杂志文章%@ 1438-8871 %I JMIR出版物%V 22 %N卡塔尔世界杯8强波胆分析 11 %P e20251 %T吸引没有动机的吸烟者走向戒烟:基于迭代交互的激励性面试聊天机器人设计%A Almusharraf,Fahad %A Rose,Jonathan %A Selby,Peter %+ Edward S. Rogers Sr.多伦多大学应用科学与工程学院电气与计算机工程系，多伦多，ON, M5S 3G4，加拿大，1 4169786992，jonathan.rose@ece.utoronto.ca %K戒烟%K动机访谈%K聊天机器人%K自然语言处理%D 2020 %7 3.11.2020 %9原创论文%J J医学互联网Res %G英语%X背景:在任何给定的时间，人群中的大多数吸烟者都是矛盾的，没有戒烟的动机。动机性访谈(MI)是一种基于证据的技术，旨在诱导矛盾吸烟者做出改变。MI从业人员既稀缺又昂贵，而且很难接触到吸烟者。吸烟者可以通过网络联系到，如果一个自动聊天机器人可以模仿MI对话，它可以形成一个低成本和可扩展的干预的基础，激励吸烟者戒烟。目的:本研究的主要目标是设计、训练和测试一个基于mis的自动聊天机器人，能够在与吸烟者的对话中引发反思。本研究描述了收集训练数据的过程，以提高聊天机器人生成面向信息管理的响应的能力，特别是反思和总结语句。本研究的第二个目标是通过与聊天机器人完成对话后的自愿反馈来观察对参与者的影响。方法:MI专家和计算机工程和自然语言处理(NLP)专家之间的跨学科合作共同设计了聊天机器人的对话和算法。 A sample of 121 adult cigarette smokers in 11 successive groups were recruited from a web-based platform for a single-arm prospective iterative design study. The chatbot was designed to stimulate reflections on the pros and cons of smoking using MI’s running head start technique. Participants were also asked to confirm the chatbot’s classification of their free-form responses to measure the classification accuracy of the underlying NLP models. Each group provided responses that were used to train the chatbot for the next group. Results: A total of 6568 responses from 121 participants in 11 successive groups over 14 weeks were received. From these responses, we were able to isolate 21 unique reasons for and against smoking and the relative frequency of each. The gradual collection of responses as inputs and smoking reasons as labels over the 11 iterations improved the F1 score of the classification within the chatbot from 0.63 in the first group to 0.82 in the final group. The mean time spent by each participant interacting with the chatbot was 21.3 (SD 14.0) min (minimum 6.4 and maximum 89.2). We also found that 34.7% (42/121) of participants enjoyed the interaction with the chatbot, and 8.3% (10/121) of participants noted explicit smoking cessation benefits from the conversation in voluntary feedback that did not solicit this explicitly. Conclusions: Recruiting ambivalent smokers through the web is a viable method to train a chatbot to increase accuracy in reflection and summary statements, the building blocks of MI. A new set of 21 smoking reasons (both for and against) has been identified. Initial feedback from smokers on the experience shows promise toward using it in an intervention. %M 33141095 %R 10.2196/20251 %U //www.mybigtv.com/2020/11/e20251 %U https://doi.org/10.2196/20251 %U http://www.ncbi.nlm.nih.gov/pubmed/33141095