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Patient-Reported Experiences With Long-Term Lifestyle Self-Monitoring in Heart Disease: Mixed Methods Study (Preprint)

Mayra Goevaerts, Nicole Tenbült - Van Limpt, Willem J Kop, Hareld Kemps, Yuan Lu

2025

Vollständiger Abstract

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BACKGROUND Lifestyle behaviors strongly predict cardiovascular morbidity and mortality, emphasizing the need for strategies that support sustained lifestyle changes in patients with cardiac disease. Digital health solutions, including wearables, mobile apps, and chatbots, enable self-monitoring of lifestyle behaviors but often face challenges with engagement and usability. While self-monitoring systems can increase awareness and accountability, maintaining user engagement remains crucial for their effectiveness in promoting behavior change and long-term improvements. OBJECTIVE This study evaluated patient experiences with a lifestyle monitoring system combining a web application, health watch, and chatbot. We explored facilitators of and barriers to long-term adherence and assessed the impact of self-monitoring on lifestyle awareness and behavior change in patients with cardiac disease. METHODS We conducted a mixed methods study with patients who used an eHealth platform for self-monitoring lifestyle behaviors during 1 year following an invasive cardiac procedure. This study included 100 patients (mean age 61.6, SD 10.4 y; n=88, 88% male) comprising both completers (n=57, 57%) and dropouts (n=43, 43%). Patients engaged in quarterly phone interviews and questionnaires and completed an end-of-study questionnaire. Completers participated in a structured evaluation interview; dropouts provided a reason for discontinuation. Quantitative and qualitative data analyses focused on usability, long-term adherence facilitators and barriers, lifestyle awareness, and behavior change. RESULTS Patients completed 157 quarterly questionnaires (n=145, 92.4% by completers and n=12, 7.6% by dropouts) and 217 phone interviews (n=171, 78.8% with completers and n=46, 21.2% with dropouts). In total, 77 patients (of whom n=54, 70% were completers and n=23, 30% were dropouts) completed end-of-study questionnaires, and 98% (56/57) of completers participated in the evaluation interviews. Completers reported higher perceptions of the platform’s usefulness, ease of use, and satisfaction (P<.001 in all cases) than dropouts. Dropout reasons linked to self-monitoring (34/43, 79%) included high self-report burden and dissatisfaction with the chatbot, poor overall usability experience, health watch technical challenges causing frustration, limited perceived usefulness, mental stress from self-monitoring, and low motivation. Key facilitators of long-term engagement included routine formation, structured reminders, and minimal effort associated with the wearable. Barriers included repetitive chatbot questions (causing cognitive burden) and technical issues with the health watch. Self-monitoring increased lifestyle awareness among completers, particularly regarding physical activity (25/56, 45%) and nutrition (29/56, 52%), with smaller effects for sleep quality (7/56, 13%) and mental stress (1/56, 2%). It facilitated behavior change in physical activity and nutrition (16/56, 29% each) and sleep quality (4/56, 7%) but not in mental stress. Adaptive personalization, mobile accessibility, and real-time feedback could improve adherence. CONCLUSIONS Fostering routine formation while minimizing patient burden through personalized, flexible, and adaptive features is important for sustained patient engagement in eHealth monitoring systems. Enhancing relevance and usability while reducing complexity and technical barriers can optimize digital health tools and promote lasting behavior change. INTERNATIONAL REGISTERED REPORT RR2-10.1186/s12872-023-03222-x

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Publikationsdaten

Autor:innen
Mayra Goevaerts, Nicole Tenbült - Van Limpt, Willem J Kop, Hareld Kemps, Yuan Lu
Quelle
JMIR Publications Inc.
Publikation
2025-01-01
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Mayra Goevaerts, Nicole Tenbült - Van Limpt, Willem J Kop, Hareld Kemps, Yuan Lu (2025). Patient-Reported Experiences With Long-Term Lifestyle Self-Monitoring in Heart Disease: Mixed Methods Study (Preprint). https://doi.org/10.1186/s12872-026-06452-x
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