Factors Associated with the Appropriate Use of Asthma Drugs
Bibliographic record
Abstract
BACKGROUND: When used properly, asthma drugs can reduce asthma-related morbidity and mortality. OBJECTIVE: To assess the use of asthma drugs, and to identify factors associated with appropriateness of use among patients 12 to 45 years of age. METHODS: Asthmatic patients were interviewed about their asthma drug(s) use and the factors potentially associated with appropriateness of use according to the 2003 Canadian Asthma Consensus Conference guidelines. To determine the factors associated with the appropriate use of asthma drugs, a multivariate logistic regression model was built using a stepwise procedure, and ORs and associated 95% CIs were calculated. RESULTS: Of the 349 study participants, 43 (12.3%) reported appropriate use of their asthma drugs. Respondents who were more likely to report appropriate use were patients with sound knowledge of their asthma drugs (OR 2.61 [95% CI 1.29 to 5.29]), those in good, very good or excellent self-perceived health (OR 3.37 [95% CI 1.31 to 8.71]), those who had consulted a specialist during the preceding year (OR 2.28 [95% CI 1.05 to 4.97]) and those who declared themselves short of drugs due to a lack of money (OR 2.78 [95% CI 1.26 to 6.17]). CONCLUSIONS: Results of the present study suggested that recommendations in the current guidelines regarding the appropriate use of asthma medications are being poorly implemented. Educational interventions with the aim of improving quality of care and knowledge about asthma drugs should be offered.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".