Approximately 94.2 million (22.7%) older adults (ages 65 to 79 years) had diabetes in 2015, and this number is expected to increase to 200.5 million by 2040 (International Diabetes Federation, 2015). In South Korea, the prevalence of diabetes among older adults is 30.4% (approximately 1.95 million individuals), and 10.8% of patients with diabetes remain untreated (Korean Diabetes Association, 2016). Individuals with diabetes require daily self-management of diet, exercise, and stress to control blood glucose, reduce risk of complications, and improve quality of life (Shrivastava, Shrivastava, & Ramasamy, 2013). However, older adults are more likely to experience aging-related physical, cognitive, and mental changes that influence their ability to self-manage their diabetes (Song, Lee, & Shim, 2010).
Health literacy is the state of having cognitive and social skills that allow individuals to access, understand, and use information to promote and maintain good health (Nutbeam, 1998). This state is a necessary element for communicating with health professionals and understanding, learning, and performing their instructions (Park & Hwang, 2014). More than one half of older adults have a low level of health literacy (Kim & Lee, 2008), which affects their health status, chronic disease management, and health care burden (Berkman et al., 2011). Although many health literacy–related studies evaluating individuals who speak English and Spanish exist, few have evaluated individuals who speak Korean, which may be because the Korean alphabet (“Hangul”) allows for pronunciation even if the speaker does not understand the word's meaning, making it difficult to notice the necessity of health literacy–related research. Therefore, research regarding the health literacy of Korean older adults remains a relatively young field (Kim, Park, & Lee, 2014).
Health literacy influences social, cognitive, and psychological determinants of knowledge, health beliefs, and self-efficacy. These factors influence health behaviors and biomarkers (Von Wagner, Steptoe, Wolf, & Wardle, 2009). According to Fransen, von Wagner, and Essink-Bot's (2012) causal pathway, health literacy is significantly and positively correlated with knowledge and self-efficacy. Moreover, knowledge, health beliefs, and self-efficacy significantly influence diabetes self-management and HbA1c levels (Fransen et al., 2012). However, recent studies have mainly targeted individuals with diabetes who were not Asian and younger than 65 (Cavanaugh et al., 2009; Lorig, Holman, Sobel, Laurent, & Gonzalez, 2006; Wallace et al., 2009), and it is unclear if their findings are relevant for Asian older adults (age >70 years) with diabetes. For example, older adults may have non-specific diabetic symptoms, and the blood glucose levels of community-dwelling Korean older adults may differ compared to those of non-Asian adults from community health centers and primary care clinics (Chang, 2010; Rosal et al., 2011; Rothman et al., 2004). Moreover, most Korean older adults with diabetes do not perform appropriate diabetes self-management, such as regular blood glucose testing (Chang, 2010).
Senior centers are places where older adults can access a variety of educational and leisure programs (Jeong et al., 2012), and nurses in senior centers provide many programs to address the high demand for health education in this population (Song & Kim, 2006). However, as there are no programs specifically developed for older adults, senior centers generally use public health programs designed for younger adults. Furthermore, Korean public health programs provide health-related educational materials that require the ability to read at or above the sixth-grade level, which is higher than the recommended level for this type of program (Chin & Choi, 2014). Therefore, the current study aimed to develop and evaluate a health literacy–considered diabetes self-management program among older adults in South Korea. The program was based on the causal pathway (Fransen et al., 2012) through which health literacy–considered diabetes self-management would be expected to influence diabetes self-management knowledge (DSK), diabetes health beliefs (DHB), and diabetes self-efficacy (DSE), which would influence diabetes self-management behavior (DSMB) and diabetes biomarkers. Thus, all strategies in the program were developed to complement older adults' health literacy and health-related characteristics. The effects of the program were compared to usual care using pre–post analysis, and it was hypothesized that the intervention group would experience improvements in DSK, DHB, DSE, DSMB, and diabetes biomarkers (i.e., HbA1c, blood pressure, and serum lipids level).
Design and Sample
The current randomized controlled trial was conducted between July 6, 2015 and December 28, 2015. The intervention group completed the health literacy–considered diabetes self-management program and the control group received usual care (i.e., a standard lecture series). The study's protocol was approved by the governing institutional review boards in South Korea.
Participants were recruited through bulletin announcements at two senior centers (D and G) in a single South Korean city. The two senior centers were the largest centers in the D and G districts, which are close to each other and have similar living standards. The D senior center has approximately 16,000 registered users, and the G senior center has approximately 20,000 registered users, with approximately 1,000 active users each day. Inclusion criteria were adults 65 and older, diagnosed with type 2 diabetes, and receiving medication for ≥6 months. Exclusion criteria were individuals with severe communication problems (e.g., difficulty reading or communicating when using eyeglasses, a magnifying glass, or a hearing aid) and dementia, based on a score <24 on the Korean Version of the Mini-Mental State Examination (MMSE-K; Park & Kwon, 1989). Eligible individuals were included if they provided written informed consent after receiving an explanation regarding the study's purpose, procedure, duration, benefits, and risks.
The required sample size was calculated using G*Power 3.1.7 (Faul, Erdfelder, Buchner, & Lang, 2009). The significance level (alpha) was 0.05 and the test power (1–β) was 0.8 based on the sizing for similar behavioral research in nursing. The effect size was 0.81 based on a previous meta-analysis (Tshiananga et al., 2011). Thus, the required number of participants was 25 for each group, and 28 participants were assigned to the intervention group and control group to account for potential dropouts. A total of 51 participants completed the study, which provided an effect size of 0.89.
Randomization and Blinding
Participants were randomized using a randomization program (access http://www.randomization.com) by an independent researcher who did not have contact with participants. Participants and researchers were blinded to participants' assignments, data, physical examination results, and blood test results.
Both groups completed 12-week programs according to their assignment (26 participants in the intervention group and 25 participants in the control group). However, to account for any dissemination of the program, the control group completed the program before the intervention group began the program. Before the intervention program was implemented, a professor of gerontological nursing (M.S.) and a diabetes specialist evaluated the program and its workbook.
Health Literacy Program
Participants in the intervention group were invited to attend weekly 1-hour sessions for 12 consecutive weeks to learn about how to manage diabetes. This program was designed based on older adults' health literacy and their health-related characteristics to target improvements in DSK, DHB, and DSE that would lead to improvements in DSMB and diabetes biomarkers. Health literacy differs from reading literacy, and represents the cognitive and social skills that control an individual's motivation and ability to access, understand, and use information to promote and maintain good health (Nutbeam, 1998).
To improve DSK, the program was drafted based on seven self-care behaviors (i.e., health status, problem solving, healthy eating, being active, medications, reducing risks, and healthy coping) from Tomky et al. (2008) and the health-related characteristics of older adults (Table A, available in the online version of this article). The program included a workbook with self-management checklists and worksheets for the 12 weekly sessions, as well as secondary materials. The workbook was based on the Korean version of the Suitability Assessment of Materials, which evaluates individuals with low health literacy using six categories (Sung, Lee, & Park, 2004) (Table B, available in the online version of this article). Secondary materials included a blood glucose meter, which measured and automatically transmitted results to a website; a rice bowl with three divisions per 100 calories; and a TheraBand® (i.e., resistance band). The program was delivered using clear communication strategies (Kripalani & Weiss, 2006) and teach-back methods (Schillinger et al., 2003). Clear communication was facilitated by measuring participants' health literacy level, translating medical terms into common words, and using “help” boxes in the workbook for important medical terms (Ntiri & Stewart, 2009). Time and number of repetitions were determined based on participants' health literacy and skills (Ntiri & Stewart, 2009). The teach-back method was implemented using a hypothetical individual with recently diagnosed diabetes, which allowed participants to express what they learned in their own language to avoid feeling like they were being tested.
The Contents of the Program
The Workbook Based on the Suitability Assessment of Material (SAM)
To improve DHB, all participants received their blood test results and were educated regarding diabetes risk factors to motivate self-management. The benefits of self-management and tips for overcoming barriers were also discussed.
To improve DSE, goal-setting strategies were used to evaluate performances (Lorig et al., 2006). Group interventions were performed for vicarious experiences, and each participant received personalized telephone counseling (5 to 10 minutes/week). During the telephone counseling, the current authors reviewed the participant's blood glucose results, self-management checklists, and stress caused by self-management, and asked whether he/she achieved weekly goals and encouraged him/her to achieve desired DSMB.
Participants in the control group were invited to attend weekly 1-hour sessions for 12 consecutive weeks, although this intervention was only a general lecture regarding diabetes. The topic of the lecture was the same as the program, but it did not consider participants' health literacy and health-related characteristics, and did not use multiple strategies. Materials used in the lecture were based on the government website (access http://health.mw.go.kr) and public health center open sources that senior centers usually used.
Both groups' outcomes were evaluated using pre–post analyses, with DSMB and diabetes biomarkers as the primary outcomes. Posttest evaluations were performed immediately after the 12-week programs finished, and included surveys (i.e., sociodemographic characteristics, health literacy, and diabetes-related variables), a physical examination (with blood pressure testing), and blood testing (HbA1c and serum lipids). The surveys and physical examinations were performed by four trained third-and fourth-year nursing students who helped participants complete the questionnaires. HbA1c levels were evaluated by an employee of the company that supplied the HbA1c analyzer, and nursing graduate students measured the serum lipids level. All participants fasted for 8 hours on the day before the blood samples were obtained, and were subsequently offered milk and boiled eggs.
Sociodemographic Characteristics. A survey was used to obtain information regarding age, sex, living status, income, education, and health status. Self-reported health status included the duration of diabetes, number of complications, MMSE-K score (Park & Kwon, 1989), experience with diabetes education, and experience with hypoglycemia. The MMSE-K has 30 items, and each item is worth 1 point; scores <24 points indicate the presence of dementia (Park & Kwon, 1989), and any individuals with dementia were excluded from the study.
Health Literacy. Health literacy levels were measured at the pretest evaluation using the self-administered 4-item Korean Health Literacy Assessment Tool (Lee et al., 2011), which was developed based on the Rapid Estimate of Adult Literacy in Medicine (Davis et al., 1993). The instrument uses a 4-point Likert scale to examine the individual's understanding of 66 medical terms without experiencing the feeling of being tested. A score <44 points indicates an education below the sixth-grade level. The instrument has a Cronbach's alpha of 0.97 among community-dwelling older adults with diabetes (Park & Hwang, 2014). Cronbach's alpha for the current study was 0.96.
Diabetes Self-Management Knowledge. The Diabetes Self-Management Knowledge for Older Adults (Song et al., 2013) was used to evaluate DSK. This instrument was developed for older adults with diabetes in senior centers, and 75% of the development populations were receiving oral treatments for diabetes. The instrument comprises 22 single-point items, and higher total scores reflect greater DSK. The construct and criterion validity have been verified with K-R 20 reliability (Cronbach's alpha = 0.54). Cronbach's alphas for the current study were 0.61 to 0.65.
Diabetes Health Belief. The Health Belief Scale for Diabetes (Park, 1985) was used to evaluate DHB. This instrument has 18 items that are evaluated using a 5-point Likert scale. The items evaluate susceptibility and severity (nine items, Cronbach's alpha = 0.76), barriers (four items, Cronbach's alpha = 0.65), and benefits (five items, Cronbach's alpha = 0.69) (Park, 1985). In the current study, Cronbach's alphas were 0.82 to 0.85 for susceptibility and severity, 0.61 to 0.69 for barriers, and 0.69 to 0.82 for benefits.
Diabetes Management Self-Efficacy. The Diabetes Management Self-Efficacy Scale for Older Adults (Song et al., 2014) was used to evaluate DSE. This instrument has 17 items that evaluate being active (two items), healthy eating (two items), monitoring health status and problem solving for hypoglycemia (four items), problem solving for hyperglycemia (two items), medications and healthy coping (three items), and reducing risks (four items). Each item is evaluated using a 4-point Likert scale, and higher scores indicate better DSE. The construct and criterion validity have been verified, and Cronbach's alpha was 0.84. In the current study, Cronbach's alphas were 0.80 to 0.90.
Diabetes Self-Management Behaviors. The Korean version of the Summary of Diabetes Self-Care Activities Questionnaire (Chang & Song, 2009) was used to evaluate DSMB. This instrument has 17 items that evaluate diet (five items), exercise (two items), medication (three items), glucose monitoring (two items), and foot care (five items). The construct validity was verified, and Cronbach's alpha was 0.77 (Chang & Song, 2009). In the current study, Cronbach's alphas were 0.73 to 0.74.
Diabetes Biomarkers. Diabetes biomarkers were defined as HbA1c, blood pressure, and serum lipids. HbA1c levels reflect blood glucose management during the past 2 to 3 months; <7.5% is the normal standard for older adults with diabetes, but this standard varies according to individuals' health status (American Diabetes Association, 2016). Serum lipids included total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein, and triglycerides (TG). Serum levels of HbA1c and lipids were measured using portable analyzers (HbA1c: A1Care®; serum lipids: Cholestech LDX®). Based on the manufacturers' instructions, blood samples were collected from the fingertip using sample collectors (2.5 µL for HbA1c and 40 µL for serum lipids), which were subsequently inserted into the cartridge. The analyses take approximately 4 minutes for HbA1c levels and 7 minutes for serum lipids levels. An upper arm automatic blood pressure monitor (Omron T-M®) was used based on the manufacturer's instructions while participants sat comfortably in a chair with their arms in the horizontal position.
All data were analyzed using SPSS® version 21. Sociodemographic characteristics were reported using n values and percentages or means and standard deviations. The pre–post analysis compared differences between groups using chi-square test or Fisher's exact test for categorical variables, and the independent t test or Mann-Whitney U test for continuous variables. For the pre–post analysis in each group for HbA1c levels, the paired t test and Wilcoxon test were used. Differences were considered statistically significant at a level of 0.05. There were no missing data, as most participants requested help from the nursing students to complete the surveys.
Sixty-three individuals were recruited, but seven were excluded based on exclusion criteria. Thus, 56 participants were randomly assigned to the groups, but five subsequently withdrew because of hospitalization (two in the intervention group and one in the control group), change of address (one in the control group), and personal issues (one in the control group). Therefore, data from 51 participants were analyzed (26 in the intervention group and 25 in the control group). The average participation rate was 85.7% for each session in the intervention group, and nine participants attended all 12 sessions. However, the participation rate was only 78.6% in the control group, and only five participants attended all 12 sessions. The number of withdrawals was greater in the control group. Participants in the intervention group indicated they were highly satisfied with the program (intervention group: mean [SD] = 3.8 [1.2] versus control group: mean [SD] = 3.7 [2.4] using a 4-point Likert scale).
Mean participant age was 74.5 years (SD = 4.8 years). Participants had been diagnosed with diabetes for an average of 11.5 years (SD = 8.2 years), had an average of 1.5 complications (SD = 1.2 complications), and had an average MMSE-K score of 27.4 points (SD = 2 points). Approximately 57% of participants were women. The mean health literacy level was 46.2 points (SD = 15 points), and 43.13% of participants were below the sixth-grade health literacy level. Only 15.7% of participants had experience with diabetes education. There were no significant differences in the sociodemographic characteristics (Table 1).
Sociodemographic Characteristics at Pretest
DSK, DHB, DSE, and DSMB
The pretest analysis did not reveal any significant differences between groups regarding DSK, DHB, DSE, and DSMB. The posttest analysis revealed significantly higher scores in the intervention group for DSK (p = 0.046), DSE (p = 0.046), and DSMB total score (p = 0.012) (Table 2). Among the DSMB subscales, the intervention group had a significantly higher self-monitoring of blood glucose (SMBG) score (p = 0.002, Mann-Whitney U test), although no inter-group differences in DHB were observed for susceptibility and severity (p = 0.989, t test), barriers (p = 0.556), and benefits (p = 0.079). There were also significant differences between groups in pre–post changes for the DHB benefit subscale (p = 0.043), DSE (p = 0.006), DSMB total (p = 0.008), DSMB diet (p = 0.029), and SMBG subscale (p < 0.001) (Table 3). The effect sizes of the variables were 0.58 for DSK, 0.57 for DSE, and 0.73 for DSMB.
Comparison of Variable Between Groups
Pre–Post Changes Between Groups
The pretest analysis did not reveal any significant intergroup differences in diabetes biomarkers. Furthermore, no significant differences were observed between groups in the posttest analysis for HbA1c levels (p = 0.287), systolic blood pressure level (p = 0.313), diastolic blood pressure level (p = 0.527), and serum lipids levels (p = 0.969) (Table 2). Moreover, there were no significant intergroup differences in pre–post changes for HbA1c levels (p = 0.821), systolic blood pressure levels (p = 0.057), diastolic blood pressure levels (p = 0.056), and serum lipids levels (p = 0.269) (Table 3). Nevertheless, the intervention group had significantly improved HbA1c levels in the pre–post analysis (p = 0.008, paired t test), although no significant difference was observed in the control group (p = 0.051, Wilcoxon test).
Senior centers have generally used diabetes self-management programs that were developed for relatively young adults, whereas the current study evaluated a program that was customized based on the characteristics and health literacy of older adults. In addition, a workbook and educational materials were developed that decreased the reliance on the communication skills of the educator(s). The program generated significant inter-group differences at the posttest analysis for DSK, DSE, and DSMB, as well as in pre–post changes for the DHB benefit subscale, DSE, DSMB total, DSMB diet, and SMBG subscale. Participants also reported being highly satisfied with the program.
The intervention group had a significantly higher DSK score than the control group in the posttest analysis, although most participants did not have previous diabetes education experience and both groups had relatively high DSK score changes. Moreover, the health literacy score of the intervention group (mean [SD] = 44.4 ) was lower than that of the control group (mean [SD] = 48 [12.6]), and a significant inter-group difference was observed in posttest DSK. This finding is because of health literacy–considered need assessment, material development, and multiple strategies, which corresponds well with a previous study (Rothman et al., 2004) that used mixed strategies: teach-back methods, concrete and simplified education, and goal setting strategies. A systematic review also revealed that interventions using mixed strategies were more effective than single-strategy interventions (Sheridan et al., 2011). In addition, the effect size of the DSK score (0.58) from the current study was higher than that from a similar study (0.33), which was based on social cognitive theory and considered health literacy and culture (Rosal et al., 2011). Therefore, the current program appears to be effective for improving DSK scores.
In DHB, previous research has revealed that only DSK indirectly affected DHB, which subsequently improved DSMB (Osborn, Bains, & Egede, 2010). Few previous studies have evaluated the relationship between health literacy and DHB, but a significant difference was observed in the current study in the benefit subscale score between the intervention (0.28) and control (−0.08) groups. This result indicates that participants recognized the benefit of diabetes self-management. However, the posttest analysis did not reveal any significant differences in the DHB score, although it can be difficult to modify lifetime-based DHB during a short period, which could indicate that a long-term intervention is required to change DHB.
The intervention group had a significantly higher DSE score compared to the control group, and significant inter-group differences were detected in pre–post changes because participants were given many opportunities to practice in everyday life and experience the effectiveness of self-management. Similar results were observed in a study of a telephone consulting program for patients with diabetes and low health literacy, which was based on the self-efficacy theory (Schillinger, Handley, Wang, & Hammer, 2009). Moreover, the effect size from the previous study (0.41) was noticeably lower than that in the current study (0.57), which indicates that the current program was more effective in improving DSE.
The current study also revealed significant differences in the DSMB posttest and pre–post change results, with better values observed in the intervention group. Similar findings were reported by Wallace et al. (2009), who evaluated an adult health literacy–appropriate program that involved goal setting, problem solving, and short consultations for adult patients with diabetes. Furthermore, the current study revealed significantly greater pre–post changes for diet and the SMBG subscale in the intervention group. In a previous study (Fisher, Kohut, Schachner, & Stenger, 2011), older adults with diabetes experienced more SMBG-related barriers, such as lack of knowledge, skills, money, and blurred vision. Although regular SMBG is required to manage diabetes, many older adults only check their blood glucose levels when they visit a hospital. Moreover, in South Korea, only 8.9% of patients with diabetes receive insulin-based treatment, which is highly correlated with SMBG (Korean Diabetes Association, 2016). In contrast, 28.7% of American patients with diabetes receive insulin-based treatment (American Diabetes Association, 2015). Through practice and telephone consultations in the program, the current study attempted to overcome knowledge, skills, and health status barriers. In addition, an autotransmitting blood glucose meter and related products were provided at no cost. Moreover, the blood glucose meter showed changes instantly, which allowed participants to more actively control their diet. The health literacy–considered program also provided simple instructions for diet control.
No significant differences were observed in the values for HbA1c, systolic and diastolic blood pressure, and serum lipids. The absence of these differences is likely related to participants having approximately the recommended values for HbA1c, blood pressure, and serum lipids (HbA1c: <7.5%, blood pressure: <140/90 mmHg, HDL: ≥40 mg/dL for men and ≥50 mg/dL for women, and TG: ≤150 mg/dL) (American Diabetes Association, 2016). Similar results have been reported by Schillinger et al. (2009) and Rosal et al. (2011), who did not detect any significant differences because mean systolic and diastolic blood pressure, HDL, and TG levels were already within the recommended ranges. It is also possible that the control group performed sufficient self-management based on the usual care they received. For example, a previous study did not detect any significant differences between groups because both experienced improvements (Rosal et al., 2011). Finally, it is possible that the study's duration was insufficient to achieve significant changes in the measured biomarkers (especially HbA1c levels) through only weekly self-management sessions. Nevertheless, significant pre–post improvement was detected in the intervention group's HbA1c levels. Therefore, the current results indicate that the health literacy program improved participants' DSK, DHB subscale, DSE, and DSMB values, but had limited ability to alter their diabetes biomarkers during the study's duration.
The current study has several limitations. First, participants were only selected from two senior centers, which is associated with a risk of selection bias. Second, the sample was small. Third, use of self-reported data is associated with known risks of bias, although the instruments used were considered valid. Finally, using multiple inference tests may have increased the likelihood of type I errors.
Implications for Clinical Practice
The current study revealed that the program could improve participants' DSK, DSE, and DSMB values, and that participants were highly satisfied with the program. As the study considered the health literacy and health-related characteristics of older adults, the program may be useful for health care providers who work with older adults, such as nurses who work in senior centers. Thus, nurses may be able to use this program to improve their nursing practice as well as the health of their patients. Nevertheless, further studies with larger sample sizes and longer follow up are needed to validate the findings. It may also be useful to consider health literacy programs for other chronic diseases.
Health literacy can help determine individuals' health status, facilitate decision making, and improve implementation of self-management programs. However, diabetes self-management research regarding healthy literacy remains a relatively young field in Korea, and few Korean studies exist evaluating this issue among older adults. Although the underlying mechanisms require further research, the current study revealed that the program was effective in improving participants' DSK, DSE, and DSMB, which may be useful for improving HbA1c levels.
- American Diabetes Association. (2015). Fast facts—Data and statistics about diabetes. Retrieved from http://professional.diabetes.org/content/fast-facts-data-and-statistics-about-diabetes
- American Diabetes Association. (2016). Standards of medical care in diabetes: 2016. Diabetes Care, 39(Suppl. 1), S4–S5. doi:10.2337/dc16-S003 [CrossRef]
- Berkman, N.D., Sheridan, S.L., Donahue, K.E., Halpern, D.J., Viera, A., Crotty, K. & Viswanathan, M. (2011). Health literacy interventions and outcomes: An updated systematic review (Vol. 199). Rockville, MD: Agency for Healthcare Research and Quality.
- Cavanaugh, K., Wallston, K.A., Gebretsadik, T., Shintani, A., Huizinga, M.M., Davis, D. & DeWalt, D. (2009). Addressing literacy and numeracy to improve diabetes care: Two randomized controlled trials. Diabetes Care, 32, 2149–2155. doi:10.2337/dc09-0563 [CrossRef]
- Chang, S. (2010). Structural equation modeling on health-related quality of life in older adults with type 2 diabetes mellitus (Unpublished doctoral dissertation). Seoul National University, Seoul.
- Chang, S. & Song, M. (2009). The validity and reliability of a Korean version of the summary of diabetes self-care activities questionnaire for older patients with type 2 diabetes. Korean Journal of Adult Nursing, 21, 235–244.
- Chin, Y.-R. & Choi, K.-W. (2014). Readability and suitability evaluation of educational materials on diabetes mellitus. Korean Journal of Health Service Management, 8, 161–174. doi:10.12811/kshsm.2014.8.2.161 [CrossRef]
- Davis, T.C., Long, S.W., Jackson, R.H., Mayeaux, E., George, R.B., Murphy, P.W. & Crouch, M.A. (1993). Rapid estimate of adult literacy in medicine: A shortened screening instrument. Family Medicine, 25, 391–395.
- Faul, F., Erdfelder, E., Buchner, A. & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41, 1149–1160. doi:10.3758/BRM.41.4.1149 [CrossRef]
- Fisher, W.A., Kohut, T., Schachner, H. & Stenger, P. (2011). Understanding self-monitoring of blood glucose among individuals with type 1 and type 2 diabetes. Diabetes Educator, 37, 85–94. doi:10.1177/0145721710391479 [CrossRef]
- Fransen, M.P., von Wagner, C. & Essink-Bot, M.-L. (2012). Diabetes self-management in patients with low health literacy: Ordering findings from literature in a health literacy framework. Patient Education and Counseling, 88, 44–53. doi:10.1016/j.pec.2011.11.015 [CrossRef]
- International Diabetes Federation. (2015). IDF diabetes atlas: 7th edition. Retrieved from http://www.diabetesatlas.org
- Jeong, G., Oh, Y., Lee, Y., Son, C., Park, B. & Lee, S. (2012). Survey of the elderly 2011. Retrieved from https://www.kihasa.re.kr/html/jsp/english/public/view.jsp?bid=31&ano=601&key=title&query=2011&queryString=YmlkPTMxJmtleT10aXRsZSZxdWVyeT0yMDEx
- Kim, S.H. & Lee, E. (2008). The influence of functional literacy on perceived health status in Korean older adults. Journal of Korean Academy of Nursing, 38, 195–203. doi:10.4040/jkan.2008.38.2.195 [CrossRef]
- Kim, Y.S., Park, B.H. & Lee, H.Y. (2014). A study on predicting health literacy of Korean elderly using Andersen's health behavior model. Journal of Welfare for the Aged, 65, 35–57.
- Korean Diabetes Association. (2016). Diabetes fact sheet in Korea 2016. Retrieved from http://www.diabetes.or.kr/bbs/index.html?code=e_resource&category=1
- Kripalani, S. & Weiss, B.D. (2006). Teaching about health literacy and clear communication. Journal of General Internal Medicine, 21, 888–890. doi:10.1111/j.1525-1497.2006.00543.x [CrossRef]
- Lee, S.H., Choi, E.-H.-R., Je, M.-J., Han, H.-S., Park, B.-K. & Kim, S.-S. (2011). Comparison of two versions of KHLAT for improvement strategies. Korean Journal of Health Education and Promotion, 28, 57–65.
- Lorig, K., Holman, H., Sobel, D., Laurent, D. & Gonzalez, V. (2006). Living a healthy life with chronic conditions: Self-management of heart disease, fatigue, arthritis, worry, diabetes, frustration, asthma, pain, emphysema, and others. Palo Alto, CA: Bull.
- Ntiri, D.W. & Stewart, M. (2009). Transformative learning intervention: Effect on functional health literacy and diabetes knowledge in older African-Americans. Gerontology & Geriatrics Education, 30, 100–113. doi:10.1080/02701960902911265 [CrossRef]
- Nutbeam, D. (1998). Health promotion glossary. Health Promotion International, 13, 349–364. doi:10.1093/heapro/13.4.349 [CrossRef]
- Osborn, C.Y., Bains, S.S. & Egede, L.E. (2010). Health literacy, diabetes self-care, and glycemic control in adults with type 2 diabetes. Diabetes Technology & Therapeutics, 12, 913–919. doi:10.1089/dia.2010.0058 [CrossRef]
- Park, H. (1985). Effect of personality and health belief to the therapeutic behavior on diabetes patients (Unpublished Master's thesis). Korea University, Seoul.
- Park, H. & Hwang, S.-K. (2014). Linguistic and functional health literacy among community-dwelling old adults. Global Health Nursing, 4, 49–58.
- Park, J.-H. & Kwon, Y.C. (1989). Standardization of Korean Version of the mini-mental state examination (MMSE-K) for use in the elderly. Part II: Diagnostic validity. Journal of Korean Neuropsychiatric Association, 28, 508–513.
- Rosal, M.C., Ockene, I.S., Restrepo, A., White, M.J., Borg, A., Olendzki, B. & Reed, G. (2011). Randomized trial of a literacy-sensitive, culturally tailored diabetes self-management intervention for low-income Latinos. Diabetes Care, 34, 838–844. doi:10.2337/dc10-1981 [CrossRef]
- Rothman, R., DeWalt, D.A., Malone, R., Bryant, B., Shintani, A., Crigler, B. & Pignone, M. (2004). Influence of patient literacy on the effectiveness of a primary care–based diabetes disease management program. JAMA, 292, 1711–1716. doi:10.1001/jama.292.14.1711 [CrossRef]
- Schillinger, D., Handley, M., Wang, F. & Hammer, H. (2009). Effects of self-management support on structure, process, and outcomes among vulnerable patients with diabetes: A three-arm practical clinical trial. Diabetes Care, 32, 559–566. doi:10.2337/dc08-0787 [CrossRef]
- Schillinger, D., Piette, J., Grumbach, K., Wang, F., Wilson, C., Daher, C. & Bindman, A.B. (2003). Closing the loop: Physician communication with diabetic patients who have low health literacy. Archives of Internal Medicine, 163, 83–90. doi:10.1001/archinte.163.1.83 [CrossRef]
- Sheridan, S.L., Halpern, D.J., Viera, A.J., Berkman, N.D., Donahue, K.E. & Crotty, K. (2011). Interventions for individuals with low health literacy: A systematic review. Journal of Health Communication, 16, 30–54. doi:10.1080/10810730.2011.604391 [CrossRef]
- Shrivastava, S.R., Shrivastava, P.S. & Ramasamy, J. (2013). Role of self-care in management of diabetes mellitus. Journal of Diabetes & Metabolic Disorders, 12, 12–14. doi:10.1186/2251-6581-12-14 [CrossRef]
- Song, M., Choi, S., Kim, S.-A., Seo, K., Lee, S.J. & Kim, E.H. (2014). Development and validation of the diabetes management self-efficacy scale for older adults (DMSES-O). Journal of Muscle and Joint Health, 21, 184–194. doi:10.5953/JMJH.2014.21.3.184 [CrossRef]
- Song, M., Kim, S.-A., Choi, S.Y., Seo, K.S., Lee, S.J. & Kim, E.H. (2013). Development and validation of the diabetes self-management knowledge scale for older adults (DSMK-O). Journal of the Korean Gerontological Society, 33, 537–550.
- Song, M. & Kim, S.H. (2006). The health services of Korean senior centers. Journal of Korean Gerontological Nursing, 8, 15–23. doi:10.4040/jkan.2006.36.1.15 [CrossRef]
- Song, M., Lee, M. & Shim, B. (2010). Barriers to and facilitators of self-management adherence in Korean older adults with type 2 diabetes. International Journal of Older People Nursing, 5, 211–218. doi:10.1111/j.1748-3743.2009.00189.x [CrossRef]
- Sung, N.J., Lee, D.U. & Park, K.H. (2004). Suitability assessment of patients' education materials made by Korean Academy of Family Medicine. Journal of the Korean Academy of Family Medicine, 25, 669–677.
- Tomky, D., Cypress, M., Dang, D., Maryniuk, M., Peyrot, M. & Mensing, C. (2008). AADE7™ self-care behaviors. Diabetes Educator, 34, 445–449. doi:10.1177/0145721708316625 [CrossRef]
- Tshiananga, J.K.T., Kocher, S., Weber, C., Erny-Albrecht, K., Berndt, K. & Neeser, K. (2011). The effect of nurse-led diabetes self-management education on glycosylated hemoglobin and cardiovascular risk factors: A meta-analysis. Diabetes Educator, 38, 108–123. doi:10.1177/0145721711423978 [CrossRef]
- von Wagner, C., Steptoe, A., Wolf, M.S. & Wardle, J. (2009). Health literacy and health actions: A review and a framework from health psychology. Health Education & Behavior, 36, 860–877. doi:10.1177/1090198108322819 [CrossRef]
- Wallace, A.S., Seligman, H.K., Davis, T.C., Schillinger, D., Arnold, C.L., Bryant-Shilliday, B. & DeWalt, D.A. (2009). Literacy-appropriate educational materials and brief counseling improve diabetes self-management. Patient Education and Counseling, 75, 328–333. doi:10.1016/j.pec.2008.12.017 [CrossRef]
Sociodemographic Characteristics at Pretest
|Variable||n (%)||t Test or Chi-Square||p Value|
|Intervention Group (n = 26)||Control Group (n = 25)|
| Female||14 (53.9)||15 (60)||0.20||0.657|
| Male||12 (46.2)||10 (40)|
| Alone||12 (46.2)||10 (40)||2.15a||0.589|
| Spouse||9 (34.6)||7 (28)|
| Two generations||4 (15.4)||4 (16)|
| Three generations or more||1 (3.9)||4 (16)|
| <200,000||6 (23.1)||6 (24)||0.02||0.990|
| ∼200,000 to 400,000||7 (26.9)||7 (28)|
| >400,000||13 (50)||12 (48)|
| None||5 (19.2)||2 (8)||3.89a||0.448|
| Elementary school||8 (30.8)||6 (24)|
| Middle school||5 (19.2)||9 (36)|
| High school||5 (19.2)||7 (28)|
| College or more||3 (11.5)||1 (4)|
| >44 (above six-grade level)||14 (53.9)||15 (60)||0.20||0.657|
| ≤44 (below sixth-grade level)||12 (46.2)||10 (40)|
|Experience with diabetes education|
| No||23 (88.5)||20 (80)||0.69a||0.465|
| Yes||3 (11.5)||5 (20)|
|Experience with hypoglycemia|
| No||20 (76.9)||16 (64)||1.03||0.311|
| Yes||6 (23.1)||9 (36)|
Comparison of Variable Between Groups
|Variable||Time||Mean (SD)||t Test or Mann-Whitney U Test||p Value|
|Intervention Group (n = 26)||Control Group (n = 25)|
|DSK||Pretest||15.54 (2.79)||15.48 (3.29)||−0.06||0.946|
|Posttest||18.58 (2.14)||17.04 (3.14)||−2.05||0.046*|
| Susceptibility and severity||Pretest||3.03 (0.80)||3.15 (1.04)||0.47||0.643|
|Posttest||3.25 (0.86)||3.25 (0.74)||−0.01||0.989|
| Barrier||Pretest||2.85 (0.77)||3.00 (0.78)||0.71||0.482|
|Posttest||2.77 (0.91)||2.92 (0.91)||0.59||0.556|
| Benefit||Pretest||3.82 (0.59)||3.74 (0.67)||−0.40||0.690|
|Posttest||4.09 (0.85)||3.67 (0.85)||−1.80||0.079|
|DSE||Pretest||49.04 (8.89)||51.24 (9.71)||0.85||0.402|
|Posttest||57.77 (8.18)||52.88 (8.88)||−2.05||0.046*|
| Total||Pretest||65.92 (15.99)||69.52 (16.9)||0.78||0.439|
|Posttest||83.27 (11.62)||73.52 (14.8)||−2.62||0.012*|
| Diet||Pretest||3.47 (1.7)||4.16 (1.64)||1.48||0.146|
|Posttest||4.53 (1.3)||4.04 (1.29)||−1.35||0.184|
| Exercise||Pretest||4.54 (1.74)||3.98 (2.08)||−1.04||0.304|
|Posttest||4.48 (1.23)||4.10 (1.83)||−0.88||0.386|
| SMBG||Pretest||2.29 (1.19)||2.42 (2.31)||249.00a||0.144|
|Posttest||5.37 (1.9)||3.12 (2.42)||162.00a||0.002*|
| Foot care||Pretest||4.40 (1.75)||4.68 (1.51)||0.61||0.544|
|Posttest||5.45 (0.85)||3.12 (1.54)||−1.14||0.263|
| Medication||Pretest||6.46 (1.21)||6.26 (1.51)||309.50a||0.685|
|Posttest||6.85 (0.61)||6.82 (0.56)||312.00a||0.635|
| Total||Pretest||6.82 (0.79)||7.15 (1.02)||1.29||0.204|
|Posttest||6.51 (0.83)||6.73 (0.6)||1.08||0.287|
| Systolic||Pretest||141.69 (19.52)||132.16 (14.71)||−1.964||0.055|
|Posttest||132.58 (11.5)||131.08 (13.77)||−0.422||0.313|
| Diastolic||Pretest||75.31 (7.27)||78.76 (8.37)||1.575||0.122|
|Posttest||75.50 (7.64)||73.24 (6.92)||−1.106||0.527|
|Serum lipids (mg/dL)|
| Total cholesterol||Pretest||164.38 (35.65)||156.40 (29.17)||−0.87||0.387|
|Posttest||159.97 (28.99)||160.31 (32.72)||0.04||0.969|
| High-density lipoprotein||Pretest||48.27 (17.13)||45.84 (15.6)||−0.53||0.599|
|Posttest||49.62 (15.3)||48.04 (18.13)||−0.34||0.738|
| Triglyceride||Pretest||159.54 (72.97)||136.12 (43.7)||−1.38||0.173|
|Posttest||156.00 (77.39)||157.64 (75.77)||0.08||0.939|
| Low-density lipoprotein||Pretest||83.62 (34.92)||83.32 (25.99)||−0.03||0.973|
|Posttest||79.15 (27.61)||80.74 (30.7)||0.2||0.846|
Pre–Post Changes Between Groups
|Variable||Mean (SD)||t Test or Mann-Whitney U Test||p Value|
|Intervention Group (n = 26)||Control Group (n = 25)|
|DSK||3.04 (3.55)||1.56 (3.19)||228.00a||0.065|
| Susceptibility and severity||0.23 (0.73)||0.10 (0.67)||−0.64||0.529|
| Barrier||−0.08 (0.89)||−0.08 (0.89)||−0.01||0.990|
| Benefit||0.28 (1.00)||−0.08 (0.72)||218.50a||0.043*|
|DSE||8.73 (7.98)||1.64 (12.38)||178.00a||0.006*|
| Total||17.35 (16.42)||4.00 (16.90)||184.50a||0.008*|
| Diet||1.60 (2.18)||−0.12 (1.50)||−2.26||0.029*|
| Exercise||−0.06 (1.87)||0.12 (1.51)||0.37||0.711|
| SMBG||3.08 (2.11)||0.70 (2.26)||124.50a||<0.001*|
| Foot care||1.05 (1.98)||0.37 (1.73)||−1.30||0.199|
| Medication||0.38 (1.17)||0.56 (1.24)||300.00a||0.526|
| Total||−0.32 (0.56)||−0.42 (1.00)||313.00a||0.821|
| Systolic||−9.52 (17.35)||−1.00 (13.69)||−1.95||0.057|
| Diastolic||0.19 (8.66)||−5.52 (10.18)||−2.16||0.056|
|Serum lipids (mg/dL)|
| Total cholesterol||−4.42 (32.07)||3.91 (19.77)||1.12||0.269|
| High density lipoprotein||1.35 (9.09)||2.20 (6.13)||313.50a||0.828|
| Triglyceride||−3.54 (72.13)||21.52 (57.06)||233.50a||0.085|
| Low density lipoprotein||−4.46 (32.14)||−2.58 (18.58)||322.50a||0.962|
The Contents of the Program
|Session||AADE-7 Domains & Characteristics of older adults||Topics||Session Specific Strategies||Common Procedure|
|1||Monitoring health status & Problem Solving: At risk of cognitive impairment, memory loss, blurred vision, and hypoglycemia||Overview of the program Pre-test|
Consulting pre-test results
|For each topic:
Reviewing the last session topic and checking the self-management practice diary for the last 1 week (5min)†
Presenting today's topic and key questions by virtual character (5min)*
Learning the contents (20min) *
Participants explain the answers to the virtual character (8min)*
Checking the answer (2min)*
Assessing current self-management status (5min)†
Setting-goals and discuss the way to achieve goals (5min)†
Explaining the self-management practice diary as homework (10min)†
|2||Understanding diabetes management|
Educate the meaning and managing of diabetes using 14 font letters, illustrations and photos
|Blood glucose monitoring|
Educate how to use the blood glucose meter
Repeat the device using practice
Educate hypoglycemia symptoms (typical/atypical) and management
|4||Healthy Eating: At risk of obesity, constipation, and change in sweet or salty taste||Dietary management 1: The food good for diabetes|
Educate the proper amount of carbohydrate, protein, fat, fruit, sugar, and salt intake using place mat and rice bowl, soy milk, and water with salinity 0.6%
Provide cooking tips
Recommend fiber intake
|5||Dietary management 2: The food need to be careful|
|6||Being Active: At risk of arthritis, osteoporosis, blurred vision, and decreased lung elasticity or cardiac output||Exercise management 1: Warm-up/wrap-up exercise|
Exercise with warm-up/wrap-up and Thera-band video
Exercise in the safe place
Control the exercise time and intensity
|7||Exercise management 2: Thera-band exercise|
|8||Medication: At risk of cognitive impairment, and memory loss||Medication management|
Explain the individual prescription
Educate tips for medication at the right time without forgetting
|9||Reducing Risks: At risk of injury or delayed wound healing, and changing in the mouth||Complications management 1: Foot care|
Educate foot assessment with hand mirror
Educate and practice foot exercise and massage
|10||Complications management 2: Oral care|
Educate and practice brushing using toothbrush model, dental floss, and interdental tooth brush
Educate the proper denture care
|11||Healthy Coping: At risk of depression||Depression and stress management|
Assess the depression symptoms or risk factors
Educate depression and stress management with comedy video and music
|12||-||Closing Ceremony Post-test|
Consulting post-test results
The Workbook Based on the Suitability Assessment of Material (SAM)
Provide a purpose and topic of each session
Present the topic at the left upper side of the workbook in each session
Provide limited essential information: less than 5 sub-headings
Provide key messages at the end of the each session
Written in conversational style and active voice with simple sentences: less than 8 words
Contains simple information in each sentence
Change medical terms into common words
Provide the context by the virtual character before presenting new information
Provide topic and sub-headings in each session
Provide the cover of the workbook with older adults and the self-management essentials illustrations
Provide simple and familiar illustrations and tables
Provide the illustrations related to the topics
Provide captions in illustrations, tables, and photographs that explain the key messages
|Layout and typography|
Follow fixed layout frame with adequate space in every session
Print in non-gloss surface with high contrast between type and paper
Use underline or bold for key messages
Use Gothic text with 14 font type
Provide sub-headings for more than 5 items
|Learning stimulation and motivation|
Present topic related questions by the virtual character at the beginning of each session
Minimize the writing and maximized using O, X or multiple choice
Explain specific behaviors in common words and examples
Divide topics into sub-headings
Provide virtual character recently diagnosed diabetic older adult
Provide images and examples represent the culture of the older adults in positive ways