{
  "abstract": "Objectives To develop and validate educational clinical vignettes (CVs) based on real-life patients with serious pathology from the disciplines of oncology, internal medicine and orthopaedics that are relevant for physiotherapists (PTs) working in a non-direct access system.Design A mixed-methods study using an iterative design was employed to develop and validate CVs that focused on serious pathology.Setting Academic and clinical settings within health faculties at three universities in Austria and the UK.Participants Medical doctors (MD) (n=3) and PTs (n=4) developed CVs in the disciplines of internal medicine, oncology and orthopaedics. Validation of the CVs was undertaken in three stages: internal validation by the research team (n=7), external validation by MDs (n=3) and external validation by PTs (n=18).Results 25 CVs focusing on internal medicine (9), oncology (8) and orthopaedics (8) were developed. Results of the consensus method of Haute Autorité de Santé ranged between 7 and 9 in the internal validation stage. In the external validation stage with MDs, one orthopaedic CV was excluded, resulting in a final total of 24 validated CVs.Conclusions This is the first time educational CVs have been developed and validated across such a broad range of pathologies for countries without direct access to physiotherapy, for use in the education of PTs. Furthermore, the approach described in the Methods section of this paper may serve as a template in similar future projects.",
  "authors": [
    {
      "affiliations": [
        "Institute of Therapeutic and Midwifery Sciences, Department of Health Sciences, University of Applied Sciences Krems, Krems an der Donau, Lower Austria, Austria"
      ],
      "name": "Wolfgang Lackenbauer"
    },
    {
      "affiliations": [
        "Institute of Therapeutic and Midwifery Sciences, Department of Health Sciences, University of Applied Sciences Krems, Krems an der Donau, Lower Austria, Austria"
      ],
      "name": "Simon Gasselich"
    },
    {
      "affiliations": [
        "Karl Landsteiner University of Health Sciences, Human Medicine, Krems an der Donau, Lower Austria, Austria"
      ],
      "name": "Martina Edda Lickel"
    },
    {
      "affiliations": [
        "University Hospital Tulln, Clinical Department of Orthopaedics and Traumatology, Tulln, Lower Austria, Austria"
      ],
      "name": "Lars Schabel"
    },
    {
      "affiliations": [
        "Institute of Therapeutic and Midwifery Sciences, Department of Health Sciences, University of Applied Sciences Krems, Krems an der Donau, Lower Austria, Austria"
      ],
      "name": "Reinhard Beikircher"
    },
    {
      "affiliations": [
        "Institute of Therapeutic and Midwifery Sciences, Department of Health Sciences, University of Applied Sciences Krems, Krems an der Donau, Lower Austria, Austria"
      ],
      "name": "Christian Keip"
    },
    {
      "affiliations": [
        "Karl Landsteiner University of Health Sciences, Human Medicine, Krems an der Donau, Lower Austria, Austria"
      ],
      "name": "Manfred Wieser"
    },
    {
      "affiliations": [
        "Department of Health Professions, Manchester Metropolitan University, Manchester, England, UK"
      ],
      "name": "James Selfe"
    },
    {
      "affiliations": [
        "Department of Health Professions, Manchester Metropolitan University, Manchester, England, UK"
      ],
      "name": "Bruno Mazuquin"
    },
    {
      "affiliations": [
        "Department of Health Professions, Manchester Metropolitan University, Manchester, England, UK"
      ],
      "name": "Gillian Yeowell"
    },
    {
      "affiliations": [
        "Institute of Therapeutic and Midwifery Sciences, Department of Health Sciences, University of Applied Sciences Krems, Krems an der Donau, Lower Austria, Austria"
      ],
      "name": "Jessie Janssen"
    }
  ],
  "title": "Development and validation of clinical vignettes to inform an educational intervention for physiotherapists to detect serious pathologies: a mixed-methods study",
  "uid": "d152bb2a-0af3-5114-a6b5-b6bbcd66f957"
}