The 2004 tsunami and mental health in Thailand: a longitudinal analysis of one‐and two‐year post‐disaster data
Bibliographic record
Abstract
Some 280,000 people died in the Indian Ocean tsunami on 26 December 2004. This cohort study examined its impact on mental health one and two years later. It did so by investigating the association between six consequent variables (personal injury, loss of home, loss of business, death of a family member, injury to a family member, or loss of a family member's business) and mental health, as measured by the 36-item Short Form Health Survey (SF-36), among residents in four provinces of Thailand. One year later, participants who suffered a personal injury, the loss of a business, or the loss of a family member reported poorer mental health than those who were unaffected. Two years later, participants who experienced the loss of a family member reported poorer mental health than those who were unaffected. This research shows that such a disaster may have long-lasting ramifications for mental health, and that diverse losses may influence mental health differently.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".