Factors Influencing Preventive Intention Behavior Towards COVID-19 in Indonesia
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Since early 2020, the COVID-19 outbreak and its spread across the globe have disrupted many sectors. In Indonesia the COVID-19 have caused a severe impact on the economic, social, and political. Various actions were considered as preventive measures to slow down the virus propagation. This study aimed to investigate the relationship between attitude, knowledge, risk perception, information exposure and preventive intention behavior toward COVID-19 in Indonesia. An empirical quantitative study was conducted using data collected in March and April 2020. The sample consisted of 214 respondents in Indonesia through online survey questionnaires based on convenience sampling methods. The regression analysis results showed that 42% of the variance in behavioral change on the infection was explained by the dependent variables. Attitude had a strong positive relationship with intention behavior with (β = .37, p = .000). This study found that intention behavior was elicited by attitude (β = .37, p = .000), information exposure (β = .10, p = .01), and risk perception (β=.29, p = .000). However, knowledge did not influence preventive intention behavior (β=.00, p = .94). These findings contribute towards preventive intention literature to support practitioners, public health authorities, health care policymakers, and the government to shape effective prevention communication.
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Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. (2001). Nature and operations of attitudes. Annual Review of Psychology, 52, 27–58. https://doi.org/10.1146/annurev.psych.52.1.27
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice Hall.
Alsubaie, S., Hani Temsah, M., Al-Eyadhy, A. A., Gossady, I., Hasan, G. M., Al-rabiaah, A., Jamal, A. A., Alhaboob, A. A., Alsohime, F., & Somily, A. M. (2019). Middle East Respiratory Syndrome Coronavirus epidemic impact on healthcare workers' risk perceptions, work, and personal lives. The Journal of Infection in Developing Countries, 13(10), 920–926. https://doi.org/10.3855/jidc.11753
Andarge, E., Fikadu, T., Temesgen, R., Shegaze, M., Feleke, T., Haile, F., Endashaw, G., Boti, N., Bekele, A., & Glagn, M. (2020). Intention and practice on personal preventive measures against the COVID-19 pandemic among adults with chronic conditions in southern Ethiopia: A survey using the theory of planned behavior. Journal of Multidisciplinary Healthcare, 13, 1863–1877. https://doi.org/10.2147/JMDH.S284707
American Library Association (2020). COVID-19 Corona Virus Pandemic. Worldometer. https://www.worldometers.info/coronavirus/?utmcampaign=homeAdvegas1?%22
Bashirian, S., Jenabi, E., Khazaei, S., Barati, M., Karimi-Shahanjarini, A., Zareian, S., Rezapur-Shahkolai, F., & Moeini, B. (2020). Factors associated with preventive behaviours of COVID-19 among hospital staff in Iran in 2020: An application of the Protection Motivation Theory. Journal of Hospital Infection, 105(3), 430–433. https://doi.org/10.1016/j.jhin.2020.04.035
Baudouin, S. B., Wongsawat, P., & Sudnongbua, S. (2020) Using the theory of planned behaviour to predict preventive intention on sexual behaviours among junior high school students in lower Northern region of Thailand. International Journal of Adolescence and Youth, 25(1), 364-372. https://doi.org/10.1080/02673843.2019.1657025
Bates, B. R., Villacís, A. G., Mendez-Trivino, A., Mendoza, L. E., & Grijalva, M. J. (2020). Determinants of intentions to prevent triatomine infestation based on the health belief model: An application in rural southern Ecuador. PLOS Neglected Tropical Diseases, 14(1), Article e0007987. https://doi.org/10.1371/journal.pntd.0007987
Chen, X., & Chen, H. (2020). Differences in preventive behaviors of COVID-19 between urban and rural residents: Lessons learned from a cross-sectional study in China. International Journal of Environmental Research and Public Health, 17(12), Article 4437. https://doi.org/10.3390/ijerph17124437
Choi, J. S., & Kim, J. S. (2016). Factors influencing preventive behavior against Middle East Respiratory Syndrome-Coronavirus among nursing students in South Korea. Nurse Education Today, 40, 168–172. https://doi.org/10.1016/j.nedt.2016.03.006
Dennis, M., Simic, N., Bigler, E. D., Abildskov, T., Agostino, A., Taylor, H. G., Rubin, K.; Vannatta, K, Gerhardt, C. A., Stancin, T., & Yeates, K. O. (2013). Cognitive, affective, and conative Theory of Mind (ToM) in children with traumatic brain injury. Developmental Cognitive Neuroscience, 5, 25–39. https://doi.org/10.1016/j.dcn.2012.11.006
Derwin, K. C., Chun-Qing, Z., & Karin, W. J. (2020). Why people failed to adhere to COVID-19 preventive behaviors? Perspectives from an integrated behavior change model. Infection Control & Hospital Epidemiology. https://doi.org/10.1017/ice.2020.245
Djalante, R., Lassa, J., Setiamarga, D., Sudjatma, A., Indrawan, M., Mahfud, C., Sinapoy, M. S., Djalante, S., Rafliana, I., Gunawan, L. A., Surtiari, G. A. K., & Warsilah, H. (2020). Review and analysis of current responses to COVID-19 in Indonesia: Period of January to March 2020. Progress in Disaster Science, 6. Article 100091. https://doi.org/10.1016/j.pdisas.2020.100091
Dryhurst, S., Schneider, C. R., Kerr, J., Freeman, A. L. J., Recchia, G., Van Der Bles, A. M., Spiegelhalter, D., & Van Der Linden, S. (2020). Risk perceptions of COVID-19 around the world. Journal of Risk Research, 23(7-8), 994-1006. https://doi.org/10.1080/13669877.2020.1758193
Engle, R. F. (2001). GARCH 101: The use of ARCH/GARCH models in applied econometrics. Journal of Economic Perspectives, 15(4), 157-168. https://doi.org/10.1257/jep.15.4.157
Errett, N. A., Sauer, L. M., & Rutkow, L. (2020). An integrative review of the limited evidence on international travel bans as an emerging infectious disease disaster control measure. Journal of Emergency Management (Weston, Mass.), 18(1), 7–14. https://doi.org/ 10.5055/jem.2020.0446
Farooq, A., Laato, S., & Najmul-Islam, A. K. M. (2020). Impact of online information on self-isolation intention during the COVID-19 Pandemic: Cross-sectional study. Journal of Medical Internet Research, 22(5), Article e19128. https://doi.org/10.2196/19128
Gajdács, M., Paulik, E., & Szabó, A. (2020). Knowledge, attitude and practice of community pharmacists regarding antibiotic use and infectious diseases: A cross-sectional survey in Hungary (KAPPhA-HU). Antibiotics, 9(2), Article 41. https://doi.org/10.3390/antibiotics9020041
Ghozali, I. (2018). Aplikasi Analisis Multivariate dengan Program IBM Spss 25 [Multivariate Analysis Application with IBM Spss 25 Program]. Badan Penerbit Universitas Diponerogo.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis. Pearson Education Limited.
Huang, F., Ding, H., Liu, Z., Wu, P., Zhu, M., Li, A., & Zhu, T. (2020). How fear and collectivism influence public’s preventive intention towards COVID-19 infection: A study based on big data from the social media. BMC Public Health, 20, Article 1707. https://doi.org/10.1186/s12889-020-09674-6
Hubner, A. Y., & Hovick, S. R. (2020). Understanding Risk Information Seeking and Processing during an Infectious Disease Outbreak: The Case of Zika Virus. Risk Analysis, 40(6), 1212-1225. https://doi.org/10.1111/risa.13456
Hui, D. S., I Azhar, E., Madani, T. A., Ntoumi, F., Kock, R., Dar, O., Zumla, A., & Petersen, E. (2020). The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health: The latest 2019 novel coronavirus outbreak in Wuhan, China. International Journal of Infectious Diseases, 91, 264–266. https://doi.org/10.1016/j.ijid.2020.01.009
Hutt, R. (2020). The economic effects of the COVID-19 coronavirus around the world. World Economic Forum. https://www.weforum.org/agenda/2020/02/coronavirus-economic-effects-global-economy-trade-travel/
Jang, K., & Park, N. (2018). The Effects of repetitive information communication through multiple channels on prevention behavior during the 2015 MERS Outbreak in South Korea. Journal of Health Communication, 23(7), 670–678. https://doi.org/10.1080/10810730.2018.1501440
Jang, W. M., Cho, S., Jang, D. H., Kim, U. N., Jung, H., Lee, J. Y., & Eun, S. J. (2019). Preventive behavioral responses to the 2015 Middle East Respiratory Syndrome Coronavirus Outbreak in Korea. International Journal of Environmental Research and Public Health, 16(12), Article 2161. https://doi.org/10.3390/ijerph16122161
Jang, W. M., Kim, U. N., Jang, D. H., Jung, H., Cho, S., Eun, S. J., & Lee, J. Y. (2020). Influence of trust on two different risk perceptions as an affective and cognitive dimension during Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Outbreak in South Korea: Serial cross-sectional surveys. BMJ Open, 10(3), Article e033026. https://doi.org/10.1136/bmjopen-2019-033026
Ju, Y., & You, M. (2020). The outrage effect of personal stake, dread, and, moral nature on fine dust risk perception moderated by media use. Health Communication. https://doi.org/10.1080/10410236.2020.1723046
Ko, N. Y., Lu, W. H., Chen, Y. L., Li, D. J., Chang, Y. P., Wang, P. W., & Yen, C. F. (2020). Cognitive, affective, and behavioral constructs of COVID-19 health beliefs: A comparison between sexual minority and heterosexual individuals in Taiwan. International Journal of Environmental Research and Public Health, 17(12), Article 4282. https://doi.org/10.3390/ijerph17124282
Kurniawan, I. (2021, January 11). Update Corona Indonesia hari ini Senin 11 Januari 2021: Jumlah kasus aktif tembus 123.636 pasien [Corona Indonesia update today Monday 11 January 2021: Number of active cases translucent 123,636 patients]. Prfmnews. https://prfmnews.pikiran-rakyat.com/nasional/pr-131255152/update-corona-indonesia-hari-ini-senin-11-januari-2021-jumlah-kasus-aktif-tembus-123636-pasien
Lee, M., & You, M. (2020). Psychological and behavioral responses in South Korea during the early stages of Coronavirus Disease 2019 (COVID-19). International Journal of environmental Research and Public Health, 17(9), Article 2977. http://doi.org/10.3390/ijerph17092977
Lennon, R. P., Sakya, S. M., Miller, E. L., Snyder, B., Yaman, T., Zgierska, A. E., Ruffin, M. T., & Van Scoy, L. J. (2020). Public intent to comply with COVID-19 public health recommendations. Health Literacy Research and Practice, 4(3), e161–e165. https://doi.org/10.3928/24748307-20200708-01
Liu, L., Xie, J., Li, K., & Ji, S. (2020). Exploring how media influence preventive behavior and excessive preventive intention during the COVID-19 pandemic in China. International Journal of Environmental Research and Public Health, 17(21), Article 7990. https://doi.org/10.3390/ijerph17217990
Memish, Z. A., Steffen, R., White, P., Dar, O., Azhar, E. I., Sharma, A., & Zumla, A. (2019). Mass gatherings medicine: Public health issues arising from mass gathering religious and sporting Events. The Lancet, 393(10185), 2073–2084. https://doi.org/10.1016/S0140-6736(19)30501-X
Mitchell, K. C., Ryan, P., Howard, D. E., & Feldman, K. A. (2018). Understanding knowledge, attitudes, and behaviors toward West Nile virus prevention: A survey of high-risk adults in Maryland. Vector-Borne and Zoonotic Diseases, 18(3), 173–180. https://doi.org/10.1089/vbz.2017.2188
Oh, S. H., Lee, S. Y., & Han, C. (2020). The effects of social media use on preventive behaviors during Infectious disease outbreaks: The mediating role of self-relevant emotions and public risk perception. Health Communication. https://doi.org/10.1080/10410236.2020.1724639
Orset, C. (2018). People’s perception and cost-effectiveness of home confinement during an influenza pandemic: Evidence from the French case. European Journal of Health Economics, 19(9), 1335–1350. https://doi.org/10.1007/s10198-018-0978-y
Park, T., Ju, I., Ohs, J. E., & Hinsley, A. (2020). Optimistic bias and preventive behavioral engagement in the context of COVID-19. Research in Social and Administrative Pharmacy, 17(1), 1859-1866. https://doi.org/10.1016/j.sapharm.2020.06.004
Prasetyo, Y. T., Castillo, A. M., Salonga, L. J., Sia, J. A., & Seneta, J. A. (2020). Factors affecting perceived effectiveness of COVID-19 prevention measures among Filipinos during Enhanced Community Quarantine in Luzon, Philippines: Integrating Protection Motivation Theory and extended Theory of Planned Behavior. International Journal of Infectious Diseases, 99, 312–323. https://doi.org/10.1016/j.ijid.2020.07.074
Raza, A., Ali, Q., & Hussain, T. (2020). Role of knowledge, behavior, norms, and e-guidelines in controlling the spread of COVID-19: Evidence from Pakistan. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-020-10931-9
Saifulloh, M. (2020). Nafsu Mudik Dini ditengah Pandemic Corona [Early homecoming desire in the Middle of the Corona Pandemic]. Okezone. https://www.okezone.com/tren/ read/2020/03/27/620/2190127/nafsu-mudik-dini-di-tengah-pandemi-virus-corona
Shahin, M. A. H., & Hussien, R. M. (2020). Risk perception regarding the COVID-19 outbreak among the general population: a comparative Middle East survey. Middle East Current Psychiatry, 27, Article 71. https://doi.org/10.1186/s43045-020-00080-7
Sobkow, A., Zaleskiewicz, T., Petrova, D., Garcia-Retamero, R., & Traczyk, J. (2020). Worry, risk perception, and controllability predict intentions toward COVID-19 preventive behaviors. Frontiers in Psychology, 11, Article 582720. https://doi.org/10.3389/fpsyg.2020.582720
Sekaran, U., & Bougie, R. (2016). Research Methods for Business: A Skill Building Approach (7th ed.). Wiley.
Seo, M. (2019). Amplifying panic and facilitating prevention: Multifaceted effects of traditional and Social Media use during the 2015 MERS Crisis in South Korea. Journalism and Mass Communication Quarterly, 98(1), 221-240. https://doi.org/10.1177/1077699019857693
Song, S., Yao, X., & Wen, N. (2021). What motivates Chinese consumers to avoid information about the COVID-19 pandemic? The perspective of the stimulus-organism-response model. Information Processing and Management, 58(1), Article 102407. https://doi.org/10.1016/j.ipm.2020.102407
Tomczyk, S., Rahn, M., & Schmidt, S. (2020). Social distancing and stigma: Association between compliance with behavioral recommendations, risk perception, and stigmatizing attitudes during the COVID-19 Outbreak. Frontiers in Psychology, 11, Article 1821. https://doi.org/10.3389/fpsyg.2020.01821
Usuwa, I. S., Akpa, C. O., Umeokonkwo, C. D., Umoke, M., Oguanuo, C. S., Olorukooba, A. A., Bamgboye, E., & Balogun, M. S. (2020). Knowledge and risk perception towards Lassa fever infection among residents of affected communities in Ebonyi State, Nigeria: Implications for risk communication. BMC Public Health, 20, Article 217. https://doi.org/10.1186/s12889-020-8299-3
Van Bavel, J. J., Katherine, B., Paulo S. B., Valerio, C., Aleksandra, C., Mina, C., Molly J. C., Alia, J. C., Karen, M. D., James, N. D., John, D., Oeindrila, D., Naomi, E., Eli,J. F., James, H. F., Michele, G, Shihui, H. S., Alexander, H., Jetten, J., … Robb, W. (2020). Using social and behavioural science to support COVID-19 pandemic response. Nature Human Behavior, 4(5), 460-471. http://dx.doi.org/10.1038/s41562-020-0884-z
Vargas, G., Medeiros Geraldo, L. H., Gedeão Salomão, N., Viana Paes, M., Regina Souza Lima, F., & Carvalho Alcantara Gomes, F. (2020). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and glial cells: Insights and perspectives. Brain, Behavior, & Immunity - Health, 7, Article 100127. https://doi.org/10.1016/j.bbih.2020.100127
Volterrani, A. (2017). From perception to change. A Model for prevention communication. Proceedings of the 3rd World Conference on Media and Mass Communication, 2(1), 82-90. https://doi.org/10.17501/medcom.2017.2110
Wen, J., Aston, J., Liu, X., & Ying, T. (2020). Effects of misleading media coverage on public health crisis: a case of the 2019 novel coronavirus outbreak in China. Anatolia, 31(2), 331–336. https://doi.org/10.1080/13032917.2020.1730621
Weston, D., Hauck, K., & Amlôt, R. (2018). Infection prevention behaviour and infectious disease modelling: A review of the literature and recommendations for the future. BMC Public Health, 18(1), 1-16. https://doi.org/10.1186/s12889-018-5223-1
World Health Organization. (2021). Weekly operational update on COVID-19 - 11 January 2021. World Health Organization (January). https://www.who.int/publications/m/item/weekly-operational-update-on-covid-19---11-january-2021
Witzling, L., Shaw, B., & Amato, M. S. (2015). Incorporating information exposure into a Theory of Planned Behavior model to enrich understanding of proenvironmental behavior. Science Communication, 37(5), 551–574. https://doi.org/10.1177/1075547015593085
Xu, Y. (2020). Unveiling the origin and transmission of 2019-nCoV. Trends in Microbiology, 28(4), 239–240. https://doi.org/10.1016/j.tim.2020.02.001
Yanti, B., Mulyadi, E., Wahiduddin, W., Novika, R. G. H., Arina, Y. M. D., Martani, N. S., & Nawan, N. (2020). Community knowledge, attitudes, and behavior towards social distancing policy as prevention transmission of Covid-19 in Indonesia. Jurnal Administrasi Kesehatan Indonesia, 8, 4-14. https://doi.org/10.20473/jaki.v8i2.2020.4-14
Yazdanpanah, M., Abadi, B., Komendantova, N., Zobeidi, T., & Sieber, S. (2020). Some at risk for COVID-19 are reluctant to take precautions, but others are not: A case from rural in Southern Iran. Frontiers in Public Health, 8, Article 562300. https://doi.org/10.3389/fpubh.2020.562300