Alharbi Layan Yousef, Alrashoud Rema Rashed, Alotaibi Bader Shabib, Al Dera Abdulaziz Meshal, Alajlan Raghad Saleh, AlHuthail Reem Rashed, Alessa Dalal Ibrahim
College of Medicine, Imam Mohammad Ibn Saud Islamic University (IMSIU), Prince Mohammed Ibn Salman Ibn Abdulaziz Road , Riyadh 13318 , Saudi Arabia, Riyadh, Saudi Arabia, SA.
Department of Ophthalmology, College Of Medicine, Imam Mohammad Ibn Saud Islamic University(IMSIU), Riyadh, Saudi Arabia, SA.
JMIR Form Res. 2025 Jun 30. doi: 10.2196/73642.
Background: Chemical ocular injuries are a major public health issue. They cause eye damage from harmful chemicals and can lead to severe vision loss or blindness if not treated promptly and effectively. Although medical knowledge has advanced, accessing reliable and understandable information on these injuries remains a challenge. This is due to unverified online content and complex terminology. Artificial Intelligence (AI) tools like ChatGPT provide a promising solution by simplifying medical information and making it more accessible to the general public.
Objective: This study aims to assess the use of ChatGPT in providing reliable, accurate, and accessible medical information on chemical ocular injuries. It evaluates the correctness, thematic accuracy, and coherence of ChatGPT's responses compared to established medical guidelines and explores its potential for patient education.
Methods: Nine questions were entered to ChatGPT regarding various aspects of chemical ocular injuries. These included the definition, prevalence, etiology, prevention, symptoms, diagnosis, treatment, follow-up, and complications. The responses provided by ChatGPT were compared to the ICD-9 and ICD-10 guidelines for chemical (alkali and acid) injuries of the conjunctiva and cornea. The evaluation focused on criteria such as correctness, thematic accuracy, coherence to assess the accuracy of ChatGPT's responses. The inputs were categorized into three distinct groups, and statistical analyses, including Flesch-Kincaid readability tests, ANOVA, and trend analysis, were conducted to assess their readability, complexity and trends.
Results: The results showed that ChatGPT provided accurate and coherent responses for most questions about chemical ocular injuries, demonstrating thematic relevance. However, the responses sometimes overlooked critical clinical details or guideline-specific elements, such as emphasizing the urgency of care, using precise classification systems, and addressing detailed diagnostic or management protocols. While the answers were generally valid, they occasionally included less relevant or overly generalized information. This reduced their consistency with established medical guidelines. The average FRES was 33.84 ± 2.97, indicating a fairly challenging reading level, while the FKGL averaged 14.21 ± 0.97, suitable for readers with college-level proficiency. Passive voice was used in 7.22% ± 5.60% of sentences, indicating moderate reliance. Statistical analysis showed no significant differences in FRES (p = .385), FKGL (p = .555), or passive sentence usage (p = .601) across categories, as determined by one-way ANOVA. Readability remained relatively constant across the three categories, as determined by trend analysis.
Conclusions: ChatGPT shows strong potential in providing accurate and relevant information about chemical ocular injuries. However, its language complexity may prevent accessibility for individuals with lower health literacy and sometimes miss critical aspects. Future improvements should focus on enhancing readability, increasing context-specific accuracy, and tailoring responses to person needs and literacy levels.
This is not RCT.
化学性眼外伤是一个重大的公共卫生问题。它们由有害化学物质导致眼部损伤，如果不及时有效治疗，可能会导致严重视力丧失或失明。尽管医学知识不断进步，但获取有关这些损伤的可靠且易懂的信息仍然是一项挑战。这是由于网上内容未经核实以及术语复杂所致。像ChatGPT这样的人工智能工具通过简化医学信息并使其更易于公众获取，提供了一个有前景的解决方案。
本研究旨在评估ChatGPT在提供有关化学性眼外伤的可靠、准确且可获取的医学信息方面的应用。它将ChatGPT的回答与既定医学指南进行比较，评估其正确性、主题准确性和连贯性，并探索其在患者教育方面的潜力。
就化学性眼外伤的各个方面向ChatGPT输入了九个问题。这些问题包括定义、患病率、病因、预防、症状、诊断、治疗、随访和并发症。将ChatGPT提供的回答与用于结膜和角膜化学（碱和酸）损伤的ICD - 9和ICD - 10指南进行比较。评估集中在正确性、主题准确性、连贯性等标准上，以评估ChatGPT回答的准确性。输入被分为三个不同的组，并进行了统计分析，包括弗莱什 - 金凯德可读性测试、方差分析和趋势分析，以评估其可读性、复杂性和趋势。
结果表明，ChatGPT对大多数关于化学性眼外伤的问题提供了准确且连贯的回答，显示出主题相关性。然而，回答有时会忽略关键的临床细节或特定指南的要素，例如强调护理的紧迫性、使用精确的分类系统以及处理详细的诊断或管理方案。虽然答案总体上是有效的，但它们偶尔会包含不太相关或过于笼统的信息。这降低了它们与既定医学指南的一致性。平均弗莱什阅读简易度得分（FRES）为33.84 ± 2.97，表明阅读水平颇具挑战性，而弗莱什 - 金凯德年级水平得分（FKGL）平均为14.21 ± 0.97，适合大学水平的读者。7.22% ± 5.60%的句子使用了被动语态，表明有一定程度的依赖。单向方差分析确定，各类别在FRES（p = 0.385）、FKGL（p = 0.55）或被动句使用（p = 0.601）方面无显著差异。趋势分析确定，三个类别之间的可读性保持相对稳定。
ChatGPT在提供有关化学性眼外伤的准确且相关信息方面显示出强大潜力。然而，其语言复杂性可能会使健康素养较低的人难以获取信息，并且有时会遗漏关键方面。未来的改进应侧重于提高可读性、增强特定情境的准确性以及根据个人需求和素养水平调整回答。
本研究非随机对照试验。
