The Relationships Amongst Pediatric Nurses' Work Environments, Work Attitudes, and Experiences of Burnout
Bibliographic record
Abstract
Background: Pediatric nurses care for some of the most vulnerable patients in our healthcare system. Research on health care provider organizational behavior shows that the quality of care nurses provide is directly related to their well-being, influenced by Burnout and job stress, in the workplace. However, most of the research conducted on nursing populations neglects to separately study nurses who care for children. In a resource limited system where health care provider well-being is recognized as a priority, it is important for administrators to understand the environmental and attitudinal work factors most influential to pediatric nurse work outcomes in order to target optimization strategies. The aim of the study was to identify which modifiable work environment factors, e.g., [Incivility, Perceived Organizational Support, Quality of Work-life] make the greatest contribution to the work outcome of Burnout (i.e., Personal Accomplishment, Emotional Exhaustion, Depersonalization) in pediatric nurses. Methods: A cross-sectional survey design was used at a large quaternary care pediatric hospital in Toronto, Canada. We administered a survey to a convenience sample of all registered nurses with >3 months experience in the Pediatric, Cardiac, and Neonatal Intensive Care Units from January 2021–March 2021. Path analysis was used to test our proposed model which was specified a priori based on a review of the literature. Results: 143 nurses completed the survey. Path analysis of the tested model resulted in good fit. Quality of Work-life had the largest direct effect on Work Engagement (β = 0.582, S.E. = 0.111, p < 0.001). Work Engagement had the largest direct effect on Personal Accomplishment (β = 0.68, S.E. = 0.53, p < 0.001). Quality of Work-life had the largest indirect effect on Personal Accomplishment (β = 0.4, S.E. = 0.65, p < 0.001), Emotional Exhaustion (β = −0.33, S.E. = 0.87, p < 0.001), and Depersonalization (β =−0.17, S.E. = 0.41, p = 0.006), respectively. Work Engagement had the largest total effect on Personal Accomplishment (β = 0.68, S.E. = 0.64, p < 0.001) and the third largest total effect on Emotional Exhaustion (β = −0.57, S.E. = 0.83, p < 0.001). Quality of Work-life had the second largest total effect on Work Engagement (β = 0.58, S.E. = 0.11, p < 0.001) indicating that Quality of Work-life is mediated through Work Engagement for its effect on Burnout. Conclusions: Our results indicate work environment and work attitude factors that can provide organizational leadership with a targeted focus to reduce pediatric critical care nurse Burnout, and thus improve provider well-being, in a resource limited system.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".