Poly Social Media Use: Roles of Informational Norms and Emotion Regulation

References

• Afifi, W. A., & Weiner, J. L. (2004). Toward a theory of motivated information management. Communication Theory, 14(2), 167–190. doi:10.1111/j.1468-2885.2004.tb00310.x
   Web of Science ®Google Scholar
• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. doi:10.1016/0749-5978(91)90020-T
   Web of Science ®Google Scholar
• Altshuler, J., & Ruble, D. (1989). Developmental changes in children’s awareness of strategies for coping with uncontrollable stress. Child Development, 60, 1337–1349. doi:10.2307/1130925
   PubMed Web of Science ®Google Scholar
• American Psychological Association. (2020). Psychological impact of COVID-19. https://www.apa.org/topics/covid-19/psychological-impact
   Google Scholar
• Andersen, R. M. (1995). Revisiting the behavioral model and access to medical care: Does it matter? Journal of Health and Social Behavior, 36(1), 1–10. doi:10.2307/2137284
   PubMed Web of Science ®Google Scholar
• Arslan, G., Yıldırım, M., & Zangeneh, M. (2021). Coronavirus anxiety and psychological adjustment in college students: Exploring the role of college belongingness and social media addiction. International Journal of Mental Health and Addiction, 1–14. doi:10.1007/s11469-020-00460-4
   PubMed Web of Science ®Google Scholar
• Asmundson, G. J., & Taylor, S. (2020). How health anxiety influences responses To viral outbreaks like covid-19: what all decision-makers, health authorities, and health care professionals need to know. Journal of Anxiety Disorders, 71, 102211. doi:10.1016/j.janxdis.2020.102211
   PubMed Web of Science ®Google Scholar
• Atkinson, A. M., Ross-Houle, K. M., Begley, E., & Sumnall, H. (2017). An exploration of alcohol advertising on social networking sites: An analysis of content, interactions and young people’s perspectives. Addiction Research & Theory, 25(2), 91–102. doi:10.1080/16066359.2016.1202241
   Web of Science ®Google Scholar
• Bagozzi, R. P., Wong, N., Abe, S., & Bergami, M. (2000). Cultural and situational contingencies and the theory of reasoned action: application to fast food restaurant consumption. Journal of Consumer Psychology, 9(2), 97–106. doi:10.1207/S15327663JCP0902_4
   Web of Science ®Google Scholar
• Baker, T. B., Piper, M. E., McCarthy, D. E., Majeskie, M. R., & Fiore, M. C. (2004). Addiction motivation reformulated: an affective processing model of negative reinforcement. Psychological Review, 111(1), 33–51. doi:10.1037/0033-295X.111.1.33
   PubMed Web of Science ®Google Scholar
• Bandura, A. (1998). Health promotion from the perspective of social cognitive theory. Psychology & Health, 13(4), 623–649. doi:10.1080/08870449808407422
   Web of Science ®Google Scholar
• Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3(3), 265–299. doi:10.1207/S1532785XMEP0303_03
   Web of Science ®Google Scholar
• Boyle, S. C., Kettering, V., Young, S. H., & LaBrie, J. W. (2020). Lesbians’ use of popular social media sites is associated with perceived drinking norms & interest in receiving personalized normative feedback on alcohol use. Alcoholism Treatment Quarterly, 38(4), 415–429. doi:10.1080/07347324.2020.1723459
   PubMed Web of Science ®Google Scholar
• Chen, E., Lerman, K., & Ferrara, E. (2020). Tracking social media discourse about the Covid-19 pandemic: Development of a public coronavirus twitter data set. JMIR Public Health and Surveillance, 6(2), e19273. doi:10.2196/19273
   PubMedGoogle Scholar
• Chew, C., & Eysenbach, G. (2010). Pandemics in the age of Twitter: Content analysis of tweets during the 2009 H1N1 outbreak. PLoS One, 5(11), e14118. doi:10.1371/journal.pone.0014118
   PubMed Web of Science ®Google Scholar
• Cruz, M. G., Henningsen, D. D., & Williams, M. L. (2000). The presence of norms in the absence of Groups? the impact of normative influence under hidden‐profile conditions. Human Communication Research, 26(1), 104–124. doi:10.1111/j.1468-2958.2000.tb00752.x
   Web of Science ®Google Scholar
• Dai, B., Ali, A., & Wang, H. (2020). Exploring information avoidance intention of social media users: A cognition–affect–conation perspective. Internet Research, 30(5). doi:10.1108/INTR-06-2019-0225
   Web of Science ®Google Scholar
• Diamond, L. M., & Aspinwall, L. G. (2003). Emotion regulation across the life span: An integrative perspective emphasizing self-regulation, positive affect, and dyadic processes. Motivation and Emotion, 27(2), 125–156. doi:10.1023/A:1024521920068
   Web of Science ®Google Scholar
• Dillard, J. P. (1994). Rethinkin the study of fear appeals: An emotional perspective. Communication Theory, 4(4), 295–323. doi:10.1111/j.1468-2885.1994.tb00094.x
   Web of Science ®Google Scholar
• Dillard, J. P., & Anderson, J. W. (2004). The role of fear in persuasion. Psychology & Marketing, 21(11), 909–926. doi:10.1002/mar.20041
   Web of Science ®Google Scholar
• Ding, H., & Zhang, J. (2010). Social media and participatory risk communication during the H1N1 flu epidemic: A comparative study of the United States and China. China Media Research, 6(4), 80–91.
   Google Scholar
• eMarketer. (2022, April 1). US social video usage 2022. https://www.emarketer.com/
   Google Scholar
• Fishbein, M., & Yzer, M. C. (2003). Using theory to design effective health behavior interventions. Communication Theory, 13(2), 164–183. doi:10.1111/j.1468-2885.2003.tb00287.x
   Web of Science ®Google Scholar
• Goldenberg, A., & Gross, J. J. (2020). Digital emotion contagion. Trends in Cognitive Sciences, 24(4), 316–328. doi:10.1016/j.tics.2020.01.009
   PubMed Web of Science ®Google Scholar
• Griffin, R. J., Dunwoody, S., & Neuwirth, K. (1999). Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. Environmental Research, 80(2), S230–245. doi:10.1006/enrs.1998.3940
   PubMed Web of Science ®Google Scholar
• Griffin, R. J., Dunwoody, S., & Yang, Z. J. (2013). Linking risk messages to information seeking and processing. Annals of the International Communication Association, 36(1), 323–362. doi:10.1080/23808985.2013.11679138
   Google Scholar
• Griffin, R. J., Neuwirth, K., Dunwoody, S., & Giese, J. (2004). Information sufficiency and risk communication. Media Psychology, 6(1), 23–61. doi:10.1207/s1532785xmep0601_2
   Web of Science ®Google Scholar
• Gross, J. J. (1998). The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2(3), 271–299. doi:10.1037/1089-2680.2.3.271
   Google Scholar
• Gross, J. J. (2014). Emotion regulation: Conceptual and empirical foundations. In J. J. Gross (Ed.), Handbook of emotion regulation (pp. 3–20). Guilford Press. doi:10.1080/00140130600971135
   Google Scholar
• Harris, P. L., Guz, G. R., Lipian, M. S., & Man-Shu, Z. (1985). Insight into the time course of emotion among Western and Chinese children. Child Development, 972–988. doi:10.2307/1130109
   Web of Science ®Google Scholar
• Hayes, S. C., Strosahl, K., Wilson, K. G., Bissett, R. T., Pistorello, J., Toarmino, D., McCurry, S. M. … McCurry, S. M. (2004). Measuring experiential avoidance: A preliminary test of a working model. The Psychological Record, 54(4), 553–578. doi:10.1007/BF03395492
   Web of Science ®Google Scholar
• Hoffman, E. W., Pinkleton, B. E., Weintraub Austin, E., & Reyes-Velázquez, W. (2014). Exploring college students’ use of general and alcohol-related social media and their associations with alcohol-related behaviors. Journal of American College Health, 62(5), 328–335. doi:10.1080/07448481.2014.902837
   PubMed Web of Science ®Google Scholar
• Holmes, E. A., O’Connor, R. C., Perry, V. H., Tracey, I., Wessely, S., & Arseneault, L., (2020). Multidisciplinary research priorities for the COVID-19 pandemic: A call for action for mental health science. The Lancet Psychiatry, 7, 547–560. doi:10.1016/S2215-0366(20)30168-1
   PubMed Web of Science ®Google Scholar
• Hovick, S. R., Kahlor, L., & Liang, M. C. (2014). Personal cancer knowledge and information seeking through PRISM: The planned risk information seeking model. Journal of Health Communication, 19(4), 511–527. doi:10.1080/10810730.2013.821556
   PubMed Web of Science ®Google Scholar
• Hovland, C., Janis, I., & Kelley, H. (1953). Communication and persuasion. New Haven, CT: Yale University.
   Google Scholar
• Jang, K., & Baek, Y. M. (2019). When information from public health officials is untrustworthy: The use of online news, interpersonal networks, and social media during the MERS outbreak in South Korea. Health Communication, 34(9), 991–998. doi:10.1080/10410236.2018.1449552
   PubMed Web of Science ®Google Scholar
• Janis, I. L. (1967). Effects of fear arousal on attitude change: Recent developments in theory and experimental research. Advances in Experimental Social Psychology, 3, 166–224. doi:10.1016/S0065-2601(08)60344-5
   Google Scholar
• Ju, I., Ohs, J., Park, T., & Hinsley, A. (2021). Harnessing an Integrated Health Communication (IHC) framework for campaigns: A case of prescription drug decision making. Health Communication, advance online doi:10.1080/10410236.2021.1986885
   Web of Science ®Google Scholar
• Ju, I., Park, T., & Ohs, J. E. (2018). Consumer engagement with prescription medicine decisions: Influences of health beliefs and health communication sources. Health Communication, 35(2), 135–147. doi:10.1080/10410236.2018.1545336
   PubMed Web of Science ®Google Scholar
• Jurkowitz, M., & Mitchell, A. (2020, March 25). Americans who primarily get news through social media are least likely to follow COVID-19 coverage, most likely to report seeing-up news. Pew Research Center. https://www.journalism.org/2020/03/25/americans-who-primarily-get-news-through-social-media-are-least-likely-to-follow-covid-19-coverage-most-likely-to-report-seeing-made-up-news/
   Google Scholar
• Kahlor, L. (2010). PRISM: A planned risk information seeking model. Health Communication, 25(4), 345–356. doi:10.1080/10410231003775172
   PubMed Web of Science ®Google Scholar
• Kahlor, L., Dunwoody, S., Griffin, R. J., & Neuwirth, K. (2006). Seeking and processing information about impersonal risk. Science Communication, 28(2), 163–194. doi:10.1177/1075547006293916
   Web of Science ®Google Scholar
• Kong, F., Gong, X., Sajjad, S., Yang, K., & Zhao, J. (2019). How is emotional intelligence linked to life satisfaction? The mediating role of social support, positive affect and negative affect. Journal of Happiness Studies, 20(8), 2733–2745. doi:10.1007/s10902-018-00069-4
   Web of Science ®Google Scholar
• Lapinski, M. K., & Rimal, R. N. (2005). An explication of social norms. Communication Theory, 15(2), 127–147. doi:10.1111/j.1468-2885.2005.tb00329.x
   Web of Science ®Google Scholar
• Larach, H. P. (2021, March 31). 3 ways to humanize the virtual health care experience. Harvard Business Review. https://hbr.org/2021/03/3-ways-to-humanize-the-virtual-health-care-experience
   Google Scholar
• Lee, C. J. (2009). The interplay between media use and interpersonal communication in the context of healthy lifestyle behaviors: Reinforcing or substituting? Mass Communication and Society, 13(1), 48–66. doi:10.1080/15205430802694869
   PubMed Web of Science ®Google Scholar
• Lee, S. A., Mathis, A. A., Jobe, M. C., & Pappalardo, E. A. (2020). Clinically significant fear and anxiety of COVID-19: A psychometric examination of the coronavirus anxiety scale. Psychiatry Research, 290. doi:10.1016/j.psychres.2020.113112
   Web of Science ®Google Scholar
• Madianou, M. (2014). Smartphones as polymedia. Journal of Computer-Mediated Communication, 19(3), 667–680. doi:10.1111/jcc4.12069
   Web of Science ®Google Scholar
• Madianou, M., & Miller, D. (2013). Polymedia: Towards a new theory of digital media in interpersonal communication. International Journal of Cultural Studies, 16(2), 169–187. doi:10.1177/1367877912452486
   Web of Science ®Google Scholar
• Meczkowski, E. J., Dillard, J. P., & Shen, L. (2016). Threat appeals and persuasion: Seeking and finding the elusive curvilinear effect. Communication Monographs, 83, 373–395. doi:10.1080/03637751.2016.1158412
   Web of Science ®Google Scholar
• Merchant, R. M., Elmer, S., & Lurie, N. (2011). Integrating social media into emergency-preparedness efforts. The New England Journal of Medicine, 365(4), 289–291. doi:10.1056/NEJMp1103591
   PubMed Web of Science ®Google Scholar
• Morton, T. A., & Duck, J. M. (2001). Communication and health beliefs: Mass and interpersonal influences on perceptions of risk to self and others. Communication Research, 28(5), 602–626. doi:10.1177/009365001028005002
   Web of Science ®Google Scholar
• National Center for Health Statistics (2020). Mental health household pulse survey. https://www.cdc.gov/nchs/covid19/pulse/mental-health.htm
   Google Scholar
• Ochsner, K. N., & Gross, J. J. (2008). Cognitive emotion regulation: Insights from social cognitive and affective neuroscience. Current Directions in Psychological Science, 17(2), 153–158. doi:10.1111/j.1467-8721.2008.00566.x
   PubMed Web of Science ®Google Scholar
• 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, 36(8), 972–981. doi:10.1080/10410236.2020.1724639
   PubMed Web of Science ®Google Scholar
• Rains, S. A., Brunner, S. R., & Oman, K. (2014). Social media and risk communication. In H. Cho, T. Reimer, & K. A. McComas (Eds.), Sage handbook of risk communication (pp. 228–243). Thousand Oaks, CA: Sage.
   Google Scholar
• Rimal, R. N., Flora, J. A., & Schooler, C. (1999). Achieving improvements in overall health orientation: Effects of campaign exposure, information seeking, and health media use. Communication Research, 26(3), 322–348. doi:10.1177/009365099026003003
   Web of Science ®Google Scholar
• Rimal, R. N., & Lapinski, M. K. (2015). A re-explication of social norms, ten years later. Communication Theory, 25(4), 393–409. doi:10.1111/comt.12080
   Web of Science ®Google Scholar
• Ross, L., Kohler, C. L., Grimley, D. M., Green, B. L., & Anderson-Lewis, C. (2007). Toward a model of prostate cancer information seeking: Identifying salient behavioral and normative beliefs among African American men. Health Education & Behavior, 34(3), 422–440. doi:10.1177/1090198106290751
   PubMed Web of Science ®Google Scholar
• Shah, D. V., Cho, J., Nah, S., Gotlieb, M. R., Hwang, H., Lee, N. J., McLeod, D. M. , and McLeod, D. M. (2007). Campaign ads, online messaging, and participation: Extending the communication mediation model. Journal of Communication, 57(4), 676–703. doi:10.1111/j.1460-2466.2007.00363.x
   Web of Science ®Google Scholar
• Shearer, E. (2021). More than eight-in-ten Americans get news from digital devices. Pew Research Center, 12. https://www.pewresearch.org/fact-tank/2021/01/12/more-than-eight-in-ten-americans-get-news-from-digital-devices/
   Google Scholar
• Sheeran, P., Maki, A., Montanaro, E., Avishai-Yitshak, A., Bryan, A., Klein, W. M., Miles, E. & and Rothman, A. J. (2016). The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: A meta-analysis. Health Psychology, 35(11), 1178. doi:10.1037/hea0000387
   PubMed Web of Science ®Google Scholar
• Sheppes, G., Scheibe, S., Suri, G., & Gross, J. J. (2011). Emotion-regulation choice. Psychological Science, 22(11), 1391–1396. doi:10.1177/0956797611418350
   PubMed Web of Science ®Google Scholar
• So, J. (2013). A further extension of the extended parallel process model (E-EPPM): Implications of cognitive appraisal theory of emotion and dispositional coping style. Health Communication, 28(1), 72–83. doi:10.1080/10410236.2012.708633
   PubMed Web of Science ®Google Scholar
• So, J., Kuang, K., & Cho, H. (2019). Information seeking upon exposure to risk messages: Predictors, outcomes, and mediating roles of health information seeking. Communication Research, 46(5), 663–687. doi:10.1177/0093650216679536
   Web of Science ®Google Scholar
• Song, J., Song, T. M., Seo, D. C., Jin, D. L., & Kim, J. S. (2017). Social big data analysis of information spread and perceived infection risk during the 2015 middle east respiratory syndrome outbreak in South Korea. Cyberpsychology, Behavior and Social Networking, 20(1), 22–29. doi:10.1089/cyber.2016.0126
   PubMed Web of Science ®Google Scholar
• Southwell, B. G., & Torres, A. (2006). Connecting interpersonal and mass communication: science news exposure, perceived ability to understand science, and conversation. Communication Monographs, 73(3), 334–350. doi:10.1080/03637750600889518
   Web of Science ®Google Scholar
• Strekalova, Y. A., & Krieger, J. L. (2017). Beyond words: Amplification of cancer risk communication on social media. Journal of Health Communication, 22(10), 849–857. doi:10.1080/10810730.2017.1367336
   PubMed Web of Science ®Google Scholar
• Tandoc, E. C., Lou, C., & Min, V. L. H. (2019). Platform-swinging in a poly-social-media context: How and why users navigate multiple social media platforms. Journal of Computer-Mediated Communication, 24(1), 21–35. doi:10.1093/jcmc/zmy022
   Web of Science ®Google Scholar
• Tannenbaum, M. B., Hepler, J., Zimmerman, R. S., Saul, L., Jacobs, S., Wilson, K., & Albarracín, D. (2015). Appealing to fear: A meta-analysis of fear appeal effectiveness and theories. Psychological Bulletin, 141(6), 1178–1204. doi:10.1037/a0039729
   PubMed Web of Science ®Google Scholar
• Thackeray, R., Neiger, B. L., Hanson, C. L., & McKenzie, J. F. (2008). Enhancing promotional strategies within social marketing programs: Use of Web 2.0 social media. Health Promotion Practice, 9(4), 338–343. doi:10.1177/1524839908325335
   PubMedGoogle Scholar
• Thompson, R. A. (1994). Emotion regulation: A theme in search of definition. Monographs of the Society for Research in Child Development, 59(2–3), 25–52. doi:10.1111/j.1540-5834.1994.tb01276.x
   PubMedGoogle Scholar
• Tsui, E., Rao, R. C., Carey, A. R., Feng, M. T., & Provencher, L. M. (2020). Using social media to disseminate ophthalmic information during the #COVID19 pandemic. Ophthalmology, 127(9), e75–78. doi:10.1016/j.ophtha.2020.05.048
   PubMed Web of Science ®Google Scholar
• Valkenburg, P. M., & Peter, J. (2013). The differential susceptibility to media effects model. The Journal of Communication, 63(2), 221–243. doi:10.1111/jcom.12024
   Web of Science ®Google Scholar
• Wheaton, M. G., Prikhidko, A., & Messner, G. (2021). Is fear of COVID-19 contagious? The effects of emotion contagion and social media use on anxiety in response to the coronavirus pandemic. Frontiers in Psychology, 11, 3594. doi:10.3389/fpsyg.2020.567379
   Web of Science ®Google Scholar
• Wirz, C. D., Xenos, M. A., Brossard, D., Scheufele, D., Chung, J. H., & Massarani, L. (2018). Rethinking social amplification of risk: Social media and Zika in three languages. Risk Analysis, 38(12), 2599–2624. doi:10.1111/risa.13228
   PubMed Web of Science ®Google Scholar
• Witte, K. (1994). Fear control and danger control: A test of the extended parallel process model (EPPM). Communications Monographs, 61(2), 113–134. doi:10.1080/03637759409376328
   Web of Science ®Google Scholar
• World Health Organization. (2022, April 1). Infodemic. https://www.who.int/health-topics/infodemic#tab=tab_1
   Google Scholar
• Yang, Z. J., Aloe, A. M., & Feeley, T. H. (2014). Risk information seeking and processing model: A meta-analysis. The Journal of Communication, 64(1), 20–41. doi:10.1111/jcom.12071
   Web of Science ®Google Scholar
• Yang, J. Z., & Chu, H. (2018). Who is afraid of the Ebola outbreak? The influence of discrete emotions on risk perception. Journal of Risk Research, 21(7), 834–853. doi:10.1080/13669877.2016.1247378
   Web of Science ®Google Scholar