BMC Psychiatry. 2026 Jun 6. doi: 10.1186/s12888-026-08255-y. Online ahead of print.
ABSTRACT
BACKGROUND: Early identification of autism spectrum disorder (ASD) is essential for improving developmental outcomes but remains challenging due to diagnostic delays, subjectivity, and resource limitations. Eye-tracking offers objective indices of social attention and could improve access to early screening when deployed on consumer devices at home. This scoping review synthesizes evidence on home-deployable eye-tracking as digital biomarkers for early ASD screening, associated machine learning methods, and feasibility of real-world implementation.
METHODS: Following the Arksey and O'Malley framework and Joanna Briggs Institute (JBI) methodology, reported per PRISMA Extension for Scoping Reviews (PRISMA-ScR), we searched PubMed and Scopus (2015-2025) for English-language human studies using terms for autism, eye-tracking, and home-based assessment. Using a Population, Concept, Context (PCC) framework (Population: infants/ children; Concept: eye-tracking as digital biomarker; Context: home/ clinical settings), two reviewers screened each record and charted data on participant characteristics, stimuli, devices, analytic methods, diagnostic performance, and implementation indicators. Extracted data, including diagnostic performance metrics (PPV, NPV, confidence intervals), study design classifications, validation methods, and biomarker readiness ratings, are provided in full in Supplementary Tables S2-S6. The protocol was preregistered on the Open Science Framework (OSF Registries osf.io/mdz2e/; https://doi.org/10.17605/OSF.IO/MDZ2E). Searches were last executed on 1 August 2025. A process-based estimation approach was used to quantify the EOL carbon footprint of two timber floor systems-Adhesive & Screw and Sharp Plate & Screw, following ISO 14040/44 standards. Four realistic EOL pathways (landfilling, downcycling, component reuse, and full assembly reuse) were assessed under three recovery-rate scenarios (90%, 60%, and 30%) to capture both ideal deconstruction and conventional demolition conditions. EOL impacts, biogenic carbon flows, and Stage D credits (potential environmental benefits beyond building life) were integrated to determine the EOL climate outcomes.
RESULTS: Across 90 studies, reported discrimination typically ranged from moderate to high. Sample sizes varied from small pilots to large datasets (n = 30-1,000+), with ages from 5 months to 18 years. Studies were categorized by system type: hardware-based, wearable, webcam-based, and home-deployed. By study purpose, studies ranged from prospective screening evaluations and internally validated case-control classification studies to exploratory group-difference analyses and feasibility evaluations; the majority fall into the latter two categories. Common tasks included faces/social scenes, biological motion, and joint-attention cues; frequently reported metrics included fixation proportion, dwell time, saccade dynamics, and interest-area contrasts (eyes/face vs. objects). Supervised learning (e.g. SVM, random forests) and deep learning pipelines were used, though external validation and calibration-robustness were inconsistently reported. Practical barriers included ambient-light variability, viewing distance, caregiver facilitation, device heterogeneity, and data privacy/governance.
CONCLUSION: This review mapped 90 studies across four eye-tracking platform stages to assess translational readiness for home-based ASD screening. Gaze-based biomarkers carry robust discriminative signal, but the evidence derives almost entirely from laboratory-based, case-control studies. Only three studies collected data in home-deployed settings, none with externally validated accuracy. Priorities include prospective multisite home-based trials with prespecified endpoints, standardised stimulus protocols, evaluation of model robustness to distribution shift, and navigation of jurisdiction-specific regulatory pathways. Limitations include English-only sourcing, two databases, the 2015-2025 window, and lack of critical appraisal.
CLINICAL TRIAL NUMBER: Not Applicable.
PMID:42251334 | DOI:10.1186/s12888-026-08255-y