Physiotherapy experiences of injured immigrant workers in Quebec: an intersectional perspective
Bibliographic record
Abstract
PURPOSE: Immigrant workers are more likely to suffer work-related injuries compared to native-born Canadians. Their physical rehabilitation usually involves physiotherapy. This study sought to better understand the experiences of injured immigrant workers receiving compensation and physiotherapy treatments. MATERIALS AND METHODS: We conducted a qualitative study using an interpretive descriptive methodology. Semi-structured interviews were completed with 10 compensated immigrant workers about the physiotherapy services they received. Transcripts were analyzed thematically and with an intersectional lens. RESULTS: Two major themes were identified: 1) complex pathways to physiotherapy, and 2) key pillars of physiotherapy experiences. The first theme demonstrates that a lack of familiarity with the health and compensation systems, delayed access to physiotherapy, and cumulative burdens complicate the care of immigrant workers. The second theme shows that moral/emotional support, pain relief, and the recognition of sociocultural beliefs and fears are key aspects to improving the experiences of care for these workers. CONCLUSIONS: This study offers new insights into physiotherapy in the context of a work injury, which may help physiotherapists adapt care to the complex needs of immigrant workers. The intersectional lens used in the analysis offers interesting ways of accounting for the multiple social identities of these workers.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".