Psychometric Examination of the Proposed Specifiers for Conduct Disorder Self-Report (PSCD) Among an Adult Community Sample From Brazil
Bibliographic record
Abstract
The Proposed Specifiers for Conduct Disorder (PSCD) is a promising novel scale that measures psychopathic traits and includes an additional conduct disorder factor that taps the antisocial dimension of psychopathy. The current study sought to broaden the application of PSCD by examining the factor structure, convergent and discriminant validity, and connections to delinquency in a young adult sample ( N = 450; M = 31.91 years, SD = 13.02 years) obtained from the Brazilian community. Participants completed a self-report version of the PSCD along with other theoretically meaningful psychometric measures. Results supported a four-factor intercorrelated factor structure, with male participants scoring significantly higher than female participants on the PSCD total, grandiose-manipulative (GM), callous-unemotional (CU), daring-impulsive (DI), and conduct disorder (CD) factors. The four factors of the PSCD mainly presented positive, moderate to high significant inter-correlations and adequate reliability. The convergent validity with measures of the dark tetrad of personality, difficulties in emotion regulation, and self-reported delinquency also revealed positive moderate significant associations. Our findings support the use of the PSCD as a promising short, time-effective self-report measure of psychopathic traits in young adults.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".