Applying the ORBIT model to design a patient-facing mHealth app for diabetes prevention in urban primary care: translating patient perspectives into app design.

BACKGROUND

Prediabetes affects nearly one in three U.S. adults-often progressing to type 2 diabetes within 10 years. Although prediabetes is increasingly identified in primary care and prevention strategies exist, uptake remains low, particularly in urban safety-net settings. This translational gap reflects the complexity of prevention, which is preference- and context-sensitive. Mobile health could bridge this gap and improve engagement, but effective design requires understanding patient needs, barriers, and care context.

PURPOSE: Guided by the Obesity-Related Behavioral Intervention Trials (ORBIT) model, this formative study identified perspectives on prediabetes and diabetes prevention and translated them into components of a patient-facing digital intervention.

METHODS

Semi-structured qualitative interviews were conducted among 24 adult primary care patients with documented prediabetes in an urban safety-net health system. Interviews explored understanding of prediabetes, decision-making about prevention options, motivation for lifestyle change, and integration of behavioral changes into daily routines. Interviews were transcribed and analyzed using rapid qualitative analysis.

RESULTS

Participants (mean age 58.8 years; 83% women; 46% African American/Black; 46% Hispanic/Latino) described six interrelated themes: understanding the diagnosis; making informed treatment decisions; integrating lifestyle change into daily life; finding motivation; staying on track with behavior change; and navigating prevention within health and financial constraints. Themes revealed gaps in risk understanding, counseling, and action planning and were mapped to preliminary app features.

CONCLUSIONS

This study translated patient-identified needs into initial components for a patient-informed mHealth tool. The findings define early-stage content domains and behavioral targets that will inform prototype refinement, usability testing, and evaluation in primary care.