Use of focus groups to assess the educational needs of the primary care physician for the management of asthma
Bibliographic record
Abstract
OBJECTIVES: To determine the educational needs of primary care physicians, in the management of patients with asthma. DESIGN: Focus group discussions with physicians, pharmacists, respiratory therapists and patients. SETTING: Metropolitan Edmonton, Alberta, Canada. PARTICIPANTS: Out of an original mail request to 100 potential recruits, 52 people attended the focus group sessions. These included physicians, pharmacists, respiratory therapists, adult patients and paediatric patients accompanied by their parents. MAIN OUTCOME MEASURE: Consensus of the specific group being interviewed using facilitator-mediated responses, to identify problems in the care of asthma patients and appropriate educational methods to improve the situation. RESULTS: Both diagnostic and treatment concerns were identified by the primary care physicians and others in the study. Confusion with infection was the most common diagnostic problem. Major treatment problems involved confusion about aspects of management strategy and a lack of communication between physicians, patients and other members of the health care team. Poor patient compliance and patients changing doctors frequently were also of major concern. There were inconsistencies in the treatment of asthma between physicians. While most physicians felt that they were up-to-date in management, Asthma Control Guidelines were seldom followed. CONCLUSIONS: There is an urgent need for continuing medical education, not only in management but also in communication with patients and with other members of the health care team. The data permit the development of an ongoing educational programme which is practical and designed to deal with the issues identified in this survey.
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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 | 0.028 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".