Examining Share plus—A Continuous Glucose Monitoring Plus Data-Sharing Intervention in Older Adults and Their Care Partners: Protocol for a Randomized Control Study
Bibliographic record
Abstract
Background Older adults with type 1 diabetes (T1D) are increasingly turning to care partners (CPs) as resources to support their diabetes management. With the rise in diabetes technologies, such as continuous glucose monitoring (CGM), there is great potential for CGM data sharing to increase CP involvement in a way that improves persons with diabetes’ glucose management and reduces distress. Objective The specific aims of this paper are to (1) evaluate the feasibility, usability, and acceptability of the Share plus intervention compared to the CGM Follow app plus diabetes self-management education and support; (2) evaluate the effect of the Share plus intervention on time-in-range (TIR; primary outcome) and diabetes distress (secondary outcome); and (3) explore differences between groups in person with diabetes and CP dyadic appraisal and coping, quality of life, diabetes self-care, and CP burden at 12 and 24 weeks and associations of dyadic variables on outcomes. Methods This is a protocol for a feasibility, pilot randomized controlled trial. Older adults with T1D and their CP (N=80 dyads) will be randomized 1:1 to the Share plus intervention or Follow app plus diabetes self-management education. The trial will include a 12-week active intervention to determine the change in primary (TIR) and secondary (diabetes distress) outcomes, followed by a 12-week, observation-only phase to examine maintenance effects. The evaluation is guided by the Dyadic Coping Model. Patient-level effectiveness outcomes (TIR, hemoglobin A1c [HbA1c], diabetes distress, diabetes appraisal, coping, quality of life, diabetes self-care behaviors, and CP burden) will be assessed, using patient-reported outcomes measures and a home HbA1c test kit. Patient- and CP-level acceptability and feasibility will be assessed using surveys and interviews. Quantitative feasibility, acceptability, and usability data will be described using frequencies and percentages. Acceptability will be summarized based on Likert questions and open-ended questions. Usability will be examined separately for the intervention and control groups based on the System Usability Scale, with a study benchmark of ≥68 indicating good usability. TIR will be computed based on 2 weeks’ worth of data at baseline (prior to intervention) and 2 weeks each after the intervention (week 12) and at follow-up (week 24). Results Recruitment started in August 2023 and enrollment began in November 2023. To date, 24 participants have been enrolled in this study. We expect to conclude this study in March 2026 and expect to disseminate results in March 2026. Conclusions To our knowledge, this will be the first pilot randomized controlled trial to evaluate both feasibility and effectiveness outcomes for the web-based, platform-delivered Share plus intervention for older adults with T1D and their CP. This research has implications for CGM data sharing in other age groups with T1D and type 2 diabetes. Trial Registration ClinicalTrials.gov NCT05937321; https://clinicaltrials.gov/study/NCT05937321 International Registered Report Identifier (IRRID) DERR1-10.2196/60004
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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 | 0.037 | 0.033 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.063 | 0.011 |
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".