Customer Incivility and Counterproductive Work Behaviors in Egyptian Healthcare Service: Does Workplace Social Support Buffer?
Bibliographic record
Abstract
Employees in the healthcare industry encounter a high volume of challenging and stressful events, particularly in light of global health disasters. Customer incivility is frequently occurring in the healthcare industry which severely depletes both psychological and physical resources. Anecdotal evidence suggests that customer incivility leads to counterproductive work behaviors (CWB). Based on the assumptions of the conservation of resources theory and stressor-strain framework, this study demonstrates empirically the impact of customer incivility on the two most common forms of CWB among Egyptian healthcare professionals. Moreover, this work sheds a spotlight on whether workplace social support (WSS) may buffer against the damaging consequences of customer incivility. Structural equation modeling was used to analyze the data collected from 343 professionals employed in public—government and parastatal—hospitals in Dakahlia Governorate in Egypt. The findings demonstrate that customer incivility increases both interpersonal-targeted and organizational-targeted CWB. However, the role of WSS as a protective mechanism against the adverse consequences of customer incivility remains contingent on the form of CWB.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".