Mount Sinai Researchers Identify Important Considerations for Online Psychiatric Research: Defining Conditions Like Autism Using Self-Reported Traits Instead of Clinical Evaluation May Lead to Different Results
Corresponding Author: Xiaosi Gu, PhD, Director of the Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, and other coauthors.
Bottom Line Without additional context, self-reported symptom surveys may not be sufficient to identify or draw representative conclusions about certain diagnoses, including autism spectrum disorder (ASD).
Results: Despite similarly high levels of self-reported autistic traits, adults recruited online (without self-identification of an ASD diagnosis) and those recruited in-person (with an ASD diagnosis confirmed through clinical evaluation) displayed different psychiatric profiles and tendencies during simulated social interactions, suggesting they may represent different groups. Additionally, for in-person ASD participants, no agreement was detected between self-reported symptom surveys and clinical evaluations, highlighting the need for separate interpretations of each measure.
Why the Research Is Interesting: As anonymous online research becomes increasingly popular, it is essential to evaluate its limitations to determine the scientific questions it can most effectively address. The findings demonstrate that, while self-reported symptoms are important for understanding subjective experiences, they may not be effective diagnostic shortcuts for ASD or other conditions associated with introspective differences.
Who: The study consisted of three groups of participants: adults recruited online with low self-reported autistic traits, adults recruited online with high self-reported autistic traits, and adults recruited in-person with clinically confirmed diagnoses of autism spectrum disorder (ASD).
When: Research participants were between 18 and 50 years old.
What: The study sought to systematiclaly evaluate different methods for 1) identifying autistic individuals and 2) measuring autism symptoms.
How: To evaluate differences in clinical recruitment methods, the study compared the online and in-person groups on a core feature of ASD: social differences. To this end, the study assessed their behavior during social interaction tasks and their scores on surveys assessing traits known to impact social behavior (e.g., social anxiety). To evaluate differences in symptom measurement, the study compared self- and clinician-reported autism symptoms in the in-person group.
Study Conclusions: The groups displayed notably different social profiles. Compared to both high- and low-trait online groups, the in-person ASD group acted less affiliative towards other people and detected fewer opportunities for social influence during simulated social interactions and reported lower social anxiety and social avoidance. In adults with a confirmed ASD diagnosis, higher clinician-rated symptoms did not correspond to higher self-reported symptoms, suggesting the two measures capture different aspects of ASD. These results indicate that, when researching conditions like autism, clinically ascertained and trait-defined symptoms and samples may produce different results. This work emphasizes the important distinction between diagnoses and traits and provides a caution against the potential for generating assumptions about one group based on the findings from research conducted in another.
Paper Title: Phenotypic divergence between individuals with self-reported autistic traits and clinically ascertained autism
Said Mount Sinai’s Dr. Xiaosi Gu of the research: “This study highlights the limitation of self-reports as a diagnostic proxy and the importance of clinician evaluation in the context of autism diagnosis. It remains to be seen if the same discrepancy might exist for other neuropsychiatric conditions.”
To request a copy of the paper or to schedule an interview with Dr. Gu, please contact Mount Sinai’s Director of Media and Public Affairs, Elizabeth Dowling, at elizabeth.dowling@mountsinai.org or at 212 241-9200.
