Uptake of a Consumer-Focused mHealth Application for the Assessment and Prevention of Heart Disease: The <30 Days Study.

BACKGROUND: Lifestyle behavior modification can reduce the risk of cardiovascular disease, one of the leading causes of death worldwide, by up to 80%. We hypothesized that a dynamic risk assessment and behavior change tool delivered as a mobile app, hosted by a reputable nonprofit organization, would promote uptake among community members. We also predicted that the uptake would be influenced by incentives offered for downloading the mobile app. OBJECTIVE: The primary objective of our study was to evaluate the engagement levels of participants using the novel risk management app. The secondary aim was to assess the effect of incentives on the overall uptake and usage behaviors. METHODS: We publicly launched the app through the iTunes App Store and collected usage data over 5 months. Aggregate information included population-level data on download rates, use, risk factors, and user demographics. We used descriptive statistics to identify usage patterns, t tests, and analysis of variance to compare group means. Correlation and regression analyses determined the relationship between usage and demographic variables. RESULTS: We captured detailed mobile usage data from 69,952 users over a 5-month period, of whom 23,727 (33.92%) were registered during a 1-month AIR MILES promotion. Of those who completed the risk assessment, 73.92% (42,380/57,330) were female, and 59.38% (34,042/57,330) were <30 years old. While the older demographic had significantly lower uptake than the younger demographic, with only 8.97% of users aged ≥51 years old downloading the app, the older demographic completed more challenges than their younger counterparts (F8, 52,422 = 55.10, P<.001). In terms of engagement levels, 84.94% (44,537/52,431) of users completed 1-14 challenges over a 30-day period, and 10.03% (5,259/52,431) of users completed >22 challenges. On average, users in the incentives group completed slightly more challenges during the first 30 days of the intervention (mean 7.9, SD 0.13) than those in the nonincentives group (mean 6.1, SD 0.06, t28870=-12.293, P<.001, d=0.12, 95% CI -2.02 to -1.47). The regression analysis suggested that sex, age group, ethnicity, having 5 of the risk factors (all but alcohol), incentives, and the number of family histories were predictors of the number of challenges completed by a user (F14, 56,538 = 86.644, P<.001, adjusted R(2) = .021). CONCLUSION: While the younger population downloaded the app the most, the older population demonstrated greater sustained engagement. Behavior change apps have the potential to reach a targeted population previously thought to be uninterested in or unable to use mobile apps. The development of such apps should assume that older adults will in fact engage if the behavior change elements are suitably designed, integrated into daily routines, and tailored. Incentives may be the stepping-stone that is needed to guide the general population toward preventative tools and promote sustained behavior change.

The effectiveness of loyalty rewards to promote the use of an Internet-based heart health program.

BACKGROUND: Internet-based health programs have been shown to be effective in reducing risk for cardiovascular disease. However, their rates of enrollment and engagement remain low. It is currently unclear whether rewards from established loyalty programs can serve as a conditioned stimulus to improve the use of a freely available Internet-based program. OBJECTIVE: The objectives of the study were to (1) examine enrollment rates and levels of engagement with the My Health eSupport program between a Conditioned Reward group and a Control group, and (2) investigate the influence of loyalty rewards and participant characteristics on levels of enrollment and program engagement. METHODS: The study sample (n=142,726) consisted of individuals who were offered enrollment in an Internet-based health intervention (My Health eSupport) after completing the Heart&Stroke Risk Assessment on the Heart and Stroke Foundation website. My Health eSupport programs provided encouragement and tips for lifestyle change. This is a free, self-guided, fully automated program that proactively delivers tailored email messages at 2-week intervals based on the participant's stage of motivational "readiness" and priority for lifestyle change. Participants in the Conditioned Reward group were offered a single exposure of 20 loyalty reward points from the Air Miles loyalty program for completing the Heart&Stroke Risk Assessment (10 reward points) and enrolling in the Internet-based program (10 reward points). Meanwhile, no rewards were given to the Control group participants. All data were collected between February 1, 2011 and February 10, 2012. RESULTS: In total, 51.38% (73,327/142,726) of individuals in the Conditioned Reward group and 48.62% (69,399/142,726) of individuals in the Control group completed the Heart&Stroke Risk Assessment. Subsequently, significantly more individuals from the Conditioned Reward group (52.96%, 38,835/73,327) enrolled in the My Health eSupport program than Controls (4.07%, 2826/69,399). Regression analyses indicated that individuals were 27.9 times (95% CI 26.4-29.4; P<.001) more likely to join the My Health eSupport program when presented with loyalty rewards controlling for gender, age, education, ethnicity, employment, and number of modifiable risk factors. However, ongoing engagement level was low in both groups and it was not influenced by loyalty rewards. Instead, individuals were more likely to engage with the My Health eSupport program if they were greater than 60 years of age (OR 12.56, 95% CI 5.66-27.8; P<.001), were female (OR 1.27, 95% CI 1.09-1.46; P=.002), or had one or more modifiable risk factors (OR 1.38, 95% CI 1.31-1.45; P<.001). CONCLUSIONS: Our findings suggest that a single exposure of loyalty rewards may be used to encourage individuals to enroll in an Internet-based preventative health program, but additional strategies are required to maintain engagement level. Future studies need to examine the schedules of loyalty reward reinforcement on the long-term engagement level of Internet-based health programs.

An Internet-Based Counseling Intervention With Email Reminders that Promotes Self-Care in Adults With Chronic Heart Failure: Randomized Controlled Trial Protocol.

BACKGROUND: Chronic heart failure (CHF) is a public health priority. Its age-standardized prevalence has increased over the past decade. A major challenge for the management of CHF is to promote long-term adherence to self-care behaviors without overtaxing available health care resources. Counseling by multidisciplinary health care teams helps to improve adherence to self-care behaviors and to reduce the rate of death and hospitalization. In the absence of intervention, adherence to self-care is below recommended standards. OBJECTIVE: This trial aims to establish and evaluate a Canadian e-platform that will provide a core, standardized protocol of behavioral counseling and education to facilitate long-term adherence to self-care among patients with CHF. METHODS: Canadian e-Platform to Promote Behavioral Self-Management in Chronic Heart Failure (CHF-CePPORT) is a multi-site, double blind, randomized controlled trial with a 2 parallel-group (e-Counseling + Usual Care vs e-Info Control + Usual Care) by 3 assessments (baseline, 4-, and 12-month) design. We will identify subjects with New York Heart Association Class II or III systolic heart failure from collaborating CHF clinics and then recruit them (n=278) by phone. Subjects will be randomized in blocks within each site (Toronto, Montreal, and Vancouver). The primary outcome will be improved quality of life, defined as an increased number of subjects with an improvement of ≥5 points on the summary score of the Kansas City Cardiomyopathy Questionnaire. We will also assess the following secondary outcomes: (1) diet habits, depression, anxiety, smoking history, stress level, and readiness for change using self-report questionnaires, (2) physical activity level, current smoking status, and vagal-heart rate modulation by physiological tests, and (3) exercise capacity, prognostic indicators of cardiovascular functioning, and medication adherence through medical chart review. The primary outcome will be analyzed using generalized estimation equations with repeated measures on an intention-to-treat basis. Secondary outcomes will be analyzed using repeated-measures linear mixed models with a random effects intercept. All significant main effects or interactions in the statistical models will be followed up with post hoc contrasts using a Bonferroni correction with a 2-sided statistical significance criterion of P<.05. RESULTS: This 3.5-year, proof-of-principle trial will establish the e-infrastructure for a pan-Canadian e-platform for CHF that is comprised of a standardized, evidence-based protocol of e-Counseling. CONCLUSIONS: CHF-CePPORT is designed to improve long-term adherence to self-care behaviors and quality of life among patients with CHF. It will demonstrate a distinct Canadian initiative to build capacity for preventive eHealth services for patients with CHF. TRIAL REGISTRATION: ClinicalTrials.gov NCT01864369; http://clinicaltrials.gov/ct2/show/NCT01864369 (Archived by WebCite at http://www.webcitation.org/6Iiv6so7E).

Therapeutic benefit of internet-based lifestyle counselling for hypertension.

BACKGROUND: Preventive electronic (e)-counselling has been shown to reduce cardiovascular risk factors. However, heterogeneity in outcomes is commonly reported due to differences in e-protocols. We incorporated key features of an established behavioural therapy, motivational interviewing, to help standardize e-counselling in order to reduce blood pressure in patients with hypertension. METHODS: Subjects (n = 387, mean age = 56 years, 59% female, 72% taking ≥ 1 antihypertensive drug) were diagnosed with stage 1 or 2 hypertension. Subjects were randomized to a 4-month protocol of e-counselling (beta version of the "Blood Pressure Action Plan", Heart and Stroke Foundation of Canada) vs waitlist control (general e-information on heart-healthy living). Outcomes were systolic, diastolic, and pulse pressures, and total lipoprotein cholesterol after treatment. RESULTS: Intention to treat analysis did not find a significant group difference in outcomes due to contamination across the 2 arms of this trial. However, per protocol analysis indicated that subjects receiving ≥ 8 e-counselling messages (a priori therapeutic dose) vs 0 e-counselling messages (control) demonstrated greater reduction in systolic blood pressure (mean, -8.9 mm Hg; 95% confidence interval [CI], -11.5 to -6.4 vs -5.0 mm Hg; 95% CI, -6.7 to -3.3, P = 0.03), pulse pressure (-6.1 mm Hg; 95% CI, -8.1 to -4.1 vs -3.1 mm Hg; 95% CI, -4.3 to -1.8, P = 0.02) and total cholesterol (-0.24 mmol/L; 95% CI, -0.43 to -0.06 vs 0.05 mmol/L; 95% CI, -0.06 to 0.16, P = 0.03), but not diastolic blood pressure. CONCLUSIONS: These findings support the merit of evaluating whether e-counselling can improve blood pressure control and reduce cardiovascular risk over the long-term.

Can eHealth tools enable health organizations to reach their target audience?

Data from the health risk assessment operated by the Heart and Stroke Foundation found users were more likely to be female; married; have completed post secondary education; and report hypertension, stroke, or being overweight or obese. In developing and operating eHealth tools for health promotion, organizations should compare users to their target population(s). eHealth tools may not be optimal for reaching some higher-risk sub-groups, and a range of social marketing approaches may be required.