What are the respiratory health research priorities in Alberta, Canada? A stakeholder consultation
Bibliographic record
Abstract
OBJECTIVE: The Respiratory Health Strategic Clinical Network (RHSCN) was launched to facilitate respiratory and sleep health through implementation of innovative, patient-centred, evidence-informed coordinated services in Alberta. In collaboration with project partners, the RHSCN aimed to determine the respiratory research priorities for Alberta. DESIGN: The four phases of this research prioritisation project were (1) identifying research questions from stakeholders, (2) determining which research questions had been answered in existing literature, (3) prioritising unanswered questions and (4) finalising the priorities through an inperson workshop. SETTING: The study occurred in Alberta, Canada over a 2-year period beginning in March 2017. PARTICIPANTS: A total of 448 patients, clinicians and other stakeholders consented to participate in the survey. RESULTS: A total of 595 possible questions were submitted, with 343 unique questions identified. Of the questions, 94 were out of scope, 155 answered by existing literature and 10 were combined with others, while 83 were determined to be unanswered in the literature. Stakeholders were surveyed again to prioritise the remaining 83 questions and they were reviewed by the project's Steering Committee (clinicians and patients). At the inperson workshop, the Steering Committee identified 17 research topics as priority areas for respiratory and sleep research in Alberta. CONCLUSION: A stakeholder-led research prioritisation process identified optimal clinical management/follow-up, equitable access to services, and management of social, psychological and mental health issues related to respiratory/sleep health as priority research areas.
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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 | 0.126 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.036 | 0.012 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.008 | 0.012 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".