Anxiety and Depression Among Internally Displaced Persons in North Central Nigeria: Prevalence, Correlates, and Policy Implications
Bibliographic record
Abstract
INTRODUCTION: Internally displaced persons (IDPs) in Nigeria face disproportionate mental health problems, yet rigorously designed epidemiological evidence in urban camps remains limited. METHODS: A cross-sectional survey of 264 IDPs across 2 Abuja camps (Durumi and Wassa) employing culturally adapted Hausa and English versions of the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 to assess anxiety and depression prevalence, severity, and correlates. RESULTS: Moderate-to-severe symptoms affected 18.9% of participants for depression and 17.4% for anxiety. Multivariable analysis identified older age (≥35 years; adjusted odds ratio [AOR]: depression = 4.36; anxiety = 6.64), female sex (depression AOR = 2.36; anxiety AOR = 2.86), and absence of prior psychological counseling (depression AOR = 4.28; anxiety AOR = 2.96) as significant correlates. Generalized additive models revealed increasing symptom severity with age, with adjusted mean depression and anxiety scores rising from approximately 3.6 and 3.4 among younger participants to 7.1 in those aged ≥35 years. Sensitivity analyses using a negative-control outcome (communication language) and E-values assessed the robustness of the findings to potential unmeasured confounding and selection bias. CONCLUSION: By integrating rigorous bias assessment with locally grounded data, this study demonstrated the significant rates of anxiety and depression among internally displaced persons in Nigeria utilizing a culturally tailored mental health evaluation.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".