Physiotherapists’ Perspectives Towards Using Telehealth for Acute Concussion Care
Bibliographic record
Abstract
A traumatic brain injury reflects a heterogeneous description. The mildest form has been referred to as that of a concussion, with recent steps being taken to reclassify this as mild traumatic brain injury (mTBI). Management has developed in tandem with the understanding of what mTBI, as have methods that physiotherapists (PTs) may use to provide care. The most recent catalyst to the use of in-person versus virtual healthcare was observed during the COVID-19 pandemic. Despite its use, very little is known regarding the perceptions of the PTs who engaged in this method of care, or whether virtual physiotherapy (VPT) may be continued. The purpose of this basic qualitative study was to explore PTs’ perspectives around the use of VPT in their current practice in adult patients with acute mTBI. A framework that centered around the self-efficacy (SE) of the PT was applied. A single, semi-structured interview involvings nine PTs who were experienced in using VPT with mTBI patients. A study-specific questionnaire was developed to explore the PTs’ perceptions related to their SE, potential barriers, as well as factors affecting future use. The results indicated SE beliefs towards VPT use were related to patient and professional factors, technology, and perceived barriers. Barriers were reported at patient-, PT-, and technological-levels. Factors related to future use of VPT were noted as being both intrinsic and extrinsic. Physiotherapists developed their SE beliefs from a variety of intrinsic and extrinsic sources. This study presented a jumping off point to inform a knowledge gap in which more research is required to evaluate PT perspectives across a greater sample size and diverse population. Further study into the perspectives of other stakeholders may be beneficial to explore related to VPT application.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".