Kimber, C;
Frings, D;
Cox, S;
Sideropoulos, V;
Naughton, F;
Brown, J;
McRobbie, H;
(2020)
Tailored interventions to assist smokers to stop smoking using e-cigarettes (TASSE): Study protocol [version 3].
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, Article 9RDLJA.3. 10.32388/9rdlja.3.
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Abstract
Background: T here is increasing evidence that e-cigarettes (EC) are an effective smoking cessation aid when combined with behavioural support. T here is further evidence for digital tailored interventions as cost effective approaches that can increase smoking cessation rates. Experimental work also suggests the addition of a ‘nicotine fact sheet’ can improve smokers’ risk perceptions related to EC. However, multifaceted approaches to deliver ‘tailored advice’ for smoking cessation combining various key evidenced based components are lacking. T he aim of this study is to use a Multiphase Optimisation Strategy (MOST ) to determine which of five, or a combination thereof, EC-orientated intervention components is associated with self-reported cessation over the previous 4-weeks at 12-week follow-up. Methods/Design: T his online study will utilise a 2x2x2x2x2 factorial design resulting in 32 experimental conditions. T he five intervention components will be: 1: tailored advice on EC device; 2: tailored advice on e-liquid nicotine strength; 3: tailored advice on eliquid flavour; 4: e-cigarette written information; 5: text message support. A sample of N=1184 adult, UK resident smokers will be randomly allocated to one of the 32 conditions, which will be permutations of the 5 components (counter-balanced). T he primary outcome is 4 weeks of self-reported complete abstinence at 12 weeks post randomisation. Secondary outcomes are 7-day point prevalence, 50% reduction in baseline cigarettes smoked per day, time to switch and adherence to recommendation. T he primary analysis will be by intent-to-treat with the assumption that missing equals smoking. Logistic regression will be used to model the five main effects and the ten 2x2 interactions. A number of secondary analyses will also be conducted including models adjusting for demographic and smoking indices and including only those who received the intervention. Discussion: T o date, components that assist quitting by use of EC or other aids have largely been studied in isolation. T his study presents the first attempt to combine evidenced based interventions, using the MOST method, to test which components are associated with quitting. T he findings will be used to inform which components to include and their estimated effect sizes for a definitive randomised controlled trial (RCT ) to examine the efficacy of the intervention compared with usual care (own choice and no support).
Type: | Article |
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Title: | Tailored interventions to assist smokers to stop smoking using e-cigarettes (TASSE): Study protocol [version 3] |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.32388/9rdlja.3 |
Publisher version: | https://doi.org/10.32388/9rdlja.3 |
Language: | English |
Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Digital interventions; Tailored Advice; Smoking cessation; Smoking reduction; E-cigarettes; Multi-phase Optimisation Strategy (MOST ); Tobacco; Nicotine; Vaping |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Behavioural Science and Health |
URI: | https://discovery.ucl.ac.uk/id/eprint/10101088 |
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