Brian M Doornenbal, Tim van Zutphen, Lise F E Beumeler, Rimke C Vos, Mark Derks, Hinke Haisma, M Elske van den Akker-van Marle, Jessica C Kiefte-de Jong
Development and validation of a Context-sensitive Positive Health Questionnaire (CPHQ): A factor analysis and multivariate regression study
Journal of patient-reported outcomes
amyloidosis rare multisystem condition often requires complex multidisciplinary care low prevalence underscores importance efforts ensure availability highquality patient education materials better outcomes chatgpt openai large language model powered artificial intelligence offers potential avenue disseminating accurate reliable accessible educational resources patients providers userfriendly interface engaging conversational responses capability users ask followup questions make promising future tool delivering accurate tailored information patients performed multidisciplinary assessment accuracy reproducibility readability chatgpt answering questions related amyloidosis total 98 amyloidosis questions related cardiology gastroenterology neurology curated medical societies institutions amyloidosis facebook support groups inputted chatgpt35 chatgpt4 cardiology gastroenterologyrelated responses independently graded boardcertified cardiologist gastroenterologist respectively specialize amyloidosis 2 reviewers rg dck also graded general questions disagreements resolved discussion neurologyrelated responses graded boardcertified neurologist aah specializes amyloidosis reviewers used following grading scale 1 comprehensive 2 correct inadequate 3 correct incorrect 4 completely incorrect questions stratified categories analysis reproducibility assessed inputting question twice model readability chatgpt4 responses also evaluated using textstat library python python software foundation textstat readability package r software r foundation statistical computing chatgpt4 n98 provided 93 95 responses accurate information 82 84 comprehensive chatgpt35 n83 provided 74 89 responses accurate information 66 79 comprehensive examined question category chatgtp4 chatgpt35 provided 53 95 48 86 comprehensive responses respectively general questions n56 examined subject chatgpt4 chatgpt35 performed best response cardiology questions n12 models producing 10 83 comprehensive responses gastroenterology n15 chatgpt4 received comprehensive grades 9 60 responses chatgpt35 provided 8 53 responses overall 96 98 98 responses chatgpt4 73 83 88 chatgpt35 reproducible readability chatgpt4s responses ranged 10th beyond graduate us grade levels average 155 sd 19 large language models promising tool accurate reliable health information patients living amyloidosis however chatgpts responses exceeded american medical associations recommended fifth sixthgrade reading level future studies focusing improving response accuracy readability warranted prior widespread implementation technologys limitations ethical implications must explored ensure patient safety equitable implementation