Pain-specific Beliefs and Pain Experience in Children with Juvenile Idiopathic Arthritis: A Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: to assess longitudinal associations between pain-specific health beliefs and pain in children with juvenile idiopathic arthritis (JIA), and to compare a selected group of patients with high pain and low disease activity (high-pain patients) with the remaining group. METHODS: forty-seven children with JIA, aged 7-15 years, completed the children's version of the Survey of Pain Attitudes (SOPA-C) and a 3-week pain diary at study entry (T1) and in a followup study 2 years later (T2). Parents also rated the Childhood Health Assessment Questionnaire (CHAQ), and an arthritis activity score was calculated each time. Second-order principal component analysis was conducted to reduce the number of independent variables. Regression analysis of the dependent measure was performed. The use of health beliefs was compared using t test for independent samples. RESULTS: T1 health beliefs predicted 7% of the variance in T2 pain scores after controlling for T1 pain, CHAQ, and disease activity. At T2, statistical differences were found between the scores of the high-pain group and the rest of the group for the health belief subscales of disability (mean ± SD 2.7 ± 0.5 and 2.2 ± 0.7, respectively) and harm (mean ± SD 3.8 ± 0.8 and 3.3 ± 0.6). CONCLUSION: our findings suggest that pain beliefs are influential on the longitudinal course of pain in children with JIA. Dysfunctional health beliefs in patients with high pain seem to be stable over time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".