Investigation of Theory of Mind, Disgust Sensitivity, and Mental Contamination in Patients with Obsessive-Compulsive Disorder
Bibliographic record
Abstract
Objective: The aim of this study is to examine the relationships between theory of mind (ToM), disgust sensitivity, and mental contamination patients with obsessive-compulsive disorder (OCD). Methods: In this cross-sectional study, 37 patients with OCD and 45 healthy volunteers with similar socio-demographic characteristics were enrolled at the Silifke State Hospital Department of Psychiatry between October 2023 and March 2024. We utilized the Padua Inventory - Washington State University Revision, the Dokuz Eylül Theory of Mind Index, the Disgust Scale — Revised, and the Vancouver Obsessive-Compulsive Inventory — Mental Contamination Scale. Results: Patients with OCD exhibited significantly higher sensitivity to disgust (mean ± standard deviation 68.19±12.28) and mental contamination (mean ± standard deviation= 25.54± 7.64) compared to healthy controls. Although the differences in ToM abilities approached significance, they did not reach statistical significance. A significant correlation was identified between the subscale of "disgust related to contamination" and "checking compulsions" (r = 0.433), as well as with "obsessive thoughts about harming oneself/others" (r = 0.515). No significant correlation was found between mental contamination and the other variables (r = 0.240). Conclusion: The findings highlight impairments in certain ToM skills among patients with OCD, alongside elevated disgust sensitivity and mental contamination, relative to controls. The significant correlations between disgust sensitivity and specific OCD symptoms emphasize the influence of disgust in exacerbating certain compulsive behaviors. These insights contribute to our understanding of the interactions between OCD symptoms, ToM abilities, and disgust sensitivity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".