Validation of a French version of the Vancouver Obsessional Compulsive Inventory–Mental Contamination scale (VOCI-MC) and the Contamination Thought–Action Fusion scale (CTAF) in non-clinical and clinical samples
Bibliographic record
Abstract
The Vancouver Obsessional Compulsive Inventory-Mental Contamination scale (VOCI-MC) and the Contamination Thought-Action Fusion scale (CTAF) are two self-report instruments that assess symptoms of mental contamination and fusion between thoughts, and feelings and behaviours associated with contamination, respectively. The aim of this study was to investigate the psychometric properties of the French version of these two scales in non-clinical and clinical samples. We included 79 participants diagnosed with obsessive-compulsive disorder (OCD), 31 diagnosed with anxiety disorders, who were recruited from the University Department of Adult Psychiatry in Montpellier, and 320 non-clinical participants recruited from the general population. Psychometric properties of the French VOCI-MC and CTAF were investigated. Results showed that the French versions of the VOCI-MC and the CTAF had high internal consistency, good convergent and divergent validity, as well as good temporal stability. Exploratory and confirmatory factor analyses showed a one-factor structure for the two scales in both non-clinical and OCD samples. Adequate discriminative validity was established by comparing OCD patients with contamination-related symptoms and OCD patients who did not report contamination-related symptoms. The French VOCI-MC and CTAF are valid and appropriate tools for measuring mental contamination in both clinical and research contexts.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".