The Associations between Callous-unemotional Traits and Symptoms of Conduct Problems, Hyperactivity and Emotional Problems: A Study of Adolescent Twins Screened for Neurodevelopmental Problems
Bibliographic record
Abstract
Callous-unemotional (CU) traits (e.g., lack of empathy, lack of guilt, shallow affect) are associated with severe and persistent conduct problems in youth. There is evidence showing a substantial genetic correlation between CU traits and conduct problems. The etiological associations between CU traits and other psychopathological symptoms, including symptoms of hyperactivity and emotional problems (such as anxiety and depression symptoms), have been less explored. To examine the etiological associations between CU traits and symptoms of conduct problems, hyperactivity and emotional problems separately through the use of a twin design. Participants were same-sex twin pairs (n = 426 twins; 42% female; 43% MZ; age = 15) drawn from the Child and Adolescents Twin Study in Sweden, a longitudinal study of twins born in Sweden. The sample was mainly composed of children who screenpositive on neurodevelopmental problems/mental health problems or at-risk children (i.e., screen-negative children considered to be genetically at-risk siblings). We used self-report measures of CU traits, conduct problems, hyperactivity and emotional problems. Model-fitting analyses were conducted using structural equation modeling. We found a strong positive genetic correlation between CU traits and conduct problems and a moderate genetic correlation between CU traits and hyperactivity. We also found a relatively modest, but significant negative genetic correlation between CU traits and emotional problems. Using a sample of adolescent twins screened for neurodevelopmental problems, we replicated previous findings that showed a strong genetic correlation between CU traits and conduct problems and we extended research by examining further the etiological associations between CU traits and symptoms of hyperactivity and emotional problems.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".