Further Support for Five Dimensions of Obsessive-Compulsive Symptoms
Bibliographic record
Abstract
Attempts to explain the phenotypic heterogeneity of obsessive-compulsive disorder (OCD) have resulted in three to six OCD symptom dimensions. This study aimed to clarify the nature of these symptom dimensions using a self-report instrument (Vancouver Obsessional Compulsive Inventory [VOCI]) in addition to the clinician-rated Yale-Brown Obsessive Compulsive Scale-Symptom Checklist (YBOCS-SC). Participants (N = 154) were recruited to a study designed to specifically assess OCD symptom dimensions. Symptoms assessed via the YBOCS-SC and the VOCI were subjected to principal components analysis (PCA). Linear regression was used to assess the relationship between the YBOCS-SC-derived symptom dimensions and the VOCI symptom subscales. PCA of the YBOCS-SC and the VOCI revealed five OCD symptom dimensions that explained 68% and 60% of the variance, respectively. The results also supported a distinction between the doubt/checking symptom dimension and the unacceptable/taboo thoughts dimension that includes mental rituals. The YBOCS-SC-derived symptom components were predicted by their respective VOCI symptom subscale scores.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".