Understanding health outcomes following workplace aggression: A social exchange perspective
Bibliographic record
Abstract
This study explored health outcomes following workplace aggression among social workers in Israel. Grounded in the social exchange theory, a relationship-based perspective was used to explain the mechanism through which exposure to workplace aggression results in employee outcomes. Reports of employees and managers were analysed with respect to the impact of varied forms of aggressive behaviours perpetrated by clients and co-workers on posttraumatic stress and somatic symptoms. The intervening effects on symptoms of two forms of perceived organisational support, organisational procedural support and interpersonal co-worker support operationalised as team trust were examined. Overall, 548 employees and 89 managers in 31 social services departments completed self-report questionnaires. Results revealed positive associations between exposure to both co-worker and client aggression, and posttraumatic stress and somatic symptoms. Importantly, while perceived organisational support is often equated with social support, this study found that two elements, organisational procedural support and team trust, had differing impacts on somatic and posttraumatic stress symptoms following WPA. Specifically, team trust was negatively associated with symptoms, while organisational procedural support showed no effect. This study has important implications for timely prevention measures to deal with workplace aggressions and valuable directions for future studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".