Prevalence, Risk Factors, and Use of Health Care in Depression: A Survey in a Large Region of France between 1991 and 2005
Bibliographic record
Abstract
OBJECTIVE: To compare the prevalence, risk factors, and use of care for depression between 2 periods, concerning changes in social factors and health care provision. METHOD: We compared data from 2 surveys carried out in a large urbanized French region (Ile-de-France) 15 years apart (1991, n = 1192; 2005, n = 5308), using comparable methodology and tools. RESULTS: The overall prevalence of depression has slightly increased over this period. In contrast, the tendency of people who claim they feel depressed has dramatically increased. At-risk populations have also changed during this period. The proportion of people consulting a psychiatrist for depression has not changed, while general practitioner (GP) consultations have decreased and psychologist consultations have increased 3-fold. Psychotropic use by people who are depressed has decreased significantly. CONCLUSION: The trend toward increased depressive symptoms does not correspond to an increase in depressed disorders. In a well-staffed urbanized French region, psychologists are playing a growing role in managing depression at the expense of GPs, when the use of a psychiatrist remains unchanged; decreased use of psychotropic drugs may be a consequence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".