Chinese self-report version of biological rhythms interview for assessment in neuropsychiatry (C-BRIAN-SR) - psychometric properties and prospective follow-up in patients with non-seasonal depression
Bibliographic record
Abstract
This study examined the psychometric properties and longitudinal changes of the self-reporting Traditional Chinese version of Biological Rhythms Interview for Assessment in Neuropsychiatry (C-BRIAN-SR) among healthy controls (HC) and patients with major depressive episode (MDE). Eighty patients with a current MDE and 80 HC were recruited. Assessments were repeated after two weeks in HC, and upon the discharge of MDE patients to examine the prospective changes upon remission of depression. The C-BRIAN-SR score was significantly higher in the MDE than HC group. The concurrent validity was supported by a positive correlation between scores of C-BRIAN-SR, Insomnia Severity Index and the Hospital Anxiety Depression Scale. C-BRIAN-SR negatively correlated MEQ in the MDE group (r = .30, p = 0.009), suggesting higher rhythm disturbances were associated with a tendency toward eveningness. A moderate test-retest reliability was found (r = .61, p < 0.001). A cut-off of 38.5 distinguished MDE subjects from HC with 82.9% of sensitivity and 81.0% of specificity. C-BRIAN-SR score normalized in remitted MDE patients but remained higher in the non-remitted. The C-BRIAN-SR is a valid and reliable scale for measuring the biological rhythms and may assist in the screening of patients with MDE.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".