Long-term lifestyle monitoring adherence in patients after cardiac intervention: a prospective observational trial.
Lifestyle behaviours are important predictors of morbidity and mortality in patients with cardiovascular disease. However, structured lifestyle monitoring is insufficiently integrated into clinical practice. This study evaluated dropout and long-term adherence to an eHealth system for self-monitoring lifestyle behaviours in patients with cardiovascular disease.
Patients undergoing a cardiac intervention used an eHealth system (web application with integrated health watch and chatbot) to monitor physical activity, nutrition, stress, and sleep for 1 year. The primary outcome was dropout, defined as system disengagement. Secondary outcomes included adherence (percentage of prescribed health watch wear time and chatbot responses) and usability. The predictive value of demographic, clinical, and psychosocial factors was examined using logistic regression models. Of 100 patients (mean age 61.6 ± 10.4 years; 88% male; 45% percutaneous coronary intervention, 55% other intervention), there were 43 dropouts; most (27; 63%) occurred in the first quarter, with participation burden being the most cited reason (51%). Health watch adherence was higher than chatbot adherence (80.7% (66.6-90.3%) vs. 60.8% (30.7-82.7%), P < 0.001). Low chatbot adherence was associated with poorer mental well-being, while lower health watch adherence was associated with higher levels of depressive symptoms. System usability was rated acceptably usable (62.2 ± 14.7).
Long-term lifestyle monitoring of multiple health-related behaviours is feasible after cardiac intervention, highlighting its potential for integration into clinical practice. Patient engagement could be enhanced by targeting subgroups at risk of low adherence, particularly in the early phase, and by reducing self-reporting burden while improving usability.
Patients undergoing a cardiac intervention used an eHealth system (web application with integrated health watch and chatbot) to monitor physical activity, nutrition, stress, and sleep for 1 year. The primary outcome was dropout, defined as system disengagement. Secondary outcomes included adherence (percentage of prescribed health watch wear time and chatbot responses) and usability. The predictive value of demographic, clinical, and psychosocial factors was examined using logistic regression models. Of 100 patients (mean age 61.6 ± 10.4 years; 88% male; 45% percutaneous coronary intervention, 55% other intervention), there were 43 dropouts; most (27; 63%) occurred in the first quarter, with participation burden being the most cited reason (51%). Health watch adherence was higher than chatbot adherence (80.7% (66.6-90.3%) vs. 60.8% (30.7-82.7%), P < 0.001). Low chatbot adherence was associated with poorer mental well-being, while lower health watch adherence was associated with higher levels of depressive symptoms. System usability was rated acceptably usable (62.2 ± 14.7).
Long-term lifestyle monitoring of multiple health-related behaviours is feasible after cardiac intervention, highlighting its potential for integration into clinical practice. Patient engagement could be enhanced by targeting subgroups at risk of low adherence, particularly in the early phase, and by reducing self-reporting burden while improving usability.
Authors
Goevaerts Goevaerts, Tenbült-Van Limpt Tenbült-Van Limpt, Goossen Goossen, Birk Birk, Liu Liu, Regis Regis, Brouwers Brouwers, Lu Lu, Kop Kop, Kemps Kemps
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