Cognitive behavioral group intervention for pain and well-being in children with juvenile idiopathic arthritis: a study of feasibility and preliminary efficacy
Bibliographic record
Abstract
BACKGROUND: Pain is still a part of everyday living for several children with juvenile idiopathic arthritis (JIA) despite improvement in treatment. Psychological interventions may contribute to diminish pain complaints and improve well-being in children with JIA. Only few studies have investigated the efficacy of psychological therapy in children with arthritis and with mixed results. The aim of the study was to evaluate the feasibility and preliminary efficacy of a cognitive behavioral therapy group intervention for children with JIA and their parents. METHODS: Nineteen children with JIA and their parents were allocated to six sessions' group cognitive-behavioral therapy (n = 9) or a waitlist control condition (n = 10). Results were measured from self-reported scales and one-week pain diaries. Clinical data was collected by a rheumatologist. RESULTS: The participation rate was low; 33 % of the invited families participated. However, the participants rated the intervention's credibility and satisfaction with the intervention as high. The dropout rate was low and attendance rate high. Increased quality of life and improvements in adaptive pain cognitions was reported in the intervention condition compared to the waitlist condition, whereas no differences were found for pain and functional disability. The disease activity increased in the treatment condition but not in the control condition. CONCLUSIONS: The feasibility of this study seemed high with regards to the acceptability of the families participating in the intervention. However, the feasibility in general was challenged by implementation problems with a low participation rate. A reduction in pain after the intervention was not found even though pain management was the main target in the intervention. Preliminary analysis showed that although the severity of the disease status increased, an increase in quality of life, reduction in pain catastrophizing, and an improvement in adaptive pain cognitions (the beliefs in controlling pain and self-efficacy) were seen in the intervention condition. The study highlights the importance of considering the disease status when evaluating the efficacy of a psychological intervention in children with arthritis. Conclusions on the strength of the efficacy require further research in a large, randomized controlled trial.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".