An assessment of adaptation and fidelity in the implementation of an audit and feedback-based intervention to improve transition to adult type 1 diabetes care in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: The fit between an intervention and its local context may affect its implementation and effectiveness. Researchers have stated that both fidelity (the degree to which an intervention is delivered, enacted, and received as intended) and adaptation to the local context are necessary for high-quality implementation. This study describes the implementation of an audit and feedback (AF)-based intervention to improve transition to type 1 diabetes adult care, at five sites, in terms of adaptation and fidelity. METHODS: An audit and feedback (AF)-based intervention for healthcare teams to improve transition to adult care for patients with type 1 diabetes was studied at five pediatric sites. The Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS) was used to document the adaptations made during the study. Fidelity was determined on three different levels: delivery, enactment, and receipt. RESULTS: Fidelity of delivery, receipt, and enactment were preserved during the implementation of the intervention. Of the five sites, three changed their chosen quality improvement initiative, however, within the parameters of the study protocol; therefore, fidelity was preserved while still enabling participants to adapt accordingly. CONCLUSIONS: We describe implementing a multi-center AF-based intervention across five sites in Ontario to improve the transition from pediatric to adult diabetes care for youth with type 1 diabetes. This intervention adopted a balanced approach considering both adaptation and fidelity to foster a community of practice to facilitate implementing quality improvement initiatives for improving transition to adult diabetes care. This approach may be adapted for improving transition care for youth with other chronic conditions and to other complex AF-based interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT03781973. Registered 13 December 2018. Date of enrolment of the first participant to the trial: June 1, 2019.
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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 | 0.028 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".