Psychometric Properties of the Obsessive—Compulsive Inventory—Revised in a Turkish Analogue Sample
Bibliographic record
Abstract
The Obsessive-Compulsive Inventory-Revised (OCI-R) assesses distress associated with the symptoms of obsessive-compulsive disorder (OCD). This study reports on the psychometric properties of the Turkish version of the OCI-R as a widely known measure. The sample consisted of 319 Turkish university students (67.1% women; M age = 21.5, SD = 2.0). The questionnaire battery included measures of OCD symptoms, specific cognitions, thought control, and personality characteristics. A target rotation analysis supported the factorial validity of the Turkish OCI-R as indicated by its replicability with the original factor structure (i.e., checking, washing, obsessing, hoarding, ordering, and mental neutralizing). High-scoring OCD symptom groups also significantly differed on the Turkish OCI-R and thus presented preliminary evidence for its criterion validity. Correlational analysis supported convergent and divergent validity of the measure, with significant correlations between the Turkish OCI-R and OCD symptoms, OCD-specific beliefs, two thought control strategies (e.g., worry and punishment), and neuroticism, but not with psychoticism or extraversion. The current findings provide initial evidence of sound psychometric properties for the Turkish OCI-R in a nonclinical sample.
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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 | 0.002 | 0.008 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".