{
  "abstract": "Purpose\n\nParents increasingly consult large language model (LLM) chatbots about pediatric flexible flatfoot, a common condition that rarely requires treatment and in which the clinical task is chiefly communication. We compared four LLMs on the quality, readability, and reproducibility of parent-oriented answers.Methods\n\nThis was a cross-sectional, comparative content analysis of AI-generated text. No patients, clinical records, or human participants were involved; the units of analysis were parent-oriented questions and the chatbot responses they generated. Twenty parent-oriented questions were submitted in triplicate to ChatGPT, Claude, DeepSeek, and Gemini in independent, memory-disabled sessions (240 responses). Two blinded pediatric orthopedic surgeons scored responses (Mika grade, four-point Likert, and a hallucination taxonomy; PEMAT-P, DISCERN, and QUEST on pooled material). Readability used five indices. Between-model differences were tested with Friedman and Dunn-Bonferroni post-hoc tests; agreement and reproducibility used intraclass correlation coefficients (ICC).Results\n\nAll five readability indices differed between models (P < 0.001); none reached the recommended sixth-grade level. DeepSeek was most accessible (FRES 66.3) and ChatGPT least (FRES 17.7). On pooled-material instruments (inter-rater ICC 0.63-0.74), Claude scored highest for understandability (91.6%) and actionability (88.3%). Per-response clinical-quality measures were closely clustered, showed poor inter-rater agreement (ICC -0.01 to +0.07), and did not discriminate. Readability reproducibility across identical queries was moderate (FRES ICC 0.49-0.72).Conclusions\n\nClinical-quality scales did not reliably distinguish the four LLMs, whereas readability differed substantially; none met recommended readability standards, and output was only moderately reproducible. Model choice should be guided by readability and actionability, under clinician oversight.Significance of study\n\nFor a condition managed mainly through parent education, LLM selection should rest on readability and actionability rather than presumed clinical accuracy, with output used under clinician oversight.Level of evidence\n\nV (cross-sectional comparative content analysis of AI-generated text; no human participants).",
  "abstract_shown": true,
  "affiliations": [
    "Department of Orthopaedics and Traumatology, Faculty of Medicine, Gaziantep University, Gaziantep, Türkiye.",
    "Department of Orthopaedics and Traumatology, Faculty of Medicine, Gaziantep Islamic Science and Technology University, Gaziantep, Türkiye.",
    "Department of Orthopaedics and Traumatology, Ministry of Health Aksaray Education and Research Hospital, Aksaray, Türkiye.",
    "Department of Orthopaedics and Traumatology, Ministry of Health Pazarcık State Hospital, Kahramanmaraş, Türkiye."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Erkan Servet"
    },
    {
      "affs": [
        1
      ],
      "name": "Beytullah Unat"
    },
    {
      "affs": [
        2
      ],
      "name": "Musa Alperen Bilgin"
    },
    {
      "affs": [
        3
      ],
      "name": "Çağrı Karabulut"
    },
    {
      "affs": [
        0
      ],
      "name": "Nevzat Gönder",
      "orcid": "0000-0003-0691-1289"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/amnzxkbrewh7h.bib",
  "cited_by": 0,
  "doi": "10.1177/18632521261500230",
  "fulltext_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13716893/?tool=EBI",
  "id": "amnzxkbrewh7h",
  "issns": [
    "1863-2521",
    "1863-2548"
  ],
  "landing_url": "https://europepmc.org/article/PMC/PMC13716893",
  "language": "eng",
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Original Clinical Article"
    ],
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      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
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  ],
  "openalex": "W7224134556",
  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13716893/pdf/?tool=EBI",
  "pmcid": "PMC13716893",
  "pmid": "42959203",
  "published": "2026-10-28",
  "publisher": "SAGE Publications",
  "ris": "https://research.draconitic.com/paper/amnzxkbrewh7h.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T00:20:37Z",
      "native_id": "PMC:PMC13716893",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13716893"
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    {
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      "native_id": "MED:42959203",
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      "native_id": "PMC13716893",
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  "subjects": [
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      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
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  ],
  "title": "Four large language models in parent-oriented education for pediatric flexible flatfoot: Quality, readability, hallucination, and reproducibility",
  "title_text": "Four large language models in parent-oriented education for pediatric flexible flatfoot: Quality, readability, hallucination, and reproducibility",
  "type": "peer-reviewed",
  "updated_at": "2026-11-02T12:21:18Z",
  "url": "https://research.draconitic.com/paper/amnzxkbrewh7h",
  "venue": "Journal of children's orthopaedics",
  "versions": []
}