From Crisis to Opportunity: A Qualitative Study on Rehabilitation Therapists’ Experiences and Post-Pandemic Perspectives
Bibliographic record
Abstract
Rehabilitation therapists (RTs) have developed substantial mental health problems since the pandemic. Our study aimed to understand the experience of COVID-19 on occupational therapists and physiotherapists practicing in Canada, how the pandemic may have affected care delivery, and to identify new learnings articulated by RTs. A qualitative descriptive study design guided data collection through one-on-one interviews, dyadic interviews, and focus groups. We recruited active RTs across Canada, advertising on professional practice networks and social media platforms and using snowball sampling. Forty-nine RTs representing seven Canadian provinces participated. The four overarching themes developed using thematic analysis were (1) navigating uncertainty along with ever-changing practices, policies, and attitudes, (2) morphing roles within a constrained system, (3) witnessing patients suffering and experiencing moral distress, and (4) recognizing the personal toll of the pandemic on self and others, as well as lessons learned. Our study demonstrated that many RTs suffered moral distress, poor mental health, and some from challenging financial situations, especially those in the private sector. They also expressed a resilient attitude in response to these stressors. Implications in the future include identifying promising communication strategies that could act as protective factors, addressing workforce constraints and diminishing resources through innovative models of care.
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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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.018 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| 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".