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However, there is still a significant gap in research when it comes to understanding and enhancing the capabilities of LLMs in the field of mental health. In this work, we present a comprehensive evaluation of multiple LLMs on various mental health prediction tasks via online text data, including Alpaca, Alpaca-LoRA, FLAN-T5, GPT-3.5, and GPT-4. We conduct a broad range of experiments, covering zero-shot prompting, few-shot prompting, and instruction fine-tuning. The results indicate a promising yet limited performance of LLMs with zero-shot and few-shot prompt designs for mental health tasks. More importantly, our experiments show that instruction finetuning can significantly boost the performance of LLMs for all tasks simultaneously. Our best-finetuned models, Mental-Alpaca and Mental-FLAN-T5, outperform the best prompt design of GPT-3.5 (25 and 15 times bigger) by 10.9% on balanced accuracy and the best of GPT-4 (250 and 150 times bigger) by 4.8%. They further perform on par with the state-of-the-art task-specific language model. We also conduct an exploratory case study on LLMs' capability on mental health reasoning tasks, illustrating the promising capability of certain models such as GPT-4. We summarize our findings into a set of action guidelines for potential methods to enhance LLMs' capability for mental health tasks. Meanwhile, we also emphasize the important limitations before achieving deployability in real-world mental health settings, such as known racial and gender bias. We highlight the important ethical risks accompanying this line of research.<\/jats:p>","DOI":"10.1145\/3643540","type":"journal-article","created":{"date-parts":[[2024,3,6]],"date-time":"2024-03-06T13:12:36Z","timestamp":1709730756000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":191,"title":["Mental-LLM"],"prefix":"10.1145","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5930-3899","authenticated-orcid":false,"given":"Xuhai","family":"Xu","sequence":"first","affiliation":[{"name":"Massachusetts Institute of Technology &amp; University of Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8329-4610","authenticated-orcid":false,"given":"Bingsheng","family":"Yao","sequence":"additional","affiliation":[{"name":"Rensselaer Polytechnic Institute, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-2013-1157","authenticated-orcid":false,"given":"Yuanzhe","family":"Dong","sequence":"additional","affiliation":[{"name":"Stanford University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9353-951X","authenticated-orcid":false,"given":"Saadia","family":"Gabriel","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9263-5035","authenticated-orcid":false,"given":"Hong","family":"Yu","sequence":"additional","affiliation":[{"name":"University of Massachusetts Lowell, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3056-1960","authenticated-orcid":false,"given":"James","family":"Hendler","sequence":"additional","affiliation":[{"name":"Rensselaer Polytechnic Institute, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6349-7251","authenticated-orcid":false,"given":"Marzyeh","family":"Ghassemi","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3004-0770","authenticated-orcid":false,"given":"Anind K.","family":"Dey","sequence":"additional","affiliation":[{"name":"University of Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9371-9441","authenticated-orcid":false,"given":"Dakuo","family":"Wang","sequence":"additional","affiliation":[{"name":"Northeastern University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,3,6]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2022. 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