Assessment of the Affective Dimensions of Psychopathy with the Danish version of the Inventory of Callous-Unemotional Traits among Incarcerated Boys: A study of Reliability, Criterion Validity, and Construct Validity
Bibliographic record
Abstract
Abstract Background: Callous-unemotional (CU) traits have been found to index an important subgroup of antisocial youth who are at high risk for developing psychopathic personality pathology, and for becoming severe and persistent offenders. On the basis of such research findings, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition , have included a “with limited prosocial emotions” specifier in the diagnostic criteria for conduct disorder to designate a subtype with high levels of CU traits. This creates the need for psychometrically sound measures for the assessment of these traits. The self-report questionnaire Inventory of Callous-Unemotional Traits (ICU) was designed to provide an efficient, reliable, and valid measure of CU traits among youth populations. Method: Eighty Danish adolescent boys between the ages of 15 to 18 years in secure institutions were assessed concurrently with the ICU, the Psychopathy Checklist: Youth Version (PCL:YV), self-report measures of aggression and empathy, and ratings of psychosocial problems. Approximately nine days later, the ICU was readministered in a subset of the sample ( n = 40) to examine test-retest reliability. Results: Internal consistency was satisfactory, and test-retest reliability was excellent. Concurrent validity associations with the PCL:YV ranged from moderate to high. The ICU displayed excellent discriminative validity for identifying persons who displayed high levels of psychopathic traits. CU traits were also found to be associated with psychosocial impairments, aggression, and reduced empathy. Conclusions: Overall, these findings support the reliability; construct validity, and criterion validity of the ICU.
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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 | 0.002 | 0.005 |
| 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 | 0.000 | 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".