Patters of use and key predictors for the use of wearable health care devices by US adults: insights from a national survey

Article


Chandrasekaran, R., Katthula, V. and Moustakas, E. 2020. Patters of use and key predictors for the use of wearable health care devices by US adults: insights from a national survey. Journal of Medical Internet Research. 22 (10). https://doi.org/10.2196/22443
TypeArticle
TitlePatters of use and key predictors for the use of wearable health care devices by US adults: insights from a national survey
AuthorsChandrasekaran, R., Katthula, V. and Moustakas, E.
Abstract

Background: Despite 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.
Objective: The 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.
Methods: Using 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.
Results: About 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.
Conclusions: The 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
[Abstract copyright: ©Ranganathan Chandrasekaran, Vipanchi Katthula, Evangelos Moustakas. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.10.2020.]

KeywordsHINTS, health technology adoption and use, mobile health, smart wearables, wearable healthcare devices
PublisherJMIR Publications
JournalJournal of Medical Internet Research
ISSN1438-8871
Publication dates
Print16 Oct 2020
Publication process dates
Deposited30 Oct 2020
Submitted12 Jul 2020
Accepted26 Jul 2020
Output statusPublished
Publisher's version
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Copyright Statement

©Ranganathan Chandrasekaran, Vipanchi Katthula, Evangelos Moustakas. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.10.2020. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

Digital Object Identifier (DOI)https://doi.org/10.2196/22443
LanguageEnglish
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