Proposed Specifiers for Conduct Disorder (PSCD): Further validation of the parent-report version in a nationally representative U.S. sample of 10- to 17-year-olds.
Bibliographic record
Abstract
The Proposed Specifiers for Conduct Disorder (PSCD; Salekin & Hare, 2016) is a new self-report and informant measure designed to assess psychopathic characteristic domains along with symptoms of conduct disorder in youth. Previous factor analytic studies on the PSCD have found that the items are accounted for by a four-factor model reflecting grandiose-manipulative, callous-unemotional, daring-impulsive, and conduct disorder (CD) symptoms. The present study examined the factor structure, psychometric properties, and criterion-related validity of the parent-report version of the PSCD (PSCD-P) in a nationally representative U.S. sample of children and adolescents (N = 1,091, Mage = 13.39, SD = 2.20, range age = 10-17; 50.0% boys, 76% White). Confirmatory factor analyses for the full (24-item) and a shortened (13-item) PSCD-P revealed good internal reliability estimates and support for the four-factor model (grandiose-manipulative, callous-unemotional, daring-impulsive, CD). Results also provided evidence for (a) measurement invariance of the PSCD-P items across sex, race/ethnicity, and age of the child; (b) convergent validity with CD/oppositional defiant disorder symptoms and discriminant validity with a measure of neuroticism; and (c) criterion-related validity with respect to prosociality, peer and family functioning, reactive and proactive aggression, delinquency, academic performance, and substance use. The prevalence for psychopathic personality propensity was found to be 2%. We discuss clinical and research implications regarding the use of the parent-report version of the PSCD for school-aged children. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".