Using opioids to treat dyspnea in advanced COPD: attitudes and experiences of family physicians and respiratory therapists.
Bibliographic record
Abstract
OBJECTIVE: To explore the experiences of family physicians and respiratory therapists in treating advanced chronic obstructive pulmonary disease (COPD) and their attitudes to the use of opioids for dyspnea in this context. DESIGN: Qualitative methodology using one-on-one semistructured interviews. SETTING: Southern New Brunswick (St Stephen to Sussex). PARTICIPANTS: Ten family physicians and 8 respiratory therapists who worked in primary care settings. METHODS: Participant interviews were audiorecorded, transcribed verbatim, coded conceptually, and thematically analyzed using interpretive description. MAIN FINDINGS: Participants reported that patients with advanced COPD often suffered from inadequate control of their dyspnea in advanced stages and that they saw the potential value of opioids in this context; however, family physicians described discomfort prescribing opioids. Barriers included insufficient knowledge, lack of education and guidelines, and fear of censure. Those with palliative care experience tended to be more comfortable with opioid prescribing. CONCLUSION: Findings suggest an important need to address barriers related to more effective treatment of refractory dyspnea in advanced COPD. Further, findings indicate these efforts should focus on effective palliation and innovative educational initiatives, as well as the development, promotion, and uptake of evidence-based practice guidelines related to prescribing opioids for these patients.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".