Theories Informing eHealth Implementation: Systematic Review and Typology Classification

Abstract

Background Theory-guided approaches to implementation science have informed translation efforts and the acceptance of eHealth (digital health) interventions in clinical care. However, there is scarce evidence on which theories are best suited to addressing the inherent complexity of eHealth implementation. Objective The objectives of this systematic review are to identify theories that inform and explain eHealth implementation and to classify these theories using the typology by Sovacool and Hess for theories of sociotechnical change. Methods An electronic search was conducted in the PsycINFO, MEDLINE, Embase, CINAHL, Scopus, Sociological Source Ultimate, Web of Science, ABI/INFORM, EBSCO, and ProQuest databases in June 2019. Studies were included if they were published between 2009 and June 2019; were written in English; reported on empirical research, regardless of study or publication type; reported on one or more theories in the context of eHealth implementation; and were published in a peer-reviewed journal. A total of 2 reviewers independently assessed the titles, abstracts, and full texts. Theories identified were classified using a typology for theories of sociotechnical change, which was considered a useful tool for ordering and analyzing the diverse theoretical approaches as a basis for future theory building. Results Of the 13,101 potentially relevant titles, 119 studies were included. The review identified 36 theories used to explain implementation approaches in eHealth. The most commonly used approaches were the Technology Acceptance Model (TAM) (n=33) and the Unified Theory of Acceptance and Use of Technology (UTAUT) (n=32). These theories were primarily concerned with individual and interpersonal elements of eHealth acceptance. Less common were theories that reflect the various disorderly social processes and structural dimensions of implementation, such as the normalization process theory (n=17) and the structuration theory (n=6). Conclusions Theories currently informing the implementation of eHealth interventions predominantly focus on predicting or explaining end-user acceptance. Theoretical perspectives that capture the dense and intricate relationships and structures required to enact sustainable change are less well represented in the eHealth literature. Given the growing acknowledgment of the inherent complexity of eHealth implementation, future research should develop and test models that recognize and reflect the multidimensional, dynamic, and relational nature of this process.

Barriers and facilitators to the use of e-health by older adults: a scoping review

“…This highlights an urgent need for future research examining factors that facilitate or hinder the use of e-health services by specific groups of older people, who may be particularly vulnerable or marginalised. Combining UTAUT2 with normative theories of social justice and equity may facilitate such efforts [ 47 ].…”

“…The Unified Theory of Acceptance and Technology Use (UTAUT) is one of the most comprehensive and widely used technology acceptance models [ 47 ]. UTAUT proposes that behavioural intention to use technology is affected by an individual’s effort expectancy (degree to which the technology is perceived to be easy to use), performance expectancy (degree to which the technology is perceived to be useful), social influence (degree to which using the technology is supported by an individual’s social network), facilitating conditions (the degree to which an individual believes to have the resources to use the technology) [ 48 ].…”

Usability Testing and Technology Acceptance of an mHealth App at the Point of Care During Simulated Pediatric In- and Out-of-Hospital Cardiopulmonary Resuscitations: Study Nested Within 2 Multicenter Randomized Controlled Trials

“…Scales and queries with high levels of internal consistency (ie, Cronbach α >.70) were derived and slightly adapted from prior research to fit the trial’s context ( Multimedia Appendix 2 ) [ 44 ]. This integrative model gathers the 2 most commonly used models in the literature that inform technology acceptance [ 45 ], namely the TAM [ 15 ] and UTAUT [ 20 , 21 ], as well as additional dimensions of technology acceptance models [ 19 , 20 , 46 - 50 ], with the following eight core constructs: (1) perceived usefulness (4 items), (2) perceived ease of use (4 items), (3) TTF (4 items), (4) performance expectancy (3 items), (5) impact on image (2 items), (6) personal innovativeness (3 items), (7) acceptance (3 items), and (8) behavioral intention to use the technology (3 items). The items measured the constructs by asking participants to agree or disagree with statements using 5-point Likert-type scales, ranging from strongly disagree (1) to strongly agree (5).…”

eHealth Services and SDG3: Increasing the Capacity of Care

“…Integrating MHAOD at individual and social levels supported by the technology level is a benefit of activity theory for optimising uptake. In contrast, technology usability and adoption studies and the theorising that underpins them mainly concern channel interface issues at the individual level (Heinsch, Wyllie, et al, 2021;Sun & Qu, 2015). Although few studies call for examining the uptake of cooccurring MHAOD services using a multi-level lens (i.e.…”

“…In the broader health and information systems literature, the adoption of eHealth services for patient (i.e. end-user) care remains only partially understood where most user adoption models such as Theory of Reasoned Action, Theory of Planned Behaviour, Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology (UTAUT) residing at the individual level of analysis (Heinsch, Wyllie, et al, 2021;Sun & Qu, 2015). Specifically, these models neglect the involvement of multiple actors beyond the user that are intertwined in the use of eHealth technologies including clinicians, nurses and general practitioners (GP's) for the co-creation and completion of tasks involving a network of activity, tasks and supporting processes (Sun & Qu, 2015).…”