Determinants of coronary artery disease risk factor management across three world regions

The Effects of mHealth Interventions on Quality of Life, Anxiety, and Depression in Patients With Coronary Heart Disease: Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Coronary heart disease (CHD) is the leading cause of death globally. In addition, 20% to 40% of the patients with CHD have comorbid mental health issues such as anxiety or depression, affecting the prognosis and quality of life (QoL). Mobile health (mHealth) interventions have been developed and are widely used; however, the evidence for the effects of mHealth interventions on QoL, anxiety, and depression in patients with CHD is currently ambiguous.

OBJECTIVE

In this study, we aimed to assess the effects of mHealth interventions on QoL, anxiety, and depression in patients with CHD.

METHODS

We searched the Cochrane Library, PubMed, Embase, CINAHL, Web of Science, China National Knowledge Infrastructure, and Wanfang databases from inception to August 12, 2023. Eligible studies were randomized controlled trials that involved patients with CHD who received mHealth interventions and that reported on QoL, anxiety, or depression outcomes. We used the Cochrane risk-of-bias tool for randomized trials to evaluate the risk of bias in the studies, ensuring a rigorous and methodologically sound analysis. Review Manager (desktop version 5.4; The Cochrane Collaboration) and Stata MP (version 17.0; StataCorp LLC) were used to conduct the meta-analysis. The effect size was calculated using the standardized mean difference (SMD) and its 95% CI.

RESULTS

The meta-analysis included 23 studies (5406 participants in total) and showed that mHealth interventions significantly improved QoL in patients with CHD (SMD 0.49, 95% CI 0.25-0.72; Z=4.07; P<.001) as well as relieved their anxiety (SMD -0.46, 95% CI -0.83 to -0.08; Z=2.38; P=.02) and depression (SMD -0.34, 95% CI -0.56 to -0.12; Z=3.00; P=.003) compared to usual care. The subgroup analyses indicated a significant effect favoring the mHealth intervention on reducing anxiety and depressive symptoms compared to usual care, especially when (1) the intervention duration was ≥6 months (P=.04 and P=.001), (2) the mHealth intervention was a simple one (only 1 mHealth intervention was used) (P=.01 and P<.001), (3) it was implemented during the COVID-19 pandemic (P=.04 and P=.01), (4) it was implemented in low- or middle-income countries (P=.01 and P=.02), (5) the intervention focused on mental health (P=.01 and P=.007), and (6) adherence rates were high (≥90%; P=.03 and P=.002). In addition, comparing mHealth interventions to usual care, there was an improvement in QoL when (1) the mHealth intervention was a simple one (P<.001), (2) it was implemented in low- or middle-income countries (P<.001), and (3) the intervention focused on mental health (P<.001).

CONCLUSIONS

On the basis of the existing evidence, mHealth interventions might be effective in improving QoL and reducing anxiety and depression in patients with CHD. However, large sample, high-quality, and rigorously designed randomized controlled trials are needed to provide further evidence.

TRIAL REGISTRATION

PROSPERO CRD42022383858; https://tinyurl.com/3ea2npxf.

The efficacy of mobile health in alleviating risk factors related to the occurrence and development of coronary heart disease: A systematic review and meta-analysis

The association between the efficacy of mobile health and the occurrence and development of coronary heart disease (CHD) is still unclear. Mobile health can alleviate the risk factors for CHD. PubMed, EMbase, Web of Science, The Cochrane Library, CNKI, WanFang, and VIP databases were searched from inception through May 28, 2020. Randomized controlled trials of the effect of mobile health in alleviating the risk factors of CHD's occurrence and development were included. Risks of bias were assessed by two independent reviewers by using the RevMan 5.3, GRADEpro, and RoB2.0 to generate findings. Meta-analyses were performed to investigate the effects of mobile health on risk factors for CHD. Subgroup analyses were conducted. Sixteen randomized controlled trials, including 3898 patients with CHD, were included. Meta-analysis results showed that mobile health can reduce BMI (mean difference [MD] = - 1.24, 95% CI = - 2.02 to - 0.45, p < .05), waist circumference (MD = - 4.40, 95% CI = - 4.72 to - 4.08, p < .00001), total cholesterol (TC) level (MD = - 0.43, 95% CI = - 0.64 to - 0.22, p < 0.00001), low-density lipoprotein cholesterol (LDL-C) level (MD = - 0.31, 95% CI = - 0.48 to - 0.15, p < .05), diastolic blood pressure (MD = - 2.01, 95% CI = - 3.40 to - 0.623, p < .05), and depression (MD = - 8.32, 95% CI = - 12.83 to - 3.81, p < .05) and increase high-density lipoprotein cholesterol level (MD = 0.16, 95% CI = 0.01 to 0.32, p < .05) with statistically significant differences. The results of subgroup analyses indicated that the simple mobile health intervention has more remarkable advantages in reducing BMI, TC, LDL-C, and systolic blood pressure than the complex mobile health intervention. Mobile health can alleviate the risk factors for CHD and has a certain effect on the prevention and recovery of CHD. Simple mobile health has a remarkable advantage. Limited by the quantity and quality of included studies, future research enrolling high-quality studies should be taken to verify the above conclusions.