Lessons in Sexual Assault and Violence: A Scoping Review of Undergraduate Nursing Education
Bibliographic record
Abstract
Background More than half of women and one third of men have experienced sexual violence in their lifetime. Nurses must be able to screen and treat patients who have experienced sexual assault, yet they may lack the knowledge and identification skills based on their exposure to content in their undergraduate nursing programs. This study examined the current state of the science regarding sexual assault and violence education in undergraduate nursing curricula. Method This scoping review was guided by Levac's five-step framework. Databases were searched using the key terms “nursing education” and “sexual assault education.” Results A total of 501 articles were identified; eight articles were included in the review. Themes of knowledge, confidence, and educational preparedness emerged. Conclusion Despite the importance and prevalence of sexual assault, limited educational content is provided in undergraduate nursing schools. Results urge implementing educational didactic, simulation, and clinical placement opportunities to improve nursing students' knowledge. [ J Nurs Educ . 2024;63(10):665–670.]
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".