Worldwide impact of economic cycles on suicide trends over 3 decades: differences according to level of development. A mixed effect model study
Bibliographic record
Abstract
OBJECTIVES: To investigate the trends and correlations of gross domestic product (GDP) adjusted for purchasing power parity (PPP) per capita on suicide rates in 10 WHO regions during the past 30 years. DESIGN: Analyses of databases of PPP-adjusted GDP per capita and suicide rates. Countries were grouped according to the Global Burden of Disease regional classification system. DATA SOURCES: World Bank's official website and WHO's mortality database. STATISTICAL ANALYSES: After graphically displaying PPP-adjusted GDP per capita and suicide rates, mixed effect models were used for representing and analysing clustered data. RESULTS: Three different groups of countries, based on the correlation between the PPP-adjusted GDP per capita and suicide rates, are reported: (1) positive correlation: developing (lower middle and upper middle income) Latin-American and Caribbean countries, developing countries in the South East Asian Region including India, some countries in the Western Pacific Region (such as China and South Korea) and high-income Asian countries, including Japan; (2) negative correlation: high-income and developing European countries, Canada, Australia and New Zealand and (3) no correlation was found in an African country. CONCLUSIONS: PPP-adjusted GDP per capita may offer a simple measure for designing the type of preventive interventions aimed at lowering suicide rates that can be used across countries. Public health interventions might be more suitable for developing countries. In high-income countries, however, preventive measures based on the medical model might prove more useful.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".