Digital Technology Interventions for Risk Factor Modification in Patients With Cardiovascular Disease: Systematic Review and Meta-analysis

Abstract

Background: Approximately 50% of cardiovascular disease (CVD) cases are attributable to lifestyle risk factors. Despite widespread education, personal knowledge, and efficacy, many individuals fail to adequately modify these risk factors, even after a cardiovascular event. Digital technology interventions have been suggested as a viable equivalent and potential alternative to conventional cardiac rehabilitation care centers. However, little is known about the clinical effectiveness of these technologies in bringing about behavioral changes in patients with CVD at an individual level.

Objective: The aim of this study is to identify and measure the effectiveness of digital technology (eg, mobile phones, the internet, software applications, wearables, etc) interventions in randomized controlled trials (RCTs) and determine which behavior change constructs are effective at achieving risk factor modification in patients with CVD.

Methods: This study is a systematic review and meta-analysis of RCTs designed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) statement standard. Mixed data from studies extracted from selected research databases and filtered for RCTs only were analyzed using quantitative methods. Outcome hypothesis testing was set at 95% CI and P=.05 for statistical significance.

Results: Digital interventions were delivered using devices such as cell phones, smartphones, personal computers, and wearables coupled with technologies such as the internet, SMS, software applications, and mobile sensors. Behavioral change constructs such as cognition, follow-up, goal setting, record keeping, perceived benefit, persuasion, socialization, personalization, rewards and incentives, support, and self-management were used. The meta-analyzed effect estimates (mean difference [MD]; standard mean difference [SMD]; and risk ratio [RR]) calculated for outcomes showed benefits in total cholesterol SMD at -0.29 [-0.44, -0.15], P<.001; high-density lipoprotein SMD at -0.09 [-0.19, 0.00], P=.05; low-density lipoprotein SMD at -0.18 [-0.33, -0.04], P=.01; physical activity (PA) SMD at 0.23 [0.11, 0.36], P<.001; physical inactivity (sedentary) RR at 0.54 [0.39, 0.75], P<.001; and diet (food intake) RR at 0.79 [0.66, 0.94], P=.007. Initial effect estimates showed no significant benefit in body mass index (BMI) MD at -0.37 [-1.20, 0.46], P=.38; diastolic blood pressure (BP) SMD at -0.06 [-0.20, 0.08], P=.43; systolic BP SMD at -0.03 [-0.18, 0.13], P=.74; Hemoglobin A_1C blood sugar (HbA_1c) RR at 1.04 [0.40, 2.70], P=.94; alcohol intake SMD at -0.16 [-1.43, 1.10], P=.80; smoking RR at 0.87 [0.67, 1.13], P=.30; and medication adherence RR at 1.10 [1.00, 1.22], P=.06.

Conclusions: Digital interventions may improve healthy behavioral factors (PA, healthy diet, and medication adherence) and are even more potent when used to treat multiple behavioral outcomes (eg, medication adherence plus). However, they did not appear to reduce unhealthy behavioral factors (smoking, alcohol intake, and unhealthy diet) and clinical outcomes (BMI, triglycerides, diastolic and systolic BP, and HbA_1c).

Keywords: behavior; cardiac rehabilitation; cardiovascular diseases; digital technologies; eHealth; mHealth; meta-analysis; mobile phone; risk factors; systematic review; telehealth.

Figure 1

Database search flowchart. RCT: randomized controlled trial.

Figure 2

Outcomes of the examined studies for BMI.

Figure 3

Outcomes of the examined studies for total cholesterol.

Figure 4

Outcomes of the examined studies for high-density lipoprotein.

Figure 5

Outcomes of the examined studies for low-density lipoprotein.

Figure 6

Outcomes of the examined studies for triglycerides.

Figure 7

Outcomes of the examined studies for diastolic blood pressure.

Figure 8

Outcomes of the examined studies for systolic blood pressure.

Figure 9

Outcomes of the examined studies for blood sugar HbA_1c.

Figure 10

Outcomes of the examined studies for physical activity.

Figure 11

Outcomes of the examined studies for physical inactivity.

Figure 12

Outcomes of the examined studies for food intake.

Figure 13

Outcomes of the examined studies for healthy diet.

Figure 14

Outcomes of the examined studies for unhealthy food intake.

Figure 15

Outcomes of the examined studies for alcohol consumption.

Figure 16

Outcomes of the examined studies for smoking.

Figure 17

Medication adherence for all trials.

Figure 18

Medication adherence for multiple treatment with SMS.

Figure 19

Medication adherence for target treatment only with SMS text message intervention.

Figure 20

Medication adherence for treatment with non-sms intervention.

Figure 21

Medication adherence treatment for all sms intervention.