Psychometric Properties of the Persian Version of the Vancouver Obsessional-Compulsive Inventory Inventory (VOCI) in Iranian Non-Clinical Sample
Bibliographic record
Abstract
The Vancouver Obsessional-Compulsive Inventory (VOCI) is a self-report inventory developed to assess a wide range of Obsessive-Compulsive symptoms. The aim of this study was to investigate psychometric properties of the Persian version of the VOCI in non-clinical samples. A questionnaire package including the VOCI, BDI-II, BAI, MOCI, OCI-R and PSWQ was administered to volunteer undergraduate students (n = 233, 139 females, 94 males) from two Iran universities (Tehran University of Medical Sciences and Allameh Tabatabaei University). All the assessments were repeated in the same sample after 2 weeks. Psychometric analyses were run to assess reliability and validity of the Persian version of the VOCI. We converged an exploratory factor analysis to test the factor structure. The VOCI-Persian had good internal consistency, test-retest reliability, convergent and divergent validity. The present study showed that the factor structure of the questionnaire consisted of five main factors: VOCI Contamination, Checking, Obsessions, Hoarding and Perfectionism/Indecisiveness. Further studies are needed to develop psychometric tools with stronger diagnostic performance for OCD assessment.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".