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mHealth Intervention to Promote Nonexercise Physical Activity in Patients With Type 2 Diabetes: Secondary Analysis
Minna Aittasalo1,2, Kari Tokola1, Henri Vähä-Ypyä1
1The UKK Institute for Health Promotion Research, Tampere, Finland.
Background:
Physical activity (PA) has an important role in the prevention and treatment of type 2 diabetes (T2D). Interventions with mobile-based technology (mobile health [mHealth]) seem promising in PA promotion, but their behavioral framework is often vague, and the implementation is seldom reported.
Objective:
This paper examines perceived behavior change needs and implementation of an mHealth approach in increasing nonexercise PA in patients with T2D.
Methods:
A 3-arm mHealth intervention was conducted in primary care. Information on perceived behavior change needs was collected with a modified capability, opportunity, motivation-behavior (COM-B) questionnaire before the intervention from a separate sample of patients with T2D (n=25) and at the intervention baseline (n=119). Implementation evaluation focused on the fidelity and acceptability of the main arm of the intervention (n=39), which included 24-hour accelerometer use, a smartphone app with personal feedback, a PA leaflet, a YouTube video on walking, and individual counseling with 3 face-to-face sessions and 4 telephone contacts. Data on fidelity were accumulated during the intervention through counseling cards and cloud computing. Data on acceptability were collected with a questionnaire at the end of the intervention (Likert scale from 1 to 5). Data analysis was mainly descriptive.
Results:
The participants' responses revealed 3 items in capability and 2 in motivation, which stood out as perceived behavior change needs. Moreover, the main intervention arm showed good fidelity (eg, face-to-face sessions: 112/117, 96% and telephone contacts completed: 145/156, 93%; mean weekly accelerometer use 54%; ranging from 80% to 17% during the intervention) and acceptability (mean score ranging from 3.8 to 4.8), although some challenges were also experienced, especially in cloud-computed feedback and accelerometer-app use.
Conclusions:
The findings on behavior change needs call for additional research since no comparable studies were found. In addition, the explanatory value of the COM-B model and the psychometric properties of the COM-B questionnaire deserve further attention. The main intervention arm seemed applicable to clinical practice. However, the challenges discovered underscore the importance of pretesting technology-based approaches in patients with T2D.
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