The Reliever Reliance Test: evaluating a new tool to address SABA over-reliance
Bibliographic record
Abstract
Over-use of SABA is associated with poor asthma control and greater risk of exacerbations and death. Identifying and addressing the beliefs driving SABA over-reliance is key to reducing over-use. This study aimed to assess the utility, impact and acceptability of the Reliever Reliance Test (RRT), a brief patient self-test behaviour-change tool to identify and address SABA over-reliance. Patients with asthma who completed the RRT in Argentina were invited to an online survey exploring the acceptability of the RRT, and its impact on patients' perceptions of SABA and intention to discuss asthma treatment with a doctor. 93 patients completed the questionnaire. The RRT classified 76/93 (82%) as medium-to-high risk of SABA over-reliance (a mindset where SABA is perceived as the most important aspect of asthma treatment), with 73% of these reporting SABA overuse (3 or more times a week). 75% intended to follow the RRT recommendations to review their asthma treatment with their doctor. The RRT is acceptable to patients and was effective at raising awareness of, identifying and addressing SABA over-reliance and encouraging patients to review their treatment with their doctor.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".