Nonrestorative sleep scale: a reliable and valid short form of the traditional Chinese version
Bibliographic record
Abstract
PURPOSE: Previous research has suggested the essential unidimensionality of the 12-item traditional Chinese version of the Nonrestorative Sleep Scale (NRSS). This study aimed to develop a short form of the traditional Chinese version of the NRSS without compromising its reliability and validity. METHODS: Data were collected from 2 cross-sectional studies with identical target groups of adults residing in Hong Kong. An iterative Wald test was used to assess differential item functioning by gender. Based on the generalized partial credit model, we first obtained a shortened version such that further shortening would result in substantial sacrifice of test information and standard error of measurement. Another shortened version was obtained by the optimal test assembly (OTA). The two shortened versions were compared for test information, Cronbach's alpha, and convergent validity. RESULTS: Data from a total of 404 Chinese adults (60.0% female) who had completed the Chinese NRSS were gathered. All items were invariant by gender. A 6-item version was obtained beyond which the test performance substantially deteriorated, and a 9-item version was obtained by OTA. The 9-item version performed better than the 6-item version in test information and convergent validity. It had discrimination and difficulty indices ranging from 0.44 to 2.23 and - 7.58 to 2.13, respectively, and retained 92% of the test information of the original 12-item version. CONCLUSION: The 9-item Chinese NRSS is a reliable and valid tool to measure nonrestorative sleep for epidemiological studies.
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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 | 0.001 |
| 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) | 0.004 | 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".