Similarities and Differences Between Asthma Health Care Professional and Patient Views Regarding Medication Adherence
Bibliographic record
Abstract
BACKGROUND: The recent literature has reported disparate views between patients and health care professionals regarding the roles of various factors affecting medication adherence. OBJECTIVE: To examine the perspectives of asthma patients, physicians and allied health professionals regarding adherence to asthma medication. METHODOLOGY: A qualitative, multiple, collective case study design with six focus-group interviews including 38 participants (13 asthma patients, 13 pulmonologist physicians and 12 allied health professionals involved in treating asthma patients) was conducted. RESULTS: Patients, physicians and allied health professionals understood adherence to be an active process. In addition, all participants believed they had a role in treatment adherence, and agreed that the cost of medication was high and that access to the health care system was restricted. Major disagreements regarding patient-related barriers to medication adherence were identified among the groups. For example, all groups referred to side effects; however, while patients expressed their legitimate concerns, health care professionals believed that patients' opinions of medication side effects were based on inadequate perceptions. CONCLUSION: Differences regarding medication adherence and barriers to adherence among the groups examined in the present study will provide insight into how disagreements may be translated to overcome barriers to optimal asthma adherence. Furthermore, when designing an intervention to enhance medication adherence, it is important to acknowledge that perceptual gaps exist and must be addressed.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".