A novel ED-based sexual assault centre in western Kenya: description of patients and analysis of treatment patterns
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to establish the feasibility of a Kenyan emergency department (ED)-based sexual assault centre; and to improve knowledge of the characteristics of sexual assault in the region. METHODS: The Center for Assault Recovery-Eldoret (CAR-E) was established to provide timely, culturally sensitive treatment of Kenyan sexual assault survivors using a standardised evaluation/treatment protocol. A retrospective review of charts of all sexual assault survivors attending CAR-E from May 2007-May 2008 was performed. Simple descriptive statistics, t tests, and OR were calculated. RESULTS: CAR-E treated 321 survivors over 13 months. Patients' mean age was 15.9 years; 50% were younger than 14years old. Survivors were predominately female and single. Most knew their assailant. Younger age was associated with increased likelihood of genital trauma. Only 43% of assaults were reported to the police. Sexually transmitted infection prophylaxis was given per protocol to 84% eligible; emergency contraception to 64%; and HIV prophylaxis to 63%. Only 44% received counselling. Survivors were more likely to get sexually transmitted infection and HIV prophylaxis, and emergency contraception if they had genital injury. CONCLUSIONS: Development of an ED-based sexual assault centre at a referral hospital in Kenya using a standardised history, physical, and treatment protocol was feasible, and high rates of prophylaxis were provided. Based on characteristics of people who have been assaulted, community prevention efforts should concentrate on decreasing the societal acceptability of rape. In conjunction with improvement of protocols at the centre under consideration, development of similar centres in sub-Saharan African ED should be encouraged.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".