Genetic and environmental aetiology of the dimensions of Callous-Unemotional traits
Bibliographic record
Abstract
BACKGROUND: A Callous-Unemotional trait specifier (termed 'Limited Prosocial Emotions') was added to the diagnosis of conduct disorder in DSM-5. The Inventory of Callous-Unemotional Traits (ICU) is a comprehensive measure of these traits assessing three distinct, yet correlated dimensions--Callousness, Uncaring, and Unemotional--all thought to reflect the general Callous-Unemotional construct. The present study was the first to examine the degree to which the aetiology of these dimensions is shared v. independent. METHOD: Parent-reported ICU data from 5092 16-year-old twin pairs from the Twins Early Development Study were subjected to confirmatory factor analysis. Multivariate genetic modelling was applied to the best-fitting structure. RESULTS: A general-specific structure, retaining a general factor and two uncorrelated specific factors (Callousness-Uncaring, Unemotional), provided the best fit to the data. The general factor was substantially heritable (h2 = 0.58, 95% CI 0.51-0.65). Unusually, shared environmental influences were also important in accounting for this general factor (c2 = 0.26, 95% CI 0.22-0.31), in addition to non-shared environmental influences. The Unemotional dimension appeared phenotypically and genetically distinct as shown by the substantial loadings of unemotional items on a separate dimension and a low genetic correlation between Unemotional and Callousness-Uncaring. CONCLUSIONS: A general factor, indicative of a shared phenotypic structure across the dimensions of the ICU was under substantial common genetic and more modest shared environment influences. Our findings also suggest that the relevance of the Unemotional dimension as part of a comprehensive assessment of CU traits should be investigated further.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".