Prevalence, Associated Factors, and Impact of Violence and Racism Experienced by Nursing Students in Clinical Placements
Bibliographic record
Abstract
Background: Amidst a growing crisis in the Canadian nursing workforce, nursing students serve as a crucial component in strengthening and sustaining the healthcare system. As part of education, nursing students are required to complete clinical placements in healthcare settings where violence and racism often persist. Previous research has found that such incidents can result in significant psychological and physiological harm, including disrupted learning and increased rates of attrition. Within the Canadian context, there is a gap in understanding the depth and severity of this issue due to a lack of quantitative data. Aim: The aim of this study was to obtain current quantitative data on the prevalence of violence and racism experienced by nursing students in clinical placements, the associated factors, and impacts of these experiences. The research questions that guided this study were (1) What are the types and frequency of violence and racism experienced by nursing students, and who are the perpetrators? (2) How do nursing students respond to and report violence and racism? (3) What negative outcomes do students report after experiencing violence and racism? (4) What protective factors do students report that mitigate the negative impacts of violence and racism? and (5) What recommendations do students report that address violence and racism on the individual, professional, and organizational levels? Methods: This study utilized a descriptive cross-sectional design and an anonymous online survey to collect data. Participants were nursing students currently enrolled in either the basic or accelerated stream of a nursing program who were currently engaged in, or had completed, at least one clinical placement in Southwestern Ontario. Data were analyzed using IBM® SPSS software to compute frequencies and counts for the study variables. Results: 82 out of 485 nursing students responded to the study survey yielding a response rate of approximately 17%. The mean age of participants was 22 years (SD=±2.80), with 87% identifying as female. Approximately 61% of participants reported experiencing at least one form of violence within the last twelve months. The most prevalent form of violence was verbal violence (43%), followed by racism (30%), physical violence (18%), and sexual violence (12%). Patients were identified as the primary perpetrators across all forms of violence; however, multiple sources, including staff nurses, patients’ visitors, and preceptors, were also reported for verbal violence and racism. The most frequently reported negative outcomes were anxiety, disrupted learning, and anger. Participants commonly reported taking no action in response to experiences of violence and racism. Overall, incidents were underreported with verbal violence being the most frequently reported (26%), followed by physical violence (13%), racism (12%), and sexual violence (10%). Family and friends were often identified as the individuals to whom incidents were disclosed. Participants who chose not to report incidents cited reasons such as the belief that nothing will get done about it, the incident was not important enough to them, or that they did not know how to report it. Participants frequently reported personal resilience and supportive clinical learning environments as key protective factors against negative outcomes. To mitigate violence and racism, participants commonly recommended education and training for both clinical placement staff and clinical teachers. Implications: This study emphasizes the urgent need for clearly defined, trauma-informed, and anti-oppressive policies to address violence and racism experienced by nursing students in clinical placements. It outlines the importance of implementing structured reporting mechanisms, zero-tolerance policies with appropriate language to address the severity of the issue, as well as collaborative partnerships between educational institutions and clinical organizations to promote safe learning environments. Clinical and educational staff should receive targeted, trauma-informed training that is grounded in anti-oppressive and anti-racist principles, while changes to curricula should be implemented to prepare students for the realities of clinical environments before their placements. This study also advocates that the responsibility for addressing violence and racism should not fall solely on students, recognizing their vulnerable position within clinical hierarchies. Finally, this study calls for further research to better understand the psychological and educational impacts of these experiences and to develop evidence-based, trauma-informed strategies for prevention and response.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".