Examining Theoretical Frameworks and Antecedents of Health Apps and Wearables Use: A Scoping Review

ABSTRACT

The advancement of health apps and wearables has garnered substantial academic attention, particularly in examining why individuals decide to use or not use them. In response to the extensive body of research on this topic, we conducted a scoping review of 61 articles published from 2007 to 2022, aiming to examine the dominant theoretical frameworks and antecedents of health apps and wearables use. The findings demonstrated that the dominant theoretical frameworks within this domain were rooted in the human-computer interaction theories, notably the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Next, our review identified four levels of antecedents: technological, individual, societal, and policy. At the technological level, emphasis was placed on functionality, reliability, and technological infrastructure. Individual antecedents encompassed socio-demographics, personality traits, cognitive responses to benefits and risks, emotional and affective responses, self-efficacy, and digital literacy. Societal antecedents highlighted the role of social networks and social norms, while policy antecedents elaborated on laws, regulations, and guidelines that encouraged health technology adoption. Our discussion illuminated that the evolving trend of theoretical frameworks in health apps and wearables use research, initially rooted in human-computer interaction, is progressively moving toward more comprehensive perspectives. We further underscored the importance of delving into societal and policy antecedents, which often are overshadowed by the more commonly discussed technological and individual factors. In conclusion, we advocated for a multi-stakeholder collaborative network approach, as this would enable communication researchers to understand the use of health apps and wearables more comprehensively.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was supported by Nanyang Technological University, Singapore [Start Up Grant: 020154-00001].