Does mental contamination mediate the relationship between perceived teasing experiences and body dysmorphic disorder-related symptoms?
Bibliographic record
Abstract
Objective This study aimed to examine the relationship between body dysmorphic disorder (BDD) symptoms and mental contamination (MC). Specifically, it explored whether appearance-related teasing episodes evoke feelings of MC and whether these feelings mediate the association between teasing and BDD symptoms and their severity in a nonclinical sample.Method Three hundred and eighty-five undergraduate students completed online measures that included the Body Dysmorphic Disorder Symptom Scale, the Perception of Appearance- and Competency Related Teasing Scale, and the Vancouver Obsessive-Compulsive Inventory-Mental Contamination Scale.Results Appearance-related teasing was significantly associated with BDD symptoms and symptom severity, and MC partially mediated this relationship. Significant correlations were found between teasing, BDD cognitions, and checking and avoidance behaviours. MC was most strongly associated with BDD cognitions, checking, and avoidance, indicating its potential role in maintaining these behaviours. Mediation analyses confirmed that MC partially explained the relationship between teasing and both BDD symptoms and severity.Conclusions Mental contamination partially mediated the relationship between appearance-related teasing and BDD symptoms in a nonclinical sample. These preliminary findings, based on correlational data, suggest that mental contamination may play a role in the development and maintenance of BDD, warranting further exploration with clinical samples.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".