Exploring How Sexual Assault Nurse Examiners Practise Trauma-Informed Care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Sexual violence is a term describing sexual acts where consent is not freely given. Registered nurses employed as sexual assault nurse examiners (SANEs) provide care to address the medical and legal needs of victims/survivors of sexual violence. Trauma-informed care (TIC) is an approach recommended when caring for individuals who have experienced trauma. PURPOSE: The study purpose was to understand how SANEs incorporate trauma-informed approaches in the care of adult and postpubescent adolescent victims/survivors of sexual violence. METHODS: Eight SANEs were purposively recruited to participate in online semistructured interviews. Interview data were analyzed using qualitative interpretive description. RESULTS: Six themes emerged from the analysis: (a) the importance of understanding the patient's experience; (b) personalized connection: developing a safe nurse-patient relationship; (c) choice: the framework of how we do things; (d) rebuilding strengths and skills to support healing and posttraumatic growth; (e) a wonderful way to practise: facilitators and benefits of trauma-informed practice; and (f) challenges to trauma-informed practice. CONCLUSIONS: These findings indicate the perceived value of TIC and the need for enhanced support of providers who deliver TIC. More research is warranted to strengthen the evidence about trauma-informed practice in SANE programs and across healthcare settings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it