@Article{信息:doi 10.2196 / / jmir。7277，作者="Van der Mispel, Celien和Poppe, Louise和Crombez, Geert和Verloigne, Ma{\"i}t{\'e} and De Bourdeaudhuij, Ilse"，标题="基于自我调节的电子健康干预促进健康生活方式:调查与消耗相关的用户和网站特征"，期刊="J Med Internet Res"，年="2017"，月="7月"，日="11"，卷="19"，数="7"，页数="e241"，关键词="体育活动;健康的饮食;电子健康;磨损;背景:电子健康干预可以覆盖大量人群，并有效地增加身体活动(PA)和水果和蔬菜摄入量。然而，电子卫生干预措施的效果被高流失率所掩盖。当用户决定离开干预措施时，更仔细地检查可以帮助eHealth开发人员做出明智的决定，确定哪些干预措施组件应该重新定义或简单地删除。调查哪些用户更有可能退出干预，可以让开发人员了解他们的干预是否以及如何适应特定的用户子群体。目的:本研究调查了基于网络的干预以增加PA、水果和蔬菜摄入量的消耗模式。 The first aim was to describe attrition rates according to different self-regulation components. A second aim was to investigate whether certain user characteristics are predictors for start session completion, returning to a follow-up session and intervention completion. Methods: The sample consisted of 549 adults who participated in an online intervention, based on self-regulation theory, to promote PA and fruit and vegetable intake, called ``MyPlan 1.0.'' Using descriptive analysis, attrition was explored per self-regulation component (eg, action planning and coping planning). To identify which user characteristics predict completion, logistic regression analyses were conducted. Results: At the end of the intervention program, there was an attrition rate of 78.2{\%} (330/422). Attrition rates were very similar for the different self-regulation components. However, attrition levels were higher for the fulfillment of questionnaires (eg, to generate tailored feedback) than for the more interactive components. The highest amount of attrition could be observed when people were asked to make their own action plan. There were no significant predictors for first session completion. Yet, two subgroups had a lower chance to complete the intervention, namely male users (OR: 2.24, 95{\%} CI=1.23-4.08) and younger adults (OR: 1.02, 95{\%} CI=1.00-1.04). Furthermore, younger adults were less likely to return to the website for the first follow-up after one week (OR: 1.03, 95{\%} CI=1.01-1.04). Conclusions: This study informs us that eHealth interventions should avoid the use of extensive questionnaires and that users should be provided with a rationale for several components (eg, making an action plan and completing questions). Furthermore, future interventions should focus first on motivating users for the behavior change before guiding them through action planning. Though, this study provides no evidence for removal of one of the self-regulation techniques based on attrition rates. Finally, strong efforts are needed to motivate male users and younger adults to complete eHealth interventions. ", issn="1438-8871", doi="10.2196/jmir.7277", url="//www.mybigtv.com/2017/7/e241/", url="https://doi.org/10.2196/jmir.7277", url="http://www.ncbi.nlm.nih.gov/pubmed/28698168" }