Implementation and Evaluation of an Audit and Feedback-Based Intervention to Improve the Transition from Pediatric to Adult Diabetes Care in Adolescents and Young Adults (AYA) with Type 1 Diabetes
Bibliographic record
Abstract
Adolescents and young adults (AYA) with type 1 diabetes (T1D) demonstrate suboptimal glycemic management when transitioning from pediatric to adult care, increasing the risk of diabetes complications. There is an evidence gap in diabetes transition care marked by inconsistencies in care delivery, contributing to suboptimal health outcomes. Audit and feedback (AF) can improve diabetes care quality, but there is a need for systematically designed interventions which are thoroughly and transparently evaluated. This thesis evaluates an audit and feedback-based intervention which leveraged a structured approach to transition care to improve glycemic management in AYA with T1D in the year after transfer from pediatric to adult diabetes care. The goals of this thesis were to: 1) describe the implementation of the audit and feedback-based intervention, and 2) to examine whether the intervention was associated with the completion of important transition care activities for AYA with T1D prior to transfer to adult care.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".