Insights, attitudes, and perceptions about asthma and its treatment: a multinational survey of patients from Europe and Canada
Bibliographic record
Abstract
BACKGROUND: Asthma surveys completed within the past 10 years in the Americas and the Asia-Pacific region have shown significant underassessment of asthma severity in addition to undertreatment of asthma and have suggested the need to improve long-term asthma management. In this study, we examined the frequency of asthma symptoms and severe episodes, patients' perceived asthma control, and use of asthma medications in Europe and Canada. METHODS: The Asthma Insight and Management survey (54 questions) was conducted in Europe (Germany, Italy, Spain and the United Kingdom) and Canada from June 14 through July 28, 2010. Telephone interviews were conducted with randomly screened patients or parents of adolescents (aged 12-17 years) with asthma; patients younger than 12 years of age were excluded from the survey. Responses were reported separately for each country and in total for all five countries. RESULTS: Seventy-five thousand three hundered thirty-five households were screened, and 2003 patients were interviewed. The survey respondents represented a wide range of severity. Overall, 26 % of patients reported symptoms daily or most days over the past 4 weeks, but most patients (81 %) perceived their asthma to be well or completely controlled. Over the past year, 41 % of patients had episodes of frequent/severe symptoms, and 50 % reported acute treatment (e.g. hospitalization, emergency visit, unscheduled physician visit) for asthma. Across countries, 52 % of patients reported taking controller medication every day over the past year, 27 % reported not taking any controller medication, and 14 % reported stopping controller treatment for 3 months or longer the last time they stopped. Many patients considered asthma well controlled if each year they had only two urgent doctor visits (50 %), three or four exacerbations (60 %), and/or one emergency room visit (41 %). DISCUSSION: This is the largest survey of patients with asthma in Europe and Canada in more than a decade. CONCLUSION: In 2010, many surveyed patients in Europe and Canada reported features indicating uncontrolled asthma, yet the majority believed they were well controlled, indicating that they had low expectations of long-term asthma management. Use of controller medications was substantially less than recommended in treatment guidelines.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".