Clinician Wellbeing and Resilience: The Impact of Working in Complex Care Rehabilitation
Bibliographic record
Abstract
Introduction: This study explored the experiences of working in complex rehabilitation, the impact this had on clinician wellness, and resilience strategies utilized in practice. Methods: A qualitative descriptive approach was used to understand clinician’s experiences working in complex care, at a large Toronto-based complex rehabilitation hospital. In-person interviews were conducted with fourteen therapists and nurses, and analyzed using inductive qualitative content analysis strategies. Results: Clinicians perceived most patients to be ‘complex’; however reflected both positive and negative effects of working with complex stroke patients. Clinicians faced tensions in the balance between care provision and maintaining personal wellness, and often discussed the importance of putting up ‘barriers’ for self-preservation. Collaborative working relationships and support provided by the interprofessional team were critical in managing practice pressures. Conclusion: This study identified positive and negative long standing impacts of working in a complex care environment and how they impact the clinician’s ability to thrive in the workplace.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".