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.