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Annals of global health
chatgpt artificial intelligence language model uses natural language processing simulate human conversation seen wide range applications including healthcare education research clinical practice study evaluated accuracy chatgpt providing accurate quality information answer questions myopia series 11 questions nine categories general summary cause symptom onset prevention complication natural history treatment prognosis generated crosssectional study question entered five times fresh chatgpt sessions free influence prior questions responses evaluated fivemember team optometry teaching research staff evaluators individually rated accuracy quality responses likert scale higher score indicated greater quality information 1 poor 2 poor 3 acceptable 4 good 5 good median scores question estimated compared evaluators agreement five evaluators reliability statistics questions estimated 11 questions myopia chatgpt provided good quality information median scores 40 10 questions acceptable responses median scores 30 one question 275 responses total 66 24 rated good 134 49 rated good whereas 60 22 rated acceptable 10 36 rated poor 5 18 rated poor cronbachs 0807 indicated good level agreement test items evaluators ratings demonstrated slight agreement fleisss 0005 significant difference scoring among evaluators kruskalwallis test p 0001 overall chatgpt generated good quality information answer questions myopia although chatgpt shows great potential rapidly providing information myopia presence inaccurate responses demonstrates evaluation awareness concerning limitations crucial avoid potential misinterpretation