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Abstract

This study investigates the role of media in risk communication during crises by comparing two theoretical perspectives. The first paradigm views media as a determining factor, while the second sees media as a mediator. The study analyzes two survey data sets: cross-sectional data on nuclear waste issues from eight regions (Mainland China, Hong Kong, Taiwan, Singapore, Japan, South Korea, the United States, and the United Kingdom; N = 8,591) and longitudinal panel data on the COVID-19 pandemic in Hong Kong (N = 920). Results consistently support the the greater explanatory power of the first paradigm. Individuals’ willingness to adopt preventive measures highly depends on the media-constructed risks.

Keywords

media effects risk perception cross-culture crisis communication nuclear waste COVID-19

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References

Armstrong

C. L.

VanDyke

M. S.

(2025). Verify, accept, or ignore: The complexities of media trust along Southeastern U.S. coastal communities during severe weather events. Journalism & Mass Communication Quarterly. https://doi.org/10.1177/10776990251347659

Balatsoukas

Kennedy

C. M.

Buchan

Powell

Ainsworth

(2015). The role of social network technologies in online health promotion: A narrative review of theoretical and empirical factors influencing intervention effectiveness. Journal of Medical Internet Research, 17(6), e3662. https://doi.org/10.2196/jmir.3662

Bekalu

M. A.

McCloud

R. F.

Viswanath

(2019). Association of social media use with social well-being, positive mental health, and self-rated health: Disentangling routine use from emotional connection to use. Health Education & Behavior, 46, 69S–80S. https://www.jstor.org/stable/48625502

Berger

(1995). Essentials of mass communication theory. Sage.

Chae

Lee

C.-J.

(2019). The psychological mechanism underlying communication effects on behavioral intention: Focusing on affect and cognition in the cancer context. Communication Research, 46(5), 597–618. https://doi.org/10.1177/0093650216644021

Champion

V. L.

Monahan

P. O.

Springston

J. K.

Russell

Zollinger

T. W.

Saywell

R. M.

Jr. Maraj

(2008). Measuring mammography and breast cancer beliefs in African American women. Journal of Health Psychology, 13(6), 827–837. https://doi.org/10.1177/1359105308093867

Dai

Huang

Y.-H. C.

Jia

Cai

(2022). The paradoxical effects of institutional trust on risk perception and risk management in the Covid-19 pandemic: Evidence from three societies. Journal of Risk Research, 25(11-12), 1337–1355. https://doi.org/10.1080/13669877.2022.2108122

Drew

(2016). Technological determinism. In Burns

(Eds.), A companion to popular culture (pp. 165–183). Wiley Publications. https://doi.org/10.1002/9781118883341.ch10

Entman

R. M.

(1993). Framing: Toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51–58.

10.

Fenta

E. T.

Bogale

E. K.

Anagaw

T. F.

(2024). The role of social media on COVID-19 preventive behaviors worldwide, systematic review. PLOS ONE, 19(7), e0306284. https://doi.org/10.1371/journal.pone.0306284

11.

Ferrer

R. A.

Portnoy

D. B.

Klein

W. M. P.

(2013). Worry and risk perceptions as independent and interacting predictors of health protective behaviors. Journal of Health Communication, 18(4), 397–409. https://doi.org/10.1080/10810730.2012.727954

12.

Geiger

Newhagen

(1993). Revealing the black box: Information processing and media effects. Journal of Communication, 43(4), 42–50. https://doi.org/10.1111/j.1460-2466.1993.tb01303.x

13.

Gerbner

Gross

Morgan

Signorielli

(1980). The “mainstreaming” of America: Violence profile number 11. Journal of Communication, 30(3), 10–29.

14.

Gostin

L. O.

Ratzan

S. C.

Bloom

B. R.

(2019). Safe vaccinations for a healthy nation: Increasing US vaccine coverage through law, science, and communication. Journal of the American Medical Association, 321(20), 1969–1970.

15.

Griffin

R. J.

Dunwoody

Neuwirth

(1999). Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. Environmental Research, 80(2), S230–S245. https://doi.org/10.1006/enrs.1998.3940

16.

Hill

(2001). Media risks: The social amplification of risk and the media violence debate. Journal of Risk Research, 4(3), 209–225. https://doi.org/10.1080/13669870152023773

17.

Hita

M. L. R.

Grégoire

Lussier

Boissonneault

Vandenberghe

Sénécal

(2023). An extended health belief model for COVID-19: Understanding the media-based processes leading to social distancing and panic buying. Journal of the Academy of Marketing Science, 51(1), 132–152. https://doi.org/10.1007/s11747-022-00865-8

18.

Huang

Y.-H. C.

Cai

Wang

Sun

(2025). What drives public support for health policies? The protection-motivated mediating model of institutional trust and risk paradox. Social Science and Medicine. https://doi.org/10.1016/j.socscimed.2025.118310

19.

Huang

Y. H. C.

Liu

(2022). Go for zero tolerance: Cultural values, trust, and acceptance of zero-COVID policy in two Chinese societies. Frontiers in Psychology, 13, 1047486. https://doi.org/10.3389/fpsyg.2022.104748

20.

Huang

Y. H. C.

Liu

Sun

(2025). Understanding the conditional media effects: Trust, new media exposure, and preventive behaviors during the COVID-19 pandemic. Chinese Journal of Communication, 18(1), 96–113. https://doi.org/10.1080/17544750.2024.2374269

21.

Huang

Y. H. C.

Liu

Zhang

(2025). Does age matter? The impact of social media exposure on people’s mental health. Health Policy and Technology, 14(3), 100997. https://doi.org/10.1016/j.hlpt.2025.100997

22.

Huang

Y.-H. C.

Wang

Fong

I. W.-Y.

(2021). Examining the role of trust in regulators in food safety risk assessment: A cross-regional analysis of three Chinese societies using an integrative framework. SAGE Open. https://doi.org/10.1177/21582440211061579

23.

Johnson

J. D.

Meischke

(1993). A comprehensive model of cancer-related information seeking applied to magazines. Human Communication Research, 19(3), 343–367. https://doi.org/10.1111/j.1468-2958.1993.tb00305.x

24.

Katz

Blumler

J. G.

Gurevitch

(1973). Uses and gratifications research. The Public Opinion Quarterly, 37(4), 509–523.

25.

Katz

Lazarsfeld

P. F.

(1955). Personal influence: The part played by people in the flow of mass communications. Transaction Publisher.

26.

Lazarsfeld

P. F.

Berelson

Gaudet

(1968). The people’s choice: How the voter makes up his mind in a presidential campaign. Columbia University Press. https://doi.org/10.7312/laza93930

27.

Liu

P. L.

(2021). COVID-19 information on social media and preventive behaviors: Managing the pandemic through personal responsibility. Social Science & Medicine, 277, Article 113928. https://doi.org/10.1016/j.socscimed.2021.113928

28.

Liu

Huang

Y.-H. C.

Sun

Lau

Cai

(2022). A shot in the arm for vaccination intention: The media and the health belief model in three Chinese societies. International Journal of Environmental Research and Public Health, 19(6), 3705. https://doi.org/10.3390/ijerph19063705

29.

Loewenstein

Weber

E. U.

Hsee

C. K.

(2001). Risk as feelings. Psychological Bulletin, 127(2), 267–286.

30.

Lowery

S. A.

Defleur

M. L.

(1995). Milestones in mass communication research: Media effects (3rd ed.). Longman.

31.

Melki

Tamim

Hadid

Farhat

Makki

Ghandour

Hitti

(2022). Media exposure and health behavior during pandemics: The mediating effect of perceived knowledge and fear on compliance with COVID-19 prevention measures. Health Communication, 37(5), 586–596. https://doi.org/10.1080/10410236.2020.1858564

32.

Moorhead

S. A.

Hazlett

D. E.

Harrison

Carroll

J. K.

Irwin

Hoving

(2013). A new dimension of health care: Systematic review of the uses, benefits, and limitations of social media for health communication. Journal of Medical Internet Research, 15(4), e1933. https://doi.org/10.2196/jmir.1933

33.

Niedenthal

P. M.

Halberstadt

J. B.

Innes-Ker

Å. H.

(1999). Emotional response categorization. Psychological Review, 106(2), 337. https://doi.org/10.1037/0033-295X.106.2.337

34.

Niu

Jiang

Liu

Yang

Song

(2022). The influence of media consumption on public risk perception: A meta-analysis. Journal of Risk Research, 25(1), 21–47. https://doi.org/10.1080/13669877.2020.1819385

35.

Pennycook

McPhetres

Bago

Rand

D. G.

(2022). Beliefs about COVID-19 in Canada, the United Kingdom, and the United States: A novel test of political polarization and motivated reasoning. Personality and Social Psychology Bulletin, 48(5), 750–765. https://doi.org/10.1177/01461672211023652

36.

Potter

W. J.

Riddle

(2007). A content analysis of the media effects literature. Journalism & Mass Communication Quarterly, 84(1), 90–104. https://doi.org/10.1177/107769900708400107

37.

Rosenstock

I. M.

(1974). The health belief model and preventive health behavior. Health Education Monographs, 2(4), 354–386.

38.

Santoro

Castelnuovo

Zoppis

Mauri

Sicurello

(2015). Social media and mobile applications in chronic disease prevention and management. Frontiers in Psychology, 6, 567. https://doi.org/10.3389/fpsyg.2015.00567

39.

Sarkar

G. M.

Lyles

C. R.

Ramo

Linos

Bibbins-Domingo

(2018). Using social media to target cancer prevention in young adults: Viewpoint. Journal of Medical Internet Research, 20(6), e203. https://doi.org/10.2196/jmir.8882

40.

Shen

Min

Chu

Y. J.

(2021). The effect of cognition and affect on preventive behaviors during the COVID-19 pandemic: A cross-sectional study in China. BMC Public Health, 21(1), Article 722. https://doi.org/10.1186/s12889-021-10784-y

41.

Slovic

Peters

(2006). Risk perception and affect. Current Directions in Psychological Science, 15(6), 322–325. https://doi.org/10.1111/j.1467-8721.2006.00461.x

42.

Valkenburg

P. M.

Peter

Walther

J. B.

(2016). Media effects: Theory and research. Annual Review of Psychology, 67(1), 315–338. https://doi.org/10.1146/annurev-psych-122414-033608

43.

Wang

Zheng

Huang

Y. H. C.

(2023). Examining the pathways from information acquisition to preventive behaviors: The information-response model. Science Communication, 45(6), 724–750. https://doi.org/10.1177/10755470231204317

44.

Wartberg

Kammerl

Bröning

Hauenschild

Petersen

K.-U.

Thomasius

(2015). Gender-related consequences of Internet use perceived by parents in a representative quota sample of adolescents. Behaviour & Information Technology, 34(4), 341–348. https://doi.org/10.1080/0144929X.2014.928746

45.

Watson

Clark

L. A.

Tellegen

(1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063. https://doi.org/10.1037/0022-3514.54.6.1063

46.

Wong

(2023, August 24). Fukushima: China retaliates as Japan releases treated nuclear water. BBC News. https://www.bbc.com/news/world-asia-66577769

47.

World Health Organization. (2024). WHO Coronavirus Disease (COVID-19) Dashboard. https://covid19.who.int/

48.

Zanna

M. P.

Rempel

J. K.

(2008). Attitudes: A new look at an old concept. In Fazio

R. H.

Petty

R. E.

(Eds.), Attitudes: Their structure, function, and consequences (pp. 7–15). Psychology Press.

49.

Zhao

Rosoff

John

R. S.

(2019). Media disaster reporting effects on public risk perception and response to escalating tornado warnings: A natural experiment. Risk Analysis, 39(3), 535–552. https://doi.org/https://doi.org/10.1111/risa.13205

Determining or Mediating Media? Model Comparisons on the Role of Media and Risk in Shaping Preventive Behaviors During Crises

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