INTRODUCTION Chatbots emulate human-like interactions and may usefully provide on-demand access to tailored smoking cessation support. We have developed a prototype smartphone application-based smoking cessation chatbot, named Quin, grounded in real-world, evidence-, and theory-based smoking cessation counseling sessions. METHODS Conversation topics and interactions in Quitline counseling sessions (N = 30; 18 h) were characterized using thematic, content, and proponent analyses of transcripts. Quin was created by programming this content using a chatbot framework which interacts with users via speech to text. Reiterative changes and additions were made to the conversation structure and dialogue following regular consultation with a multidisciplinary team from relevant fields, and from evidence-based resources. RESULTS Chatbot conversations were encoded into initial and scheduled follow-up "appointments." Collection of demographic information, and smoking and quit history, informed tailored discussion about pharmacotherapy preferences, behavioral strategies, and social and professional support to form a quit plan. Follow-up appointments were programmed to check in on user progress, review elements of the quit plan, answer questions, and solve issues. Quin was programmed to include teachable moments and educational content to enhance health literacy and informed decision-making. Personal agency is encouraged through exploration and self-reflection of users' personal behaviors, experiences, preferences, and ideas. CONCLUSIONS Quin's successful development represents a movement toward improving access to personalized smoking cessation support. Qualitative foundations of Quin provide greater insight into the smoking cessation counseling relationship and enhances the conversational ability of the technology. The prototype chatbot will be refined through beta-testing with end users and stakeholders prior to evaluation in a clinical trial. IMPLICATIONS Our novel study provides transparent description of the translation of qualitative evidence of real-world smoking cessation counseling sessions into the design and development of a prototype smoking cessation chatbot. The successful iterative development of Quin not only embodies the science and art of health promotion, but also a step forward in expanding the reach of tailored, evidence based, in-pocket support for people who want to quit smoking.

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Quin 简介：支持戒烟的原型聊天机器人的设计和开发。


简介 聊天机器人模拟类人交互，可以有效地按需提供定制的戒烟支持。我们开发了一款基于智能手机应用程序的戒烟聊天机器人原型，名为 Quin，基于现实世界、基于证据和理论的戒烟咨询课程。方法 通过对记录的主题、内容和支持者分析来表征戒烟热线咨询会议（N = 30；18 小时）中的对话主题和互动。 Quin 是通过使用聊天机器人框架对这些内容进行编程而创建的，该框架通过语音到文本与用户进行交互。在与来自相关领域的多学科团队和基于证据的资源定期协商后，对对话结构和对话进行了反复的修改和补充。结果 聊天机器人对话被编码到初始和预定的后续“约会”中。收集人口统计信息、吸烟和戒烟史，对药物治疗偏好、行为策略以及社会和专业支持进行有针对性的讨论，以形成戒烟计划。后续预约旨在检查用户进度、审查戒烟计划的要素、回答问题并解决问题。奎因的计划包括教学时刻和教育内容，以提高健康素养和明智的决策。通过探索和自我反思用户的个人行为、经历、偏好和想法来鼓励个人代理。结论 Quin 的成功开发代表着一场改善个性化戒烟支持机会的运动。 Quin 的定性基础提供了对戒烟咨询关系的更深入的了解，并增强了技术的对话能力。在临床试验评估之前，原型聊天机器人将通过最终用户和利益相关者进行 Beta 测试来完善。意义我们的新颖研究提供了将现实世界戒烟咨询课程的定性证据转化为原型戒烟聊天机器人的设计和开发的透明描述。 Quin 的成功迭代开发不仅体现了健康促进的科学和艺术，而且在扩大为想要戒烟的人提供定制的、基于证据的、现金支持的范围方面向前迈出了一步。