Analysis of Disease Prevention Behavior Based on Health Belief Model (HBM)
DOI:
https://doi.org/10.55642/phasij.v6i01.1265Keywords:
Health Belief Model; Disease Prevention Behavior; Self-Efficacy; SEM-PLS; Malaysian Urban CommunityAbstract
Disease prevention behavior is an essential component of public health promotion, yet its psychological determinants require further exploration in the post-COVID-19 Malaysian context. This study analyzes factors influencing disease prevention behavior using the Health Belief Model (HBM) framework. A quantitative cross-sectional approach was applied to 320 respondents from Malaysian urban communities through purposive sampling. Analysis was conducted using SEM-PLS (SmartPLS 4.0) with 5,000 bootstrapping subsamples. Results demonstrate that self-efficacy (β=0.358, p<0.001), perceived benefits (β=0.319, p<0.001), perceived susceptibility (β=0.287, p<0.01), perceived severity (β=0.241, p<0.01), and perceived barriers (β=-0.196, p<0.05) significantly influence disease prevention behavior. Cues to action moderated the perceived susceptibility–prevention behavior relationship (β=0.143, p<0.05). The model explained 61.7% of variance (R²=0.617, Q²=0.389). Findings support individually-tailored health promotion interventions and community self-efficacy strengthening.
References
Ahmad, N., Ismail, R., & Zulkifli, A. (2023). Determinants of preventive health behaviors among Malaysian adults: A cross-sectional study using the Health Belief Model. Malaysian Journal of Public Health Medicine, 23(2), 112–124. https://doi.org/10.37268/mjphm/vol.23/no.2/art.1876
Al-Mohaithef, M., & Padhi, B. K. (2020). Determinants of COVID-19 vaccine acceptance in Saudi Arabia: A web-based national survey. Journal of Multidisciplinary Healthcare, 13, 1657–1663. https://doi.org/10.2147/JMDH.S276771
Chew, C. C., Lim, X. J., & Chang, C. T. (2021). COVID-19 preventive behaviors and associated factors among Malaysian adults: A cross-sectional study. BMC Public Health, 21, 2005. https://doi.org/10.1186/s12889-021-12036-5
Fadhilah, S. N., Hassan, M. R., & Ismail, S. (2023). Applying the Health Belief Model to dengue prevention behavior in urban Malaysia: A structural equation modeling approach. Tropical Biomedicine, 40(1), 67–79. https://doi.org/10.47665/tb.40.1.008
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(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2022). When to use and how to report the results of PLS-SEM (2nd ed.). European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Henseler, J., Ringle, C. M., & Sarstedt, M. (2020). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Ismail, A., Hamid, S. A., & Noor, N. M. (2022). Perceived barriers and facilitators of non-communicable disease prevention in rural Malaysian communities. International Journal of Environmental Research and Public Health, 19(4), 2318. https://doi.org/10.3390/ijerph19042318
Department of Statistics Malaysia. (2023). Urban community survey report Malaysia 2022/2023. Department of Statistics Malaysia.
Jones, C. L., Jensen, J. D., Scherr, C. L., Brown, N. R., Christy, K., & Weaver, J. (2023). The Health Belief Model as an explanatory framework in communication research: Exploring parallel, serial, and moderated mediation. Health Communication, 38(9), 1143–1156. https://doi.org/10.1080/10410236.2021.2007145
