Empowering Family Physicians to Impart Proper Inhaler Teaching to Patients with Chronic Obstructive Pulmonary Disease and Asthma
Bibliographic record
Abstract
BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) and asthma depend on inhalers for management, but critical errors committed during inhaler use can limit drug effectiveness. Outpatient education in inhaler technique remains inconsistent due to limited resources and inadequate provider knowledge. OBJECTIVE: To determine whether a simple, two-session inhaler education program can improve physician attitudes toward inhaler teaching in primary care practice. METHODS: An inhaler education program with small-group hands-on device training was instituted for family physicians (FP) in British Columbia and Alberta. Sessions were spaced one to three months apart. All critical errors were corrected in the first session. Questionnaires surveying current inhaler teaching practices and attitudes toward inhaler teaching were distributed to physicians before and after the program. RESULTS: Forty-one (60%) of a total 68 participating FPs completed both before and after program questionnaires. Before the program, only 20 (49%) reported providing some form of inhaler teaching in their practices, and only four (10%) felt fully competent to teach patients inhaler technique. After the program, 40 (98%) rated their inhaler teaching as good to excellent. Thirty-four (83%) reported providing inhaler teaching in their practices, either by themselves or by an allied health care professional they had personally trained. All stated they could teach inhaler technique within 5 min. Observation of FPs during the second session by certified respiratory educators found that none made critical errors and all had excellent technique. CONCLUSION: A physician inhaler education program can improve attitudes toward inhaler teaching and facilitate implementation in clinical practices.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".