An mHealth intervention for promoting nonexercise physical activity in type 2 diabetes patients showed good fidelity and acceptability in primary care, though challenges with cloud-computed feedback and accelerometer-app use underscore the importance of pretesting technology-based approaches.
Key Findings
Results
Patients with type 2 diabetes identified specific behavior change needs in capability and motivation domains prior to the intervention.
Behavior change needs were assessed using a modified capability, opportunity, motivation-behavior (COM-B) questionnaire
Data were collected from a separate sample of patients with T2D (n=25) before the intervention and at intervention baseline (n=119)
Participants' responses revealed 3 items in capability and 2 in motivation that stood out as perceived behavior change needs
No comparable studies were found to contextualize the findings on behavior change needs
Results
The main intervention arm demonstrated high fidelity across face-to-face sessions and telephone contacts.
Face-to-face sessions completed: 112/117 (96%)
Telephone contacts completed: 145/156 (93%)
The main intervention arm included 39 participants
Fidelity data were accumulated during the intervention through counseling cards and cloud computing
Results
Accelerometer use showed moderate mean weekly compliance but with wide variation across the intervention period.
Mean weekly accelerometer use was 54% across the intervention
Weekly accelerometer use ranged from 80% to 17% during the intervention
Participants used 24-hour accelerometers as part of the main intervention arm
Challenges were experienced especially in cloud-computed feedback and accelerometer-app use
Results
The main intervention arm showed good acceptability as rated by participants on a Likert scale.
Acceptability was assessed with a questionnaire at the end of the intervention using a Likert scale from 1 to 5
Mean acceptability scores ranged from 3.8 to 4.8 across items
Some challenges were also experienced, particularly with cloud-computed feedback and accelerometer-app use
Data analysis was mainly descriptive
Methods
The intervention was a 3-arm mHealth trial conducted in primary care targeting nonexercise physical activity in type 2 diabetes patients.
The main arm of the intervention (n=39) included 24-hour accelerometer use, a smartphone app with personal feedback, a PA leaflet, a YouTube video on walking, and individual counseling
Counseling consisted of 3 face-to-face sessions and 4 telephone contacts
Total intervention baseline sample was n=119
Implementation evaluation focused on fidelity and acceptability of the main arm
Discussion
The explanatory value of the COM-B model and the psychometric properties of the COM-B questionnaire were identified as areas requiring further attention.
A modified COM-B questionnaire was used to assess perceived behavior change needs
The authors noted that no comparable studies were found for the behavior change needs findings
The paper calls for additional research on both the COM-B model's explanatory value and the psychometric properties of the COM-B questionnaire
The behavioral framework of mHealth interventions is described as often vague in the existing literature
Aittasalo M, Tokola K, Vähä-Ypyä H, Husu P, Mänttäri A, Martiskainen T, et al.. (2026). mHealth Intervention to Promote Nonexercise Physical Activity in Patients With Type 2 Diabetes: Secondary Analysis and Implementation Study.. JMIR formative research. https://doi.org/10.2196/80304