Development and Evaluation of a Mobile App for Medication Adherence Support

Thesis Abstract

Non-adherence to prescribed medication regimens remains a significant challenge in managing chronic diseases, contributing to suboptimal treatment outcomes and increased healthcare costs worldwide. Despite the proliferation of digital health interventions, there is a paucity of tailored mobile applications explicitly designed to enhance medication adherence among diverse patient populations. This study aims to develop, implement, and evaluate a user-centered mobile application that supports medication adherence for patients managing chronic illnesses such as hypertension and diabetes mellitus. The specific objectives include designing the app based on behavioral change theories, assessing its usability and acceptability, and measuring its impact on medication adherence over a six-month period. Employing a mixed-methods research design, the study encompasses both qualitative and quantitative approaches. The development phase utilizes the Design Science Research methodology, guided by the Health Belief Model and the Theory of Planned Behavior, to inform app features that address motivational, cognitive, and behavioral barriers to adherence. The target population comprises 300 adult patients diagnosed with hypertension or diabetes, recruited from outpatient clinics within a metropolitan healthcare facility. A stratified sampling technique ensures representative inclusion across age, gender, and technological proficiency. A subset of 30 participants is selected for in-depth usability testing through think-aloud protocols and semi-structured interviews, while the broader cohort participates in a quasi-experimental pre-test/post-test design. Data collection instruments include validated medication adherence scales (e.g., Medication Adherence Report Scale), usability questionnaires (System Usability Scale), and app usage analytics. The reliability and validity of instruments are established through pilot testing and Cronbach’s alpha analysis. Quantitative data undergo descriptive statistics, paired t-tests, and multiple regression analysis to evaluate changes in adherence scores, identify predictors of adherence, and examine the relationship between app engagement and behavioral outcomes. Qualitative data from interviews are analyzed thematically using NVivo software, allowing exploration of user experiences, perceived barriers, and facilitators to app use. It is anticipated that the app will demonstrate high usability scores (mean SUS score >70), with significant improvement in medication adherence among users post-intervention (p < 0.01). Higher engagement levels are expected to correlate positively with adherence improvement, supporting the app’s efficacy. The findings are expected to substantiate the theoretical framework’s application in digital health interventions and elucidate behavioral factors influencing adherence behaviors. The study contributes to existing knowledge by providing a rigorously developed and empirically evaluated mobile application tailored to medication adherence support, filling a notable gap in digital health tools designed for chronic disease management in resource-constrained settings. It offers insights into user-centered design processes, theoretical underpinning, and practical considerations for deploying mHealth solutions within clinical workflows. In conclusion, the developed mobile app is expected to serve as an effective tool for enhancing medication adherence, thereby improving clinical outcomes and reducing healthcare burdens. Recommendations include integrating the app into routine care, conducting larger-scale randomized controlled trials for long-term efficacy assessment, and exploring its scalability across different chronic conditions and diverse populations. Future research should focus on customizable features, integration with electronic health records, and evaluating cost-effectiveness to inform policy and practice in digital health interventions.