Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement

Nadal, C. and Sas, C. and Doherty, G. (2020) Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement. Journal of Medical Internet Research, 22 (7): e17256. ISSN 1439-4456

Abstract

BACKGROUND: Designing technologies that users will be interested in, start using, and keep using has long been a challenge. In the health domain, the question of technology acceptance is even more important, as the possible intrusiveness of technologies could lead to patients refusing to even try them. Developers and researchers must address this question not only in the design and evaluation of new health care technologies but also across the different stages of the user's journey. Although a range of definitions for these stages exists, many researchers conflate related terms, and the field would benefit from a coherent set of definitions and associated measurement approaches. OBJECTIVE: This review aims to explore how technology acceptance is interpreted and measured in mobile health (mHealth) literature. We seek to compare the treatment of acceptance in mHealth research with existing definitions and models, identify potential gaps, and contribute to the clarification of the process of technology acceptance. METHODS: We searched the PubMed database for publications indexed under the Medical Subject Headings terms "Patient Acceptance of Health Care" and "Mobile Applications." We included publications that (1) contained at least one of the terms "acceptability," "acceptance," "adoption," "accept," or "adopt"; and (2) defined the term. The final corpus included 68 relevant studies. RESULTS: Several interpretations are associated with technology acceptance, few consistent with existing definitions. Although the literature has influenced the interpretation of the concept, usage is not homogeneous, and models are not adapted to populations with particular needs. The prevalence of measurement by custom surveys suggests a lack of standardized measurement tools. CONCLUSIONS: Definitions from the literature were published separately, which may contribute to inconsistent usage. A definition framework would bring coherence to the reporting of results, facilitating the replication and comparison of studies. We propose the Technology Acceptance Lifecycle, consolidating existing definitions, articulating the different stages of technology acceptance, and providing an explicit terminology. Our findings illustrate the need for a common definition and measurement framework and the importance of viewing technology acceptance as a staged process, with adapted measurement methods for each stage. ©Camille Nadal, Corina Sas, Gavin Doherty. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 06.07.2020.