Relationship between occupational stress, emotional intelligence, and self-efficacy among faculty members in faculty of nursing Zagazig University, Egypt
Bibliographic record
Abstract
Background/Aim: Different studies, in international context, have linked occupational stress to emotional intelligence or self-efficacy of faculty members. However, investigating the relationship between these three constructs in this context was limited. So, the researchers investigated the relationship between occupational stress, emotional intelligence and self-efficacy among faculty members. Method: The study was conducted at the Faculty of Nursing, Zagazig University using a descriptive correlational design. A convenience sample of 91 faculty members working in Faculty of Nursing Zagazig University during the academic year 2011-2012 were recruited for the study. Four tools were used for data collection: Questionnaire about demographic data, Emotional Intelligence Scale, General Self-Efficacy Scale, and Occupational Stress Scale. Results: The study findings indicate that the majority of faculty members experience a high level of occupational stress, while they have a low level of emotional intelligence and self-efficacy. The occupational stress was negatively related with faculty members’ emotional intelligence and self-efficacy. Conclusion and Recommendation: The findings of current study confirm that occupational stress has negative relationships with the faculty members’ emotional intelligence and self-efficacy. Therefore, we suggest that the Faculty of Nursing should keep the stress level of their faculty members lower and help them to stay healthier by holding training courses on emotional intelligence improving their social skills and increase their efficiency at work. Moreover, the perceived self-efficacy can be improved among the faculty members through training programmes and courses this would help the faculty members enhance their stress bearing capacity and also improve their productivity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".