Document Type
Honors Thesis
Major
Computer Science
Advisor(s)
Greg Nelson
Committee Members
Katherine Weatherford Darling, Robert W. Glover, Laura Gurney
Graduation Year
May, 2025
Publication Date
2025
Abstract
Most diabetes-prevention apps prescribe generic guidance without testing what works for each individual. We designed and evaluated From Generalized Advice to Personalized Insights, a mobile platform that embeds brief N-of-1 trials within a CDC-compliant Diabetes Prevention Program. Guided by person-based participatory design (Yardley et al., 2015) and the COM-B model (Michie et al., 2011), we ran Discover-Define-Develop cycles with lifestyle coaches (n = 5). Journey mapping surfaced 29 requirements—two-thirds addressing psychological capability—that shaped a React-Native prototype automating randomized epochs and coach-mediated reflection. From the coaches’ feedback, the mixed-methods evaluation indicated high usability and that patients conducting experiments gained clearer insight into their individual response patterns. Shorter epochs boosted engagement but reduced statistical power, underscoring classic N-of-1 trade-offs. Aligning interface choices with Health-UTAUT constructs preserved workflow fit while minimizing data-entry burden. Through iterative collaboration with diabetes-prevention practitioners, the project developed and embedded self-experimentation protocols into their daily workflows, enabling systematic tracking and analysis of lifestyle interventions.
Recommended Citation
Cournane, Samson, "From Generalized Advice to Personalized Insights: Designing a Mobile App for Prediabetes Self-Management With Health Coach Input" (2025). Honors College. 932.
https://digitalcommons.library.umaine.edu/honors/932