Is Poor Sleep Quality at High Altitude Separate from Acute Mountain Sickness? Factor Structure and Internal Consistency of the Lake Louise Score Questionnaire
Bibliographic record
Abstract
MacInnis, Martin J., Shawnda C. Lanting, Jim L. Rupert, and Michael S. Koehle. Is poor sleep quality at high altitude separate from acute mountain sickness? Factor structure and internal consistency of the Lake Louise Score Questionnaire. High Alt Med Biol 14:334–337, 2013.—Background: The factor structure and internal consistency of the Lake Louise Score Questionnaire (LLSQ) have not been determined in a large population at high altitude; however, a single-factor structure and a high internal consistency are preferable for accurate clinical and research applications of the LLSQ. Methods: A large group of Nepalese pilgrims (n=491) were assessed for acute mountain sickness with a verbal Nepali translation of the LLSQ after rapidly ascending from 1950 m to 4380 m. The factor structure and internal consistency of the LLSQ were determined with a confirmatory factor analysis (CFA) and the ordinal alpha coefficient, respectively. Results: A one-factor structure with all five items of the LLSQ was accepted. Four items (headache, gastrointestinal upset, fatigue/weakness, and dizziness/lightheadedness) loaded strongly on this factor (>0.70), but sleep quality had a low factor loading (0.33). The internal consistency (ordinal alpha coefficient) was 0.79, but removing the sleep quality item improved this value to 0.84. Conclusions: The sleep quality item of the LLSQ was weakly related to the other items of the LLSQ. Future research should further investigate whether impaired sleep at altitude should be considered separately from other symptoms of AMS.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".