Encouraging Behavior Changes and Preventing Cardiovascular Diseases Using the Prevent Connect Mobile Health App: Conception and Evaluation of App Quality

Abstract

Background Cardiovascular diseases are a major cause of death worldwide. Mobile health apps could help in preventing cardiovascular diseases by improving modifiable risk factors such as eating habits, physical activity levels, and alcohol or tobacco consumption. Objective The aim of this study was to design a mobile health app, Prevent Connect, and to assess its quality for (1) assessing patient behavior for 4 cardiovascular risk factors (unhealthy eating, sedentary lifestyle, alcohol, and tobacco consumption) and (2) suggesting personalized recommendations and mobile health interventions for risky behaviors. Methods The knowledge base of the app is based on French national recommendations for healthy eating, physical activity, and limiting alcohol and tobacco consumption. It contains a list of patient behaviors and related personalized recommendations and digital health interventions. The interface was designed according to usability principles. Its quality was assessed by a panel of 52 users in a 5-step process: completion of the demographic form, visualization of a short presentation of the app, testing of the app, completion of the user version of the Mobile App Rating Scale (uMARS), and an open group discussion. Results This app assesses patient behaviors through specific questionnaires about 4 risk factors (unhealthy eating, sedentary lifestyle, alcohol, and tobacco consumption) and suggests personalized recommendations and digital health interventions for improving behavior. The app was deemed to be of good quality, with a mean uMARS quality score of 4 on a 5-point Likert scale. The functionality and information content of the app were particularly appreciated, with a mean uMARS score above 4. Almost all the study participants appreciated the navigation system and found the app easy to use. More than three-quarters of the study participants found the app content relevant, concise, and comprehensive. The aesthetics and the engagement of the app were also appreciated (uMARS score, 3.7). Overall, 80% (42/52) of the study participants declared that the app helped them to become aware of the importance of addressing health behavior, and 65% (34/52) said that the app helped motivate them to change lifestyle habits. Conclusions The app assessed the risky behaviors of the patients and delivered personalized recommendations and digital health interventions for multiple risk factors. The quality of the app was considered to be good, but the impact of the app on behavior changes is yet to be demonstrated and will be assessed in further studies.

Behavior Change Effectiveness Using Nutrition Apps in People With Chronic Diseases: Scoping Review

“…Furthermore, there were different diets or treatments among the studies, with variations in targeted behavioral domains and outcomes measured in the mHealth app nutrition interventions. App features for these studies included food tracking [ 8 , 39 - 41 ], physical activity tracking [ 8 , 41 , 42 ], nutrition and exercise knowledge and recommendations [ 8 , 40 - 43 ], scheduled reminders [ 39 , 40 , 42 , 43 ], clinician portals [ 41 - 43 ], connectivity to digital health devices [ 42 ], demonstration of the desired behavior [ 40 , 43 ], and challenges [ 41 ]. The aim of all studies (6/6, 100%) was to evaluate the effectiveness of mHealth in the CVD population.…”

“…Second, many studies (24/46, 52%) did not include a control group for comparison, and their sample size was small, limiting the interpretation of the results of the studies. Third, many apps are at risk of becoming rapidly obsolete owing to the fast pace at which technologies progress and, therefore, new technological innovations must be considered [ 8 ]. For example, the latest mobile technologies can connect and interact with each other, update and track personal health data in real time, and send alerts to users [ 8 ].…”

“…Therefore, mobile health (mHealth) technology is rapidly gaining popularity among health care providers and consumers [ 7 ]. mHealth technology is defined as mobile devices (ie, mobile phones or monitoring devices) intended to be worn, carried, or accessed by patients or health care providers to monitor health status or improve health outcomes [ 8 ]. Among mobile devices, the most used are smartphones, with more than three-quarters of Americans having one, and at least one-third of smartphone owners use a health app [ 7 , 9 ].…”

Football Fandom as a Platform for Digital Health Promotion and Behaviour Change: A Mobile App Case Study

“…Within the constraints of how the technologies are encoded and sports and fitness programmes are treated differently, the structural elements of smartphone health apps offer a variety of different health-tracking opportunities [ 24 ]. What we hope to accomplish with this paper is to add to the growing body of research on the lived experiences of self-tracking [ 25 ].…”

Monitoring Risk Factors and Improving Adherence to Therapy in Patients With Chronic Kidney Disease (Smit-CKD Project): Pilot Observational Study

“…Several mobile apps for the management of chronic conditions, such as diabetes and high blood pressure, are available in Google Play and the App Store [18][19][20]. Some of them are designed to monitor and correct patient behavior in order to reduce modifiable cardiovascular risk factors [21]; other solutions implement home-based rehabilitation programs for critically ill cardiovascular patients [22]. However, the large majority of these apps do not have medication monitoring as the main purpose [23], are not specifically focused on CKD patients [14,24,25], or are dedicated to patients in the late stages (eg, dialysis patients) [26].…”