{
  "abstract": "Objectives\n\nGenerative artificial intelligence (GenAI) is increasingly explored in healthcare, yet its potential to support care at home remains largely unexamined. In paediatric rheumatology, where families frequently undertake complex tasks to manage treatment plans between appointments, safe and effective guidance is essential. The aim of the current study was to understand healthcare professionals' (HCPs') views on adopting GenAI tools to help families manage their child's care.Methods\n\nUtilising a vignette-based methodology, paediatric rheumatology HCPs were invited to focus groups and presented with 3 hypothetical scenarios: (1) injection administration, (2) flare assessment, and (3) physiotherapy exercises. Following the principles outlined by Braun and Clarke, data were analysed using thematic analysis.Results\n\nA total of 37 HCPs from the wider multidisciplinary team from 14 different hospitals participated in this study. Six main themes were identified: (1) opportunities of GenAI to benefit patient care; (2) disadvantages and challenges; (3) risks, safety netting, and evaluation; (4) different approaches of utilising GenAI; (5) role of HCPs in the world of GenAI; and (6) ensuring inclusivity and accessibility.Conclusions\n\nHCPs recognised opportunities for how GenAI could support caregivers in managing their child's healthcare or young people's self-management, particularly through guidance support rather than clinical interpretation. However, concerns were raised regarding the accuracy, reliability, privacy, and data governance of currently existing GenAI tools. The perspectives of HCPs are critical to ensuring that the application of GenAI in healthcare aligns with clinical expectations, ethical standards, regulatory processes, and the needs of patients and families.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Paediatric Rheumatology, Great Ormond Street Hospital National Health Service (NHS) Foundation Trust, London, UK.",
    "University College London (UCL) Great Ormond Street Institute of Child Health, Infection, Immunity, and Inflammation Research and Teaching Department, University College London, London, UK.",
    "National Institute for Health and Care Research (NIHR) Great Ormond Street Hospital Biomedical Research Centre, UCL Great Ormond Street Institute of Child Health, London, UK.",
    "UCL Interaction Centre, Department of Computer Science and Division of Psychology and Language Sciences, University College London, London, UK."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Klaudia H Kupiec"
    },
    {
      "affs": [
        3
      ],
      "name": "Sabina Sweet"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Sandrine Compeyrot-Lacassagne"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Polly Livermore"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7pe9rxspps4z1.bib",
  "cited_by": 0,
  "doi": "10.1016/j.ero.2026.100258",
  "fulltext_url": "https://europepmc.org/articles/PMC13695108",
  "id": "7pe9rxspps4z1",
  "issns": [
    "3050-7081"
  ],
  "landing_url": "https://europepmc.org/article/MED/42926939",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
    ]
  ],
  "openalex": "W7222973562",
  "pdf_url": "https://europepmc.org/articles/PMC13695108?pdf=render",
  "pmcid": "PMC13695108",
  "pmid": "42926939",
  "published": "2026-10-19",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7pe9rxspps4z1.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:18Z",
      "native_id": "MED:42926939",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42926939"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "'Let's work alongside it': healthcare professionals' perspectives of generative AI in supporting care at home in paediatric rheumatology.",
  "title_text": "'Let's work alongside it': healthcare professionals' perspectives of generative AI in supporting care at home in paediatric rheumatology.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:21:18Z",
  "url": "https://research.draconitic.com/paper/7pe9rxspps4z1",
  "venue": "EULAR rheumatology open",
  "versions": []
}