E‐cigarette support for smoking cessation: Identifying the effectiveness of intervention components in an on‐line randomized optimization experiment

Catherine Kimber, Vassilis Sideropoulos, Sharon Cox, Daniel Frings, Felix Naughton, Jamie Brown, Hayden McRobbie, Lynne Dawkins

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
15 Downloads (Pure)

Abstract

Aims, design and setting: The aim of this study was to determine which combination(s) of five e-cigarette-orientated intervention components, delivered on-line, affect smoking cessation. An on-line (UK) balanced five-factor (2 × 2 × 2 × 2 × 2 = 32 intervention combinations) randomized factorial design guided by the multi-phase optimization strategy (MOST) was used.

Participants: A total of 1214 eligible participants (61% female; 97% white) were recruited via social media.

Interventions: The five on-line intervention components designed to help smokers switch to exclusive e-cigarette use were: (1) tailored device selection advice; (2) tailored e-liquid nicotine strength advice; (3): tailored e-liquid flavour advice; (4) brief information on relative harms; and (5) text message (SMS) support.

Measurements: The primary outcome was 4-week self-reported complete abstinence at 12 weeks post-randomization. Primary analyses were intention-to-treat (loss to follow-up recorded as smoking). Logistic regressions modelled the three- and two-way interactions and main effects, explored in that order.

Findings: In the adjusted model the only significant interaction was a two-way interaction, advice on flavour combined with text message support, which increased the odds of abstinence (odds ratio = 1.55, 95% confidence interval = 1.13-2.14, P = 0.007, Bayes factor = 7.25). There were no main effects of the intervention components.

Conclusions: Text-message support with tailored advice on flavour is a promising intervention combination for smokers using an e-cigarette in a quit attempt.
Original languageEnglish
Pages (from-to)2105-2117
Number of pages13
JournalAddiction
Volume118
Issue number11
Early online date16 Jul 2023
DOIs
Publication statusPublished - Nov 2023

Cite this