Satisfaction, Usability, and Compliance With the Use of Smartwatches for Ecological Momentary Assessment of Knee Osteoarthritis Symptoms in Older Adults: Usability Study.

ROAMM compliance ecological momentary assessment ehealth fatigue knee osteoarthritis mobile application mobile health older adults pain personal satisfaction real-time online assessment and mobility monitor smartwatch usability wearable electronic device

Journal

JMIR aging
ISSN: 2561-7605
Titre abrégé: JMIR Aging
Pays: Canada
ID NLM: 101740387

Informations de publication

Date de publication:
14 Jul 2021
Historique:
received: 24 09 2020
accepted: 22 04 2021
revised: 12 01 2021
entrez: 14 7 2021
pubmed: 15 7 2021
medline: 15 7 2021
Statut: epublish

Résumé

Smartwatches enable physicians to monitor symptoms in patients with knee osteoarthritis, their behavior, and their environment. Older adults experience fluctuations in their pain and related symptoms (mood, fatigue, and sleep quality) that smartwatches are ideally suited to capture remotely in a convenient manner. The aim of this study was to evaluate satisfaction, usability, and compliance using the real-time, online assessment and mobility monitoring (ROAMM) mobile app designed for smartwatches for individuals with knee osteoarthritis. Participants (N=28; mean age 73.2, SD 5.5 years; 70% female) with reported knee osteoarthritis were asked to wear a smartwatch with the ROAMM app installed. They were prompted to report their prior night's sleep quality in the morning, followed by ecological momentary assessments (EMAs) of their pain, fatigue, mood, and activity in the morning, afternoon, and evening. Satisfaction, comfort, and usability were evaluated using a standardized questionnaire. Compliance with regard to answering EMAs was calculated after excluding time when the watch was not being worn for technical reasons (eg, while charging). A majority of participants reported that the text displayed was large enough to read (22/26, 85%), and all participants found it easy to enter ratings using the smartwatch. Approximately half of the participants found the smartwatch to be comfortable (14/26, 54%) and would consider wearing it as their personal watch (11/24, 46%). Most participants were satisfied with its battery charging system (20/26, 77%). A majority of participants (19/26, 73%) expressed their willingness to use the ROAMM app for a 1-year research study. The overall EMA compliance rate was 83% (2505/3036 responses). The compliance rate was lower among those not regularly wearing a wristwatch (10/26, 88% vs 16/26, 71%) and among those who found the text too small to read (4/26, 86% vs 22/26, 60%). Older adults with knee osteoarthritis positively rated the ROAMM smartwatch app and were generally satisfied with the device. The high compliance rates coupled with the willingness to participate in a long-term study suggest that the ROAMM app is a viable approach to remotely collecting health symptoms and behaviors for both research and clinical endeavors.

Sections du résumé

BACKGROUND BACKGROUND
Smartwatches enable physicians to monitor symptoms in patients with knee osteoarthritis, their behavior, and their environment. Older adults experience fluctuations in their pain and related symptoms (mood, fatigue, and sleep quality) that smartwatches are ideally suited to capture remotely in a convenient manner.
OBJECTIVE OBJECTIVE
The aim of this study was to evaluate satisfaction, usability, and compliance using the real-time, online assessment and mobility monitoring (ROAMM) mobile app designed for smartwatches for individuals with knee osteoarthritis.
METHODS METHODS
Participants (N=28; mean age 73.2, SD 5.5 years; 70% female) with reported knee osteoarthritis were asked to wear a smartwatch with the ROAMM app installed. They were prompted to report their prior night's sleep quality in the morning, followed by ecological momentary assessments (EMAs) of their pain, fatigue, mood, and activity in the morning, afternoon, and evening. Satisfaction, comfort, and usability were evaluated using a standardized questionnaire. Compliance with regard to answering EMAs was calculated after excluding time when the watch was not being worn for technical reasons (eg, while charging).
RESULTS RESULTS
A majority of participants reported that the text displayed was large enough to read (22/26, 85%), and all participants found it easy to enter ratings using the smartwatch. Approximately half of the participants found the smartwatch to be comfortable (14/26, 54%) and would consider wearing it as their personal watch (11/24, 46%). Most participants were satisfied with its battery charging system (20/26, 77%). A majority of participants (19/26, 73%) expressed their willingness to use the ROAMM app for a 1-year research study. The overall EMA compliance rate was 83% (2505/3036 responses). The compliance rate was lower among those not regularly wearing a wristwatch (10/26, 88% vs 16/26, 71%) and among those who found the text too small to read (4/26, 86% vs 22/26, 60%).
CONCLUSIONS CONCLUSIONS
Older adults with knee osteoarthritis positively rated the ROAMM smartwatch app and were generally satisfied with the device. The high compliance rates coupled with the willingness to participate in a long-term study suggest that the ROAMM app is a viable approach to remotely collecting health symptoms and behaviors for both research and clinical endeavors.

Identifiants

pubmed: 34259638
pii: v4i3e24553
doi: 10.2196/24553
pmc: PMC8319786
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e24553

Subventions

Organisme : NIA NIH HHS
ID : P30 AG028740
Pays : United States
Organisme : NIA NIH HHS
ID : R21 AG059207
Pays : United States

Informations de copyright

©Charlotte Rouzaud Laborde, Erta Cenko, Mamoun T Mardini, Subhash Nerella, Matin Kheirkhahan, Sanjay Ranka, Roger B Fillingim, Duane B Corbett, Eric Weber, Parisa Rashidi, Todd Manini. Originally published in JMIR Aging (https://aging.jmir.org), 14.07.2021.

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Auteurs

Charlotte Rouzaud Laborde (C)

Department of Pharmacy, University of Toulouse, Toulouse, France.
Department of Aging and Geriatric research, University of Florida, Gainesville, FL, United States.

Erta Cenko (E)

Department of Epidemiology, University of Florida, Gainesville, FL, United States.

Mamoun T Mardini (MT)

Department of Aging and Geriatric research, University of Florida, Gainesville, FL, United States.
Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States.

Subhash Nerella (S)

Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States.

Matin Kheirkhahan (M)

Google, Mountain View, California, CA, United States.

Sanjay Ranka (S)

Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, United States.

Roger B Fillingim (RB)

Department of Community Dentistry and Behavioral Science, University of Florida, Gainesville, FL, United States.

Duane B Corbett (DB)

Department of Aging and Geriatric research, University of Florida, Gainesville, FL, United States.

Eric Weber (E)

Department of Community Dentistry and Behavioral Science, University of Florida, Gainesville, FL, United States.

Parisa Rashidi (P)

Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States.

Todd Manini (T)

Department of Aging and Geriatric research, University of Florida, Gainesville, FL, United States.

Classifications MeSH