What is the role of advanced physiotherapy practice for adults in urgent care and emergency department settings? A scoping review protocol.
Bibliographic record
Abstract
Introduction: The Advanced Practice Physiotherapy (APP)bmodel of care is implemented internationally, with notable variations in its application across different healthcare systems. Nonetheless, APP has been shown as a means of mitigating against emergency department (ED) crowding and reducing pressure on EDs. This protocol outlines the methods in conducting a scoping review to identify the extent of APP roles in urgent care and ED settings, their expertise levels, the profile of patients they treat and the components of care they provide. Methods: This scoping review will be conducted in line with the Joanna Briggs Institute framework for scoping reviews. The Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for scoping reviews (PRISMA-ScR) will be used to guide the reporting of this review. This review will include published studies of any design that are focussed on APP assessment and/ or subsequent treatment in the ED or urgent care setting among adults. The electronic databases: Medline (Ovid), Pubmed, CINAHL Complete, EMBASE, Epistemonikos, Central Register of Controlled Trials in the Cochrane Library and Scopus, trial registries and grey literature databases will be searched. The reference list of included sources of evidence in the review will be searched for additional sources. The methodological quality of the studies will not be formally explored. Relevant data will be extracted from each article using a predefined data extraction form by two independent reviewers. Data synthesis will be derived from the 'PCC' framework (population, concept, and context). Conclusions: This scoping review will serve to characterise the roles, responsibilities, levels of expertise and the specific components of care that APP offers in urgent and emergency care settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".