{"title":"“This is human intelligence debugging artificial intelligence”: Examining how people prompt GPT in seeking mental health support","authors":"Zhuoyang Li , Zihao Zhu , Xinning Gui , Yuhan Luo","doi":"10.1016/j.ijhcs.2025.103555","DOIUrl":null,"url":null,"abstract":"<div><div>Large language models (LLMs) could extend digital support for mental well-being with their unprecedented language understanding and generation ability. While we have seen individuals who lack access to professional care utilizing LLMs for mental health support, it is unclear how they prompt and interact with LLMs given their individualized emotional needs and life situations. In this work, we analyzed 49 threads and 7,538 comments on Reddit, aiming to understand how people seek mental health support from GPT by creating and crafting various prompts. Despite GPT explicitly disclaiming that it is not an alternative to professional care, we found that users continued to use it for support and devised different prompts to bypass the safety guardrails. Meanwhile, users actively refined and shared their prompts to make GPT more human-like by specifying nuanced communication styles and cultivating in-depth discussions. They also came up with several strategies to make GPT communicate more efficiently to enrich the customized personas on the fly or gain multiple perspectives. Reflecting on these findings, we discuss the tensions associated with using LLMs for mental health support and the implications for designing safer and more empowering human-LLM interactions.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"203 ","pages":"Article 103555"},"PeriodicalIF":5.1000,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Human-Computer Studies","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1071581925001120","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
引用次数: 0
Abstract
Large language models (LLMs) could extend digital support for mental well-being with their unprecedented language understanding and generation ability. While we have seen individuals who lack access to professional care utilizing LLMs for mental health support, it is unclear how they prompt and interact with LLMs given their individualized emotional needs and life situations. In this work, we analyzed 49 threads and 7,538 comments on Reddit, aiming to understand how people seek mental health support from GPT by creating and crafting various prompts. Despite GPT explicitly disclaiming that it is not an alternative to professional care, we found that users continued to use it for support and devised different prompts to bypass the safety guardrails. Meanwhile, users actively refined and shared their prompts to make GPT more human-like by specifying nuanced communication styles and cultivating in-depth discussions. They also came up with several strategies to make GPT communicate more efficiently to enrich the customized personas on the fly or gain multiple perspectives. Reflecting on these findings, we discuss the tensions associated with using LLMs for mental health support and the implications for designing safer and more empowering human-LLM interactions.
期刊介绍:
The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities.
Research areas relevant to the journal include, but are not limited to:
• Innovative interaction techniques
• Multimodal interaction
• Speech interaction
• Graphic interaction
• Natural language interaction
• Interaction in mobile and embedded systems
• Interface design and evaluation methodologies
• Design and evaluation of innovative interactive systems
• User interface prototyping and management systems
• Ubiquitous computing
• Wearable computers
• Pervasive computing
• Affective computing
• Empirical studies of user behaviour
• Empirical studies of programming and software engineering
• Computer supported cooperative work
• Computer mediated communication
• Virtual reality
• Mixed and augmented Reality
• Intelligent user interfaces
• Presence
...