Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Sep 30, 2020
Date Accepted: Nov 20, 2020
Date Submitted to PubMed: Dec 10, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Attitudes towards COVID-19 mHealth use among Adults with Chronic Health Conditions: A Secondary Data Analysis of the COVID-19 Impact Survey
ABSTRACT
Background:
Adults with chronic conditions are disproportionately burdened by COVID-19 morbidity and mortality. While COVID-19 mobile-health (mHealth) applications have emerged, research examining attitudes towards COVID-19 mHealth use among those with chronic conditions is scarce.
Objective:
To examine attitudes and identify determinants of COVID-19 mHealth use across demographic and health-related characteristics; and evaluate associations of having chronic health conditions with attitudes towards COVID-19 mHealth use (e.g. use of mHealth or web-based methods to track COVID-19 exposures, symptoms, and recommendations).
Methods:
We utilized nationally-representative data from the COVID-19 Impact Survey collected from April-June 2020 (n=10,760). Chronic conditions were defined using self-reported diagnoses and categorized as cardiometabolic-related, respiratory-related, immune-related, mental health, and overweight/obesity. Primary outcomes were attitudes of COVID-19 mHealth: (1) likelihood of using a mobile-phone app to track COVID-19 symptoms and receive recommendations, (2) likelihood of using a website to track COVID-19 symptoms, location, and receive recommendations, and (3) likelihood of using an app using location to track potential COVID-19 exposure. Response options were categorized into extremely/very likely, moderately likely, or not likely. Multinomial logistic regression was used to compare likelihood of COVID-19 mHealth use across chronic health conditions, with not likely as the reference category for each outcome. We evaluated determinants of each form of COVID-19 mHealth intervention using Poisson regression.
Results:
Among the 10,760 respondents, about half were aged 30-59 years, female, had a household income <$50,000, and had employer-sponsored insurance. Overall, 22% were extremely/very likely to use a mobile-phone app or a website to track their COVID-19 symptoms and receive recommendations. Almost one-quarter were extremely/very likely to use a mobile-phone app to track their location and receive push notifications if they have been exposed to COVID-19. When stratified by chronic disease group, we observed that patterns of likelihood of mHealth app use were largely consistent. After adjustment for covariates, adults living with mental health conditions were most likely to report being either extremely/very or moderately likely to use each mHealth intervention when compared to those who were not likely. Adults with respiratory-related chronic diseases were extremely/very (cOR:1.16, 95% CI:1.00-1.35) and moderately likely (cOR:1.23, 95% CI:1.04-1.45) to use a mobile-phone app to track their location and send push notifications if they might have been exposed to COVID-19. Across each mHealth intervention, positive determinants of extremely/very likely use included being female, racial/ethnic minority, and having at least one COVID-19 related symptom within the last seven days.
Conclusions:
Our study demonstrates that attitudes towards COVID-19 mHealth use vary widely by modality (web-based vs. app) and across chronic health conditions. These findings may inform adoption of and long-term engagement with COVID-19 apps, a crucial factor for determining their potential to reduce disparities in COVID-19 morbidity and mortality among individuals with chronic health conditions.
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