ArticleJournal of psychiatric research2026
Automatic measurement of social gaze during naturalistic conversations in autism.
Article in Journal of psychiatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- A transdiagnostic AI-based measure of interpersonal coordination in autism and other conditions.Molecular autism · 2026Article
- Beyond FACS: Data-driven Facial Expression Dictionaries, with Application to Predicting Autism.Proceedings of the ... International Conference on Automatic Face and Gesture Recognition. IEEE International Conference on Automatic Face & Gesture Recognition · 2025Article
Corrections and comments
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Authors and funding
18 authors.
Funding
Abstract
Standardized, granular measurement of social communication behaviors, such as social gaze during natural interactions, is needed for a range of psychiatric applications including diagnosis and detecting clinical change in conditions such as autism. Computational approaches show promise in automatically measuring social behaviors within natural settings. This study aims to automatically measure social gaze features from videos of dyadic conversations, characterize autism-related differences, and capture individual-level differences. 46 autistic Participants and 36 neurotypical Participants, aged 8-29 years, engaged in a brief video-recorded conversation with a research staff member (Partner). An automated social gaze detector was trained to detect whether each partner was looking at the other and achieved 89% cross-validated accuracy with human annotations. Comparing detailed automatic gaze measurements, autistic Participants spent less time looking at Partners and engaging in mutual gaze than neurotypical Participants did. They also initiated mutual gaze less frequently and had shorter mutual gaze episodes, but did not differ in mutual gaze counts. A social gaze summary score fusing individual variables correlated specifically with ADOS-2 Social Affect scores and not Restricted and Repetitive Behavior scores. A cross-validated multivariate classification model using gaze features was able to make individual-level diagnostic prediction (autism versus neurotypical) with 73% accuracy. This study provides a framework for automatically quantifying social gaze behaviors with high granularity and demonstrates its use in psychiatric research. This framework has a potential for enhancing measurement of social skills and tracking therapeutic progress in autism and other psychiatric conditions.
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Registered trials
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