Transition Readiness in Adolescents With Juvenile Idiopathic Arthritis and Childhood‐Onset Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: The transition from pediatric to adult rheumatology care represents a particularly vulnerable time for patients with juvenile idiopathic arthritis (JIA) and childhood-onset systemic lupus erythematosus (cSLE). Improving self-management skills is important in optimizing health care transition. The study's objectives were to 1) examine variability in transition readiness of adolescents and young adults within and between different ages, sexes, and disease types; 2) determine the association between age and transition readiness; and 3) identify specific challenges to transition readiness for adolescents. METHODS: Over 1 year, patients 14 to 20 years of age with JIA or cSLE were recruited from pediatric transition and young adult clinics at a single academic institution. Participants completed the 14-item Transition-Q at a single time point. Total scores range from 0 to 100; higher scores indicate greater health care self-management skills as a proxy for transition readiness. Descriptive statistics summarized patient characteristics and Transition-Q scores for the population. Regression analyses determined the association between age, sex, and disease type and Transition-Q score. RESULTS: Among 70 participants, 61 had JIA and 9 cSLE (mean disease duration 4.6 years). The mean (SD) total Transition-Q score was 59.8 (14.9). Age was significantly associated with Transition-Q score (standardized β = 0.372l P = 0.002). The most commonly reported challenges were seeing the physician alone (without parents), making one's own appointments, picking up prescriptions, and independent transportation for appointments. CONCLUSION: Transition readiness appears to increase with patient age. There is significant variability in Transition-Q scores between patients of the same age, suggesting that an individualized approach to improving self-management skills is necessary.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".