The impact of human feedback in a chatbot-based smoking cessation intervention: An empirical study into psychological, economic, and ethical factors - Data and analysis code for the PhD thesis chapter

This repository contains the data and analysis code for the chapter "The impact of human feedback in a chatbot-based smoking cessation intervention: An empirical study into psychological, economic, and ethical factors" from the PhD thesis by Nele Albers.<br><strong>Study</strong>The chapter is primarily based on data collected in a study conducted on the online crowdsourcing platform Prolific. In this study, daily smokers and vapers interacted with the text-based conversational agent Kai in up to five conversational sessions between 1 February and 19 March 2024. The Human Research Ethics Committee of Delft University of Technology granted ethical approval for the research (Letter of Approval number: 3683).<br>In each session, participants were assigned one of 37 preparatory activities for quitting smoking (e.g., envisioning their desired future self after quitting smoking/vaping, learning a breathing exercise, tracking their smoking behavior). Between each pair of sessions, participants had a 20% chance of receiving a feedback message from one of two human coaches, who were Master's students in Psychology. Out of 852 people who started the first conversational session, 500 completed all five sessions. 449 people further provided their preferences for allocating human feedback based on different principles in the post-questionnaire. There was also a follow-up questionnaire, but data from this questionnaire is not included in the analyses performed in this chapter.<br>The study was pre-registered in OSF: https://doi.org/10.17605/OSF.IO/78CNR.<br>The implementation of the conversational agent Kai is available online: https://doi.org/10.5281/zenodo.11102861.<br>The 523 human feedback messages that were written can be found here: https://doi.org/10.4121/7e88ca88-50e9-4e8d-a049-6266315a2ece.<br><strong>Data</strong>This repository includes these types of anonymized data:Data from the prescreening questionnaire (e.g., stage of change for quitting smoking),Data from people's Prolific profiles (e.g., age, gender),Data from the conversational sessions with Kai (e.g., effort spent on activities),Data from the post-questionnaire (e.g., preferences for allocation principles), andData on people clicking on the reading confirmation links in the human feedback messages.<br>The variable "rand_id" is a random participant identifier and can be used to link data from different data files.<br><strong>Analysis code</strong>All our analyses are based on either R or Python. We provide code to allow them to be reproduced.<br><br>In the case of questions, please contact Nele Albers ([e-mail]) or Willem-Paul Brinkman ([e-mail]).

本仓库包含了Nele Albers博士论文中章节《基于聊天机器人的戒烟干预中人类反馈的影响：心理、经济与伦理因素的实证研究》的相关数据与分析代码。<br><strong>研究概况</strong>本章节的研究数据主要采集自在线众包平台Prolific上开展的一项研究。本研究中，每日吸烟者与电子烟使用者可在2024年2月1日至3月19日期间，与文本型对话智能体（text-based conversational agent）Kai开展至多5轮对话会话。代尔夫特理工大学（Delft University of Technology）人类研究伦理委员会已为该研究授予伦理批准（批准函编号：3683）。<br>在每轮会话中，参与者会被分配37项戒烟准备活动中的一项（例如，畅想戒烟/戒电子烟后的理想自我、学习呼吸训练法、记录吸烟行为）。在每两轮会话之间，参与者有20%的概率收到两名心理学硕士研究生担任的人类教练所发送的反馈消息。在启动首轮对话会话的852名参与者中，共有500人完成了全部5轮会话。另有449人在后续问卷中提供了其基于不同原则分配人类反馈的偏好。本研究还设置了追踪问卷，但该问卷的数据未纳入本章节的分析范畴。<br>本研究已在OSF平台进行预注册：https://doi.org/10.17605/OSF.IO/78CNR。<br>对话智能体Kai的实现代码可在线获取：https://doi.org/10.5281/zenodo.11102861。<br>共计523条人类反馈消息可通过以下链接获取：https://doi.org/10.4121/7e88ca88-50e9-4e8d-a049-6266315a2ece。<br><strong>数据集说明</strong>本仓库包含以下几类匿名化数据：<br>1. 预筛查问卷数据（例如，戒烟行为改变阶段）<br>2. 参与者Prolific平台档案数据（例如，年龄、性别）<br>3. 与Kai的对话会话数据（例如，参与活动所投入的精力）<br>4. 后测问卷数据（例如，反馈分配原则偏好）<br>5. 参与者点击人类反馈消息中阅读确认链接的行为数据。<br>变量`rand_id`为随机生成的参与者标识符，可用于关联不同数据文件中的信息。<br><strong>分析代码</strong>本研究的所有分析均基于R语言或Python语言完成，我们已提供可复现全部分析结果的代码。<br><br>如有任何疑问，请联系Nele Albers（邮箱：[e-mail]）或Willem-Paul Brinkman（邮箱：[e-mail]）。