Do patients think that dry powder inhalers can be used interchangeably?
Bibliographic record
Abstract
As recognised in management guidelines, patients are the most important group of people in any prescribing decision. Despite their importance, few studies have asked what patients think about being switched between different inhalers. This paper reports two such studies, one involving interviews of a sample of patients and the other consisting of a quantitative survey of patients across five countries. In the qualitative study, four of the five patients interviewed reported that they would be confused, worried and unhappy about a switch in their dry powder inhaler and would revisit their physician to be shown how to use the inhaler or to ask for a new prescription for their old inhaler. In the quantitative survey of 499 patients with asthma, more than half (51%) were opposed to their current dry powder inhaler being replaced by a substitute device, with 83% reporting concerns. There was considerable concern about training in use of the new device and confusion about the need for change. Almost a quarter of patients (23%) would want training, and 23% of patients thought they would need information about the new inhaler. From limited information, it appears that patients would be concerned about switching of their existing dry powder inhaler for another, with the potential for confusion, need for additional consultations and need for training in the new device.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".