Multidimensional assessment of OCD: integration and revision of the vancouver obsessional‐compulsive inventory and the symmetry ordering and arranging questionnaire
Bibliographic record
Abstract
This article reports on the integration and revision of two self-report measures of obsessive-compulsive symptoms based on data from an obsessive-compulsive disorder (OCD) sample (n=228): the Vancouver Obsessional-Compulsive Inventory (VOCI) and the Symmetry Ordering and Arranging Questionnaire (SOAQ). The revised measure provides scores on five symptom subscales (Contamination, Checking, Hoarding, Symmetry and Ordering, Obsessions). It shows improvement upon current versions in several ways: it has a good model fit, eliminates redundancy, reduces overlap across subscales, is much shorter, and covers those OCD dimensions most frequently identified in factor-analytic studies. Strengths of the revision compared with other measures are high distinctiveness of subscales, discriminant validity with depression and anxiety, and a more fine-grained and comprehensive assessment of obsessional contents.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".