Assessing the psychometric properties of the <scp>Biphasic Sleep Scale</scp> ( <scp>BiSS</scp> ): A novel 16‐item self‐report measure
Bibliographic record
Abstract
Biphasic sleep, characterized by nighttime sleep plus daytime napping, has demonstrated some cognitive, health and performance impacts when compared with consolidated monophasic sleep. This motivated the development and validation of the Biphasic Sleep Scale, reported in this paper. Scale development involved a literature review, expert input and individual interviews. The 16-item Biphasic Sleep Scale was then administered to an international online sample (n = 6965) alongside well-established validated sleep scales. To ensure a robust evaluation of the Biphasic Sleep Scale, the sample was divided into two parts: with 15% (n = 1000) of the participants allocated to the exploratory analytic phase; and the remaining 85% (n = 5965) reserved for confirmatory analyses. Psychometric evaluation included both exploratory and confirmatory factor analysis, reliability analysis, correlations, network analysis, and item response theory. Exploratory factor analysis indicated a three-factor structure assessing daytime napping as to likelihood, consequences and effect on nighttime sleep. Confirmatory factor analysis largely confirmed this model with no sex invariance. The three-factor structure showed adequate fit. The Biphasic Sleep Scale demonstrated good internal consistency (α = 0.88, Ω = 0.89). Network analysis revealed varying centrality and connectivity of items. Item response theory found items covering a range of biphasic sleep levels. Significant positive correlations with sleep criteria provided evidence for convergent validity. Further testing is warranted to confirm the factor structure, refine model parsimony, and establish clinical utility. With additional validation, it is hoped that the Biphasic Sleep Scale will become a widely utilized tool.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".