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We investigated the ability of the large language model (LLM) GPT-4 to correctly infer social anxiety symptom strength from transcripts obtained from semi-structured interviews.\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u200951 adult participants were recruited from a convenience sample of the German population. Participants filled in a self-report questionnaire on social anxiety symptoms (SPIN) prior to being interviewed on a secure online teleconference platform. Transcripts from these interviews were then evaluated by GPT-4. GPT-4 predictions were highly correlated (\n                    <jats:italic>r<\/jats:italic>\n                    \u2009=\u20090.79) with scores obtained on the social anxiety self-report measure. Following the cut-off conventions for this population, an F\n                    <jats:sub>1<\/jats:sub>\n                    accuracy score of 0.84 could be obtained. Future research should examine whether these findings hold true in larger and more diverse datasets.\n                  <\/jats:p>","DOI":"10.1038\/s41598-024-82192-2","type":"journal-article","created":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T08:18:54Z","timestamp":1734337134000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["GPT-4 shows potential for identifying social anxiety from clinical interview data"],"prefix":"10.1038","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-3344-4753","authenticated-orcid":false,"given":"Julia","family":"Ohse","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1197-7255","authenticated-orcid":false,"given":"Bakir","family":"Had\u017ei\u0107","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7448-7857","authenticated-orcid":false,"given":"Parvez","family":"Mohammed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9481-9354","authenticated-orcid":false,"given":"Nicolina","family":"Peperkorn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9854-3780","authenticated-orcid":false,"given":"Janosch","family":"Fox","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1242-9070","authenticated-orcid":false,"given":"Joshua","family":"Krutzki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9843-8776","authenticated-orcid":false,"given":"Alexander","family":"Lyko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0492-4708","authenticated-orcid":false,"given":"Fan","family":"Mingyu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9947-2742","authenticated-orcid":false,"given":"Xiaohu","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8254-8293","authenticated-orcid":false,"given":"Matthias","family":"R\u00e4tsch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6281-0901","authenticated-orcid":false,"given":"Youssef","family":"Shiban","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,16]]},"reference":[{"key":"82192_CR1","unstructured":"World Health Organization. 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