Psychological Treatment of Obsessive-Compulsive Disorder in Patients with Major Depression: A Pilot Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To examine the efficacy of cognitive-behavioural therapy (CBT) for obsessive-compulsive disorder (OCD) in patients with comorbid major depressive disorder (MDD). METHOD: Participants (n = 29) diagnosed with comorbid OCD and MDD were randomized to receive standard CBT for OCD or integrated CBT that included an exclusive focus on treating MDD in the first phase of treatment and OCD in the second phase of treatment. RESULTS: Both treatments resulted in statistically significant improvements in OCD and MDD symptoms. Treatment effects and recovery rates in the intent-to-treat sample were lower in both treatments, compared with past studies that excluded patients with MDD. However, among treatment completers, both treatments resulted in statistically significant and clinically meaningful improvements in OCD and MDD symptoms. CONCLUSIONS: CBT holds promise as an efficacious treatment for people with comorbid OCD and MDD. The high treatment dropout rate with comorbid patients suggests that additional treatment strategies are required to enhance retention and optimize clinical outcomes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".