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Evaluating the Impact of the HeartHab App on Motivation, Physical Activity, Quality of Life, and Risk Factors of Coronary Artery Disease Patients: Multidisciplinary Crossover Study
No full textBackground: Telerehabilitation approaches have been successful in supporting coronary artery disease (CAD) patients to rehabilitate at home after hospital-based rehabilitation. However, on completing a telerehabilitation program, the effects are not sustained beyond the intervention period because of the lack of lifestyle adaptations. Furthermore, decline in patients’ motivation lead to recurrence of disease and increased rehospitalization rates. We developed HeartHab, using persuasive design principles and personalization, to enable sustenance of rehabilitation effects beyond the intervention period. HeartHab promotes patients’ understanding, motivates them to reach personalized rehabilitation goals, and helps to maintain positive lifestyle adaptations during telerehabilitation.
Objective: This study aimed to investigate the impact of the HeartHab app on patients’ overall motivation, increasing physical activities, reaching exercise targets, quality of life, and modifiable risk factors in patients with CAD during telerehabilitation. The study also investigated carryover effects to determine the maintenance of effects after the conclusion of the intervention.
Methods: A total of 32 CAD patients were randomized on a 1:1 ratio to telerehabilitation or usual care. We conducted a 4-month crossover study with a crossover point at 2 months using a mixed-methods approach for evaluation. We collected qualitative data on users’ motivation, user experience, and quality of life using questionnaires, semistructured interviews and context-based sentiment analysis. Quantitative data on health parameters, exercise capacity, and risk factors were gathered from blood tests and ergo-spirometry tests. Data procured during the app usage phase were compared against baseline values to assess the impact of the app on parameters such as motivation, physical activity, quality of life, and risk factors. Carryover effects were used to gather insights on the maintenance of effects.
Results: The qualitative data showed that 75% (21/28) of patients found the HeartHab app motivating and felt encouraged to achieve their rehabilitation targets. 84% (21/25) of patients either reached or exceeded their prescribed physical activity targets. We found positive significant effects on glycated hemoglobin (P=.01; d=1.03; 95% CI 0.24-1.82) with a mean decrease of 1.5 mg/dL and high-density lipoprotein (HDL) cholesterol (P=.04; d=0.78; 95% CI 0.02-1.55) with a mean increase of 0.61 mg/dL after patients used the HeartHab app. We observed significant carryover effects on weight, HDL cholesterol, and maximal oxygen consumption (VO2 max), indicating the maintenance of effects.
Conclusions: Persuasive design techniques integrated in HeartHab and tailoring of exercise targets were effective in motivating patients to reach their telerehabilitation targets. This study demonstrated significant effects on glucose and HDL cholesterol and positive carryover effects on weight, HDL cholesterol, and VO2 max. There was also a perceived improvement in quality of life. A longer-term evaluation with more patients could possibly reveal effectiveness on other risk factors and maintenance of the positive health behavior change
Enhancing Patient Motivation through Intelligibility in Cardiac Tele-rehabilitation
No full textPhysical exercise training and medication compliance are primary components of cardiac rehabilitation. When rehabilitating independently at home, patients often fail to comply with their prescribed medication and find it challenging to interpret exercise targets or be aware of the expected efforts. Our work aims to assist cardiac patients in understanding their condition better, promoting medication adherence and motivating them to achieve their exercise targets in a tele-rehabilitation setting. We introduce a patient-centric intelligible visualization approach to present prescribed medication and exercise targets to patients. We assessed efficacy of intelligible visualizations on patients' comprehension in two lab studies. We evaluated the impact on patient motivation and health outcomes in field studies. Patients were able to adhere to medication prescriptions, manage their physical exercises, monitor their progress and gained better self-awareness on how they achieved their rehabilitation targets. Patients confirmed that the intelligible visualizations motivated them to achieve their targets better. We observed an improvement in overall physical activity levels and health outcomes of patients
HeartHab: a study to evaluate the effectiveness of an app-based telerehabilitation program in increasing physical activity levels of patients with coronary artery disease
No full textHeartHab: a study to evaluate the effectiveness of an app-based telerehabilitation program in increasing physical activity levels of patients with coronary artery disease
No full textHeartHab: a study to evaluate the effectiveness of an app-based telerehabilitation program in increasing physical activity levels of patients with coronary artery disease
No full textHeartHab: a study to evaluate the effectiveness of an app-based telerehabilitation program in increasing physical activity levels of patients with coronary artery disease
No full textDo we need to rethink the determination of exercise-related energy expenditure in cardiac telerehabilitation interventions?
No full textThe American College of Sports Medicine determined the energy consumption of daily activities and sports. Cardiac tele-rehabilitation (CTR) requires knowing how much energy people consume in daily life outside of cardiac rehabilitation activities. Therefore, we have investigated if the estimated values are valid in CTR. Data from two studies were incorporated. The first study measured ventilatory threshold (VT)1, VT2, and peak exercise on cardiopulmonary exercise testing (CPET) collected from 272 cardiac (risk) patients and compared them to the estimated oxygen consumption (VO 2) at low-to-moderate-intense exercise (3-6 metabolic equivalents [METs]). Next, a patient-tailored application was developed to support CTR using these estimated values, and the intervention (the second study) was conducted with 24 coronary artery disease patients using this application during a CTR intervention. In the first study, VO 2 at VT1, VT2 and peak exercise corresponded to 3.2 [2.8, 3.8], 4.3 [3.8, 5.3], and 5.4 [4.5, 6.2] METs, which are significantly different from the estimated VO 2 at low-to-moderate-intense exercise, especially lower in older, obese, female, and post-myocardial infarction/heart failure patients. These VO 2 varied considerably between patients. The telerehabilitation study did not show significant progress in peak VO 2 , but using the application's estimated target, 97.2% of the patients achieved their weekly target, which is a significant overestimate. The estimated and observed exercise-related energy expenditures by CPET were significantly different, resulting in an overestimation of the exercise done by the patients at home. The results can have a significant impact on the quantification of exercise dose during (tele)rehabilitation programs.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is partially funded by the FWO-ICA project EXPERT network (G0F4220N)
Suitability of exercise guidelines for the calculation of personalized exercise targets and progress monitoring in a telerehabilitation setting
No full textTopic(s): eCardiology Other Citation: Funding Acknowledgements: Special Research Fund (BOF) of Hasselt University BACKGROUND: Determination of the appropriate intensity of exercise training is critical to achieve the benefits of cardiac rehabilitation. Clinical guidelines and decision support systems (e.g. EXPERT tool) assist clinicians in selecting appropriate exercise intensities for patients. However, a recent study indicated that guidelinebased intensity domains for CVD patients seem inconsistent. PURPOSE: We aim to investigate the applicability and suitability of the exercise guidelines for the calculation of personalized exercise targets and progress monitoring in a telerehabilitation setting. METHODS: In an appbased telerehabilitation program, we prescribed guidelinebased personalized exercise targets with the EXPERT tool. The targets were converted into Metabolic Equivalent of Task (MET) values using the guidelinebased exercise intensity domains and ACSM's guidelines for exercise testing and prescription. Patients could log cardio (e.g. walking) and noncardio (e.g. gardening) physical activities in the app. Progress towards the targets was determined using ACSM's guidelines and activity specific MET values from the Compendium of Physical Activities. We evaluated our approach in a crossover trial with 32 coronary artery disease patients who used the app for 710 weeks. Application logs and CPET data (collected before and after using the app) were analysed. RESULTS: During the crossover trial, 4 patients dropped out and 4 patients did not log any activities. Of the remaining 24 patients, 83% achieved their minimum exercise targets every week and 8% reached their maximum targets at all times. In general, 63% of patients achieved their maximum exercise targets for at least half of the weeks. However, amongst patients who reached their maximal targets 70% of the time there was no significant difference in VO2 max (P=0.268). For example, one patient exceeded his maximum exercise target at all time, but still did not improve VO2 max. Furthermore, 46% of the patients reported mostly noncardio physical activities, including household chores, gardening, and mowing the lawn. We found a significant difference in achieving the minimum (P=0.018) / maximum (P=0.001) exercise target when considering only cardio activities or all physical activities logged in the app. CONCLUSION: The guidelinebased intensity domains and activity specific MET values from the Compendium of Physical Activity seem nonoptimal for determining personalized exercise targets to improve maximal exercise capacity. Patients often overachieved their prescribed exercise targets and yet failed to gain a significant increase in maximal exercise capacity. Therefore, the approach of this relatively short study was not sufficient to increase maximal exercise capacity but may be sufficient to have a positive effect on health and submaximal exercise capacity
Suitability of exercise guidelines for the calculation of personalized exercise targets and progress monitoring in a telerehabilitation setting
No full textTopic(s): eCardiology Other Citation: Funding Acknowledgements: Special Research Fund (BOF) of Hasselt University BACKGROUND: Determination of the appropriate intensity of exercise training is critical to achieve the benefits of cardiac rehabilitation. Clinical guidelines and decision support systems (e.g. EXPERT tool) assist clinicians in selecting appropriate exercise intensities for patients. However, a recent study indicated that guidelinebased intensity domains for CVD patients seem inconsistent. PURPOSE: We aim to investigate the applicability and suitability of the exercise guidelines for the calculation of personalized exercise targets and progress monitoring in a telerehabilitation setting. METHODS: In an appbased telerehabilitation program, we prescribed guidelinebased personalized exercise targets with the EXPERT tool. The targets were converted into Metabolic Equivalent of Task (MET) values using the guidelinebased exercise intensity domains and ACSM's guidelines for exercise testing and prescription. Patients could log cardio (e.g. walking) and noncardio (e.g. gardening) physical activities in the app. Progress towards the targets was determined using ACSM's guidelines and activity specific MET values from the Compendium of Physical Activities. We evaluated our approach in a crossover trial with 32 coronary artery disease patients who used the app for 710 weeks. Application logs and CPET data (collected before and after using the app) were analysed. RESULTS: During the crossover trial, 4 patients dropped out and 4 patients did not log any activities. Of the remaining 24 patients, 83% achieved their minimum exercise targets every week and 8% reached their maximum targets at all times. In general, 63% of patients achieved their maximum exercise targets for at least half of the weeks. However, amongst patients who reached their maximal targets 70% of the time there was no significant difference in VO2 max (P=0.268). For example, one patient exceeded his maximum exercise target at all time, but still did not improve VO2 max. Furthermore, 46% of the patients reported mostly noncardio physical activities, including household chores, gardening, and mowing the lawn. We found a significant difference in achieving the minimum (P=0.018) / maximum (P=0.001) exercise target when considering only cardio activities or all physical activities logged in the app. CONCLUSION: The guidelinebased intensity domains and activity specific MET values from the Compendium of Physical Activity seem nonoptimal for determining personalized exercise targets to improve maximal exercise capacity. Patients often overachieved their prescribed exercise targets and yet failed to gain a significant increase in maximal exercise capacity. Therefore, the approach of this relatively short study was not sufficient to increase maximal exercise capacity but may be sufficient to have a positive effect on health and submaximal exercise capacity
HeartHab: From Persuasion to Self-management in Cardiac Tele-rehabilitation
No full textCardiovascular disease (CVD) is the leading cause of morbidity and influences mortality globally. Cardiac rehabilitation and secondary prevention have proven to be effective in minimizing risk and recurrence of disease. The penetration of e-health and mobile health (mHealth) technologies over recent years offers great
potential for enabling remote healthcare delivery. In the context of cardiac rehabilitation, such technologies play a pivotal role in supporting telemonitoring and tele-rehabilitation of patients. Nonetheless, there lacks a deeper understanding of patient and caregiver needs in order to provide tailored and comprehensive
solutions. Furthermore, during tele-rehabilitation, there is lack of support to
motivate patients in gradually changing their unhealthy lifestyle habits and foster sustained health behavior change.
This dissertation investigates the challenges in the uptake of and adherence to cardiac rehabilitation programs. On one hand, it integrates persuasive technology alongside user-centered approaches to motivate patients and increase adherence to
rehabilitation goals. On the other hand, it bridges the needs of patients and caregivers’ perspectives to deliver a tailored and comprehensive rehabilitation solution.
To this end, I present 3 key contributions in this dissertation and add to the existing knowledge in domains of Human-Computer Interaction (HCI) and cardiac tele-rehabilitation. I present the patient-centered HeartHab application supported by a caregiver-centered dashboard application that forms a tailored comprehensive tele-rehabilitation solution. I delve into how we translated theories on behavior change and persuasion into the design of the HeartHab app. Finally, I present the impact of the comprehensive tele-rehabilitation solution on patients’ motivation, health and quality of life.
The work presented in this dissertation aims to address most of the current problems in the uptake of cardiac tele-rehabilitation and adherence to rehabilitation goals. While the systems presented in this dissertation are specific to cardiac rehabilitation, the overarching methods and concepts can be leveraged by other researchers working in similar health domains targeting patient motivation and health behavior change
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