On the Convergence Between PSY-5 Domains and PID-5 Domains and Facets
Bibliographic record
Abstract
The DSM-5 Personality and Personality Disorders workgroup and their consultants have developed the 220-item, self-report Personality Inventory for the DSM-5 (PID-5) for direct assessment of the proposed personality trait system for DSM-5; however, most practicing clinical psychologists will likely continue to rely on separate omnibus measures to index symptoms and traits associated with psychopathology. The Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF) is one such measure and assesses the Personality Psychopathology Five (PSY-5) domains, which are conceptual cognates of the DSM-5 trait domains. The current study examined the associations between the MMPI-2-RF PSY-5 scales and the DSM-5 trait domains and facets indexed by the PID-5. A clear pattern of convergence was found indicating that each of the PSY-5 scales was most highly correlated with its conceptually expected PID-5 counterpart (rs = .44-.67; Mdn r = .53) and facet correlations generally showed the same pattern. Similarly, when each of the PSY-5 scales was regressed onto the PID-5 domains, the conceptually expected pattern of associations emerged even more clearly. Finally, a joint exploratory factor analysis with the PSY-5 and PID-5 trait facet scales indicated a five-factor solution that clearly resembled both of the PSY-5/DSM-5 trait domains. These results show clear evidence that the MMPI-2-RF has utility in the assessment of dimensional personality traits proposed for the upcoming DSM-5.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".