The relationship between obsessive compulsive disorder and mental contamination (MC): psychometric properties of Vancouver obsessive compulsive inventory-MC scale and thought-action fusion-contamination scale
Bibliographic record
Abstract
Objective: Mental contamination is defined as feelings of internal dirtiness in absence of actual contact with a dirty physical object or a person. Mental contamination is considered to play an important role in maintenance and persistence of obsessive compulsive disorder (OCD). This study aimed to examine psychometric properties of the Turkish version of two objective measures of mental contamination: Vancouver Obsessive Compulsive Inventory-Mental Contamination Scale (VOCI-MC) and Thought-Action Fusion-Contamination Scale (TAF-CS). Method: The participants were 255 university students (183 females and 70 males) with the age range of 18-28 years. The participants were asked to fill out the questionnaire set consisted of VOCI-MC, TAF-CS, Thought-Action Fusion Scale (TAFS), Disgust Scale-Revised, Trait Anger Expression Inventory and Obsessive Compulsive Inventory-Revised (OCI-R). Results: Reliability analyses indicated that internal consistency of VOCI-MC and TAF-CS were 0.93 and 0.92, and test-retest reliabilities were 0.79 and 0.61, respectively. Consistent with the original study, the results of explanatory and confirmatory factor analysis indicated that both scales had one factor structure. Convergent and divergent validity analyses revealed that both scales were positively correlated with OCI-R total scores and its subscales as well as TAF total score and its subscales; but this relationship was significantly less strong for Trait Anger and Disgust Sensitivity. While VOCI-MC significantly predicted OCD symptomatology, TAF-CS had no predictive power in this regard. Conclusions: The results support that psychometric properties of the Turkish versions of the scales meet acceptable standards for validity and reliability, and therefore can be used among Turkish population.
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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 | 0.001 | 0.012 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".