Analysis of ChatGPT responses to breastfeeding questions
Main Article Content
Abstract
Introduction: Artificial intelligence tools are impacting medicine in a way that makes knowledge more accessible to both doctors and patients, but their absolute accuracy is still little studied. Objective: This study aims to evaluate the quality of responses provided by ChatGPT to potential inquiries from families regarding breastfeeding. Methods: A cross-sectional study was conducted through an online questionnaire with active Brazilian pediatricians (n=56) who expressed their opinions on ten pairs of questions and answers related to breastfeeding. Questions were formulated based on common doubts, and responses were obtained after submitting the queries to ChatGPT. The quality of responses was assessed on a scale of 1 to 5 points. Results: The findings revealed an average score exceeding 4.0 for all questions posed to the artificial intelligence regarding "Clarity of the provided answer" and "Conformity with current scientific knowledge." Regarding "I am satisfied with the presented response," participants rated ChatGPT responses above 4.0 for most questions. Most pediatricians agreed with the statement, "If I were responding to this question for a real patient, my answer would be different." Conclusion: Responses generated by ChatGPT received high satisfaction rates from the population of pediatricians who evaluated them, being considered clear and based on updated scientific knowledge. However, most pediatricians stated they would provide different responses to their patients.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY) that allows others to share and adapt the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.References
Ayers JW, Poliak A, Dredze M, Leas EC, Zhu Z, Kelley JB, et al. Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA Intern Med. 2023;183(6):589-96. https://doi.org/10.1001/jamainternmed.2023.1838
Javaid M, Haleem A, Singh R. ChatGPT for healthcare services: An emerging stage for an innovative perspective. Bench Council Transact Benchmarks Stand Evaluation. 2023;3(1):100105. https://doi.org/10.1016/j.tbench.2023.100105
Pan A, Musheyev D, Bockelman D, Loeb S, Kabarriti AE. Assessment of artificial intelligence chatbot responses to top searched queries about cancer. JAMA Oncol. 2023;9(10):1437-40. https://doi.org/10.1001/jamaoncol.2023.2947
Chen S, Kann BH, Foote MB, Aerts HJWL, Savova GK, Mak RH, et al. Use of artificial intelligence chatbots for cancer treatment information. JAMA Oncol. 2023;9(10):1459-62. https://doi.org/10.1001/jamaoncol.2023.2954
Lee TC, Staller K, Botoman V, Pathipati MP, Varma S, Kuo B. ChatGPT answers common patient questions about colonoscopy. Gastroenterology. 2023;165(2):509-11.e7. https://doi.org/10.1053/j.gastro.2023.04.033
Kubb C, Foran HM. Online health information seeking parents for their children: systematic review and agenda for further research. J Med Internet Res. 2020;22(8):e19985. https://doi.org/10.2196/19985
Estudo Nacional de Alimentação e Nutrição Infantil (ENANI). Aleitamento materno: prevalência e práticas entre crianças brasileiras menores de 2 anos. 4: ENANI - 2019. Rio de Janeiro: UFRJ, 2021.
World Health Organization (WHO). United Nations Children’s Fund (UNICEF). Global Breastfeeding Scorecard, 2019: Increasing commitment to breastfeeding through funding and improved policies and programmes. Geneva: WHO/UNICEF, 2019.
Yeo YH, Samaan JS, Ng WH, Ting PS, Trivedi H, Vipani A, et al. Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma. Clin Mol Hepatol. 2023;29(3):721-32. https://doi.org/10.3350/cmh.2023.0089
Johnson SB, King AJ, Warner EL, Aneja S, Kann BH, Bylund CL. Using ChatGPT to evaluate cancer myths and misconceptions: artificial intelligence and cancer information. JNCI Cancer Spectr. 2023;7(2):pkad015. https://doi.org/10.1093/jncics/pkad015
Roque MC. Amamentação: mitos e verdades. Companhia de Desenvolvimento dos Vales do São Francisco e do Parnaíba – Codevasf, 2022, p. 1-32. Available from: https://www.codevasf.gov.br/acesso-ainformacao/institucional/biblioteca-geraldo-rocha/publicações
Nov O, Singh N, Mann D. Putting ChatGPT's Medical Advice to the (Turing) Test: Survey Study. JMIR Med Educ. 2023;9:e46939. https://doi.org/10.2196/46939
Garg RK, Urs VL, Agarwal AA, Chaudhary SK, Paliwal V, Kar SK. Exploring the role of ChatGPT in patient care (diagnosis and treatment) and medical research: A systematic review. Health Promot Perspect. 2023;13(3):183-91. https://doi.org/10.34172/hpp.2023.22
Figueiredo TC, Ribeiro Neto U. Contribuições da educação em saúde na promoção do aleitamento materno. VI Encontro Internacional de Gestão, Desenvolvimento e Inovação. 2022;6(1):1-6.