Funding Acknowledgements Type of funding sources: None. Background An important aim of cardiac rehabilitation (CR) programs is to reduce the risk of further cardiac events and improve the ability of people living with cardiovascular disease to manage their symptoms. Current CR strategies focus on (lifestyle) behaviour change, however, often patients are not activated enough to generate and self-sustain this lifestyle behaviour change. To stimulate adherence to lifestyle change recommendations, health behaviour should be (self-)assessed and then optimized in a personalized treatment plan. Although lifestyle monitoring apps are emerging rapidly, these applications are mostly targeted at a single lifestyle domain and often lack clinical validation. Purpose The purpose of the study was to evaluate the usability of a self-developed mobile application (Lifestylescore), that enables (self-)assessment of all cardiovascular risk behaviour domains (e.g. body composition, physical activity and sedentary behaviour, smoking, alcohol consumption, nutrition behaviour and psychological stress), using a combination of validated instruments. Secondly, it was investigated whether the use of the app was associated with an increase in patient activation and health behaviour improvement. Methods In this single-centre, non-randomized observational pilot study patients referred for CR due to coronary artery disease (stable angina pectoris or acute coronary syndrome, or after coronary revascularization) were recruited. Patients were asked to complete the Lifestylescore application, and, in addition, the Patient Activation Measure (PAM-13), and System Usability Scale (SUS). All measurements were performed during the intake procedure (baseline) and after completion of the rehabilitation program (after three months (follow-up)). After completion of the application, patients discussed the results with their CR case manager and set individual goals. Results All participants (n = 20) completed the study. The participants scored the Lifestylescore application with a SUS-score of above average (>68). Patient activation did not increase after the CR program as compared to baseline. Although the majority of the patients acknowledged that activation for lifestyle improvement is important, only a small minority reported that they took action (Figure 1). Also, there was no improvement in lifestyle behaviour after completion of CR (Figure 2). Conclusions The Lifestylescore application showed acceptable usability among CR patients. However, its use was not associated with an increase in patient activation, nor with an improvement in lifestyle behaviour after CR. Therefore, further research is needed to evaluate how the application should be incorporated in the CR program to further increase patient’s awareness, empowerment and, ultimately, effectuate more sustained behavioral change.

Funding Acknowledgements Type of funding sources: None. Background Dietary intervention in cardiac rehabilitation (CR) plays an integral role in health promotion and improving the quality of life for those with cardiovascular diseases (CVDs). Innovative techniques offer great potential to deliver cost-effective dietary modifications by providing dietary intake self-tracking and personalized advice. Nevertheless, the time-consuming inconvenience of manual food logging has led to the development of conversational agents that alleviate the tracking burden and promote self-reflection. However, the usability of nutrition chatbots among CVD patients has not yet been investigated in clinical practice. Purpose This study aimed to examine the usability of a chatbot-based dietary assessment tool among CVD patients in a prospective observational trial and discuss the preliminary results. Methods In the clinical trial, patients who are scheduled for or recently have undergone specific surgical procedures are selected for participation. Data collection starts one week before the intervention and continues until one year after discharge. Participants collect self-reported food intake data via the chatbot several times per day for a maximum of 4 non-consecutive days every other week. Quarterly assessments are scheduled to gather feedback on the use of the system. This paper focuses on the data collected in the first quarter of this trial. The usability was measured through chatbot usage and qualitative input through interviews. Results Participant recruitment started in December 2021. Thirteen out of sixteen participants (1 female and 15 males, mean_age=62.6) completed their first quarter of the trial. We included 1267 valid data entry points by evaluating the reported items and participants' self-perceived tracking accuracy. The average response rate is 87.83%, with the average self-perceived accuracy as 8.05. Although there's no significant difference in the time they spent reporting each meal (mean 110.79s, p>0.05), we observed a significant increase in the number of reported items for each meal (mean 3.79, p<0.05) and a significant decrease in time they spent reporting each item (mean 29.69s, p<0.01). Participants explained that while getting familiar with the chatbot, they found it increasingly easier to report more items if needed, and the self-reporting became less time-consuming. During the interview, the participants shared their enthusiasm about using the chatbot for food tracking and praised its simplicity and learnability. Meanwhile, they gave suggestions to improve the chatbot: 1) involving their partners when using the chatbot; 2) knowing the dietary behaviour of their peers; 3) receiving recognition with anonymous competitions. Conclusion The chatbot was found efficient to use with reasonable high learnability among participants. With insights into the usability issues and patients' expectations from the chatbot, we will conduct further research on developing personalized recommendations.

Background Lifestyle factors such as physical fitness, dietary habits, mental stress, and sleep quality, are strong predictors of the occurrence, clinical course, and overall treatment outcomes of common cardiovascular diseases. However, these lifestyle factors are rarely monitored, nor used in daily clinical practice and personalized cardiac care. Moreover, non-adherence to long-term self-reporting of these lifestyle factors is common. In the present study, we evaluate adherence to a continuous unobtrusive and patient-friendly lifestyle monitoring system using evidence-based assessment tools. Methods In a prospective observational trial (N = 100), the project investigates usability of and adherence to a monitoring system for multiple lifestyle factors relevant to cardiovascular disease, i.e., daily physical activity levels, dietary habits, mental stress, smoking, and sleep quality. Patients with coronary artery disease, valvular disease and arrhythmias undergoing an elective intervention are asked to participate. The monitoring system consists of a secured online platform with a custom-built conversational interface—a chatbot—and a wrist-worn wearable medical device. The wrist-worn device collects continuous objective data on physical activity and the chatbot is used to collect self-report data. Participants collect self-reported lifestyle data via the chatbot for a maximum of 4 days every other week; in the same week physiological data are collected for 7 days for 24 h. Data collection starts one week before the intervention and continues until 1-year after discharge. Via a dashboard, patients can observe their lifestyle measures and adherence to self-reporting, set and track personal goals, and share their lifestyle data with practitioners and relatives. The primary outcome of the trial is adherence to using the integrated platform for self-tracking data. The secondary outcomes include system usability, determinants of adherence and the relation between baseline lifestyle behaviour and long-term patient-relevant outcomes. Discussion Systematic monitoring during daily life is essential to gain insights into patients’ lifestyle behaviour. In this context, adherence to monitoring systems is critical for cardiologists and other care providers to monitor recovery after a cardiac intervention and to detect clinical deterioration. With this project, we will evaluate patients’ adherence to lifestyle monitoring technology. This work contributes to the understanding of patient-centered data collection and interpretation, to enable personalized care after cardiac interventions in order to ultimately improve patient-relevant outcomes and reduce health care costs. Trial registration Netherlands Trial Registry (NTR) NL9861. Registered 6th of November 2021.