When Leaders Don’t Walk the Walk: A National Survey of Academic Nurse Leader Perceptions of Staff Burnout
Bibliographic record
Abstract
AIM: This survey explored nurse leaders' impressions of burnout on college/school of nursing (CON/SON) administrative staff and leadership-facilitated strategies used to promote resilience building/mitigate burnout. BACKGROUND: Administrative staff are foundational to the success of a university's CON/SON, yet few studies have explored the impact of burnout in this group. METHOD: Cross-sectional survey distributed to associate dean and business officer attendees of the 2022 American Association of Colleges of Nursing, Business Officers of Nursing Schools meeting (summer 2022) ( n = 64). RESULTS: Most respondents lacked a burnout mitigation plan (46/64, 72%); many also lacked a personal strategy for managing their own burnout (46/64, 72%) and did not personally participate in university activities to maintain their well-being (45/64, 70%). CONCLUSION: This study highlights the impact of nurse leaders who fail to model self-care, which may limit the benefit of costly burnout mitigation activities and resources in their universities.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".