Currently submitted to: JMIR Formative Research
Date Submitted: Nov 28, 2025
Open Peer Review Period: Jan 3, 2026 - Feb 28, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Clinical Implementation of Wearable-Derived Sleep and Activity Reporting for Inpatient Psychiatric Monitoring
ABSTRACT
Background:
Sleep is a core component of psychiatric assessment, yet inpatient monitoring typically relies on brief observational checks that are subjective, variable, and sometimes disruptive. Wearable devices offer a means of capturing continuous, objective sleep and activity data without disturbing patients. Although digital health technologies are increasingly used in psychiatric research, little is known about how wearable-derived data can be integrated into routine inpatient workflows or used meaningfully by clinicians.
Objective:
This implementation aimed to evaluate the feasibility, usability, and workflow integration of a wearable-derived sleep and activity reporting system within an adult psychiatric inpatient unit.
Methods:
The implementation unfolded in two phases on a 21-bed inpatient unit at a psychiatric hospital in Massachusetts, USA. Patients were offered a wrist-worn GENEActiv actigraphy device upon admission. Raw accelerometry data were processed using the DPSleep pipeline to derive daily sleep and activity metrics for patients participating in the implementation. Sleep and activity reports combining graphical summaries and natural language summaries of sleep, activity, and medication data were iteratively refined and delivered to psychiatrists providing patient care. Semi-structured qualitative interviews were conducted with clinicians and unit staff to gather feedback on the sleep and activity report prototype and discuss barriers and facilitators to implementation. Interview data were coded and analyzed by a team of two.
Results:
During the first phase of the implementation, 155 patients were admitted, 88 (56% of admits) were offered a device, and 68 (77% of admits offered a device) accepted. Sleep and activity reports were generated for 42 patients (62% of patients wearing a device) during this phase. During the second phase of the implementation, automation reduced report generation time from approximately five days to under 24 hours. Only one of the three psychiatrists assigned to the unit regularly used the reports in routine care. Reports were most useful for reconciling discrepancies between patient and nursing sleep estimates and for supporting clinical conversations about sleep patterns and medication adherence between clinician and patient. Clinicians who had not yet used the reports expressed conceptual interest but emphasized the need for integration in the electronic medical record, reliably available “last-night” sleep data, and simplified design. Barriers included challenges in the speed, reliability, and clarity of data; variable staff buy-in; and disconnects between the research and clinical teams running the implementation.
Conclusions:
Wearable-derived sleep and activity data reporting is feasible in inpatient psychiatry and offers clinically meaningful insights, particularly when patient and staff sleep reports conflict. Sustainable use is more likely with near-instantaneous data transfer, electronic medical record integration, and shared implementation ownership across staff levels. Clinical Trial: Not applicable
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