Distress and job satisfaction after robbery assaults: a longitudinal study
Bibliographic record
Abstract
BACKGROUND: External/intrusive violence at work can result in psychological distress and can be an important risk to employee health and safety. However, the vast majority of workplace violence studies have employed cross-sectional and correlational research, designed to examine immediate reactions after being assaulted at work. AIMS: To explore whether exposure to robbery as a traumatic event may contribute to the onset of typical symptoms of psychological distress (anxiety depression, dysphoria and loss of confidence) and job dissatisfaction over time. METHODS: We collected data by using a two-wave panel design, in which employees working the days of bank robberies, in an Italian bank, filled in a questionnaire between 48h and 1 week after the robbery (T1) and 2 months after the robbery (T2). We performed structural equation models to evaluate the fit of different models to our data. RESULTS: There were 513 participants at T1 (58% women) and 175 (34%) participants at T2 (62% women). There was a simultaneous association in which psychological distress leads to job dissatisfaction both following robbery and 2 months later. CONCLUSIONS: Our findings support a synchronous effects model and suggest that interventions after suffering physical assaults, apart from helping employees to recover their health, should consider restoring their trust and confidence in the organization. This study contributes to understanding the dynamic relationships between a robbery at work and its outcomes over time, by addressing several methodological deficiencies in previous longitudinal studies.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".