PASSIVE SENSING AND WEARABLES FOR BURNOUT-RELATED OUTCOMES IN HEALTH CARE WORKERS: A STRUCTURED NARRATIVE REVIEW OF DIGITAL BIOMARKERS, IMPLEMENTATION BARRIERS, AND ETHICAL GOVERNANCE
DOI:
https://doi.org/10.31435/ijitss.1(49).2026.5346Keywords:
Digital Phenotyping, Health Care Workers, Wearable Devices, Burnout, Passive Sensing, Workplace Mental HealthAbstract
Burnout in health care workers is usually monitored through intermittent self-report instruments, which makes early recognition of occupational distress difficult and often delays intervention. Wearables, smartwatches, and other forms of passive sensing offer a more continuous approach to tracking sleep, physiological stress, activity, and recovery patterns that may precede clinically relevant deterioration in well-being. This structured narrative review synthesizes current evidence on passive sensing and wearable technologies for burnout-related outcomes in health care workers, with particular attention to digital biomarkers, implementation barriers, organizational moderators, and ethical governance. The review corpus combines direct sensing studies in physicians, residents, and nurses with contextual literature on workplace interventions, resilience, documentation burden, digital phenotyping ethics, and workplace biosensors. Current direct evidence remains limited. Existing studies do not yet support a stable physiological biomarker of burnout itself. Stronger and more consistent signals appear for acute stress, depressive trajectories, resilience-related patterns, sleep disruption, and recovery. A randomized clinical trial suggests that smartwatch-supported self-monitoring may improve physician burnout and resilience, while feasibility research shows that adherence depends heavily on device fit, workflow compatibility, and perceived personal value. Overall, wearables appear more mature as tools for monitoring stress, sleep, and resilience than for directly predicting burnout. Their future value will depend on stronger reporting standards, integration of workplace-context data, and transparent, non-punitive governance that prioritizes trust.
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Copyright (c) 2026 Natalia Malatyńska, Michał Babicz, Kamil Chudzicki, Wiktor Czyżewski, Daria Danielczyk, Agata Słoma, Anna Szot, Dominik Szydełko, Martyna Szymczyk, Paweł Żurek
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