Japanese Version of the Eyberg Child Behavior Inventory: Translation and Validation<sup>1</sup>
Bibliographic record
Abstract
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.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".