Ghozali Muhammad Thesa
Department of Pharmaceutical Management, School of Pharmacy, Faculty of Medicine and Health Sciences, Universitas Muhammadiyah Yogyakarta.
J Asthma. 2025 Jun;62(6):975-983. doi: 10.1080/02770903.2025.2450482. Epub 2025 Jan 11.
Integrating Artificial Intelligence (AI) into public health education represents a pivotal advancement in medical knowledge dissemination, particularly for chronic diseases such as asthma. This study assesses the accuracy and comprehensiveness of ChatGPT, a conversational AI model, in providing asthma-related information.
Employing a rigorous mixed-methods approach, healthcare professionals evaluated ChatGPT's responses to the Asthma General Knowledge Questionnaire for Adults (AGKQA), a standardized instrument covering various asthma-related topics. Responses were graded for accuracy and completeness and analyzed using statistical tests to assess reproducibility and consistency.
ChatGPT showed notable proficiency in conveying asthma knowledge, with flawless success in the etiology and pathophysiology categories and substantial accuracy in medication information (70%). However, limitations were noted in medication-related responses, where mixed accuracy (30%) highlights the need for further refinement of ChatGPT's capabilities to ensure reliability in critical areas of asthma education. Reproducibility analysis demonstrated a consistent 100% rate across all categories, affirming ChatGPT's reliability in delivering uniform information. Statistical analyses further underscored ChatGPT's stability and reliability.
These findings underscore ChatGPT's promise as a valuable educational tool for asthma while emphasizing the necessity of ongoing improvements to address observed limitations, particularly regarding medication-related information.
将人工智能（AI）整合到公共卫生教育中是医学知识传播的一项关键进展，尤其是对于哮喘等慢性疾病而言。本研究评估了对话式人工智能模型ChatGPT在提供哮喘相关信息方面的准确性和全面性。
采用严格的混合方法，医疗保健专业人员评估了ChatGPT对《成人哮喘常识问卷》（AGKQA）的回答，AGKQA是一种涵盖各种哮喘相关主题的标准化工具。对回答的准确性和完整性进行评分，并使用统计测试进行分析，以评估可重复性和一致性。
ChatGPT在传达哮喘知识方面表现出显著的熟练程度，在病因和病理生理学类别中取得了完美的成功，在药物信息方面具有较高的准确性（70%）。然而，在与药物相关的回答中发现了局限性，其中混合准确性（30%）突出表明需要进一步完善ChatGPT的能力，以确保在哮喘教育的关键领域具有可靠性。可重复性分析表明所有类别中的一致率为100%，肯定了ChatGPT在提供统一信息方面的可靠性。统计分析进一步强调了ChatGPT的稳定性和可靠性。
这些发现强调了ChatGPT作为哮喘有价值的教育工具的前景，同时强调了持续改进以解决观察到的局限性的必要性，特别是关于与药物相关的信息。
