Dysfunctional Metacognitive Beliefs in Body Dysmorphic Disorder
Bibliographic record
Abstract
The present study aims to examine the correlation of body dysmorphic disorder, with metacognitive subscales, metaworry and thought-fusion. The study was conducted in a correlation framework. Sample included 155 high school students in Isfahan, Iran in 2013-2014, gathered through convenience sampling. To gather data about BDD, Yale-Brown Obsessive Compulsive Scale Modified for BDD was applied. Then, Meta Cognitive Questionnaire, Metaworry Questionnaire, and Thought-Fusion Inventory were used to assess metacognitive subscales, metaworry and thought-fusion. Data obtained from this study were analyzed using Pearson correlation and multiple regressions in SPSS 18. Result indicated YBOCS-BDD scores had a significant correlation with scores from MCQ (P<0.05), MWG (P<0.05), and TFI (P<0.05). Also, multiple regressions were run to predict YBOCS from TFI, MWQ, and MCQ-30. These variables significantly predicted YBOCS [F (3,151) =32.393, R(2)=0.57]. Findings indicated that body dysmorphic disorder was significantly related to metacognitive subscales, metaworry, and thought fusion in high school students in Isfahan, which is in line with previous studies. A deeper understanding of these processes can broaden theory and treatment of BDD, thereby improve the lives of sufferers and potentially protect others from developing this devastating disorder.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".