What Influences Thai Community-Dwelling Older Adults to Undertake Health Protective Behaviors in the Time of COVID-19 Pandemic? A Structural Equation Modeling Analysis
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Abstract
The changes and issues associated with aging in addition to the government’s response to the Covid-19 crisis pose a significant challenge for older people’s compliance with and adherence to the recommended preventive measures. This study examines a proposed extended Theory of Planned Behavior (TPB) model with factors affecting community-dwelling Thai older adults’ intent to undertake health protective behaviors. Ajzen’s (1985) Theory of Planned Behavior (TPB) was applied and extended to account for government trust, as a proposed additional factor. Using a structural equation modeling analysis, the research data were collected from a sample of 360 Thai older adults aged 60 years old and over living in the community in Thailand. Partial Least Square (SmartPLS) software was used to analyze Structural Equation Model (SEM). The results of this study indicate that subjective norms was the highest influencing factors (TE=0.263), followed by attitude (TE=0.257) and perceived behavioral control (TE=0.239), towards the intention that led to the health protective behaviors of the Thai older adults living in the community amid the outbreak of COVID-19. However, contrary to expectation, the government trust (TE=0.060) was not significantly related to intention to perform health protective behaviors. The findings from this study provide timely evidence needed for policy makers, healthcare professionals, and community to develop preventive measures and strategies to better target complex interventions that are responsive to the needs of local circumstances amid and beyond the crisis. This may include community-based programs or interventions that target both family members and older adults, ensuring equal opportunities and respecting older people’s rights.
Keywords: Community, Covid-19 pandemic, health protective behaviors, health promoting behaviors, older adults, theory of planned behavior
References
Applegate, W. B., & Ouslander, J. G. (2020). COVID-19 presents high risk to older persons. Journal of the American Geriatrics Society, 68(4), 681. https://doi.org/10.1111/jgs.16426
Brewster, A. L., Wilson, T. L., Kunkel, S. R., Markwood, S., & Shah, T. B. (2020). To support older adults amidst the COVID-19 pandemic, look to area agencies on aging. Retrieved from https://www.
healthaffairs.org/do/10.1377/hblog20200408.928642/full/
Cawthon, P., Orwoll, E., Ensrud, K., Cauley, J. A., Kritchevsky, S. B., Cummings, S. R., & Newman, A. (2020). Assessing the impact of the covid-19 pandemic and accompanying mitigation efforts on older adults. Journals of Gerontology - Series A Biological Sciences and Medical Sciences, 75(9), e123–e125. https://doi.org/10.1093/gerona/glaa099
Centers for Disease Control and Prevention. (2020). Severe outcomes among patients with coronavirus disease 2019 (covid-19) – United States. Retrieved from https://www.cdc.gov/mmwr/volumes/69/wr
/mm6912e2.htm
Chen, T., Dai, Z., Mo, P., Li, X., Ma, Z., Song, S., … Xiong, Y. (2020). Clinical characteristics and outcomes of older patients with coronavirus disease 2019 (covid-19) in wuhan, china: A single-centered, retrospective study. Journals of Gerontology Series A: Biological Sciences & Medical Sciences, 75(9), 1788–1795. https://doi.org/10.1093/gerona/glaa089
Chinese Center for Disease Control and Prevention. (2020). The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. Retrieved from http://weekly.chinacdc.
cn/en/article/id/e53946e2c6c4-41e9-9a9b-fea8db1a8f51
Davis, J. W., Chung, R., & Juarez, D. T. (2011). Prevalence of comorbid conditions with aging among patients with diabetes and cardiovascular disease. Hawaii Medical Journal, 70(10), 209–213.
Department of Disease Control. (2020). The coronavirus disease 2019 situation.Retrieved from https://ddc.
moph.go.th/viralpneumonia/eng/file/situation/situation-no357-311263.pdf
Gretebeck, K. A., Black, D. R., Blue, C. L., Glickman, L. T., Hutson, S. A., & Gretebeck, R. J. (2007). Physical activity and function in older adults: Theory of planned behavior. American Journal of Health Behavior, 31(2), 203–214. https://doi.org/10.5993/ajhb.31.2.9
Hair, J. F. (2006). Multivariate Data Analysis (6th ed.). Upper Saddle River, NJ: Prentice-Hall.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277-319.
Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model Fit. The Electronic Journal of Business Research Methods, 6, 53-60.
Karlamangla, A., Tinetti, M., Guralnik, J., Studenski, S., Wetle, T., & Reuben, D. (2007). Comorbidity in older adults: Nosology of impairment, diseases, and conditions. Journals of Gerontology Series A: Biological Sciences & Medical Sciences, 62(3), 296–300. https://doi.org/10.1093/gerona/62.
3.296
Lee, K. M., & Jung, K. (2019). Factors influencing the response to infectious diseases: focusing on the case of SARS and MERS in South Korea. International Journal of Environmental Research and Public Health, 16(8), 1432. https://doi.org/10.3390/ijerph16081432
Michels, T. C., & Kugler, J. P. (1998). Predicting exercise in older Americans: Using the theory of planned behavior. Military Medicine, 163(8), 524–529.
National Statistics Office. (2019). The 2019 health and welfare survey. Bangkok: National Statistics Office.
Panyaarvudh, J. (2020). Prayut's commanding style does not work in a crisis. Retrieved from https://www.
thaipbsworld.com/prayuts-commanding-style-does-not-work-in-a-crisis/
Parekh, A. K., & Barton, M. B. (2010). The challenge of multiple comorbidity for the US health care system. JAMA: The Journal of the American Medical Association, 303(13), 1303–1304.
Quinn, S. C., Parmer, J., Freimuth, V. S., Hilyard, K. M., Musa, D., & Kim, K. H. (2013). Exploring communication, trust in government, and vaccination intention later in the 2009 H1N1 pandemic: Results of a national survey. Biosecurity and bioterrorism: biodefense strategy, practice, and science, 11(2), 96–106. https://doi.org/10.1089/bsp.2012.0048
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