London South Bank University, London, UK.
IOE, UCL's Faculty of Education and Society, University College London, London, UK.
Addiction. 2023 Nov;118(11):2105-2117. doi: 10.1111/add.16294. Epub 2023 Jul 16.
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.
A total of 1214 eligible participants (61% female; 97% white) were recruited via social media.
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.
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.
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.
Text-message support with tailored advice on flavour is a promising intervention combination for smokers using an e-cigarette in a quit attempt.
目的、设计和设置：本研究旨在确定在线提供的五种电子烟导向干预成分的组合（s），哪种组合对戒烟最有效。采用在线（英国）平衡五因素（2×2×2×2×2=32 种干预组合）随机因子设计，由多阶段优化策略（MOST）指导。
共有 1214 名符合条件的参与者（61%为女性；97%为白人）通过社交媒体招募。
设计了五种在线干预成分，旨在帮助吸烟者转为仅使用电子烟：（1）量身定制的设备选择建议；（2）量身定制的电子烟液尼古丁强度建议；（3）：量身定制的电子烟液口味建议；（4）相对危害的简要信息；（5）短信（SMS）支持。
主要结果是在随机分组后 12 周的 4 周内自我报告的完全戒断。主要分析采用意向治疗（随访丢失记录为吸烟）。逻辑回归模型分别对三向和双向交互作用以及主效应进行了建模。
在调整后的模型中，唯一显著的交互作用是双向交互作用，即口味建议与短信支持相结合，增加了戒烟的可能性（优势比=1.55，95%置信区间=1.13-2.14，P=0.007，贝叶斯因子=7.25）。干预成分没有主要影响。
对于使用电子烟尝试戒烟的吸烟者，短信支持与口味建议相结合是一种很有前途的干预组合。
