Effects of adherence to treatment on short‐term outcomes in children with juvenile idiopathic arthritis
Bibliographic record
Abstract
OBJECTIVE: To determine the impact of adherence to treatment (medication and prescribed exercise) on outcomes in children with juvenile idiopathic arthritis (JIA). METHODS: In this longitudinal study, we studied parents of patients with JIA at the Montreal Children's Hospital and British Columbia Children's Hospital in Vancouver. Adherence was evaluated on a visual analog scale in the Parent Adherence Report Questionnaire. Outcomes of interest were active joint count, pain, child functional score on the Child Health Assessment Questionnaire, quality of life score on the Juvenile Arthritis Quality of Life Questionnaire, and parental global impression of overall well-being. The association between adherence to treatment and subsequent outcomes was evaluated using generalized estimating equations and logistic regression. RESULTS: Mean age and disease duration of our sample of 175 children were 10.2 and 4.1 years, respectively. Moderate adherence to medication was associated with lower active joint count (odds ratio [OR] 0.47, 95% confidence interval [95% CI] 0.22-0.99). Moderate adherence to exercise was associated with better functional score (OR 0.13, 95% CI 0.03-0.54), and lower pain during the last week (OR 0.14, 95% CI 0.04-0.50). Both high and moderate adherence to exercise were associated with parental perception of global improvement. CONCLUSION: Improved outcomes in patients who adhered to treatment underscores the need for clinicians to address adherence issues with their patients. Sustaining adherence, particularly to the more time-consuming treatment of exercise, is a challenge.
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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 | 0.003 | 0.017 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".