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Abstract

The role of gender in determining the level of health literacy in Korean adults is unclear. This study aimed to investigate the level of health literacy in Korean adults and identify factors associated with health literacy by gender. This study employed a cross-sectional survey design with a convenient sample of 585 community-dwelling Korean adults age19 years and older. Health literacy was measured by using eight items selected from Chew et al.’s 16-question self-reported health literacy measure. In accordance with Andersen’s health behavior model, predisposing, enabling, and need factors were included in the multiple regression model. Women indicated a higher level of health literacy than men in understanding medical forms, directions on medication bottles, and written information offered by health care providers. Additionally, for Korean women, a higher level of health literacy was associated with attaining a higher education level and having a consistent place to receive care. Unmarried men and men who had higher self-rated health reported a higher level of health literacy compared with their counterparts. Lower level of depression and higher monthly income were significantly linked to a higher level of health literacy in both men and women. This study has established the importance of gender differences in health literacy and suggests gender-specific intervention may be warranted to reduce the existing gap in health literacy in both Korean men and women. Future research should replicate this study to confirm whether or not our finding is an international phenomenon.

Keywords

health literacy gender depression health behavior model health equity Korean adults

Introduction

Attention to the issue of health literacy has increased in South Korea (hereafter “Korea”), just as it has in the United States. In Korea, more than one third of adults have limited health literacy (J. Kim, 2011; S. Kim, Kim, & Lee, 2005), which is similar to the rate among American adults (Kunter, Greenberg, Jin, & Paulsen, 2006; Paasche-Orlow, Parker, Gazmararian, Nielsen-Bohlman, & Rudd, 2005). This phenomenon is concerning given that limited health literacy is associated with less knowledge of health services (Davis et al., 1996; Lindau et al., 2002), infrequent utilization of preventive health care services (Scott, Gazmararian, Williams, & Baker, 2002), poorer adherence to medical instructions (DeWalt, Berkman, Sheridan, Lohr, & Pignone, 2003; Kalichman, Ramachandran, & Catz, 1999), and increased mortality (Bennett et al., 1998; Kunter et al., 2006).

Existing literature in Korea has identified that educational attainment and monthly income are significantly associated with the level of health literacy regardless of age of study participants (J. Kim, 2011; S. Kim et al., 2005; S. H. Kim, & Lee, 2008; Lee & Kang, 2008; Park & June, 2011). However, findings about an association between gender and health literacy are mixed. In S. Kim et al.’s (2005) study, the level of health literacy was significantly higher in Korean males, which is in conflict with J. Kim’s (2011) study reporting that levels were higher in females. This inconsistency is also found in studies conducted in the United States (Kunter et al., 2006; Paasche-Orlow et al., 2005).

The purpose of this study was to investigate the level of health literacy in Korean males and females and identify factors associated with health literacy by gender. Relevant factors to health literacy were included in the model guided by Andersen’s behavioral model of health services use (Andersen, 1995). Andersen’s model was initially developed to understand individuals’ health care service utilization (Andersen, 1995). However, the model can be utilized to identify factors associated with health literacy (Lee, Choi, & Park, 2014; Wister, Malloy-Weir, Rootman, & Desjardins, 2010) because health literacy is directly associated with health care seeking and the use of health care services. In the Andersen model, health literacy might be a resource or component rather than an outcome. In this context, individuals with a higher level of health literacy may be able to achieve a higher level of health care utilization.

Existing studies, for example, reported a direct positive correlation between adequate level of heath literacy and timely use of preventive health care (Chen, Hsu, Tung, & Pan, 2013) and a negative association with hospitalization and emergency room use (Cho, Lee, Arozullah, & Crittenden, 2008). Higher levels of cost for use of emergency care or hospital service was observed among people with low health literacy (Cho, Lee, Arozullah, & Crittenden, 2008; Howard, Gazmararian, & Parker, 2005). Another benefit of using the model is that it provides a systematic framework for examining factors associated with health literacy inclusively by categorizing factors as predisposing, enabling, and need factors (see the study’s conceptual framework in Figure 1).

Figure 1.

Conceptual framework of the study.

According to Andersen’s behavioral model, predisposing factors are exogenous, such as demographics; enabling factors include resources that are necessary but not sufficient conditions for use of health care; and need factors include perceived need for health care (Andersen, 1995). Adopting this model, we classified potentially relevant factors to health literacy as predisposing (age, marital status, and use of Eastern medicine), enabling (education, monthly income, and having a primary hospital/clinic), and need (self-rated health, depression, and number of chronic diseases) factors to understand what factors might play a significant role in determining health literacy in Korean males and females. The current study provides insight about gender differences in health literacy that could inform gender-specific intervention strategies to improve health literacy, and thereby, health equity, for both genders in modern Korean society.

Methods

Research Design and Data Collection

This study employed a cross-sectional survey research design. A purposive and convenient sampling strategy was selected by using a nonprobability quota sampling strategy to ascertain proportional representativeness of the sample by gender and age categories (Neuman, 1994). To select the sample, this study chose two metropolitan cities—Seoul and Kwangju. In both cities, study participants were recruited through three university-affiliated outpatient clinics and five social service agencies and senior centers in 2009. In total, 605 Korean men and women aged 19 to 83 years agreed to participate in the study. Research participants were informed about the purpose of the study, eligibility criteria, confidentiality, and voluntary participation in the study. Participants age 19 to 59 years were required to complete a self-administered survey. All participants age 60 years and older were assisted by trained research staff to complete a survey to reduce respondents’ misunderstanding of terminology and the number of missing responses. For the analysis, only 585 participants were included due to skewed responses or responses out of potential response range. This study was approved by the University of Minnesota Institutional Review Board.

Measures

Dependent Variable

This study adopted Chew, Bradley, & Boyko’s (2004) 16-question self-reported health literacy measure, and the questions were translated into Korean, using the back translation method. We conducted factor analysis with 16-questions using principal axis factoring methods and deleted six items which were not associated with the rest of the items. Additionally, two more items were excluded because the Cronbach’s alpha coefficient score was increased after deleting them. As a result, this study used only the remaining eight items to measure health literacy (see the appendix for the results of factor analysis). The response format was a 5-point Likert-type scale from not at all (1), to to a great extent (5). The health literacy score was estimated by using item response theory (IRT; see details in Embretson & Reise, 2000; Thissen & Orlando, 2001) instead of computing arithmetic means or total scores based on classical test theory. Using IRT over classical test theory has a few advantages. First, this approach is beneficial in overcoming potentially unequal response intervals (i.e. difference between not at all to very little and very little to somewhat), and imputing proper values based on maximum likelihood approach for missing responses. Second, applications of IRT in health research measurement have recently increased considerably because of its utility in item and scale analysis, scale scoring, instrument linking, and adaptive testing. Lastly, it has been argued that state-of-the-art scale development should use IRT methods to determine the psychometric performance of scale items (Beevers, Strong, Meyer, Pilkonis, & Miller, 2007; Embretson & Riese, 2000).

The item parameters for the remaining eight items were estimated by using Winstep version 3.71 software (Linacre, 2011) based on the Rasch model (Rasch, 1960). Based on this item parameter for each item, a health literacy score for each person was estimated. The reliability score, Cronbach’s alpha coefficient, of health literacy was .86, which is the same as we identified among Korean American immigrants in New York City (α = .86; Lee, Choi, & Lee, 2014). Although the survey was administered in two different ways, the reliability scores were not greatly different (α = .84 for self-administered group and α = .86 for interview group).

Independent Variables

This study used three sets of independent variables informed by existing literature: Predisposing factors (age, gender, marital status, and use of Eastern medicine), Enabling factors (education, monthly income level, and consistent place to receive care), and Need factors (self-rated health status, mental health, and number of chronic disease). Among predisposing factors, age was coded as a continuous variable, but gender and marital status (married vs. others) were coded dichotomously. The use of Eastern medicine variable is a construct variable measured with two items (Tang, Solomon, & McCracken, 2000) and the score was estimated in the same way for health literacy by using the IRT model (α = .683). Among enabling factors, education was coded as no education = 1 through graduate school = 6, and monthly income level was measured by 12 categories with gradation by $500. The consistent place to receive care (having a primary hospital/clinic) was coded as yes = 1, and no = 0. Lastly, among need factors, health status was measured by a 5-point rating scale ranging from very poor = 1 through very good = 5, and depression was measured by the 10-item shortened CES-D (Center for Epidemiologic Studies–Depression scale; Andresen, Malmgren, Carter, & Patrick, 1994). The Cronbach’s alpha reliability score for the 10-item CES-D scale was .82 which is slightly lower than the 20-item original scale’s reliability, which was .85 in the general population and .90 in the medical patient population (Radloff, 1977). However, this can be attributed to a smaller number of items than the original scale. The number of diseases was measured by summing up the total frequency of 19 chronic disease items.

Data Analysis

Univariate and bivariate analysis were used to describe the sociodemographic characteristics of the sample by gender. First, the χ² analyses examined proportional differences of demographic variables and responses to health literacy items between genders. Second, in order to estimate the effects of the predictors on health literacy, ordinary least squares regression analysis was used. Based on Andersen’s theoretical framework, the regression model included predisposing, enabling, and need factors. Last, in order to compare effect size between genders, Cohen’s f²statistics, which can be obtained by dividing R² by (1 − R²) was used. For the statistical procedure, IBM SPSS 20.0 software package (IBM Corp., 2011) was used.

Findings

Table 1 presents sociodemographic characteristics of the sample by gender. The average age of the 585 participants was 48 years. Three hundred participants were females and 285 were males. About 70% (n = 399) were married and male respondents were more likely to be married, living with a domestic partner or cohabiting than female participants (χ² = 8.561, df = 1, p = .003). More than half of the sample (n = 297, 52.8%) achieved an education level of college or higher and the males were more likely to have obtained a higher level of education (χ² = 37.582, df = 2, p < .001). Approximately half of the respondents earned a monthly income of less than $2,000 and female respondents were more likely to have a lower income level (χ² = 19.494, df = 3, p < .001). About 73% (n = 426) of the sample was employed with males having a higher rate of employment (χ² = 38.457, df = 1, p < .001). More female participants than males (n = 159, 53.5% vs. n = 123, 43.3%) responded that they had a consistent place to receive care (χ² = 6.077, df = 1, p = .014). More than 80% (n = 499) of the sample rated their health status as being fair to very good and male respondents were more likely to rate their health status in positive way (χ² = 14.002, df = 4, p = .007). Females had significantly higher depression scores than males (t = 2.531, p = .012). As a group, the sample had an average of approximately two chronic diseases. Females had significantly more chronic diseases than males (t = 2.431, p = .015).

Table 1.

Sociodemographic Characteristics of the Sample by Gender.

Variable	Category	Females (N = 300)		Male (N = 285)		χ² by gender
Variable	Category	n	%	n	%	χ² by gender
Marital status	Married^a	187	0.39	212	74.65	8.561**
Marital status	Others^b	108	36.61	72	25.35
Education^c	Less than middle school	85	28.91	25	9.29	37.582**
	High school	81	27.55	75	27.88
	College education or higher	128	43.54	169	62.83
Income level^d	Less than $2,000	158	0.44	105	38.32	19.494**
	$2,000-$4,000	66	23.16	104	37.96
	$4,000-$7,000	49	17.19	55	20.07
	More than $7,000	12	4.21	10	3.65
Employment	Yes	185	62.08	241	84.86	38.457**
Employment	No	113	37.92	43	15.14
Consistent place to receive care	Yes	159	53.54	123	43.31	6.077**
Consistent place to receive care	No	138	46.46	161	56.69
Self-rated health status	Very poor	3	1.00	2	0.70	14.002**
	Poor	51	17.00	29	10.21
	Fair	184	61.33	168	59.15
	Good	55	18.33	63	22.18
	Very good	7	2.33	22	7.75
		M	SD	M	SD	t
Depression^e		9.90	4.83	8.93	4.42	2.531^**
Age		47.86	15.49	47.95	16.09	.070^**
Number of disease		1.90	1.81	1.54	1.82	2.431^**

“Married” included “domestic partnership” and “cohabiting”.

“Others” included “not married”, “separated”, “divorced”, and “widowed”.

Originally measured with 7 categories from 0 = no education to 6 = graduate school.

Collapsed 12 ordinal categories from 1 = under $500 to 12 = more than $7,000.

Depression questionnaire contained 10 items and scored from 0 = not at all to 3 = always. The higher total score means the higher depression.

p < .05, **p < .01.

Gender Differences in Health Literacy

Table 2 presents the frequency of the eight items in health literacy scale by gender. We created three levels of health literacy by combining five response items into three: (1) inadequate (to a great extent + usually), (2) marginal (somewhat), and (3) adequate (very little + not at all). Based on the χ²analyses, there were significant proportional differences in Korean men’s response toward three health literacy items compared to those of Korean women. First of all, Korean males were more likely to have an inadequate understanding of how to understand and fill out medical forms than Korean females (χ² = 6.594, df = 2, p = .037). Males also were significantly more likely to have difficulty understanding the directions on medication bottles than Korean females (χ² = 7.515, df = 2, p = .023). Lastly, more Korean females than males had an adequate understanding of written information from a health care provider, such as a physician, nurse, or nurse practitioner (χ² = 9.975, df = 2, p = .007).

Table 2.

Gender Differences in Health Literacy

Statement		χ²
1. How often are appointment slips difficult to understand?	AdequateMarginalInadequate	0.945df = 2N = 579
2. How often are medical forms difficult to understand and fill out?	AdequateMarginalInadequate	6.594* df = 2N = 570
3. How often are directions on medication bottles difficult to understand?	AdequateMarginalInadequate	7.515* df = 2N = 582
4. How often do you have difficulty understanding written information your health care provider (like doctor, nurse, nurse practitioner) gives you?	AdequateMarginalInadequate	9.975** df = 2N = 583
5. How often do you have problems getting to your clinic appointments at the right time because of difficulty understanding written instructions?	AdequateMarginalInadequate	3.434df = 2N = 583
6. How often do you have problems completing medical forms because of difficulty understanding the instructions?	AdequateMarginalInadequate	3.101df = 2N = 583
7. How often do you have problems learning about your medical condition because of difficulty understanding written information?	AdequateMarginalInadequate	2.243df =2N = 582
8. How often are you unsure about how to take your medication(s) correctly because of problems understanding written information on the bottle label?	AdequateMarginalInadequate	0.550df = 2N = 583

Note. Inadequate = to a great extent (1) + usually (2); Marginal = somewhat (3); Adequate = very little (4) + not at all (5).

p < .05, **p < .01.

Approximately half of the men and women were characterized at the adequate level for the following questions: (1) having problems getting to clinic appointments due to difficulty understanding written instructions (68.9% of females and 62.7% of males), (2) difficulty in taking medication(s) correctly because of problems understanding written information on the bottle label (56.7% of females and 56.1% of males), and (3) difficulty in understating appointment slips (52.6% of females and 49% of males). However, another half of the study participants experienced difficulty at inadequate and marginal levels in the following three items: (1) understanding and filling out medical forms (60.7% of females and 70% of males), (2) having difficulty understanding directions on medication bottles (52.6% of females and 58.9% of males), and (3) having difficulty understanding written information that health care providers provide (47.0% of females and 60.0% of males).

Factors Affecting Health Literacy by Gender

This study adopted Andersen’s behavior model to identify the major predictors of health literacy by gender. For the female group, all predictors in enabling factors had significant effects on health literacy (β_education = 0.270, p = .001; β_income = 0.140, p = .049; β_{primary hospital} = 0.194, p < .001) while none of Predisposing predictors did. Among need factors, only depression was significantly associated with health literacy (β = −0.183, p = .002; Table 3).

Table 3.

Multiple Regression Analysis on Health Literacy by Gender

Independent variables	Gender
Independent variables	Female, β	Male, β
Predisposing factors
Age^a	.037	.041
Marital status (Ref = Not married)	−.064	−.225**
Use of Eastern medicine^a	−.070	.036
Enabling factors
Education^b	.270 **	−.059
Monthly income^c	.140*	.299 **
Primary hospital/clinic (Ref = No)	.194 **	.036
Need factors
Self-rated health^a	.003	143 *
Depression^a	−.183**	−.178**
Number of chronic disease^a	−.116	.064
N	271	255
Constant	37.896 **	44.910 **
R ²	.269	.137
Effect size (Cohen’s f²)	.368	.159

Note. Dependent variable is health literacy (item response theory) scale score (M = 50, and SD = 15)

Included in the model as a continuous variable.

Ordinal variable with 7 categories (0 = no education to 6 = graduate school).

Ordinal variable with 12 categories (1 = under $500 to 12 = more than $7,000).

p < .05, **p < .01.

Significant predictors in model are bolded.

For the male group, one of the predisposing factors, marital status, was reported to have a significant association, (β = −0.225, p = .007). Only monthly income among enabling factors had significant associations with health literacy (β = −0.299, p < .001). Among need factors, self-rated health status had a significant positive association with health literacy (β = 0.143, p = .030), while it wasn’t significant in females. Depression also had a significant association with health literacy, but it was negative in direction (β = −0.178, p = .006). Monthly income and depression seemed to be general predictors of health literacy regardless of gender. On the other hand, education and primary hospital/clinic were more unique predictors for the female group, while marital status and health status were stronger predictors than others in the male group. From the R²value, the proportion of explained variance in health literacy for the female group was 0.269, and this is almost twice as large as that of the male group, which was 0.137.

Discussion

This study investigated gender differences in the levels of health literacy and relevant factors associated with health literacy using Andersen’s behavioral model. Interestingly, Korean women reported a significantly higher level of health literacy than men in three areas: (1) understanding and filling out medical forms (39.3% of females vs. 30% of males), (2) understanding directions on medication bottles (47.4% of females vs. 41.1% of males), and (3) understanding written information provided by health care professionals (53.0% of females vs. 40.0% of males).

The finding that Korean women have higher health literacy levels than Korean men adds important information to the growing understanding of the role of gender in health literacy. The same pattern has been revealed in British adults (von Wagner, Knight, Steptoe, & Wardle, 2007), the elderly in Korea (Park & June, 2011), and in the United States (Sudore et al., 2006). The gap between men and women in health literacy may be associated with women’s increased familarity in navigating the health care system from the process of dealing with health issues. Previous research supports that women tend to report more health issues, and have higher medical service utilization and charges than men (Anson, Paran, Neumann, & Chernichovsky, 1993; Bertakis, Azari, Helms, Callahan, & Robbins, 2000). In fact, women in the current study reported more depressive symptoms and chronic diseases than men. Another explanation may be relevant to women’s traditional role of caring for sick family members and children (Arber & Ginn, 1995; Stimpson, Jensen, & Neff, 1992; Won & Pascall, 2004). This traditional gender expectation may provide women with more interactions with the healthcare system, giving them more opportunities to build their knowledge base, and therefore resulting in higher health literacy levels than those of men.

The multivariate analysis revealed that different factors were associated with health literacy in both men and women. Of predisposing factors (age, marital status, and use of Eastern medicine), none of the included factors were closely associated with women’s health literacy, and marital status was the only significant factor associated with men’s health literacy. Specifically, married men were more likely to have lower health literacy levels than unmarried men. This supports the idea that having a spouse or partner may not necessarily increase men’s health literacy. Given Korean culture, married men may rely on their spouse or partner for their health issues. Men’s reliance on a spouse or partner is also prevalent in Latino men (Peak, Gast, & Ahlstrom, 2010). The reliance may decrease opportunities for men to navigate health care systems or health information. This may result in lower levels of married men’s health literacy. Interestingly, this finding is not consistent with previous studies. For example, Lee and Kang (2008) identified that marital status was an insignificant factor in health literacy levels in Korean elderly adults after controlling for other sociodemographic factors in their multivariate model. Based on their bivariate analysis, both Lee and Kang (2008) and Park and June (2011) reported that married people tend to have higher health literacy. The inconsistency between these findings and the current study may partly be attributed to the difference in study populations, as both Lee and Kang (2008) and Park and June (2011) included only Korean older adults.

All enabling factors (level of education, income, and having a consistent place to receive care) were associated with women’s health literacy, whereas monthly income was the only enabling factor significantly associated with men’s health literacy. Women who had a consistent place to receive care (primary hospital/clinic), who had a higher level of educational attainment, and higher monthly income were more likely to have higher levels of health literacy. This suggests that having access to education, a greater income, or health care system still significantly facilitates Korean women’s ability to adequately obtain and process health information and services.

Men with higher monthly income possessed higher health literacy. Interestingly, an association between education and health literacy was not found among Korean men in the current study. The finding is contradictory to a review study that reported the level of education is more consistently associated with health literacy than that of income (Paasche-Orlow et al., 2005). It is suspected that a significant association between income and health literacy was found in the current study because Korean men’s income rates vary more widely from individual to individual than does their educational status in the current study. In fact, the sample of Korean men in the current study had a little variability of education level. Only very few Korean men have less than a middle school education. Further study is needed to identify an influence of education and income on the level of health literacy.

Of need factors, depression was inversely associated with health literacy in both Korean men and women. This finding is in line with previous studies that reported a significant link between a lower level of health literacy and a higher level of depression. For instance, a lower health literacy level was significantly associated with more severe depression among participants with alcohol and drug dependence in the United States (Lincoln et al., 2006; Lincoln et al., 2008) and Latino American immigrants (Coffman & Norton 2010). For Korean elders, a lower level of health literacy was closely related to poorer physical and mental health (S. H. Kim & Yu, 2010). Although our finding supports an association between depression and health literacy, it is still unclear what serves as a cause. Given that people with depressive symptoms may be less likely to actively seek out helpful healthcare resources or services, and health literacy level is changeable over time (Berkman, Davis, & McCormack, 2010), further research should investigate if level of depression causally affects the level of health literacy.

To the best of our knowledge, this study is among the first to use Andersen’s behavioral model to identify predisposing, enabling, and need factors associated with health literacy in Korean men and women. Andersen’s behavioral model was useful in our study in that theoretical definitions of each factor guided selections of variables in regression analysis and provided a way to identify factors. Based on these, we could improve the health literacy through clinical intervention and health policy. According to this model, while the predisposing factors are not typically alterable, the enabling factors might provide some ways to improve health literacy. Our findings indicate that Korean women with a lower level of education and income and without having primary hospital, and Korean men with a lower level of income had a greater need for improvement in health literacy. Thus, for Korean females, intervention efforts should focus on providing more educational opportunities that are designed to improve health literacy and increase health accessibility where Korean women can be exposed to health information and the health care system. With regard to Korean males, health literacy intervention should targert those who have a lower level of income due to their high risk of having inadequate level of health literacy.

While this study provides useful information on gender differences in health literacy, the findings should be interpreted with caution because of several limitations. First, it is difficult to generalize the study results to all Korean adult populations because we used a nonprobability sampling method. Second, we urge cautious interpretation of the study’s findings due to the cross-sectional study design. Factors identified in this study cannot be considered as causes that increase or decrease the level of health literacy. These should be examined with a longitudinal study design that assures temporal aspects of causal relationships. Third, the current study used Andersen’s behavioral model of health care service utilization, but did not include an outcome measure of healthcare service utilization. Further study is needed to investigate if health litearcy mediates factors identified in the current study to health care utilization. Fourth, the health literacy measurement used in the study may not be culturally sensitive and may therefore limit its ability to measure Koreans’ health literacy levels. To address this cultural issue and increase validity of the measurement, the current study only included several sensitive items of all original measurement based on factor analysis. Further study is needed to apply culturally sensitive health literacy measurements that are specifically applicable to Koreans in order to confirm our findings. Finally, we used two different data collection methods (self-administered survey vs. individual interview). Although we used individual interviews for older adults group to capture accurate responses and reduce missing data, this might have generated bias in the results.

Findings from the current study suggest several implications for health care practice and policy. First, health care professionals need to be aware of gender differences in the level of health literacy among Korean adults. According to our study, Korean men are more likely to have difficulty understanding health information, such as medication directions or other written information, despite the fact that they are generally more highly educated than Korean women. Thus, health care professionals should not assume that their patient’s health literacy is based on the patient’s assessed education level, and should provide gender-specific and tailored verbal and nonverbal communication to each patient at his or her individual level of health literacy. Strategies such as the teach back technique can be used to ensure that both patients and health care providers communicate effectively (Baker, 2006).

Second, our findings sugget that both men and women with low incomes and who also have depressive symptoms would benefit from targeted health care services designed to increase health literacy levels. Currently, large Korean hospitals in metropolitan areas have hired nurses who explain health services in detail to patients and answer patient questions that may arise after a patient sees a physician. However, this service is provided based on patient request and is not offered as routine care. The findings of this study suggest that if hospitals and clinics were to expand this type of supportive service they would increase health literacy, especially for people with low incomes or depressive symptoms. Given that health literacy is associated with the use of health care services and health status, the effort to increase health literacy among these vulnerable populations would contribute to achieving health equity among Korean adults.

Footnotes

Appendix

Factor Analysis on 16-Item Health Literacy Scale

All 16-Item health literacy scale	Factors
All 16-Item health literacy scale	1	2	3
9. How often do you have difficulty understanding written information your health care provider (like doctor, nurse, nurse practitioner) gives you? (*)	.645	−.151	.255
11. How often do you have problems completing medical forms because of difficulty understanding the instructions? (*)	.640	−.136	.425
8. How often are directions on medication bottles difficult to understand? (*)	.635	−.169	.188
6. How often are appointment slips difficult to understand? (*)	.593	−.160	.044
12. How often do you have problems learning about your medical condition because of difficulty understanding written information? (*)	.558	−.079	.484
13. How often are you unsure about how to take your medication(s) correctly because of problems understanding written information on the bottle label? (*)	.540	−.037	.492
10. How often do you have problems getting to your clinic appointments at the right time because of difficulty understanding written instructions? (*)	.514	−.135	.426
7. How often are medical forms difficult to understand and fill out? (*)	.509	−.114	.155
5. How often are hospital or clinic signs difficult to understand?	.453	.001	−.101
16. How often do you have someone (like a family member, friend, hospital/clinic worker, or caregiver) help you read hospital materials?	.306	.013	.092
3. How often are medication labels written in a way that is easy to read and understand?	−.119	.738	−.206
2. How often are medical forms written in a way that is easy to read and understand?	−.058	.737	−.112
4. How often are patient educational materials written in a way that is easy to read and understand?	−.130	.717	−.140
1. How often are appointment slips written in a way that is easy to read and understand?	−.086	.664	−.059
15. How confident do you feel you are able to follow the instructions on the label of a medication bottle?	−.146	.280	−.562
14. How confident are you filling out medical forms by yourself?	−.074	.316	−.405
Eigenvalues	5.253	2.235	1.137
Percentage of total variance	32.832	13.967	7.109
Number of test measures	10	4	2

Note. Extraction method: principal axis factoring. Three factors were extracted. Rotation method: varimax with Kaiser normalization. Items marked with an asterisk (*) indicate items included in the analysis for this study.

Acknowledgements

The authors would like to extend their gratitude to the Korean adults who participated in this study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for this research was provided by a grant from the Minnesota Agricultural Experiment Station (MIN-55-01) to the first author.

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Gender Differences in Health Literacy Among Korean Adults

Abstract

Keywords

Introduction

Methods

Research Design and Data Collection

Measures

Dependent Variable

Independent Variables

Data Analysis

Findings

Gender Differences in Health Literacy

Factors Affecting Health Literacy by Gender

Discussion

Footnotes

Appendix

Acknowledgements

Declaration of Conflicting Interests

Funding

References