Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Aug 8, 2019
Date Accepted: Mar 25, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Demonstrating how to identify evidence-based content for self-management apps. A participatory design for pressure injuries in spinal cord injury.
ABSTRACT
Background:
Technological solutions, particularly mhealth, have been shown to be a potentially viable approach to sustaining individuals’ self-management of chronic health conditions. Theoretically based interventions have been shown to be more successful, as evidence-based information is an essential prerequisite for appropriate self-management. However, several reviews have shown that many existing mobile applications (apps) fail to be either theoretically grounded or evidence-based. Even though some authors have attempted to address these two issues by focusing on the development process of the apps, concrete efforts to systematically select evidence-based content are scant.
Objective:
The objective of the present paper is to demonstrate how one can apply a rigorous and replicable procedure for the participatory identification of evidence-based content to ground the development of a self-management app.
Methods:
To illustrate the procedure, we used the prevention and management of pressure injuries in spinal cord injury (SCI) as a case in point. The procedure consisted of three steps: the identification of existing evidence through a systematic review and synthesis of existing recommendations on the prevention and self-management of pressure injuries in SCI; a consensus meeting with experts from the field of SCI and individuals with SCI to select the recommendations that are relevant and applicable to community-dwelling individuals in their daily lives; and the consolidation of the results of the study.
Results:
In this case study, at the end of the three-step procedure, 98 recommendations were selected as the basis for the app’s content.
Conclusions:
This study describes a rigorous procedure for the participatory identification and selection of disease-specific evidence and professional best practices to inform mhealth interventions. This procedure might be especially useful in cases of complex chronic health conditions, as every recommendation in these cases needs to be evaluated and considered in light of all other self-management requirements. Hence, the agreement of experts and the individuals affected is essential to ensuring the selection of evidence-based content that is (considered to be) relevant and applicable.
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