Rasch Analysis of the Chinese Version of the Nociception Coma Scale–Revised in Patients with Prolonged Disorders of Consciousness
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to analyze the Chinese version of the Nociception Coma Scale-Revised in patients with prolonged disorders of consciousness within the framework of Rasch modeling, including investigating the invariance of total scores across different etiologies of disorders of consciousness. DESIGN: Prospective psychometric study. PARTICIPANTS: Patients with prolonged disorders of consciousness from the Rehabilitation and Neurology units in hospital. INTERVENTIONS: None. MAIN OUTCOME MEASURE: The Nociception Coma Scale-Revised was undertaken by trained raters and the Coma Recovery Scale-Revised was used to assess patients' consciousness. The psychometric properties within the Rasch model including item-person targeting, reliability and separation, item fit, unidimensionality, and differential item functioning were assessed. RESULTS: 84 patients with prolonged disorders of consciousness (mean age 53 years; mean injury 5 months; 42 with Minimally Conscious State and 42 with Unresponsive Wakefulness Syndrome) of 252 observations were enrolled in the study. Through the procedure of repeated assessment and differential item function, a lower item bias Rasch set was purified. The Rasch model assumptions were examined and met, with item reliability and validity meeting the recommended threshold. CONCLUSIONS: The Chinese version of the Nociception Coma Scale-Revised demonstrated unidimensionality, good reliability and separation, and good item fit, but dissatisfied person fit and item-person targeting. The verbal subscale showed a notable discrepancy between person responses and the difficulty of the items, suggesting limited clinical significance.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".