@Article{信息:doi 10.2196 / / jmir。1893，作者=“肯尼迪，卡特里奥娜M和鲍威尔，约翰和佩恩，托马斯H和安斯沃思，约翰和博伊德，艾伦和巴肯，伊恩”，标题=“健康相关行为改变的主动辅助技术:跨学科综述”，期刊=“J医学互联网研究”，年=“2012”，月=“六月”，日=“14”，卷=“14”，数=“3”，页=“e80”，关键词=“行为改变;消费者健康信息学;健康的沟通;健康促进;背景:信息技术可以帮助个体改变健康行为。这是由于它在动态和无偏见的信息处理方面的潜力，使用户能够监测自己的进展，并了解特定于不断变化的环境和动机的风险和机会。然而，在许多行为改变干预措施中，由于将信息技术视为专注于有效传递信息和积极用户体验的被动媒介，信息技术未得到充分利用。目的:进行一项跨学科文献综述，以确定动态和自适应信息处理的主动技术能力在行为改变干预中的应用程度，并确定其在这些干预中的作用。方法:定义语义信息处理、模式识别和自适应等主动技术的关键类别。 We conducted the literature search using keywords derived from the categories and included studies that indicated a significant role for an active technology in health-related behavior change. In the data extraction, we looked specifically for the following technology roles: (1) dynamic adaptive tailoring of messages depending on context, (2) interactive education, (3) support for client self-monitoring of behavior change progress, and (4) novel ways in which interventions are grounded in behavior change theories using active technology. Results: The search returned 228 potentially relevant articles, of which 41 satisfied the inclusion criteria. We found that significant research was focused on dialog systems, embodied conversational agents, and activity recognition. The most covered health topic was physical activity. The majority of the studies were early-stage research. Only 6 were randomized controlled trials, of which 4 were positive for behavior change and 5 were positive for acceptability. Empathy and relational behavior were significant research themes in dialog systems for behavior change, with many pilot studies showing a preference for those features. We found few studies that focused on interactive education (3 studies) and self-monitoring (2 studies). Some recent research is emerging in dynamic tailoring (15 studies) and theoretically grounded ontologies for automated semantic processing (4 studies). Conclusions: The potential capabilities and risks of active assistance technologies are not being fully explored in most current behavior change research. Designers of health behavior interventions need to consider the relevant informatics methods and algorithms more fully. There is also a need to analyze the possibilities that can result from interaction between different technology components. This requires deep interdisciplinary collaboration, for example, between health psychology, computer science, health informatics, cognitive science, and educational methodology. ", issn="1438-8871", doi="10.2196/jmir.1893", url="//www.mybigtv.com/2012/3/e80/", url="https://doi.org/10.2196/jmir.1893", url="http://www.ncbi.nlm.nih.gov/pubmed/22698679" }