Overcoming the Barriers to Spirometry Testing for COPD in British Columbia: A Systematic Review
Bibliographic record
Abstract
Spirometry is an important method of assessment for lung health, and plays a vital role in the diagnosis, differentiation and management of respiratory illnesses such as chronic obtrusive pulmonary disease (COPD), as well as other conditions such as asthma (Coates et al., 2013). It is able to detect respiratory disease early on in a primary care setting, which is paramount for timely and effective health interventions (Johns et al., 2014). Despite its importance, as well as a strong evidence base and multiple clinical guideline recommendations, spirometry remains underused in practice (Roberts et al., 2011). There are several studies that have examined the efficacy of interventions to improve access to and use of spirometry. Typically, these interventions address the barriers to spirometry use that have been identified. To date, however, there has been no synthesis of these studies in terms of the characteristics of the interventions, the barriers they aim to mitigate, and the outcomes measures used.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.104 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.010 | 0.000 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".