{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T16:41:07Z","timestamp":1791996067657,"version":"4.4.0"},"reference-count":52,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,2,4]],"date-time":"2025-02-04T00:00:00Z","timestamp":1738627200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Background\/Objectives: The evolving capabilities of large language models, such as generative pre-trained transformers (ChatGPT), offer new avenues for disseminating health information online. These models, trained on extensive datasets, are designed to deliver customized responses to user queries. However, as these outputs are unsupervised, understanding their quality and accuracy is essential to gauge their reliability for potential applications in healthcare. This study evaluates responses generated by ChatGPT addressing common patient concerns and questions about cleft lip repair. Methods: Ten commonly asked questions about cleft lip repair procedures were selected from the American Society of Plastic Surgeons\u2019 patient information resources. These questions were input as ChatGPT prompts and five board-certified plastic surgeons assessed the generated responses on quality of content, clarity, relevance, and trustworthiness, using a 4-point Likert scale. Readability was evaluated using the Flesch reading ease score (FRES) and the Flesch\u2013Kincaid grade level (FKGL). Results: ChatGPT responses scored an aggregated mean rating of 2.9 out of 4 across all evaluation criteria. Clarity and content quality received the highest ratings (3.1 \u00b1 0.6), while trustworthiness had the lowest rating (2.7 \u00b1 0.6). Readability metrics revealed a mean FRES of 44.35 and a FKGL of 10.87, corresponding to approximately a 10th-grade literacy standard. None of the responses contained grossly inaccurate or potentially harmful medical information but lacked citations. Conclusions: ChatGPT demonstrates potential as a supplementary tool for patient education in cleft lip management by delivering generally accurate, relevant, and understandable information. Despite the value that AI-powered tools can provide to clinicians and patients, the lack of human oversight underscores the importance of user awareness regarding its limitations.<\/jats:p>","DOI":"10.3390\/jcm14030993","type":"journal-article","created":{"date-parts":[[2025,2,4]],"date-time":"2025-02-04T08:25:23Z","timestamp":1738657523000},"page":"993","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Exploring the Utility of ChatGPT in Cleft Lip Repair Education"],"prefix":"10.3390","volume":"14","author":[{"given":"Monali","family":"Mahedia","sequence":"first","affiliation":[{"name":"Department of Surgery, Rutgers University\u2014NJMS, Newark, NJ 07103, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachel N.","family":"Rohrich","sequence":"additional","affiliation":[{"name":"Department of Plastic and Reconstructive Surgery, MedStar Georgetown University Hospital, Washington, DC 20007, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaiser O\u2019Sahil","family":"Sadiq","sequence":"additional","affiliation":[{"name":"Department of Surgery, University of Washington, Seattle, WA 98195, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4065-4541","authenticated-orcid":false,"given":"Lauren","family":"Bailey","sequence":"additional","affiliation":[{"name":"Department of Plastic Surgery, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3168-1879","authenticated-orcid":false,"given":"Lucas M.","family":"Harrison","sequence":"additional","affiliation":[{"name":"Department of Plastic Surgery, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9025-399X","authenticated-orcid":false,"given":"Rami R.","family":"Hallac","sequence":"additional","affiliation":[{"name":"Department of Plastic Surgery, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA"},{"name":"Analytical Imaging and Modeling Center, Children\u2019s Health, Dallas, TX 75235, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Walker, H.L., Ghani, S., Kuemmerli, C., Nebiker, C.A., M\u00fcller, B.P., Raptis, D.A., and Staubli, S.M. (2023). Reliability of Medical Information Provided by ChatGPT: Assessment Against Clinical Guidelines and Patient Information Quality Instrument. J. Med. Internet Res., 25.","DOI":"10.2196\/47479"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Xie, Y., Seth, I., Hunter-Smith, D.J., Rozen, W.M., Ross, R., and Lee, M. (2023). Aesthetic Surgery Advice and Counseling from Artificial Intelligence: A Rhinoplasty Consultation with ChatGPT. Aesthetic Plast. Surg., 47.","DOI":"10.1007\/s00266-023-03338-7"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.mcpdig.2023.06.002","article-title":"Plastic Surgery and Artificial Intelligence: How ChatGPT Improved Operation Note Accuracy, Time, and Education","volume":"1","author":"Abdelhady","year":"2023","journal-title":"Mayo Clin. Proc. Digit. Health"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Shiraishi, M., Lee, H., Kanayama, K., Moriwaki, Y., and Okazaki, M. (2024). Appropriateness of Artificial Intelligence Chatbots in Diabetic Foot Ulcer Management. Int. J. Low. Extrem. Wounds.","DOI":"10.1177\/15347346241236811"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1097\/PRS.0000000000010342","article-title":"OpenAI\u2019s ChatGPT and Its Role in Plastic Surgery Research","volume":"151","author":"Weidman","year":"2023","journal-title":"Plast. Reconstr. Surg."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Xue, V.W., Lei, P., and Cho, W.C. (2023). The potential impact of ChatGPT in clinical and translational medicine. Clin. Transl. Med., 13.","DOI":"10.1002\/ctm2.1216"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Babai, A., and Irving, M. (2023). Orofacial Clefts: Genetics of Cleft Lip and Palate. Genes, 14.","DOI":"10.3390\/genes14081603"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1177\/10556656221089160","article-title":"Range and Frequency of Congenital Malformations Among Children With Cleft Lip and\/or Palate","volume":"60","author":"Fitzsimons","year":"2023","journal-title":"Cleft Palate Craniofacial J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2621","DOI":"10.4103\/jfmpc.jfmpc_472_20","article-title":"Cleft of lip and palate: A review","volume":"9","author":"Vyas","year":"2020","journal-title":"J. Fam. Med. Prim. Care"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Paradowska-Stolarz, A., Mikulewicz, M., and Du\u015b-Ilnicka, I. (2022). Current Concepts and Challenges in the Treatment of Cleft Lip and Palate Patients\u2014A Comprehensive Review. J. Pers. Med., 12.","DOI":"10.3390\/jpm12122089"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Stock, N.M., Blaso, D., and Hotton, M. (2024). Caring for a Child with a Cleft Lip and\/or Palate: A Narrative Review. Cleft Palate Craniofacial J.","DOI":"10.1177\/10556656241280071"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/5584_2019_396","article-title":"The Internet as a Source of Health Information and Services","volume":"1211","year":"2019","journal-title":"Adv. Exp. Med. Biol."},{"key":"ref_13","unstructured":"Gualtieri, L.N. (2009, January 4\u20139). The doctor as the second opinion and the internet as the first. Proceedings of the Conference on Human Factors in Computing Systems\u2014Proceedings, Boston, MA, USA."},{"key":"ref_14","first-page":"530","article-title":"A quality assessment of online patient information regarding rhinoplasty","volume":"38","author":"Shamil","year":"2021","journal-title":"Facial Plast. Surg."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2067","DOI":"10.1177\/10556656231193966","article-title":"Dr. ChatGPT: Utilizing Artificial Intelligence in Surgical Education","volume":"61","author":"Lebhar","year":"2023","journal-title":"Cleft Palate-Craniofacial J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"116","DOI":"10.7181\/acfs.2024.00115","article-title":"The new frontier: Utilizing ChatGPT to expand craniofacial research","volume":"25","author":"Zhang","year":"2024","journal-title":"Arch. Craniofacial Surg."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1001\/jamainternmed.2023.1838","article-title":"Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum","volume":"183","author":"Ayers","year":"2023","journal-title":"JAMA Intern. Med."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1089\/fpsam.2023.0224","article-title":"Artificial Intelligence Versus Expert Plastic Surgeon: Comparative Study Shows ChatGPT \u201cWins\u201d Rhinoplasty Consultations: Should We Be Worried?","volume":"26","author":"Durairaj","year":"2023","journal-title":"Facial Plast. Surg. Aesthetic Med."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"124","DOI":"10.3390\/dermato4040013","article-title":"Dermatological Knowledge and Image Analysis Performance of Large Language Models Based on Specialty Certificate Examination in Dermatology","volume":"4","author":"Fan","year":"2024","journal-title":"Dermato"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Shamil, E., Ko, T.K., Fan, K.S., Schuster-Bruce, J., Jaafar, M., Khwaja, S., Eynon-Lewis, N., D\u2019Souza, A.R., and Andrews, P. (2024). Assessing the quality and readability of online patient information: ENT UK patient information e-leaflets vs responses by a Generative Artificial Intelligence. Facial Plast. Surg.","DOI":"10.1055\/a-2413-3675"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Mesk\u00f3, B. (2023). Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial. J. Med. Internet Res., 25.","DOI":"10.2196\/50638"},{"key":"ref_22","unstructured":"American Society of Plastic Surgeons (2024, December 23). Cleft Lip and Cleft Palate Repair. Available online: https:\/\/www.plasticsurgery.org\/reconstructive-procedures\/cleft-lip-and-cleft-palate-repair."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Eltorai, A.E.M., Ghanian, S., Adams, C.A., Born, C.T., and Daniels, A.H. (2014). Readability of Patient Education Materials on the American Association for Surgery of Trauma Website. Arch. Trauma Res., 3.","DOI":"10.5812\/atr.18161"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Yun, J.Y., Kim, D.J., Lee, N., and Kim, E.K. (2023). A comprehensive evaluation of ChatGPT consultation quality for augmentation mammoplasty: A comparative analysis between plastic surgeons and laypersons. Int. J. Med. Inform., 179.","DOI":"10.1016\/j.ijmedinf.2023.105219"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"945","DOI":"10.1177\/10556656221149127","article-title":"A Comprehensive Assessment of Cleft Lip and Palate Websites and Patient Education Information","volume":"61","author":"Sunkara","year":"2023","journal-title":"Cleft Palate-Craniofacial J."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1114","DOI":"10.1016\/j.ijom.2018.03.003","article-title":"Clefts of the lip and palate: Is the Internet a trustworthy source of information for patients?","volume":"47","author":"Karamitros","year":"2018","journal-title":"Int. J. Oral Maxillofac. Surg."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1055\/s-0041-1741502","article-title":"The Quality of Online Information on Cosmetic Injectable Fillers: Current Status","volume":"38","author":"Shamil","year":"2022","journal-title":"Facial Plast. Surg. FPS"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1177\/1055665619866349","article-title":"YouTube as a Patient-Information Source for Cleft Lip and Palate","volume":"57","author":"Korkmaz","year":"2019","journal-title":"Cleft Palate-Craniofacial J."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Grollemund, B., Dissaux, C., Gavelle, P., Mart\u00ednez, C.P., Mullaert, J., Alfaiate, T., Guedeney, A., Vazquez, M.P., Bruand-Rodier, C., and Danion-Grilliat, A. (2020). The impact of having a baby with cleft lip and palate on parents and on parent-baby relationship: The first French prospective multicentre study. BMC Pediatr., 20.","DOI":"10.1186\/s12887-020-02118-5"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1007\/s00238-019-01530-0","article-title":"Parental and health care professional views on psychosocial and educational outcomes in patients with cleft lip and\/or cleft palate","volume":"42","author":"Stiernman","year":"2019","journal-title":"Eur. J. Plast. Surg."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hallac, R.R., Lee, J., Pressler, M., Seaward, J.R., and Kane, A.A. (2019). Identifying Ear Abnormality from 2D Photographs Using Convolutional Neural Networks. Sci. Rep., 9.","DOI":"10.1038\/s41598-019-54779-7"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Hallac, R.R., Jackson, S.A., Grant, J., Fisher, K., Scheiwe, S., Wetz, E., Perez, J., Lee, J., Chitta, K., and Seaward, J.R. (2021). Assessing outcomes of ear molding therapy by health care providers and convolutional neural network. Sci. Rep., 11.","DOI":"10.1038\/s41598-021-97310-7"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Wang, D., Chen, X., Wu, Y., Tang, H., and Deng, P. (2022). Artificial intelligence for assessing the severity of microtia via deep convolutional neural networks. Front. Surg., 9.","DOI":"10.3389\/fsurg.2022.929110"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Agarwal, S., Hallac, R.R., Daescu, O., and Kane, A. (2021). Classification of Craniosynostosis Images by Vigilant Feature Extraction. Advances in Computer Vision and Computational Biology, Springer.","DOI":"10.1007\/978-3-030-71051-4_23"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Qamar, A., Bangi, S.F., and Barve, R. (2023). Artificial Intelligence Applications in Diagnosing and Managing Non-syndromic Craniosynostosis: A Comprehensive Review. Cureus, 15.","DOI":"10.7759\/cureus.45318"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Kuehle, R., Ringwald, F., Bouffleur, F., Hagen, N., Schaufelberger, M., Nahm, W., Hoffmann, J., Freudlsperger, C., Engel, M., and Eisenmann, U. (2023). The Use of Artificial Intelligence for the Classification of Craniofacial Deformities. J. Clin. Med., 12.","DOI":"10.3390\/jcm12227082"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Rosero, K., Salman, A.N., Harrison, L.M., Kane, A.A., Busso, C., and Hallac, R.R. (2025). Deep Learning-Based Assessment of Lip Symmetry for Patients With Repaired Cleft Lip. Cleft Palate Craniofacial J.","DOI":"10.1177\/10556656241312730"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Miranda, F., Choudhari, V., Barone, S., Anchling, L., Hutin, N., Gurgel, M., Al Turkestani, N., Yatabe, M., Bianchi, J., and Aliaga-Del Castillo, A. (2023). Interpretable artificial intelligence for classification of alveolar bone defect in patients with cleft lip and palate. Sci. Rep., 13.","DOI":"10.1038\/s41598-023-43125-7"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"ElHawary, H., Gorgy, A., and Janis, J.E. (2023). Large Language Models in Academic Plastic Surgery: The Way Forward. Plast. Reconstr. Surg.-Glob. Open, 11.","DOI":"10.1097\/GOX.0000000000004949"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Gomez-Cabello, C.A., Borna, S., Pressman, S.M., Haider, S.A., and Forte, A.J. (2024). Large Language Models for Intraoperative Decision Support in Plastic Surgery: A Comparison between ChatGPT-4 and Gemini. Medicina, 60.","DOI":"10.3390\/medicina60060957"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1055\/s-0043-1772704","article-title":"Leveraging Large Language Models (LLM) for the Plastic Surgery Resident Training: Do They Have a Role?","volume":"56","author":"Mohapatra","year":"2023","journal-title":"Indian J. Plast. Surg."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1111\/hex.13105","article-title":"Shared decision making in surgery: A scoping review of the literature","volume":"23","author":"Niburski","year":"2020","journal-title":"Health Expect."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1049","DOI":"10.1093\/bjs\/znac291","article-title":"Shared decision-making should be a standard part of surgical care","volume":"109","author":"Ubbink","year":"2022","journal-title":"Br. J. Surg."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Vermeir, P., Vandijck, D., Degroote, S., Peleman, R., Verhaeghe, R., Mortier, E., Hallaert, G., Van Daele, S., Buylaert, W., and Vogelaers, D. (2015). Communication in healthcare: A narrative review of the literature and practical recommendations. Int. J. Clin. Pract., 69.","DOI":"10.1111\/ijcp.12686"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1016\/j.jopan.2021.07.001","article-title":"The Effect of Patient Education Prior to Rhinoplasty Surgery on Anxiety, Pain, and Satisfaction Levels","volume":"37","author":"Topan","year":"2022","journal-title":"J. Perianesthesia Nurs."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Shamil, E., Jaafar, M., Fan, K.S., Ko, T.K., Schuster-Bruce, J., Eynon-Lewis, N., and Andrews, P. (2024). The use of large language models like ChatGPT on delivering patient information relating to surgery. Facial Plast. Surg.","DOI":"10.1055\/a-2413-3529"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Ghorbani, F., Ahmadi, H., and Davar, G. (2023). Patient dissatisfaction following rhinoplasty: A 10-year experience in Iran. Maxillofac. Plast. Reconstr. Surg., 45.","DOI":"10.1186\/s40902-022-00369-z"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Park, B.Y., Kwon, J., Kang, S.R., and Hong, S.E. (2016). Informed Consent as a Litigation Strategy in the Field of Aesthetic Surgery: An Analysis Based on Court Precedents. Arch. Plast. Surg., 43.","DOI":"10.5999\/aps.2016.43.5.402"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1132","DOI":"10.1093\/asj\/sjaa380","article-title":"Characterization of Medical Malpractice Litigation After Rhinoplasty in the United States","volume":"41","author":"Ong","year":"2021","journal-title":"Aesthetic Surg. J."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Willems, J. (2023). ChatGPT at Universities\u2014The Least of Our Concerns. SSRN Electron. J.","DOI":"10.2139\/ssrn.4334162"},{"key":"ref_51","first-page":"862e","article-title":"Implications for the Use of Artificial Intelligence in Plastic Surgery Research and Practice","volume":"153","author":"Kwon","year":"2023","journal-title":"Plast. Reconstr. Surg."},{"key":"ref_52","first-page":"1","article-title":"Editorial\u2014The Use of Large Language Models in Science: Opportunities and Challenges","volume":"9","author":"Almarie","year":"2023","journal-title":"Princ. Pract. Clin. Res."}],"container-title":["Journal of Clinical Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2077-0383\/14\/3\/993\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:26:45Z","timestamp":1760027205000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2077-0383\/14\/3\/993"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,4]]},"references-count":52,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,2]]}},"alternative-id":["jcm14030993"],"URL":"https:\/\/doi.org\/10.3390\/jcm14030993","relation":{},"ISSN":["2077-0383"],"issn-type":[{"value":"2077-0383","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,4]]}}}