The Interplay of e-Health Literacy, Health Literacy, and Self-Care among Hypertension and Diabetes Risk Groups: A Community-Based Investigation in Southern Thailand
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1
Sirindhorn College of Public Health, Trang, Faculty of Public Health and Allied Health Sciences, Praboromarajchanok Institute, Trang, Thailand
2
Chang Klang District Public Health Office, Nakhon Si Thammarat, Thailand
3
Excellent Center for Public Health Research, School of Public Health, Walailak University, Nakhon Si Thammarat, Thailand
4
Strategy and Planning Division, Ministry of Public Health, Nonthaburi, Thailand
Popul. Med. 2026;8(Supplement Supplement 1):
ABSTRACT
BACKGROUND-AIM:
Electronic health literacy (e-HL), health literacy (HL), and self-care behaviors are critical determinants of health outcomes among populations at risk for diabetes and hypertension. However, empirical evidence on these factors in the Chang Klang community remains limited. This study aimed to: (1) assess levels of electronic health literacy, health literacy, and self-care behaviors; (2) examine relationships among these variables; and (3) identify predictors of self-care behaviors among individuals at risk for diabetes and hypertension in Chang Klang community, Southern Thailand.
METHODS:
A community-based cross-sectional survey was conducted in December 2024. A total of 371 participants from risk groups were recruited using proportionate stratified sampling. Data were analyzed using descriptive statistics, Pearson’s product-moment correlation, and multiple regression analysis.
RESULTS:
Mean scores for electronic health literacy, self-care behavior, participation in health education activities, and learning from health role models were at moderate levels (3.48 ± 0.88, 3.58 ± 0.65, 3.50 ± 0.71, and 3.51 ± 0.71, respectively). Overall health literacy was at a high level (3.78 ± 0.68), with the highest score in accessing health information and services (3.90 ± 0.77) and the lowest in understanding self-care information (3.69 ± 0.76). Significant positive correlations were found between electronic health literacy, health literacy, participation in learning activities, learning from health role models, and self-care behavior (p < 0.001). These variables jointly explained 42.5% of the variance in self-care behavior (R² = 0.425).
CONCLUSIONS:
Although individuals in risk groups can access health information, difficulties remain in understanding and applying it to self-care practices. Strengthening health role models, increasing participation in health activities, and promoting digital health resources may enhance electronic health literacy and improve self-care behaviors among at-risk populations.