A statistician-blinded randomized controlled clinical trial with a parallel group design was conducted in patients with CAD who underwent a PCI with stent implantation in the cardiology unit of a public specialty reference hospital in the province of Cádiz, Spain, between November 2019 and June 2022.

A total of 134 patients participated, 67 in the intervention group and 67 in the control group. The initial sample size proposed was 240 participants, but the increase in hospital occupancy due to the COVID-19 pandemic reduced the number of patients scheduled for coronary intervention with a nonurgent pathology. However, this sample size is sufficient to detect an effect size (Cohen d) of 0.5 on adherence to the Mediterranean diet (mean 8.7, SD 2 points) [19], time spent doing PA (mean 416.8, SD 374 min/week) [20], level of knowledge of CVRFs (mean 104.7, SD 9.7) [21], and a difference in the prevalence of stopping smoking of over 20% [22], with a 95% CI and statistical power of 90%.

The study included patients with CAD aged between 18 and 75 years who owned a smartphone with an internet connection during the whole study period.

Those excluded from the study were people with severe heart failure, congenital, structural, or serious rheumatic heart disease, chronic kidney or liver disease, physical disability or dementia, and those who were already using a health control app or whose mobile phone was incompatible with the app.

All the participants in both the mHealth group and the control group were evaluated after 36 weeks. Their digital medical records were reviewed to check and record clinical data of medical visits, recent analyses (the same data from the baseline plasma analysis), and adverse events that occurred over that period. Due to the COVID-19 pandemic, the questionnaires were administered by telephone.

A descriptive statistical analysis was performed (mean, median, SD, 95% CI, interquartile interval, frequencies, and percentages). The primary quantitative results from the 2 groups—mHealth and control—were compared using the Student 2 tailed t test (variables with normal distribution) and the Mann-Whitney U test (variables not distributed normally). The χ² or Fisher test was used for the comparison of proportions. A 2-tailed P value of <.05 was considered statistically significant. The data analysis was performed using SPSS (version 24.0; IBM Corp) for Windows.

The Biomedical Research Ethics Committee of Andalusia approved the study (003_ene19_PI-EVITE-18). The patients signed a written informed consent form. The app included data encryption mechanisms and guaranteed safety measures in accordance with current European Data Protection Regulations. This study was registered on ClinicalTrials.gov (NCT04118504).

Figure 2 shows a flowchart of the process for recruiting the participants to the clinical trial. During the recruitment period, 1327 patients underwent a PCI and were evaluated for inclusion in the study. After applying the inclusion and exclusion criteria, 1153 were excluded, and 40 refused to participate. The 134 remaining patients were randomized: 67 to the control group and 67 to the mHealth group. There were 6 dropouts in the control group during the follow-up. No participants dropped out of the intervention group. In the end, 128 were analyzed: 61 from the control group and 67 from the mHealth group.

Table 1 shows the baseline characteristics of the participants. Most were male (92/128, 71.9%) with a mean age of 59.49 (SD 8.97) years. In general, both groups were homogeneous.

This study of people with CAD after a PCI analyzed the effect of an educational intervention based on the use of an mHealth app on the following factors: changes in lifestyle in terms of diet, PA, and tobacco use; level of knowledge of a healthy lifestyle; and the control of CVRFs, therapeutic adherence, and quality of life. The results obtained show that the intervention led to significant improvements in lifestyle in terms of adherence to the Mediterranean diet, PA, and stopping smoking, and that the patients increased their knowledge about a healthy lifestyle and controlling CVRFs. The patients’ quality of life improved, and they reported a high level of satisfaction with the health care they received.

The Mediterranean diet is considered a cornerstone of a healthy lifestyle to prevent cardiovascular diseases [4,42,43]. In this study, adherence to the Mediterranean diet improved in both groups at the end of the study, but this improvement was more noticeable in the patients in the mHealth group. This group of patients also increased the frequency with which they consumed healthy foods, such as fruit, vegetables, and whole-meal cereals, and decreased the frequency with which they consumed unhealthy foods, such as red meat and industrial pastries, to a greater extent than those in the control group (Table 2). On the contrary, the clinical trial conducted by Choi et al [29] on the effectiveness of dietary advice provided to patients with heart conditions through a smartphone found that the mHealth intervention did not increase adherence to the Mediterranean diet. However, other authors, such as Widmer et al [44], reported a more favorable score for the consumption of healthy food among patients undergoing cardiac rehabilitation who used an mHealth app. Given our results, providing dietary guidance through a mobile app may be a practical way of achieving healthy changes in people’s diets, with the added advantage of using fewer resources than face-to-face visits.

As our results show, the time spent performing PA (patient-reported) was significantly higher in the mHealth group than in the control group. These results are in line with other clinical trials that observed improvements in the PA performed associated with an mHealth intervention [45-47]. However, Johnston et al [48] Did not find significant increases in the PA performed by patients using a health app for smartphones. Nevertheless, a recent meta-analysis has highlighted that mHealth apps are effective at encouraging patients to increase the amount of PA they do after a coronary event [18]. In the secondary prevention of CAD, one of the essential lifestyle changes that patients have to make is to perform regular PA, such as walking for at least 30 minutes every day [4,43]. For this reason, our results show that the mobile app was able to encourage the participants to start and continue doing more PA. However, our study did not have data available from an accelerometer as the PA was self-reported.

This study found an important decrease in the proportion of smokers and nicotine dependence measured by the Fagerström test at the end of the follow-up period in both the mHealth and control groups. However, the decrease in this addictive behavior was significantly greater among the participants in the mHealth group. Moreover, 75% (25/67) of the smokers in the mHealth group stopped smoking, while in the group receiving standard health care, only 42% (11/61) did so, even though at the beginning of the study the prevalence of smokers in the 2 groups was similar. Several meta-analyses have studied the effect of telehealth interventions on the prevalence of smoking, obtaining mixed results. While some [18,49] did not find statistically significant improvements in tobacco use when these technologies were used, another meta-analysis did observe a beneficial effect on stopping smoking among patients with CAD through the use of mHealth strategies [50]. Our positive results about stopping smoking with the use of the digital intervention could be due to several reasons, such as the support perceived by the patients and the interaction with the app that kept them motivated to change.

Our results show a significant improvement in the level of knowledge of a healthy lifestyle and the control of CVRFs among the patients using the health app compared to the control group. Few clinical trials involving mHealth interventions analyze the effectiveness of these interventions in improving the patient’s knowledge. Among these, Dorje et al [51] reported an increase in the level of knowledge among patients using a telehealth app. Furthermore, the results of the studies included in EUROASPIRE II highlighted that in patients who had experienced a coronary event, a correlation existed between knowledge of CAD and changes in lifestyle and therapeutic adherence [52]. Knowledge of the risk factors for the disease is an essential requirement for patients to decide to adopt behaviors in line with a healthy lifestyle. However, people also need to be motivated to incorporate such behavior into their daily lives [53-55]. Innovative mHealth technology could help to achieve both objectives by increasing the patients’ knowledge and motivation.

Therapeutic adherence improved to a similar extent at the end of the follow-up period in both groups, mHealth (54/67, 84%) and standard health care (44/61, 78%). Although data from previous studies indicate that adherence to treatment decreases progressively after a coronary event, reaching around 50% a year after experiencing a myocardial infarction [56-58], our results do not seem to support these data since the therapeutic adherence in both groups was greater than the figures reported by other authors. In addition, recent meta-analyses [18,59] have observed improvements in adherence to treatment in patients with cardiovascular disease with the use of mHealth apps with medication reminders or alarms on mobile devices.

Our results show that the patients in the mHealth group benefited from significant improvements in the physical component of quality of life compared with the participants receiving standard health care. These results are in partial agreement with a recent meta-analysis [18] but not with another meta-analysis [49] that did not observe significant increases in the quality of life of these patients. The favorable effects of the mHealth intervention highlighted by our results may partly be related to the remote health care option provided by this intervention, whereby patients could resolve queries without having to leave their homes. Patients were given support, thus enhancing their self-sufficiency and the perception they have of their health. Improvements in quality of life may, in turn, motivate patients to comply with secondary prevention recommendations.

The overall satisfaction with the health care received was significantly higher in the patients from the mHealth group than in the control group, and satisfaction with the mHealth app was also high (mean 44.38, SD 6.176 points out of 50). The average score for the usability of the app was 95.22 (SD 7.36) out of 100. These results agree with those obtained by Johnston et al [48]. Our positive results could be attributed to the fact that the patients perceived the app to be a support tool that provided them with information about their disease as well as the motivation to adopt a healthy lifestyle. Telehealth interventions have the potential to overcome barriers and could represent a ground-breaking alternative for providing cardiac rehabilitation to patients for whom face-to-face health care is more complicated. Factors to be taken into consideration when choosing this option could be the patient’s risk profile, preferences, and accessibility to health services.

The EVITE interactive tool provided relevant information about the disease, increased the patient’s knowledge of their health status, promoted the self-reporting of important CVRF variables, and supplied the patients with visual feedback about changes, motivating them to improve their health. The patients felt more connected with the health professionals, obviating the need for unnecessary visits for trivial reasons. Most of the patients in the mHealth group stated that they would like to continue using the interactive support tool and that they would recommend the tool to other patients.

Our results showed no significant differences between the 2 groups with regard to BMI and WC at the end of the study, although recent meta-analyses show controversial results [18,60].

Lipid variables, blood pressure, and HbA_1c did not show significant differences between the 2 groups. These results agree with recent meta-analyses [18,61], which could be due to the intensive prescription of secondary prevention medication among the participants.

Patients have been found to experience the symptoms of anxiety and depression straight after undergoing a PCI, and these may persist for months or even years [62,63]. However, our results show a decrease in the level of anxiety and depression during the follow-up period in both the mHealth group and the control group (Multimedia Appendix 1). These results are in line with previous studies [18], although not with another meta-analysis [60].

Major adverse events were very rare in both groups, as were hospital readmissions. As a result of the important improvements achieved in recent years in the treatment of patients with CAD, the prevalence of short-term adverse events is generally low in different trials.

The improvements observed in the mHealth group are clinically relevant, according to scientific evidence [4]. One year after myocardial infarction, patients who continue to smoke have worse cardiovascular outcomes and death than nonsmokers, and the long-term outcomes among those who quit smoking are comparable with those of nonsmokers [64]. We observed a 33% higher prevalence of smoking cessation in the mHealth group than in the control group.

Adults are recommended to perform at least 150-300 minutes a week of moderate-intensity PA, and additional benefits are gained with even more [4,65]. In our study, cardiologists advised the patients to walk for at least 1 hour every day, resulting in 420 minutes per week of PA. While all the participants in our study complied with the PA recommendations, those in the mHealth group performed more, so they would be expected to benefit from this because they are more active than the control group, with an important effect size (Cohen d) of 0.6. It should be noted that this study was performed in a geographical area in which the weather is generally good, which encourages people to go outside for a walk.

Adherence to the Mediterranean diet improves survival rates and reduces the risk of cardiovascular disease in individuals with CVD [66]. Moreover, greater adherence to this diet is associated with a 10% reduction in cardiovascular events or mortality [67]. In our study, the prevalence of good adherence to the Mediterranean diet (>9 points) was 15% higher among participants in the mHealth group. A meta-analysis reported a 4% lower risk of cardiovascular mortality for each additional serving of fruit and vegetables per day [68]. Likewise, a high intake of processed meat and unprocessed red meat is associated with an increased risk of atherosclerotic cardiovascular disease of 7% and 3%, respectively [69]. In our study, the prevalence of red meat consumption of ≤1 time per week was 18% higher in the mHealth group.

Knowledge of cardiovascular disease helps patients control risk factors and adopt behaviors that promote cardiovascular health [53,54]. For this reason, it could be considered that the more favorable results in the level of knowledge observed in our patients in the mHealth group could have a clinical impact.

Improving quality of life is one of the most important objectives to be achieved with CAD [70]. Thus, assessing quality of life allows the impact of the disease and its treatment on daily life to be determined. In our study, the score in the physical dimension of quality of life was statistically higher in the mHealth group, a finding that may be related to the capacity of the EVITE app to provide support to patients.

Our study has a few limitations. First, the participants included in the mHealth group agreed to participate voluntarily and gave their written consent, meaning that they may have been more motivated to adhere to secondary prevention. A second limitation could be that to participate in the mHealth programs, the patients had to have a mobile phone or tablet with an internet connection, which could suggest that the participants were younger. However, 99% of the European population currently has a mobile telephone, and 86% of homes have an internet connection [71], although our results could also be due to the fact that participants in the mHealth group had a higher socioeconomic status. Moreover, women were less represented in our study, as only 29% (36/128 of the participants belonged to this population group. The third limitation is the limited sample size and the duration of the follow-up. The barrier to recruiting more participants was that the hospital was occupied by patients with COVID-19. A larger sample size and a longer follow-up could enhance the knowledge gleaned about the efficacy of the intervention. The fourth limitation is that most of the primary outcomes were self-reported and the study was open-label, but we assumed the patients responded honestly since they filled out the questionnaire without indicating their names. The questionnaires only contained an identification number so that the statisticians could record information in the database. This was explained to the patients so that they could respond freely. The fifth limitation is detection and performance bias since the blinding of the participants was not possible because of the nature of the intervention. The coordinators and the researchers analyzing the results were blinded to the allocation of participants, however. Finally, this study was conducted at a single public specialty reference hospital, and it would be necessary to test whether the favorable effects observed are generalizable to other health care settings. Additionally, in our study, we did not carry out an economic evaluation that could provide useful information to clarify whether the implementation of this mHealth intervention in the health care of these patients is cost-effective.

This study also presents some strengths, such as the fact that the sample is representative of patients who experience a coronary event in different localities, as the study was conducted on patients treated in the cardiology unit of a reference hospital that receives patients from both rural and urban areas. In addition, all the instruments and tools used in the clinical trial were validated internationally, which allows for generalization and for the study to be compared with others. Another strength was that the trial was conducted using a smartphone app, so the intervention involved the latest, up-to-date technology. In addition, the study included exclusively patients with CAD, so the sample of patients was more homogeneous than in studies that included patients with cardiovascular disease. The inclusion of different kinds of behavioral, metabolic, and psychosocial variables provides a broad view of the results obtained with mHealth technology. Finally, most previous trials were conducted with apps that encouraged behavioral changes related to performing PA, weight loss, or therapeutic adherence but did not comprehensively tackle all the CVRFs as our app does.

Using the EVITE app with patients who have experienced a coronary event is an effective way to improve their lifestyle in terms of adherence to the Mediterranean diet, frequency of healthy food consumption, PA, stopping smoking, knowledge of a healthy lifestyle, and controlling CVRFs, quality of life, and satisfaction with the health care received.

More studies are required to examine the impact of smartphone interventions on people who have undergone a coronary event, with long-term follow-ups that analyze mortality and cardiac-cause hospitalization, because these are important yardsticks of the success of secondary prevention strategies that make it possible to establish the clinical importance of the findings. Cost analyses are also required to promote the generalized use of these tools, their implementation, and their feasibility.