Emergency Nurses Job Satisfaction Prediction Model: Personality traits, Resilience, Emotional Expression and Ambiguity Tolerance
Bibliographic record
Abstract
Background: Nursing is considered as one of the most stressful jobs due to the emotional nature of the patient's demands, long working hours, professionals and interpersonal conflicts. Aim: The purpose of present research was the study of job satisfaction predictors consisted personality traits, resilience, emotional expression and ambiguity tolerance of emergency nurses in Tehran hospitals. Methods: This is a descriptive and correlational study. The population includes all emergency nurses in all hospitals of Tehran in 2017. The sample size consisted of 300 nurses who were selected randomly. For data collection were used NEO Personality Inventory, Berkeley Emotional Expression Questionnaire (BEQ), Job Satisfaction Survey (JSS), Resilience Scale (RS) and Ambiguity Tolerance Scale (ATS). Results: The results demonstrate that ambiguity tolerance, resilience and emotional expression respectively had respectively the highest impact on job satisfaction, but personality traits had the lowest impact on it. Implications for Practice: Personality traits can be a predictor of the job satisfaction of emergency nurses in hospital environment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".