JMIR Publications

ABSTRACT

Background:

Digital health technologies have become integral to modern healthcare, yet consumer adoption remains uneven. These technologies span a range of consumer-facing tools, including remote care services, mobile applications, wearable devices, conversational agents, and digital medication services, with uptake varying considerably across tool types and by gender. An earlier analysis of this dataset revealed a gender paradox: women reported higher digital literacy compared to men yet demonstrated lower adoption and curiosity toward digital health tools. To explore this paradox, this study applies the Capability, Opportunity, Motivation – Behaviour (COM-B) model of behaviour, which proposes that behaviour occurs when individuals have the capability (skills and confidence), opportunity (access, affordability, and contextual support), and motivation (trust, perceived usefulness, and willingness) to act.

Objective:

To examine associations between digital literacy, self-reported COM-B domains, gender, and adoption across five consumer-facing digital health technologies, and to explore whether these associations differ by gender.

Methods:

A cross-sectional quantitative study with an integrated qualitative component involving 416 adults used multivariable logistic regression to examine associations between COM-B domains and adoption across five digital health technologies. Exploratory gender-by-predictor interaction and gender-stratified analyses examined potential gender-specific patterns, while self-reported reasons for non-use were mapped to COM-B domains using directed content analysis.

Results:

Women had lower adjusted odds of chatbot/virtual assistant use (aOR 0.32, 95% CI 0.18–0.59), marginally lower odds of e-pharmacy use (aOR 0.48, 95% CI 0.22–1.01), and higher odds of mobile health app use (aOR 2.59, 95% CI 1.28–5.25). Of 20 exploratory interaction tests, chatbot digital literacy-by-gender (p=.021) and capability-by-gender (p=.044) interactions were nominally significant. In the directed barrier analysis, the gender distribution differed significantly for mobile health apps (p=.009), while the wearable result showed a trend (p=.079); motivation-related barriers were most frequent for most technologies.

Conclusions:

Behavioural determinants of digital health adoption varied by technology type. Women used several technologies less often than men despite reporting higher digital literacy, capability and motivation, and Opportunity emerged as the most consistent factor across the models examined. Exploratory analyses suggested these patterns may differ by gender for selected technologies but did not support a single gender-differentiated pathway. These findings are exploratory and require confirmation in larger studies.