mHealth Intervention for Vietnamese Living With Diabetes: Protocol for a Stepped Wedge Pilot Study
Bibliographic record
Abstract
BACKGROUND: . Language and cultural differences may be barriers to program participation resulting in ineffective self-management, but these factors can be addressed with appropriate interventions. Given the high health care costs associated with diabetes complications, we developed a multicomponent, culturally tailored Self-Management Mobile Health Intervention for US Vietnamese With Diabetes (SMart-D). OBJECTIVE: This study aims to evaluate the SMart-D intervention's feasibility, acceptability, and effectiveness with intentions to scale up the intervention in the future. This mixed methods study incorporates the Reach, Effectiveness, Adoption, Implementation, Maintenance framework to evaluate the intervention. METHODS: This stepped wedge randomized controlled pilot study will be conducted over 2 years in collaboration with primary care clinics. Eligible participants are patients with type 2 diabetes who are receiving health care from participating clinics. Clinics will be randomly assigned to an implementation date and will begin with patients enrolling in the control period while receiving standard care, then cross over to the intervention period where patients receive standard care plus the SMart-D intervention for over 12 weeks. Focus groups or interviews will be conducted with clinicians and patients after study completion. Qualitative data will be analyzed using NVivo. Outcomes on self-care behavior changes will be measured with the Summary of Diabetes Self-Care Activities scale and clinical changes will be measured using laboratory tests. A generalized linear mixed-effect model will be used to compute time effect, clustering effect, and the interaction of the control and intervention periods using SAS (version 9.4; SAS Institute). RESULTS: We hypothesize that (1) at least 50% (n=5) of eligible clinics and 50% (n=40) of eligible patients who are invited will participate, and at least 70% (n=56) of patients will complete the program, and (2) patients who receive the intervention will have improved self-care behaviors and clinical test results with at least 75% (n=60) of the patients maintaining improved outcomes at follow-up visits compared with baseline, and participants will verbalize that the intervention is feasible and acceptable. As of August 2023, we enrolled 10 clinics and 60 patients. Baseline data results will be available by the end of 2023 and outcome data will be published in 2025. CONCLUSIONS: This is the first Vietnamese diabetes self-management education and support intervention that leverages mobile health technology to address the barriers of language and culture differences through collaboration with primary care clinics. This study will provide a better understanding of the implementation process, demonstrate the potential effectiveness of the intervention, accelerate the pace of moving evidence-based interventions to practice among the US Vietnamese population, and potentially provide a replicable implementation model that can be culturally adapted to other non-English speaking ethnic minorities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48585.
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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 | 0.034 | 0.020 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.067 | 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".