Psychometric properties of the Yale-Brown obsessive-compulsive scale, second edition, self-report (Y-BOCS-II-SR)
Bibliographic record
Abstract
The Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) is the gold-standard tool for measuring obsessive compulsive symptom severity. An updated second edition was introduced to address limitations of the original instrument, with both clinician-administered and self-report versions. No published studies have examined the psychometric properties of the self-report version, which is the purpose of the current study. Individuals with a diagnosis of obsessive-compulsive disorder (OCD, N = 67) completed the clinician-administered and self-report Y-BOCS-II, as well as a number of other self-report measures assessing obsessive-compulsive symptoms, depression, and impairment from symptoms in a counterbalanced order. Results suggest an internally consistent measure (α = .90) that has strong convergent validity with measures of OCD symptoms including the clinician-rated Y-BOCS-II, but only moderate correlations with the Obsessive-Compulsive Inventory-Revised. The self-report version also demonstrated fair discriminant validity. A reliable change index of 8 was found for this measure, which was associated with a large effect size following cognitive-behavioral therapy for OCD. Limitations include a predominantly White and female sample. The self-report version of the Y-BOCS-II appears to be a psychometrically reasonable measure for use with individuals with OCD though its ability to discriminate OCD from other disorders characterized by anxiety or depression requires further study. • The 2nd edition of the Yale-Brown Obsessive-Compulsive Scale has a self-report version. • This tool has strong internal consistency. • It also demonstrated strong overlap with the clinician-administered version. • Overlap with measures of depression and other forms of anxiety were moderate. • The Y-BOCS-II-SR appears to be a useful tool for assessing the breadth and severity of OCD symptoms.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".