Efficacy of e-health interventions for smoking cessation management in smokers: a systematic review and meta-analysis

Shen Li, Zhan Qu, Yiyang Li,Xuelei Ma

ECLINICALMEDICINE(2024)

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Abstract
Background Smoking is one of the major risk factors for shortened lifespan and disability, while smoking cessation is currently the only guaranteed method to reduce the harm caused by smoking. E -health is a field that utilizes information and communication technology to support the health status of its users. The emergence of this digital health approach has provided a new way of smoking cessation support for smokers seeking help, and an increasing number of researchers are attempting to use e -health for a wide range of effective smoking cessation interventions. We conducted a systematic review and meta -analysis of studies that used e -health as a smoking cessation support tool. Methods This systematic review and meta -analysis searched the PubMed, Embase, and Cochrane Library databases until December 2022. The included studies were randomized controlled trials (RCTs) comparing the use of e -health interventions and traditional offline smoking cessation care interventions. The primary outcome of the studies was the point smoking cessation rate (7 -day and 30 -day), and the secondary outcome was sustained smoking cessation rates. Studies were excluded if there was no clear e -health intervention described or if standard -compliant cessation outcomes were not clearly reported. Fixed -effects meta -analysis and meta -regression analyses were performed on the included study data to evaluate the effectiveness of the interventions. The meta -analysis outcome was the risk ratio (RR) and a 95% confidence interval. The study was registered with PROSPERO, CRD42023388667. Findings We collectively screened 2408 articles, and ultimately included 39 articles with a total of 17,351 eligible participants, of which 44 studies were included in the meta -analysis. The meta -analysis revealed that compared to traditional smoking cessation interventions, e -health interventions can increase point quit rates (RR 1.86, 95% CI 1.69-2.04) as well as sustained quit rates in the long-term (RR 1.79, 95% CI 1.60-2.00) among smokers. Subgroup analysis showed that text and telephone interventions in e -health significantly improved short-term quit rates for up to 7 days (RR 2.10, 95% CI 1.77-2.48). Website and app interventions also had a positive impact on improving short-term quit rates for up to 7 days (RR 1.74, 95% CI 1.56-1.94). The heterogeneity of the study results was low, demonstrating the significant smoking cessation advantages of e -health interventions. Interpretation We have found that personalized e -health interventions can effectively help smokers quit smoking. The diverse remote intervention methods of e -health can provide more convenient options for further customization. Additionally, further follow-up research is needed to evaluate the sustained effectiveness of interventions on smokers' continuous abstinence over a longer period (greater than one year). In the future, e -health can further optimize smoking cessation strategies. Copyright (c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY -NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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Key words
eHealth,Smoking cessation,Meta-analysis,Intervention
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