Mixed-methods findings from the Ngutulu Kagwero (agents of change) participatory comic pilot study on post-rape clinical care and sexual violence prevention with refugee youth in a humanitarian setting in Uganda
Bibliographic record
Abstract
There is a dearth of evidence-based post-rape clinical care interventions tailored for refugee adolescents and youth in low-income humanitarian settings. Comics, a low-cost, low-literacy and youth-friendly method, integrate visual images with text to spark emotion and share health-promoting information. We evaluated a participatory comic intervention to increase post-exposure prophylaxis (PEP) knowledge and acceptance, and prevent sexual and gender-based violence, in Bidi Bidi refugee settlement, Uganda. Following a formative qualitative phase, we conducted a pre-test post-test pilot study with refugee youth (aged 16–24 years) (n = 120). Surveys were conducted before (t0), after (t1), and two-months following (t2) workshops. Among participants (mean age: 19.7 years, standard deviation: 2.4; n = 60 men, n = 60 women), we found significant increases from t0 to t1, and from t0 to t2 in: (a) PEP knowledge and acceptance, (b) bystander efficacy, and (c) resilient coping. We also found significant decreases from t0 to t1, and from t0 to t2 in sexual violence stigma and depression. Qualitative feedback revealed knowledge and skills acquisition to engage with post-rape care and violence prevention, and increased empathy to support survivors. Survivor-informed participatory comic books are a promising approach to advance HIV prevention through increased PEP acceptance and reduced sexual violence stigma with refugee youth.Trial registration: ClinicalTrials.gov identifier: NCT04656522.
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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 | 0.059 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".