JMIR Publications

ABSTRACT

Background:

While there’s a push towards encouraging Mobile Health (mHealth) adoption to harness the potential it brings, the reality is that there are many challenges that sometimes go beyond the technology itself, mainly due to the complexity of the healthcare ecosystem.

Objective:

The aim of this review is to explore which frameworks are used the most to understand clinicians’ adoption of mHealth, as well as identify potential gaps within them. Highlighting these gaps, and the main factors that were not specifically covered in the most frequently used frameworks will assist future researchers to better focus their research design, and to include all relevant key factors.

Methods:

This review is an in-depth sub-analysis of a larger systematic review that included research published between 2008 and 2018 and focused on the social, organizational, and technical factors impacting clinicians’ adoption of mHealth. The initial systematic review included 171 studies, out of which 50 studies used a theoretical framework. These 50 studies are the subject of this qualitative review, reflecting further on the frameworks used, and how these can help future researchers design solid and reliable research that investigates the topic of mHealth adoption more robustly.

Results:

The most commonly used frameworks were different forms of extensions of the Technology Acceptance Model (TAM) (34%), the Diffusion of Innovation theory (DOI) (16%), and different forms of extensions of the Unified Theory of Acceptance and Use of Technology (UTAUT) (12%). Some studies used a combination of the TAM and DOI frameworks (6%); others used the Consolidated Framework for Implementation Research (CFIR) (6%), and Sociotechnical Theory (4%). The factors cited by more than 20% of the included studies were usefulness, output quality, ease of use, technical support, data privacy, self-efficacy, attitude, organizational inner setting, training, leadership engagement, workload, and workflow fit. Most factors could be linked to one or the other framework, but there was hardly any single framework that could adequately cover all relevant factors without some expansion.

Conclusions:

Healthcare technologies are generally more complex than tools that address individual user-need as they usually support patients with comorbidities that are typically treated by multi-disciplinary teams who might even work in different healthcare organizations. This special nature of how the healthcare sector operates, its highly regulated nature, the usual budget deficits, and the interdependence between healthcare organisations necessitate some crucial expansions to existing theoretical frameworks usually used when studying adoption. We propose a shift towards theoretical frameworks that take into account implementation challenges that factor in the complexity of the sociotechnical structure of healthcare organizations, and the interplay between the technical, social and organizational aspects. Clinical Trial: NA.