The semi-structured interview for bipolar at-risk states (SIBARS): psychometric properties and validation
Bibliographic record
Abstract
Background Established psychometric instruments to detect individuals at high-risk of bipolar disorders (BD) are essential to advance preventive approaches. Methods The Semi-structured Interview for Bipolar At-Risk States (SIBARS)’s psychometric properties were evaluated through: (i) dimensionality (confirmatory factor analysis, CFA); (ii) reliability (internal/inter-rater reliability); and (iii) validity in terms of convergent validity (Hamilton Depression Rating Scale, HAM-D, Mini-International Neuropsychiatric Interview, MINI; Temperament Evaluation of Memphis, Pisa, and San Diego Autoquestionnaire, TEMPS-A; Young Mania Rating Scale, YMRS), divergent validity (Comprehensive Assessment of At-Risk Mental States, CAARMS; Hamilton Anxiety Rating Scale, HAM-A), concurrent criterion validity (Bipolar Prodrome Symptom Interview and Scale–Abbreviated Screen for Patients, BPSS-AS-P). Results A total of 193 participants were included. The CFA for depression plus mania showed excellent data fit (Root Mean Square Error Approximation = 0.02). Internal (Cronbach's α = 0.90; McDonald's ω = 0.96) and inter-rater (Intra-class Correlation Coefficient = 0.97) reliability were excellent. Convergent validity was confirmed by moderate-to-strong associations between the SIBARS mania scale and the YMRS ( β = 0.49, p < 0.001), the SIBARS depression scale and the HAM-D ( β = 0.54, p < 0.001), and the SIBARS cyclothymic temperament scale and the TEMPS-A ( β = 0.69 p < 0.001). Divergent validity was evidenced by very weak associations between SIBARS and CAARMS' outcomes ( χ 2 = 4.14, p = 0.042, phi = 0.15) or the HAM-A ( r = 0.16, p = 0.025). Concurrent validity was indexed by a significant association of SIBARS' researcher-based ratings and BPSS-AS-P participant-based ratings ( r = 0.23, p = 0.001). Limitations. The cross-sectional design did not allow to test predictive validity. Conclusions There is convincing psychometric evidence supporting the SIBARS as a reliable and valid instrument for detecting individuals at clinical high-risk of BD.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".