Using Implementation Science to Explore the Facilitators and Barriers of Creating a Workplace Violence Reporting System in the Context of Pakistan
Bibliographic record
Abstract
AbstractBackground: Workplace violence (WPV) is a serious, global, occupational problem. The magnitude of WPV is particularly high in hospitals. Nurses face a heightened risk of WPV, as they work closely with patients and their family members. However, implementing interventions to reduce WPV remains challenging, due to the persistent under-reporting of incidents. As a result, this dissertation assesses the feasibility of implementing a WPV reporting system for nurses in Pakistan that addresses the issue of under-reporting. This dissertation also assesses nurses’ understanding of and ability to recognize WPV, as well as their level of awareness surrounding the importance of reporting WPV incidents. Methods: As part of this dissertation, studies were conducted in one public and one private hospital in Pakistan. Data was also collected from nurses who are from Pakistan and currently work in the Canadian healthcare system. The dissertation followed an implementation science approach and focused on the Exploration Phase. To track violent incidents, the Violence Incident Form, a one-page reporting checklist, was introduced to the study settings. To achieve this purpose, a qualitative descriptive design was used. Subsequently, online In-depth Interviews were conducted with nurses, nursing supervisors, and nursing administrators. Meetings were also conducted with hospital administrators. Further, Key Informant Interviews were conducted with nurses currently working in Canadian healthcare settings. Results: The findings were categorized into two sections (a) the current state of WPV against nurses in healthcare settings in Pakistan, and (b) barriers to and facilitators of WPV reporting in the healthcare settings in Pakistan. Each section is divided into various themes and subthemes. Overall, the barriers and facilitators are integrated around the six domains of the implementation hexagon tool, including implementation site indicators (need, capacity, fitness) and implementation program indicators (evidence, supports, useability). Conclusion: The findings from this dissertation suggest that interventions to reduce WPV will only be successful if hospital management is aware of the severity of the issue and is actively involved in creating a violence-free environment for healthcare providers. Achieving this goal is critical because a safe work environment encourages nurses to remain in the nursing profession and provide quality care to patients, which will lead to a positive impact on health outcomes within society.
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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 | 0.098 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".