Validation of the Korean Version of the Biological Rhythms Interview of Assessment in Neuropsychiatry
Bibliographic record
Abstract
OBJECTIVE: The Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN) is a scale used to clinically evaluate disturbances in biological rhythm. In this study, we aimed to examine the reliability and validity of the Korean version of the BRIAN (K-BRIAN) in a Korean population. METHODS: A total of 181 participants, including 141 outpatients with bipolar disorder (BD; type I, 62; type II, 79) and 40 controls, were recruited. Construct validity was tested by comparing the mean K-BRIAN scores of the BD patients and control subjects. Concurrent validity was tested by evaluating the association between the K-BRIAN and the Morningness-Eveningness Questionnaire (MEQ). RESULTS: The mean K-BRIAN scores of the control subjects and patients with BD differed significantly (p<0.001). Particularly, the mean K-BRIAN score was considerably lower among control subjects (mean±standard deviation=35.00±8.88) than among patients with BD type I (41.19±12.10) and type II (50.18±13.73). The Cronbach's alpha for the K-BRIAN was 0.914. The K-BRIAN was found to correlate with the MEQ (r=-0.45, p<0.001). CONCLUSION: The findings affirm that the K-BRIAN has good construct validity and internal consistency. This suggests that the K-BRIAN can be used to assess biological rhythms in the Korean population, especially for patients with mood disorder.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".