Novel Quality Control Metric for the Pharmacotherapy of Major Depressive Disorder
Bibliographic record
Abstract
Studies suggest that people with major depressive disorder (MDD) often receive treatment that is not concordant with practice guidelines. To evaluate this, we (1) developed a guideline concordance algorithm for MDD pharmacotherapy (GCA-8), (2) scored it using clinical data, and (3) compared its explanation of patient-reported symptom severity to a traditional concordance measure. codes), from the Penn State Psychiatry Clinical Assessment and Rating Evaluation System (PCARES) registry (visits from February 1, 2015, to April 13, 2021). We (1) scored 1-year concordance using the Canadian Network for Mood and Anxiety Treatments (CANMAT) guidelines and deviation from 8 pharmacotherapy-related criteria and (2) examined associations between concordance and Patient Health Questionnaire depression module (PHQ-9) scores. = .008). By measuring naturalistic MDD pharmacotherapy guideline concordance with the GCA-8, we revealed potential treatment gaps and an inverse association between guideline concordance and MDD symptom severity.
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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 | 0.046 | 0.186 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".