ArticleHealth science reports2026
Text-to-Video Generative Artificial Intelligence in Pediatrics: Potential Applications, Ethical Considerations, and Future Directions.
Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
1 author.
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Abstract
Background: Text-to-video (T2V) generative artificial intelligence (AI) models can produce short videos from natural-language prompts, creating new opportunities for medical visualization and communication. In pediatrics, visual explanations and preparatory media are already used to support learning and to reduce distress during procedures; however, current T2V systems (including proprietary models such as OpenAI's Sora) have not been clinically validated for routine pediatric care. Objective: To provide a forward-looking perspective on how T2V generative AI could be used in pediatric education, patient and caregiver communication, and simulation, while clearly distinguishing current evidence from hypothetical applications. Approach: We performed a narrative (nonsystematic) review of the literature on (i) generative AI and T2V models in healthcare and (ii) pediatric video-based education, procedural preparation, and digital distraction (PubMed and Google Scholar; search through June 2025; representative keywords included "pediatric" AND "video-based education," "procedural preparation," "anxiety," "pain," and "simulation"). Key Points: Potential applications include scenario-based training videos for clinicians, tailored educational animations for families, and child-friendly preparatory videos to reduce anxiety and pain. Key limitations and risks include inaccurate or oversimplified content, bias, privacy and data-governance concerns, unclear accountability, commercialization pressures, and inequitable access. Pediatric-specific safeguards (transparent disclosure, clinician review, age-appropriate design, consent/assent practices, and equity planning) are essential. Conclusion: T2V generative AI should be framed as an experimental adjunct rather than a near-term clinical solution. Rigorous validation, governance, and equity-focused implementation strategies are needed before pediatric deployment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.