The reliability and validity of the Japanese version of the Levels of Emotional Awareness Scale (LEAS-J)
Bibliographic record
Abstract
BACKGROUND: The Levels of Emotional Awareness Scale (LEAS) was developed to assess five levels of emotional awareness: bodily sensations, action tendencies, single emotions, blends of emotion, and combinations of blends. It is a paper and pencil performance questionnaire that presents 20 emotion-evoking scenes. We developed a Japanese version of the LEAS (LEAS-J), and its reliability and validity were examined. METHODS: The LEAS-J level was independently assessed by two researchers who scored each response according to the LEAS scoring manual. High inter-rater reliability and internal consistency were obtained for the LEAS-J. Measures were socioeconomic status, LEAS-J, Toronto Alexithymia Scale-20 (TAS-20), Interpersonal Reactivity Index (IRI), and NEO Five-Factor Inventory (NEO-FFI). TAS-20, IRI and NEO-FFI were the measures used to explore the construct validity of LEAS-J, as it was predicted that higher scores on the LEAS-J would be related to fewer alexithymic features, greater empathetic ability, and a greater sense of cooperation with others. Questionnaires were completed by 344 university students. RESULTS: The criterion-referenced validity was determined: a significant negative relationship was found with the externally-oriented thinking scores of TAS-20, and positive relationships were found with fantasy, perspective taking, and empathic concern on IRI and with extraversion, openness to experience, and agreeableness on NEO-FFI. CONCLUSIONS: Consistent with our expectations, the findings provide evidence that the LEAS-J has good reliability and validity. In addition, women had significantly higher scores than men on LEAS-J, showing that the gender difference identified in the original LEAS was cross-culturally consistent.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".