Trauma, Power, and Psychological Safety: Understanding the Mental Health Impact of Workplace Bullying
Bibliographic record
Abstract
BACKGROUND: Workplace bullying, harassment and sexual abuse cause psychological harm, and can pose a significant threat to the success of an organization as well. This type of violence in the workplace, comprising negative actions and often abuse of power, can lead to trauma, anxiety, depression, PTSD and in severe cases, suicide. These acts impact workplace performance, negatively impact psychological safety and lead to high turnover and loss of productivity in an organization. OBJECTIVES: This narrative review outlines the key concepts of bullying, its impact on the individual, and the ways an organization can obstruct and manage it, using recent works (2018-2025) and some highlighted literature on trauma, power, and psychological safety. METHODOLOGY: Research conducted on leadership, safety climate, psychological safety and trauma-informed- as well as meta-analyses and relevant gray literature, journal articles, and other studies on bullying that A narrative synthesis of peer-reviewed and selected gray literature was conducted across PsycINFO, MEDLINE, Scopus, and Web of Science were integrated to this review. RESULTS: Exposure to bullying was connected to anxiety, depression, burnout, post-traumatic stress disorders, cardiovascular problems, absenteeism, and turnover. Diminished psychological safety, as well as disordered leadership, increases the damaging effect. In contrast, ethical trauma-informed leadership and a strong psychosocial safety climate promote recovery and decrease the incidence of bullying. CONCLUSIONS: Recognizing workplace bullying, harassment, and sexual abuse as forms of violence-and as both occupational and public health hazards-underscores the urgency of prevention. Embedding psychological safety as a core organizational value at every level is essential to fostering healthier, more resilient workplaces.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".