Cango Lyec (Healing the Elephant): Probable post-traumatic stress disorder (PTSD) and depression in Northern Uganda five years after a violent conflict
Bibliographic record
Abstract
Background: From 1986 to 2006, Northern Uganda experienced an atrocious civil war between the Lord's Resistance Army (LRA) and the Ugandan government. Acholi people living in the region continue to be impacted by trauma sequelae of the war and a wide range of daily stressors including poverty, hunger, and high rates of HIV infection. To date, there is a dearth of gender-differentiated mental health research in this post-conflict setting. The current study aimed to estimate the prevalence of probable post-traumatic stress disorder (PTSD) and depression in three districts most affected by the Northern Ugandan conflict and examine socio-structural, war-related, and sexual vulnerability factors associated with mental health. Methods: = 2,458) completed the Harvard Trauma Questionnaire (HTQ) and Hopkins Symptom Checklist-25 (HSCL-25) for screening PTSD and depression, in addition to a detailed questionnaire assessing socio-demographic-behavioral characteristics. Baseline categorical variables were compared between males and females using Fisher's exact test. Multivariate logistic regression was used to model correlates of probable PTSD and depression. All analyses were stratified by gender. Results: The overall prevalence of probable PTSD and depression was 11.7% and 15.2% respectively. Among former abductees, the prevalence was 23.2% for probable PTSD and 26.6% for probable depression. Women were significantly more likely to experience mental distress than men. Factors associated with mental distress included wartime trauma (adjusted odds ratios ranging from 2.80 to 7.19), experiences of abduction (adjusted odds ratios ranging from 1.97 to 3.03), and lack of housing stability and safety (adjusted odds ratios ranging from 1.95 to 4.59). Additional risk factors for women included HIV infection (AOR=1.90; 95% CI: 1.29-2.80), sexual abuse in the context of war (AOR=1.58; 95% CI: 1.02-2.45), and intimate partner violence (AOR=2.45; 95% CI: 1.07-5.63). Conclusion: Cango Lyec participants displayed lower than previously reported yet significant levels of probable PTSD and depression. Based on findings from this study, providing trauma-informed care, ensuring food and housing security, eliminating gender-based violence, and reintegrating former abductees remain important tasks to facilitate post-conflict rehabilitation 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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".