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Record W2905747889 · doi:10.1111/jir.12579

Asthma prevalence and control levels among Special Olympics athletes, and asthma‐related knowledge of their coaches

2018· article· en· W2905747889 on OpenAlexaffabout
Carley O’Neill, Matthew S. Russell, Robert Balogh, Meghann Lloyd, Shiwangi Dogra

Bibliographic record

VenueJournal of Intellectual Disability Research · 2018
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsAsthmaAthletesMedicinePhysical therapyQuality of life (healthcare)PopulationEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The prevalence of asthma among athletes with intellectual disabilities, and the asthma knowledge levels of their coaches, is unknown. METHODS: Special Olympics Canada athletes completed a demographic questionnaire (n = 208). Athletes who identified as having ever or current asthma completed the Asthma Control Questionnaire and the Mini Asthma Quality of Life Questionnaire and were measured for height, weight and lung function (n = 73). National level coaches (n = 27) completed a questionnaire pertaining to asthma knowledge. RESULTS: The prevalence of ever and current asthma were 35.5% (n = 73) and 21.1% (n = 44), respectively. Athletes with asthma reported that they had inadequately controlled asthma, but good quality of life. Coaches correctly answered 43% true/false questions on the survey, indicating suboptimal asthma knowledge. CONCLUSIONS: Athletes with intellectual disabilities appear to have a greater prevalence of asthma than the general population; however, coaches of these athletes appear to have limited knowledge pertaining to asthma and exercise-induced asthma.

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)0.008
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.011
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.085
GPT teacher head0.374
Teacher spread0.288 · 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 designObservational
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

Citations5
Published2018
Admission routes2
Has abstractyes

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