Assessing the Effectiveness of Artificial Intelligence in Educating Pediatric Patients: A Comparative Cross-Sectional Analysis
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By
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Ellaha Haidar
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Alice Ruan
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September 25, 2026
Clinical Report: Assessing the Effectiveness of Artificial Intelligence in Educating Pediatric Patients
Overview
This study evaluates the readability and quality of health information produced by AI chatbots compared to NHS leaflets for pediatric ophthalmological conditions.
Background
This study specifically addresses the effectiveness of AI chatbots in producing educational materials for pediatric patients.
Data Highlights
| Source | Flesch-Kincaid Grade Level (FKGL) | Flesch Reading Ease (FRE) | EQIP Score |
|---|---|---|---|
| NHS Leaflets | 4.1 (SD 0.90) | 74.8 (SD 6.74) | 69.61 (SD 4.74) |
| ChatGPT | 7.5 (SD 1.81) | 57.7 (SD 11.36) | 58.26 (SD 3.35) |
| DeepSeek | 9.2 (SD 1.02) | 48.1 (SD 5.01) | 56.75 (SD 4.73) |
Key Findings
- NHS materials had the lowest required reading grade (mean 4.1).
- ChatGPT and DeepSeek required higher reading levels (mean 7.5 and 9.2, respectively).
- NHS leaflets achieved the recommended FRE benchmark score, while AI outputs did not.
- Information quality was higher in NHS materials compared to AI-generated content.
- AI-generated materials lacked citations and visual aids.
- Timeliness of AI content delivery was noted as an advantage.
Clinical Implications
Healthcare professionals should be aware of the limitations of AI-generated educational materials, particularly regarding readability and quality.
Conclusion
This study highlights the limitations of AI in producing accessible and high-quality patient education materials.
Related Resources & Content
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- Frontiers in Psychiatry, 2026 -- A Comparative Cross-Sectional Study Assessing the Diagnostic Accuracy of AI Platforms for Identifying Autism Spectrum Disorder
- Intensive Care Medicine -- Advancing AI from Development to Clinical Application: A Comprehensive Review of Its Implementation in Neonatal and Pediatric Intensive Care Units
- Frontiers in Digital Health, 2026 -- Artificial intelligence in rehabilitation: a review of clinical effectiveness, real-world performance, safety, and equity across modalities and settings
- Beyond screen time: Policy discusses how to approach immersive digital ecosystem | AAP News
- Ethics and governance of artificial intelligence for health: Guidance on large multi-modal models
- https://assets.cureus.com/uploads/original_article/pdf/489012/20260507-63456-cuh4vr.pdf
- Exploring artificial intelligence chatbots in pediatric fluoride education: a cross-sectional study | Scientific Reports
- Performance of three large language models in answering parent-focused questions on rickets: a dual pediatric–orthopedic specialist evaluation | BMC Pediatrics | Springer Nature Link
Based on findings from:
Evaluating the efficacy of artificial intelligence as a patient education tool in paediatric care: a cross-sectional comparative study
Ellaha Haidar, Alice Ruan. Bmj Paediatrics Open, 2026.
https://bmjpaedsopen.bmj.com/content/10/1/e004890
This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.
