A scoping review of telehealth diagnosis of autism spectrum disorder

Background Considering the COVID-19 pandemic, understanding the reliability, validity, social validity, and feasibility of using telehealth to diagnose ASD is a critical public health issue. This paper examines evidence supporting the use of telehealth methods to diagnose ASD and outlines the necessary modifications and adaptations to support telehealth diagnosis. Methods and procedures Studies were identified by searching PubMed and Psychlnfo electronic databases and references lists of relevant articles. Only peer reviewed articles published in English with a focus on using telehealth for the purposes of diagnosing ASD were included. Searches were conducted through June 3rd, 2021. Outcomes and results A total of 10 studies were identified as meeting inclusion criteria. Of the eight papers that reported on reliability (e.g., accuracy), telehealth methods to diagnose ASD were between 80-91% accurate when compared with traditional in-person diagnosis. Six studies reported on validity (i.e., sensitivity and/or specificity). All six studies calculated sensitivity, with values ranging from 75% and 100%. Five of the six studies calculated specificity, with values ranging from 68.75% and 100%. The seven papers that reported social validity indicated that caregivers, as well as adult participants and clinicians, were mostly satisfied with telehealth. Feasibility was reported by seven studies and suggests that telehealth methods appear largely viable, though some challenges were reported. Conclusions and implications Although findings reviewed here are promising, more research is needed to verify the accuracy, validity, and feasibility of utilizing telehealth to diagnose ASD. Studies with larger sample sizes and samples across sites will be critical, as these will allow clinicians to identify subjects most likely to benefit from telehealth as well as those more likely to require an in-person assessment. This research is important not only due to the current pandemic, but also due to increased prevalence rates of ASD and an insufficient number of diagnostic providers-particularly in rural and/or otherwise under-served communities.

Automated summary

This paper examines the use of telehealth for diagnosing ASD and finds that it is a feasible and effective method, with accuracy ranging from 80-91% compared to in-person diagnosis. The sensitivity values range from 75% to 100%, and specificity values range from 68.75% to 100%. The majority of caregivers, adult participants, and clinicians express satisfaction with telehealth for diagnosis. However, further research is needed to confirm the accuracy and validity of this method.