@Article{信息:doi 10.2196 / / jmir。1812年，作者=“Smit, Eline Suzanne和de Vries, Hein和Hoving, Ciska”，标题=“基于web的多种定制戒烟计划的有效性:荷兰成年吸烟者的随机对照试验”，期刊=“J Med Internet Res”，年=“2012”，月=“6”，日=“11”，卷=“14”，数=“3”，页=“e82”，关键词=“戒烟;基于web的干预;电脑裁剪;迭代反馈;干预;背景:通过互联网分发多种电脑定制的戒烟干预对提供者和接受者都有几个好处。最重要的是，在保持高度个性化和个性化的反馈形式的同时，可以接触到大量吸烟者。然而，这样的戒烟计划还没有在荷兰发展和实施。目的:研究基于网络的多种计算机定制戒烟程序对荷兰成年吸烟者戒烟结果的影响。 Methods: Smokers were recruited from December 2009 to June 2010 by advertising our study in the mass media and on the Internet. Those interested and motivated to quit smoking within 6 months (N = 1123) were randomly assigned to either the experimental (n = 552) or control group (n = 571). Respondents in the experimental group received the fully automated Web-based smoking cessation program, while respondents in the control group received no intervention. After 6 weeks and after 6 months, we assessed the effect of the intervention on self-reported 24-hour point prevalence abstinence, 7-day point prevalence abstinence, and prolonged abstinence using logistic regression analyses. Results: Of the 1123 respondents, 449 (40.0{\%}) completed the 6-week follow-up questionnaire and 291 (25.9{\%}) completed the 6-month follow-up questionnaire. We used a negative scenario to replace missing values. That is, we considered respondents lost to follow-up to still be smoking. The computer-tailored program appeared to have significantly increased 24-hour point prevalence abstinence (odds ratio [OR] 1.85, 95{\%} confidence interval [CI] 1.30--2.65), 7-day point prevalence abstinence (OR 2.17, 95{\%} CI 1.44--3.27), and prolonged abstinence (OR 1.99, 95{\%} CI 1.28--3.09) rates reported after 6 weeks. After 6 months, however, no intervention effects could be identified. Results from complete-case analyses were similar. Conclusions: The results presented suggest that the Web-based computer-tailored smoking cessation program had a significant effect on abstinence reported after a 6-week period. At the 6-month follow-up, however, no intervention effects could be identified. This might be explained by the replacement of missing values on the primary outcome measures due to attrition using a negative scenario. While results were similar when using a less conservative scenario (ie, complete-case analyses), the results should still be interpreted with caution. Further research should aim at identifying strategies that will prevent high attrition in the first place and, subsequently, to identify the best strategies for dealing with missing data when studies have high attrition rates. Trial Registration: Dutch Trial Register NTR1351; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1351 (Archived by WebCite at http://www.webcitation.org/67egSTWrz) ", issn="1438-8871", doi="10.2196/jmir.1812", url="//www.mybigtv.com/2012/3/e82/", url="https://doi.org/10.2196/jmir.1812", url="http://www.ncbi.nlm.nih.gov/pubmed/22687887" }