Maltreatment and parenting in youth with primary and secondary callous‐unemotional traits: Anxiety matters
Bibliographic record
Abstract
Background: Youth with conduct disorder (CD) and high callous-unemotional (CU) traits are not a homogenous group and can be disaggregated into primary and secondary subgroups. However, there are inconsistencies in defining primary and secondary subgroups, with some studies using anxiety, others using maltreatment and still others using both features to identify subgroups. There is a paucity of work comparing primary and secondary subgroups with typically developing (TD) youth on experiences of maltreatment and parenting as well as a lack of studies investigating sex differences. Methods: = 885, 60% female), we used latent profile analysis in youth with CD aged between 9 and 18 years to address four aims: (i) to demonstrate how primary and secondary subgroup membership differs when anxiety, maltreatment, or both are used as continuous indicators, (ii) to compare primary and secondary subgroups with TD youth on abuse and neglect measures, and (iii) to compare primary and secondary subgroups with TD youth on parenting experiences, and (iv) to examine whether the results were consistent across sexes. Results: values >0.05). Conclusions: We provide evidence that anxiety and maltreatment cannot be used interchangeably to identify youth with primary versus secondary CU traits. Anxiey yielded the best fitting and most theoretically interpretable classifications across both sexes. Our results signify the need for researchers and clinicians to adopt a unified approach to defining primary and secondary subgroups of CU traits using anxiety in both sexes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".