@Article{信息:doi 10.2196 / / jmir。1179，作者="Wanner, Miriam和Martin- diener, Eva和Braun-Fahrl{\"a}nder, Charlotte和Bauer, Georg和Martin, Brian W"，标题="主动在线的有效性，一个个性化的体育活动干预，在现实生活中的设置:随机控制试验"，期刊="J医学互联网研究"，年="2009"，月=" 7月"，日="28"，卷="11"，数="3"，页="e23"，关键词="有效性;定制的干预;成年人;互联网;背景:需要有效的干预措施来减少慢性疾病的流行。互联网有潜力以相对较低的成本为大量人群提供个人建议。目的:研究的重点是基于网络的针对性体育活动干预。主要研究问题是(1)与非量身定制的网站相比，在线活动在现实生活环境中提高一般人群自我报告和客观测量的身体活动水平方面的效果如何?(2)随机研究招募的受访者与主动在线的自发用户是否存在差异，这两组之间的有效性有何差异? (3) What is the impact of frequency and duration of use of Active-online on changes in physical activity behavior? Methods: Volunteers recruited via different media channels completed a Web-based baseline survey and were randomized to Active-online (intervention group) or a nontailored website (control group). In addition, spontaneous users were recruited directly from the Active-online website. In a subgroup of participants, physical activity was measured objectively using accelerometers. Follow-up assessments took place 6 weeks (FU1), 6 months (FU2), and 13 months (FU3) after baseline. Results: A total of 1531 respondents completed the baseline questionnaire (intervention group n = 681, control group n = 688, spontaneous users n = 162); 133 individuals had valid accelerometer data at baseline. Mean age of the total sample was 43.7 years, and 1146 (74.9{\%}) were women. Mixed linear models (adjusted for sex, age, BMI category, and stage of change) showed a significant increase in self-reported mean minutes spent in moderate- and vigorous-intensity activity from baseline to FU1 (coefficient = 0.14, P = .001) and to FU3 (coefficient = 0.19, P < .001) in all participants with no significant differences between groups. A significant increase in the proportion of individuals meeting the HEPA recommendations (self-reported) was observed in all participants between baseline and FU3 (OR = 1.47, P = .03), with a higher increase in spontaneous users compared to the randomized groups (interaction between FU3 and spontaneous users, OR = 2.95, P = .02). There were no increases in physical activity over time in any group for objectively measured physical activity. A significant relation was found between time spent on the tailored intervention and changes in self-reported physical activity between baseline and FU3 (coefficient = 1.13, P = .03, intervention group and spontaneous users combined). However, this association was no longer significant when adjusting for stage of change. Conclusions: In a real-life setting, Active-online was not more effective than a nontailored website in increasing physical activity levels in volunteers from the general population. Further research may investigate ways of integrating Web-based physical activity interventions in a wider context, for example, primary care or workplace health promotion. ", issn="1438-8871", doi="10.2196/jmir.1179", url="//www.mybigtv.com/2009/3/e23/", url="https://doi.org/10.2196/jmir.1179", url="http://www.ncbi.nlm.nih.gov/pubmed/19666456" }