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Record W4404090051 · doi:10.1038/s41533-024-00389-4

The Reliever Reliance Test: evaluating a new tool to address SABA over-reliance

2024· article· en· W4404090051 on OpenAlexaff
Zoe Moon, Alan Kaplan, Vincent Mak, Luís J. Nannini, Tonya Winders, Amy Hai Yan Chan, Holly Foot, Rob Horne

Bibliographic record

Venuenpj Primary Care Respiratory Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsTD Bank GroupUniversity of Toronto
FundersAstraZeneca
KeywordsMindsetMedicineAsthmaTest (biology)Family medicineIntensive care medicineImmunology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.510
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.348
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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