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Publication Detail
Behaviour Change Techniques Associated with Smoking Cessation in Intervention and Comparator Groups of Randomised Controlled Trials: A Systematic Review and Meta-Regression
Abstract
AIMS: To estimate the strengths of associations between use of behaviour change techniques (BCTs) and clusters of BCTs in behavioural smoking cessation interventions and comparators with smoking cessation rates. METHOD: Systematic review and meta-regression of biochemically verified smoking cessation rates on BCTs in interventions and comparators in randomised controlled trials, adjusting for a priori defined potential confounding variables, together with moderation analyses. Studies were drawn from the Cochrane Tobacco Addiction Group Specialised Register. Data were extracted from published and unpublished (i.e., obtained from study authors) study materials by two independent coders. Adequately described intervention (k = 143) and comparator (k = 92) groups were included in the analyses (N = 43992 participants). Using bivariate mixed-effects meta-regressions, while controlling for key a priori confounders, we regressed smoking cessation on a) three BCT groupings consistent with dual-process theory (i.e., associative, reflective motivational, and self-regulatory), b) 17 expert-derived BCT groupings (i.e., BCT taxonomy v1 clusters), and c) individual BCTs from the BCT taxonomy v1. RESULTS: Amongst person-delivered interventions, higher smoking cessation rates were predicted by BCTs targeting associative and self-regulatory processes (B = 0.034-0.041, p < .05), and by three individual BCTs (prompting commitment, social reward, identity associated with changed behaviour), Amongst written interventions, BCTs targeting taxonomy cluster 10a (rewards) predicted higher smoking cessation (B = 0.394, p < .05). Moderation effects were observed for nicotine dependence, mental health status, and mode of delivery. CONCLUSIONS: Amongst person-delivered behavioural smoking cessation interventions, specific behaviour change techniques and clusters of techniques are associated with higher success rates.
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