Screening for Obsessive and Compulsive Symptoms: Validation of the Clark-Beck Obsessive-Compulsive Inventory.
Bibliographic record
Abstract
The 25-item Clark-Beck Obsessive-Compulsive Inventory (CBOCI) was developed to assess the frequency and severity of obsessive and compulsive symptoms. The measure uses a graded-response format to assess core symptom features of obsessive-compulsive disorder (OCD) based on Diagnostic and Statistical Manual of Mental Disorders (4th ed.; American Psychiatric Association, 1994) criteria and current cognitive-behavioral formulations. Revisions were made to the CBOCI on the basis of psychometric and item analyses of an initial pilot study of clinical and nonclinical participants. The construct validity of the revised CBOCI was supported in a subsequent validation study involving OCD, nonobsessional clinical, and nonclinical samples. A principal-factor analysis of the 25 items found 2 highly correlated factors of Obsessions and Compulsions. OCD patients scored significantly higher on the measure than nonobsessional anxious, depressed, and nonclinical samples. The questionnaire had strong convergent validity with other OCD symptom measures but more modest discriminant validity.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".