Past, Present and Future of Respiratory Research: A Survey of Canadian Health Care Professionals
Bibliographic record
Abstract
BACKGROUND: The Canadian Respiratory Health Professionals (CRHP) is the multidisciplinary health care professional group of the Canadian Lung Association. Although the CRHP has a growing number of highly qualified researchers, the landscape of their research in Canada has not been described. OBJECTIVES: To describe the level of respiratory research engagement; identify barriers and facilitators to research engagement; describe the experience and interest in developing research skills; and identify priority areas of future respiratory research among health care professionals. METHODS: An online survey of CRHP members was used to collect demographic information; barriers and facilitators to conducting research; future directions in respiratory research; and research funding and mentorship. Experience with and interest in 'upskilling' research skills were also evaluated. RESULTS: A total of 119 surveys were completed (22% response rate), of which 69 (58%) respondents were engaged in respiratory research. Reasons for not being involved in respiratory research were lack of mentorship, support and funding. The top research areas were chronic obstructive pulmonary disease (74%) and asthma (41%). The top facilitators for research engagement were amount of funding (29%) and mentorship (28%). Respondents in research positions rated their experience in research skills as high; those in nonresearch positions as low. However, both groups expressed interest in improving their research skills. CONCLUSIONS: Areas of development, such as research skills, greater funding opportunities and mentorship to increase the research capacity of health care professionals in respiratory health were identified. Health professional researchers have an important role in the national respiratory research strategy to increase interdisciplinary engagement and build collaborative teams.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".