ArticleSpine deformity2025
Patient education strategies in pediatric orthopaedics: using ChatGPT to answer frequently asked questions on scoliosis.
Article in Spine deformity, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Scoping review: artificial intelligence in patient education for scoliosis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Review
- An expert-led benchmark using common patient questions: evaluating large language models for adolescent idiopathic scoliosis education.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Use of Generative Artificial Intelligence in the Management of Low Back Pain: a Scoping Review.Journal of medical systems · 2026Article
- Large language models for automated and audience-tailored labeling of latent classes.JAMIA open · 2026Article
- Evaluating large language models as tools for public health education on scoliosis.Frontiers in public health · 2026Article
- Assessing large language model responses to pediatric depression FAQs: a cross-sectional study on readability, accuracy, and sentiment.Frontiers in psychiatry · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposePatients increasingly rely on online resources to better understand their health conditions. ChatGPT could satisfy the demand for reliable and accessible online health education resources, yet few studies have applied this to pediatric orthopaedic counseling. This study quantifies the accuracy and comprehensibility of ChatGPT responses to frequently asked questions (FAQs) regarding scoliosis.
methodsTwelve FAQs regarding scoliosis were compiled following a literature review, and ChatGPT Version 3.5 was utilized to answer them. The responses were analyzed for accuracy and clarity using the Mika et al. scoring system and modified DISCERN score in collaboration with two fellowship-trained pediatric orthopaedic surgeons. Readability was assessed using several published educational-level indices.
resultsThe ChatGPT responses received a Mika et al. average of 2.4 (satisfactory requiring minimal to moderate clarification) and an averaged mean DISCERN score of 45.9. The estimated reading level necessary for comprehension ranged from 11
conclusionsWhen prompted with 12 scoliosis FAQs, ChatGPT produces responses of satisfactory accuracy but require further clarification and are written at an inappropriately high reading level for the scoliosis patient population. Future research should explore strategies to verify the reliability of AI services for counseling on other pediatric orthopaedic conditions.
Indexed as
Identifiers
40186826What OpenQuestion holds
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 OpenQuestion graph.