Longitudinal associations among primary and secondary psychopathic traits, anxiety, and borderline personality disorder features across adolescence.
Bibliographic record
Abstract
The individual and societal burden of psychopathy warrants an investigation into identifying its early precursors and developmental course. Accordingly, we examined the longitudinal pathways between primary and secondary psychopathic traits, anxiety, and borderline personality disorder (BPD) features across adolescence. Participants included 572 Canadian adolescents (253 girls; aged 13.96 [SD = 0.37] in Grade 8; 70.6% Caucasian) who were assessed annually on five occasions (Grades 8-12) using the Antisocial Process Screening Device (psychopathic traits), the Behavior Assessment System for Children-2 (symptoms of anxiety), and the Borderline Personality Features Scale for Children (features of BPD). Autoregressive latent trajectory models with structured residuals provided stringent tests of within-person cross-lagged associations, while controlling for sex, race/ethnicity, household income, and parental education. Results indicated that primary psychopathic traits were preceded by and predicted anxiety such that individuals who increased in primary psychopathic traits subsequently declined in anxiety, and vice versa. Results also indicated that BPD features were associated with secondary psychopathic traits and anxiety. Specifically, increases in BPD features were linked with increases in secondary psychopathic traits and anxiety. Our results suggest that even after accounting for between-person associations and other known correlates, the development of psychopathic traits is embedded within the development of emotional characteristics and personality features. This highlights areas for intervention in adolescence, particularly around the core, shared trait of impulsivity and anger. (PsycINFO Database Record (c) 2019 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".