• Patient Prefer Adher · Jan 2018

    Review

    Which eHealth interventions are most effective for smoking cessation? A systematic review.

    • DoHuyen PhucHPSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia, phuchuyen@gmail.com.Institute for Global Health Innovations, Duy Tan University, Danang, Vietnam, phuchuyen@gmail.com., Bach Xuan Tran, Quyen Le Pham, Long Hoang Nguyen, TranTung ThanhTTInstitute for Global Health Innovations, Duy Tan University, Danang, Vietnam, phuchuyen@gmail.com., Carl A Latkin, Michael P Dunne, and Philip Ra Baker.
    • School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia, phuchuyen@gmail.com.
    • Patient Prefer Adher. 2018 Jan 1; 12: 206520842065-2084.

    PurposeTo synthesize evidence of the effects and potential effect modifiers of different electronic health (eHealth) interventions to help people quit smoking.MethodsFour databases (MEDLINE, PsycINFO, Embase, and The Cochrane Library) were searched in March 2017 using terms that included "smoking cessation", "eHealth/mHealth" and "electronic technology" to find relevant studies. Meta-analysis and meta-regression analyses were performed using Mantel-Haenszel test for fixed-effect risk ratio (RR) and restricted maximum-likelihood technique, respectively. Protocol Registration Number: CRD42017072560.ResultsThe review included 108 studies and 110,372 participants. Compared to nonactive control groups (eg, usual care), smoking cessation interventions using web-based and mobile health (mHealth) platform resulted in significantly greater smoking abstinence, RR 2.03 (95% CI 1.7-2.03), and RR 1.71 (95% CI 1.35-2.16), respectively. Similarly, smoking cessation trials using tailored text messages (RR 1.80, 95% CI 1.54-2.10) and web-based information and conjunctive nicotine replacement therapy (RR 1.29, 95% CI 1.17-1.43) may also increase cessation. In contrast, little or no benefit for smoking abstinence was found for computer-assisted interventions (RR 1.31, 95% CI 1.11-1.53). The magnitude of effect sizes from mHealth smoking cessation interventions was likely to be greater if the trial was conducted in the USA or Europe and when the intervention included individually tailored text messages. In contrast, high frequency of texts (daily) was less effective than weekly texts.ConclusionsThere was consistent evidence that web-based and mHealth smoking cessation interventions may increase abstinence moderately. Methodologic quality of trials and the intervention characteristics (tailored vs untailored) are critical effect modifiers among eHealth smoking cessation interventions, especially for web-based and text messaging trials. Future smoking cessation intervention should take advantages of web-based and mHealth engagement to improve prolonged abstinence.

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