Background Despite the potential of mobile health (mHealth) interventions to facilitate the early detection of signs of heart failure (HF) decompensation and provide personalized management of symptoms, the outcomes of such interventions in patients with HF have been inconsistent. As engagement with mHealth is required for interventions to be effective, poor patient engagement with mHealth interventions may be associated with mixed evidence. It is crucial to understand how engagement with mHealth interventions is measured in patients with HF, and the effects of engagement on HF outcomes. Objective In this review, we aimed to describe measures of patient engagement with mHealth interventions and the effects of engagement on HF outcomes. Methods We conducted a systematic literature search in 7 databases for relevant studies published in the English language from 2009 to September 2021 and reported the descriptive characteristics of the studies. We used content analysis to identify themes that described patient engagement with mHealth interventions in the qualitative studies included in the review. Results We synthesized 32 studies that operationalized engagement with mHealth interventions in 4771 patients with HF (3239/4771, 67.88%, male), ranging from a sample of 7 to 1571 (median 53.3) patients, followed for a median duration of 90 (IQR 45-180) days. Patient engagement with mHealth interventions was measured only quantitatively based on system usage data in 72% (23/32) of the studies, only qualitatively based on data from semistructured interviews and focus groups in 6% (2/32) of studies, and by a combination of both quantitative and qualitative data in 22% (7/32) of studies. System usage data were evaluated using 6 metrics of engagement: number of physiological parameters transmitted (19/30, 63% studies), number of HF questionnaires completed (2/30, 7% studies), number of log-ins (4/30, 13% studies), number of SMS text message responses (1/30, 3% studies), time spent (5/30, 17% studies), and the number of features accessed and screen viewed (4/30, 13% studies). There was a lack of consistency in how the system usage metrics were reported across studies. In total, 80% of the studies reported only descriptive characteristics of system usage data. The emotional, cognitive, and behavioral domains of patient engagement were identified through qualitative studies. Patient engagement levels ranged from 45% to 100% and decreased over time. The effects of engagement on HF knowledge, self-care, exercise adherence, and HF hospitalization were inconclusive. Conclusions The measures of patient engagement with mHealth interventions in patients with HF are underreported and lack consistency. The application of inferential analytical methods to engagement data is extremely limited. There is a need for a working group on mHealth that may consolidate the previous operational definitions of patient engagement into an optimal and standardized measure.

Background: Mobile Health applications (mHealth apps) have been demonstrated as an effective strategy for improving self-care abilities in patients with heart failure (HF). However, the uptake of the apps by patients remains low. Little is known about the patient’s perspectives on the factors that influence their uptake of the apps. This study explored HF patients’ perspectives on the barriers and motivators to the uptake and utilization of mHealth apps. Method: Semi-structure interviews and demographic questionnaires were used to gather data from patients with HF (N= 43) recruited from an academic medical center. An in-depth analysis of the interviews was conducted using a deductive thematic approach with the help of qualitative software, Atias.ti version 8. Results: Among the participants ( median age = 62 [35-92] years, mean±SD ejection fraction = 37.3±17, 41.9% female, 70% smartphone owners), 90.7% (n =39) had no prior use of mHealth apps for self-care. The majority of the participants with no prior use of mhealth (79.5%, n = 31), including 64.7% (n= 17) of participants aged 65yrs and above, expressed an intention to use the apps for self-care. All the participants (100%) stated that their healthcare providers (HCP) had never recommended the use of mHealth apps for self-care. Other barriers included lack of knowledge of the apps, the perceived financial cost of mHealth apps or smartphones, concern for privacy, and security of personal information, resistance to the change of previous self-care strategies, and perceived technology incompetence. Motivators to the uptake of mHealth included perceived usefulness of mHealth apps, mHealth apps’ ease of use, and the belief that the use of mHealth apps may alleviate perceived threat to health, and availability of technical support. Conclusion: This study suggests that patients with HF are willing to use mHealth apps to improve their self-care abilities. Thus, the effort to improve patients’ perceptions of mHealth apps’ usefulness and HCP recommendation of the apps are warranted to turn patients' “intention to use” to actual apps usage.

Aims Despite evidence-based recommendations for clinically stable patients with heart failure (HF) to engage in unsupervised exercise, the minimum cumulative dose of exercise per week associated with improvement in HF outcomes, especially in patients with poor functional capacity, has not been examined. We examined whether patients with HF and poor functional capacity who reported engagement in a guideline-recommended minimum weekly exercise had longer event-free survival than patients who did not exercise. Methods and results This analysis included 310 patients with HF who had completed the Duke Activity Status Index (DASI) and reported their level of engagement in exercise. Patients were grouped into good and poor functional capacity using a DASI cut-point of ≥19 and then further stratified based on their self-reported exercise level: high (≥60 min/week) and low (<60 min/week). Cox regression modelling was used to predict event-free survival for the four groups after adjusting for covariates. Patients (mean age = 61.6 ± 11.4 years, 30.3% female, 44.2% NYHA Classes III–IV) were followed for a median of 362 days. There were eight deaths and 108 all-cause hospitalizations. Patients with poor functional capacity who reported high exercise engagement had a 36% lower risk of all-cause hospitalization or mortality compared with patients with poor functional capacity who reported low exercise engagement (hazard ratio: 0.64, P = 0.028). Conclusion Self-reported engagement in a minimum of 60 min of exercise per week was associated with a significant improvement in event-free survival, even in patients with HF with low functional capacity. These results provide evidence that this dose of exercise is beneficial in patients with HF and poor functional capacity.

Introduction: Videoconferencing (VC) technology is one approach to increasing access to interventions targeting cardiovascular disease (CVD) risk reduction among rural dwellers, particularly caregivers of those with chronic illnesses. It is important to understand factors affecting engagement with such interventions in order to improve engagement. We examined demographic, clinical, psychological, and technological factors that predicted engagement with VC-based interventions. Method: We used data from the intervention group (n=131) in a randomized controlled trial of a CVD risk reduction intervention. Engagement was defined as the number of interventions or booster sessions (total 26 possible) completed per participant. Depressive symptoms and caregiving stress were measured with the Patient Health Questionnaire and Zarit Burden Interview respectively. Negative binomial regression with backward stepwise regression was used to determine predictors of engagement. Result: Among participants (mean age = 54.83 ± 13.8 years, 79.4% female) the mean engagement rate was 17.08 ± 7.2 sessions. Higher level of depressive symptoms (incidence rate (IR) = 0.98 , p < .05) was associated with decreased engagement. Higher caregiving burden (IR= 1.008, p < .01) and, employment status (working in the home or retired compared to. employment outside the home IR: 1.25, p < .03) were associated with increased engagement. The association between age and engagement rate was dependent on level of technical problems ( IR = 1.02, p < .00 ), and financial status (average vs. low IR = 1.02, p < .02, high vs. low IR = 1.04, p < .00) (Fig. 1). Conclusion: Depressive symptoms, older age in those with low financial status, and working outside the home were associated with low engagement rate with VC-based intervention targeting CVD-risk reduction among rural caregivers. Thus, tailoring such interventions to address these factors is essential in improving engagement in remote interventions.

BACKGROUND Publicly available patient-focused mobile health applications (mHealth apps) are being increasingly integrated into routine heart failure (HF)-related self-care. However, there is a dearth of research on patients’ experiences using mHealth apps for self-care in real-world settings. OBJECTIVE The purpose of this study was to explore patients’ experiences using a commercially available mHealth app, OnTrack to Health, for HF self-care in a real-world setting. METHODS Patient satisfaction, measured with a 5-point Likert scale and an open-ended survey were used to gather data from 23 patients with HF who were provided the OnTrack to Health app as a part of routine HF management. A content analysis of patients’ responses was conducted with qualitative software, Atlas. ti version 8. RESULTS Patients (median IQR age 64, 57-71 years; 17/23, 74% male) used OnTrack to Health for a median(IQR) duration of 164 (51-640) days before the survey. All patients reported excellent experiences related to app use and would recommend the app to other patients with HF. Five themes emerged from the responses to the open-ended questions: (1) features that enhanced self-care of HF (medication tracker, graphic performance feedback and automated alerts, secured messaging features, and HF self-care education); (2) perceived benefits (provided assurance of safety, improved HF self-care, and decreased hospitalization rates ); (3) challenges with using apps for self-care (giving up previous self-care strategies); (4) facilitators (perceived ease of use, availability of technical support); and (5) suggested improvements (streamlining data entry, integration of apps with an electronic medical record, and personalization of app features). CONCLUSIONS Patients were satisfied with using Ontrack to Health for self-care. They perceived the features of the app as valuable tools for improving self-care ability and decreasing hospitalization rates. The development of apps in collaboration with end-users is essential to ensure high-quality patient experiences related to app use for self-care.