Sales of antidepressants, suicides and hospital admissions for depression in Veneto Region, Italy, from 2000 to 2005: an ecological study
Bibliographic record
Abstract
BACKGROUND: Increased prescription of antidepressants has been consistently associated with a decrease in suicide rates in several countries. The aim of this study is to explore antidepressant consumption, suicide rates and admission for depression in the Veneto Region, Italy, in order to see whether the same pattern could be detected. METHODS: Data from the Italian Ministry of Health (admissions for depression), the Pharmacy Service of a Local Health Unit (antidepressant prescribing) and from the Epidemiological System of the Veneto region (suicide rates) were collected from 2000 to 2005 for the Veneto region. RESULTS: Suicide rates did not show any marked increase but were stable in males and females. Antidepressant prescribing increased exponentially over the period examined, whilst admissions for depression markedly decreased. The trend for an exponential increase in antidepressant prescribing in the Veneto region is shared with other countries and locales. CONCLUSIONS: It is possible that the increase in antidepressant prescribing might be associated with earlier treatment of depression, thus decreasing the likelihood of aggravation of depression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".