Comparison of HIV-related vulnerabilities between former child soldiers and children never abducted by the LRA in northern Uganda
Bibliographic record
Abstract
BACKGROUND: Thousands of former child soldiers who were abducted during the prolonged conflict in northern Uganda have returned to their home communities. Programmes that facilitate their successful reintegration continue to face a number of challenges. Although there is increasing knowledge of the dynamics of HIV infection during conflict, far less is known about its prevalence and implications for population health in the post-conflict period. This study investigated the effects of abduction on the prevalence of HIV and HIV-risk behaviours among young people in Gulu District, northern Uganda. An understanding of abduction experiences and HIV-risk behaviours is vital to both the development of effective reintegration programming for former child soldiers and the design of appropriate HIV prevention interventions for all young people. METHODS: In 2010, we conducted a cross-sectional study of 2 sub-counties in Gulu District. A demographic and behavioural survey was interview-administered to a purposively selected sample of 384 transit camp residents aged 15-29. Biological specimens were collected for HIV rapid testing in the field and confirmatory laboratory testing. Descriptive statistics were used to describe characteristics of abduction. Additionally, a gender-stratified bivariate analysis compared abductees' and non-abductees' HIV risk profiles. RESULTS: Of the 384 participants, 107 (28%) were former child soldiers (61% were young men and 39% were young women). The median age of participants was 20 and median age at abduction was 13. HIV prevalence was similar among former abductees and non-abductees (12% vs. 13%; p = 0.824), with no differences observed by gender. With respect to differences in HIV vulnerability, our bivariate analysis identified greater risky sexual behaviours in the past year for former abductees than non-abductees, but there were no differences between the two groups' survival/livelihood activities and food insufficiency experiences, both overall and by gender. The analysis further revealed that young northern Ugandans in general are in desperate need of education, skills development, and support for victims of sexual violence. CONCLUSIONS: This study persuasively demonstrates that all young people in northern Ugandan have been similarly affected by HIV infection during war and displacement. Post-conflict programme planners must therefore abandon rudimentary targeting practices based on abductees as a high-profile category. Instead, they must develop evidence-based HIV interventions that are commensurate with young people's specific needs. As such programmes will be less stigmatizing, more oriented to self-selection, and more inclusive, they will effectively reach the most vulnerable young people in northern Uganda.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".