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Wearable Use in an Observational Study Among Older Adults: Adherence, Feasibility, and Effects of Clinicodemographic Factors.

作者信息

Paolillo Emily W, Lee Shannon Y, VandeBunte Anna, Djukic Nina, Fonseca Corrina, Kramer Joel H, Casaletto Kaitlin B

机构信息

Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States.

Department of Psychology, Palo Alto University, Palo Alto, CA, United States.

出版信息

Front Digit Health. 2022 Jun 10;4:884208. doi: 10.3389/fdgth.2022.884208. eCollection 2022.


DOI:10.3389/fdgth.2022.884208
PMID:35754462
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9231611/
Abstract

INTRODUCTION: Wearables have great potential to improve monitoring and delivery of physical activity interventions to older adults with downstream benefits to multisystem health and longevity; however, benefits obtained from wearables depend on their uptake and usage. Few studies have examined person-specific factors that relate to wearable adherence. We characterized adherence to using a wearable activity tracker for 30 days and examined associations between adherence and demographics, cognitive functioning, brain volumes, and technology familiarity among community-dwelling older adults. METHODS: Participants were 175 older adults enrolled in the UCSF Longitudinal Brain Aging Study who were asked to wear a Fitbit Flex 2 during waking hours for 30 days. Sixty two of these participants were also asked to sync their devices to the Fitbit smartphone app daily to collect minute-level data. We calculated adherence to wearing the Fitbit daily (i.e., proportion of days with valid activity data) and adherence to daily device syncing (i.e., proportion of days with minute-level activity data). Participants also completed a brain MRI and in-person cognitive testing measuring memory, executive functioning, and processing speed. Spearman correlations, Wilcoxon rank sum tests, and logistic regression tested relationships between wearable adherence and clinicodemographic factors. RESULTS: Participants wore the Fitbits for an average of 95% of study days and were 85% adherent to the daily syncing protocol. Greater adherence to wearing the device was related to female sex. Greater adherence to daily device syncing was related to better memory, independent of demographic factors. Wearable adherence was not significantly related to age, education, executive functioning, processing speed, brain gray matter volumes, or self-reported familiarity with technology. Participants reported little-to-no difficulty using the wearable and all reported willingness to participate in another wearable study in the future. CONCLUSIONS: Older adults have overall high adherence to wearable use in the current study protocol. Person-specific factors, however, may represent potential barriers to equitable uptake of wearables for physical activity among older adults, including demographics and cognitive functioning. Future studies and clinical providers utilizing wearable activity trackers with older adults may benefit from implementation of reminders (e.g., texts, calls) for device use, particularly among men and individuals with memory impairment.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/345d/9231611/6ec5fa95dfed/fdgth-04-884208-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/345d/9231611/b64bdcf84203/fdgth-04-884208-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/345d/9231611/6ec5fa95dfed/fdgth-04-884208-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/345d/9231611/b64bdcf84203/fdgth-04-884208-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/345d/9231611/6ec5fa95dfed/fdgth-04-884208-g0002.jpg

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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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本文引用的文献

[1]
Social determinants of multimorbidity in Jamaica: application of latent class analysis in a cross-sectional study.

BMC Public Health. 2021-6-23

[2]
Older Adults' Experiences With Using Wearable Devices: Qualitative Systematic Review and Meta-synthesis.

JMIR Mhealth Uhealth. 2021-6-3

[3]
Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review.

JMIR Mhealth Uhealth. 2021-5-28

[4]
World Health Organization 2020 guidelines on physical activity and sedentary behaviour.

Br J Sports Med. 2020-12

[5]
The effectiveness of a wearable activity tracker (WAT)-based intervention to improve physical activity levels in sedentary older adults: A systematic review and meta-analysis.

Arch Gerontol Geriatr. 2020

[6]
Factors Associated with Older Adults' Long-Term Use of Wearable Activity Trackers.

Telemed J E Health. 2020-6

[7]
Digital biomarkers for Alzheimer's disease: the mobile/ wearable devices opportunity.

NPJ Digit Med. 2019

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Ageing Res Rev. 2019-4-30

[9]
Effects of Mobile Health Including Wearable Activity Trackers to Increase Physical Activity Outcomes Among Healthy Children and Adolescents: Systematic Review.

JMIR Mhealth Uhealth. 2019-4-30

[10]
Consumer-Based Wearable Activity Trackers Increase Physical Activity Participation: Systematic Review and Meta-Analysis.

JMIR Mhealth Uhealth. 2019-4-12

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