Prevalence of mental disorders and torture among Bhutanese refugees in Nepal: a systemic review and its policy implications
Bibliographic record
Abstract
The mass expulsion and exile of Bhutanese de facto refugees to displaced camps in Nepal represents one of the world's most neglected humanitarian crises. We aimed to summarize the impact of the long-term displacement on refugee mental illness using systematic review techniques, a methodology seldom used in the humanitarian field. In order to examine the impact among the population and the association between tortured refugees over non-tortured refugees, we searched 11 electronic databases from inception to 12 May 2006. We additionally contacted researchers at the United Nations High Commission for Refugees (UNHCR) and at the Centre for Victims of Torture, Kathmandu, and searched the websites of Amnesty International, Human Rights Watch, Relief-Web, and the US State Department. We included any studies that use a pre-defined protocol to determine mental illness within this population. Six studies met our inclusion criteria. All were conducted amongst the Bhutanese populations residing in Nepalese refugee camps, and include a sub-sample of 2,331 torture survivors residing in the camps, identified in 1995. All studies report a dramatically high incidence of mental illness including depression, anxiety and post-traumatic stress disorder. Both tortured and non-tortured participants reported elevated rates of mental illness. Our review indicates that the prevalence of serious mental health disorders within this population is elevated. The reported incidence of torture is a possible contributor to the illnesses. The use of systematic review techniques strengthens the inference that systematic human rights violations were levied upon this population and that they continue to suffer as a result. The international community must resolve this protracted crisis.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".