Nicola Black1,2, Marie Johnston1, Susan Michie3, Jamie Hartmann-Boyce4, Robert West5, Wolfgang Viechtbauer6, Maarten C Eisma1,7, Claire Scott1,8, Marijn de Bruin1,9. 1. Health Psychology Group, Institute of Applied Health Sciences, University of Aberdeen, Health Sciences Building, Aberdeen, UK. 2. National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia. 3. Centre for Behaviour Change, University College London, London, UK. 4. Nuffield Department of Primary Care Health Sciences, Radcliffe Observatory Quarter, Oxford and United Kingdom and National Institute of Health Research, Oxford Biomedical Research Centre, University of Oxford, Unipart House Business Centre, Oxford, UK. 5. Department of Behavioural Science and Health, University College London, London, UK. 6. Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands. 7. Department of Clinical Psychology and Experimental Psychopathology, University of Groningen, Groningen, the Netherlands. 8. Scottish Dental Clinical Effectiveness Programme, NHS Education for Scotland, Dundee Dental Education Centre, Dundee, UK. 9. Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, the Netherlands.
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 randomized 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 Data were extracted from published and unpublished (i.e. obtained from study authors) study materials by two independent coders.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 = 43 992 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 version 1 clusters) and (c) individual BCTs from the BCT taxonomy version 1. RESULTS: Among person-delivered interventions, higher smoking cessation rates were predicted by BCTs targeting associative and self-regulatory processes (B = 0.034, 0.041, P < 0.05), and by three individual BCTs (prompting commitment, social reward, identity associated with changed behaviour). Among written interventions, BCTs targeting taxonomy cluster 10a (rewards) predicted higher smoking cessation (B = 0.394, P < 0.05). Moderation effects were observed for nicotine dependence, mental health status and mode of delivery. CONCLUSIONS: Among person-delivered behavioural smoking cessation interventions, specific behaviour change techniques and clusters of techniques are associated with higher success rates.
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 randomized 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 = 43 992 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 version 1 clusters) and (c) individual BCTs from the BCT taxonomy version 1. RESULTS: Among person-delivered interventions, higher smoking cessation rates were predicted by BCTs targeting associative and self-regulatory processes (B = 0.034, 0.041, P < 0.05), and by three individual BCTs (prompting commitment, social reward, identity associated with changed behaviour). Among written interventions, BCTs targeting taxonomy cluster 10a (rewards) predicted higher smoking cessation (B = 0.394, P < 0.05). Moderation effects were observed for nicotine dependence, mental health status and mode of delivery. CONCLUSIONS: Among person-delivered behavioural smoking cessation interventions, specific behaviour change techniques and clusters of techniques are associated with higher success rates.
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