What about males? Exploring sex differences in the relationship between emotion difficulties and eating disorders
Bibliographic record
Abstract
OBJECTIVE: While eating disorders (EDs) are more commonly diagnosed in females, there is growing awareness that men also experience EDs and may do so in a different way. Difficulties with emotion processing and emotion regulation are believed to be important in EDs, but as studies have involved predominantly female samples, it is unclear whether this is also true for males. METHODS: In a sample of 1604 participants (n = 631 males), we assessed emotion processing and emotion regulation in males with EDs (n = 109) and compared results to both females with EDs (n = 220) and males from the general population (n = 522). We also looked at whether emotion processing and emotion regulation difficulties predicted various aspects of eating psychopathology and whether this was moderated by sex. We assessed emotion processing with the Toronto Alexithymia Scale, emotion regulation with the Difficulties in Emotion Regulation Scale and the Emotion Regulation Questionnaire, and eating psychopathology with the Eating Disorder Examination Questionnaire. RESULTS: We found that males with ED, like their female counterparts, suffered from emotion processing and emotion regulation deficits. We did find some sex differences, in that males with EDs tended to report more difficulties with their emotions as well as a more externally oriented thinking style compared to females with EDs. Difficulties with emotion processing and emotion regulation were strongly predictive of various aspects of eating psychopathology in both sexes. Importantly, we found that sex moderated the relationship between cognitive reappraisal and eating restraint. As such, low use of reappraisal was found to be associated with higher levels of restraint in females but not in males. DISCUSSION: Difficulties with emotion processing and emotion regulation are associated with eating psychopathology in both males and females. Reappraisal was not found to be associated with reduced eating psychopathology in males, suggesting a cautious approach to interventions targeting this strategy. Research around explanatory mechanisms and interventions must adopt a broader viewpoint including those that are traditionally overlooked in EDs.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".