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: