Type 2 diabetes mellitus (T2DM) remains one of the most pressing global health challenges, contributing significantly to morbidity, mortality, and healthcare expenditures worldwide (International Diabetes Federation 2025). As of 2021, the International Diabetes Federation (IDF) estimated that 537 million adults were living with diabetes globally, a figure projected to rise to 783 million by 2045, with more than three-quarters residing in low- and middle-income countries (LMICs) (Sun et al. 2022). The disease burden is particularly severe in Indonesia, where diabetes prevalence continues to rise sharply, and the national health system faces substantial barriers to delivering accessible, consistent, and patient-centered care (Soewondo et al. 2013). The IDF predicts that Indonesia alone may account for over 28 million diabetes cases by 2045, underscoring the urgent need for scalable, cost-effective interventions to support self-management and improve glycemic outcomes at the primary care level (International Diabetes Federation 2025).

T2DM self-management, encompassing medication adherence, dietary control, blood glucose monitoring, and physical activity, is fundamental to achieving glycemic control (De Groot et al. 2021). However, patients often struggle to sustain these behaviors within conventional care models, especially where patients have limited access to ongoing education, monitoring, and healthcare-provider interaction (Al-Badri and Hamdy 2021). In this context, mobile health (mHealth) technologies offer promising, patient-centered tools to bridge these gaps (Agarwal et al. 2019). Recent reviews have highlighted that digital interventions can significantly enhance medication adherence and self-care behavior, particularly among patients with chronic illnesses such as T2DM (Georgieva et al. 2023). Smartphone-based applications can deliver continuous support through interactive educational content, automated reminders, and communication with healthcare professionals (Al-Badri and Hamdy 2021). Furthermore, diabetes monitoring systems and digital platforms have demonstrated the potential to improve glycemic control and clinical decision-making, particularly when integrated into healthcare settings (Kamusheva et al. 2021). A growing body of systematic reviews and meta-analyses has consistently demonstrated that mHealth interventions contribute to significant improvements in glycemic control among individuals with type 2 diabetes, with meta-analytic estimates ranging from 0.4% to 0.5% mean reduction in HbA1c compared to control conditions (Liang et al. 2011; Cui et al. 2016; Hou et al. 2016).

Despite these promising findings, the effectiveness of mHealth interventions varies widely across studies and settings. For example, a multicenter pragmatic RCT of the BlueStar mobile app in the United States showed no significant difference in HbA1c reduction between intervention and control groups after 3 months (Agarwal et al. 2019), largely due to low and variable app engagement. Similarly, studies from South Korea and Europe confirm that contextual factors, including digital literacy, healthcare infrastructure, and patient-provider interaction, critically influence outcomes (Yang et al. 2020; Bretschneider et al. 2022). Most of these trials have been conducted in high-income countries, with limited evaluation in LMICs, where mobile health innovations may be most impactful. In Indonesia, evidence regarding the feasibility and clinical effectiveness of mHealth interventions in routine primary care settings remains scarce (Damayanti et al. 2021; Kusuma et al. 2023, 2024).

To address this gap, we designed a quasi-experimental study to evaluate the effectiveness of a culturally adapted mobile health application in improving glycemic control among patients with T2DM in public health center (puskesmas) settings in Bandung, Indonesia. The intervention integrated multimedia diabetes education, automated reminders, and real-time pharmacist consultations to support daily self-management. This study provides novel insights into the real-world utility of mobile app–based digital interventions in an LMIC context and explores their potential for scalability within national diabetes care strategies.

To the best of our knowledge, this is the first quasi-experimental study in Indonesia to evaluate the effectiveness of a mobile health (mHealth) application that integrates pharmacist consultation, multimedia education, and personalized blood glucose monitoring reminders in the management of type 2 diabetes mellitus (T2DM) in a primary care setting. Over 24 weeks, participants in the intervention group experienced a substantial and statistically significant reduction in HbA1c from 9.31% to 8.13%. In contrast, the control group, which continued receiving routine care, showed negligible change (from 8.99% to 8.96%). These findings align with existing clinical evidence suggesting that a reduction of ≥1% in HbA1c is associated with a 21% reduction in diabetes-related mortality, a 14% reduction in myocardial infarction, and a 37% reduction in microvascular complications (Bukhsh et al. 2018). These figures, derived from UKPDS and ADA guidelines, reinforce the clinical importance of our observed outcomes and support the role of digital interventions in achieving meaningful therapeutic benefits in glycemic control (Eikenhorst et al. 2017).

The pattern of HbA1c decline was both progressive and sustained. Improvements were observed as early as week 12 and maintained through week 24, suggesting long-term behavioral change and adherence to therapy rather than short-lived novelty effects (Berget et al. 2020). In contrast, the control group exhibited slight variability with no meaningful trend, indicative of the inherent limitations of conventional care models (Arnold et al. 2023). These typically offer education in static, infrequent formats, often lacking interactivity or patient-centered follow-up (Alba and Tunsi 2016). The digital intervention, by contrast, provided daily cues, weekly content refreshes, and individualized support (Takenouchi et al. 2016). This type of structured and persistent reinforcement is critical for chronic disease management, as emphasized by Marden et al. (2017), who argue that sustainable health outcomes depend on systems that reinforce behavior in real time and across diverse contexts.

The superior outcomes in the intervention group can be attributed to the multifaceted behavioral mechanisms embedded within the app (Azelton et al. 2021). Functioning as a “digital health coach,” the platform incorporated evidence-based features such as medication reminders, glucose monitoring prompts, pharmacist consultation through chat or video calls, and adaptive educational modules (Azelton et al. 2021). These components align with the Information–Motivation–Behavioral Skills (IMB) model, which posits that sustainable health behavior change occurs when individuals are adequately informed, internally motivated, and provided with the behavioral skills needed to act (Camacho et al. 2023; Coventry et al. 2019). For instance, reminders and prompts acted as environmental cues, reducing reliance on memory and fostering habit formation, while motivational content increased perceived benefits and self-efficacy (Avalos et al. 2024). Self-regulation theory further supports the idea that frequent feedback–especially when personalized–closes the gap between intention and behavior, enabling patients to sustain complex regimens such as blood glucose monitoring and dietary adjustment (Castro et al. 2022).

In line with Social Cognitive Theory, the intervention’s real-time bidirectional feedback mechanisms, particularly pharmacist interaction, likely enhanced patients’ self-efficacy and capacity for autonomous disease management (Kooij et al. 2017). Several recent meta-analyses have confirmed that digital interventions incorporating real-time provider interaction are more effective in reducing HbA1c compared to static educational tools (Bennett et al. 2017). Michie et al. (2017), for instance, reported that mHealth apps with interactive features achieved up to 0.8% greater HbA1c reduction compared to control conditions. This suggests that immediacy and personalization in feedback not only maintain patient engagement but also empower users to adjust behavior in a timely and context-sensitive manner (Knight et al. 2016).

Importantly, our results demonstrated not only a reduction in average HbA1c but also improvements in glycemic stability (Garcia et al. 2017). As illustrated in Fig. 2, the intervention group displayed a lower median HbA1c, narrower interquartile range, and fewer outliers at week 24, indicating reduced variability in glucose control (Seok et al. 2015). This is clinically important because glycemic variability, independent of mean HbA1c, is linked to increased oxidative stress, inflammation, and vascular complications (Liu et al. 2020). Huang et al. (2024) demonstrated that fluctuations in glucose levels contribute more to endothelial dysfunction than sustained hyperglycemia alone. The enhanced glycemic stability observed in our study may reflect the timely, dynamic nature of the app’s intervention, allowing patients to anticipate and mitigate disruptions in their diabetes management (Okumura et al. 2016).

The feasibility and usability of the intervention were further supported by its successful implementation across a demographically diverse sample (Chew et al. 2025). The majority of participants were aged 51–70 years, and many had only secondary-level education, yet they engaged meaningfully with the app (Rodríguez et al. 2019). This is notable because older adults and individuals with limited educational backgrounds often exhibit lower digital literacy, posing a barrier to technology adoption (Chew et al. 2025). Our intervention overcame this through intuitive interface design, caregiver integration, and the use of familiar communication tools like WhatsApp (Rodríguez et al. 2019; Kim et al. 2021). These design elements align with the Technology Acceptance Model (TAM), which emphasizes that perceived ease of use and perceived usefulness are key predictors of technology uptake (Tsai et al. 2017). The app’s success across varied user groups suggests strong potential for scalability within Indonesia’s public health infrastructure and other low-resource settings (Chou et al. 2024).

The cumulative impact of reduced HbA1c, improved glycemic consistency, high user engagement, and wide demographic applicability underscores the intervention’s potential as a transformative tool for T2DM self-management (Bonet et al. 2023). The study was conducted in a real-world primary care setting involving 10 public clinics, with full retention across the 24 weeks, enhancing the ecological validity of our findings (Bentley et al. 2016). The app itself was developed using user-centered design principles and underwent pre-deployment usability testing, ensuring cultural and technological fit (Bonet et al. 2023). Additionally, HbA1c, used as our primary outcome, represents a validated and objective measure of long-term glycemic control, enhancing the scientific rigor of our evaluation (Terauchi et al. 2017).

Despite these strengths, this study has several limitations. The quasi-experimental design without randomization introduces the possibility of selection bias, although baseline comparability between groups was maintained. HbA1c was the sole clinical endpoint; we did not assess complementary health indicators such as BMI, blood pressure, or lipid profiles, which limits the scope of interpretation. The 24-week duration, while sufficient to observe intermediate outcomes, does not allow for an assessment of the long-term sustainability of the intervention’s effects. Additionally, external confounders such as concurrent use of other digital health tools or informal support from family members were not controlled for and may have influenced results.

This quasi-experimental study provides strong preliminary evidence that a culturally tailored mobile health application, integrated with pharmacist support, behavioral reinforcement, and multimedia education, can significantly improve glycemic control and support sustained self-management in patients with type 2 diabetes mellitus in Indonesian primary care settings. The significant reductions in HbA1c, enhanced glycemic stability, and high engagement across diverse user groups underscore the intervention’s feasibility, usability, and potential for broader implementation. Future randomized controlled trials are needed to validate long-term effectiveness, cost-efficiency, and scalability.