Measurement invariance of the Child Problematic Traits Inventory across sexes and longitudinally from early to late childhood.
Bibliographic record
Abstract
Several assessment tools have been developed to assess psychopathic traits in childhood and adolescence. However, knowledge on the continuity and change in psychopathic traits remains limited, especially because of uncertainties regarding the capacity of these tools to assess these traits using a common metric across development. To fill this void, this study tested the measurement invariance of the Child Problematic Traits Inventory (CPTI), a teacher-rated scale designed to assess psychopathic traits from ages 3 to 12 years. Data were drawn from a Swedish population-based sample of 2,121 children followed longitudinally across 8 years from early to late childhood. Results from confirmatory factor analyses and multigroup invariance analyses showed an excellent fit of the theoretically proposed three-factor model of the CPTI and supported the scalar invariance hypothesis of this model across sexes at all assessment time points. Longitudinal invariance analyses further supported the hypothesis of scalar invariance of the three-factor model across the study design, hence suggesting that dimension scores can be reliably compared across this period. These results substantially add to previous psychometric evaluations of the CPTI by suggesting that assessments of psychopathic traits using the CPTI confer a metric that is comparable both across sexes and from early childhood to late childhood. Implications for future longitudinal studies aimed at understanding the developmental origins of these traits are discussed. (PsycInfo Database Record (c) 2026 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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".