Sociodemographic predictors of digital health adoption in patients with asthma and COPD - Téllez, Daniela; Boers, Elroy; Kaye, Leanne; Vuong, Vy; Barrett, Meredith A. (Frontiers in Digital Health, 2025)
IntroductionRemote healthcare adoption has grown significantly in United States (US). However, better characterization of patient behaviors and comfort with the use of digital health is needed, especially among vulnerable populations. The objective of this study was to evaluate how sociodemographic characteristics may relate to the adoption of digital health among patients with asthma and chronic obstructive pulmonary disease (COPD).MethodsAdults residing in the US and using a digital platform for asthma or COPD management were surveyed to understand (1) level of comfort sharing health data with their healthcare providers and (2) the presence of remote care concerns, specifically clinical, technological, privacy and financial concerns. Multivariable logistic regression models assessed the relationship between baseline disease status, sex, age, race, education, insurance, and income, with health data sharing patterns and areas of concern with remote care.ResultsAbout one-third of survey respondents reported sharing health data with their provider, and most respondents had at least one concern in receiving remote care, with clinical and privacy concerns being the most frequently reported. However, attitudes and behaviors toward virtual health delivery were mixed. Patients with lower income were 65% more likely to share any health data (OR 1.65, 95% CI 1.13–2.43, p = 0.0104), but were also more likely to report at least one concern on virtual healthcare delivery. White patients (vs. non-white) were 2.5 times more likely to report clinical concerns when obtaining remote care (OR 2.5 95% CI 1.57–3.96, p = 0.0001).DiscussionPatterns of data sharing and concerns with remote care varied across sociodemographic predictors, sometimes in opposing ways. These learnings highlight the need for further research, including moderating and mediating factors like social support, health literacy, and rurality, to uncover the real-world use and impact of digital health services at a population level.