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:

Using the COM-B model of behaviour, this study examines behavioural determinants of digital health adoption and tests gender-specific pathways across five technologies: telehealth, mobile health apps, wearable devices, chatbots or virtual assistants, and e-pharmacies.

Methods:

A cross-sectional mixed-methods study of 416 adults combined logistic regression, gender-by-predictor interaction analyses, exploratory nested model comparisons, and qualitative mapping of self-reported reasons for non-use.

Results:

Women reported higher digital literacy, capability, and motivation, yet lower adoption of wearables (64% vs 89%), chatbots (53% vs 87%), and e-pharmacies (75% vs 93%). Opportunity emerged as the strongest overall predictor of adoption for both genders (adjusted OR 2.7–7.0, p < 0.01). However, gender moderated the underlying pathways: capability played a greater role in men’s adoption, particularly for chatbots (p = 0.044), while qualitative findings reinforced that women’s non-use centred on opportunity-related barriers such as access, affordability, and contextual support.

Conclusions:

While opportunity is central to digital health adoption for all users, women’s engagement is more heavily shaped by opportunity-related barriers, whereas men’s engagement is more influenced by capability. These differentiated pathways highlight the need for digital health interventions that prioritise equitable access and supportive conditions. The Behaviour Change Wheel framework provides a structured approach for designing targeted interventions to address the identified opportunity barriers.