Development and use of a Biological Rhythm Interview
Bibliographic record
Abstract
Introduction: As several lines of evidence point to irregular biological rhythms in bipolar disorder, and its disruption may lead to new illness episodes, having an instrument that measures biological rhythms is critical. This report describes the validation of a new instrument, the Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN), designed to assess biological rhythms in the clinical setting. Methods: Eighty-one outpatients with a diagnosis of bipolar disorder and 79 control subjects matched for type of health service used, sex, age and educational level were consecutively recruited. After a pilot study, 18 items evaluating sleep, activities, social rhythm and eating pattern were probed for discriminant, content and construct validity, concurrent validity with the Pittsburgh Sleep Quality Index (PSQI), internal consistency and test-retest reliability. Results: A three-factor solution, termed sleep/ social rhythm factor, activity factor and feeding factor, provided the best theoretical and most parsimonious account of the data; items essentially loaded in factors as theoretically intended, with the exception of the sleep and social scales, which formed a single factor. Test-retest reliability and internal consistency were excellent. Highly significant differences between the two groups were found for the whole scale and for each BRIAN factor. Total BRIAN scores were highly correlated with the global PSQI score. Discussion: The BRIAN scale presents a consistent profile of validity and reliability. Its use may help clinicians to better assess their patients and researchers to improve the evaluation of the impact of novel therapies targeting biological rhythm pathways.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".