Research and Healthcare Priorities of Individuals Living with COPD
Bibliographic record
Abstract
This study describes the research and healthcare priorities of individuals living with COPD. On an online survey, individuals living with COPD assigned a percentage of funding to 22 research priorities and a percentage of time spent communicating with a healthcare provider to 24 healthcare priorities, indicating which topics were most important. For each research and healthcare priority, we examined the selection frequency of the priority and used chi-square analyses to examine differences in priority selection by quartiles of airflow obstruction (percent predicted forced expiratory volume in 1-sec (FEV1%predicted)) and breathlessness burden and exacerbation risk. Based on participants’ responses (N = 148, 47% women; Mean ± Standard Deviation age = 68 ± 9 yrs) relief of breathlessness was the most often selected research (76% of respondents) and healthcare priority (61% of respondents). It was selected most often, regardless of disease severity or breathlessness burden and exacerbation risk. We found differences for disease severity and breathlessness burden and exacerbation risk in some research priorities (e.g., to improve the maximal amount of exercise of adults living with COPD in and out of the home (χ2(3) = 9.97, Cramer’s V =.28) and healthcare priorities (e.g., increase your ability to exercise (χ2(3) = 9.72, Cramer’s V =.27)). This study provides empirical evidence that relief of breathlessness is a top research and healthcare priority for individuals living with COPD. Future healthcare and research activities should align with the priorities of individuals with COPD to improve their care by minimizing disease/symptom burden and optimizing health-related quality of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".