Assessing a population-based approach to the management of respiratory disease
Bibliographic record
Abstract
The prevalence of respiratory disease (asthma, allergies and COPD) has increased dramatically in the last 25 years, with a heavy economic and social burden. Provision of information is recognized as a means to improve patient knowledge and self-management skills, and can overall result in improved disease management and quality of life. The Partnership in Lung Age Testing and Education (PLATE) Programme was a one-year demonstration project designed to investigate the effectiveness of a population-based approach to the management of respiratory disease. The PLATE objectives were: to improve patient education and disease management skills; increase public awareness about respiratory disease; and promote a healthy lifestyle. During phase one, 13 Airways Clinics were established in Toronto and Hamilton at various community settings (e.g. pharmacies, shopping malls, libraries), providing community residents with respiratory health education, which aimed to improve the implementation of best practices for chronic disease management through clinical assessments, peak flow testing, and follow-up with regular health care providers. Project participants were categorized into three groups: 1) with physician-diagnosed asthma (61%); 2) with physician-diagnosed COPD (11%); and 3) with respiratory symptoms, but without a diagnosis and/or long-time smokers (28%). More than half (60%) of the participants were female; over 75% were over the age of 40 years. Participants were provided with an educational kit to encourage ongoing education for management of their chronic disease. Phase two is currently under-way and includes a community outreach component, in addition to a follow-up survey to examine changes in the levels of knowledge gained from phase one. Despite the small sample size (87 participants), findings indicate that the highest level of interest came from high-needs communities, and that pharmacies are the most appropriate setting within which to host clinics, while shopping malls are best for information displays. More research is needed to confirm these findings.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".