Reliability and Responsiveness of the Standardized Universal Pain Evaluations for Rheumatology Providers for Children and Youth (SUPER-KIDZ)
Bibliographic record
Abstract
Aims: To determine the test-retest reliability and responsiveness of a new computerized 20-item pain measure, SUPER-KIDZ, in children with juvenile idiopathic arthritis (JIA).\nMethods: A single centre prospective cohort study of JIA patients aged 8-18 years was performed. For each SUPER-KIDZ item, test-retest reliability analysis was done in patients expected to have stable pain, and responsiveness was evaluated after intra-articular steroid injection(s). \nResults: Fifty-one subjects were included. Good internal consistency (α=0.73-0.92) was demonstrated for the 3 SUPER-KIDZ domains. Acceptable test-retest reliability (intraclass correlation coefficient or kappa ≥0.80) was found for 15 SUPER-KIDZ items. At 2 weeks post-injection, 16 items were responsive to change in pain (standardized response mean=0.66-0.82, significant Wilcoxon signed rank and linear mixed model). \nConclusions: The majority of the SUPER-KIDZ items have acceptable test-retest reliability and responsiveness properties. If validity is demonstrated, this measure could be implemented as a standardized comprehensive pain tool for JIA patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".