Text message-based intervention, Keeping in Touch (KiT), to support youth as they transition to adult type 1 diabetes care: a protocol for a multisite randomised controlled superiority trial
Bibliographic record
Abstract
INTRODUCTION: Transition from paediatric to adult care can be challenging for youth living with type 1 diabetes (T1D), as many youth feel unprepared to transfer to adult care and are at high risk for deterioration of glycaemic management and acute complications. Existing strategies to improve transition experience and outcomes are limited by cost, scalability, generalisability and youth engagement. Text messaging is an acceptable, accessible and cost-effective way of engaging youth. Together with adolescents and emerging adults and paediatric and adult T1D providers, we co-designed a text message-based intervention, Keeping in Touch (KiT), to deliver tailored transition support. Our primary objective is to test the effectiveness of KiT on diabetes self-efficacy in a randomised controlled trial. METHODS AND ANALYSIS: We will randomise 183 adolescents with T1D aged 17-18 years within 4 months of their final paediatric diabetes visit to the intervention or usual care. KiT will deliver tailored T1D transition support via text messages over 12 months based on a transition readiness assessment. The primary outcome, self-efficacy for diabetes self-management, will be measured 12 months after enrolment. Secondary outcomes, measured at 6 and 12 months, include transition readiness, perceived T1D-related stigma, time between final paediatric and first adult diabetes visits, haemoglobin A1c, and other glycaemia measures (for continuous glucose monitor users), diabetes-related hospitalisations and emergency department visits and the cost of implementing the intervention. The analysis will be intention-to-treat comparing diabetes self-efficacy at 12 months between groups. A process evaluation will be conducted to identify elements of the intervention and individual-level factors influencing implementation and outcomes. ETHICS AND DISSEMINATION: The study protocol version 7 July 2022 and accompanying documents were approved by Clinical Trials Ontario (Project ID: 3986) and the McGill University Health Centre (MP-37-2023-8823). Study findings will be presented at scientific conferences and in peer-reviewed publications. TRIAL REGISTRATION NUMBER: NCT05434754.
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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 | 0.049 | 0.044 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.070 | 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".