Effectiveness of an asthma integrated care program on asthma control and adherence to inhaled corticosteroids
Bibliographic record
Abstract
Objective: To measure the effectiveness of an integrated care program for individuals with asthma aged 12–45 years, on asthma control and adherence to inhaled corticosteroids (ICS). Methods: Researchers used a theoretical model to develop the program and assessed effectiveness at 12 months, using a pragmatic controlled clinical trial design. Forty-two community pharmacists in Quebec, Canada recruited participants with either uncontrolled or mild-to-severe asthma. One group was exposed to the program; another received usual care. Asthma control was measured with the Asthma Control Questionnaire; ICS adherence was assessed with the Morisky medication adherence scale and the medication possession ratio. Program effectiveness was assessed with an intention-to-treat approach using multivariate generalized estimating equation models. Results: Among 108 exposed and 241 non-exposed, 52.2% had controlled asthma at baseline. At 12-months, asthma control had improved in both groups but the interaction between study groups and time was not significant (p = 0.09). The proportion of participants with good ICS adherence was low at baseline. Exposed participants showed improvement in adherence and the interaction between study groups and time was significant (p = 0.02). Conclusion: An integrated intervention, with healthcare professionals collaborating to optimize asthma control, can improve ICS adherence.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".