Transition to Adulthood through Coaching and Empowerment in Rheumatology (TRACER): A feasibility study protocol
Bibliographic record
Abstract
The transition from pediatric to adult care for patients with chronic disease is a vulnerable period, with risks of disengagement from care and subsequent complications of inadequately managed disease. This period comes at a time when there are many other transitions occurring in the young person's life, including changes to vocation, social supports, and to their physiology. The aim of the TRACER study is to assess the feasibility of conducting a multi-center, randomized-controlled trial of a virtual Transition Coach Intervention in youth transferring from pediatric to adult rheumatology care. Patients are being recruited at their last pediatric rheumatology visit from McMaster Children's Hospital and Children's Hospital, London Health Sciences Centre in Ontario, Canada. Participants are then randomized to standard of care or to eight transition coaching sessions, covering topics around health management, future planning, and self-advocacy. The primary outcomes of the study are to demonstrate protocol feasibility, including optimal recruitment and consent rates, ≥ 90% coaching session completion, and complete data collection with ≤ 5% missing data. Baseline demographics, transition readiness, global functional assessment, disease activity, and self-efficacy will be collected to characterize the study population. Recruitment has begun and is estimated to last 19 months. This study will inform the design of a robust, multi-centered, randomized-controlled study to investigate the impact of a virtual transition coaching program in supporting the physical, mental, and social well-being of youth with rheumatic disease transitioning into adult care. Clinical trial registration: ClinicalTrials.Gov protocol ID: 14499.
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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 | 0.041 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.063 | 0.012 |
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".