Examining Compassion Satisfaction and Work-Related Stress Within a Hospice for the Homeless (H4H) Organization: Results From a Multi-Method Survey
Bibliographic record
Abstract
Purpose Communities in Canada have created targeted hospice palliative care strategies such as facility-based hospices for the homeless (H4H) to promote equitable access to care. To ensure the sustainability of H4H programs, there is a need to prevent and mitigate burnout and enhance workplace wellbeing. The objectives for this study were to, (1) develop a better understanding of H4H staff and volunteers’ experiences of stress and wellbeing; and (2) explore opportunities for additional resources to support workplace wellbeing. Methods We developed and administered an anonymous 26-item survey to 104 providers including both staff (eg, nurses, administrators) and volunteers at a facility-based H4H in Ontario. The survey gathered open and closed-ended data on sociodemographic information, compassion satisfaction, and H4H stories of workplace experiences. Findings The response rate was 56% ( n = 58). Most respondents had high compassion satisfaction. However, multiple factors causing stress at work across the socio-ecological model were discussed. Requests for additional resources to foster workplace wellbeing included educational, process-related, spiritual/psychological, and social supports. Respondents storied that positive workplace wellbeing includes being able to provide quality care, and having supportive relationships, personal fulfillment, and a respectful culture within the workplace. Conclusion Provider participants were satisfied with their ability to be effective carers, yet chronic multi-level work-related stressors can erode a sense of meaning in H4H work. A multi-faceted evidence-based approach to supporting workplace wellbeing is needed in H4H settings. Research has shown that mindfulness could be an effective strategy, as it can decrease burnout and promote coping, team connection, and anti-oppressive 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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".