Artists' satisfaction with telerehabilitation in physiotherapy during the COVID‐19 pandemic: A cross‐sectional study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: To our knowledge, there is currently no research on telerehabilitation concerning artists. This study aims to assess the feasibility, acceptability, and effectiveness of utilizing video-based telerehabilitation in physiotherapy among artists during the COVID-19 pandemic. METHODS: Fifty-one artists who accessed virtual physiotherapy between November 2020 and February 2022 at a healthcare center that provides specialized healthcare services to artists of all disciplines who reside or work in Ontario, Canada were asked to complete a 26-item online questionnaire about their experience with virtual physiotherapy. RESULTS: The 51 respondents were from a range of artistic disciplines, with the largest portion being musicians (n = 22; 43%). Of the respondents, 86% (n = 44) felt the virtual physiotherapy met their expectations in therapeutic benefits, 78% (n = 40) were confident in performing all the exercises that the physiotherapist demonstrated on the virtual platform, 80% (n = 41) did not run into many technological challenges when booking or attending virtual sessions, and 54% (n = 20) reported similar treatment outcomes between virtual and in-person sessions. Although artists liked the convenience of accessing physiotherapy from home, 53% (n = 17) of respondents rated the lack of physical contact as a major limitation in telerehabilitation. CONCLUSION: Telerehabilitation for artists during the COVID-19 pandemic has shown potential to be an effective and viable alternative to in-person physiotherapy, as demonstrated by high satisfaction levels and comparable treatment outcomes, especially when public health restrictions were in place. Future research can explore hybrid models (mix of in-person and virtual sessions) in physiotherapy to meet the needs for physical contact during sessions.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".