TY  - JOUR
AU  - Shi, Beibei
AU  - Li, Guangkai
AU  - Wu, Shuang
AU  - Ge, Hongli
AU  - Zhang, Xianliang
AU  - Chen, Si
AU  - Pan, Yang
AU  - He, Qiang
PY  - 2024
DA  - 2024/7/31
TI  - Assessing the Effectiveness of eHealth Interventions to Manage Multiple Lifestyle Risk Behaviors Among Older Adults: Systematic Review and Meta-Analysis
JO  - J Med Internet Res
SP  - e58174
VL  - 26
KW  - eHealth
KW  - lifestyle risk behaviors
KW  - older adults
KW  - multiple health behavior change
KW  - mobile phone
AB  - Background: Developing adverse lifestyle behaviors increases the risk of a variety of chronic age-related diseases, including cardiovascular disease, obesity, and Alzheimer disease. There is limited evidence regarding the effectiveness of eHealth-based multiple health behavior change (MHBC) interventions to manage lifestyle risk behaviors. Objective: The purpose of this systematic evaluation was to assess the effectiveness of eHealth MHBC interventions in changing ≥2 major lifestyle risk behaviors in people aged ≥50 years. Methods: The literature search was conducted in 6 electronic databases—PubMed, Embase, Web of Science, Scopus, Cochrane Library, and SPORTDiscus—from inception to May 1, 2024. Eligible studies were randomized controlled trials of eHealth interventions targeting ≥2 of 6 behaviors of interest: alcohol use, smoking, diet, physical activity (PA), sedentary behavior, and sleep. Results: A total of 34 articles with 35 studies were included. eHealth-based MHBC interventions significantly increased smoking cessation rates (odds ratio 2.09, 95% CI 1.62-2.70; P<.001), fruit intake (standardized mean difference [SMD] 0.18, 95% CI 0.04-0.32; P=.01), vegetable intake (SMD 0.17, 95% CI 0.05-0.28; P=.003), self-reported total PA (SMD 0.22, 95% CI 0.02-0.43; P=.03), and objectively measured moderate to vigorous PA (SMD 0.25, 95% CI 0.09-0.41; P=.002); in addition, the interventions decreased fat intake (SMD –0.23, 95% CI –0.33 to –0.13; P<.001). No effects were observed for alcohol use, sedentary behavior, or sleep. A sensitivity analysis was conducted to test the robustness of the pooled results. Moreover, the certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework. Conclusions: eHealth-based MHBC interventions may be a promising strategy to increase PA, improve diet, and reduce smoking among older adults. However, the effect sizes were small. Further high-quality, older adult–oriented research is needed to develop eHealth interventions that can change multiple behaviors. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42023444418; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023444418 
SN  - 1438-8871
UR  - https://www.jmir.org/2024/1/e58174
UR  - https://doi.org/10.2196/58174
DO  - 10.2196/58174
ID  - info:doi/10.2196/58174
ER  -