Evaluation of the BALANCE Program as a Digital Therapeutic Solution for Type 2 Diabetes Management: Protocol for a Prospective Lifestyle Intervention Study
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a growing global health concern. In 2016, 9.7% of Bruneian adults aged 18 to 69 years had diabetes, making it the third leading cause of death. Effective self-management can mitigate complications that require health care interventions and lower health care costs. Brunei Darussalam has deployed BruHealth, a national mobile health platform synced with the Brunei Health Information Management System, allowing patients to access health records, schedule appointments, and explore medical articles. A digital therapeutics module for T2DM (diabetes mellitus digital therapeutics [DM DTx]) has been developed, consisting of a digital lifestyle intervention module within BruHealth and a separate health care professional portal for health coaches. The 16-week BALANCE program aims to support self-management. This study explores the efficacy of DM DTx in managing T2DM through digital lifestyle interventions. OBJECTIVE: The primary objective is to determine the proportion of participants who achieve at least a 0.6% reduction in glycated hemoglobin after 16 weeks. Secondary objectives include evaluating changes in glycated hemoglobin, fasting lipid profile, blood glucose, BMI, and waist circumference and analyzing participant feedback. Given the predominantly Muslim population, the study also aims to gain insight into fasting practices for Muslim participants with T2DM. METHODS: This single-arm, nonrandomized intervention study involves adults aged 18 to 70 years with T2DM. Participants complete a fully online 16-week program via BruHealth that includes diabetes self-management education, personalized diet and exercise plans, self-monitoring tools (eg, glucometer and smartwatch), and support from health coaches through video consultations and instant messaging. Anthropometric and biochemical measures are collected at baseline and after the intervention. Data sources include the Brunei Health Information Management System, BruHealth app logs, and the health care professional portal. Descriptive statistics will summarize participant characteristics and outcomes. Paired 2-tailed t tests or Wilcoxon signed-rank tests will compare the results before and after the intervention. Subgroup analyses will explore outcomes based on glycemic changes, BMI, medication type, and program engagement. Participant feedback will be qualitatively analyzed. Fasting risk in Muslim participants will be stratified using the International Diabetes Federation-Diabetes and Ramadan Alliance Risk score. RESULTS: Recruitment began on August 20, 2024, following project approval in July 2024, and continued until July 2025. By the end of data collection on November 12, 2025, a total of 459 participants had been enrolled, and 422 (91.9%) had completed the program. Data analysis is currently ongoing, with results expected in early 2026. CONCLUSIONS: Self-management mobile health apps are promising tools for chronic disease management, including T2DM. The BALANCE program is Brunei's first national-scale study evaluating a fully online T2DM intervention. Localization to a region's population may support improved health outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/73964.
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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 | 0.031 | 0.018 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.047 | 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".