The TRUST Study—TRansition US Together: Evaluating the Impact of a Parent- and Adolescent-Centered Transition Toolkit on Transition Readiness in Patients with Juvenile Idiopathic Arthritis and Childhood-Onset Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Adolescents with chronic rheumatic disease must increasingly take on more responsibility for disease management from parents as they transition from pediatric to adult care. Yet, there are limited resources to inform and support parents about transition. Here, we evaluate the impact of a Transition Toolkit, geared towards parents and adolescents, on transition readiness, and explore the potential impact of parent-adolescent communication. METHODS: A prospective cohort study of youths aged 14-18 years old and their parents was performed. Participant demographics, disease characteristics, transition readiness scores (Transition-Q, max 100), and parent-adolescent communication scores (PACS, max 100) were collected at enrollment (when the Transition Toolkit was shared with adolescents and their parents. Generalized estimating equation (GEE) analyses determined the influence of the Toolkit on transition readiness and explored the role of parent-adolescent communication quality. Subgroup analyses were conducted by sex. RESULTS: < 0.05, respectively). CONCLUSION: Transition readiness improved at each follow-up, the greatest increase was seen after the Toolkit was shared. Parent-adolescent communication quality did not appear to impact changes in transition readiness.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".