An overview of patient adherence to asthma medication in Canada
Bibliographic record
Abstract
Introduction: Despite national management guidelines and advances in treatment, many asthma patients remain uncontrolled in Canada. Patient adherence is known to be a key contributor to effective asthma management. Objective: To assess patterns of asthma medication adherence in Canada Methods: A literature search was performed in PubMed, Embase and EMCare to identify published English literature from 2000 to 2011 related to patient adherence to asthma medication in Canada. Titles and abstracts were screened by 2 independent reviewers in a 2-step process to select articles that met the inclusion criteria. Study quality was assessed using methodological checklists, and data abstracted to form the basis of the review. Results: 7 of 270 studies identified met selection criteria and were included in this review: 4 cohorts, 1 cross-sectional, 1 RCT, and 1 qualitative study. Different methods of measuring medication adherence such as persistence rates and mean proportion of prescription days were presented. The review found that adults took 72% of their inhaled corticosteroids (ICS) prescriptions. The data also showed that only 13% and 11% of patients were still using ICS and long-acting b-agonists (LABA), respectively, 1 year after therapy initiation. Overall ICS adherence in children aged 5-16, from 1997 to 2002, was shown to be 62.4% and decreased to 36.8% in children with ≥7 prescriptions. Predictors of increased adherence included: increasing age and use of fixed-dose combinations. Presence of oropharyngeal symptoms decreased compliance. Conclusions: Despite differences in measurement of adherence, all 7 studies consistently found inadequate adherence of asthma medication among all patient groups in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.028 | 0.055 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".