Exploring the Impact of Perceived Organizational Support in the Context of Patient Violence
Bibliographic record
Abstract
Workplace violence is known risk factor for diminished mental health and turnover intentions. Yet, to this day, researchers still do not know how victimized workers cope over time or how organizations can best help them recover. This study sought to document the evolution of psychological distress in a sample of recently victimized professionals (N=81) immediately after the event and over the course of one year. Mixed-modeling was used to assess distress scores at four different time points (3, 11, 27, 52 weeks). Findings suggest that patient violence had a serious impact on staff mental health with close to 35% of women and 11% of men suffering from severe distress after returning to work. Perceived organizational support proved to be a good protective factor against severe distress but its effect eroded with cumulative exposure to violence. Considering the high risk of experiencing violence in certain work settings, this article concludes by discussing how organizations can be more considerate of the needs of traumatized workers.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".