Exploring Self-Care Interventions to Improve Glycemic Control in Type 2 Diabetes Mellitus: A Scoping Review

Design

This scoping review was conducted to summarize evidence-based alternatives to identify self-care interventions used to control blood glucose levels in patients with T2DM. The review adopted five key stages: (1) identifying the research question, (2) searching for relevant studies, (3) selecting relevant studies, (4) mapping the research data, and (5) compiling, summarizing, and reporting the findings. The study protocol is based on the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines.²⁶

Phase I: Defining the research question

This review addresses the following question: What self-care interventions are used to control blood glucose levels in patients with T2DM?

Phase II: Identifying relevant studies and search strategy

The article search was restricted to Full-text articles, Articles published in English, and Articles from the last 5 years (2019–2024). The formulation of searching using the Population Concept and Context (PCC) framework (Table 1). All selected literature was retrieved from the following databases: PubMed using the following keywords: ((Self-Care [Title/Abstract]) AND (Type 2 Diabetes Mellitus [Title/Abstract])) AND ((((HbA1) OR (A1C)) OR (random blood glucose)) OR (fasting blood glucose)). ProQuest using the search string: title (Self-Care) AND title (diabetes mellitus type 2) AND title (HbA1) OR title(A1C) OR title (random blood glucose) OR title (fasting blood glucose). Scopus using the search string: self AND care AND type 2 diabetes AND mellitus AND hba1 OR a1c OR random AND blood AND glucose OR fasting AND blood AND glucose ( Table 2).

Phase III: Study selection

All relevant articles were reviewed and analyzed. The inclusion criteria included all studies published in the last 5 years (between 2019 and 2024), written in English, and available in full text. The literature search was conducted in January 2025. The study selection process involved reviewing the title, abstract, and full text. All selected articles were organized using the Rayyan AI application on https://new.rayyan.ai for further screening. The screening stage in Rayyan AI was conducted by three reviewers. If an article received conflicting decisions from two reviewers or was marked as a conflict, the reviewers with differing opinions engaged in an open discussion to justify their inclusion or exclusion decisions. This discussion was guided by the pre-established inclusion and exclusion criteria and based on the article's title, abstract, or full text. This stage was meticulously documented using a flow diagram based on PRISMA-ScR guidelines ( Figure 1). This scoping review has been registered at https://osf.io/a3jq7/overview.

Figure 1. PRISMA-ScR guidelines flowchart.

Mapping the data

Data collected from previous studies were then mapped into a synthesis table. This synthesis table provides details of the articles, including the author's name, year of publication, publication title, research objectives, methods, population and sample, results, and conclusions. The full synthesis analysis of the included studies is available as Extended Data (Extended Data Table 3).

Study characteristics

Thirty-three articles were included across five regions: Asia, North America, South America, Europe, and the Middle East. The majority of studies were selected from Asia (21 studies). The country contributing the most studies was China, with a total of 5,^{38,45,49,51,54} followed by Saudi Arabia with 4 studies,^22,39,41,48 Thailand with 3 studies,^37,44,50 and Iran with 2 studies.^46,53 Other contributing countries included Singapore,¹⁸ Malaysia,³¹ Vietnam,³⁴ Turkey,²⁷ Lebanon,¹³ and Nepal.^42,56 Studies from Europe were represented by Italy²⁹ and Lithuania,³⁶ while North America was represented by the United States.^30,35,52 Additionally, some studies originated from Middle Eastern countries such as Kuwait⁴³ and Bahrain,³³ as well as from African countries, including Ethiopia²⁸ and Egypt.⁴⁰

Based on the study settings, the majority of studies were conducted in hospitals, with a total number of 15.^{13,18,27,28,29,33,45,54,57} Community settings were used in 10 studies.^{37,42,44,50,51,52,56} Meanwhile, primary healthcare centers served as study settings in five studies.^{31,40,41,46,49} Additionally, 3 studies utilized digital platforms or technology as a medium for health education interventions.^36,38,51

Research methods

Among the 33 analyzed articles, various study designs were used to evaluate the impact of health education on improving self-care among patients with T2DM. These studies can be classified as Randomized Controlled Trials (RCTs) (12 studies). This design was the most commonly used experimental method. These studies include.^{18,27,32,42,44,45,54} Quasi-Experimental Design (9 studies): include.^{13,22,27,31,41,51,53} Cross-Sectional Studies (13 studies): These studies examined the relationship between self-care behavior and blood sugar control without providing direct intervention.^{28,30,33,34,37,40,43,46,47,48,49,52,56} Experimental and Prospective Cohort Studies (4 studies): These studies aimed to examine the long-term effects of self-care interventions on HbA1c control.^35,36,38,39 Various methods were used in the studies, including questionnaire surveys to gather self-reported data on self-care behaviors, linear regression analysis to explore relationships between self-care activities and glycemic control, randomized controlled trials (RCTs), and quasi-experimental designs to evaluate the effectiveness of interventions, and HbA1c monitoring to assess the clinical outcomes of DM management.

Study population and sample

The scoping review in this study consisted of diverse populations and sample sizes (51 to 2,645 individuals). The meta-analysis conducted through the synthesis of 22 studies included the largest sample size, comprising 2,645 patients with T2DM.¹⁸ Meanwhile, the quasi-experimental study conducted in Iran involved the smallest sample size, with only 51 patients.⁵³ Several other studies also involved relatively large sample sizes, including a multinational web-based survey that collected data from 1,854 respondents, and a multicenter study in Thailand that examined 700 patients with T2DM.⁵⁰ Randomized Controlled Trials (RCTs) demonstrated considerable variation in sample sizes, ranging from 150 participants²⁸ to 612 participants.³² Quasi-experimental studies typically involve sample sizes between 75 and 250 participants,⁴¹ with some studies including up to 180 participants.⁵¹ Cross-sectional studies also showed a wide range of sample sizes, varying from 120 to 300 participants, such as a study involving 240 patients⁴⁰ and another with 300 participants.²⁸ Community-based and digital technology-based studies showed notable variation in sample sizes as well, such as an eHealth-based study involving 220 participants³⁸ and an evaluation of the Klinio mobile application with 160 patients with T2DM.³⁶ Several studies focused on specific populations, such as a study with 200 female patients with T2DM in Saudi Arabia²² and another with 180 elderly participants with T2DM in Thailand.⁴⁶ Additionally, a study conducted in the United States specifically examined T2DM among men, involving 190 participants.³⁵ Overall, the populations in these studies mainly consisted of adult T2DM patients aged between 40 and 70 years. However, some studies focused on specific groups, including studies that examined elderly patients⁴¹ and studies involving female patients.³¹ This variation in sample sizes highlights the broad scope of the study in evaluating self-care interventions and factors influencing glycemic control among patients with T2DM across different countries and research settings.

Self-care interventions

The 33 studies on managing T2DM involved a variety of self-care interventions, incorporating digital technology, educational interventions, and community support. Several studies utilized app-based solutions to enhance patient adherence to self-care routines. For example, one study introduced smartphone-based self-monitoring of blood glucose,¹⁸ while others applied the Klinio app and digital monitoring systems to aid in controlling blood sugar levels.^36,51 Additionally, platforms such as WhatsApp were used for educational purposes, and eHealth programs were developed to improve patients' understanding of self-care practices.^22,38

Beyond digital technology, several studies focused on educational interventions to improve DM management through structured learning and skill-building. A study introduced a subscription-based program for self-monitoring blood glucose, using a mobile platform to provide continuous support and feedback for patients,³¹ while another study initiative applied a patient-centered self-care approach, integrating personalized education sessions through a digital platform that allowed patients to track their blood glucose levels and receive tailored advice.³² The significance of culturally tailored, patient-centered self-care education was highlighted in multiple studies that used eHealth platforms to deliver personalized content and interactive learning.^13,41 An additional study explored how health literacy, through dedicated training modules, contributed to better self-care management by enhancing patients’ ability to navigate DM care.^48,50 Moreover, one study examined shared-care clinics where group education sessions, coupled with routine glucose monitoring, were provided to enhance collaborative care and improve patient engagement in DM management.⁴⁵

Across the 33 studies included in this scoping review, self-care interventions for the management of type 2 diabetes mellitus (T2DM) were categorized into four main approaches: digital self-care interventions,^{28,31,37,42,57} educational and health literacy interventions,^{26,34,35,52,53} community and social support,⁴⁴ and patient-centered approaches^26,59 ( Figure 2).

Figure 2. Self care interventions in T2DM management.

Key findings

In terms of outcomes, among the 33 studies analyzed, self-care interventions were found to significantly reduce HbA1c levels in patients with T2DM compared to control groups. Several key patterns emerged from the various studies, highlighting the effectiveness of digital technology-based solutions, educational and training-based interventions, patient-centered approaches, and community-based systems in improving glycemic control. Studies implementing digital technology, such as mobile applications, WhatsApp, and eHealth, demonstrated a significant impact on reducing HbA1c levels in patients with T2DM compared to control groups, with statistically significant p-values ranging from <0.05 to <0.001. Studies utilizing digital technology consistently demonstrated reductions in HbA1c. For instance, the use of the Klinio mobile application resulted in an HbA1c level of 7.5% in the intervention group compared to 8.4% in the control group (p< 0.05).³⁶ Another study reported that an eHealth-based DM management application reduced HbA1c to 7.55% compared to 7.52% in the control group, with a significant difference (p = 0.001).³⁸ Using an educational WhatsApp group led to a decrease in HbA1c from 8.61% to 7.92% in the intervention group (p < 0.001). At the same time, no significant change was observed in the control group.²²

In addition to digital technology, educational approaches and social support were also effective. A study showed a reduction in HbA1c of more than 0.5% at 3 months post-intervention, which was sustained at 6 months (p = 0.02).¹³ A telephone counseling intervention based on the IMB model lowered HbA1c from 9.28 to 8.76 in the intervention group, while the control group remained stable at around 9.16 (p < 0.001).²⁷ The PACE-SMI study conducted among South Asian populations also demonstrated a reduction in HbA1c from 8.81% to 8.49% at 3 months post-intervention, compared to 8.74% in the control group, with a statistically significant difference (p = 0.03).³²

Meaningful reductions in HbA1c were also observed in studies evaluating self-monitoring of blood glucose and patient-centered education. One study reported a combined mean difference of -0.55 between the intervention and control groups (p < 0.001).¹⁸ Another found that HbA1c significantly decreased in the intervention group receiving a self-monitoring package to 7.3% compared to 8.0% in the control group (p = 0.008).³⁸ In Saudi Arabia, a patient education intervention reduced HbA1c from 8.38% to 7.55% after 6 months (p < 0.001).³⁹ The use of glucose monitoring applications resulted in HbA1c of 6.9% in the intervention group compared to 8.1% in the control group (p < 0.05).⁵⁵ Similarly, the use of the Klinio application led to a lower HbA1c of 7.5% in the intervention group compared to 8.4% in the control group (p < 0.05).³⁶

Beyond digital technology, education, and social support also played a crucial role in enhancing adherence to self-care. Peer support-based interventions reduced HbA1c levels to 7.3% compared to 8.1% in the control group (p < 0.05).³⁵ Similarly, health literacy-based education reduced HbA1c to 7.0% compared to 8.1% (p = 0.04), indicating that improved health literacy contributes to better DM management.³⁷

Patient-centered and target-based approaches were also proven effective in improving glycemic control. A patient-targeted intervention successfully reduced HbA1c to 7.2% compared to 8.4% in the control group (p < 0.05).⁴² Another study that emphasized patient activation in self-care showed lower HbA1c levels in the intervention group (7.2%) compared to the control group (8.6%, p < 0.001).³⁹

Telephone-based interventions also demonstrated a positive impact on blood sugar control. Telephone counseling based on the IMB model reduced HbA1c to 8.76% compared to 9.28% (p < 0.001),²⁷ while brief motivational interviewing through telephone lowered HbA1c to 7.1% compared to 8.3% (p < 0.05).⁴⁴

In general, the results of this study reaffirm that self-care approaches, including self-monitoring, education, digital technology, and social support, can enhance patient adherence in managing T2DM and significantly reduce HbA1c levels. This study proves that patient-centered interventions utilizing modern technology can be an effective long-term DM management strategy.

Self-care intervention

The analysis of 33 studies showed that self-care interventions in managing T2DM are implemented in various forms, such as self-monitoring blood glucose, patient-centered education, and community-based approaches. Several studies examining self-monitoring of blood glucose have shown positive outcomes in blood sugar management. For instance, a study has demonstrated that self-monitoring of blood glucose significantly reduces HbA1c levels. Furthermore, patient-centered education, as implemented, indicated that increased self-care activity could lower HbA1c, with patients who were more active in managing their condition showing better glycemic control.^29,31 Despite these positive results, some studies suggest limitations over the long term, with self-care interventions providing short-term benefits but not always sustaining behavior change. This highlights the need to consider sociodemographic factors, such as health literacy and social support, when designing sustainable interventions. Self-care interventions focusing on blood glucose monitoring or patient education can yield significant results in managing blood glucose levels. In general, self-care interventions focused on blood glucose monitoring or patient education can provide significant results in managing blood glucose levels. However, for long-term effectiveness, these interventions should be combined with a more holistic approach that accounts for external factors such as social and psychosocial support.⁴⁶

Digital technology

In this study, digital technology, particularly mobile applications, has proven effective in enhancing patient adherence to DM management. Studies have shown that smartphone applications used for self-monitoring blood glucose increase routine monitoring and reduce fluctuations in blood sugar levels.^18,58 Applications such as Klinio also demonstrated significant reductions in HbA1c, with the intervention group showing better results than the control group investigated.³⁶ Although numerous studies highlight the success of technology in diabetes management, several challenges remain. For instance, some studies indicate that digital technology may not be effective for all populations, particularly in areas with limited access to technology or among individuals less skilled in using digital devices.³⁷ This can limit the positive impact of technology-based interventions for many diabetes patients. Although digital technology offers substantial benefits in facilitating self-monitoring and increasing patient engagement, accessibility, and user competence must be addressed to maximize its impact fully.

Cultural tailored approach

A culturally tailored approach has been shown to enhance the effectiveness of self-care interventions in DM management. A study found that culturally tailored self-care education can improve patient adherence to DM management.¹³ This is particularly relevant in countries with significant cultural diversity, where cultural factors influence how patients perceive and manage their illness. However, some results suggest that cultural factors can hinder the effectiveness of self-care interventions. For instance, cultural beliefs can impede the success of DM education programs, specifically when patients feel that the program does not align with their cultural values.³⁰ This indicates the need for interventions that are more culturally sensitive to ensure they are better accepted by patients.

In general, a culturally tailored approach has shown better results in enhancing the effectiveness of self-care interventions, but they require greater attention to cultural differences and patient beliefs to ensure success. Interventions aligned with cultural values can improve patient engagement in DM management.

Social support and peer support

In addition to digital technology and culturally tailored education, social and peer support have proven to play an important role in the effectiveness of self-care interventions. Several studies emphasize the significance of support from family, friends, and peer groups in improving adherence to diabetes management. For example, peer support interventions involving diabetes patients in support groups can enhance motivation to engage more actively in DM management.³⁵ The study also indicated that positive social relationships can reduce feelings of loneliness and improve patients’ psychosocial well-being. This support also reduces feelings of loneliness and improves psychosocial well-being. Nonetheless, the type of support received—whether from family, friends, or peers—can vary in quality and influence self-care adherence. Inconsistent or poorly understood support may diminish the benefits of such interventions.⁴⁰ Social and peer support improve adherence to DM management, but ensuring high-quality, consistent support is crucial for maximizing its impact.

Research limitations

Although the results are promising, several limitations are consistently observed across studies, including Heterogeneity in Study Designs and Measurement Instruments: Variations in research designs and outcome measurement instruments pose a significant challenge in broadly generalizing the results.^36,59 Short Intervention Duration: Some studies have short intervention and follow-up durations, making it difficult to assess the long-term sustainability of intervention effects.^33,42 Limited Sample Sizes: The small sample sizes in some studies reduce the statistical power and external validity of the results.⁶⁰

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