Participatory design and implementation of an organizational plan to address burnout in hospice employees
Bibliographic record
Abstract
Hospice professionals face practice challenges that place them at increased risk for burnout. Limited research has reported on organizational efforts to address burnout and reduce work-related stressors with participatory involvement from employee stakeholders. In a large state-wide hospice organization, focus groups were initially conducted by external researchers with mixed groups of interdisciplinary employees to evaluate workplace stressors and to determine team member perceptions relative to burnout and its’ management. The paper reports an innovative multifaceted organizational education strategy that was conceived and implemented in response to the focus group findings to address or remediate work related stressors to support interdisciplinary employees across rural and urban regions who were involved in home or institutional hospice care delivery. Key executive leadership members evaluated and approved the multi-pronged organizational action plan. Interdisciplinary workgroups were formed and tasked with generating practice strategies to address four major areas of employee concern including work-related stressors, technology issues, staff appreciation and recognition, and communication. Implementation of the workgroups and delivery of the workplace changes have practice, education, and research implications. The process of stakeholder engagement with focus group findings to generate solutions may be utilized in other organizations seeking to learn strategies to address workplace stressors and improve employee wellbeing.
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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 | 0.049 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| 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".