TY -的盟Almusharraf法赫德AU -玫瑰,乔纳森AU -塞尔比,彼得PY - 2020 DA - 2020/11/3 TI -参与动机不明的吸烟者戒烟走向:设计激励Interviewing-Based Chatbot通过迭代互动乔- J地中海互联网Res SP - e20251六世- 22 - 11 KW -戒烟KW -动机性访谈KW - Chatbot KW -自然语言处理AB -背景:在任何给定的时间,大多数吸烟者人口矛盾没有动力戒烟。动机访谈(MI)是一种基于证据的技术，旨在引起矛盾吸烟者的改变。MI从业者稀缺且价格昂贵，吸烟者很难接触到。吸烟者可以通过网络联系到，如果自动聊天机器人可以模仿MI对话，它就可以成为低成本和可扩展的干预措施的基础，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mi的自动聊天机器人，该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mi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专家与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。从网络平台上招募了11组121名成年吸烟者的样本，进行单臂前瞻性迭代设计研究。这个聊天机器人的设计是为了激发人们对吸烟利弊的思考，使用MI的领先技术。 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. SN - 1438-8871 UR - //www.mybigtv.com/2020/11/e20251 UR - https://doi.org/10.2196/20251 UR - http://www.ncbi.nlm.nih.gov/pubmed/33141095 DO - 10.2196/20251 ID - info:doi/10.2196/20251 ER -