Evidence map›Paper›PMID 40825226›Full record

ArticleJournal of medical Internet research2025

Determinants of Continuous Smartwatch Use and Data-Sharing Preferences With Physicians, Public Health Authorities, and Private Companies: Cross-Sectional Survey of Smartwatch Users.

Anthony James Goodings, Kayode Philip Fadahunsi, Derjung M Tarn, Jennifer Lutomski, Allison Chhor, Frances Shiely, Patrick Henn, John O'Donoghue

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. 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

8 authors.

Anthony James GoodingsSchool of Medicine, University College Cork, Cork, Ireland.ORCID http://orcid.org/0009-0005-9702-0968
Kayode Philip FadahunsiDepartment of Primary Care and Public Health, Imperial College London, London, United Kingdom.ORCID http://orcid.org/0000-0003-1470-5493
Derjung M TarnDavid Geffen School of Medicine at UCLA, University of California, Los Angeles, 10880 Wilshire Blvd, Suite 1800, Los Angeles, CA, 90024, United States, 1 (310) 794-8242.ORCID http://orcid.org/0000-0001-7426-6387
Jennifer LutomskiDepartment of Emergency and Critical Health Care, HAN University of Applied Sciences, Nijmegen, The Netherlands.ORCID http://orcid.org/0000-0002-1963-5749
Allison ChhorFaculty of Medicine, University of Ottawa, Ottawa, ON, Canada.ORCID http://orcid.org/0009-0004-4042-6628
Frances ShielyHRB Clinical Research Facility and School of Public Health, University College Cork, Cork, Ireland.ORCID http://orcid.org/0000-0003-0969-8321
Patrick HennSchool of Medicine, University College Cork, Cork, Ireland.ORCID http://orcid.org/0000-0001-5958-6163
John O'DonoghueMalawi eHealth Research Centre, Mzuzu University, Mzuzu, Malawi.ORCID http://orcid.org/0000-0001-6056-8640

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Smartwatches are widely adopted globally for tracking health metrics, offering potential for enhancing individual health care and public health efforts. Continuous use of the devices and users' willingness to share the data collected are critical to realizing their full benefits. Objective: This study aimed to identify key factors that determine continuous smartwatch use and users' comfort levels in sharing health data with health care providers and public health authorities. Methods: A cross-sectional online survey of current and past smartwatch users (aged >18 years) was conducted to assess determinants of continuous use based on the Expectation-Confirmation Model (ECM) and user comfort levels with different data-sharing methods. Structural equation modeling was used to evaluate relationships between habit formation, satisfaction, perceived enjoyment, and perceived usefulness with continuous use. Wilcoxon signed-rank tests were used to analyze user comfort in sharing data, comparing noninternet- versus internet-based sharing methods and fully versus partially anonymized data. Results: A total of 273 responses were analyzed, with participants aged 18-65 (mean 35.6, SD 11.7) years. The results indicate that continuous use of smartwatches is explained by habit (β=.35; P<.001) and satisfaction (β=.38; P<.001), which is in turn explained by perceived usefulness (β=.38; P<.001), perceived enjoyment (β=.32; P<.001), confirmation (β=.24; P<.001), and perceived usability (β=.10; P=.03). Smartwatch users preferred noninternet-based sharing options (z=-5.793; P<.001) when sharing data with their physician. Similarly, users were more comfortable sharing fully anonymized data with public health authorities than partially anonymized data (z=-3.592; P<.001). Conclusions: Habit formation and satisfaction emerged as pivotal drivers of continuous intention to use smartwatches, emphasizing the need for features that foster integration into daily routine and a rewarding user experience. Preferences for noninternet-based data sharing with physicians highlight privacy concerns that must be addressed to build users' trust. By aligning device features and data-sharing protocols with user preferences, manufacturers, health care providers, and policy makers can enhance user engagement and maximize the potential of smartwatches to support individual health management and public health initiatives.

Indexed as

Information DisseminationPhysiciansPublic HealthWearable Electronic DevicesAdolescentAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung Adultconfidentialitycontinuous usecross-sectionaldata anonymizationdata sharingdigital healthexpectation-confirmation modelhealth behavioronline surveyperceived enjoymentphysicianspreferencesprivacyprivate companypublic health authoritiessmartwatchsmartwatchessmartwatch usestructural equation modelingsurveystelemedicineuser engagementusersuser satisfactionwearable electronic deviceswearableswearable technology

Identifiers

PMID40825226
PMCPMC12360733

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.