"It Listens Better Than My Therapist": Exploring Social Media Discourse on LLMs as Mental Health Tool
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Abstract (arXiv)
The emergence of generative AI chatbots such as ChatGPT has prompted growing public and academic interest in their role as informal mental health support tools. While early rule-based systems have been around for several years, large language models (LLMs) offer new capabilities in conversational fluency, empathy simulation, and availability. This study explores how users engage with LLMs as mental health tools by analyzing over 10,000 TikTok comments from videos referencing LLMs as mental health tools. Using a self-developed tiered coding schema and supervised classification models, we identify user experiences, attitudes, and recurring themes. Results show that nearly 20% of comments reflect personal use, with these users expressing overwhelmingly positive attitudes. Commonly cited benefits include accessibility, emotional support, and perceived therapeutic value. However, concerns around privacy, generic responses, and the lack of professional oversight remain prominent. It is important to note that the user feedback does not indicate which therapeutic framework, if any, the LLM-generated output aligns with. While the findings underscore the growing relevance of AI in everyday practices, they also highlight the urgent need for clinical and ethical scrutiny in the use of AI for mental health support.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 2 of its 35 references that are in the map. First posted on arXiv 14 Apr 2025.
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2 of 35 references.
References · 2
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2026Using LLM-as-a-Judge/Jury to Advance Scalable, Clinically-Validated Safety Evaluations of Model Responses to Users Demonstrating Psychosiscited by 3
- 2025Developing and Validating the Arabic Version of the Attitudes Toward Large Language Models Scalecited by 0
- 2026LLMs for health: Perceived benefits, risks, intention to use AI chatbots, and willingness to self-disclose across sensitive health topicscited by 0
- 2026LLMs for health: Perceived benefits, risks, intention to use AI chatbots, and willingness to self-disclose across sensitive health topics10 Jul 2026
- 2026Using LLM-as-a-Judge/Jury to Advance Scalable, Clinically-Validated Safety Evaluations of Model Responses to Users Demonstrating Psychosis20 Mar 2026
- 2025Developing and Validating the Arabic Version of the Attitudes Toward Large Language Models Scale14 Oct 2025