Evidence map›Paper›PMID 42268609›Full record

ArticleJAMA network open2026

Wearable Devices and Data Sharing in the US.

Aline F Pedroso, Lovedeep S Dhingra, Arya Aminorroaya, Rohan Khera

Abstract read
In one paragraph

Article in JAMA network open, 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

4 authors.

Aline F PedrosoSection of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
Lovedeep S DhingraSection of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
Arya AminorroayaSection of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
Rohan KheraSection of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.

Funding

Deep learning enhanced detection and personalized monitoring of aortic stenosis - The DETECT-AS StudyR01AG089981 · NIA · YALE UNIVERSITY · PI Rohan Khera · 2024 to 2026
$2.4M
Translating Personalized Inference from Randomized Clinical Trials to Real-World Cardiovascular CareR01HL167858 · NHLBI · YALE UNIVERSITY · PI Rohan Khera · 2024 to 2026
$2.3M
Evaluating and Improving Utilization of Evidence-Based Medical Therapy in Patients with Heart Failure using Automated Tools in the Electronic Health RecordK23HL153775 · NHLBI · YALE UNIVERSITY · PI KHERA, ROHAN · 2021 to 2025
$918k
NHLBI NIH HHS K23 HL153775NHLBI NIH HHS R01 HL167858NIA NIH HHS R01 AG089981
6 · The paper itself

Abstract

Importance: Large-scale efforts to expand the role of wearables in digital health require a contemporary assessment of patterns and drivers of wearable use, willingness to share data, and actual data sharing. Objective: To characterize national trends in wearable device use, daily engagement, willingness to share wearable-derived health data, and actual sharing with clinicians among US adults from 2020 to 2024. Design, Setting, and Participants: This serial survey study used data from 3 consecutive cycles of the Health Information National Trends Survey (HINTS), a nationally representative, population-based survey of community-dwelling US adults, from 2020, 2022, and 2024. Main Outcomes and Measures: The primary outcomes were use of a wearable device to track health, daily wearable utilization, willingness to share wearable data with clinicians, and actual sharing of personal health information with clinicians among users. Longitudinal trends were evaluated in the overall US adult population, among individuals with cardiovascular disease (CVD) or major CVD risk factors, and across sociodemographic subgroups using the Rao-Scott χ2 test. Survey analyses evaluated contemporary drivers of wearable use and data-sharing behaviors. Results: There were 3865, 6252, and 7278 HINTS participants across the 3 survey cycles, representing 254 million US adults in 2020, 258 million in 2022, and 262 million in 2024. The weighted mean (SD) age of wearable users was 48.7 (18.1) years, 55.3% (95% CI, 52.3%-58.2%) were women, and 62.3% (95% CI, 60.9%-63.7%) had CVD or risk factors. Wearable use increased from 30.2% (95% CI, 27.6%-32.7%) in 2020 to 41.1% (95% CI, 39.0%-43.2%) in 2024, with similar upward trends among adults with CVD or risk factors. Among users, daily use remained low, with approximately one-half of users reporting daily use, and did not increase over time. Willingness to share wearable data was high but declined from 81.3% (95% CI, 77.1%-85.5%) to 73.4% (95% CI, 70.7%-76.2%), whereas actual sharing remained low across cycles (from 14.2% [95% CI, 12.4%-16.0%] in 2020 to 19.2% [95% CI, 17.7%-20.6%] in 2024). In adjusted analyses, wearable use increased by 30% per 2-year interval (adjusted odds ratio, 1.30; 95% CI, 1.19-1.41), but daily use, willingness to share data, or actual data sharing showed no meaningful change. Temporal trends were consistent across sociodemographic subgroups of age, sex, race and ethnicity, and income. In 2024, higher digital literacy was associated with greater willingness to share, but not with actual data sharing. Conclusions and Relevance: In this serial survey study, wearable device use increased among US adults, but daily use and clinician-directed data sharing remained limited. These findings suggest that there is a need for approaches to help realize the potential of wearable devices as health care tools, both by broadening uptake and promoting consistent use.

Indexed as

Digital HealthInformation DisseminationWearable Electronic DevicesAdultAgedCardiovascular DiseasesFemaleHumansMaleMiddle AgedSurveys and QuestionnairesUnited States

Identifiers

PMID42268609
PMCPMC13254737

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.