Evidence map›Paper›PMID 42413039›Full record

ArticleJMIR formative research2026

Evaluating Wearable Devices for Remote Monitoring in Psychosis: Pilot Study Nested Within the CONNECT Cohort Study.

Siân Bladon, John Ainsworth, Roberto Cahuantzi, Matteo Cella, Richard J Drake, Emily Eisner, Richard Emsley, Sophie Faulkner, Kathryn Greenwood, Andrew Gumley and 13 more

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

23 authors.

Siân BladonDivision of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Vaughan House, Manchester, United Kingdom.ORCID 0000-0001-9087-6505
John AinsworthDivision of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Vaughan House, Manchester, United Kingdom.ORCID 0000-0002-2187-9195
Roberto CahuantziDivision of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Vaughan House, Manchester, United Kingdom.ORCID 0000-0002-0212-6825
Matteo CellaDepartment of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.ORCID 0000-0002-5701-0336
Richard J DrakeDivision of Psychology and Mental Health, School of Health Sciences, University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PY, United Kingdom, 441613066000, ext 60422.ORCID 0000-0003-0220-4835
Emily EisnerDivision of Psychology and Mental Health, School of Health Sciences, University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PY, United Kingdom, 441613066000, ext 60422.ORCID 0000-0001-5164-2407
Richard EmsleyDepartment of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.ORCID 0000-0002-1218-675X
Sophie FaulknerDivision of Psychology and Mental Health, School of Health Sciences, University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PY, United Kingdom, 441613066000, ext 60422.ORCID 0000-0003-1549-0922
Kathryn GreenwoodSchool of Psychology, University of Sussex, Falmer, United Kingdom.ORCID 0000-0001-7899-8980
Andrew GumleySchool of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.ORCID 0000-0002-8888-938X
Gillian HaddockDivision of Psychology and Mental Health, School of Health Sciences, University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PY, United Kingdom, 441613066000, ext 60422.ORCID 0000-0001-6234-5774
Kimberley KendallCentre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom.ORCID 0000-0002-6755-6121
Alex KennyMcPin Foundation, London, United Kingdom.ORCID 0000-0002-0162-9009
Jane LeesDivision of Psychology and Mental Health, School of Health Sciences, University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PY, United Kingdom, 441613066000, ext 60422.ORCID 0000-0001-5009-4066
Shôn LewisDivision of Psychology and Mental Health, School of Health Sciences, University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PY, United Kingdom, 441613066000, ext 60422.ORCID 0000-0003-1861-4652
Glen P MartinDivision of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Vaughan House, Manchester, United Kingdom.ORCID 0000-0002-3410-9472
Matthias SchwannauerSchool of Health in Social Science, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-4683-2596
Matthew SperrinDivision of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Vaughan House, Manchester, United Kingdom.ORCID 0000-0002-5351-9960
James T R WaltersCentre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom.ORCID 0000-0002-6980-4053
Annabel E L WalshMcPin Foundation, London, United Kingdom.ORCID 0000-0002-6503-7969
Pauline WhelanDivision of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Vaughan House, Manchester, United Kingdom.ORCID 0000-0001-8689-3919
Til WykesDepartment of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.ORCID 0000-0002-5881-8003
Sandra BucciDivision of Psychology and Mental Health, School of Health Sciences, University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PY, United Kingdom, 441613066000, ext 60422.ORCID 0000-0002-6197-5333

Funding

Wellcome 222875/Z/21/Z
6 · The paper itself

Abstract

Background: Digital remote monitoring technologies, including smartphones and wearables, offer promising avenues for early detection of psychosis relapse. However, selecting devices that are acceptable to participants and produce high-quality data remains challenging. Objective: The aim of this nested pilot study was to assess the acceptability and data quality of 3 commercially available wearable devices in people with psychosis recruited to the CONNECT cohort study. Methods: Participants recruited to the CONNECT study before July 31, 2024, were included in the pilot study and selected 1 of 3 wearable devices: a Fitbit Charge 5, Samsung Galaxy Watch 5, or Apple Watch SE. Baseline demographics were compared between device groups. Acceptability of devices to participants was assessed through a Wearable Device Satisfaction Questionnaire after 3 months of use, with the proportion of positive responses to each question calculated and compared. Data completeness was also assessed by calculating the number (and percentage) of valid days of step count, heart rate, and sleep data, and comparing between groups. Data quality was assessed through summarizing the amount of troubleshooting required, additional metrics available from the wearables, and continuity of data completeness by calculating the proportion of participants with at least 3 days of heart rate data per week for the first 20 weeks of follow-up. Predefined criteria were used to determine the next steps for the wider CONNECT study: if one device was superior, this would be selected; if none were found to be superior and the Fitbit was found to be noninferior, then Fitbit would be retained. Results: Of the first 107 participants recruited to CONNECT, 105 were included in the pilot study evaluation. The Samsung Galaxy Watch was selected most frequently by participants (46/105, 43.8%), followed by the Apple Watch (27/105, 25.7%), and Fitbit Charge (23/105, 21.9%). Differences in participant demographics were observed across device groups. Self-reported acceptability after use did not differ substantially between devices. However, in terms of data completeness, the median proportion of valid heart rate data days was significantly lower for Samsung Galaxy (median 31.2%, IQR 8.5%-46.0%) compared to Fitbit (median 80.1%, IQR 26.7%-95.0%; P=.003) and Apple Watch (median 49.3%, IQR 21.5%-86.0%; P=.02). There was no significant difference between Fitbit and Apple Watch. Similar patterns were observed for step count and sleep data. The Samsung Galaxy Watch required more frequent troubleshooting for data flow issues and lacked additional physiological metrics, available from the other devices. Conclusions: Due to comparatively lower data quality and technical performance, the Samsung Galaxy Watch was discontinued for use in the subsequent phase of the CONNECT study. The study highlights the importance of incorporating nested evaluations of devices in long-term research.

Indexed as

Psychotic DisordersWearable Electronic DevicesAdultCohort StudiesDigital HealthFemaleHumansMaleMiddle AgedPilot ProjectsRemote Patient MonitoringSurveys and Questionnairesdigital remote monitoringfitness trackerpassive sensingpsychosisschizophrenia spectrum disorderssevere mental illnesssmartwatchwearable devices

Identifiers

PMID42413039
PMCPMC13340901

What OpenQuestion holds

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LicenceCC BY
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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.