{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T13:39:09Z","timestamp":1793021949597,"version":"4.5.0"},"reference-count":21,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T00:00:00Z","timestamp":1778025600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["European Journal of Ophthalmology"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To evaluate and compare the performance of five artificial intelligence (AI) chatbots\u2014ChatGPT (OpenAI 4), Google Gemini, Grok (xAI), DeepSeek, and Meta Llama \u2014in delivering accurate, clear, educational, and safe responses to caregiver-facing queries related to strabismus.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Sixteen standardized caregiver questions on strabismus were presented to each chatbot in independent sessions. Five fellowship-trained pediatric ophthalmologists rated each response across four domains\u2014Accuracy, Clarity, Educational Value, and Safety\u2014using a 5-point Likert scale (1\u2009=\u2009Poor, 5\u2009=\u2009Excellent). Between-chatbot differences were analyzed using cumulative link mixed models (CLMMs) with odds ratios (OR) and 95% confidence intervals (CI). Holm-adjusted pairwise contrasts corrected for multiple comparisons. Inter-rater reliability was assessed using quadratic-weighted Fleiss\u2019 \u03ba and Gwet's AC1 to address prevalence and bias effects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      ChatGPT achieved the highest proportion of top ratings (\u22654) for Accuracy (65%) and Clarity (59%), followed by Llama (41% and 47.5%, respectively). For Educational Value, Llama (43.8%) and Gemini (42.5%) performed slightly better, while Safety ratings were highest for Gemini (40%) and Llama (37.5%). CLMM analysis showed significant between-chatbot differences for Accuracy, Clarity, and Educational Value (\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009&lt;\u20090.05) but not for Safety. Compared with ChatGPT, lower odds of higher ratings were seen for Grok (OR 0.48) and DeepSeek (OR 0.61). Inter-rater reliability indicated moderate agreement (Fleiss\u2019 \u03ba\u2009=\u20090.59) and strong consensus (Gwet's AC1\u2009=\u20090.87).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>ChatGPT showed superior accuracy and clarity, while Gemini and Llama excelled in educational value and safety. High expert agreement supports AI chatbots as adjuncts in pediatric ophthalmology education requiring continued validation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/11206721261445529","type":"journal-article","created":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T13:14:11Z","timestamp":1778073251000},"page":"1553-1561","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["AI chatbots in strabismus care: A multidomain expert evaluation of caregiver-facing information"],"prefix":"10.1177","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2198-1413","authenticated-orcid":false,"given":"Dhiman","family":"Shweta","sequence":"first","affiliation":[{"name":"Department of Pediatric Ophthalmology &amp; Strabismus, JPM Rotary Eye Hospital and Research Institute, Cuttack, Odisha, India-753014"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dutta","family":"Paromita","sequence":"additional","affiliation":[{"name":"Maulana Azad Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3158-5581","authenticated-orcid":false,"given":"Thacker","family":"Prolima","sequence":"additional","affiliation":[{"name":"Dr. Ram Manohar Lohia Institute of Medical Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1929-4451","authenticated-orcid":false,"given":"Kaur","family":"Savleen","sequence":"additional","affiliation":[{"name":"PGIMER"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maniar","family":"Ashini","sequence":"additional","affiliation":[{"name":"Consultant Pediatric Ophthalmology, Squint and Neuro ophthalmologist, B.J. Wadia Children's Hospital, Mumbai, India-400054"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7781-4852","authenticated-orcid":false,"given":"Kenia","family":"Raj","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, JPM Rotary Eye Hospital and Research Institute, Cuttack, Odisha, India-753014"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Balakrishnan","family":"Logesh","sequence":"additional","affiliation":[{"name":"Apollo Hospitals"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mishra","family":"Chitaranjan","sequence":"additional","affiliation":[{"name":"Trilochan Netralaya"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,5,6]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2004.07.033"},{"key":"e_1_3_2_3_2","first-page":"493","article-title":"Prevalence and risk factors for strabismus in a UK birth cohort","volume":"93","author":"Williams C","year":"2008","unstructured":"Williams C, Northstone K, Howard M, et al. Prevalence and risk factors for strabismus in a UK birth cohort. Arch Dis Child 2008; 93: 493\u2013498.","journal-title":"Arch Dis Child"},{"key":"e_1_3_2_4_2","first-page":"151.e1","article-title":"Parental concerns and misconceptions about strabismus and its treatment: a survey of caregivers","volume":"25","author":"Taira O","year":"2021","unstructured":"Taira O, Tanabe S, Watanabe T, et al. Parental concerns and misconceptions about strabismus and its treatment: a survey of caregivers. 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Evaluating multiple large language models in pediatric ophthalmology. arXiv preprint 2023: arXiv:2311.04368.","journal-title":"arXiv preprint"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajoint.2025.100188"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1136\/archdischild-2012-303002"},{"key":"e_1_3_2_13_2","article-title":"Artificial intelligence (AI) chatbots in medicine: a supplement, not a substitute","volume":"15","author":"Altamimi I","year":"2023","unstructured":"Altamimi I, Altamimi A, Alhumimidi AS, et al. Artificial intelligence (AI) chatbots in medicine: a supplement, not a substitute. 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