{
  "abstract": "With the rapid advancement of artificial intelligence (AI) technologies, growing interest has emerged in its potential application in pediatric healthcare. Understanding the factors influencing AI acceptability among parents and clinical staff is an important prerequisite for facilitating its integration in clinical routine. To date, these factors have not been systematically assessed across different stakeholder groups. Here we investigated AI acceptability among parents (first cohort n = 198; second cohort: n = 79) and pediatric health care professionals (n = 33) across different disease, diagnosis or treatment scenarios. The effects of demographic variables and contextual predictors, such as data privacy, AI knowledge and perceived disease severity, on willingness to use AI were evaluated. More liberal data privacy was associated with reduced willingness to use AI (p < .001). A higher perceived disease severity was linked to higher willingness to use AI ({beta} = .10, p = .013) in the second parent group. When AI and clinicians recommendations conflicted, parents were more likely to choose AI over clinicians judgment in treatment compared to diagnosis scenarios. Healthcare professionals showed similar patterns but additionally weighted perceived disease severity when resolving disagreements. These findings highlight the importance of addressing stakeholder concerns regarding disease specific customization, accuracy, data privacy and accountability when introducing AI into pediatric healthcare settings.\n\nHighlightsO_LIParents are more willing to use AI for conditions they perceive as more severe C_LIO_LIData sharing beyond institutional level significantly reduces willingness to use AI C_LIO_LIDigital literacy and previous medical knowledge facilitate tolerance for AI errors C_LIO_LIAI applications are preferred in treatment over diagnosis scenarios C_LIO_LIHuman judgements are prioritized over AI during inconsistent recommendations C_LI",
  "abstract_shown": true,
  "affiliations": [
    "Institute of Neurosciences and Medicine (Brain and Behavior, INM-7), Research Center Juelich, Juelich, Germany"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "F. Lin"
    },
    {
      "name": "A. C. Bischops"
    },
    {
      "name": "J.-L. Kerth"
    },
    {
      "name": "T. Meissner"
    },
    {
      "name": "T. Bruni"
    },
    {
      "name": "S. B. Eickhoff"
    },
    {
      "name": "B. Heinrichs"
    },
    {
      "name": "J. M. Lahnakoskia"
    },
    {
      "name": "J. Dukart"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6ryj00vdqc3zc.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.10.26362703",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.09.10.26362703v1.full",
  "id": "6ryj00vdqc3zc",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.09.10.26362703v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "medical ethics"
    ],
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
    ]
  ],
  "openalex": "W7213275657",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.09.10.26362703v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-10",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6ryj00vdqc3zc.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:31Z",
      "native_id": "10.64898/2026.09.10.26362703",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.09.10.26362703v2"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Acceptability of AI-applications in routine clinical care for children and adolescents: perspectives of parents and healthcare professionals",
  "title_text": "Acceptability of AI-applications in routine clinical care for children and adolescents: perspectives of parents and healthcare professionals",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:42Z",
  "url": "https://research.draconitic.com/paper/6ryj00vdqc3zc",
  "venue": "medRxiv",
  "versions": []
}