Development of a Mobile App for Remote Postoperative Rehabilitation Monitoring

Thesis Abstract

Postoperative rehabilitation is a critical phase in patient recovery, yet it faces significant challenges related to patient adherence, accessibility, and timely monitoring, particularly in geographically remote areas. These issues often lead to suboptimal recovery outcomes and increased healthcare costs due to delayed interventions and complications. The study aims to develop and evaluate a mobile application designed to remotely monitor and support patients during postoperative rehabilitation, thereby improving adherence, facilitating real-time clinical feedback, and optimizing recovery trajectories. The specific objectives include (1) designing a user-centered mobile app integrating evidence-based rehabilitation protocols and real-time data capture; (2) assessing the feasibility and usability of the app among postoperative patients; (3) examining the app’s impact on patient adherence to prescribed rehabilitation exercises; and (4) evaluating the app’s effectiveness in improving clinical outcomes compared to standard care. The research adopts a mixed-methods approach, combining quantitative and qualitative data collection and analysis. A quasi-experimental design will be employed involving a sample of 200 postoperative patients recovering from orthopaedic procedures, recruited from two tertiary hospitals. Participants will be randomly assigned to either an intervention group, which will utilize the mobile app for a six-week rehabilitation period, or a control group receiving conventional face-to-face supervision. Data collection instruments include standardized adherence questionnaires, usability scales, and clinical recovery metrics such as range of motion, pain levels, and functional scores. Semi-structured interviews will also be conducted with a subset of 30 participants to explore user experiences and barriers to app utilization. The reliability and validity of quantitative instruments will be established through Cronbach’s alpha coefficients and pilot testing, respectively. Data analysis will employ descriptive statistics to summarize demographic and baseline characteristics, while inferential analyses will include t-tests and chi-square tests to compare adherence rates and clinical outcomes between groups. Logistic regression analysis will identify predictors of adherence, and thematic analysis will be applied to qualitative interview transcripts. The Unified Theory of Acceptance and Use of Technology (UTAUT) and Social Cognitive Theory will underpin the app's conceptual framework, guiding the assessment of factors influencing technology adoption and behavioral change. Expected findings anticipate that the mobile app will significantly increase patient adherence to prescribed rehabilitation exercises, improve clinical recovery metrics, and be rated as usable and acceptable by patients. It is also expected that factors such as perceived ease of use, self-efficacy, and social support will positively influence app adoption and engagement. The study aims to demonstrate that remote monitoring through mobile technology is a feasible, effective, and scalable solution for postoperative care, particularly in resource-limited settings. This research will contribute to the growing body of knowledge on digital health interventions by providing empirical evidence of the effectiveness of mobile apps in enhancing postoperative rehabilitation outcomes. It offers a theoretically grounded, patient-centered solution that leverages ICT to bridge gaps in traditional physiotherapy practice, thereby informing best practices and policy formulations for integrating tele-rehabilitation into routine care. The main conclusion is that a well-designed mobile application can serve as an effective adjunct to conventional physiotherapy, fostering improved adherence, patient engagement, and clinical recovery. Recommendations include the adoption of similar digital tools in diverse healthcare contexts, with ongoing refinement based on user feedback and technological advancements. Future studies should explore long-term outcomes, integration with electronic health records, and expansion to other clinical populations.