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      Assessing the utility of ChatGPT as an artificial intelligence‐based large language model for information to answer questions on myopia

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          Abstract

          Purpose

          ChatGPT is an artificial intelligence language model, which uses natural language processing to simulate human conversation. It has seen a wide range of applications including healthcare education, research and clinical practice. This study evaluated the accuracy of ChatGPT in providing accurate and quality information to answer questions on myopia.

          Methods

          A series of 11 questions (nine categories of general summary, cause, symptom, onset, prevention, complication, natural history, treatment and prognosis) were generated for this cross‐sectional study. Each question was entered five times into fresh ChatGPT sessions (free from influence of prior questions). The responses were evaluated by a five‐member team of optometry teaching and research staff. The evaluators individually rated the accuracy and quality of responses on a Likert scale, where a higher score indicated greater quality of information (1: very poor; 2: poor; 3: acceptable; 4: good; 5: very good). Median scores for each question were estimated and compared between evaluators. Agreement between the five evaluators and the reliability statistics of the questions were estimated.

          Results

          Of the 11 questions on myopia, ChatGPT provided good quality information (median scores: 4.0) for 10 questions and acceptable responses (median scores: 3.0) for one question. Out of 275 responses in total, 66 (24%) were rated very good, 134 (49%) were rated good, whereas 60 (22%) were rated acceptable, 10 (3.6%) were rated poor and 5 (1.8%) were rated very poor. Cronbach's α of 0.807 indicated good level of agreement between test items. Evaluators' ratings demonstrated ‘slight agreement’ (Fleiss's κ, 0.005) with a significant difference in scoring among the evaluators (Kruskal–Wallis test, p < 0.001).

          Conclusion

          Overall, ChatGPT generated good quality information to answer questions on myopia. Although ChatGPT shows great potential in rapidly providing information on myopia, the presence of inaccurate responses demonstrates that further evaluation and awareness concerning its limitations are crucial to avoid potential misinterpretation.

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          Most cited references32

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          The Measurement of Observer Agreement for Categorical Data

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            Global Prevalence of Myopia and High Myopia and Temporal Trends from 2000 through 2050.

            Myopia is a common cause of vision loss, with uncorrected myopia the leading cause of distance vision impairment globally. Individual studies show variations in the prevalence of myopia and high myopia between regions and ethnic groups, and there continues to be uncertainty regarding increasing prevalence of myopia.
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              Effect of Time Spent Outdoors at School on the Development of Myopia Among Children in China: A Randomized Clinical Trial.

              Myopia has reached epidemic levels in parts of East and Southeast Asia. However, there is no effective intervention to prevent the development of myopia.
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                Author and article information

                Contributors
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                Journal
                Ophthalmic and Physiological Optics
                Ophthalmic Physiologic Optic
                Wiley
                0275-5408
                1475-1313
                November 2023
                July 21 2023
                November 2023
                : 43
                : 6
                : 1562-1570
                Affiliations
                [1 ] School of Optometry, College of Health and Life Sciences Aston University Birmingham UK
                Article
                10.1111/opo.13207
                37476960
                4acd9a2c-58f8-46d5-9e1c-198fc8bcb1d1
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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