Abstract
BackgroundThe increasing number of internet users presents an opportunity to deliver health interventions to large populations. Despite their potential, many web-based interventions, including those for smoking cessation, face high rates of attrition. Further consideration of how intervention features impact attrition is needed.ObjectiveThe aim of this systematic review is to investigate whether tailored web-based smoking cessation interventions for smokers are associated with reduced rates of attrition compared with active or passive untailored web-based interventions. The outcomes of interest were dropout attrition at 1-, 3-, 6-, and 12-month follow-ups.MethodsLiterature searches were conducted in May 2018 and updated in May 2020 on MEDLINE (Medical Literature Analysis and Retrieval System Online), PsycINFO (Psychological Information), EMBASE (Excerpta Medica dataBASE), CINAHL (Cumulated Index to Nursing and Allied Health Literature), Scopus, and the Cochrane Tobacco Addiction Group Specialized Register with the following search terms: smoking cessation, tailored, or web- or internet-based. Included studies were published in English before or in May 2020 using a randomized controlled trial design. Studies were restricted to those with web-based delivery, a tailored intervention group, an untailored control group, and a reported outcome of smoking cessation. Studies were assessed for methodological quality using the Cochrane Risk of Bias tool. Two reviewers independently extracted the study characteristics and the number of participants lost to follow-up for each treatment group.ResultsA total of 13 studies were included in the systematic review, of which 11 (85%) were included in the meta-analysis. Tailoring had no statistically significant effect on dropout attrition at 1-month (risk ratio [RR]=1.02, 95% CI 0.95-1.09; P=.58; I2=78%), 3-month (RR=0.99, 95% CI 0.95-1.04; P=.80; I2=73%), 6-month (RR=1.00, 95% CI 0.95-1.05; P=.90; I2=43%), or 12-month (RR=0.97, 95% CI 0.92-1.02; P=.26; I2=28%) follow-ups. Subgroup analyses suggested that there was a statistically significant effect of tailoring between the active and passive subgroups at 1-month (P=.03), 3-month (P<.001), and 6-month (P=.02) follow-ups but not at 12-month follow-up (P=.25).ConclusionsThe results suggest that tailoring of web-based smoking cessation interventions may not be associated with reduced rates of dropout attrition at 1-, 3-, 6-, or 12-month follow-ups. Significant differences between studies that include untailored active and passive control groups suggest that the role of tailoring may be more prominent when studies include a passive control group. These findings may be because of variability in the presence of additional features, the definition of smokers used, and the duration of smoking abstinence measured. Future studies should incorporate active web-based controls, compare the impact of different tailoring strategies, and include populations outside of the Western countries.
Highlights
IntroductionSmoking is the leading cause of preventable death [1]
BackgroundSmoking is the leading cause of preventable death [1]
A total of 13 studies were included in the systematic review, of which 11 (85%) were included in the meta-analysis
Summary
Smoking is the leading cause of preventable death [1]. Over 7 million deaths worldwide are attributed to cigarette smoking [2], leading to a global loss of 150 million disability-adjusted life years [3]. The majority of smokers want to quit [4]; it can take 30 or more attempts to successfully quit [5]. Smoking cessation is difficult, the price of not quitting is high—over 50% of long-term smokers die from smoking [6,7]. Evidence-based smoking cessation interventions can double or triple the chances that a quit attempt will result in long-term cessation [8]. The increasing number of internet users presents an opportunity to deliver health interventions to large populations. Despite their potential, many web-based interventions, including those for smoking cessation, face high rates of attrition. Further consideration of how intervention features impact attrition is needed
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