Evaluation of Inference-Based Cognitive-Behavioral Therapy for Obsessive-Compulsive Disorder: A Multicenter Randomized Controlled Trial with Three Treatment Modalities
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Inference-based cognitive-behavioral therapy (I-CBT) is a specialized psychological treatment for obsessive-compulsive disorder (OCD) without deliberate and prolonged exposure and response prevention (ERP) that focuses on strengthening reality-based reasoning and correcting the dysfunctional reasoning giving rise to erroneous obsessional doubts and ideas. OBJECTIVE: The present study aimed to evaluate the effectiveness of I-CBT through a comparison with appraisal-based cognitive behavioral therapy (A-CBT) and an adapted mindfulness-based stress reduction (MBSR) intervention. METHODS: This was a two-site, parallel-arm randomized controlled trial (RCT) comparing I-CBT with A-CBT. The MBSR intervention acted as a non-specific active control condition. Following formal evaluation, 111 participants diagnosed with OCD were randomly assigned. The principal outcome measure was the Yale-Brown Obsessive-Compulsive Scale. RESULTS: All treatments significantly reduced general OCD severity and specific symptom dimensions without a significant difference between treatments. I-CBT was associated with significant reductions in all symptom dimensions at post-test. Also, I-CBT led to significantly greater improvement in overvalued ideation, as well as significantly higher rates of remission as compared to MBSR at mid-test. CONCLUSIONS: I-CBT and MBSR appear to be effective, alternative treatment options for those with OCD that yield similar outcomes as A-CBT. I-CBT may have an edge in terms of the rapidity by which patients reach remission, its generalizability across symptom dimension, its potentially higher level of acceptability, and effectiveness for overvalued ideation. Future research is needed to assess whether additional alternative treatments options can help to increase the number of people successfully treated.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it