Depression Among Last-Year High School Students in Vientiane, Capital City of Lao PDR
Bibliographic record
Abstract
In spite of being a major public health issue, no data on depression in young people exist in Laos. Decision makers are therefore poorly equipped to define the degree of prioritization of this pathology among their preoccupations. This study aimed at estimating the prevalence of depression among last-year high schools students and exploring some of its determinants with a qualitative approach. The quantitative component was based on a survey of a representative sample consisting of 210 students studying in 30 schools in the capital city, Vientiane, using the Beck Depression Inventory validated in the Lao language. The qualitative component was based on interviews with 5 nondepressive and 5 depressive students. Clinical depression prevalence was 24%. Depressed students were aware of the effectiveness of available medication and its importance in controlling the disease. The other students had little knowledge about the disease and how to handle it.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".