Associations between the Personality Inventory for DSM-5 trait facets and aggression among outpatients with personality disorder: A multimethod study
Bibliographic record
Abstract
BACKGROUND: Most research on the Personality Inventory for DSM-5 (PID-5) was conducted with self-reports. One of the specific areas for which a multimethod design has yet to be implemented is for the PID-5's associations with aggression. The main objectives of this study were to (a) compare the PID-5 associations with self-reported and file-rated aggression, (b) compare these associations between women and men, and (c) identify the relative importance of PID-5 facet predictors. METHODS: A sample of outpatients with personality disorder (N = 285) was recruited in a specialized public clinic to complete questionnaires, and a subsample was assessed for file-rated aggression (n = 227). Multiple regression analyses were performed with PID-5 facets as statistical predictors but using distinct operationalizations of aggression (self-reported vs. file-rated). Moderation analyses were performed to identify the moderating effect of biological sex. Dominance analyses were computed to identify the relative importance of predictors. RESULTS: PID-5 facet predictors of self-reported and file-rated aggression were very consistent in both conditions. However, the amount of explained variance was reduced in the latter case (from 39% to 14%), especially for women (from 40% to 2%). The most important predictors were Hostility, Risk Taking, and Callousness. CONCLUSION: Pertaining to the statistically significant facets associated with aggression, strong evidence of multimethod replication was found. The women-men discrepancies were not most obvious in their specific associations with aggression, but rather in their amount of explained variance, maybe reflecting examiners' or patients' implicit biases, and/or different manifestations of aggression between women and men.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".