Digital Health (Mar 2024)

mHealth App to improve medication adherence among older adult stroke survivors: Development and usability study

  • Wenjing Cao,
  • Juan Wang,
  • Yuhui Wang,
  • Intan Idiana Hassan,
  • Azidah Abdul Kadir

DOI
https://doi.org/10.1177/20552076241236291
Journal volume & issue
Vol. 10

Abstract

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Background Effective medication adherence is vital for older adult stroke survivors, yet 20–33% cease treatment within a year post-discharge, increasing risks of recurrent strokes and mortality. A mobile health (mHealth) app could be a novel tool to improve medication adherence among stroke survivors because of its potential to increase patient empowerment. A few stroke-related apps provide information and support to stroke survivors. However, none have focused on medication adherence and documented their development and evaluation process, particularly those focused on this older population. Objective This study aims to design and develop a smartphone app called OASapp to improve medication adherence among older adult stroke survivors and evaluate its usability. Methods OASapp was developed in a three-phase development process. Phase 1 is the exploration phase (including a cross-sectional survey, a systematic review, a search for stroke apps on the app stores of Apple App Store and Google Play Store, and a nominal group technique). In phase 2, a prototype was designed based on the Health Belief Model and Technology Acceptance Model. In phase 3, Alpha and Beta testing was conducted to validate the app. Results Twenty-five features for inclusion in the app were collected in round one, and 14 features remained and were ranked by the participants during nominal group technique. OASapp included five core components (medication management, risk factor management, health information, communication, and stroke map). Users of OASapp were satisfied based on reports from Alpha and Beta testing. The mean Usability Metric for User Experience (UMUX) score was 71.4 points (SD 14.6 points). Conclusion OASapp was successfully developed using comprehensive, robust, and theory-based methods and was found to be highly accepted by users. Further research is needed to establish the clinical efficacy of the app so that it can be utilized to improve clinically relevant outcomes.