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Record W2277614801 · doi:10.1177/1367493516632616

‘It might hurt, but you have to push through the pain’

2016· article· en· W2277614801 on OpenAlexaff
Douglas Race, Joanie Sims‐Gould, Lori B. Tucker, Ciarán M. Duffy, Debbie Ehrmann Feldman, Michele Gibbon, Kristin Houghton, Jennifer Stinson, Elizabeth Stringer, Shirley M. L. Tse, Heather McKay

Bibliographic record

VenueJournal of Child Health Care · 2016
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsUniversité de MontréalUniversity of OttawaDalhousie UniversityUniversity of TorontoBC Children's HospitalChildren's Hospital of Eastern OntarioHospital for Sick ChildrenUniversity of British Columbia
Fundersnot available
KeywordsCategorizationMedicineQualitative researchArthritisFamily medicinePsychologyPhysical therapyClinical psychology

Abstract

fetched live from OpenAlex

Our primary objective was to gather perspectives of children diagnosed with juvenile idiopathic arthritis (JIA) and their parents as they relate to physical activity (PA) participation. To do so, we conducted a study on 23 children diagnosed with JIA and their parents ( N = 29). We used convenience sampling to recruit participants and qualitative method- logies (one-on-one semi-structured interviews). We adopted a five-step framework analysis to categorize data into themes. Children and their parents described factors that act to facilitate or hinder PA participation. Pain was the most commonly highlighted PA barrier described by children and their parents. However, children who were newly diagnosed with JIA and their parents were more likely to highlight pain as a barrier than were child/parent dyads where children had been previously diagnosed.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.006
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.343
Teacher spread0.322 · 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

Citations27
Published2016
Admission routes1
Has abstractyes

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