Cross‐generational comparison of dispensed pharmacotherapy for depression
Bibliographic record
Abstract
PURPOSE: The purpose of this paper is to compare predictors of receipt of recommended first-line pharmacotherapy in three generational cohorts of patients with new episode depression. DESIGN/METHODOLOGY/APPROACH: This retrospective database cohort study included adolescent, adult and senior Quebec Public Prescription Drug Insurance Plan beneficiaries with new episode depression, who were diagnosed by primary care physicians or psychiatrists (October 2000 to March 2001) and received pharmacotherapy. Receipt of recommended first-line pharmacotherapy, based on the first psychoactive medication dispensed following the depression diagnosis, was defined according to Canadian guidelines. FINDINGS: Receipt of first-line pharmacotherapy was documented in 52 percent, 71 percent and 50 percent of adolescents, adults and seniors, respectively. Among adolescents and seniors, diagnosis by a psychiatrist was associated with a lower likelihood of receipt of recommended pharmacotherapy. Adolescent females and senior males were more likely and adults with comorbidity were less likely to receive recommended pharmacotherapy. For all age groups, having a physician who both diagnosed the depression and prescribed the initial pharmacotherapy was associated with an increased likelihood of receiving recommended pharmacotherapy. Relational continuity of care influenced receipt of recommended first-line pharmacotherapy. Gender differences in treatment were found in adolescents and seniors. ORIGINALITY/VALUE: This paper identifies predictors of receipt of recommended first-line pharmacotherapy in three generational cohorts of patients with new episode 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".