Divergent Outcomes in Cognitive-Behavioral Therapy and Pharmacotherapy for Adult Depression
Bibliographic record
Abstract
OBJECTIVE: Although the average depressed patient benefits moderately from cognitive-behavioral therapy (CBT) or pharmacotherapy, some experience divergent outcomes. The authors tested frequencies, predictors, and moderators of negative and unusually positive outcomes. METHOD: Sixteen randomized clinical trials comparing CBT and pharmacotherapy for unipolar depression in 1,700 patients provided individual pre- and posttreatment scores on the Hamilton Depression Rating Scale (HAM-D) and/or Beck Depression Inventory (BDI). The authors examined demographic and clinical predictors and treatment moderators of any deterioration (increase ≥1 HAM-D or BDI point), reliable deterioration (increase ≥8 HAM-D or ≥9 BDI points), extreme nonresponse (posttreatment HAM-D score ≥21 or BDI score ≥31), superior improvement (HAM-D or BDI decrease ≥95%), and superior response (posttreatment HAM-D or BDI score of 0) using multilevel models. RESULTS: About 5%-7% of patients showed any deterioration, 1% reliable deterioration, 4%-5% extreme nonresponse, 6%-10% superior improvement, and 4%-5% superior response. Superior improvement on the HAM-D only (odds ratio=1.67) and attrition (odds ratio=1.67) were more frequent in pharmacotherapy than in CBT. Patients with deterioration or superior response had lower pretreatment symptom levels, whereas patients with extreme nonresponse or superior improvement had higher levels. CONCLUSIONS: Deterioration and extreme nonresponse and, similarly, superior improvement and superior response, both occur infrequently in randomized clinical trials comparing CBT and pharmacotherapy for depression. Pretreatment symptom levels help forecast negative and unusually positive outcomes but do not guide selection of CBT versus pharmacotherapy. Pharmacotherapy may produce clinician-rated superior improvement and attrition more frequently than does CBT.
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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 | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".