Factors Influencing Stroke Prevention in Patients with High Blood Pressure in Sakaeo Province
Main Article Content
Abstract
Introduction: This cross-sectional study aimed to examine predisposing, enabling, and reinforcing factors, as well as stroke prevention behaviors, and to analyze factors associated with stroke prevention behaviors among patients with hypertension in Sa Kaeo Province. Materials and Method: The sample consisted of 239 participants selected through multistage sampling. Data were collected using a structured questionnaire. Statistical analyses included descriptive statistics, Pearson’s correlation coefficient, and stepwise multiple regression analysis. Results: The results showed that social support and access to health information were significantly associated with stroke prevention behaviors (p < 0.05), whereas perceived barriers showed an inverse relationship with these behaviors. Stepwise multiple regression analysis revealed that sex (β = 0.491, p < 0.001), access to health information (β = -0.147, p = 0.008), social support (β = 0.122, p = 0.026), and perceived barriers (β = 0.116, p = 0.036) were significantly associated with stroke prevention behaviors. These variables jointly explained 30.80% of the variance in stroke prevention behaviors (R² = 0.308, Adjusted R² = 0.296). Conclusion: In conclusion, social support, particularly guidance from health professionals, was associated with stroke prevention behaviors among patients with hypertension. Access to health information and perceived barriers were also important factors to consider in promoting health behaviors. However, due to the cross-sectional design, causal relationships cannot be established, and the use of selfreported data may be subject to response bias.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles in this journal are copyrighted by the Royal Thai Army Medical Department and published under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.
may be read and used for academic purposes, such as teaching, research, or citation, with proper credit given to the author and the journal.
Use or modification of the articles is prohibited without permission.
Statements expressed in the articles are solely the opinions of the authors.
Authors are fully responsible for the content and accuracy of their articles.
Any other republication of the articles requires permission from the journal.
References
Green LW, Kreuter M. Health program planning: an educational and ecological approach. NewYork: McGraw-Hill; 2005.
Sa Kaeo Provincial Public Health Office. Annual report. Sa Kaeo: Sa Kaeo Provincial Public Health Office; 2024.
Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale (NJ): Lawrence Erlbaum Associates; 1988.
Ruangchaithavisuk K. Predictors of stroke prevention behavior in stroke-risk patients. J Nurs (Thail). 2021;14(1):213-25.
Green SB. How many subjects does it take to do a regression analysis? Multivariate Behav Res. 1991;26(3):499-510. doi:10.1207/s15327906mbr2603_7
Sombattheera K. Questionnaire response rate and related factors in mail surveys in nursing and public health research. KKU Res J (GS). 2015;15(1):105-13. Thai
National Statistical Office. Report on the 2021 physical activity survey. Bangkok: National Statistical Office; 2021. p.35-40. Thai
Ruangchaithavisuk K, Wongpiriyayotha A, Wongphanarak N. Predictors of stroke prevention behavior in at-risk patients. J Nurs. 2021;70(3):25-34. Thai
Tipayanet N, Chanabut W. Risk factors associated with stroke in hypertensive patients. Burapha Univ Public Health J. 2016;11(2):45-56. Thai
Bloom BS. Taxonomy of educational objectives: the classification of educational goals. NewYork: McKay; 1975.
Becker MH. The health belief model and personal health behavior. Health Educ Monogr. 1974;2:324-73. doi:10.1177/109019817400200407
Rosenstock IM. Historical origins of the health belief model. Health Educ Monogr. 1974;2:328-35. doi:10.1177/109019817400200403
Nutbeam D. Health literacy as a public health goal: a challenge for health education and communication strategies. Health Promot Int. 2000;15(3):259-67. doi:10.1093/heapro/15.3.259
Ngaruiya C, Bernstein R, Leff R, Wallace L, Agrawal P, Selvam A, et al. Systematic review on chronic non-communicable disease in disaster settings. BMC Public Health. 2022;22(1):1234. doi:10.1186/s12889-022-13399-z
Lawes CM, Bennett DA, Feigin VL, Rodgers A. Blood pressure and stroke: an overview of published reviews. Stroke. 2004;35(4):1024-33. doi:10.1161/01.STR.0000126208.14181.DD
Pérez-de-Heredia-Torres M, Huertas-Hoyas E, Trugeda-Pedrajo N, Serrada-Tejeda S, Gómez-GilDíaz-Río A, Martínez-Castrillo JC. Personality profile in focal hand dystonia. Int J Environ Res Public Health. 2021;18(15):7863. doi:10.3390/ijerph18157863
Chirathananuwat A. Factors affecting access to health services for the elderly in urban areas. J Health Sci. 2022;31(2):45-58. Thai
Theptha S. Factors affecting the use of services at community health centers. J Community Public Health. 2018;14(3):112-23. Thai
Srithanyarat W. Factors related to health care behavior of chronic disease patients in the community. J Community Public Health. 2018;14(3):95-108. Thai
House JS. Work stress and social support. Reading (MA): Addison-Wesley; 1981.
National Statistical Office. Report on the 2021 population employment survey. Bangkok: National Statistical Office; 2021. Thai