Chronicity of self-harming behaviors among adolescent teenage girls living in refugee settlements in Northern Uganda
Bibliographic record
Abstract
BACKGROUND: Self-harming ideations demand targeted research due to their persistent nature, especially among female adolescents within refugee populations who face unique challenges that can exacerbate self-harming tendencies. This study aimed to assess the factors associated with self-harming ideations chronicity among female teenagers living in refugee settlement in Northern Uganda. METHOD: This cross-sectional study used a pretested questionnaire to assess self-harming ideations and other demographic characteristics. Ordinal logistic regression was used to determine factors associated with chronicity of self-harm ideations. RESULTS: Of 385 participants, the prevalence of self-harming ideations was 4.2% (n = 16) for acute, 8% (n = 31) for subacute, and 3.1% (n = 12) for chronic. The likelihood of having more chronic self-harming ideations increased with having ever been pregnant (adjusted odds ratio [aOR] = 3.78, 95% Confidence Interval [CI] = 1.57-9.08). However, having a spouse as the family head reduced the likelihood of having more chronic self-harming ideations (aOR = 0.19, 95% CI = 0.04-0.95). CONCLUSIONS: The persistence of self-harming thoughts among female teenagers in Northern Ugandan refugee settlements varies. Pregnancy history is associated with a higher chance of prolonged self-harming thoughts while having a spouse as the family's head is linked with a lower likelihood. Examining different demographic and familial elements when addressing the mental well-being of female teenage refugees is vital. It stresses the necessity for customized interventions and support networks targeting the reduction of self-harm behaviors among this vulnerable group.
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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 | 0.000 |
| 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 | 0.001 |
| 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".