{"title":"简短的研究文章：人工智能语言模型在精神病患者教育中的评估。","authors":"Aditya Sathe, Harish Chikanna","doi":"10.1111/camh.70000","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The incorporation of artificial intelligence (AI) and machine learning (ML) into medicine has enhanced clinical information processing. ChatGPT, an AI language model, has demonstrated proficiency in generating human-like responses to complex medical queries. This study explores ChatGPT's potential to instruct parents on behavioral parent training (BPT) for managing attention-deficit hyperactivity disorder (ADHD) in children.</p><p><strong>Methods: </strong>ChatGPT was prompted with three parent-focused questions regarding BPT for ADHD. An ADHD-specialized psychiatrist reviewed the model's responses to assess clarity, accuracy, and clinical relevance.</p><p><strong>Results: </strong>ChatGPT provided responses that were easy to understand and included actionable behavioral strategies. The answers referenced professional literature; however, some references were outdated. Limitations were noted in the specificity and depth of the information provided.</p><p><strong>Conclusion: </strong>AI tools like ChatGPT show promise as supplementary resources in patient education and caregiver support. While helpful, current limitations-particularly in depth and reference accuracy-indicate a need for refinement to maximize their effectiveness in clinical communication and patient management contexts.</p>","PeriodicalId":49291,"journal":{"name":"Child and Adolescent Mental Health","volume":" ","pages":""},"PeriodicalIF":6.8000,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Short Research Article: Evaluation of an artificial intelligence language model in psychiatric patient education.\",\"authors\":\"Aditya Sathe, Harish Chikanna\",\"doi\":\"10.1111/camh.70000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The incorporation of artificial intelligence (AI) and machine learning (ML) into medicine has enhanced clinical information processing. ChatGPT, an AI language model, has demonstrated proficiency in generating human-like responses to complex medical queries. This study explores ChatGPT's potential to instruct parents on behavioral parent training (BPT) for managing attention-deficit hyperactivity disorder (ADHD) in children.</p><p><strong>Methods: </strong>ChatGPT was prompted with three parent-focused questions regarding BPT for ADHD. An ADHD-specialized psychiatrist reviewed the model's responses to assess clarity, accuracy, and clinical relevance.</p><p><strong>Results: </strong>ChatGPT provided responses that were easy to understand and included actionable behavioral strategies. The answers referenced professional literature; however, some references were outdated. Limitations were noted in the specificity and depth of the information provided.</p><p><strong>Conclusion: </strong>AI tools like ChatGPT show promise as supplementary resources in patient education and caregiver support. While helpful, current limitations-particularly in depth and reference accuracy-indicate a need for refinement to maximize their effectiveness in clinical communication and patient management contexts.</p>\",\"PeriodicalId\":49291,\"journal\":{\"name\":\"Child and Adolescent Mental Health\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2025-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Child and Adolescent Mental Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/camh.70000\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PEDIATRICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Child and Adolescent Mental Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/camh.70000","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PEDIATRICS","Score":null,"Total":0}
Short Research Article: Evaluation of an artificial intelligence language model in psychiatric patient education.
Background: The incorporation of artificial intelligence (AI) and machine learning (ML) into medicine has enhanced clinical information processing. ChatGPT, an AI language model, has demonstrated proficiency in generating human-like responses to complex medical queries. This study explores ChatGPT's potential to instruct parents on behavioral parent training (BPT) for managing attention-deficit hyperactivity disorder (ADHD) in children.
Methods: ChatGPT was prompted with three parent-focused questions regarding BPT for ADHD. An ADHD-specialized psychiatrist reviewed the model's responses to assess clarity, accuracy, and clinical relevance.
Results: ChatGPT provided responses that were easy to understand and included actionable behavioral strategies. The answers referenced professional literature; however, some references were outdated. Limitations were noted in the specificity and depth of the information provided.
Conclusion: AI tools like ChatGPT show promise as supplementary resources in patient education and caregiver support. While helpful, current limitations-particularly in depth and reference accuracy-indicate a need for refinement to maximize their effectiveness in clinical communication and patient management contexts.
期刊介绍：
Child and Adolescent Mental Health (CAMH) publishes high quality, peer-reviewed child and adolescent mental health services research of relevance to academics, clinicians and commissioners internationally. The journal''s principal aim is to foster evidence-based clinical practice and clinically orientated research among clinicians and health services researchers working with children and adolescents, parents and their families in relation to or with a particular interest in mental health. CAMH publishes reviews, original articles, and pilot reports of innovative approaches, interventions, clinical methods and service developments. The journal has regular sections on Measurement Issues, Innovations in Practice, Global Child Mental Health and Humanities. All published papers should be of direct relevance to mental health practitioners and clearly draw out clinical implications for the field.
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