The Toronto Hospital Alertness Test scale: relationship to daytime sleepiness, fatigue, and symptoms of depression and anxiety
Bibliographic record
Abstract
OBJECTIVE: The Toronto Hospital Alertness Test (THAT) scale was designed to measure alertness, defined as the capacity of the mind to respond appropriately to external and internal stimuli. The present study's aim is to determine normative values of alertness on the THAT and to explore the relationship among excessive daytime sleepiness, fatigue, depressive symptoms, and alertness. METHODS: Normative data were collected from 60 healthy males and females. To explore the relationship among alertness, daytime sleepiness, fatigue, depression, and anxiety, data were collected from charts of sleep clinic patients. All study subjects completed measures for fatigue, sleepiness, depressive symptoms, and anxiety. RESULTS: The average score on the THAT was 34.9±7.2 (range 22-50) for the control group. The cutoff score for the THAT, indicative of clinically significant reduced alertness, was determined to be ≤20.5 (mean -2 SD). THAT alertness scores were found to be modestly, significantly, and negatively correlated with fatigue levels (r=-0.39, P<0.001), depressive symptoms (r=-0.53, P<0.001), and anxiety symptoms (r=-0.41, P<0.001). No correlations were found between alertness levels and daytime sleepiness. Regression analyses revealed a significant model (F=19.9, P<0.001, adjusted R (2)=0.35) with depressive symptoms (P<0.001) and fatigue (P=0.006) emerging as the only significant predictors of scores on the THAT. CONCLUSION: The findings of this study support that sleepiness is not the same as poor alertness. Depressive symptoms and fatigue, but not sleepiness, were found to have a strong and significant impact on levels of alertness. This is the first study to link poor alertness to depressive symptoms.
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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 | 0.003 |
| 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) | 0.002 | 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".