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Record W4415913116 · doi:10.1177/10731911251385843

Examining the Within- and Between-Person Structure of Callous-Unemotional Traits in Adolescents and Young Adults in Daily Life

2025· article· en· W4415913116 on OpenAlexafffund
Hao Zheng, Yao Zheng

Bibliographic record

VenueAssessment · 2025
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsMultilevel modellingYoung adultReliability (semiconductor)Multilevel modelLongitudinal studyPsychometricsMeasurement invariance

Abstract

fetched live from OpenAlex

Intensive longitudinal designs have been used to examine the fluctuations of callous-unemotional (CU) traits and their dynamic links with daily correlates; however, scant research has explored how CU traits manifest in daily contexts at the within-person level. This study evaluated the multilevel factor structure and psychometric properties of a short version of the Inventory of CU Traits in daily contexts among adolescents ( n = 99, 2,132 daily reports) and young adults ( n = 313, 6,431, and 4,018 daily reports at each wave). Both bifactor and correlated-factor models showed acceptable fit and reliability at the within- and between-person levels, though the general factor in the bifactor model demonstrated low reliability in university students. Longitudinal measurement invariance was supported among university students over a 2.5-year period, while structural differences emerged between the two samples. Findings highlight meaningful within-person fluctuations in daily CU traits. Future studies should evaluate the applicability of different factor models for a more accurate assessment across age groups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.316
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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