JMIR Publications

ABSTRACT

Background:

Digital therapeutics, such as interventions provided via smartphones or the Internet, have been proposed as promising solutions to support self-management in persons with chronic conditions. However, the evidence supporting self-management interventions through technology in stroke is scarce, and the intervention development processes are often not well described, creating challenges in explaining why and how the intervention would work.

Objective:

This study describes the use of intervention mapping and taxonomy of behavioral change techniques in designing a digital intervention for self-management in persons after a stroke.

Methods:

We adopted the first four steps of the intervention mapping process to adapt an existing face-to-face self-management program and translate it to a digital platform, namely the interactive Self-Management Augmented by Rehabilitation Technologies (iSMART). The iSMART is a 12-week self-management intervention, including three components: psychoeducation, behavioral activation coaching, and text messaging. We applied behavioral change technique taxonomy to specify strategies that help individuals change self-management behaviors. Planning group members were involved in adapting the intervention. They also completed three implementation measures to assess the acceptability, appropriateness, and feasibility of the iSMART.

Results:

In Step 1, we completed a needs assessment consisting of assembling a planning group, phone surveys of stroke survivors (N= 125), and a systematic review to identify service needs and the theory for developing a digital post-stroke self-management intervention. We identified activity scheduling, symptom management, stroke prevention, access to care resources, and cognitive enhancement/training as key service needs after a stroke. The review suggested that theory-based digital self-management interventions effectively reduce depression, anxiety, and fatigue and enhance self-efficacy in neurologic disorders, especially those using cognitive-behavior theory. Step 2 identified key determinants, objectives, and strategies for self-management in the iSMART, including knowledge, behavioral regulation, skills, self-efficacy, motivation, negative and positive affect, and social and environmental support. In Step 3, we generated the intervention components underpinned by appropriate behavior change techniques. In Step 4, we developed the iSMART with the planning group members. The iSMART was found to be acceptable (mean = 4.6 out of 5), appropriate (4.6 out of 5), and feasible (4.6 out of 5).

Conclusions:

We describe a detailed example of using intervention mapping and taxonomy of behavior change techniques for designing and developing a complex digital intervention to support post-stroke self-management. Clinical Trial: NA