Use of mobile health applications for health-promoting behavior among individuals with chronic medical conditions. (October 2019)

• Record Type: Journal Article
• Authors: Mahmood, Asos; Kedia, Satish; Wyant, David K; Ahn, SangNam; Bhuyan, Soumitra S
• Is Part Of: Digital health. Volume 5(2019)
• Publication Date: 2019-10
• Subjects: Chronic disease -- mHealth -- smartphone -- tablet -- digital divide -- health-promoting behavior; Medical care -- Data processing -- Periodicals; Medical informatics -- Periodicals; 362.10285
• DOI: 10.1177/2055207619882181
• Languages: English
• ISSNs: 2055-2076

Abstract

Background: Chronic medical conditions (CCs) are leading causes of morbidity and mortality in the United States. Strategies to control CCs include targeting unhealthy behaviors, often through the use of patient empowerment tools, such as mobile health (mHealth) technology. However, no conclusive evidence exists that mHealth applications (apps) are effective among individuals with CCs for chronic disease self-management. Methods: We used data from the Health Information National Trends Survey (HINTS 5, Cycle 1, 2017). A sample of 1864 non-institutionalized US adults (≥18 years) who had a smartphone and/or a tablet computer and at least one CC was analyzed. Using multivariable logistic regressions, we assessed predisposing, enabling, and need predictors of three health-promoting behaviors (HPBs): tracking progress on a health-related goal, making a health-related decision, and health-related discussions with a care provider among smart device and mHealth apps owners. Results: Compared to those without mHealth apps, individuals with mHealth apps had significantly higher odds of using their smart devices to track progress on a health-related goal (adjusted odds ratio (aOR) 8.74, 95% confidence interval (CI): 5.66–13.50, P < .001), to make a health-related decision (aOR 1.77, 95% CI: 1.16–2.71, P < .01) and in health-related discussions with care providers (aOR 2.0, 95% CI: 1.26–3.19, P < .01). Other significant factors of at least one type of HPB among smart device and mHealth apps users were age, gender, education, occupational status, having a regular provider, and self-rated general health. Conclusion: mHealth apps are associated with increased rates of HPB among individuals with CCs. However, certain groups, like older adults, are most affected by a digital divide where they have lower access to mHealth apps and thus are not able to take advantage of these tools. Rigorous randomized clinical trials among various segments of the population and different health conditions are needed to establish the effectiveness of these mHealth apps. Healthcare providers should encourage validated mHealth apps for patients with CCs.