A Narrative Inquiry into Professional Quality of Life among Therapeutic Recreation Practitioners working in Long-Term Care Homes
Bibliographic record
Abstract
Professional Quality of Life (ProQoL) incorporates positive (e.g., compassion satisfaction) and negative (e.g., compassion fatigue and burnout) aspects of working in healthcare (Stamm, 2010). Although studies have examined ProQoL of frontline staff in long-term care (LTC) homes, the perspective of therapeutic recreation (TR) professionals is largely missing. To address this gap, this paper explores ProQoL with four TR practitioners who work in LTC homes in Ontario, Canada. Participants were invited to explore past and present experiences that contribute to ProQoL in individual interviews and write two personal narratives that embody compassion satisfaction and compassion fatigue. Narrative thematic analysis revealed 3 threads of PQoL among practitioners: fueling the soul through connection and purpose, draining the TR spirit through workplace conflict and role ambiguity, and developing professional valour. Findings suggest that although practitioners derive great fulfilment from their career, workplace culture and conflict are chronic challenges that erode the PQoL of practitioners. Recommendations for future research and practice are offered.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".