Childhood maltreatment and trauma is common and severe in body dysmorphic disorder
Bibliographic record
Abstract
BACKGROUND: Childhood maltreatment and trauma may be risk factors for the development of body dysmorphic disorder (BDD). However, the limited research to date on these topics has been constrained by either the absence of a matched healthy control group or non-comprehensive assessments. METHODS: This study assessed the prevalence and severity of childhood maltreatment and other traumatic events in 52 BDD participants (56% female) and 57 matched controls (51% female) with no history of mental illness, using the Childhood Trauma Questionnaire and a checklist assessing broader traumatic events. RESULTS: In comparison with controls, participants with BDD showed a higher prevalence of emotional abuse (61.5% vs. 33.3%) and physical neglect (59.6% vs. 28.1%), as well as more severe overall maltreatment, emotional abuse, and emotional and physical neglect. BDD participants were also more likely to meet cut-offs for multiple types of maltreatment and reported an elevated number and variety of broader traumatic childhood events (e.g., life-threatening illness). In BDD, increasingly severe maltreatment was correlated with greater severity of BDD symptoms, anxiety and suicidal ideation. CONCLUSIONS: These data suggest that childhood maltreatment and exposure to other traumatic events are common and severe in BDD and are cross-sectionally associated with the severity of clinical symptoms. Adversity linked to maladaptive family functioning during childhood may therefore be especially relevant to people with BDD and could relate to social and emotional processing problems in the 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".