Prevalence of mental disorders and psychological trauma among conflict- affected population in Somalia: a cross-sectional study
Bibliographic record
Abstract
Background Despite the longstanding psychosocial impact of the interactable conflict in Somalia for the last 30 years, there is lack of epidemiological studies of mental health conditions, especially at the population level. Objectives The aim of this study is to fill the epidemiological gap and provide population based data on mental health conditions in the South-Central region of Somalia. The specific objectives were: (1) To determine the epidemiological patterns of mental disorders in three sites; Baidoa, Dolow and Kismayo, (2) Understand the socio-demographic characteristics associated with mental health conditions in the study sites, and (3) To assess the correlates between psychological trauma and the mental wellbeing of the population. Methods This was a cross-sectional study of 713 respondents recruited from the three sites namely Dolow, Baidoa and Kismayo. Data on sociodemographic characteristics and mental disorders were collected using the MINI and sociodemographic questionnaire. Basic descriptive statistics were used to summarize sociodemographic characteristics. Univariable and multivariable logistic regressions were used to examine factors associated with common mental disorders. Statistical significance was considered at a value of p <0.05. Results Participants’ mean age was 32.6 (±10.7) years. More than half (58.5%) of the respondents were male. The overall prevalence of common mental disorders was 557 (78.1%) with panic disorder (39.3%), generalized anxiety disorders (34.9%), major depressive episode current (32.1) and PTSD (29.9%). According to the multivariable logistic regression analysis, being male AOR = 1.74 (95%CI = 1.25, 2.42), having a family size of more than 10 members AOR =1.37 (95% CI = 1.00, 1.89), being unemployed AOR = 1.90 (95%CI = 1.18, 3.06), experienced starvation AOR =3.46 (95%CI = 2.23, 5.37), khat use AOR = 5.87 (955 CI, 1.75–19.65), were identified as predicting factors for the common mental disorders among the study participants. Conclusion There is a high prevalence of mental disorders with anxiety disorders being the commonest. Findings reflect earlier studies that showed higher rates in conflict and post-conflict settings. It also aligns with past studies in Somalia. As such, there is an urgent need to integrate mental health and psychosocial support within the primary healthcare and other service sectors such as education considering the vast majority of the population are young.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".