{
  "abstract": "Collecting data on signs and symptoms of neurological disorders requires extensive resources, limiting feasibility. This study reports on the NeuroEpiTool, a digital tool designed to facilitate data collection in neuroepidemiological studies. Eighty participants (47.5% female, n = 38) with and without neurological disorders were evaluated using the NeuroEpiTool. Inter-rater reliability was assessed between two health professionals using the tool. Additionally, convergent validity and usability were explored. Moderate to strong inter-rater agreement was observed across most neurological tests. The 30-s chair stand test, though not typically part of a standard neurological exam, showed one of the highest agreement levels (κ = 0.82, p < 0.001). Feedback from physicians suggested that the NeuroEpiTool closely resembled a standard neurological examination. Usability had an average of 81.88 ± 10.87. Inter-rater reliability scores support the potential for data collection by non-experts. Future studies should pursue large-scale validation and real-world implementation to support electronic health (eHealth) solutions in neuroepidemiology.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "Article",
  "arxiv": null,
  "author_total": 16,
  "authors": [
    {
      "name": "Vasco Ribeiro Ferreira",
      "orcid": "0000-0001-7060-9733"
    },
    {
      "name": "Stefan Malinovski"
    },
    {
      "name": "Zara Belcheva"
    },
    {
      "name": "Dogukan Tuna"
    },
    {
      "name": "Wieke Bouwes",
      "orcid": "0009-0006-1747-9486"
    },
    {
      "name": "Paolo Ragonese",
      "orcid": "0000-0003-2516-1567"
    },
    {
      "name": "Richard Houeze"
    },
    {
      "name": "Francesca Madonia"
    },
    {
      "name": "Irene Assessou"
    },
    {
      "name": "Fadi Mohsen"
    },
    {
      "name": "Pierre-Marie Preux"
    },
    {
      "name": "Dieu Donné Gnonlonfoun"
    },
    {
      "name": "Constant Kodjo Adjien"
    },
    {
      "name": "Tim van Zutphen"
    },
    {
      "name": "Esther Metting"
    },
    {
      "name": "Valentina Gallo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4pkn4pywqgzn4.bib",
  "cited_by": 0,
  "doi": "10.1016/j.isci.2026.117977",
  "fulltext_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13722562/?tool=EBI",
  "id": "4pkn4pywqgzn4",
  "issns": [
    "2589-0042"
  ],
  "landing_url": "https://www.cell.com/iscience/fulltext/S2589-0042(26)03360-2",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Article"
    ],
    [
      "heading",
      "Health sciences"
    ],
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      "heading",
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    ],
    [
      "heading",
      "Medical specialty"
    ],
    [
      "heading",
      "Medicine"
    ],
    [
      "heading",
      "Neurology"
    ],
    [
      "heading",
      "Public health"
    ],
    [
      "openalex",
      "2613|Statistical Methods in Epidemiology"
    ]
  ],
  "openalex": "W7223448346",
  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13722562/pdf/?tool=EBI",
  "pmcid": "PMC13722562",
  "pmid": "42966922",
  "published": "2026-10-24",
  "publisher": "Elsevier BV",
  "ris": "https://research.draconitic.com/paper/4pkn4pywqgzn4.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:16Z",
      "native_id": "10.1016/j.isci.2026.117977",
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      "url": "https://www.cell.com/iscience/fulltext/S2589-0042(26)03360-2"
    },
    {
      "first_seen": "2026-10-30T12:17:49Z",
      "native_id": "10.1016/j.isci.2026.117977",
      "source": "crossref",
      "url": "https://linkinghub.elsevier.com/retrieve/pii/S2589004226033602"
    },
    {
      "first_seen": "2026-11-02T03:21:51Z",
      "native_id": "PMC:PMC13722562",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13722562"
    },
    {
      "first_seen": "2026-11-04T12:21:21Z",
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      "source": "pmc",
      "url": "https://doi.org/10.1016/j.isci.2026.117977"
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  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "heading:Public health",
      "subfield": "epidemiology-public-health"
    },
    {
      "field": "medicine",
      "origin": "heading:Neurology",
      "subfield": "neurology"
    }
  ],
  "title": "The NeuroEpiTool—A digital tool to ascertain neurological outcomes in population-based studies",
  "title_text": "The NeuroEpiTool—A digital tool to ascertain neurological outcomes in population-based studies",
  "type": "peer-reviewed",
  "updated_at": "2026-11-04T12:21:21Z",
  "url": "https://research.draconitic.com/paper/4pkn4pywqgzn4",
  "venue": "iScience",
  "versions": []
}