetection that warrant further research.

Age of Diagnosis for Co-occurring Autism and Attention Deficit Hyperactivity Disorder During Childhood and Adolescence: a Systematic Review

Early identification and intervention are recognised as important elements of the clinical pathway for autism spectrum disorder (ASD). Children with ASD and attention deficit hyperactivity disorder (ADHD) may be diagnosed at a different age than children who only have one of these diagnoses. This systematic review aimed to identify the age at which children were diagnosed with both ASD and ADHD. Of the 9552 articles screened, 12 were included in the review. The findings suggest that ASD is typically diagnosed later when ADHD is present, and ADHD is typically diagnosed earlier when ASD is present. Further research is needed to understand the factors impacting a delayed ASD diagnosis and an earlier ADHD diagnosis when the two conditions co-occur.

Diagnostic Utility of the Gilliam Autism Rating Scales-3rd Edition Parent Report in Clinically Referred Children

There is limited research regarding the Gilliam Autism Rating Scales-3rd Edition (GARS-3) despite its extensive use. A comprehensive diagnostic evaluation, including the Autism Diagnostic Observation Schedule-2nd Edition (ADOS-2) was provided to 186 clinically referred children suspected of autism ([Formula: see text] age = 8.98; Autism [AUT] n = 87; Not Autism [NOT] n = 99). Mean difference analyses, Logistic Regressions, and ROC analyses were non-significant for both Autism Index scores. The author-suggested cutoff score of 70 correctly classified approximately 47% of participants, with false positive rates = 82.83-87.88%. ADOS-2 correlations were significantly lower vis-à-vis the standardization sample. The Social Interaction subscale demonstrated weak, marginal results, and sensitivity/specificity could not be optimized. In its current form, the GARS-3 does not demonstrate adequate criterion validity for use in assessment of complex community samples.

CLEAR Autism Diagnostic Evaluation (CADE): Evaluation of Reliability and Validity

Recent surveillance efforts indicate that 1 in 54 American children meet the criteria for Autism Spectrum Disorder (ASD), making it the fastest growing neurodevelopmental disorder in the U.S. Despite evidence that ASD can be reliably diagnosed as early as 24 months, the median age at ASD diagnosis in 2016 in the U.S. was 51 months. The CLEAR Autism Diagnostic Evaluation (CADE; Willard & Kroncke, 2019), was developed in response to the need to improve, shorten, and standardize the clinical ASD evaluation process. The CADE is a 33-item rating scale designed to be completed by caregivers and clinicians. The current study was conducted to examine the reliability and validity of the CADE using a sample of 191 individuals who received a private evaluation for ASD. Using the client's evaluation records, clinicians completed the CADE items. The coefficient alpha was .94, which indicates that the items form a scale that has high internal consistency. The CADE total scores were highly correlated with ADOS scores, with r values ranging from .52-.86, and discriminated between those participants with a diagnosis of ASD and those without (p < .001). Receiver operator characteristic (ROC) curve analyses indicated excellent diagnostic accuracy of the CADE total score (ROC area under the curve = .998). Results suggest that the CADE can be used as an efficient and accurate means of evaluating ASD. Limitations and implications for use of the CADE are discussed.

Brief Report: Emotional and Behavioral Problems Among Young Children with ASD: An Exploratory Study of ADOS E-Codes and Child Characteristics

Emotional and behavioral problems (EBPs), such as anxiety, overactivity, and aggression, can influence the diagnosis of autism spectrum disorder (ASD). The gold standard diagnostic tool for ASD, the Autism Diagnostic Observation Schedule-Second Edition, includes three items ("E-codes") for EBPs that are frequently associated with ASD. Few empirical investigations have explored the use of E-codes. This study examined the relationship between E-codes and child characteristics (e.g., cognitive abilities, ASD symptom severity) in a sample of young children with ASD (N = 233). Findings indicated that E-codes positively correlated with ASD symptom severity and negatively associated with IQ. Symptom severity also significantly accounted for the variance in EBPs. Implications for ASD assessment as well as future research are discussed.

Is the Combination of ADOS and ADI-R Necessary to Classify ASD? Rethinking the "Gold Standard" in Diagnosing ASD

Diagnosing autism spectrum disorder (ASD) requires extensive clinical expertise and training as well as a focus on differential diagnoses. The diagnostic process is particularly complex given symptom overlap with other mental disorders and high rates of co-occurring physical and mental health concerns. The aim of this study was to conduct a data-driven selection of the most relevant diagnostic information collected from a behavior observation and an anamnestic interview in two clinical samples of children/younger adolescents and adolescents/adults with suspected ASD. Via random forests, the present study discovered patterns of symptoms in the diagnostic data of 2310 participants (46% ASD, 54% non-ASD, age range 4-72 years) using data from the combined Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview-Revised (ADI-R) and ADOS data alone. Classifiers built on reduced subsets of diagnostic features yield satisfactory sensitivity and specificity values. For adolescents/adults specificity values were lower compared to those for children/younger adolescents. The models including ADOS and ADI-R data were mainly built on ADOS items and in the adolescent/adult sample the classifier including only ADOS items performed even better than the classifier including information from both instruments. Results suggest that reduced subsets of ADOS and ADI-R items may suffice to effectively differentiate ASD from other mental disorders. The imbalance of ADOS and ADI-R items included in the models leads to the assumption that, particularly in adolescents and adults, the ADI-R may play a lesser role than current behavior observations.

First Psychometric Properties of the Dutch Interview for Diagnostic Assessment of Autism Spectrum Disorder in Adult Males Without Intellectual Disability

For autism spectrum disorder (ASD) in adults there are several diagnostic instruments available with a need for consideration of the psychometric properties. This study aimed to conduct a first psychometric evaluation of a new diagnostic ASD instrument, the NIDA (Dutch Interview for Diagnostic assessment of ASD in adults) in 90 adult males without intellectual disability (age 18-65 years) in the Netherlands: 30 with ASD, 30 with a Personality Disorder and 30 nonpatient controls. The interrater agreement ranged from 0.79 to 1.00, the convergent validity including sensitivity and specificity ranged from 0.76 to 1.00, and we observed an adequate concurrent criterion-related validity. These promising findings can serve as foundation for future psychometric NIDA studies in a more diverse population. TRIAL REGISTRATION: The Netherlands National Trial Register NTR6391. Registered 04 May 2017.

The impact of atypical sensory processing on adaptive functioning within and beyond autism: The role of familial factors

LAY ABSTRACT

Individuals diagnosed with autism tend to process sensory information differently than individuals without autism, resulting for instance in increased sensitivity to sounds or smells. This leads to challenges in everyday life and may restrict the individual's daily functioning. How direct this link is, however, is currently unclear. We investigated this question in 289 twins of whom 60 were diagnosed with autism and further 61 were diagnosed with other neurodevelopmental disorders. We looked at the association between unusual sensory processing and adaptive skills, both across individuals and within-twin pairs, testing whether individuals with higher levels of atypical sensory processing showed reduced adaptive skills compared to their twins. Since twins share 50%-100% of their genes and part of their environment (e.g. family background), associations within-twin pairs are free from effects of these familial factors. We found that an increased sensitivity to, as well as the avoiding of, sensory input (hyper-responsiveness) was linked to reduced adaptive skills across individuals-but not within-twin pairs. We also found an association between the degree to which individuals seek for sensory input (sensation seeking) and reduced adaptive skills, but only in individuals diagnosed with autism. The results suggest that sensory hyper-responsiveness has negative effects on individuals' general ability to function, but that this link is influenced by familial factors and hence not direct. In addition, sensation seeking behaviors might have a negative impact on adaptive skills specifically in autistic individuals.

Assessment of Autism Spectrum Disorder in Deaf Adults with Intellectual Disability: Feasibility and Psychometric Properties of an Adapted Version of the Autism Diagnostic Observation Schedule (ADOS-2)

This study describes the adaptation of the autism diagnostic observation schedule (ADOS-2) to assess autism spectrum disorder (ASD) in adults with intellectual disability (ID) and hearing loss who communicate primarily visually. This adapted ADOS-2 was applied to residents of specialized therapeutic living communities (n = 56). The internal consistency of the adapted ADOS-2 was excellent for the Social Affect of modules 2 and 3 and acceptable for Restricted and Repetitive Behaviors subscale of module 2, but poor for module 3. Interrater reliability was comparable to standard ADOS-2 modules 1–3. Results suggest that autism symptoms of deaf adults with ID can be reliably identified by an adapted ADOS-2, provided adequate expertise in deafness, ID, ASD and proficiency in signed language by the administrator.

The utility of parent-report screening tools in differentiating autism versus attention-deficit/hyperactivity disorder in school-age children

LAY ABSTRACT

We tested the ability of a short, recently developed parent interview and two widely used parent-report questionnaires to discriminate school-age verbal children with autism spectrum disorder from those with attention-deficit/hyperactivity disorder without autism spectrum disorder (ADHD_w/oASD). These measures included the Autism Symptom Interview - School-Age, the Social Responsiveness Scale - 2nd Edition, and the Social Communication Questionnaire - Lifetime. The classification accuracy of all three parent screeners fell in the moderate range. Accuracy varied by instrument, and the Social Communication Questionnaire - Lifetime questionniare showed the highest accuracy. Children with autism spectrum disorder who were incorrectly classified by all parent screeners did not differ from those correctly classified in regard to demographics, intellectual abilities, nor in any specific clinical area beyond general parent concerns. These findings showed that there are valid screening options for assessing school-age verbal children with autism spectrum disorder versus ADHD_w/oASD. They also underscore the need to assess multiple sources of information for increased accuracy.

The Toddler Autism Symptom Inventory: Use in diagnostic evaluations of toddlers

LAY ABSTRACT

Determining whether a young child has an autism spectrum disorder requires direct observation of the child and caregiver report of the child's everyday behaviors. There are few interviews for parents that are specifically designed for children under 3 years of age. The Toddler Autism Symptom Inventory is a new interview that asks caregivers of children age 12-36 months about symptoms of possible autism spectrum disorder. The Toddler Autism Symptom Inventory uses a cutoff score to indicate likelihood for autism spectrum disorder; this cutoff score appears to accurately identify most children who are diagnosed with autism spectrum disorder without identifying too many who do not have autism spectrum disorder. The Toddler Autism Symptom Inventory interview can help clinicians to determine whether a young child shows symptoms suggestive of an autism spectrum disorder.

Cerebrospinal fluid and serum protein markers in autism: A co-twin study

No robust biomarkers have yet been identified for autism spectrum disorder (ASD) or autistic traits. Familial factors likely influence biomarkers such as protein concentrations. Comparing twins with ASD or high autistic traits to the less affected co-twin allows estimating the impact of familial confounding. We measured 203 proteins in cerebrospinal fluid (n = 86) and serum (n = 127) in twins (mean age 14.2 years, 44.9% females) enriched for ASD and other neurodevelopmental conditions. Autistic traits were assessed by using the parent-report version of the Social Responsiveness Scale-2. In cerebrospinal fluid, autistic traits correlated negatively with three proteins and positively with one. In serum, autistic traits correlated positively with 15 and negatively with one. Also in serum, six were positively-and one negatively-associated with ASD. A pathway analysis of these proteins revealed immune system enrichment. In within twin pair analyses, autistic traits were associated with serum B-cell activating factor (BAFF) only, whereas Cystatin B (CSTB) remained significantly associated with ASD. These associations did not remain significant when only considering monozygotic twins. For the remainder, the within-pair analysis indicated familial confounding, including shared environment and genes, influencing both autism and protein levels. Our findings indicate proteins involved in immunity as putative biomarkers of autistic traits and ASD with partial genetic confounding. Although some results are in line with previous studies in general, further studies are needed for replication.

A clinical and cost-effectiveness trial of a parent group intervention to manage challenging restricted and repetitive behaviours in young children with autism spectrum disorder: study protocol for a randomised controlled trial

BACKGROUND

Restricted and repetitive behaviours vary greatly across the autism spectrum, and although not all are problematic some can cause distress and interfere with learning and social opportunities. We have, alongside parents, developed a parent group based intervention for families of young children with autism, which aims to offer support to parents and carers; helping them to recognise, understand and learn how to respond to their child's challenging restricted repetitive behaviours.

METHODS

The study is a clinical and cost-effectiveness, multi-site randomised controlled trial of the Managing Repetitive Behaviours (MRB) parent group intervention versus a psychoeducation parent group Learning About Autism (LAA) (n = 250; 125 intervention/125 psychoeducation; ~ 83/site) for parents of young children aged 3-9 years 11 months with a diagnosis of autism. All analyses will be done under intention-to-treat principle. The primary outcome at 24 weeks will use generalised estimating equation (GEE) to compare proportion of children with improved RRB between the MRB group and the LAA group. The GEE model will account for the clustering of children by parent groups using exchangeable working correlation. All secondary outcomes will be analysed in a similar way using appropriate distribution and link function. The economic evaluation will be conducted from the perspective of both NHS costs and family access to local community services. A 'within trial' cost-effectiveness analysis with results reported as the incremental cost per additional child achieving at least the target improvement in CGI-I scale at 24 weeks.

DISCUSSION

This is an efficacy trial to investigate the clinical and cost-effectiveness of a parent group based intervention designed to help parents understand and manage their child's challenging RRB. If found to be effective, this intervention has the potential to improve the well-being of children and their families, reduce parental stress, greatly enhance community participation and potential for learning, and improve longer-term outcomes.

TRIAL REGISTRATION

Trial ID: ISRCTN15550611 Date registered: 07/08/2018. Sponsor and Monitor: Cumbria, Northumberland, Tyne and Wear NHS Foundation Trust R&D Manager Lyndsey Dixon, Address: St Nicholas Hospital, Jubliee Road, Gosforth, Newcastle upon Tyne NE3 3XT, lyndsey.dixon@cntw.nhs.uk , Tel: 0191 246 7222.

Diagnostic Tools for Autism Spectrum Disorders by Gender: Analysis of Current Status and Future Lines

Studies on the prevalence of autism spectrum disorders have shown gender disproportion. In recent years, there has been an increasing interest in this investigation area. There are two main research lines; the first is focused mostly on gender-related biological reasons that could account for low ASD prevalence in women (i.e., related to some protective factors related to hormones or the immune system, among others), and the second research line studies possible diagnostic biases. In the present study, a review of the latter line of research is made based on two main objectives: (a) analysis of possible biases in diagnostic tools and (b) other nonbiological ASD prevalence explained by gender differences. As a result of our theoretical review, we found that the articles reviewed showed contradictory results and possible diagnostic biases, not only in their design but also in their assessment standards. We concluded that specific or complementary diagnostic tools and procedures differentiated by gender should be developed in order to reduce these biases.

Replication study of ADOS-2 Toddler Module cut-off scores for autism spectrum disorder classification

The Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) has been regarded as the gold standard assessment of autism spectrum disorder (ASD). While clinical validity of ADOS-2 Modules 1-4 have been extensively studied, there has been very limited research examining the clinical validity of ADOS-2 Toddler Module. The goal of this study was to examine alignment of the ADOS-2 Toddler Module classification with clinicians' determination of ASD, with assessing cut-off scores for diagnosing ASD in toddlers. A total of 412 toddlers ages 12-30 months who received ADOS-2 Toddler Module as well as a best estimate clinical (BEC) diagnosis, were included in this study. ADOS-2 Toddler Module cut-off scores were determined using the appropriate algorithms (Algorithm 1 for toddlers aged 12-20 months and those aged 21-30 months with <5 words, Algorithm 2 for toddlers aged 21-30 months with 5 words or more). Receiver operating characteristic (ROC) curves were used to assess cut-off scores that optimized sensitivity and specificity when compared against BEC diagnosis. The selected cut-off scores were examined using frequency tables to compare ADOS-2 classification against BEC diagnosis. For Algorithm 1, classification statistics were optimized at the cut-off score of 12 with an area under the curve (AUC) of 0.92. For Algorithm 2, classification statistics were optimized at the cut-off score of 10 with an AUC of 0.96. The ADOS-2 Toddler Module classification is strongly aligned with BEC diagnosis. The optimal cut-off scores identified in the current study reflect the same results configured by the prior study. LAY SUMMARY: ADOS-2 Toddler Module has been widely used for the ASD assessment, but there have been limited research on its clinical validity. This study is the first replication of the ADOS-2 Toddler Module with a large independent sample. We examined alignment of the ADOS-2 Toddler Module classification with clinicians' determination of ASD, with assessing cut-off scores, and confirmed the clinical validity of ADOS-2 Toddler Module. Cut-off scores of ADOS-2 Toddler Module cited in the manual yielded best clinical utility for diagnosing ASD in toddlers.

Systematic Review and Meta-Analysis of the Clinical Utility of the ADOS-2 and the ADI-R in Diagnosing Autism Spectrum Disorders in Children

The Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) and the Autism Diagnostic Interview, Revised (ADI-R) have high accuracy as diagnostic instruments in research settings, while evidence of accuracy in clinical settings is less robust. This meta-analysis focused on efficacy of these measures in research versus clinical settings. Articles (n = 22) were analyzed using a hierarchical summary receiver operating characteristics (HSROC) model. ADOS-2 performance was stronger than the ADI-R. ADOS-2 sensitivity and specificity ranged from .89-.92 and .81-.85, respectively. ADOS-2 accuracy in research compared with clinical settings was mixed. ADI-R sensitivity and specificity were .75 and .82, respectively, with higher specificity in research samples (Research = .85, Clinical = .72). A small number of clinical studies were identified, indicating ongoing need for investigation outside research settings.

Parent-Teacher Disagreement on Ratings of Behavior Problems in Children with ASD: Associations with Parental School Involvement Over Time

ASD symptomology and behavioral problems pose challenges for children with ASD in school. Disagreement between parents and teachers in ratings of children's behavior problems may provide clinically relevant information. We examined parent-teacher disagreement on ratings of behavior problems among children with ASD during the fall and spring of the school year. When child, teacher, and class characteristics were considered simultaneously, only ASD symptom severity predicted informant disagreement on internalizing and externalizing behavior problems. We also examined associations between informant disagreement and parent school involvement. Cross-lagged panel analyses revealed that higher informant disagreement on children's behavior problems in the fall predicted lower parent school involvement in the spring, suggesting that greater informant agreement may foster parental school involvement over time.

Precision Telemedicine through Crowdsourced Machine Learning: Testing Variability of Crowd Workers for Video-Based Autism Feature Recognition

Mobilized telemedicine is becoming a key, and even necessary, facet of both precision health and precision medicine. In this study, we evaluate the capability and potential of a crowd of virtual workers-defined as vetted members of popular crowdsourcing platforms-to aid in the task of diagnosing autism. We evaluate workers when crowdsourcing the task of providing categorical ordinal behavioral ratings to unstructured public YouTube videos of children with autism and neurotypical controls. To evaluate emerging patterns that are consistent across independent crowds, we target workers from distinct geographic loci on two crowdsourcing platforms: an international group of workers on Amazon Mechanical Turk (MTurk) (N = 15) and Microworkers from Bangladesh (N = 56), Kenya (N = 23), and the Philippines (N = 25). We feed worker responses as input to a validated diagnostic machine learning classifier trained on clinician-filled electronic health records. We find that regardless of crowd platform or targeted country, workers vary in the average confidence of the correct diagnosis predicted by the classifier. The best worker responses produce a mean probability of the correct class above 80% and over one standard deviation above 50%, accuracy and variability on par with experts according to prior studies. There is a weak correlation between mean time spent on task and mean performance (r = 0.358, p = 0.005). These results demonstrate that while the crowd can produce accurate diagnoses, there are intrinsic differences in crowdworker ability to rate behavioral features. We propose a novel strategy for recruitment of crowdsourced workers to ensure high quality diagnostic evaluations of autism, and potentially many other pediatric behavioral health conditions. Our approach represents a viable step in the direction of crowd-based approaches for more scalable and affordable precision medicine.

Big data approaches to develop a comprehensive and accurate tool aimed at improving autism spectrum disorder diagnosis and subtype stratification

Purpose

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is difficult to diagnose accurately due to its heterogeneous clinical manifestations. Comprehensive models combining different big data approaches (e.g. neuroimaging, genetics, eye tracking, etc.) may offer the opportunity to characterize ASD from multiple distinct perspectives. This paper aims to provide an overview of a novel diagnostic approach for ASD classification and stratification based on these big data approaches.

Design/methodology/approach

Multiple types of data were collected and recorded for three consecutive years, including clinical assessment, neuroimaging, gene mutation and expression and response signal data. The authors propose to establish a classification model for predicting ASD clinical diagnostic status by integrating the various data types. Furthermore, the authors suggest a data-driven approach to stratify ASD into subtypes based on genetic and genomic data.

Findings

By utilizing complementary information from different types of ASD patient data, the proposed integration model has the potential to achieve better prediction performance than models focusing on only one data type. The use of unsupervised clustering for the gene-based data-driven stratification will enable identification of more homogeneous subtypes. The authors anticipate that such stratification will facilitate a more consistent and personalized ASD diagnostic tool.

Originality/value

This study aims to utilize a more comprehensive investigation of ASD-related data types than prior investigations, including proposing longitudinal data collection and a storage scheme covering diverse populations. Furthermore, this study offers two novel diagnostic models that focus on case-control status prediction and ASD subtype stratification, which have been under-explored in the prior literature.

Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning

Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). Previous work using machine learning techniques suggested that ASD detection in children can be achieved with substantially fewer items than the original ADOS. Here, we expand on this work with a specific focus on adolescents and adults as assessed with the ADOS Module 4. We used a machine learning algorithm (support vector machine) to examine whether ASD detection can be improved by identifying a subset of behavioral features from the ADOS Module 4 in a routine clinical sample of N = 673 high-functioning adolescents and adults with ASD (n = 385) and individuals with suspected ASD but other best-estimate or no psychiatric diagnoses (n = 288). We identified reduced subsets of 5 behavioral features for the whole sample as well as age subgroups (adolescents vs. adults) that showed good specificity and sensitivity and reached performance close to that of the existing ADOS algorithm and the full ADOS, with no significant differences in overall performance. These results may help to improve the complicated diagnostic process of ASD by encouraging future efforts to develop novel diagnostic instruments for ASD detection based on the identified constructs as well as aiding clinicians in the difficult question of differential diagnosis.

Requirements for Robotic Interpretation of Social Signals “in the Wild”: Insights from Diagnostic Criteria of Autism Spectrum Disorder

The last few decades have seen widespread advances in technological means to characterise observable aspects of human behaviour such as gaze or posture. Among others, these developments have also led to significant advances in social robotics. At the same time, however, social robots are still largely evaluated in idealised or laboratory conditions, and it remains unclear whether the technological progress is sufficient to let such robots move “into the wild”. In this paper, we characterise the problems that a social robot in the real world may face, and review the technological state of the art in terms of addressing these. We do this by considering what it would entail to automate the diagnosis of Autism Spectrum Disorder (ASD). Just as for social robotics, ASD diagnosis fundamentally requires the ability to characterise human behaviour from observable aspects. However, therapists provide clear criteria regarding what to look for. As such, ASD diagnosis is a situation that is both relevant to real-world social robotics and comes with clear metrics. Overall, we demonstrate that even with relatively clear therapist-provided criteria and current technological progress, the need to interpret covert behaviour cannot yet be fully addressed. Our discussions have clear implications for ASD diagnosis, but also for social robotics more generally. For ASD diagnosis, we provide a classification of criteria based on whether or not they depend on covert information and highlight present-day possibilities for supporting therapists in diagnosis through technological means. For social robotics, we highlight the fundamental role of covert behaviour, show that the current state-of-the-art is unable to characterise this, and emphasise that future research should tackle this explicitly in realistic settings.

Rates and Predictors of Co-occurring Autism Spectrum Disorder in Boys with Fragile X Syndrome

Background and aims

Males with fragile X syndrome display many behavioral features of autism spectrum disorder. Despite this overlap, our understanding of autism spectrum disorder symptoms and severity in fragile X syndrome is limited due to variation in assessment methods in the literature. Furthermore, the relationship between autism spectrum disorder symptoms and child characteristics, like age, language, and cognitive abilities, are not well understood in individuals with fragile X syndrome. Therefore, the first research aim was to compare the rates of autism spectrum disorder classifications from three commonly reported autism spectrum disorder assessments in the literature. Our second research aim was to examine the relationship between autism spectrum disorder characteristics and other child characteristics.

Methods

The present study compared autism spectrum disorder classifications and symptoms using the Autism Diagnostic Observation Schedule, Autism Diagnostic Interview, Revised, and Childhood Autism Rating Scale, second edition in a sample of 33 school-age and adolescent boys with fragile X syndrome. In addition, the participants completed nonverbal IQ testing, expressive vocabulary and grammar tests, and a conversation language sample.

Results

The majority of the participants met criteria for autism spectrum disorder on the Autism Diagnostic Observation Schedule (96.97%) and Autism Diagnostic Interview, Revised (90.91%), while only half met criteria for autism spectrum disorder on the Childhood Autism Rating Scale, second edition. Sixteen boys (48.48%) met criteria for autism spectrum disorder on all three measures, and all participants met criteria for autism spectrum disorder on at least one measure. Expressive vocabulary accounted for a unique amount of variance in Childhood Autism Rating Scale, second edition and Autism Diagnostic Observation Schedule scores. Additionally, grammatical complexity accounted for a unique amount of variance in Childhood Autism Rating Scale, second edition scores. None of the child variables accounted for the variance found in Autism Diagnostic Interview, Revised scores. Although nonverbal IQ scores did not account for a significant amount of variance on the Autism Diagnostic Observation Schedule, Autism Diagnostic Interview, Revised, and Childhood Autism Rating Scale, Second Edition, boys who met criteria for autism spectrum disorder on all three measures had lower nonverbal IQ compared to the boys who did not. Additionally, mean length of utterance and expressive vocabulary scores were lower in the boys who met criteria for autism spectrum disorder on all three measures than those who did not.

Conclusions

Our findings identify areas of overlap and difference in the Autism Diagnostic Observation Schedule, Autism Diagnostic Interview, Revised, and Childhood Autism Rating Scale, second edition when used with males with fragile X syndrome. Variation in assessments may differentially identify the phenotypic behaviors of boys with fragile X syndrome that lead to a co-diagnosis of autism spectrum disorder, which contributes to the variation in reported co-morbidity of fragile X syndrome and autism spectrum disorder. Also, expressive language abilities, especially expressive vocabulary, are associated with autism spectrum disorder symptomatology.

Implications: When interpreting comorbid fragile X syndrome and autism spectrum disorder rates in the literature, it is important to consider the assessment tool that was used. Although the assessments that we used in the present study yielded scores that were highly correlated (i.e. Autism Diagnostic Observation Schedule and Childhood Autism Rating Scale, second edition), their categorical classifications did not align perfectly. Our findings also highlight the importance of considering language skills when assessing autism spectrum disorder severity in fragile X syndrome.

Description of Criterion Validity of the Autism Spectrum Rating Scales 6-18 Parent Report: Initial Exploration in a Large Community Sample

Research regarding psychometric properties of autism spectrum disorder questionnaires is lacking. This study explored the criterion validity of the ASRS 6-18 parent report (ASRS-6-18-P) in a large, well-characterized, real-world clinical sample of 422 children ([Formula: see text] autism [AUT] n = 139; non-autism [NOT] n = 283) evaluated with the Autism Diagnostic Observation Schedule-2, a gold-standard measure. Significant mean differences were observed for DSM-5, social, and unusual behaviors. Total, DSM-5, social, and unusual behaviors demonstrated significant correlations with ADOS-2 comparison scores (modules 1-3), but not with module 4 (raw) scores. DSM-5 and Unusual Behaviors demonstrated significant but poor AUCs (0.60). Findings with/without covariates (IQ/age) were overall similar. Sensitivity and specificity could not be optimized. The suggested cutpoint (T-score = 60) demonstrated unacceptably high false positive rates (> 76.33%). While findings suggest limited diagnostic utility of the ASRS-6-18-P, the sample's complex psychiatric presentation and measurement error inherent in cutoff score application should be considered when generalizing results. Further research is recommended.

Developing a Diagnostic Algorithm for the Music-Based Scale for Autism Diagnostics (MUSAD) Assessing Adults with Intellectual Disability

Initial studies have presented the Music-based Scale for Autism Diagnostics (MUSAD) as a promising DSM-5-based observational tool to identify autism spectrum disorder (ASD) in adults with intellectual disability (ID). The current study is the first to address its clinical utility in a new sample of 124 adults with ID (60.5% diagnosed with ASD). The derived diagnostic algorithm differentiated well between individuals with and without ASD (sensitivity 79%, specificity 74%, area under the curve = 0.81). Inter-rater reliability, assessed by the scorings of four independent experts in 22 consensus cases, was excellent (ICC = 0.92). Substantial correlations with scores from other ASD-specific measures indicated convergent validity. The MUSAD yields accurate and reliable scores, supporting comprehensive ASD diagnostics in adults with ID.

Social Cognition in Autism and Other Neurodevelopmental Disorders: A Co-twin Control Study

Alterations in social cognition (SC) are hypothesized to underlie social communication and interaction challenges in autism spectrum disorder (ASD). The aetiological underpinnings driving this association remain unclear. We examined SC in 196 twins with ASD, other neurodevelopmental disorders or typical development using the naturalistic Movie for the Assessment of Social Cognition. Autism and its severity were assessed with the Autism Diagnostic Observation Schedule-2, and autistic traits with the Social Responsiveness Scale-2. Using within twin-pair regression models, controlling for age, sex, IQ, and unmeasured familial confounders such as genetic background and shared-environment, SC correlated with ASD diagnosis, autism severity, and autistic traits. Our findings highlight the importance of SC alterations in autism and suggest a non-shared environmental impact on the association.

Familial confounding on the ability to read minds: A co-twin control study

Alterations in social cognition are hypothesized to underlie social communication challenges in autism spectrum disorder. However, the etiologic underpinnings driving this association, as well as the impact of other psychiatric conditions on the association, remain unclear. Using a co-twin control design, we examined n = 308 twins (mean age = 16.63; 46% females) with autism spectrum disorder, attention-deficit/hyperactivity disorder, affective disorders, or typical development using the Reading the Mind in the Eyes Test to operationalize social cognition ability. Clinical diagnosis of autism spectrum disorder, as well as the extent of quantitative autistic traits, as measured by parental reports using the Social Responsiveness Scale-2, predicted fewer expected responses on the Reading the Mind in the Eyes Test across the pairs. The association remained when adjusting for other diagnoses and IQ. In addition, male sex, lower age, and lower IQ predicted poorer performance on the Reading the Mind in the Eyes Test. The associations between autism and social cognition ability were lost within pairs in both the full sample and the monozygotic subsample. We conclude that the association between autism and social cognition across the sample highlights the importance of social cognition alterations in autism spectrum disorder when compared with other conditions. The attenuation of the association in the within-pair models indicate familial confounding, such as genes and shared environment, influencing both autism and social cognition.

Diagnostic accuracy of the ADOS and ADOS-2 in clinical practice

The Autism Diagnostic Observation Schedule is a semi-structured, standardized assessment tool for individuals with suspected autism spectrum disorders (ASD) and is deemed to be part of the gold standard for diagnostic evaluation. Good diagnostic accuracy and interpersonal objectivity have been demonstrated for the ADOS in research setting. The question arises whether this is also true for daily clinical practice and whether diagnostic accuracy depends on specialized experience in the diagnostic evaluation. The present study explores the diagnostic accuracy of the original and the revised version of the ADOS for Modules 1 through 4. Thus, seven cases of ADOS executions were recorded and coded by a group of experts of specialized outpatient clinics for ASD. In an extensive consensus process, including video analysis of every minute of the ADOS executions, a "gold standard" coding for every case was defined. The videos of the ADOS administration were presented to a large group of clinicians (from daily clinical routine care) and their codings (n = 189) were obtained and analysed. Variance of coding and congruence with the expert coding were determined. High variance was found in the codings. The accuracy of the coding depends on the experience of the coder with the ADOS as well as on characteristics of the cases and the quality of the administration of the ADOS. Specialization in the diagnostic of ASD has to be claimed. Specialized outpatient clinics for ASD are required which guarantee a qualified diagnostic/differential diagnostic and case management with the aim of demand-oriented supply of individual cases.

Autism Diagnostic Observation Schedule (ADOS) scores in males and females diagnosed with autism: a naturalistic study

Purpose

Many tools are available for assessing autism in an adult population; however, few have been studied for the effects of gender on diagnostic scores. The purpose of this paper is to evaluate the Autism Diagnostic Observation Schedule (ADOS) assessment for gender bias in a clinical population, specifically whether the ADOS favours a “male-type” of autism.

Design/methodology/approach

The ADOS scores of patients referred to an NHS specialist autism assessment service were retrospectively examined for significant gender differences. The combined ADOS scores and diagnostic outcome were grouped by gender for each participant. The data were analysed in SPSS using independent t-tests to look for significant gender differences between combined ADOS scores and diagnostic outcomes.

Findings

A significant difference was observed in the mean combined ADOS scores for those participants who later received an autism diagnosis (male=10, female=6, t (13)=3.34, p=10; 0.005). However, no significant difference was observed between mean scores of those who did not receive an autism diagnosis (t (26)=1.21, p=0.237).

Originality/value

The ADOS is a popular assessment used for autism diagnosis. These results provide support for a male gender bias. This could have clinical implications for autism assessment services, whereby lower diagnostic thresholds could be considered for female patients. This could allow more females with autism to receive a diagnosis, and access support services.

Adaptation and Validation of the ADOS-2, Polish Version

Autism Diagnostic Observation Schedule (ADOS) is one of the most popular instruments used world-widely in the diagnosis of autism spectrum disorders (ASD). Unfortunately, there are only a few studies of the psychometric properties of non-English language versions of this instrument and none of the adaptation of its second edition (ADOS-2). The objective of this study was to verify the psychometric properties of the Polish version of the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2-PL). The authors recruited 401 participants: 193 with ASDs (ASD group) and 78 with non-spectrum disorders, plus 130 typically developing participants (control group). ADOS-2-PL was found to have high interrater reliability, internal consistency and test-retest reliability. Confirmatory factor analysis confirmed a good fit of the Polish data to the two-factor model of ADOS-2. As no significant differences were found between participants with childhood autism and other ASDs, only one cut-off was established for Modules 1-4. The sensitivity, specificity and positive predictive value of ADOS-2-PL are high: sensitivity was over 90% (only for the "Older with some words" algorithm in the Toddler Module the sensitivity was 71% and "Aged 5 years or older" algorithm in Module 2 sensitivity was 84%), specificity was above 80% (with the exception of the Module 4 and Module 2 "Aged 5 years or older" algorithm where it was above 70%). The results support the use of ADOS-2-PL in clinical practice and scientific research. To the best of our knowledge, there have been no reports to date about adaptations of ADOS-2 and the psychometric properties of non-English language versions. As such, this constitutes the first attempt at adapting ADOS-2, and its results could be of interest for researchers outside of Poland.

The Role of Context in Psychosocial Stress among Adolescents with Autism Spectrum Disorder: Piloting a Semi-structured, Videogame-based Paradigm

BACKGROUND

Autism Spectrum Disorder (ASD) is characterised by altered social patterns, often associated with increased stress. While puberty is associated with increased stress, there is limited research on stress response to social interaction in adolescents with ASD. The study investigated stress response to semi-structured, videogame-based interaction in adolescents with and without ASD, and the impact of puberty.

METHOD

Twelve adolescents with ASD and 12 typically developing (TD) peers participated in a semi-structured, videogame-based social interaction. Stress was measured via salivary cortisol.

RESULTS

There were no significant between-group differences in cortisol. Pubertal development was correlated with cortisol in ASD (r = -0.901, p < 0.0001), but not TD (r = 0.022, p = 0.949).

CONCLUSIONS

Findings contribute to a fuller picture of the developmental trajectories of physiological stress in ASD, including the importance of context, structure, and puberty. The current investigation underscores the necessity of incorporating varied social contexts when assessing stress and social interaction.

High-resolution single nucleotide polymorphism arrays identified an atypical microdeletion of the Williams-Beuren syndrome interval in a patient presenting with a different phenotype

The present study aimed to identify the mutation causing an atypical syndrome. High-resolution single nucleotide polymorphism (SNP) arrays are considered to be a major detection method for submicroscopic chromosomal rearrangements smaller than 5 Mb in size. Genomic DNA samples of the patient and his parents were converted to a final concentration of 50 ng/ml. The Illumina BeadScan genotyping system and the HumanOmni1‑Quad Chip were employed to obtain the signal intensities of SNP probes. The patient presented with congenital heart disease, autism, mental retardation, growth retardation, hypercalcemia, nephroliths and cleft palate. The karyotypes of the patient and his parents were normal. The present study employed high‑resolution SNP arrays to analyze the whole genome for copy number variations (CNVs). A total of 309 CNVs were discovered. A de novo 1.5 Mb gain of chromosome 7q11.23 (Chr7: 72,357,322‑73,856,472) was identified following exclusion of CNVs presented in the Database of Genomic Variants. In conclusion, to the best of our knowledge, the current study describes the first case of a patient presenting with Williams‑Beuren syndrome alongside supravalvular aortic stenosis, autism and cleft palate, and identifies an atypical deletion at 7q11.23.

Does the Brief Observation of Social Communication Change help moving forward in measuring change in early autism intervention studies?

The field of early autism research is in dire need of outcome measures that adequately reflect subtle changes in core autistic behaviors. This article compares the ability of a newly developed measure, the Brief Observation of Social Communication Change (BOSCC), and the Autism Diagnostic Observation Schedule (ADOS) to detect changes in core symptoms of autism in 44 toddlers. The results provide encouraging evidence for the Brief Observation of Social Communication Change as a candidate outcome measure, as reflected in sufficient inter- and intra-rater reliability, independency from other child characteristics, and sensitivity to capture change. Although the Brief Observation of Social Communication Change did not evidently outperform the Autism Diagnostic Observation Schedule on any of these quality criteria, the instrument may be better able to capture subtle, individual changes in core autistic symptoms. The promising findings warrant further study of this new instrument.