RESUMEN
Background: Mobile health (mHealth) apps can be used for cardiovascular disease (CVD) prevention. User-centered design, evidence-based content and user testing can be applied to ensure a high level of usability and adequate app access. Objective: To develop and evaluate an mHealth app (HerzFit) for CVD prevention. Methods: HerzFit´s development included a user-centered design approach and guideline-based content creation based on the identified requirements of the target group. Beta testing and a preliminary usability evaluation of the HerzFit prototype were performed. For evaluation, German versions of the System Usability Scale (SUS) and the mHealth App Usability Questionnaire (GER-MAUQ) as well as free text feedback were applied. Results: User-centered design thinking led to the definition of four personas. Based on their requirements, HerzFit enables users to individually assess, monitor, and optimize their cardiovascular risk profile. Users are also provided with a variety of evidence-based information on CVD and their risk factors. The user interface and system design followed the identified functional requirements. Beta-testers provided feedback on the structure and functionality and rated the usability of HerzFit´s prototype as slightly above average both in SUS and GER-MAUQ rating. Participants positively noted the variety of functions and information presented in HerzFit, while negative feedback mostly concerned wearable synchronization. Conclusions: The present study demonstrates the user-centered development of a guideline-based mHealth app for CVD prevention. Beta-testing and a preliminary usability study were used to further improve the HerzFit app until its official release.
RESUMEN
BACKGROUND: A total of 6,500 to 8,000 steps per day are recommended for cardiovascular secondary prevention. The aim of this research was to examine how many steps per day patients achieve during ambulant cardiac rehabilitation (CR), and if there is a correlation between the number of steps and physical and cardiological parameters. METHODS: In all, 192 stable CR patients were included and advised for sealed pedometry. The assessed parameters included maximum working capacity and heart rate, body mass index (BMI), New York Heart Association (NYHA) class, ejection fraction (EF), coronary artery disease status, beta-blocker medication, age, sex, smoking behavior, and laboratory parameters. A regularized regression approach called least absolute shrinkage and selection operator (LASSO) was used to detect a small set of explanatory variables associated with the response for steps per day. Based on these selected covariates, a sparse additive regression model was fitted. RESULTS: The model noted that steps per day had a strong positive correlation with maximum working capacity (P=0.001), a significant negative correlation with higher age (P=0.01) and smoking (smoker: P<0.05; ex-smoker: P=0.01), a positive correlation with high-density lipoprotein (HDL), and a negative correlation with beta-blockers. Correlation between BMI and walking activity was nonlinear (BMI 18.5-24: 7,427±2,730 steps per day; BMI 25-29: 6,448±2,393 steps/day; BMI 30-34: 6,751±2,393 steps per day; BMI 35-39: 5,163±2,574; BMI >40: 6,077±1,567). CONCLUSION: Walking activity during CR is reduced in patients who are unfit, older, smoke, or used to smoke. In addition to training recommendations, estimated steps per day during CR could be seen as a baseline orientation that helps patients to stay generally active or even to increase activity after CR.