Factor Structure and Construct Validity of the Proposed Specifiers for Conduct Disorder (PSCD) Scale in Chinese Adolescents
Bibliographic record
Abstract
The Proposed Specifiers for Conduct Disorder (PSCD) Scale is a new measure to assess psychopathic traits and symptoms of conduct disorder (CD) in children and adolescents. The current study examined the psychometric properties of the self-report version of the PSCD in a sample of community adolescents in mainland China ( N = 1,683; mean age = 13.60, SD = 1.14; 54.1% boys). The new instrument showed good internal consistency (alpha) for the 24-item total scale and good mean interitem correlations for each of the six-item subscales. Confirmatory factor analyses (CFAs) were conducted on all 24 items, and also a subset of 13 items that demonstrated strong item-level reliabilities. Using all 24 items, CFA results supported a four-factor bifactor model indicating the total score reflects a broad syndrome with four factors. The four factors included grandiose–manipulative traits (GM traits), callous–unemotional traits (CU traits), daring–impulsive traits (DI traits), and CD traits. The 13-item CFA results provided further support for a four-factor conceptualization of the PSCD and evidence of strong measurement invariance across gender. Finally, the PSCD exhibited the expected relations with other psychopathy measures, anxiety and depression, and aggression, supporting the PSCD scores convergent, discriminant, and criterion related validity. The findings provide preliminary evidence for the four-factor structure of the PSCD and support for the utility of the self-report PSCD for measuring psychopathic traits and CD in Chinese adolescents.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".