The Impact of Emotional Intelligence on Mental Health of Pakistani Nurses: The Mediator Role of Organizational Commitment
Bibliographic record
Abstract
The present study investigates the mediating effect of organizational commitment between emotional intelligence (EI) and mental health (MH). The participants of the study were 252 nurses working in six big districts of KPK (Peshawar, Mardan, Swat, Sawabi, Charsadda & Nowshehra), Pakistan. Data were collected through Organizational Commitment Scale (Meyer, Allen, & Smith, 1993), The Hospital Anxiety and Depression Scale (Zigmond & Snaith, 1983) and EI Scale (Wong & Law, 2002). Both EI and organizational commitment were significantly related to MH. The results of Structure Equation Modeling (SEM) explored that organizational commitment partially mediated the relationship between EI and MH. The final three factor model explored a significant path from EI to MH via organizational commitment. The findings discuss the effect of EI on MH.
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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 | 0.000 | 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) | 0.002 | 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".