ArticleJMIR human factors2026
A Mobile App (Tpro) for Symptom Management in Patients With Deep Vein Thrombosis Based on Patient-Reported Outcomes: Design and Development Using an Iterative Convergent Mixed Methods Approach.
Article in JMIR human factors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Background: Deep vein thrombosis (DVT) is a significant global health issue, often associated with a high symptom burden and reduced quality of life, especially after discharge. Traditional symptom management models are typically passive, clinician-centered, and lack real-time monitoring and feedback, which can lead to delayed interventions and poor patient engagement. While mobile health (mHealth) interventions offer a promising alternative, they require rigorous usability testing to ensure both efficacy and adoption. Objective: This study aimed to design and develop Tpro (developed by the Department of Vascular Surgery, Peking Union Medical College Hospital), a patient-reported outcome (PRO)-based mobile app for patients with DVT. Using an iterative convergent mixed methods design, the app seeks to enable proactive symptom monitoring, health education, clinician-patient interaction, and peer support, thereby optimizing its usability, functionality, and alignment with patient needs. Methods: The development followed an iterative convergent mixed methods design, comprising predevelopment and iterative optimization phases. Initial functions were informed by qualitative interviews with 14 patients with DVT. Over 4 iterative cycles, qualitative feedback and quantitative usability data (including task completion rates and User Interface Usability Questionnaire [UIUQ] scores) were concurrently collected, analyzed, and integrated via joint displays to guide refinements in content, interface, and system architecture until usability benchmarks were met. Results: The final Tpro app encompasses 4 core modules, including gamified symptom reporting, multimodal health education, clinician-patient communication, and a peer support community. Iterative testing identified and resolved key usability issues. The final prototype demonstrated high usability, achieving an excellent UIUQ score (mean 89, SD 13) and a task completion rate of 92% (12/13), indicating high user acceptance and operational reliability. Conclusions: Applying the iterative convergent mixed methods approach enabled the systematic and user-centered development of Tpro. This methodology effectively integrated diverse stakeholder feedback into a functional and engaging patient-reported outcome-based app, ready for subsequent efficacy trials. This approach offers a replicable model for developing digital health tools in complex clinical contexts.
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