Development and validation of clinical vignettes to inform an educational intervention for physiotherapists to detect serious pathologies: a mixed-methods study Article Swipe
Wolfgang Lackenbauer
,
Simon Gasselich
,
Martina Edda Lickel
,
Lars Schabel
,
Reinhard Beikircher
,
Christian Keip
,
Manfred Wieser
,
James Selfe
,
Bruno Mazuquin
,
Gillian Yeowell
,
Jessie Janssen
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1136/bmjopen-2024-097107
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1136/bmjopen-2024-097107
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.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1136/bmjopen-2024-097107
- OA Status
- gold
- Cited By
- 1
- References
- 62
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413327512
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413327512Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1136/bmjopen-2024-097107Digital Object Identifier
- Title
-
Development and validation of clinical vignettes to inform an educational intervention for physiotherapists to detect serious pathologies: a mixed-methods studyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-08-01Full publication date if available
- Authors
-
Wolfgang Lackenbauer, Simon Gasselich, Martina Edda Lickel, Lars Schabel, Reinhard Beikircher, Christian Keip, Manfred Wieser, James Selfe, Bruno Mazuquin, Gillian Yeowell, Jessie JanssenList of authors in order
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https://doi.org/10.1136/bmjopen-2024-097107Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1136/bmjopen-2024-097107Direct OA link when available
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Medicine, Intervention (counseling), Health services research, Biostatistics, Public health, Medical education, Nursing, Family medicine, Physical therapyTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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62Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Participants | 73 |
| abstract_inverted_index.orthopaedics | 24, 130 |
| abstract_inverted_index.universities | 67 |
| abstract_inverted_index.mixed-methods | 39 |
| abstract_inverted_index.orthopaedics. | 91 |
| abstract_inverted_index.physiotherapy, | 201 |
| abstract_inverted_index.physiotherapists | 29 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 11 |
| citation_normalized_percentile.value | 0.91521395 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |