JMIR Publications

ABSTRACT

Background:

With the rapid development of electronic health (eHealth) and mobile health (mHealth) technologies, researchers have created and tested a variety of technology-assisted smoking cessation interventions. Given the ever-changing landscape of cessation interventions, there is a strong need for regular knowledge syntheses.

Objective:

This systematic review aims to (1) summarize recent evidence on the effectiveness of randomized controlled trials (RCTs) regarding eHealth-based smoking cessation on abstinence; and (2) assess important secondary outcome indicators such as cigarette consumption, quit attempts, and user satisfaction via narrative synthesis.

Methods:

We searched for studies published in English between 2017 to June 30, 2022 in four databases: PubMed (including MEDLINE), PsycINFO, Embase, and Cochrane Library. Two independent reviewers performed study screening, data extraction, and quality assessment based on the GRADE framework. We pooled studies based on population, follow-up time, intervention, and control characteristics and two researchers performed independent meta-analysis on smoking abstinence using the Mantel-Haenszel fixed effect model and log Risk Ratio (logRR) as effect measurement. For studies not included in the meta-analysis, we synthesized the outcomes narratively.

Results:

We identified a total of 464 studies through the initial database search after removing duplicates. After screening and full-text assessments, 39 studies covering 37,341 participants were deemed eligible for this review, and 28 of these studies were included in meta-analysis. According to the meta-analysis, SMS/App text messaging can significantly increase both 3-month (short-term) abstinence (log RR=-0.50, 95% CI 0.25–0.75, I2=0.00%) and 6-month (long-term) abstinence (log RR=0.79, 95% CI 0.52–1.05, I2=0.00%) when compared to minimal cessation support. The frequency of texting makes no difference on treatment outcome. mHealth apps may significantly increase abstinence in short term (logRR=0.73, 95% CI 0.54–0.93, I2=60.73%) but not in long term (logRR=0.00, 95% CI -0.11–0.11, I2=66.95%) when compared to less intensive cessation support. Psycho/pharmacological therapy yielded similar abstinence results with or without the accompany of mHealth apps (logRR=0.26, 95% CI -0.11–0.63, I2=0.00%). Finally, trials using biochemical verification for abstinence found a moderate increase in cessation in both short-term (logRR=0.46, 95% CI 0.23–0.70, I2=1.39%) and long-term (logRR=0.28, 95% CI 0.06–0.50, I2=13.72%) whereas studies only used self-reported outcomes found no such significant impact. Among studies reporting outcomes besides abstinence (n=28), a total of 12 studies reported significantly improved secondary outcomes in cigarette consumption (3/14, 21.43%), quit attempts (1/11, 9.09%), and user satisfaction (8/19, 42.11%).

Conclusions:

Based on 39 RCTs, we found current eHealth interventions, with mHealth being the dominant approach, could be effective in smoking cessation though the effectiveness may diminish over time. Future studies could potentially benefit from more personalized intervention designs to improve user adherence, thus achieving better long-term abstinence outcomes. Clinical Trial: PROSPERO International Prospective Register of Systematic Reviews CRD42022347104; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=347104