Harnessing interactive technologies to improve health outcomes in juvenile idiopathic arthritis
Bibliographic record
Abstract
BACKGROUND: Children and adolescents with Juvenile Idiopathic Arthritis (JIA) typically have reduced physical activity level and impaired aerobic and anaerobic exercise capacity when compared to their non-JIA counterparts. Low intensity exercise regimens appear to be safe in children with JIA and may results in improvements in overall physical function. Poor adherence to paediatric rheumatology treatment may lead to negative clinical outcomes and possibly increased disease activity. This includes symptoms such as pain, fatigue, quality of life, longer term outcomes including joint damage, as well as increase of healthcare associated costs. Low adherence to medications such as methotrexate and biological-drugs remains a significant issue for paediatric rheumatologists, with alarming reports that less than half of the children with JIA are compliant to drug-therapy. MAIN BODY: The recent advances in interactive technology resulting in a variety of wearable user-friendly smart devices may become a key solution to address important questions in JIA clinical management. Fully understanding the impact that arthritis and treatment complications have upon individual children and their families has long been a challenge for clinicians. Modern interactive technologies can be customised and accessed directly in the hands or wrists of children with JIA. These secured networks could be accessible 'live' at anytime and anywhere by the child, parents and clinicians. Multidisciplinary teams in paediatric rheumatology may benefit from adopting these technologies to better understand domains such as patient biological parameters, symptoms progression, adherence to drug-therapy, quality of life, and participation in physical activities. Most importantly the use of smart devices technologies may also facilitate more timely clinical decisions, improve self-management and parents awareness in the progression of their child's disease. Paediatric rheumatology research could also benefit from the use of these smart devices, as they would allow real-time access to meaningful data to thoroughly understand the disease-patterns of JIA, such as pain and physical activity outcomes. Data collection that typically occurs once every 1 or 3 months in the clinical setting could instead be gathered every week, day, minute or virtually live online. Arguably, few limitations in wearing such interactive technologies still exist and require further developments. CONCLUSION: Finally, by embracing and adapting these new and now highly accessible interactive technologies, clinical management and research in paediatric rheumatology may be greatly advanced.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".