The Relationship between Health Information Scanning through Social Media and Health Behavior with Moderating Effects of Perceived Susceptibility towards Cardiovascular Disease
Keywords:
Cardiovascular Disease, Health Information Scanning, Social Media, Health Behavior, Perceived SusceptibilityAbstract
Cardiovascular disease is one of the most urgent health concerns in Indonesia. Since this disease is heavily influenced by a person’s lifestyle, it is of the utmost importance to promote health behavior in those who are at risk. One area of interest in health promotion is the usage of social media to disseminate health information and increase health behavior. The purpose of this research is to study the relationship between health information scanning through social media and health behavior, as well as the moderation effects of perceived susceptibility towards cardiovascular disease. This research is aimed towards students enrolled in a university in Depok who are in the emerging adulthood phase (18-25 years old) and have a family history of cardiovascular disease. This study utilizes three instruments which measure health behavior, perceived susceptibility towards cardiovascular disease, and health information scanning through social media respectively. The total number of participants for this study was 205 university students who met the required criteria. All of the data in this study were collected online. The results of this study indicate that health information scanning has a positive and insignificant impact on healthy behavior (r = 0.082, p> 0.05). Aside from that, this study also found that the moderating effect of perceived susceptibility towards cardiovascular disease on the relationship between health information scanning through social media and healthy behavior was positive and not significant (b = 0.1003, t = 1.0927, p> 0.05). Even so, these findings imply that social media has the potential to become a powerful tool to disseminate health information. The way in which this information needs to be conveyed in order to produce significant outcomes requires further research.
References
Annur, C. M. (2020, May 18). Pengguna Tiktok Naik 20% Selama Pandemi, Terbanyak Konten Edukasi. Retrieved from https://katadata.co.id/ekarina/digital/5ec2245aa8bc7/pengguna-tiktok-naik-20-selama-pandemi-terbanyak-konten-edukasi Arnett, J. J. (2015). Emerging Adulthood: The Winding Road from the Late Teens through the Twenties. New York: Oxford University Press. Arnett, J. J. (2015). College students as emerging adults: The developmental implications of the college context. Emerging Adulthood, 4(3), 219-222. Arnett, J. J. (2020). Emerging adulthood. In R. Biswas-Diener & E. Diener (Eds), Noba textbook series: Psychology. Champaign, IL: DEF publishers. Retrieved from http://noba.to/3vtfyajs Bloom, D. E., Chen, S., McGovern, M., Prettner, K., Candelas, V., Bernaert, A., & Cristin, S. (2015). Economics of Non-Communicable Diseases in Indonesia. Retrieved from http://www3.weforum.org/docs/WEF_The_Economics_of_non_Disease_Indonesia_2015.pdf
Cardiovascular Disease. (2018). Retrieved from https://www.nhs.uk/conditions/cardiovascular-disease/ Cardiovascular diseases (CVDs). (2017, May 17). Retrieved from https://www.who.int/en/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds) Cohen, J. (1992). A power primer. Psychological bulletin, 112(1), 155. Currey, H., Nazir, M., & Abukhadra, S. (2020, April 23). Digital around the world in April 2020. Retrieved from https://wearesocial.com/blog/2020/04/digital-around-the-world-in-april-2020 Dan, S., Pant, M., & Upadhyay, S. K. (2020). The Case Fatality Rate in COVID-19 Patients With Cardiovascular Disease: Global Health Challenge and Paradigm in the Current Pandemic. Current Pharmacology Reports, 1-10. Daw, J., Margolis, R., & Wright, L. (2017). Emerging Adulthood, Emergent Health Lifestyles: Sociodemographic Determinants of Trajectories of Smoking, Binge Drinking, Obesity, and Sedentary Behavior. Journal of Health and Social Behavior, 58(2), 181–197. https://doi.org/10.1177/0022146517702421 Fatimah. (2016). Hubungan Persepsi Kerentanan Dan Self-Efficacy Dalam Perilaku Sehat Dengan Perilaku Sehat Mahasiswa Universitas Indonesia Yang Memiliki Keluarga Dengan Penyakit Tidak Menular. Family Health History of Heart Disease. (2020, February 25). Retrieved from https://www.cdc.gov/genomics/disease/fh/history_heart_disease.htm Gallagher, K. M., Updegraff, J. A., Rothman, A. J., & Sims, L. (2011). Perceived Susceptibility to Breast Cancer Moderates the Effect of Gain- and Loss-Framed Messages on Use of Screening Mammography. Health Psychology, 30(2), 145–152. https://doi.org/10.1037/a0022264 Ghasemi, A., & Zahediasl, S. (2012). Normality tests for statistical analysis: a guide for non-statisticians. International journal of endocrinology and metabolism, 10(2), 486. Gochman, D. S. (1982). Labels, systems and motives: some perspectives for future research and programs. Health education quarterly, 9(2-3), 167-174. Hornik, R., Parvanta, S., Mello, S., Freres, D., Kelly, B., & Schwartz, J. S. (2013). Effects of scanning (routine health information exposure) on cancer screening and prevention behaviors in the general population. Journal of health communication, 18(12), 1422-1435. How Smoking and Nicotine Damage Your Body. (2015). Retrieved from https://www.heart.org/en/healthy-living/healthy-lifestyle/quit-smoking-tobacco/how-smoking-and-nicotine-damage-your-body Hwang, Y., Cho, H., Sands, L., & Jeong, S. H. (2012). Effects of gain- and loss- framed messages on the sun safety behavior of adolescents: The moderating role of risk perceptions. Journal of Health Psychology, 17(6), 929–940. https://doi.org/10.1177/1359105311428536 Indonesia. (2018). Retrieved from https://www.who.int/nmh/countries/idn_en.pdf?ua=1 Islam, M. A., Barna, S. D., Raihan, H., Khan, M. N. A., & Hossain, M. T. (2020). Depression and anxiety among university students during the COVID-19 pandemic in Bangladesh: A web-based cross-sectional survey. PloS one, 15(8), e0238162. Janz, N. K., & Becker, M. H. (1984). The health belief model: A decade later. Health education quarterly, 11(1), 1-47. Kaba, Z., Khamisa, N., & Tshuma, N. (2017). Age-group differences in risk perceptions of non-communicable diseases among adults in Diepsloot township, Johannesburg, South Africa: A cross-sectional study based on the Health Belief Model. South African Medical Journal, 107(9), 797-804.
Kemp, S. (2020, February 18). Digital 2020: Indonesia - DataReportal – Global Digital Insights. Retrieved from https://datareportal.com/reports/digital-2020-indonesia Kolber, M. R., & Scrimshaw, C. (2014). Family history of cardiovascular disease. Canadian Family Physician, 60(11), 1016-1016. Lang, J. P., Wang, X., Moura, F. A., Siddiqi, H. K., Morrow, D. A., & Bohula, E. A. (2020). A current review of COVID-19 for the cardiovascular specialist. American Heart Journal. Lee, A. Y., & Aaker, J. L. (2004). Bringing the frame into focus: the influence of regulatory fit on processing fluency and persuasion. Journal of personality and social psychology, 86(2), 205. in Updegraff, J. A., Brick, C., Emanuel, A. S., Mintzer, R. E., & Sherman, D. K. (2015). Message framing for health: Moderation by perceived susceptibility and motivational orientation in a diverse sample of Americans. Health Psychology, 34(1), 20. Manning, J. (2014). Definition and classes of Social Media. Encyclopedia of Social Media and Politics, 1158-1162. McLeod, J. M., Kosicki, G. M., and Pan, Z. “On Understanding and Misunderstanding Media Effects.” In J. Curran and M. Gurevitch (eds.), Mass Media and Society. London: Edward Arnold, 1991. Mitchell, C. (2012). PAHO/WHO: Preventing non-communicable diseases in adolescents and young adults. Retrieved from https://www.paho.org/hq/index.php?option=com_content&view=article&id=6688:2012-preventing-non-communicable-diseases-adolescents-young-adults&Itemid=4327&lang=en Mohamed, H. A. E. A., Ibrahim, Y. M., Lamadah, S. M., Hassan, M., & El-Magd, A. (2016). Application of the Health Belief Model for Breast Cancer Screening and Implementation of Breast Self-Examination Educational Program for Female Students of Selected Medical and Non-Medical Faculties at Umm al Qura University. Life Science Journal, 13(5), 21–33. https://doi.org/10.7537/marslsj13051603.Key Niederdeppe, J., Hornik, R. C., Kelly, B. J., Frosch, D. L., Romantan, A., Stevens, R. S., ... & Schwartz, J. S. (2007). Examining the dimensions of cancer-related information seeking and scanning behavior. Health communication, 22(2), 153-167. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed). USA: McGraw-Hill, Inc. Orji, R., Vassileva, J., & Mandryk, R. (2012). Towards an Effective Health Interventions Design: An Extension of the Health Belief Model. Online Journal of Public Health Informatics, 4(3). https://doi.org/10.5210/ojphi.v4i3.4321 Pengpid, S., Peltzer, K., & Mirrakhimov, E. M. (2014). Prevalence of health risk behaviors and their associated factors among university students in Kyrgyzstan. International journal of adolescent medicine and health, 26(2), 175-185. Picture of America : Prevention. (2017, April 6). Retrieved from https://www.cdc.gov/pictureofamerica/pdfs/Picture_of_America_Prevention.pdf Prevention of Cardiovascular Disease : Guidelines for assessment and management of cardiovascular risk. (2007). Retrieved from https://www.who.int/cardiovascular_diseases/guidelines/Full text.pdf Profil Penyakit Tidak Menular Tahun 2016. (2017). Retrieved from http://p2ptm.kemkes.go.id/uploads/VHcrbkVobjRzUDN3UCs4eUJ0dVBndz09/2017/10/PROFIL_Penyakit_Tidak_Menular_Tahun_2016.pdf Radcliffe, D. (2020). COVID-19 ‘s impact on the media in 8 charts. Reifman, A., Arnett, J. J., & Colwell, M. J. (2007). Emerging adulthood: Theory, assessment and application. Journal of Youth Development, 2(1), 37-48. Rimal, R. N., Real, K. (2003). Perceived risk and efficacy beliefs as motivators of change. Human Communication Research, 29(3), 370-399.
Saeidi, M., & Komasi, S. (2018). A predictive model of perceived susceptibility during the year before coronary artery bypass grafting. The Journal of Tehran University Heart Center, 13(1), 6. Sampurno, M. B. T., Kusumandyoko, T. C., & Islam, M. A. (2020). Budaya Media Sosial, Edukasi Masyarakat, Dan Pandemi COVID-19. SALAM: Jurnal Sosial dan Budaya Syar-i, 7(5). Santrock, J. (2014). A Topical Approach to Life Span Development (7th Edition). New York, NY: McGraw-Hill Education. Sarafino, E. P., & Smith, T. W. (2011). Health psychology: Biopsychosocial interactions. Hoboken, NJ: Wiley. Shim, M., Kelly, B., & Hornik, R. (2006). Cancer information scanning and seeking behavior is associated with knowledge, lifestyle choices, and screening. Journal of Health Communication, 11(S1), 157-172. Simons-Morton, B., Haynie, D., O'Brien, F., Lipsky, L., Bible, J., & Liu, D. (2017). Variability in measures of health and health behavior among emerging adults 1 year after high school according to college status. Journal of American college health, 65(1), 58-66. Situasi Kesehatan Jantung. (2014). Retrieved from https://www.kemkes.go.id/resources/download/pusdatin/infodatin/infodatin-jantung.pdf St-Pierre, M., Sinclair, I., Elgbeili, G., Bernard, P., & Dancause, K. N. (2019). Relationships between psychological distress and health behaviors among Canadian adults: Differences based on gender, income, education, immigrant status, and ethnicity. SSM-population health, 7, 100385 Survey Penggunaan TIK. (2017) Retrieved from https://www.google.com/search?safe=strict&sxsrf=ALeKk02w0t9OEqCeu5Iv7pfUqaYwUNBAdw:1599192459784&ei=i71RX4bGL8zw9QOh8bbgDw&q=kominfo tik 2017&oq=kominfo tik 2017&gs_lcp=CgZwc3ktYWIQAzoECAAQRzoGCAAQFhAeOgUIIRCgAToECCEQFVC9GFjKJ2DvKmgAcAF4AIAB4gOIAcsNkgEHMi0yLjEuMpgBAKABAaoBB2d3cy13aXrAAQE&sclient=psy-ab&ved=0ahUKEwjGt_iT0M7rAhVMeH0KHaG4DfwQ4dUDCA0&uact=5# Tang L, Zou W. Health Information Consumption under COVID-19 Lockdown: An Interview Study of Residents of Hubei Province, China. Health Commun. 2021 Jan;36(1):74-80. doi: 10.1080/10410236.2020.1847447. Epub 2020 Nov 10. PMID: 33167736. Taylor, S. E. (2017). Health Psychology. New York, NY: McGraw Hill-Education. Underlying Conditions: Coronavirus. (2020). Retrieved from https://www.umms.org/coronavirus/what-to-know/managing-medical-conditions/coronavirus-risk/underlying-conditions Updegraff, J. A., Brick, C., Emanuel, A. S., Mintzer, R. E., & Sherman, D. K. (2015). Message framing for health: Moderation by perceived susceptibility and motivational orientation in a diverse sample of Americans. Health Psychology, 34(1), 20. Ursachi, G., Horodnic, I. A., & Zait, A. (2015). How reliable are measurement scales? External factors with indirect influence on reliability estimators. Procedia Economics and Finance, 20, 679-686. Rimal, R. N., Real, K. (2003). Perceived risk and efficacy beliefs as motivators of change. Human Communication Research, 29(3), 370-399. Vaterlaus, J. M., Patten, E. V., Roche, C., & Young, J. A. (2015). Gettinghealthy: The perceived influence of social media on young adult health behaviors. Computers in Human Behavior, 45(January 2014), 151–157. https://doi.org/10.1016/j.chb.2014.12.013
Vozikis, A., Drivas, K., & Milioris, K. (2014). Health literacy among university students in Greece: determinants and association with self-perceived health, health behaviours and health risks. Archives of Public Health, 72(1), 1-6. Walker, K. K., Steinfort, E. L., & Keyler, M. J. (2015). Cues to Action as Motivators for Children’s Brushing. Health Communication, 30(9), 911–921. https://doi.org/10.1080/10410236.2014.904030 World Health Organization. (2004). The atlas of heart disease and stroke.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Kyana Salapani Sangadi, Adhityawarman Menaldi

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.