Relationships Between Hostile Attribution Bias, Negative Urgency, and Reactive Aggression
Bibliographic record
Abstract
Abstract. Negative urgency defined as the tendency to act rashly when faced with intense negative emotions and hostile attribution bias (HAB) which refers to the tendency to interpret the intention of others as hostile when social context cues are ambiguous are two key psychological factors underlying reactive aggression. However, the specific associations between these factors in relation to reactive aggression have not been tested yet with competing models. The objective of the study was to test three putative models: (1) negative urgency moderates the association between HAB and reactive aggression; (2) HAB mediates the link between negative urgency and reactive aggression; (3) negative urgency mediates the relation between HAB and reactive aggression. One-hundred seventy-six participants were given self-report questionnaires to assess impulsivity, reactive aggression, as well as vignettes featuring a social situation measuring HAB in response to an ambiguous social provocation. The results showed that negative urgency constitutes a significant mediator in the association between HAB and reactive aggression. These results provide valuable insight into the cognitive processes underlying reactive aggression and may hold implications for diagnosis and intervention on aggressive behaviors.
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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 | 0.000 |
| 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) | 0.002 | 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".