Evidence map›Paper›PMID 39773905›Full record

SynthesisJMIR mental health2025

Utility of Consumer-Grade Wearable Devices for Inferring Physical and Mental Health Outcomes in Severe Mental Illness: Systematic Review.

Lamiece Hassan, Alyssa Milton, Chelsea Sawyer, Alexander J Casson, John Torous, Alan Davies, Bernalyn Ruiz-Yu, Joseph Firth

Abstract readSystematic Review
In one paragraph

Synthesis in JMIR mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Review
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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

8 authors.

Lamiece HassanSchool for Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-5888-422X
Alyssa MiltonCentral Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-4326-0123
Chelsea SawyerSchool for Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0003-2596-1580
Alexander J CassonDepartment of Electrical and Electronic Engineering, School of Engineering, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0003-1408-1190
John TorousBeth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0002-5362-7937
Alan DaviesSchool for Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0001-5737-5629
Bernalyn Ruiz-YuBoston Children's Hospital, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0003-3267-6171
Joseph FirthSchool for Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-0618-2752

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital wearable devices, worn on or close to the body, have potential for passively detecting mental and physical health symptoms among people with severe mental illness (SMI); however, the roles of consumer-grade devices are not well understood.

objectiveThis study aims to examine the utility of data from consumer-grade, digital, wearable devices (including smartphones or wrist-worn devices) for remotely monitoring or predicting changes in mental or physical health among adults with schizophrenia or bipolar disorder. Studies were included that passively collected physiological data (including sleep duration, heart rate, sleep and wake patterns, or physical activity) for at least 3 days. Research-grade actigraphy methods and physically obtrusive devices were excluded.

methodsWe conducted a systematic review of the following databases: Cochrane Central Register of Controlled Trials, Technology Assessment, AMED (Allied and Complementary Medicine), APA PsycINFO, Embase, MEDLINE(R), and IEEE XPlore. Searches were completed in May 2024. Results were synthesized narratively due to study heterogeneity and divided into the following phenotypes: physical activity, sleep and circadian rhythm, and heart rate.

resultsOverall, 23 studies were included that reported data from 12 distinct studies, mostly using smartphones and centered on relapse prevention. Only 1 study explicitly aimed to address physical health outcomes among people with SMI. In total, data were included from over 500 participants with SMI, predominantly from high-income countries. Most commonly, papers presented physical activity data (n=18), followed by sleep and circadian rhythm data (n=14) and heart rate data (n=6). The use of smartwatches to support data collection were reported by 8 papers; the rest used only smartphones. There was some evidence that lower levels of activity, higher heart rates, and later and irregular sleep onset times were associated with psychiatric diagnoses or poorer symptoms. However, heterogeneity in devices, measures, sampling and statistical approaches complicated interpretation.

conclusionsConsumer-grade wearables show the ability to passively detect digital markers indicative of psychiatric symptoms or mental health status among people with SMI, but few are currently using these to address physical health inequalities. The digital phenotyping field in psychiatry would benefit from moving toward agreed standards regarding data descriptions and outcome measures and ensuring that valuable temporal data provided by wearables are fully exploited.

trial registrationPROSPERO CRD42022382267; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=382267.

Indexed as

Wearable Electronic DevicesBipolar DisorderExerciseHeart RateHumansMental DisordersMental HealthSchizophreniabipolar disorderdigital phenotypingmental healthmobile healthphysical healthpsychiatrypsychosisremote monitoringschizophreniasevere mental illnesssleepsmartphoneSMItelehealthwearable

Identifiers

PMID39773905
PMCPMC11751658

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.