Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Jan 9, 2022
Open Peer Review Period: Jan 9, 2022 - Mar 6, 2022
Date Accepted: Mar 22, 2022
Date Submitted to PubMed: Mar 23, 2022
(closed for review but you can still tweet)
Socio-technical Factors Impacting Patients’ Adoption of Mobile Health Tools: Systematic Literature Review and Narrative Synthesis
ABSTRACT
Background:
Mobile Health (mHealth) tools have emerged as a promising healthcare technology that may contribute to cost savings, better access to care, and enhanced clinical outcomes; however, it is important to ensure their acceptance and adoption in order to harness this potential. Patient adoption has been recognized as key challenges that require further exploration.
Objective:
The aim of this review was to systematically investigate the literature to understand the factors impacting patients’ adoption of mHealth tools, by considering socio-technical factors (from technical, social and health perspectives).
Methods:
A structured search was completed following the participants, intervention, comparators, and outcomes (PICO framework. MEDLINE PubMed, the Cochrane Library, and SAGE database were searched for the studies published between January 2011 and July 2021 in the English language, yielding 5873 results, of which 147 studies met the inclusion criteria. The Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines (PRISMA) and the Cochrane handbook were followed to ensure a systematic process.
Results:
The technical factors impacting patients’ adoption of mHealth tools were categorized into 6 key themes: usefulness, ease of use, data related, monetary factors, technical issues, and user experience; which were divided into 20 sub-themes. Health related factors were categorized into 6 key themes: the disease or health condition, the care team’s role, health consciousness and literacy, health behavior, relation to other therapies, integration into patient journey, and the patients’ insurance status. Social and personal factors were split into 3 key clusters: moderating factors, personal characteristics, and social and cultural aspects; these were divided into 19 subthemes, highlighting the importance of considering these factors when addressing potential barriers to mHealth adoption and how to overcome them.
Conclusions:
This review builds on the growing body of research that investigates patients’ adoption of mHealth services, and highlights the complexity of the factors impacting adoption, including personal, social, technical, organizational and healthcare aspects. We recommend a more patient-centered approach, by ensuring the tools’ fit into the overall patient journey and treatment plan, emphasizing inclusive design, warranting comprehensive patient education and support, empowering and mobilizing clinicians and care teams, addressing ethical data management issues, and focusing on healthcare policies that may facilitate adoption. Clinical Trial: NA
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