Dataset and Analyses for Using a conversational agent for thought recording as a cognitive therapy task: feasibility, content, and feedback

This dataset contains all data and analysis scripts pertaining to the research conducted for the frontiers paper: "Using a conversational agent for thought recording as a cognitive therapy task: feasibility, content, and feedback." Following a literature review that we conducted in 2017 and 2018 on the technological state of the art of e-mental health for depression, we saw an opportunity to use technology in a more dialogical way than was being done to date. We therefore developed a conversational agent to support people in regularly recording their thoughts. This thought recording is a common technique in cognitive therapy. The cognitive approach to psychotherapy aims to change patients' maladaptive schemas, that is, overly negative views on themselves, the world, or the future. To obtain awareness of these views, they record their thought processes in situations that caused pathogenic emotional responses. We recruited 308 participants through Prolific, a crowd-sourcing platform for research participants. The participants interacted with our chatbot in two sessions, one practice session of two thought records based on scenarios and one actual session in which we asked to complete at least one personal thought record but as many additional ones as they wanted. We assessed the feasibility of completing the task with the agent, the content of the personal thought records, and whether the agent providing feedback on the content of the thought record (using natural language processing) had a positive e ect on the number of voluntarily completed thought records and participant's engagement in self-reection. We here deliver: a natural language dataset: the thoughts delineated by participants in the scenario-based and open thought records the coding of all personal thought records on their content by two independent coders: all thought records of the second session were labeled with respect to their content on the DIAMONDS and on three additional categories (COVID, Achievement/Competence, and Comprehensibility) analyses to test the hypotheses related to whether the feedback of the agent can increasemotivation to complete thought records additional materials (scenarios, qualtrics surveys, data management plan) that could assist in the replication of the study.

本数据集包含与发表于《前沿》期刊的论文"使用对话智能体（AI Agent）进行思维记录作为认知治疗任务：可行性、内容与反馈"相关的全部数据与分析脚本。我们于2017年至2018年针对抑郁症电子心理健康领域的技术前沿开展了文献综述，由此发现了采用比现有方案更具对话性的技术手段的契机，因此开发了一款对话智能体，用于辅助用户定期记录自身思维。思维记录是认知治疗中的常用技术，认知取向心理治疗的目标在于改变患者的适应不良图式——即对自身、世界或未来的过度消极认知；为察觉此类认知，患者需在引发病理性情绪反应的情境中记录自身思维过程。我们通过研究参与者众包平台Prolific招募了308名参与者，参与者需与我们开发的聊天机器人开展两次交互：一次为练习会话，基于场景完成两份思维记录；另一次为正式会话，要求参与者至少完成一份个人思维记录，也可自愿完成更多份。我们评估了使用该智能体完成任务的可行性、个人思维记录的内容，以及该基于自然语言处理（NLP）对思维记录内容提供反馈的智能体，是否对自愿完成的思维记录数量与参与者的自我反思参与度产生积极影响。本数据集提供如下资源：一是自然语言数据集，即参与者在基于场景的思维记录与开放式思维记录中描述的思维内容；二是两名独立编码员对所有个人思维记录的内容编码结果：针对第二次会话的全部思维记录，依据DIAMONDS量表以及COVID、成就/能力、可理解性三个额外类别进行内容标注，以检验关于智能体反馈能否提升思维记录完成动机的研究假设；三是可辅助该研究复现的补充材料，包括场景脚本、Qualtrics调查问卷、数据管理计划。