Evaluation of Two Different Educational Interventions for Adult Patients Consulting with an Acute Asthma Exacerbation
Bibliographic record
Abstract
Asthma education decreases the number of emergency visits in specific subgroups of patients with asthma. However, it remains unknown whether this improvement is related only to the use of an action plan alone or to other components of the educational intervention. A total of 126 patients consulting urgently for an acute asthma exacerbation were recruited; 98 completed the study. The first 45 patients were assigned to Group C (control; usual treatment). Thereafter, patients were randomized to either Group LE (limited education; teaching of the inhaler technique plus self- action plan given by the on call physician) or Group SE (same as group LE plus a structured educational program emphasizing self-capacity to manage asthma exacerbations). At baseline, there was no difference between groups in asthma morbidity, medication needs, or pulmonary function. After 12 mo, only Group SE showed a significant improvement in knowledge, willingness to adjust medications, quality of life scores, and peak expiratory flows. In the last 6 mo, the number of unscheduled medical visits for asthma was significantly lower in Group SE in comparison with groups C and LE (p = 0.03). The number (%) of patients with unscheduled medical visits also decreased significantly in Group SE compared with Groups C and LE (p = 0.02). We conclude that a structured educational intervention emphasizing self-management improves patient outcomes significantly more than a limited intervention or conventional treatment.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".