Relationship between quality of life and clinical status in asthma: a factor analysis
Bibliographic record
Abstract
Many studies have shown that correlation between clinical asthma status and asthma-specific quality of life is only weak to moderate. However, this relationship has never been explored to determine whether the weakness is due to noise of measurement or whether quality of life is a distinct component of asthma health status. With a database from three clinical trials (n = 763), factor analysis was used to explore the relationships between quality of life, measured by the Asthma Quality of Life Questionnaire (AQLQ), and conventional measures of asthma clinical status (symptoms, airway calibre and rescue beta2-agonist use). The analysis revealed that although patients with severe, poorly controlled asthma tend to have worse quality of life than milder, well-controlled patients, overall asthma health status has four components (factors): asthma-specific quality of life; airway calibre; daytime symptoms and daytime beta2-agonist use, and night-time symptoms and night-time beta2-agonist use. The clean loading of all 21 outcomes onto four distinct and clinically identifiable factors suggests that, although some weakness of correlation between clinical indices and quality of life may be due to noise of measurement, it is mainly attributable to asthma health status being composed of distinct components.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".