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Application of a Sociotechnical Framework to Uncover Factors That Influence Effective User Engagement With Digital
Brian Lo1,2, Keri Durocher1,3, Rebecca Charow2,4
1Centre for Addiction and Mental Health, Toronto, ON, Canada.
Background:
Digital health tools such as mobile apps and patient portals continue to be embedded in clinical care pathways to enhance mental health care delivery and achieve the quintuple aim of improving patient experience, population health, care team well-being, health care costs, and equity. However, a key issue that has greatly hindered the value of these tools is the suboptimal user engagement by patients and families. With only a small fraction of users staying engaged over time, there is a great need to better understand the factors that influence user engagement with digital mental health tools in clinical care settings.
Objective:
This review aims to identify the factors relevant to user engagement with digital mental health tools in clinical care settings using a sociotechnical approach.
Methods:
A scoping review methodology was used to identify the relevant factors from the literature. Five academic databases (MEDLINE, Embase, CINAHL, Web of Science, and PsycINFO) were searched to identify pertinent articles using key terms related to user engagement, mental health, and digital health tools. The abstracts were screened independently by 2 reviewers, and data were extracted using a standardized data extraction form. Articles were included if the digital mental health tool had at least 1 patient-facing component and 1 clinician-facing component, and at least one of the objectives of the article was to examine user engagement with the tool. An established sociotechnical framework developed by Sittig and Singh was used to inform the mapping and analysis of the factors.
Results:
The database search identified 136 articles for inclusion in the analysis. Of these 136 articles, 84 (61.8%) were published in the last 5 years, 47 (34.6%) were from the United States, and 23 (16.9%) were from the United Kingdom. With regard to examining user engagement, the majority of the articles (95/136, 69.9%) used a qualitative approach to understand engagement. From these articles, 26 factors were identified across 7 categories of the established sociotechnical framework. These ranged from technology-focused factors (eg, the modality of the tool) and the clinical environment (eg, alignment with clinical workflows) to system-level issues (eg, reimbursement for physician use of the digital tool with patients).
Conclusions:
On the basis of the factors identified in this review, we have uncovered how the tool, individuals, the clinical environment, and the health system may influence user engagement with digital mental health tools for clinical care. Future work should focus on validating and identifying a core set of essential factors for user engagement with digital mental health tools in clinical care environments. Moreover, exploring strategies for improving user engagement through these factors would be useful for health care leaders and clinicians interested in using digital health tools in care.
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