Evidence map›Paper›PMID 33064083›Full record

ArticleJournal of medical Internet research2020

Patterns of Use and Key Predictors for the Use of Wearable Health Care Devices by US Adults: Insights from a National Survey.

Ranganathan Chandrasekaran, Vipanchi Katthula, Evangelos Moustakas

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05966857 (FAPO-X), which is not on this map. Cited by 130 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
130citing papers in PubMed, 4 pooled it
34.5field-weighted citation impact, top 1% of its field
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.

NCT05966857 nacompletednot on this mapstarted 2023, after this paper: background citation

FAPO-X: Assisted Digital Telemonitoring With Wearables in Patients After Cardiovascular Surgery

TypeinterventionalSponsorUniversity of Sao PauloRan2023 to 2023Enrolled108ConditionsHeart, Surgery, Heart, Functional Disturbance as ResultArmsWearable: Smartwatch
3 · Its place in the literature

Who cites it

130 citing papers in PubMed, 4 syntheses or guidelines pooled it, 257 citations in OpenAlex.

  1. Inequalities in Exclusively Mobile Interventions Targeting Weight-Related Behaviors: Systematic Review of Observational Studies.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
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  7. Comparing sleep measures in cancer survivors: self-reported sleep diary versus objective wearable sleep tracker.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
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  10. Overdiagnosis in atrial fibrillation screening with wearables.Scandinavian journal of primary health care · 2026
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  13. Demographic and Socioeconomic Factors Associated with Fitbit Ownership in the NIHInternational journal of environmental research and public health · 2026
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70 more citing papers are in PubMed but not listed here.

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

3 authors at 2 institutions in 2 countries.

Ranganathan ChandrasekaranDepartment of Information & Decision Sciences, University of Illinois at Chicago, Chicago, IL, United States.ORCID 0000-0003-2001-578X
Vipanchi KatthulaDepartment of Information & Decision Sciences, University of Illinois at Chicago, Chicago, IL, United States.ORCID 0000-0002-4939-4333
Evangelos MoustakasMiddlesex University Dubai, Dubai, United Arab Emirates.ORCID 0000-0002-2671-9035
University of Illinois Chicago · USMiddlesex University Dubai · AE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the growing popularity of wearable health care devices (from fitness trackes such as Fitbit to smartwatches such as Apple Watch and more sophisticated devices that can collect information on metrics such as blood pressure, glucose levels, and oxygen levels), we have a limited understanding about the actual use and key factors affecting the use of these devices by US adults.

objectiveThe main objective of this study was to examine the use of wearable health care devices and the key predictors of wearable use by US adults.

methodsUsing a national survey of 4551 respondents, we examined the usage patterns of wearable health care devices (use of wearables, frequency of their use, and willingness to share health data from a wearable with a provider) and a set of predictors that pertain to personal demographics (age, gender, race, education, marital status, and household income), individual health (general health, presence of chronic conditions, weight perceptions, frequency of provider visits, and attitude towards exercise), and technology self-efficacy using logistic regression analysis.

resultsAbout 30% (1266/4551) of US adults use wearable health care devices. Among the users, nearly half (47.33%) use the devices every day, with a majority (82.38% weighted) willing to share the health data from wearables with their care providers. Women (16.25%), White individuals (19.74%), adults aged 18-50 years (19.52%), those with some level of college education or college graduates (25.60%), and those with annual household incomes greater than US $75,000 (17.66%) were most likely to report using wearable health care devices. We found that the use of wearables declines with age: Adults aged >50 years were less likely to use wearables compared to those aged 18-34 years (odds ratios [OR] 0.46-0.57). Women (OR 1.26, 95% CI 0.96-1.65), White individuals (OR 1.65, 95% CI 0.97-2.79), college graduates (OR 1.05, 95% CI 0.31-3.51), and those with annual household incomes greater than US $75,000 (OR 2.6, 95% CI 1.39-4.86) were more likely to use wearables. US adults who reported feeling healthier (OR 1.17, 95% CI 0.98-1.39), were overweight (OR 1.16, 95% CI 1.06-1.27), enjoyed exercise (OR 1.23, 95% CI 1.06-1.43), and reported higher levels of technology self-efficacy (OR 1.33, 95% CI 1.21-1.46) were more likely to adopt and use wearables for tracking or monitoring their health.

conclusionsThe potential of wearable health care devices is under-realized, with less than one-third of US adults actively using these devices. With only younger, healthier, wealthier, more educated, technoliterate adults using wearables, other groups have been left behind. More concentrated efforts by clinicians, device makers, and health care policy makers are needed to bridge this divide and improve the use of wearable devices among larger sections of American society.

Indexed as

AdolescentAdultFemaleHumansMaleMiddle AgedSurveys and QuestionnairesUnited StatesWearable Electronic DevicesYoung Adulthealth technology adoption and useHINTSmobile healthsmart wearableswearable healthcare devices

Identifiers

PMID33064083
PMCPMC7600024
OpenAlexW3043921266

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.