Stability and predictors of psychopathic traits from mid‐adolescence through early adulthood
Bibliographic record
Abstract
High levels of psychopathic traits in youth are associated with multiple negative outcomes including substance misuse, aggressive behavior, and criminality. Evidence regarding stability of psychopathic traits is contradictory. No previous study has examined long-term stability of psychopathic traits assessed with validated clinical measures. The present study examined the stability of psychopathic traits from mid-adolescence to early adulthood and explored adolescent factors that predicted psychopathic traits five years later. The sample included 99 women and 81 men who had consulted a clinic for substance misuse in adolescence. At an average age of 16.8 years, the adolescents were assessed using the Psychopathy Checklist: Youth Version (PCL: YV) and five years later using the PCL-Revised (PCL-R). Additionally, extensive clinical assessments of the adolescents and their parents were completed in mid-adolescence. Among both females and males, moderate to high rank-order stability was observed for total PCL and facet scores. Among both females and males, there was a decrease in the mean total PCL score, interpersonal facet score, affective facet score, and lifestyle facet score. However, the great majority of females and males showed no change in psychopathy scores over the five-year period as indicated by the Reliable Change Index. Despite the measures of multiple family and individual factors in adolescence, only aggressive behavior and male sex predicted PCL-R total scores in early adulthood after taking account of PCL:YV scores. Taken together, these results from a sample who engaged in antisocial behavior in adolescence suggest that factors promoting high psychopathy scores act early in life.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".