Examining Functional, Interactive, and Critical Health Literacy and eHealth Literacy Among Chinese Women with Young Children (P04-099-19)

Abstract

Abstract Objectives To assess functional, interactive, and critical health literacy and eHealth literacy among Chinese women with young children; to examine the relationships between personal characteristics and different categories of health literacy. Methods We used a cross-sectional online survey to reach a sample of Chinese women with children under three years old. The All Aspect Health Literacy Scale was used to assess functional, interactive, and critical health literacy. The eHealth Literacy Scale was used to assess functional, interactive, and critical eHealth literacy. Student's t-test, one-way ANOVA, Pearson's and Spearman's correlations were used to examine relationships between personal factors and health literacy levels. Results Mean age of the women (N = 382) was 30.3 ± 3.9 years; 73.8% completed college or higher education. Mean functional, interactive, and critical health literacy scores were 2.22 ± .48, 2.79 ± .33, and 2.53 ± .38, respectively (1 - 3, higher score indicates higher literacy). Mean functional, interactive, and critical eHealth literacy scores were 2.92 ± .92, 3.64 ± .65, and 3.95 ± .61, respectively (1 - 5, higher score indicates higher literacy). Education level was associated with higher critical health literacy (rs = .19, P < .001) and functional eHealth literacy (rs = .19, P < .001). Household income level was positively correlated with functional (rs = .11, P < .001), interactive (rs = .14, P < .05), and critical health literacy (rs = .11, P < .001), and functional (rs = .17, P < .001) and critical eHealth literacy (rs = .16, P < .001). Women who engaged in health-related jobs had higher functional literacy (2.58 ± .47 vs. 2.14 ± .44, P < .001) and functional eHealth literacy (3.76 ± .78 vs. 2.75 ± .85, P < .001) compared to those who were unemployed or had other jobs. Conclusions There is room for improvement in all three categories of health literacy and eHealth literacy in this highly educated population. Education, occupation, and household income appear to positively impact some, but not all types of health literacy and eHealth literacy. Funding Sources This research was funded by the University of Massachusetts Amherst School of Public Health and Health Sciences.