Remission in Major Depressive Disorder: A Comparison of Pharmacotherapy, Psychotherapy, and Control Conditions
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to assess the percentages of full remission in studies of patients with major depressive disorder in which pharmacotherapy, psychotherapy, and control conditions were directly compared. METHOD: Computerized searches of the MEDLINE and PsychINFO databases up to November 2000 were used to identify six multiple-cell randomized, controlled, double-blind trials for well-defined major depressive disorder in which medications, psychotherapy, and control conditions were directly compared and for which remission percentages were reported. RESULTS: The studies included a total of 883 outpatients with mild to moderate, primarily nonmelancholic, nonpsychotic major depressive disorder. Treatment duration ranged from 10 to 34 weeks (median=16 weeks). An intent-to-treat analysis indicated that, according to measurements by independent blind raters, antidepressant medication (tricyclic antidepressants and phenelzine) and psychotherapy (primarily cognitive behavior and interpersonal therapies) were more efficacious than control conditions, but there were no differences between active treatments. The percentages of remission for all patients randomly assigned to medication, psychotherapy, and control conditions were 46.4%, 46.3%, and 24.4%, respectively. Furthermore, significantly more patients dropped out of control conditions (54.4%) than either treatment with medication (37.1%) or psychotherapy (22.2%). CONCLUSIONS: Both antidepressant medication and psychotherapy may be considered first-line treatments for mildly to moderately depressed outpatients.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".