Cognitive distortions mediate relationships between early maladaptive schemas and aggression in women and men
Bibliographic record
Abstract
Abstract Difficult childhood experiences can lead to the development of early maladaptive schemas (EMS) that cause emotional and behavioral problems later in life. The present study examined the role of cognitive distortions in mediating relationships between EMS and aggression in adults as a function of sex. Participants were 59 women (Mage = 34.7 years, standard deviation [SD] = 8.0) and 86 men (Mage = 39.3 years, SD = 13.2) who completed the Young Schema Questionnaire—Short Form‐V3, the How I Think Questionnaire of cognitive distortions, and the Buss–Warren Aggression Questionnaire. Multiple mediation analysis identified EMS domain impaired limits to be uniquely and directly related to aggression, and the domain impaired autonomy to be indirectly related via a range of cognitive distortions. Multigroup analyses revealed no sex differences in these relationships, and analysis of covariance with age as a covariate revealed no sex differences in levels of EMS, cognitive distortion, or aggression. The results suggest that impaired limits and impaired autonomy are EMS domains of relevance to aggression regardless of sex. Furthermore, in the case of impaired autonomy, self‐serving, proaggression cognitive distortions appear to be involved. Interventions for aggression may thus benefit by focusing on clients with entitlement/grandiosity traits indicative of impaired limits, and vulnerability/dependence traits indicative of impaired autonomy, and in the latter case consider addressing the self‐serving cognitions that enable the expression of aggression in these clients.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".