JMIR Publications

ABSTRACT

Background:

Digital health interventions are a central focus of healthcare transformation efforts, yet their uptake in practice continues to fall short of its potential. In order to achieve their desired outcomes and impact, digital health interventions need to reach its target population and need to be used. Many factors can rapidly intersect between this dynamic of users and interventions. The application of theories, models and frameworks (TMF) can facilitate the systematic understanding and explanation of the complex interactions between users, practices, technology, and health system factors that underpin research questions. There remains a gap in our understanding of how TMFs have been applied to guide the evaluation of digital health interventions with the real-world health system operations.

Objective:

To map TMFs used in studies to guide the evaluation of digital health interventions. The objectives are to (1) describe the TMFs and the constructs they target; and (2) identify how TMFs have been prospectively used (i.e. their roles) in primary studies to evaluate digital health interventions; (3) to reflect on the relevance and utility of our findings for knowledge users.

Methods:

This scoping review was conducted in partnership with knowledge users using an integrated knowledge translation approach. We included papers (e.g., reports, empirical quantitative, qualitative, and mixed-methods studies, conference proceedings, dissertation) if primary insights resulting from the application of TMFs were presented. Any types of digital health interventions were eligible. Papers published from 2000 and onwards were mainly identified from those databases: MEDLINE (Ovid), CINAHL Complete (EBSCOhost), PsycINFO (Ovid), EBM Reviews (Ovid) and EMBASE (Ovid).

Results:

A total of 156 studies published between 2000 and 2022 were included. Sixty-eight distinct TMFs were identified across 85 individual studies. In more than half (85/156, 55%) of included studies, one of those six prevailing TMFs were reported: Consolidated Framework for Implementation Research; the Reach, Effectiveness, Adoption, Implementation, and Maintenance Framework (n=39 studies); the Technology of Acceptance Model (n=17); the Unified Theory on Acceptance and Use of Technology (n=12), the Diffusion of Innovation Theory (n=10); and Normalization Process Theory (n=9). The most common intended roles of the six TMFs was to inform data collection (n= 86), to inform data analysis (n=69), and to identify key constructs that may serve as barriers and facilitators (n=52).

Conclusions:

As TMFs are most often reported to be applied to support data collection and analysis, researchers should consider more clearly synthesizing key insights as practical use cases to both increase relevance and digestibility of their findings. There is also a need to adapt or develop guidelines for better reporting digital health interventions and the utilization of TMFs to guide evaluation. Hence, it would contribute to ensure ongoing technology transformation efforts are evidence and theory-informed rather than anecdotally driven.