Job satisfaction, burnout, and stress among pediatric nurses in various specialty units at an acute care hospital
Bibliographic record
Abstract
Aims: The aims of the study were to: assess job satisfaction, burnout, compassion satisfaction, and work-related stress among pediatric nurses at surgical, medical, critical care, and hematology/oncology units in a tertiary acute care hospital; and identify the predictors of job satisfaction, burnout, compassion satisfaction, and work-related stress. Methods: A cross-sectional study was conducted at a children’s hospital in southern California from February 2013 to March 2013. A convenience sample of registered nurses working in four different units (N = 240) completed the Professional Quality of Life, Brief Index of Affective Job Satisfaction, and demographic questionnaire. One-way Analysis of Variance (ANOVA) and simultaneous multiple regression procedures were performed. Results: Nurses in the hematology/oncology unit reported the lowest level of burnout and highest levels of job satisfaction and compassion satisfaction. In contrast, nurses in the surgical unit reported the opposite. Among surgical unit nurses, those with 5-9 years of RN experience reported highest burnout as well as lowest job satisfaction and compassion satisfaction. The combination of demographic variables explained a large fraction of the variance in job satisfaction ( R 2 = 0.251) and positive predictors were white ethnicity (β = 0.33) and hematology/oncology unit (β = 0.16), whereas negative predictors were surgical unit (β = -0.32) and critical care unit (β = -0.20). Conclusions: Nurses in the hematology/oncology unit reported lowest burnout and highest job satisfaction, which may be due to the educational and mentoring support from a unit-based end-of-life care program. A focused strategy targeting a specific group of nurses in a unit may help to reduce work-related stress and burnout.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".