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Record W2136629735 · doi:10.1002/art.38529

A108: Linking Exercise, Activity and Pathophysiology in Childhood Arthritis: An Innovative Canadian Knowledge Translation Strategy

2014· article· en· W2136629735 on OpenAlexaffabout
Michele Gibbon, Lori B. Tucker, Debbie Ehrmann Feldman, Heather McKay, Joanie Sims‐Gould, Jennifer Stinson, Elizabeth Stringer, Shirley M. L. Tse

Bibliographic record

VenueArthritis & Rheumatology · 2014
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsIzaak Walton Killam Health CentreUniversité de MontréalSickKids FoundationUniversity of TorontoBC Children's HospitalHospital for Sick ChildrenUniversity of British ColumbiaChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsPathophysiologyTranslation (biology)ArthritisKnowledge translationMedicinePhysical therapyInternal medicineKnowledge managementComputer scienceBiologyGenetics

Abstract

fetched live from OpenAlex

Background/Purpose: We implemented a novel knowledge translation (KT) initiative called the LEAP Ambassador Program to disseminate findings from the “Linking Exercise, Activity and Pathophysiology (LEAP) in Children with JIA study.” The main hypothesis of the study is that increased levels of physical activity will improve the outcomes (such as quality of life) of youth with juvenile idiopathic arthritis (JIA). The aim of this initiative is to inspire youth with JIA to be physically active through the creation of a community of athletes and youth with JIA, who model different levels of physical activity. Methods: The LEAP Ambassador program was developed by the LEAP study program manager and approved by the LEAP Steering Committee. Various levels of athletes, ranging from international, national, college/university level, and local LEAP study participants (youth with JIA, aged 8–16 years), were sought. Individuals agreeing to participate signed consent for use of their personal photo(s) and interview on the LEAP website ( www.leapjia.com ). Participants were asked to provide a photo of themselves involved in a sport or physical activity, and to answer 6 brief questions about their motivation to engage in sport/physical activities, in the face of disease flares and/or injuries. Each of the participating LEAP sites was encouraged to seek local LEAP ambassadors through their clinics and community connections, to ensure representation across the country. Results: To date, 15 LEAP ambassadors have been engaged in the program, including 3 international/national level athletes, 2 college/provincial level athletes and 10 youth with JIA. Different levels of physical activity and sports, including freestyle skiing, soccer, walking, horseback riding, speed skating, hockey, cycling and rowing, have been represented. The 10 youth with JIA who have agreed to be LEAP ambassadors come from across the country. Both English and Frenchspeaking ambassadors have been included. Conclusion: The LEAP ambassador program is a unique KT initiative aimed at developing a robust community across the country to support the research messages of the LEAP study, relating to the promotion of physical activity in youth with arthritis. A supportive network is being developed, in which athletes act as role models, inspiring youth with JIA to engage in physical activity, and the youth themselves encourage and motivate each other through shared experiences. Future plans include expansion of the program to include more athletes and youth with JIA, and increased use of social media to connect patients and athletes. An evaluation of the effectiveness of the program is also planned.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.055
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.519

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.060
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0100.004
Scholarly communication0.0070.003
Open science0.0040.009
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.011
GPT teacher head0.261
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2014
Admission routes2
Has abstractyes

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