MétaCan
Menu
Back to cohort
Record W1798820806 · doi:10.4236/psych.2015.613168

Disgust Emotion and Obsessive-Compulsive Symptoms in an Iranian Clinical Sample

2015· article· en· W1798820806 on OpenAlexaff
Giti Shams, Leyla Janani, Irena Milosevic, Elham Foroughi

Bibliographic record

VenuePsychology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsConcordia University
Fundersnot available
KeywordsDisgustPsychologyObsessive compulsiveClinical psychologyPsychiatryAnger

Abstract

fetched live from OpenAlex

A growing body of research has revealed robust associations between disgust and obsessive-compulsive disorder (OCD) symptoms. The present study aimed to understand if particular disgust domains are more closely associated with OC symptoms subscales, especially contamination and washing. A sample of 60 OCD patients from an outpatient Iranian psychiatric clinic completed self-report questionnaires including the Disgust Scale-Revised (DS-R), the Obsessive-Compulsive Inventory-Revised (OCI-R) and the Padua inventory-Washington State University revision (PI- WSUR). The results indicated correlations between the total, core and contamination subscales of the DS-R together with the OCI-R total score as well as with the PI-WSUR total score. However, no correlation was found between these inventories and the DS-R animal reminder subscale. The DS-R total score also correlated with the washing and checking subscales of the OCI-R and with the contamination obsessions and washing and checking compulsions of the PI-WSUR. The relationship between disgust and demographic characteristics showed that the DS-R total, core and contamination scores were significantly higher for women and married subjects, and that the animal reminder subscale score was significantly higher for women than men. Although symptoms presentation, risk factors, and outcomes may vary cross-culturally, very little is known about disgust emotion as an OCD symptom in Iranian and eastern cultures. Additional work is needed to better understand these symptoms in other eastern cultures.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.296
GPT teacher head0.425
Teacher spread0.130 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same venuePsychologySame topicPsychology of Moral and Emotional JudgmentFrench-language works237,207