Impact of Leadership Styles on the Organizational Commitment of Medical Practitioners: The Moderating Effects of Workplace Stress
Bibliographic record
Abstract
The healthcare system is now facing several problems, which demands managers and leaders learning from various leadership styles and staff empowerment techniques to establish a work environment that supports medical practitioners' dedication to patients and their company. The present study aims to examine the leadership styles and organizational commitment of medical practitioners at the Melaka State Health Department [Jabatan Kesihatan Negeri Melaka (JKNM)], Malaysia, and the influence of workplace stress. In particular, this study explored the moderating effects of workplace stress on the association between leadership styles and organizational commitment among medical practitioners. The study used a quantitative approach based on the Social Exchange Theory by Homans and Lewin’s Person-Environment Fit Model. The survey involved questionnaires distributed to obtain data from 309 medical practitioners. The data collected were analyzed using description means and hierarchical regression. The results revealed a significant correlation and moderating effect of workplace stress on leadership styles (i.e., Transformational Leadership, Transactional Leadership, and Laissez-Faire Leadership) and organizational commitment among JKNM medical practitioners. This paper also considered the theoretical and practical implications and made recommendations for future research.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".