Evidence map›Paper›PMID 42766331›Full record

ArticleJMIR formative research2026

Clinical Implementation of Wearable-Derived Sleep and Activity Reporting for Inpatient Psychiatric Monitoring.

Brien William Culhane, Robert Dennis Patterson, Habiballah Rahimi-Eichi, Agustin Go Yip, Kayla Huesman, Kristin Kostick-Quenet, Joshua Salvi, Philippe Beauchamp, Kerry James Ressler, Justin Taylor Baker

Abstract read
In one paragraph

Article in JMIR formative research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Brien William CulhaneInstitute for Technology in Psychiatry, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, United States, 1 617-855-3913.ORCID 0009-0007-3985-0992
Robert Dennis PattersonInstitute for Technology in Psychiatry, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, United States, 1 617-855-3913.ORCID 0000-0001-5663-9004
Habiballah Rahimi-EichiInstitute for Technology in Psychiatry, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, United States, 1 617-855-3913.ORCID 0000-0002-4575-0273
Agustin Go YipInstitute for Technology in Psychiatry, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, United States, 1 617-855-3913.ORCID 0000-0003-2641-3439
Kayla HuesmanInstitute for Technology in Psychiatry, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, United States, 1 617-855-3913.ORCID 0009-0008-3896-3335
Kristin Kostick-QuenetCenter for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States.ORCID 0000-0003-2510-0174
Joshua SalviInstitute for Technology in Psychiatry, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, United States, 1 617-855-3913.ORCID 0000-0002-5140-7746
Philippe BeauchampDepartment of Psychiatry, McGill University, Quebec City, QC, Canada.ORCID 0009-0007-4268-4710
Kerry James ResslerInstitute for Technology in Psychiatry, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, United States, 1 617-855-3913.ORCID 0000-0002-5158-1103
Justin Taylor BakerInstitute for Technology in Psychiatry, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, United States, 1 617-855-3913.ORCID 0000-0002-6629-2195

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 2 phases at a single 21-bed adult inpatient unit at a psychiatric hospital in Massachusetts. 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. Semistructured qualitative interviews were conducted with clinicians and unit staff to gather feedback on the sleep and activity report prototype and discuss barriers to and facilitators of implementation. Interview data were coded and analyzed by a team of 2. Unlabelled: During phase 1 of the implementation, 155 patients were admitted, of whom 88 (56.8%) were offered a device and 68 (77.3%) accepted it. Sleep and activity reports were generated for 61.8% (42/68) of patients wearing a device during this phase. During phase 2 of the implementation, automation reduced report generation time from approximately 5 days to under 24 hours. Only 1 of the 3 psychiatrists on 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 the data; variable staff buy-in; and disconnects between the research and clinical teams running the implementation. Conclusions: This implementation suggests that wearable-derived sleep and activity data reporting is technically feasible in inpatient psychiatry. This data reporting potentially offers clinically meaningful insights. Use of the reports was concentrated in 1 of the 3 psychiatrists on the unit, who served as an early adopter and project champion (AGY). Sustainable use and broad clinical uptake are more likely with reliable, near-instantaneous data transfer; electronic medical record integration; and shared implementation ownership across staff levels.

Indexed as

InpatientsSleepWearable Electronic DevicesActigraphyAdultDigital HealthFeasibility StudiesFemaleHospitals, PsychiatricHumansMaleMassachusettsMental DisordersMiddle AgedMonitoring, PhysiologicQualitative Researchactigraphybehavioral measurementdigital health technologyimplementationinpatientpsychiatricsleepwearable

Identifiers

PMID42766331
PMCPMC13592238

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.