Abstract
Background
Type 2 diabetes mellitus (T2DM) is a chronic condition requiring effective self-management for optimal health outcomes. Diabetes self-management education (DSME) is pivotal in T2DM care, with its efficacy potentially affected by patients’ health literacy levels. This study explores the moderating impact of health literacy on the correlation between DSME and DM self-care activities among individuals with T2DM in Korea, addressing the literature gap on health literacy’s influence on diabetes self-management.
Methods
This descriptive correlational study utilized data from the 2021 Korean Community Health Survey conducted by the Korea Disease Control and Prevention Agency, comprising 26,172 participants diagnosed with T2DM undergoing pharmacotherapy. The study assessed participants’ engagement in DSME, self-care monitoring activities (including HbA1c testing, retinal examinations, and microalbuminuria tests), and verbal and health text literacy levels. Statistical analyses, encompassing correlation and moderation analyses, were conducted using SPSS and SPSS Process Macro software.
Results
It was found that 29.5% of the participants engaged in appropriate self-care monitoring activities, whereas 70.5% did not. Higher levels of verbal and health text literacy were significantly linked with enhanced self-care monitoring. Furthermore, both forms of health literacy significantly moderated the correlation between DSME and self-care monitoring activities, suggesting that health literacy levels can impact the efficacy of DSME in enhancing diabetes self-management.
Conclusion
These findings underscore the critical role of health literacy in diabetes self-management. Healthcare professionals should account for patients’ health literacy levels when devising and implementing DSME programs, utilizing literacy-appropriate methods to ensure universal program benefits. This study emphasizes integrating health literacy considerations into DSME programs to enhance diabetes self-care. Subsequent research should examine the effects of various health literacy aspects on diabetes self-management and develop tailored educational strategies to improve health literacy among T2DM patients.
Keywords: Diabetes mellitus, Health literacy, Diabetes self-management education, Self-care monitoring
Introduction
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by persistent hyperglycemia that leads to progressive damage to the cardiovascular system, ocular structures, renal tissue, and peripheral nervous system [1]. Presently, 537 million adults worldwide have Diabetes mellitus (DM), and this number is expected to increase to 643 million by 2030 and 783 million by 2045 [2].
T2DM is a disorder necessitating continuous self-management, with proper management enabling a healthy life. However, complications arising from inadequate self-management are major factors that adversely affect quality of life [3]. Self-care is crucial for individuals with chronic diseases to maintain their quality of life and prevent illness-related complications [4]. Self-care can be defined as “the process of maintaining health by promoting healthy practices and managing illness.” The concept of self-care behavior comprises three key components: self-care maintenance, self-care monitoring, and self-care management [5]. Self-care maintenance involves behaviors performed to improve well-being and preserve health status, whereas self-care monitoring includes recognizing signs and symptoms and performing systematic and routine procedures, including visiting healthcare facilities to check health status. Self-management is a series of procedures that respond to newly occurring symptoms and signs caused by illness [6].
The Association of Diabetes Care & Education Specialists (ADCES) outlines seven specific areas of DM self-care: healthy eating, being active, monitoring, taking medication, problem-solving related to glucose control, healthy coping, and reducing or minimizing the risks of DM complications [7]. The ADCES and Kolb [8] suggest these areas are crucial in improving the health status and quality of life of individuals with DM.
Hemoglobin A1c, which reflects the mean blood glucose level over the past 2–3 months, should be measured every three months. Additionally, screening for diabetic complications such as diabetic retinopathy and diabetic nephropathy, which are representative complications of DM, should be conducted at least once a year for prevention and early detection [9, 10].
Diabetes self-management education (DSME) is conducted in various healthcare institutions and community settings to enhance patient understanding of the disease and promote self-management behaviors [11]. DSME focuses on fostering understanding and emphasizing the importance of maintaining blood glucose levels close to the normal range through dietary modifications, physical activity, and medication [12]. It aims to empower patients to acquire DM knowledge and treatment strategies. While the positive effects of T2DM education on self-management behaviors are evident [13], research on the duration of educational effects and the various factors influencing the relationship between DSME and self-care monitoring activities remains limited [14].
Health literacy is the ability of individuals to obtain, process, and understand basic health information and services necessary to make suitable decisions related to healthcare [15]. The health literacy of individuals with T2DM is associated with their knowledge of T2DM and is a significant factor directly affecting their self-care behaviors [16, 17]. In particular, people with low health literacy experience difficulties in understanding medical treatment or obtaining detailed information, which negatively affects their healthcare management [18].
Furthermore, health literacy is a crucial determinant that indirectly influences self-care behaviors through the moderation of self-efficacy, contributing to a reduction in the risk of T2DM complications [19]. Given that patients access health information through a variety of sources including the Internet and social media, rather than only from healthcare professionals, the influence of such information on health-related decision-making has grown significantly [20]. As such, the ability to evaluate and utilize reliable information is crucial for enhancing health management skills. Assessing patients’ literacy regarding information obtained from healthcare professionals as well as from the media is thus necessary.
Given that the effectiveness of DSME varies according to differences in health literacy [19], it is important to understand the relevance of self-management behaviors in T2DM, as well as assess the health literacy of individuals with T2DM. Meanwhile, we must be cognizant of the fact that health literacy is developed over a lifetime, influenced by formal education, the impact of parents and peers, exposure to health events, and cognitive abilities [21].
Hence, using a nationwide health dataset specific to the Korean population, this study aims to investigate the impact of health literacy on the association between DSME and self-care monitoring activities.
Methods
Study design
This descriptive correlational study aimed to identify the moderating effect of health literacy on the relationship between DSME and self-care monitoring activities in people with T2DM.
Participants
This study utilized raw data from the Community Health Survey conducted in 2021 by the Korea Disease Control and Prevention Agency [22]. The survey targeted adults aged 19 years and above nationwide in South Korea. The sample households were selected using a multi-stage probability sampling method, with an average of 900 samples per public health center in 255 regions. In total, 229,242 participants were included in this study.
The sample inclusion criteria were individuals who were diagnosed with T2DM by a physician and were currently receiving insulin therapy and/or oral hypoglycemic agents, as identified from the 2021 Korea Community Health Survey (N = 229,242). Among these, 202,887 individuals who had not been diagnosed with T2DM were excluded. Of the remaining 26,355 eligible participants, an additional 183 were excluded due to missing data on the study’s main variables, including DSME, diabetes self-management behaviors, and health literacy. As a result, 26,172 participants were included in the final analysis (Fig. 1).
Fig. 1.
Flowchart illustrating the selection of study participants
Measures
Sociodemographic and health-related characteristics (covariates)
Sociodemographic characteristics of the participants included age, gender, monthly household income, education level, employment status, and living arrangements. Monthly household income was categorized into four quartiles: less than 830,000 won, 830,000–1,900,000 won, 1,900,000–3,500,000 won, and above 3,500,000 won. Education level was classified as middle school or lower, high school, college, or higher. Employment status was determined by whether the participants were employed or unemployed based on their engagement in income-generating activities or unpaid family work exceeding 18 h in the past week. Living arrangements were categorized as living alone or with family members.
The health-related characteristics used as variables included alcohol consumption, smoking status, depressive symptoms, and perceived stress. Alcohol consumption and smoking status were determined based on whether the participants currently engaged in drinking or smoking. Depressive symptoms were assessed using the Korean version of the Patient Health Questionnaire-9 (PHQ-9), which measures the frequency of experiencing depressive symptoms over the past two weeks with a score ranging from 0 to 27 [23]. The participants were categorized into two groups: a non-depressed group (scores ranging from 0 to 9) and a group with a high likelihood of depression (scores of 10 or higher). Perceived stress was assessed by asking participants to rate their perceived stress during daily life activities on a scale of 1–4, with higher scores indicating higher levels of perceived stress.
Diabetes self-management education
Whether the study participants had received diabetic self-management education or not was determined by asking the following question: “Have you ever received diabetic self-management education?”. Study participants were classified into groups based on whether their response was “yes” or “no.”
Self-care monitoring activities
Self-care monitoring activities were assessed based on the participants’ responses to the following questions regarding DM management: How many times did you check HbA1c [glycated hemoglobin] in the past year? Did you receive an eye examination to screen for DM retinopathy in the past year? Did you take any urine test [microalbuminuria test] for diabetes-related kidney disease except stick urine test in the past year? [24].
Participants who reported receiving HbA1c testing at least twice a year, undergoing an eye examination at least once a year, or undergoing a microalbuminuria test at least once a year were classified as practicing appropriate self-care monitoring. Participants who did not meet these criteria were classified as having poor self-care monitoring activities.
Health literacy
Health literacy was assessed using self-reported measures, encompassing both verbal and textual literacy. Verbal health literacy was determined based on participants’ self-reported responses regarding their understanding of oral explanations provided by healthcare professionals. Responses were categorized as very easy, somewhat easy, somewhat difficult, or very difficult. For analysis, the responses were classified as easy or difficult.
Health text literacy was assessed based on participants’ self-reported understanding of written health information from various sources, such as newspapers, the Internet, and informational materials. Responses were categorized as very easy, somewhat easy, somewhat difficult, very difficult, or not paying attention to written health information. For analysis, the responses were grouped as easy, difficult, or uninterested. The “not interested” group exhibits a lack of motivation to seek or understand health information. This motivational deficit can lead to challenges not only in utilizing information but also in finding information [25]. These single-item measures have been previously validated and widely used in population-based Korean and international surveys, demonstrating acceptable construct validity [26, 27].
Data analysis
Data analysis was conducted using SPSS IBM SPSS/WIN 25.0. Descriptive statistics were employed to analyze the participants’ sociodemographic, health-related characteristics, DSME, DM self-care monitoring activities, and health literacy. Unweighted frequencies and percentages were used to represent variables. Differences in sociodemographic and health-related characteristics based on DSME were assessed using the Complex Samples Rao-Scott chi-square test and t-test. Correlations between DSME, DM self-care monitoring activities, and health literacy were analyzed using Cramer’s V coefficient. To assess the moderating effect of health literacy on the relationship between DSME and DM self-care monitoring activities, SPSS Process Macro V4.2 [28] was used. The relationship between DSME and DM self-care monitoring activities is illustrated with the graphs categorized into different health literacy groups.
Ethical considerations
The Korean Community Health Survey data used in this study were provided in a de-identified and anonymized format, with sensitive participant information removed. Data were obtained and approved for use by the Korean Community Health Survey website (https://chs.kdca.go.kr/chs/main.do) [29]. This secondary data analysis was approved by the Institutional Review Board of the institution to which the researcher belongs (IRB No. HYUIRB-202310-014).
Results
Differences in participant characteristics based on the appropriateness of their DM self-care monitoring activities
In this study, 19,747 participants (70.5%) inadequately managed their condition, whereas 6,425 participants (29.5%) managed it properly. Upon analyzing participant characteristics relative to their engagement in DM self-care monitoring activities, significant differences were noted in sociodemographic characteristics such as age (p <.001), gender (p =.016), household income level (p <.001), education level (p <.001), and living arrangement (p <.001). Furthermore, among health-related characteristics, statistically significant differences were found in smoking (p <.001), depressive symptoms (p =.035), and perceived stress (p =.007), as well as in aspects of health literacy, specifically verbal health literacy (p <.001), health text literacy (p <.001), and DSME (p <.001) (Table 1).
Table 1.
Characteristics of study participants by DM Self-Care monitoring activities
| Total (n*=26,172, 100%†) |
Poor (n*=19,747, 70.5%†) |
Appropriate (n*=6,425, 29.5%†) |
Rao-Scott X2/t |
p | |||||
|---|---|---|---|---|---|---|---|---|---|
| n* | %† | n* | %† | n* | %† | ||||
| Age | M ± SE | 64.60 ± 0.10 | 65.01 ± 0.12 | 63.61 ± 0.18 | 41.461 | < 0.001 | |||
| Gender | Male | 13,128 | 55.5 | 9754 | 54.9 | 3374 | 56.9 | 5.783 | 0.016 |
| Female | 13,044 | 44.5 | 9993 | 45.1 | 3051 | 43.1 | |||
| Monthly household income | Q4 | 6105 | 32.6 | 4160 | 30.3 | 1945 | 37.9 | 59.449 | < 0.001 |
| Q3 | 7179 | 29.0 | 5209 | 28.3 | 1970 | 30.8 | |||
| Q2 | 6334 | 20.7 | 4894 | 21.5 | 1440 | 18.8 | |||
| Q1 | 6261 | 17.7 | 5269 | 19.8 | 992 | 12.6 | |||
| Education level | College & higher | 4415 | 24.8 | 2880 | 22.3 | 1535 | 30.8 | 91.803 | < 0.001 |
| High school | 7127 | 32.1 | 5073 | 31.5 | 2054 | 33.5 | |||
| Middle school & lower | 14,609 | 43.1 | 11,780 | 46.2 | 2829 | 35.7 | |||
| Employment status | Employed | 13,178 | 48.1 | 9976 | 47.9 | 3202 | 48.5 | 0.485 | 0.486 |
| Unemployed | 12,994 | 51.9 | 9771 | 52.1 | 3223 | 51.5 | |||
| Living arrangements | With family | 20,209 | 81.4 | 14,903 | 80.0 | 5306 | 84.9 | 66.655 | < 0.001 |
| Alone | 5963 | 18.6 | 4844 | 20.0 | 1119 | 15.1 | |||
| Alcohol consumption | No | 15,893 | 54.7 | 12,032 | 54.7 | 3861 | 54.8 | 0.007 | 0.931 |
| Yes | 10,278 | 45.3 | 7714 | 45.3 | 2564 | 45.2 | |||
| Smoking | No | 21,892 | 80.6 | 16,423 | 79.5 | 5469 | 83.3 | 28.801 | < 0.001 |
| Yes | 4278 | 19.4 | 3323 | 20.5 | 955 | 16.7 | |||
| Depressive symptoms | No | 24,808 | 94.6 | 18,694 | 94.4 | 6114 | 95.2 | 4.450 | 0.035 |
| Yes | 1330 | 5.4 | 1022 | 5.6 | 308 | 4.8 | |||
| Perceived stress | 1.99 ± 0.01 | 1.98 ± 0.01 | 2.01 ± 0.01 | 7.224 | 0.007 | ||||
| Verbal health literacy | Easy | 18,416 | 72.8 | 13,519 | 71.0 | 4897 | 77.1 | 64.602 | < 0.001 |
| Difficult | 7756 | 27.2 | 6228 | 29.0 | 1528 | 22.9 | |||
| Health text literacy | Easy | 13,218 | 57.0 | 9362 | 66.8 | 3856 | 33.2 | 82.476 | < 0.001 |
| Difficult | 6444 | 23.0 | 5035 | 73.7 | 1409 | 26.3 | |||
| Not interested | 6510 | 20.0 | 5350 | 77.4 | 1160 | 22.6 | |||
| DSME | Received | 7951 | 37.9 | 4933 | 32.2 | 3018 | 51.4 | 556.647 | < 0.001 |
| Not received | 18,221 | 62.1 | 14,814 | 67.8 | 3407 | 48.6 | |||
DSME Diabetes self-management education
*Unweighted numbers
†Weighted percents
Correlation between completion of DSME, health literacy, and DM self-care monitoring activities
The correlations between the completion of DSME, health literacy, and DM self-care monitoring activities are presented in Table 2. There were significant correlations between DM self-care monitoring activities and completion of DSME (Cramer’s V = 0.261, p <.001), verbal health literacy (Cramer’s V = 0.115, p <.001), and health text literacy (Cramer’s V = 0.128, p <.001). Additionally, significant correlations were found between completion of DSME and verbal health literacy (Cramer’s V = 0.092, p <.001), health text literacy (Cramer’s V = 0.189, p <.001), and between verbal health literacy and health text literacy (Cramer’s V = 0.488, p <.001).
Table 2.
Correlations between DSME completion, health literacy, and DM Self-Care monitoring activities
| Variables | DSME | Verbal health literacy | Health text literacy | DM Self-care monitoring activities |
|---|---|---|---|---|
| Cramer’s V (p) | Cramer’s V (p) | Cramer’s V (p) | Cramer’s V (p) | |
| DSME | 1 | |||
| Verbal health literacy | 0.092 (< 0.001) | 1 | ||
| Health text literacy | 0.189 (< 0.001) | 0.488 (< 0.001) | 1 | |
| DM Self-care monitoring activities | 0.261(< 0.001) | 0.115 (< 0.001) | 0.128 (< 0.001) | 1 |
DM Diabetes mellitus, DSME Diabetes self-management education
Moderating effect of verbal health literacy on the relationship between DSME and self-care monitoring activities
The moderating effect of verbal health literacy on the relationship between DSME and self-care monitoring activities is presented in Table 3 after adjusting for the sociodemographic and health-related characteristics of the participants. The DSME (B = 1.0719, p <.001) and verbal health literacy (B = 0.3224, p <.001) had a significant impact on the self-care monitoring activities of individuals with DM. The influence of DSME on self-care monitoring activities was moderated by verbal health literacy (B = −0.3201, p <.001; Table 3). To explore this further, the conditional effects of verbal health literacy are illustrated in Fig. 2. Individuals who perceive verbal health literacy as challenging can still engage in DM self-care monitoring activities with the same effectiveness as those who perceive verbal health literacy as straightforward, provided they receive appropriate DSME.
Table 3.
Moderating effect of verbal health literacy on the relationship between DSME and DM Self-Care monitoring activities
| Variable | Effect | SE | Z | p | 95% cl LLCI |
95% cl ULCI |
|---|---|---|---|---|---|---|
| DSME (Received) | 1.0668 | 0.0620 | 17.2094 | < 0.001 | 0.9453 | 1.1882 |
| Verbal health literacy (Easy) | 0.3178 | 0.0445 | 7.1384 | < 0.001 | 0.2305 | 0.4050 |
| DSME × Verbal health literacy | − 0.3179 | 0.0710 | −4.4762 | < 0.001 | − 0.4571 | − 0.1787 |
Covariate variables: age, gender, monthly household income, education level, employment status, living arrangements, alcohol consumption, smoking, depressive symptoms, perceived stress LLCI Lower Level Confidence Interval, ULCI Upper Level Confidence Interval, DSME Diabetes self-management education
Fig. 2.
Graphical Representation of Moderating Effect of Verbal Health Literacy on DSME and DM Self-Care Monitoring Activities
Moderating effect of health text literacy on the relationship between DSME and self-care monitoring activities
After adjusting for participants’ general and health-related characteristics, the moderating effect of health text literacy on the relationship between DSME and self-care monitoring activities is shown in Table 4. DSME significantly affected the self-care monitoring activities of individuals with T2DM (B = 1.0404, p <.001). Self-care monitoring activities were significantly different for respondents who found health text literacy either difficult (B = 0.1138, p =.0426) or easy (B = 0.3751, p <.001) significant differences in their self-care monitoring activities. The impact of DSME on self-care monitoring activities was moderated by the ease of text literacy (B=−0.3320, p =.0001) (Table 4). To explore this further, the conditional effects of health text literacy are illustrated in Fig. 3. Receiving DSME enhanced the likelihood of engaging in self-care activities across all levels of health text literacy.
Table 4.
Moderating effect of health text literacy on the relationship between DSME and Self-Care monitoring activities
| Variable | Effect | SE | Z | p | 95% CI LLCI |
95% CI ULCI |
|---|---|---|---|---|---|---|
| DSME (Received) | 1.0404 | . 0755 | 13.7800 | < 0.001 | . 8924 | 1.1884 |
| Health text literacy (Difficult) | . 1138 | . 0561 | 2. 0280 | . 0426 | . 0038 | . 2237 |
| Health text literacy (Easy) | . 3751 | . 0500 | 7. 4999 | < 0.001 | . 2770 | . 4731 |
| DSME × Health text literacy (Difficult) | − 0.1222 | . 0990 | −1. 2346 | . 2170 | − 0.3161 | . 0718 |
| DSME × Health text literacy (Easy) | − 0.3320 | . 0852 | −3. 8956 | 0.0001 | − 0.4991 | − 0.1650 |
Covariate variables: age, gender, monthly household income, level of education, economic activity, living arrangements, alcohol consumption, smoking, depressive symptoms, stress Reference: Health text literacy – not interested
Fig. 3.
Graphical Representation of Moderating Effect of Verbal Health Literacy on DSME and DM Self-Care Monitoring Activities
Discussion
The study found that only 29.5% of participants managed their health appropriately, whereas 70.5% did not adequately perform essential self-care monitoring activities. In South Korea’s healthcare system, chronic conditions such as T2DM and hypertension are managed at local clinics primarily through internal medicine or family medicine practices [30]. However, these clinics may face challenges in conducting the necessary tests for comprehensive T2DM management. As such, the need to visit different clinics to undergo tests creates a significant barrier to timely and effective care for patients. The inconvenience and additional effort required can deter patients from completing essential monitoring procedures, contributing to unmet healthcare needs, and hindering the effective management of their condition [31]. Consequently, there is a pressing need to streamline care and consider the development of one-stop management services for diabetic complications to improve patient outcomes, minimizing the need for patients to seek services at multiple locations.
The observed association between DSME and self-care monitoring activities points to the potential significance of DSME programs, suggesting the need to tailor educational content and delivery methods to individuals with T2DM. Additionally, the correlation of verbal health literacy and health text literacy with DSME highlights that patients with higher health literacy may have better access to, and show more effective utilization of, information [32]. T2DM, a chronic condition, requires understanding and choosing among various treatment options, necessitating effective communication with healthcare professionals to accurately understand information [33]. Moreover, the ability to appropriately select and use health education materials available outside clinical settings is essential. In particular, the fact needs to be acknowledged that the reliability of information obtained from sources outside traditional healthcare settings, such as the Internet, may not always be adequately verified [34]. Discernment is thus key when selecting trustworthy information sources. The vast amount of health-related information available online can be overwhelming and sometimes misleading, making it imperative that individuals develop critical evaluation skills to identify credible and scientifically validated information [35]. Thus, enhancing health literacy not only empowers patients to effectively engage in self-management behaviors but also equips them with the ability to critically assess the reliability of health information obtained from non-clinical sources [36]. Careful selection and use of reliable information are paramount in adopting the best management strategies for their conditions, ultimately leading to improved health outcomes.
The strong correlation between verbal and text literacy suggests that educational and intervention programs aimed at improving health literacy should consider both aspects. Patient education programs need to facilitate the understanding of oral information provided by healthcare professionals and include methods for effectively reading, evaluating, and applying health information obtained through mass media [37]. These programs should incorporate simulations that practice verbal communication with healthcare providers, and exercises to analyze and understand health information texts, thereby enhancing both types of literacy. Moreover, providing personalized feedback and support tailored to an individual’s needs and preferences can maximize a patient’s ability to manage T2DM effectively.
Research findings on the positive impact of DSME on diabetic patients’ self-care monitoring activities moderated by verbal health literacy demonstrate that DSME is a pivotal element in DM care and management. These findings highlight the potential importance of education in equipping patients with the knowledge needed to engage in effective self-care practices, such as monitoring blood glucose levels, adhering to medication regimens, and managing their diet. Moreover, engaging in self-care monitoring helps patients gain a clearer insight into their health, enabling them to make informed decisions to sustain healthy lifestyle habits [38]. Furthermore, these activities provide health care providers with crucial information for tailored care and treatment plans for an individual’s specific health condition [39]. Engagement in self-care monitoring may facilitate more effective T2DM treatment, enhance the quality of life, and potentially reduce healthcare costs in the long term [40]. Therefore, it is necessary to increase the engagement of T2DM patients in self-care monitoring.
Given that both verbal and health text literacy have been identified as important factors regulating the effectiveness of DSME, comprehensive DSME and support programs addressing both forms of health literacy are crucial to enhance overall T2DM care. In this study, verbal health literacy significantly moderated the relationship between DSME and self-care monitoring activities; this highlights the critical role of healthcare professionals in delivering health information that is accessible and understandable to all patients regardless of their health literacy levels. To optimize DSME impact, it is essential to design educational programs that consider verbal health literacy. Healthcare providers should utilize literacy-appropriate methods such as the teach-back technique, personalized planning, and follow-up checks, which are especially beneficial for enhancing DSME among patients with lower health literacy [41]. The careful design of educational materials and improvement of communication strategies will ensure that information is conveyed in an easy-to-understand manner [18]. Acknowledging the wide variance in patients’ abilities to process health information, adapting DSME to accommodate both low and high levels of verbal health literacy is crucial.
In this study, health text literacy significantly moderated the relationship between DSME and self-care monitoring activities. Given this moderating effect, scrutinizing health information from sources such as the Internet and newspapers is imperative, particularly for patients with lower accessibility and comprehension levels. As access to health information increases, and the volume of information grows exponentially, identifying accurate and reliable information poses a substantial challenge [42]. It is thus crucial for healthcare professionals to oversee the dissemination of health information, ensuring that it is based on scientific evidence and prevent its misuse [43]. They should not only eliminate inaccurate information when individuals visit healthcare facilities but also assess and manage their medical information regarding T2DM as well as their health literacy. Empowering patients to evaluate and interpret health information critically through media literacy education is essential [37]. This approach enhances patients’ critical thinking and evaluative skills, ensuring that they can effectively navigate a vast landscape of health information.
This study has several limitations that should be addressed in future research. There is a need to analyze the causes of low adherence to diabetes self-care monitoring activities, which requires a multifaceted analysis considering individual and contextual factors. In addition, since the data used in this study were self-reported, there is a possibility of information bias, including social desirability bias and recall bias. In particular, the one-year recall period for HbA1c testing, eye examination and urine test, may have affected the accuracy of participants’ responses. These limitations should be considered when interpreting the findings, especially the low proportion (29.5%) of participants who adequately performed self-care monitoring activities. While this study elucidated the moderating role of verbal health literacy on the effectiveness of DSME, future research should delve deeper into the impact of different types of health literacy and educational media on DM self-management behaviors. In addition, the development of practical guidelines for applying these research findings in actual healthcare settings remains an important area of study. To gain a deeper understanding of the interaction between health text literacy and DM self-management behaviors, further research on patient groups with diverse cultural and socioeconomic backgrounds is needed. Research on specific intervention methods to improve health text literacy levels and their effectiveness is crucial. Moreover, both verbal health literacy and DSME were assessed using self-reported and simplified measures. While these items have demonstrated acceptable validity in prior large-scale studies, they may still fall short of capturing the full complexity of these constructs. Future research should consider incorporating multidimensional tools and evaluating provider communication quality to better assess the impact of health literacy and DSME on diabetes self-management. Furthermore, DSME in this study was assessed using a single binary item indicating whether participants had received diabetes education. This approach may not fully reflect the multifactorial nature of DSME, which encompasses goal setting, psychosocial support, behavioral strategies, and individualized education components. Future studies should consider employing multidimensional tools to more comprehensively assess DSME participation and its effects.
Conclusion
This study explores the moderating effect of health literacy on the relationship between DSME and self-care monitoring activities among people with T2DM. Understanding this impact will allow healthcare professionals and policymakers to develop effective DM education programs and health information delivery strategies. This will improve the ability of patients with T2DM to better understand and manage their health. This study offers significant insights into effective education and communication methods for healthcare professionals to improve DM self-management. It offers valuable information not only for patients with T2DM but also for healthcare professionals, educators, and policymakers, contributing to the development and implementation of effective DM management strategies.
These findings provide directions for future research. There is a need to further explore the impact of various aspects of health literacy on DM self-management behaviors, and to assess the levels of health literacy and accessibility to DM education across different populations. Moreover, research on the development and evaluation of specific educational and intervention strategies to enhance health literacy is crucial.
Acknowledgements
None.
Abbreviations
- DM
Diabetes mellitus
- T2DM
Type 2 diabetes mellitus
- DSME
Diabetes self-management education
- ADCES
The Association of Diabetes Care & Education Specialists
Authors’ contributions
HL analyzed and interpreted the data and drafted the manuscript. HSC contributed to the conceptualization and design of the study, contributed to manuscript writing, and was responsible for funding acquisition. All authors have read and approved the final version of the manuscript.
Funding
This research was supported by the Dankook University Research Fund in 2023.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
This secondary data analysis was approved by the Institutional Review Board of the institution to which the researcher belongs (IRB No. HYUIRB-202310-014).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analysed during the current study.