{
  "abstract": "Objective: To investigate the self-reported understanding and attitudes of healthcare workers and caregivers toward the application of artificial intelligence (AI) in pediatric healthcare in a children’s specialty hospital, and to compare differences between the two groups.\n\nMethods: This single-center cross-sectional questionnaire survey was conducted at Fujian Children’s Hospital from January 2026 to June 2026. A self-designed questionnaire was used to assess healthcare workers’ and caregivers’ self-reported understanding, trust, risk perception, and willingness to accept AI applications in pediatric healthcare. Respondents were divided into groups according to their identity. Categorical variables were compared using the chi-square test or Fisher’s exact test, while continuous variables were compared using the independent-samples t test or the Mann–Whitney U test.\n\nResults: A total of 261 respondents were included, comprising 159 caregivers and 102 healthcare workers. Healthcare workers had a higher level of self-reported understanding and a higher frequency of use of AI applications in pediatric healthcare than caregivers ( p < 0.01); however, they also showed stronger perceptions of data security risks ( p < 0.001). Caregivers reported greater trust in AI-assisted medical decision-making than healthcare workers ( p < 0.001). Most respondents believed that AI could not replace pediatric healthcare workers, with no statistically significant difference between the two groups ( p = 0.166). Regarding potential advantages, healthcare workers were more likely to agree that AI could reduce human error ( p < 0.001). Regarding potential limitations, healthcare workers expressed greater concern about the risks of misdiagnosis, lack of humanistic care, and data privacy and security issues ( p < 0.001).\n\nConclusion: In this single-center children’s specialty hospital, healthcare workers reported greater self-rated understanding and more frequent use of AI, together with stronger awareness of several potential risks, whereas caregivers showed greater trust in AI-assisted medical decision-making despite lower self-rated understanding. These findings should be interpreted cautiously and require confirmation in larger multicenter studies before being generalized to broader populations in China.",
  "abstract_shown": true,
  "affiliations": [
    "Fujian Children’s Hospital (Fujian Branch of Shanghai Children’s Medical Center), College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Si-Yu Chen"
    },
    {
      "affs": [
        0
      ],
      "name": "Li Yang"
    },
    {
      "affs": [
        0
      ],
      "name": "Qi-Gang Ding"
    },
    {
      "affs": [
        0
      ],
      "name": "Dong-Xin Huang"
    },
    {
      "affs": [
        0
      ],
      "name": "Qiu-Yu Tang"
    },
    {
      "affs": [
        0
      ],
      "name": "Xue Kong"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/eq2qp60xtabrc.bib",
  "cited_by": 0,
  "doi": "10.3389/fpubh.2026.1951776",
  "fulltext_url": "https://europepmc.org/articles/PMC13713840",
  "id": "eq2qp60xtabrc",
  "issns": [
    "2296-2565"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fpubh.2026.1951776/full",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Original Research"
    ],
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
    ]
  ],
  "openalex": "W7221767469",
  "pdf_url": "https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2026.1951776/pdf",
  "pmcid": "PMC13713840",
  "pmid": "42952857",
  "published": "2026-10-14",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/eq2qp60xtabrc.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:22Z",
      "native_id": "10.3389/fpubh.2026.1951776",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fpubh.2026.1951776/full"
    },
    {
      "first_seen": "2026-10-31T00:20:41Z",
      "native_id": "MED:42952857",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42952857"
    },
    {
      "first_seen": "2026-11-01T12:21:26Z",
      "native_id": "PMC13713840",
      "source": "pmc",
      "url": "https://doi.org/10.3389/fpubh.2026.1951776"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Self-reported understanding and attitudes of healthcare workers and caregivers toward artificial intelligence in pediatric healthcare in a children’s hospital in China: a cross-sectional study",
  "title_text": "Self-reported understanding and attitudes of healthcare workers and caregivers toward artificial intelligence in pediatric healthcare in a children’s hospital in China: a cross-sectional study",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T12:21:26Z",
  "url": "https://research.draconitic.com/paper/eq2qp60xtabrc",
  "venue": "Frontiers in Public Health",
  "versions": []
}