Tool For Autism Spectrum Disorder Research Articles

Golf training as an effective therapeutic tool for autism spectrum disorder: a multisite evaluation

Objectives A 6-week adapted golf training program was delivered to 31 individuals with autism spectrum disorder (ASD) and the effects of the program were examined on golf skills, physical fitness abilities, and socio-communicative functioning. Methods The program led to significant improvements in golf skills such as grip positioning, shot control, aim, and posture as well as physical activity abilities including leg strength, core stability, and balance. Results Additionally, staff involved with the program documented significant improvements amongst participants in expressive and receptive communication, as well as social and regulatory skills. However, there were no significant changes in social or communicative abilities in the parent-rated, standardized instrument. Conclusions The adapted golf training program proved to be effective for boosting a variety of abilities in individuals with ASD; sport-training programs should continue to be studied and implemented at autism treatment facilities.

Behavioral Phenotypes and Comorbidity in 3q29 Deletion Syndrome: Results from the 3q29 Registry.

3q29 deletion syndrome (3q29del) is associated with a significantly increased risk for neurodevelopmental and neuropsychiatric disorders. However, the full spectrum of behavioral phenotypes associated with 3q29del is still evolving. Individuals with 3q29del (n = 96, 60.42% male) or their guardian completed the Achenbach Child or Adult Behavior Checklist (CBCL/ABCL) via the online 3q29 registry (3q29deletion.org). Typically developing controls (n = 57, 49.12% male) were ascertained as a comparison group. We analyzed mean performance on the CBCL/ABCL for individuals with 3q29del and controls across composite, DSM-keyed, and developmental scales; and the relationship between CBCL/ABCL performance and clinical and developmental phenotypes for individuals with 3q29del. Individuals with 3q29del showed significantly elevated behavioral and developmental impairment relative to controls across CBCL/ABCL domains. A substantial proportion of study participants with 3q29del scored in the Borderline or Clinical range for composite and DSM-keyed scales, indicating significant behavioral problems that may require clinical evaluation. We found that the preschool CBCL DSM-keyed autism spectrum problems scale is a potential screening tool for autism spectrum disorder (ASD) for individuals with 3q29del; CBCL/ABCL DSM-keyed scales were not accurate screeners for anxiety disorders or attention-deficit/hyperactivity disorder (ADHD) in our study sample. We identified a high degree of psychiatric comorbidity in individuals with 3q29del, with 60.42% (n = 58) of individuals with 3q29del scoring in the Borderline or Clinical range on two or more DSM-keyed CBCL/ABCL scales. Finally, we found that the degree of developmental delay in participants with 3q29del does not explain the increased behavioral problems observed on the CBCL/ABCL. The CBCL/ABCL can be used as screening tools in populations such as 3q29del, even in the presence of substantial psychiatric comorbidity. These results expand our understanding of the phenotypic spectrum of 3q29del and demonstrate an effective method for recruiting and phenotyping a large sample of individuals with a rare genetic disorder.

A novel telehealth tool using a snack activity to identify autism spectrum disorder

BackgroundThe COVID-19 pandemic has caused an unprecedented need for accessible health care services and significantly accelerated the development processes of telehealth tools for autism spectrum disorder (ASD) early screening and diagnosis. This study aimed to examine the feasibility and utility of a time-efficient telehealth tool combining a structured snack time assessment activity and a novel behaviour coding scheme for identifying ASD.MethodsA total of 134 1–6-year-old individuals with ASD (age in months: mean = 51.3, SD = 13.1) and 134 age- and sex-matched typically developing individuals (TD) (age in months: mean = 54, SD = 9.44) completed a 1-min snack time interaction assessment with examiners. The recorded videos were then coded by trained coders for 17 ASD-related behaviours; the beginning and end points and the form and function of each behaviour were recorded, which took 10–15 min. Coded details were transformed into 62 indicators representing the count, duration, rate, and proportion of those behaviours.ResultsTwenty indicators with good reliability were selected for group difference, univariate and multivariate analyses. Fifteen behaviour indicators differed significantly between the ASD and TD groups and remained significant after Bonferroni correction, including the children’s response to the examiner’s initiation, eye gaze, pointing, facial expressions, vocalization and verbalization, and giving behaviours. Five indicators were included in the final prediction model: total counts of eye gaze, counts of standard pointing divided by the total counts of pointing, counts of appropriate facial expressions, counts of socially oriented vocalizations and verbalizations divided by the total counts of vocalizations and verbalizations, and counts of children using giving behaviours to respond to the examiner's initiations divided by the total counts of the examiner's initiation of snack requisitions. The ROC curve revealed a good prediction performance with an area under the curve (AUC) of 0.955, a sensitivity of 92.5% and a specificity of 84.3%.ConclusionOur results suggest that the snack activity-based ASD telehealth approach shows promise in primary health care settings for early ASD screening.

The gaze characteristics in preterm children: The appropriate timing for an eye-tracking tool

BackgroundAn objective screening tool for autism spectrum disorder (ASD), also known as an eye-tracking tool, assesses the patient’s abnormal gaze patterns and detects the risk of ASD. As this tool is generally used for children born at term, this study aimed to clarify the appropriate timing for using the tool for preterm children, factors that influence the timing, and evaluate their gaze characteristics using the Gazefinder®. MethodIn 90 preterm children, a total of 125 eye-tracking tasks were completed and analyzed in 3–6, 7–9, 10–12, 13–18, and 19–32 months of corrected age (CA). The Gazefinder® was used to compare the mean fixation time percentage (MFP) in each CA and evaluate the gaze patterns. Perinatal factors associated with low MFP were also analyzed. ResultsOnly 50% of the children scored ≥70% MFP at 3–6 months of CA. The MFP increased significantly after 7 months of CA (p = 0.0003), reached 90% at 13–18 months, and 100% at 19–32 months of CA. Chronic lung disease (CLD) was a clinical factor associated with low MFP (p = 0.036). Preterm children gazed more at eyes but gazed at mouths when the mouth moved. ConclusionIt is necessary for preterm children to begin using Gazefinder® atleast at ≥13 months of age, especially those complicated with CLD. Preterm children prefer gazing at social information just as typically developing children.

Contrastive Multi-view Composite Graph Convolutional Networks Based on Contribution Learning for Autism Spectrum Disorder Classification.

The resting-state functional magnetic resonance imaging (rs-fMRI) faithfully reflects the brain activities and thus provides a promising tool for autism spectrum disorder (ASD) classification. Up to now, graph convolutional networks (GCNs) have been successfully applied in rs-fMRI based ASD classification. However, most of these methods were developed based on functional connectivities (FCs) that only reflect low-level correlation between brain regions, without integrating both high-level discriminative knowledge and phenotypic information into classification. Besides, they suffered from the overfitting problem caused by insufficient training samples. To this end, we propose a novel contrastive multi-view composite GCN (CMV-CGCN) for ASD classification using both FCs and HOFCs. Specifically, a pair of graphs are constructed based on the FC and HOFC features of the subjects, respectively, and they share the phenotypic information in the graph edges. A novel contrastive multi-view learning method is proposed based on the consistent representation of both views. A contribution learning mechanism is further incorporated, encouraging the FC and HOFC features of different subjects to have various contribution in the contrastive multi-view learning. The proposed CMV-CGCN is evaluated on 613 subjects (including 286 ASD patients and 327 NCs) from the Autism Brain Imaging Data Exchange (ABIDE). We demonstrate the performance of the method for ASD classification, which yields an accuracy of 75.20% and an area under the curve (AUC) of 0.7338. Experimental results show that our proposed method outperforms state-of-the-art methods on the ABIDE database.

Systematic Review of Translation and Cultural Adaptations of Autism Spectrum Disorder’s Screening Tool: The Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R)

In recent years, the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R), a screening tool for autism spectrum disorder (ASD), has been translated into various languages and made accessible for the assessment of children globally. This study aims to systematically review and identify the available translations of the M-CHAT-R that have been adapted for use in different cultures, to evaluate the translation and cultural adaptation process, to report on the methodologies and psychometric properties of the adaptations of the M-CHAT-R and to critically discuss the implications for clinical practice and future research. An electronic search was performed through four main databases, EBSCOhost, Google Scholar, PubMed and Elsevier, to identify eligible articles. The PRISMA guidelines were employed as the primary search strategy and reporting system, while the COSMIN checklist was used to evaluate the selected studies' psychometric properties and cultural validity. Thirteen studies were included in this systematic review. The evaluation of screening accuracy properties for all studies showed that the M-CHAT-R translations achieved reasonable to good screening accuracy and further highlighted that sensitivity and specificity values, which are not dependent on the prevalence rate, are more appropriate measures than other psychometric properties to reflect the validity of the M-CHAT-R. The review of methodologies and results showed that the M-CHAT-R might be equally effective as the original tool in screening children aged up to 48 months, but future research is required to obtain more normative data. The large discrepancies among sample sizes and differences in population settings with ambiguous translations and adaptations highlighted the need for a more in-depth adaptation process for future cross-cultural validation studies.

Specificity and sensitivity of the social communication questionnaire lifetime screening tool for autism spectrum disorder in a UK CAMHS service.

The Social Communication Questionnaire is used to identify children and young people (CYP) who may require formal ASD assessment. However, there is a paucity of research on its utility in Children and Adolescent Mental Health Services. This evaluation aimed to determine the sensitivity and specificity of the Social Communication Questionnaire (SCQ) in a UK, Midlands CAMHS service. Forty young people (mean age 13.75years) were screened using the caregiver reported SCQ before completing 'gold standard' assessment. The SCQ had a sensitivity of 80% and a specificity of 25.7%. ROC curve analysis indicated low diagnostic accuracy. Differences in predictive accuracy of SCQ and diagnostic standard were statistically significant (p < 0.0001). This evaluation builds on previous research suggesting that the SCQ may not be an efficient screening tool in CAMHS settings.

Sparse Hierarchical Representation Learning on Functional Brain Networks for Prediction of Autism Severity Levels.

Machine learning algorithms have been widely applied in diagnostic tools for autism spectrum disorder (ASD), revealing an altered brain connectivity. However, little is known about whether an magnetic resonance imaging (MRI)-based brain network is related to the severity of ASD symptoms in a large-scale cohort. We propose a graph convolution neural network-based framework that can generate sparse hierarchical graph representations for functional brain connectivity. Instead of assigning initial features for each node, we utilized a feature extractor to derive node features and the extracted representations can be fed to a hierarchical graph self-attention framework to effectively represent the entire graph. By incorporating connectivity embeddings in the feature extractor, we propose adjacency embedding networks to characterize the heterogeneous representations of the brain connectivity. Our proposed model variants outperform the benchmarking model with different configurations of adjacency embedding networks and types of functional connectivity matrices. Using this approach with the best configuration (SHEN atlas for node definition, Tikhonov correlation for connectivity estimation, and identity-adjacency embedding), we were able to predict individual ASD severity levels with a meaningful accuracy: the mean absolute error (MAE) and correlation between predicted and observed ASD severity scores resulted in 0.96, and r = 0.61 (P < 0.0001), respectively. To obtain a better understanding on how to generate better representations, we investigate the relationships between the extracted feature embeddings and the graph theory-based nodal measurements using canonical correlation analysis. Finally, we visualized the model to identify the most contributive functional connections for predicting ASD severity scores.

Early screening tools for Autism Spectrum Disorder in infancy and toddlers

Early screening tools for Autism Spectrum Disorder in infancy and toddlers

Validation of the Chinese Version of the Autism Diagnostic Interview-Revised in Autism Spectrum Disorder.

BackgroundThe Autism Diagnostic Interview-Revised (ADI-R) is an essential semi-structured diagnostic tool for autism spectrum disorder (ASD). This study aims to validate the Chinese version of the ADI-R in Taiwan.MethodsThe Chinese version of the ADI-R was translated and back-translated by professional translators and was approved by the original authors. A group of child psychiatrists and psychologists corrected medical terminology for the final version. Then, a total of 74 participants with ASD (male, 59, 79.73%) and 33 control participants without ASD (male, 16, 48.48%) were recruited. All participants were between 3 years 4 months to 41 years old (mean: 14.63 ± 7.93 years). Exploratory factor analysis (EFA) was used to measure the factor structure.ResultsCronbach’s α showed good to excellent internal consistency (0.78–0.98) over the three core symptom domains of the Chinese version of the ADI-R. Pearson’s correlation analysis revealed very high test–retest reliability (Pearson’s correlation coefficients ranging from 0.95 to 0.99). EFA supported three categories of factors. For correct diagnosis of ASD, the Chinese version of the ADI-R had high sensitivity (97.30%), specificity (100%), positive predictive value (PPV) (100%), and negative predictive value (NPV) (94.29%). All domains also showed excellent area under the curves (0.991–1), sensitivity (94.59–98.65%), specificity (96.97–100%), Youden index (94.59–98.65%), PPV (97.78–100%), NPV (89.19–100%), positive likelihood ratio (32.55–33.00%) and negative likelihood ratio (0.00–0.05) after statistical examination.ConclusionThe Chinese version of the ADI-R is a reliable and valid diagnostic tool for the diagnosis of ASD in Clinical settings in Taiwan.

A brief review of saliva biomarkers as a diagnostic tool for autism spectrum disorder (asd)

The diagnosis of autistic spectrum disorder (ASD) remains clinical to this date. Immune dysfunction has been a recognized feature in ASD, and several researchers suggest that it can be used as a diagnostic tool by detecting biomarkers as well as an effective route for pharmacological intervention. The molecular biomarkers obtained from biological fluids are gaining relevance because of its lower invasiveness and ease of collection. Patients with autism are characterized by sensory reactivity and behavioral difficulties that can make sample collection problematic and, in this context, saliva appears to be a viable alternative for obtaining relevant biological information, being also especially indicated for children due to its painless and non-invasive sampling characteristics. Also, the saliva represents a valuable resource for studying possible biomarkers of autism. Following is a brief description of the main works published in recent years on saliva biomarkers for the diagnosis of autism.

6.2 Evaluation of an Artificial Intelligence–Based Medical Device Designed to Aid in the Diagnosis of Autism Spectrum Disorder in the Primary Care Setting

The lack of diagnostic tools for autism spectrum disorder (ASD) in primary care settings and long waiting lists for specialist assessment contribute to an average delay of 3 years between first parental concern and diagnosis. This study examined the performance of an artificial intelligence–based device intended to aid primary care practitioners (PCPs) in the diagnosis of ASD. This was a prospective multisite pivotal study conducted in 6 states using a double-blind active comparator design with 425 completed subjects (36% female) ages 18 to 72 months with concern for developmental delay. Previous research developed, tuned, and tested a device that uses a gradient-boosted decision-tree machine learning algorithm that analyzes 64 behavioral features from 3 distinct inputs: 1) caregiver questionnaire; 2) 2 to 4 minutes of home videos analyzed by trained video analysts; and 3) PCP questionnaire. Device results were compared to diagnosis by independent agreement of specialist clinicians based on clinical assessment, including a modified Child Autism Rating Scale (CARS-2) and DSM-5 criteria. Specialists were child and adolescent psychiatrists, child psychologists, pediatric neurologists, and developmental behavioral pediatricians experienced in diagnosing ASD. Comparison of device results to specialist diagnosis found the following for subjects with determinate device results: positive predictive value (PPV) = 80.8% (95% CI, 70.3-88.8); negative predictive value (NPV) = 98.3% (90.6-100); sensitivity = 98.4% (91.6-100); and specificity = 78.9% (67.6-87.7). There was no evidence that device performance significantly varied when the PCP used the device remotely compared to in-person. Using this device, PCPs could efficiently, accurately, and equitably diagnose a subset of children aged 18 to 72 months old, thereby streamlining specialist referrals and facilitating earlier ASD diagnosis and interventions. The results further provide preliminary evidence that PCP evaluation of the child can be done via telemedicine or in-person with no degradation in device performance.

Measurement invariance of the Childhood Autism Rating Scale (CARS) across six countries.

The Childhood Autism Rating Scale (CARS) is a simple and inexpensive tool for Autism spectrum disorder (ASD) assessments, with evidenced psychometric data from different countries. However, it is still unclear whether ASD symptoms are measured the same way across different societies and world regions with this tool, since data on its cross-cultural validity are lacking. This study evaluated the cross-cultural measurement invariance of the CARS among children with ASD from six countries, for whom data were aggregated from previous studies in India (n=101), Jamaica (n=139), Mexico (n=72), Spain (n=99), Turkey (n=150), and the United States of America (n=186). We analyzed the approximate measurement invariance based on Bayesian structural equation modeling. The model did not fit the data and its measurement invariance did not hold, with all items found non-invariant across the countries. Items related to social communication and interaction (i.e., relating to people, imitation, emotional response, and verbal and nonverbal communication) displayed lower levels of cross-country non-invariance compared to items about stereotyped behaviors/sensory sensitivity (i.e., body and object use, adaptation to change, or taste, smell, and touch response). This study found that the CARS may not provide cross-culturally valid ASD assessments. Thus, cross-cultural comparisons with the CARS should consider first which items operate differently across samples of interest, since its cross-cultural measurement non-invariance could be a source of cross-cultural variability in ASD presentations. Additional studies are needed before drawing valid recommendations in relation to the cultural sensitivity of particular items.

Psychometric Comparison of the English and Spanish Western-Hemisphere Versions of the Modified Checklist for Autism in Toddlers-Revised.

Parent-report screening tools for autism spectrum disorder (ASD) are widely used to promote early identification of children with or at risk for ASD. Most screening tools have been developed in English in the United States or United Kingdom; thus, translated versions are needed for use with culturally and linguistically diverse populations. Traditional translation methods include a forward translation, back translation, and review. However, when used in new cultural and linguistic contexts, this "forward-back" approach may have limitations, including differing psychometric properties compared with original instruments. This study presents a psychometric analysis of the forward-back translation methodology of an ASD screening tool. A retrospective chart review design was used to examine Modified Checklist for Autism in Toddlers-Revised (M-CHAT-R; Robins et al.) records from 2974 toddlers. Data were compared between caregivers who completed the original English M-CHAT-R and caregivers who completed its forward-back "Spanish-Western Hemisphere" translation to compare select psychometric properties of the 2 instruments. Significant differences were observed between the 2 versions, including a higher overall risk score, higher initial screen-positive rate, and increased likelihood of leaving items blank among Spanish-speaking respondents. Traditional translation methods seemed to affect select psychometric properties between translations of the M-CHAT-R. A more rigorous cultural adaptation approach may be necessary to maintain equivalence with the original instrument. Until new rigorous translations are available, it is recommended that language-specific screening tools continue to be used, along with recommended follow-up interviews, to avoid exacerbating existing health disparities.

The Early Screening for Autism and Communication Disorders: Field-testing an autism-specific screening tool for children 12 to 36 months of age.

There is a critical need for validated screening tools for autism spectrum disorder in very young children so families can access tailored intervention services as early as possible. Few screeners exist for children between the recommended screening ages of 18–24 months. This study examined the utility of a new autism-specific parent-report screening tool, the Early Screening for Autism and Communication Disorders for children 12–36 months. Field-testing was conducted from five sites with 471 children screened for communication delays in primary care or referred for familial risk or concern for autism spectrum disorder. The Early Screening for Autism and Communication Disorders was evaluated in three age groups: 12–17, 18–23, and 24–36 months. A best-estimate diagnosis of autism spectrum disorder, developmental delay, or typical development was made. Receiver operating characteristic curves were examined for all 46 items and the 30 items that best discriminated autism spectrum disorder from the non-spectrum groups. Area under the curve estimates for the total were greater than 0.90 across age groups. Cutoffs were established for each age group with sensitivity between 0.86 and 0.92 and specificity between 0.74 and 0.85. Results provide preliminary support for the validity of the Early Screening for Autism and Communication Disorders as an autism-specific screener in children 12–36 months with elevated risk of communication delay or autism spectrum disorder.Lay abstractThere is a critical need for accurate screening tools for autism spectrum disorder in very young children so families can access tailored intervention services as early as possible. However, there are few screeners designed for children 18–24 months. Developing screeners that pick up on the signs of autism spectrum disorder in very young children has proved even more challenging. In this study, we examined a new autism-specific parent-report screening tool, the Early Screening for Autism and Communication Disorders for children between 12 and 36 months of age. Field-testing was done in five sites with 471 children screened for communication delays in primary care or referred for familial risk or concern for autism spectrum disorder. The Early Screening for Autism and Communication Disorders was tested in three age groups: 12–17, 18–23, and 24–36 months. A best-estimate diagnosis of autism spectrum disorder, developmental delay, or typical development was made. Analyses examined all 46 items and identified 30 items that best discriminated autism spectrum disorder from the non-spectrum groups. Cutoffs were established for each age group with good sensitivity and specificity. Results provide preliminary support for the accuracy of the Early Screening for Autism and Communication Disorders as an autism-specific screener in children 12–36 months with elevated risk of communication delay or autism spectrum disorder.

A systematic review of technological approaches for autism spectrum disorder assessment in children: Implications for the COVID-19 pandemic

BackgroundScreening and diagnostic assessments tools for autism spectrum disorder (ASD) are important to administer during childhood to facilitate timely entry into intervention services that can promote developmental outcomes across the lifespan. However, assessment services are not always readily available to families, as they require significant time and resources. Currently, in-person screening and diagnostic assessments for ASD are limited due to the COVID-19 pandemic and will continue to be a concern for situations that limit in-person contact. Thus, it is important to expand the modalities in which child assessments are provided, including the use of technology. AimsThis systematic review aims to identify technologies that screen or assess for ASD in 0–12 year-old children, summarizing the current state of the field and suggesting future directions. MethodsAn electronic database search was conducted to gather relevant articles to synthesize for this review. Outcomes and results16 studies reported use of novel technology to assess children suspected of ASD. Conclusions and implicationsResults strongly supported live-video evaluations, video observations, and online or phone methods, but there is a need for research targeting the feasibility of these methods as it applies to the stay-at-home orders required by the pandemic, and other situations that limit clients from seeing providers in-person.

Culturally Adapted Assessment Tool for Autism Spectrum Disorder and its Clinical Significance

Diagnosing of Autism Spectrum Disorder (ASD) using tools developed in the West is challenging in the Indian setting due to a huge diversity in sociocultural and economic backgrounds. Culturally adapted tools, such as the International Clinical Epidemiology Network (INCLEN) Diagnostic Tool for Autism Spectrum Disorder, have been developed in several Indian languages, yet, they do not accommodate all verbal abilities and education backgrounds. To address this disparity, we developed a home-based, audiovisual game app (Autest) suitable for ASD risk assessment in Indian children under 10 years of age. The game has five modules for each age group with specific peer interaction and play skill assessments. Each module follows a story from the Panchatantra, a popular Indian story series for children. Gameplay and behavior are tracked to assess risk. The effectiveness of Autest was rated by 30 psychologists with respect to current tools. Ratings suggested that the tool is effective and can reduce social inhibition and facilitate assessment due to the lack of a language barrier using emojis, cultural appropriateness, ease of administration, and simple scoring. This tool is particularly useful minimally verbal, at-risk children. Further usage and development of Autest can improve risk assessment and early intervention measures for children with ASD in India.

Psychometric properties of the Autism Spectrum Disorder in Adults Screening Questionnaire (ASDASQ) in a sample of Italian psychiatric outpatients

BackgroundThe present study aimed to examine the reliability and validity of the Italian version of the Autism Spectrum Disorder in Adults Screening Questionnaire (ASDASQ), a screening tool for autism spectrum disorder (ASD) among psychiatric outpatients. MethodsWe recruited 340 subjects via an outpatient psychiatric service in Italy. Forty-eight had a diagnosis of ASD, confirmed after a comprehensive clinical assessment and the administration of the Autism Diagnostic Observation Schedule-2 (ADOS-2). The remaining 292 participants had other diagnoses, confirmed after a careful psychiatric evaluation and the administration of the Structured Clinical Interview for DSM-5 (SCID-5). The ASDASQ was administered to contact clinicians of each subject. ResultsThe ASDASQ showed outstanding accuracy (AUC = 0.96) in discriminating between ASD and non-ASD patients, with good sensitivity (0.85) and specificity (0.92). Agreement with clinical diagnosis was substantial (k = 0.68). Internal consistency of the tool was good (Cronbach’s alpha = 0.82), while intra- (ICC = 0.97) and inter-rater reliability (ICC = 0.92) were excellent. We found also a moderate correlation between ASDASQ and ADOS-2 scores in the ASD sample (r = 0.56). ConclusionOur findings suggest that the ASDASQ, in the Italian adaptation, may be considered a quick, simple, and effective tool to screen for ASD among psychiatric outpatients. Further studies are needed to evaluate its utility in other clinical settings.

Digital Behavioral Phenotyping Detects Atypical Pattern of Facial Expression in Toddlers with Autism.

Commonly used screening tools for autism spectrum disorder (ASD) generally rely on subjective caregiver questionnaires. While behavioral observation is more objective, it is also expensive, time-consuming, and requires significant expertise to perform. As such, there remains a critical need to develop feasible, scalable, and reliable tools that can characterize ASD risk behaviors. This study assessed the utility of a tablet-based behavioral assessment for eliciting and detecting one type of risk behavior, namely, patterns of facial expression, in 104 toddlers (ASD N = 22) and evaluated whether such patterns differentiated toddlers with and without ASD. The assessment consisted of the child sitting on his/her caregiver's lap and watching brief movies shown on a smart tablet while the embedded camera recorded the child's facial expressions. Computer vision analysis (CVA) automatically detected and tracked facial landmarks, which were used to estimate head position and facial expressions (Positive, Neutral, All Other). Using CVA, specific points throughout the movies were identified that reliably differentiate between children with and without ASD based on their patterns of facial movement and expressions (area under the curves for individual movies ranging from 0.62 to 0.73). During these instances, children with ASD more frequently displayed Neutral expressions compared to children without ASD, who had more All Other expressions. The frequency of All Other expressions was driven by non-ASD children more often displaying raised eyebrows and an open mouth, characteristic of engagement/interest. Preliminary results suggest computational coding of facial movements and expressions via a tablet-based assessment can detect differences in affective expression, one of the early, core features of ASD. LAY SUMMARY: This study tested the use of a tablet in the behavioral assessment of young children with autism. Children watched a series of developmentally appropriate movies and their facial expressions were recorded using the camera embedded in the tablet. Results suggest that computational assessments of facial expressions may be useful in early detection of symptoms of autism.

Fourier Transform Infrared Spectroscopy Based Complementary Diagnosis Tool for Autism Spectrum Disorder in Children and Adolescents.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that begins early in life and continues lifelong with strong personal and societal implications. It affects about 1%–2% of the children population in the world. The absence of auxiliary methods that can complement the clinical evaluation of ASD increases the probability of false identification of the disorder, especially in the case of very young children. In this study, analytical models for auxiliary diagnosis of ASD in children and adolescents, based on the analysis of patients’ blood serum ATR-FTIR (Attenuated Total Reflectance-Fourier Transform Infrared) spectra, were developed. The models use chemometrics (either Principal Component Analysis (PCA) or Partial Least Squares Discriminant Analysis (PLS-DA)) methods, with the infrared spectra being the X-predictor variables. The two developed models exhibit excellent classification performance for samples of ASD individuals vs. healthy controls. Interestingly, the simplest, unsupervised PCA-based model results to have a global performance identical to the more demanding, supervised (PLS-DA)-based model. The developed PCA-based model thus appears as the more economical alternative one for use in the clinical environment. Hierarchical clustering analysis performed on the full set of samples was also successful in discriminating the two groups.