Normative and Maladaptive Personality Trait Models of Mood, Psychotic, and Substance Use Disorders
Bibliographic record
Abstract
The Personality Inventory for DSM-5 (PID-5) is a questionnaire developed to assess the five domains represented in the alternative model for personality disorders proposed in Section III of the DSM-5 . This study examined the ability of the PID-5 to distinguish between different mental disorders compared to a questionnaire measure of the five-factor model (FFM) of normative personality. The study included the administration of the PID-5 and Revised NEO Personality Inventory (NEO PI-R), a measure of the FFM, to treatment-seeking individuals with Depressive, Bipolar, Psychotic, and Alcohol Use Disorders (AUD). Diagnostic groups were compared at the domain level of PID-5 and NEO PI-R, with sex and age as covariates. The main findings on the PID-5 included higher Detachment scores for Bipolar and Depressive Disorders than Psychotic and AUDs, lower Psychoticism/higher Disinhibition scores for the AUD group compared to all other groups, and lower Negative Affect for the Psychotic Disorders versus AUD group. On the NEO PI-R, the AUD diagnostic group was associated with lower Conscientiousness and Agreeableness scores compared to all other groups, and lower Neuroticism scores than the Bipolar and Depressive groups. Group pairwise comparisons did not appear to show many differences between the PID-5 and NEO PI-R. The results suggest that the alternative DSM-5 model for personality disorders may have clinical utility in distinguishing personality profiles between diagnostic groups. These findings emphasize the importance of additional research on the capacity of maladaptive personality to contribute to the assessment of differential diagnoses.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".