Strecher Victor J, McClure Jennifer B, Alexander Gwen L, Chakraborty Bibhas, Nair Vijay N, Konkel Janine M, Greene Sarah M, Collins Linda M, Carlier Carola C, Wiese Cheryl J, Little Roderick J, Pomerleau Cynthia S, Pomerleau Ovide F
Center for Health Communications Research, University of Michigan School of Public Health, Ann Arbor, MI 48109-0471, USA.
Am J Prev Med. 2008 May;34(5):373-81. doi: 10.1016/j.amepre.2007.12.024.
Initial trials of web-based smoking-cessation programs have generally been promising. The active components of these programs, however, are not well understood. This study aimed to (1) identify active psychosocial and communication components of a web-based smoking-cessation intervention and (2) examine the impact of increasing the tailoring depth on smoking cessation.
Randomized fractional factorial design.
Two HMOs: Group Health in Washington State and Henry Ford Health System in Michigan.
1866 smokers.
A web-based smoking-cessation program plus nicotine patch. Five components of the intervention were randomized using a fractional factorial design: high- versus low-depth tailored success story, outcome expectation, and efficacy expectation messages; high- versus low-personalized source; and multiple versus single exposure to the intervention components.
Primary outcome was 7 day point-prevalence abstinence at the 6-month follow-up.
Abstinence was most influenced by high-depth tailored success stories and a high-personalized message source. The cumulative assignment of the three tailoring depth factors also resulted in increasing the rates of 6-month cessation, demonstrating an effect of tailoring depth.
The study identified relevant components of smoking-cessation interventions that should be generalizable to other cessation interventions. The study also demonstrated the importance of higher-depth tailoring in smoking-cessation programs. Finally, the use of a novel fractional factorial design allowed efficient examination of the study aims. The rapidly changing interfaces, software, and capabilities of eHealth are likely to require such dynamic experimental approaches to intervention discovery.
基于网络的戒烟项目的初步试验总体上前景良好。然而,这些项目的有效组成部分尚未得到充分理解。本研究旨在:(1)确定基于网络的戒烟干预措施中有效的心理社会和沟通组成部分;(2)研究增加个性化程度对戒烟的影响。
随机分数析因设计。
两家健康维护组织(HMO):华盛顿州的Group Health和密歇根州的亨利·福特健康系统。
1866名吸烟者。
基于网络的戒烟项目加尼古丁贴片。采用分数析因设计对干预措施的五个组成部分进行随机分组:高深度与低深度定制的成功故事、结果期望和效能期望信息;高个性化与低个性化来源;以及对干预组成部分的多次与单次接触。
主要结局是6个月随访时7天的点患病率戒烟率。
戒烟受高深度定制的成功故事和高个性化信息来源的影响最大。三个个性化程度因素的累积赋值也导致6个月戒烟率增加,表明个性化程度有影响。
该研究确定了戒烟干预措施的相关组成部分,这些组成部分应可推广到其他戒烟干预措施中。该研究还证明了在戒烟项目中更高深度个性化的重要性。最后,使用新颖的分数析因设计能够有效地检验研究目标。电子健康快速变化的界面、软件和功能可能需要这种动态实验方法来发现干预措施。