"It Listens Better Than My Therapist": Exploring Social Media Discourse on LLMs as Mental Health Tool
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866912332991430656 |
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| author | Haensch, Anna-Carolina |
| author_facet | Haensch, Anna-Carolina |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_12337 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | "It Listens Better Than My Therapist": Exploring Social Media Discourse on LLMs as Mental Health Tool Haensch, Anna-Carolina Computation and Language Computers and Society Human-Computer Interaction Social and Information Networks J.4 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. |
| title | "It Listens Better Than My Therapist": Exploring Social Media Discourse on LLMs as Mental Health Tool |
| topic | Computation and Language Computers and Society Human-Computer Interaction Social and Information Networks J.4 |
| url | https://arxiv.org/abs/2504.12337 |