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Record W3167810074 · doi:10.1111/jpr.12365

Japanese Version of the Eyberg Child Behavior Inventory: Translation and Validation<sup>1</sup>

2021· article· en· W3167810074 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJapanese Psychological Research · 2021
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsSKiN Health
Fundersnot available
KeywordsCBCLBeck Depression InventoryPsychologyCronbach's alphaClinical psychologyInternal consistencyReliability (semiconductor)Construct validityPsychometricsPsychiatryAnxiety

Abstract

fetched live from OpenAlex

Abstract This study assessed the psychometric properties of the Japanese version of the Eyberg Child Behavior Inventory (ECBI) in children in clinical and non‐clinical settings in Japan. Validation of the ECBI for clinical and non‐clinical participants ( N = 128, 2–7 years of age) was evaluated. First, we evaluated the internal consistency reliability of the ECBI Problem and Intensity scales. We evaluated the construct and criterion‐referenced validity by comparing scores among the subscales of the ECBI, Child Behavior Checklist (CBCL), and Japanese versions of the Parenting Stress Index‐Short Form (PSI‐SF) and the Beck Depression Inventory‐II (BDI‐II). Results showed that Cronbach's alphas for both the Intensity and Problem scores were .91 and .92, respectively, which reflects high internal consistency. Results also showed that both the ECBI Intensity and Problem scores were significantly correlated with all subscales of the CBCL, PSI‐SF, and BDI‐II. These data suggest that the Japanese version of the ECBI is a psychometrically sound measure for assessing behavior problems in Japanese children.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.118
GPT teacher head0.396
Teacher spread0.278 · 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