Psychometric evaluation of the Chinese version of the Toronto Hospital Alertness Test
Bibliographic record
Abstract
BACKGROUND: Alertness is an important part of attention which is different from the opposite of sleepiness. This study aimed to translate and assess the measurement properties of the Toronto Hospital Alertness Test (THAT) in Hong Kong Chinese population. METHODS: The standard forward-backward translation procedure and cognitive debriefing were conducted to obtain the Chinese THAT. One hundred Chinese adults completed the Chinese THAT, the Center for Epidemiological Studies Depression Scale (CES-D), the Pittsburgh Sleep Quality Index (PSQI), and the Athens Insomnia Scale (AIS) by telephone interviews. RESULTS: The factorial validity was assessed by confirmatory factor analysis, and the internal reliability was examined by coefficient omega. The two negatively worded items of the THAT had low factor loadings and were removed. One more item was removed based on the modification indices of the eight-item model. The remaining seven-item THAT showed satisfactory unidimensionality with root mean square error of approximation (RMSEA) = 0.06, standardized root mean square residual (SRMR) = 0.08, and comparative fit index (CFI) = 1.00. The coefficient omega of the seven-item Chinese THAT was 0.80 (95% CI: 0.74-0.86). Convergent validity was demonstrated with THAT moderately associated with CES-D (r = - 0.45, P < 0.01), PSQI (r = - 0.40, P < 0.01), and AIS (r = - 0.45, P < 0.01). CONCLUSIONS: The Chinese version of THAT demonstrated acceptable reliability and validity in a Chinese population.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".