Neighbourhood Material and Social Deprivation and Exposure to Antidepressant Drug Treatment: A Cohort Study Using Administrative Data
Bibliographic record
Abstract
OBJECTIVE: To assess whether neighbourhood deprivation is associated with exposure to an antidepressant drug treatment (ADT) and its quality among individuals diagnosed with unipolar depression and insured by the Quebec public drug plan. METHOD: We conducted an administrative database cohort study of adults covered by the Quebec public drug plan who were diagnosed with a new episode of unipolar depression. We assessed material and social deprivation using an area-based index. We considered exposure to an ADT as having ≥1 claim for an ADT within the 365 days following depression diagnosis. Among those exposed to ADT, ADT quality was assessed with 3 indicators: first-line recommended ADT, persistence with the ADT, and compliance with the ADT. Generalized linear models were used to estimate adjusted prevalence ratios (aPR) and 95% confidence intervals (95% CI). RESULTS: Of 100,432 individuals with unipolar depression, 65,436 (65%) were exposed to an ADT in the year following the diagnosis. Individuals living in the most materially deprived areas were slightly more likely to be exposed to an ADT than those living in the least deprived areas (aPR, 1.04; 95% CI, 1.03 to 1.06). The likelihoods of being exposed to a first-line ADT, persisting for the minimum recommended duration and complying with the ADT were independent of the deprivation levels. CONCLUSIONS: Neighbourhood deprivation was not associated with ADT quality among individuals insured by the Quebec public drug plan. It might be partly attributable to the public drug plan whose goal is to provide equitable access to prescription drugs regardless of income.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".