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Record W2013518484 · doi:10.3109/01942630903245309

A Qualitative Study of Fitness Instructors' Experiences Leading an Exercise Program for Children with Juvenile Idiopathic Arthritis

2009· article· en· W2013518484 on OpenAlexafffund
Carolyn E. Hutzal, F. Virginia Wright, Samantha Stephens, Jane Schneiderman‐Walker, Brian M. Feldman

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2009
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsArthritisQualitative researchPerceptionPhysical fitnessPhysical therapyMedicinePsychologyMedical education

Abstract

fetched live from OpenAlex

Children with arthritis face challenges when they try to increase their physical activity. The study's objective was to identify elements of a successful community-based exercise program for children with arthritis by investigating the perspectives of fitness instructors who led the program. This qualitative study used a phenomenological approach. Four fitness instructors participated in individual interviews. Themes were developed through inductive analytic methods. Three main themes were identified: (a) children with arthritis require encouragement and guidance throughout the program from fitness instructors who understand their arthritis, and support from parents and peers; (b) children need help to overcome their negative perceptions about exercise; and (c) exercise program participation can launch the adoption of a more active lifestyle. Pediatric physiotherapists can encourage the establishment of successful exercise programs for children with arthritis in nonmedical or community environments through the formation of supportive, education-based partnerships with community-based fitness instructors.

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)0.009
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0100.006
Scholarly communication0.0030.003
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.045
GPT teacher head0.414
Teacher spread0.369 · 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 designQualitative
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

Citations11
Published2009
Admission routes2
Has abstractyes

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