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Record W2753369600 · doi:10.2519/jospt.2017.7375

Validation of the Standardized Universal Pain Evaluations for Rheumatology Providers for Children and Youth (SUPER-KIDZ)

2017· article· en· W2753369600 on OpenAlexaff
Nadia Luca, Jennifer Stinson, Brian M. Feldman, Susanne M. Benseler, Dorcas Beaton, Sarah Campillo, Claire LeBlanc, Margaret van Wyk, Ahmed M. Bayoumi

Bibliographic record

VenueJournal of Orthopaedic and Sports Physical Therapy · 2017
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsAlberta Children's Hospital
Fundersnot available
KeywordsMedicineIntraclass correlationConstruct validityPhysical therapyInterquartile rangeKappaObservational studyReliability (semiconductor)RheumatologyCriterion validityClinical psychologyPsychometricsInternal medicine

Abstract

fetched live from OpenAlex

Study Design Longitudinal observational clinimetric study with repeated measures. Background No validated multidimensional pain measure for children and youth with juvenile idiopathic arthritis exists. Objective To determine the test-retest reliability, construct validity, and responsiveness of English and French versions of the Standardized Universal Pain Evaluations for Rheumatology Providers for Children and Youth (SUPER-KIDZ). Methods Measurement properties of the SUPER-KIDZ (older child, younger child, and parent versions) were prospectively evaluated in patients (aged 4 to 18 years) with juvenile idiopathic arthritis at 2 centers. Internal consistency of the 3 subscales was measured using ordinal reliability alpha. Test-retest reliability for each subscale was evaluated with intraclass correlation coefficients (ICCs) from participants assumed to have stable pain (over a 1-week period with no change in treatment). Correlations of SUPER-KIDZ scores with validated measures determined construct validity. Responsiveness of SUPER-KIDZ subscales was evaluated in patients with improvement in pain, using standardized response mean and linear mixed-model regression. Results Seventy-one children aged 8 to 18 years and 29 parent-child dyads aged 4 to 7 years were included. Seventy-four percent of participants were female, with a median of 3 active joints (interquartile range, 1-5). Internal consistency was strong (α = .78-.96) for pain characteristics, interference, and emotional functioning SUPER-KIDZ subscales. Good test-retest reliability (ICC≥0.80) was found for the pain characteristics subscale in older- and younger-child versions. Most other subscales had satisfactory reliability coefficients (ICC≥0.70). Correlations of 0.50 or greater were found between the older-child SUPER-KIDZ scores and the Childhood Health Assessment Questionnaire and Patient-Reported Outcomes Measurement Information System depressive symptoms items, as well as the younger-child pain-intensity item and the Faces Pain Scale-Revised. Strong responsiveness was found for all subscales (standardized response mean, 0.63-1.54; significant linear mixed-model regression), except for the older-child emotional functioning subscale. Conclusion The SUPER-KIDZ has shown good internal consistency and responsiveness, and satisfactory test-retest reliability. Construct validity was moderate for the younger- and older-child versions, but weak for the parent version. J Orthop Sports Phys Ther 2017;47(10):731-740. Epub 4 Sep 2017. doi:10.2519/jospt.2017.7375.

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)0.027
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.042
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.309
Teacher spread0.289 · 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 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".

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Citations34
Published2017
Admission routes1
Has abstractyes

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