Using Provider Education About Self Care to Reduce Compassion Fatigue Among Nurses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many have scrolled through Facebook and news stories highlighting nurses as “heroes” of the current coronavirus pandemic. Pictures of nurses in personal protective equipment while at work or clips of nurses making fun tiktok video’s celebrating recovered COVID -19 patients. Social media does not capture the sheer emotional, physical, and spiritual wear that nurses experience providing compassionate care to patients facing light threatening illness or events. Health care organizations are under pressure to control cost, increase productivity, and increase patient satisfaction scores, all while facing a pandemic crisis. This type of pressure can create inadequate staffing and increase clinical responsibilities for the nurse. An atmosphere that creates the foundation for compassion fatigue and nurse burnout. Compassion fatigue is linked to poor personal health, nursing retention and recruitment rates, and quality of patient care with increased safety and medication errors (Registered Nurses’ Association of Ontario, 2011). Raising awareness of Compassion Fatigue in nursing is vital to improving patient outcomes and addressing the “dying” roll of the bedside nurse.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it