Relationship of Fatigue, Pain Interference, and Physical Disability in Children Newly Diagnosed With Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Our objectives were to quantify the relationships among fatigue, pain interference, and physical disability in children with juvenile idiopathic arthritis (JIA) and to test whether fatigue mediates the relationship between pain interference and physical disability in JIA. METHODS: Patients enrolled within three months of JIA diagnosis in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry between February 2017 and May 2023 were included. Their parents completed the Patient-Reported Outcomes Measurement Information System fatigue and pain interference short proxy questionnaires and the Childhood Health Assessment Questionnaire disability index at registry enrollment. Associations were assessed using Pearson correlations and multiple linear regression. Structural equation modeling (SEM) was used to test if fatigue mediates the relationship between pain interference and physical disability. RESULTS: Among 855 patients (61.4% female, 44.1% with oligoarthritis), most reported fatigue and pain interference scores similar to those in the reference population, but 15.6% reported severe fatigue and 7.3% reported severe pain interference, with wide variation across JIA categories. Fatigue was strongly correlated with pain interference (r = 0.72, P < 0.001) and with physical disability (r = 0.60, P < 0.001). Pain interference (β = 0.027, P < 0.001) and fatigue (β = 0.013, P < 0.001) were both associated with physical disability after controlling for each other and potential confounders. SEM supported our hypothesis that fatigue partially mediates the relationship between pain interference and physical disability. CONCLUSION: Our findings suggest both fatigue and pain interference are independently associated with physical disability in children newly diagnosed with JIA, and the effect of pain interference may be partly mediated by fatigue.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".