Workplace violence and risk factors for PTSD among psychiatric nurses: Systematic review and directions for future research and practice
Bibliographic record
Abstract
WHAT IS KNOWN ON THE SUBJECT?: Trauma among psychiatric nurses and other healthcare workers is related to workplace violence, but other risk factors may also contribute, including those occurring before, during or after workplace violence. WHAT DOES THIS PAPER ADD TO EXISTING KNOWLEDGE?: Most previously identified PTSD risk factors were not tested or supported in research with psychiatric nurses, although there is promising evidence for risk factors including severe or injurious assault, cumulative exposure, burnout, and other worker characteristics. We identify directions for research needed to improve knowledge, including collecting data before nurses experience workplace violence, defining workplace risk factors consistently and conducting and reporting qualitative analysis. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Provide training in risk assessment and violence prevention to psychiatric nurses. Offer mental health support to those exposed to violence, especially with cumulative exposure. ABSTRACT: Introduction Psychiatric nurses are at risk of workplace violence and post-traumatic stress disorder (PTSD). There is limited understanding of pre-trauma and post-trauma risk factors. Aim Our aim was to review factors associated with workplace PTSD in psychiatric nurses. Method We searched quantitative and qualitative studies from 1980 to 2019 in 23 databases plus abstracts for studies on psychiatric hospital nursing staff, potentially traumatic workplace events, workplace factors and PTSD. Following duplicate abstract (n = 10,064) and full-text (n = 199) screening, data were extracted in duplicate from 19 studies. Using best-fit framework synthesis, we identified workplace violence, pre-trauma and post-trauma risk factors. Results Six variables yielded evidence in at least two empirical studies scoring at least 6/8 on a quality measure, or one such study plus more than one other study ("promising": severe/injurious assault, cumulative exposure, burnout, poor mental health, low compassion satisfaction, neuroticism). Four were supported by at least one better quality study or at least two others ("suggestive": gender, poor training, any physical aggression exposure, compassion fatigue). Discussion Pre-trauma measures, consistent definitions of workplace exposures and thorough reporting of quantitative results are needed to improve research. Implications for Practice Violence prevention and mental health care for exposed nurses appear the most promising targets for PTSD prevention. Therefore, it is particularly important to understand workplace violence and mental health among nurses working in psychiatric hospitals.
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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 | 0.027 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".