{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T13:44:34Z","timestamp":1792071874690,"version":"4.4.0"},"reference-count":31,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical &amp; Exp Dental Res"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Traumatic dental injuries (TDIs) are frequent in clinical practice and require rapid, guideline\u2010based decisions, yet accessing accurate and reliable information may be challenging. Large language models (LLMs) such as ChatGPT, Gemini, DeepSeek, and Qwen are increasingly used as quick online information tools; however, evidence regarding their accuracy, consistency, and the influence of different user interfaces is limited. This study aimed to evaluate the performance of several LLMs in answering TDI\u2010related questions through both web\u2010based interfaces and mobile phone applications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Material and Methods<\/jats:title>\n                    <jats:p>\n                      Twenty questions were prepared according to the 2020 International Association of Dental Traumatology (IADT) guidelines, including 10 open\u2010ended and 10 yes\u2013no items. Four LLMs (ChatGPT\u20104o, DeepSeek\u2010V3, Gemini 2.0 Flash, Qwen2.5\u2010Max) were queried simultaneously via web and mobile interfaces over five consecutive days, generating 800 responses. Open\u2010ended answers were assessed using the Global Quality Score (GQS) and modified DISCERN (mDISCERN), while yes\u2013no responses were compared with a predetermined answer key. Statistical analyses were performed using IBM SPSS v23.0, with significance set at\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Qwen2.5\u2010Max demonstrated comparatively higher GQS and mDISCERN scores across both interfaces. Accuracy for yes\u2013no questions ranged from 86% to 91% without significant differences among models. Interface comparisons showed that ChatGPT\u20104o generated comparatively higher\u2010quality responses on the web, whereas Qwen2.5\u2010Max performed better on mobile. Over the 5\u2010day period, Qwen2.5\u2010Max showed relatively higher temporal consistency, while DeepSeek\u2010V3 exhibited notable day\u2010to\u2010day variation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>LLMs may serve as useful supplementary tools for providing guideline\u2010based information on TDIs, especially for straightforward, closed\u2010ended clinical questions. However, their performance varies by model, interface, and question type. Qwen2.5\u2010Max demonstrated comparatively higher performance across several evaluated measures. Despite these results, LLM\u2010generated information should be interpreted cautiously and verified by dental professionals before being used in clinical decision\u2010making.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cre2.70416","type":"journal-article","created":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T07:24:37Z","timestamp":1784445877000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Large Language Models for Traumatic Dental Injuries Across Web\u2010Based and Mobile\u2010Based Interfaces: Assessing Accuracy, Quality, and Temporal Consistency"],"prefix":"10.1002","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5743-5625","authenticated-orcid":false,"given":"Ezgi Can","family":"Cekic","sequence":"first","affiliation":[{"name":"Department of Endodontics, Faculty of Dentistry Usak University Usak T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9832-9428","authenticated-orcid":false,"given":"Mertkan","family":"Kumru","sequence":"additional","affiliation":[{"name":"Department of Endodontics, Faculty of Dentistry Usak University Usak T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1651-0118","authenticated-orcid":false,"given":"Burcu","family":"Yilmaz","sequence":"additional","affiliation":[{"name":"Department of Endodontics, Faculty of Dentistry Usak University Usak T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7365-5476","authenticated-orcid":false,"given":"Berk","family":"Celikkol","sequence":"additional","affiliation":[{"name":"Department of Endodontics, Faculty of Dentistry Usak University Usak T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8030-436X","authenticated-orcid":false,"given":"O\u011fuz","family":"Tavsan","sequence":"additional","affiliation":[{"name":"Department of Endodontics, Faculty of Dentistry Usak University Usak T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,19]]},"reference":[{"key":"e_1_2_12_2_1","unstructured":"Anagnostidis S. andJ.Bulian. \u201cHow Susceptible Are LLMs to Influence in Prompts?\u201d arXiv preprint arXiv:2408118652024.https:\/\/doi.org\/10.48550\/arXiv.2408.11865."},{"key":"e_1_2_12_3_1","unstructured":"Atil B. S.Aykent A.Chittams et al. \u201cNon\u2010Determinism of \u201cDeterministic\u201d LLM Settings\u201d. arXiv preprint arXiv:2408046672024.https:\/\/doi.org\/10.48550\/arXiv.2408.04667."},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.2196\/55766"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.12578"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.13078"},{"key":"e_1_2_12_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.12576"},{"key":"e_1_2_12_8_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.12573"},{"key":"e_1_2_12_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12903-025-05926-2"},{"key":"e_1_2_12_10_1","unstructured":"Guan B. T.Roosta P.Passban andM.Rezagholizadeh. \u201cThe Order Effect: Investigating Prompt Sensitivity to Input Order in LLMs.\u201d arXiv preprint arXiv:2502041342025.https:\/\/doi.org\/10.48550\/arXiv.2502.04134."},{"key":"e_1_2_12_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12020-024-04031-8"},{"key":"e_1_2_12_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.13020"},{"key":"e_1_2_12_13_1","doi-asserted-by":"publisher","DOI":"10.3389\/feduc.2023.1272229"},{"key":"e_1_2_12_14_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.13000"},{"key":"e_1_2_12_15_1","doi-asserted-by":"publisher","DOI":"10.4103\/ijdr.ijdr_846_21"},{"key":"e_1_2_12_16_1","doi-asserted-by":"publisher","DOI":"10.5152\/TurkJOrthod.2019.18064"},{"key":"e_1_2_12_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00784-024-05968-w"},{"key":"e_1_2_12_18_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.13063"},{"key":"e_1_2_12_19_1","doi-asserted-by":"publisher","DOI":"10.2307\/2529310"},{"key":"e_1_2_12_20_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.12574"},{"key":"e_1_2_12_21_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.13041"},{"key":"e_1_2_12_22_1","doi-asserted-by":"publisher","DOI":"10.1111\/edt.12389"},{"key":"e_1_2_12_23_1","doi-asserted-by":"publisher","DOI":"10.2196\/73226"},{"key":"e_1_2_12_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nlp.2024.100083"},{"key":"e_1_2_12_25_1","doi-asserted-by":"publisher","DOI":"10.52225\/narra.v5i1.2371"},{"key":"e_1_2_12_26_1","doi-asserted-by":"publisher","DOI":"10.1111\/iej.13985"},{"key":"e_1_2_12_27_1","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.220079"},{"key":"e_1_2_12_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00276-025-03723-8"},{"key":"e_1_2_12_29_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-024-07930-y"},{"key":"e_1_2_12_30_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12903-025-06648-1"},{"key":"e_1_2_12_31_1","doi-asserted-by":"publisher","DOI":"10.2196\/63731"},{"key":"e_1_2_12_32_1","doi-asserted-by":"crossref","unstructured":"Zieglmeier V. andA. M.Lehene. \u201cDesigning Trustworthy User Interfaces.\u201d In:Proceedings of the 33rd Australian Conference on Human\u2010Computer Interaction 2021:182\u2013189.","DOI":"10.1145\/3520495.3520525"}],"container-title":["Clinical and Experimental Dental Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cre2.70416","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/cre2.70416","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cre2.70416","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T12:48:38Z","timestamp":1792068518000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/cre2.70416"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,19]]},"references-count":31,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["10.1002\/cre2.70416"],"URL":"https:\/\/doi.org\/10.1002\/cre2.70416","archive":["Portico"],"relation":{},"ISSN":["2057-4347","2057-4347"],"issn-type":[{"value":"2057-4347","type":"print"},{"value":"2057-4347","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,19]]},"assertion":[{"value":"2025-11-26","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-07-07","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-07-19","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70416"}}