%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 24
%N 1
%P e26555
%T Using Intervention Mapping to Develop a Decision Support System–Based Smartphone App (selfBACK) to Support Self-management of Nonspecific Low Back Pain: Development and Usability Study
%A Svendsen,Malene Jagd
%A Sandal,Louise Fleng
%A Kjær,Per
%A Nicholl,Barbara I
%A Cooper,Kay
%A Mair,Frances
%A Hartvigsen,Jan
%A Stochkendahl,Mette Jensen
%A Søgaard,Karen
%A Mork,Paul Jarle
%A Rasmussen,Charlotte
%+ The National Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen, 2100, Denmark, 45 20259734, mas@nfa.dk
%K intervention mapping
%K behavior change
%K low back pain
%K self-management
%K mHealth
%K app-based intervention
%K decision support system
%K digital health intervention
%K mobile phone
%D 2022
%7 24.1.2022
%9 Original Paper
%J J Med Internet Res
%G English
%X Background: International guidelines consistently endorse the promotion of self-management for people with low back pain (LBP); however, implementation of these guidelines remains a challenge. Digital health interventions, such as those that can be provided by smartphone apps, have been proposed as a promising mode of supporting self-management in people with chronic conditions, including LBP. However, the evidence base for digital health interventions to support self-management of LBP is weak, and detailed descriptions and documentation of the interventions are lacking. Structured intervention mapping (IM) constitutes a 6-step process that can be used to guide the development of complex interventions. Objective: The aim of this paper is to describe the IM process for designing and creating an app-based intervention designed to support self-management of nonspecific LBP to reduce pain-related disability. Methods: The first 5 steps of the IM process were systematically applied. The core processes included literature reviews, brainstorming and group discussions, and the inclusion of stakeholders and representatives from the target population. Over a period of >2 years, the intervention content and the technical features of delivery were created, tested, and revised through user tests, feasibility studies, and a pilot study. Results: A behavioral outcome was identified as a proxy for reaching the overall program goal, that is, increased use of evidence-based self-management strategies. Physical exercises, education, and physical activity were the main components of the self-management intervention and were designed and produced to be delivered via a smartphone app. All intervention content was theoretically underpinned by the behavior change theory and the normalization process theory. Conclusions: We describe a detailed example of the application of the IM approach for the development of a theory-driven, complex, and digital intervention designed to support self-management of LBP. This description provides transparency in the developmental process of the intervention and can be a possible blueprint for designing and creating future digital health interventions for self-management. 
%M 35072645
%R 10.2196/26555
%U https://www.jmir.org/2022/1/e26555
%U https://doi.org/10.2196/26555
%U http://www.ncbi.nlm.nih.gov/pubmed/35072645