Current issue

The Korean Society for Journalism & Communication Studies - Vol. 63 , No. 6

[ Journalism Communication ]
Korean Journal of Journalism & Communication Studies - Vol. 63, No. 6, pp.96-142
Abbreviation: KSJCS
ISSN: 2586-7369 (Online)
Print publication date 31 Dec 2019
Received 09 Aug 2019 Revised 29 Nov 2019 Accepted 01 Dec 2019
DOI: https://doi.org/10.20879/kjjcs.2019.63.6.003

국내 인터넷 이용자의 미세먼지 위험 예방행위 의도에 관한 사회인지 접근의 RISP, HBM 적용모형 : 정보 노출, 주관적 규범, 부정적 감정, 위험 지각의 역할
차유리** ; 조재희***
**서강대학교 지식융합미디어학부 강사 (ilooy@sogang.ac.kr)
***서강대학교 지식융합미디어학부 부교수 (jcho76@sogang.ac.kr)

A Social-Cognitive Model of Applying RISP and HBM Model for Korean Internet Users’ Behavioral Intentions Regarding Fine-Dust Risk Protection : The Role of Information Exposure, Subjective Norms, Negative Emotions, and Risk Perception
Yuri Cha** ; Jaehee Cho***
**Lecturer, School of Media, Arts, and Science, Sogang University (ilooy@sogang.ac.kr)
***Associate Professor, School of Media, Arts, and Science, Sogang Unviersity, corresponding author (jcho76@sogang.ac.kr)
Funding Information ▼

초록

본 연구의 목적은 한국의 일반 공중이 미세먼지로 인한 위험을 예방하는 행동 과정에 대해 이해하고 설명하는 것이다. 이를 위하여 국내 미세먼지 위험 예방행위 의도 모형을 구축하고자 했고, 해당 위험문제와 예방정보의 특성 및 위험/건강 커뮤니케이션 모형들에 관한 문헌검토부터 선행했다. 사회 인지 접근에서 RISP와 HBM을 적용한 모형의 구성이 적절하다고 판단하여, 위험대상에 대한 휴리스틱 반응 차원의 ‘위험 지각’·‘부정적 감정’ 및 사회 자극 차원의 ‘주관적 규범’·‘정보 노출’을 모형의 변인으로 삼았다. 인터넷 이용자 대상 온라인 조사의 데이터(N = 300)를 바탕으로 적용모형의 적합도 및 경로를 분석한 결과, 모형은 적합하고 예방행위 의도에 대해 모든 변인들은 영향을 미치는 것으로 나타났다. ‘정보 노출’은 간접효과만 유의미했고, 직접 효과를 지닌 요인들 중 ‘부정적 감정’의 영향이 비교적 약함으로써 주요 설명요인은 ‘위험 지각’, ‘주관적 규범’인 것으로 검증됐다. 한편 부정적 감정 및 위험 지각에 대해 주관적 규범의 효과는 모두 유의미했으나, 정보 노출의 효과는 부정적 감정에 대해서만 유의미했다. 이러한 연구결과는 국내미세먼지와 관련된 커뮤니케이션 심리에 대한 이론적 설명력을 높이는 데 기여할 뿐만 아니라, 공중 교육 및 캠페인 전략 구상 시 유용한 자료가 될 수 있다.

Abstract

The purpose of this study is to understand the processes of people’s preventive behaviors for threats posed by fine dust in Korea. We established a model explaining people's preventive behavioral intentions for fine dust risks, based upon an extensive review of the discussions of the risks in the country, characteristics of prevention information, and the previous models in health communication. Informed by RISP(Risk Information Seeking and Processing) and HBM(Health Belief Model) in the social cognition approach, we constructed an applied model with the two variables of risk perception and negative emotions to tap into the dimension of heuristic responses to the object of risk and another two variables of subjective norm and exposure to information to capture the dimension of social influence. In order to test multiple hypotheses focusing on the relationships among main study variables, this research collected quantitative data through an online survey. A research company with a large pool of panels progressed the survey. To increase the representativeness of the samples, a proportionate stratified sampling was used, considering portion of gender, residential areas, and age. In total, 300 usable survey could be collected and used for further statistical analyses. A path analysis was used to test all of those proposed hypotheses. Results of a path analysis of online survey data collected from Korean Internet users (N = 300) supported the model and the variables. Risk perception(β = .40, p < .001) and subjective norm(β = .36, p < .001) were found to be the strongest explanatory variables for people's behavioral intentions, with negative emotions(β = .16, p < .001) and exposure to information(β = .24, p < .01) carrying a relatively weaker power and having an indirect relationship respectively. While subjective norm influenced both negative emotions(β = .20, p < .01) and risk perception (β = .55, p < .001), exposure to information affected negative perception only (β = .18, p < .001), indicating the usefulness of a heuristic approach to explaining the processes of the formation of people’s preventive behavioral intentions. The main findings from this research contribute to strengthening theoretical explanations of communication psychology in terms of fine dust risks prevention, especially addressing the main connections among perceptual, emotional, and behavioral variables in regards to preventive behaviors of fine dust risks. Moreover, those findings may also be useful for developing measures and education campaigns for the public. Because it has been well known that fine dust causes or exacerbates diverse diseases including respiratory diseases, cardiovascular disorders, diabetes, and so on, public health campaigns in regards to fine dust risks have become more and more necessary. This research’s main findings are helpful for developing practical strategies for those campaigns.


Keywords: fine-dust risks, preventive behavioral intention, social cognitive approach, subjective norm, information exposure
키워드: 미세먼지 위험 예방행위 의도, 사회인지이론, 주관적 규범, 정보 노출, 적용모형

Acknowledgments

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A3A2074932). (본 연구는 2018년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구 (NRF-2018S1A3A2074932)임).


References
1. Ajzen I. (1988). Attitudes, personality, and behavior. Milton Keynes, UK: Open University Press.
2. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
3. Ajzen, I. (2005). Frequently asked questions about TPB. Retrieved 8/9/19 from http://www.people.umass.edu/aizen/faq.html
4. Anand, P., & Sternthal, B. (1991). Perceptual fluency and affect without recognition. Memory & cognition, 19(3), 293-300.
5. Anderson, J., & Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
6. Balantekin, K. N., Birch, L. L., & S Avage, J. S. (2018). Family, friend, and media factors are associated with patterns of weight-control behavior among adolescent girls. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity, 23(2), 215-223.
7. Bamberg, S., Masson, T., Brewitt, K., & Nemetschek, N. (2017). Threat, coping and flood prevention. Journal of Environmental Psychology, 54, 116-126.
8. Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ: Prentice Hall.
9. Bandura, A. (2002). Social cognitive theory of mass communication. In J. Bryant, & D. Zillmann (Eds.), Media effects (pp. 121–154) (2nd ed.). Mahweh, NJ: Lawrence Erlbaum Associates
10. Brewer, N. T., Chapman, G. B., Gibbons, F. X., Gerrard, M., McCaul, K. D., & Weinstein, N. D. (2007). Meta-analysis of the relationship between risk perception and health behavior. Health Psychology, 26(2), 136.
11. Butler, L. T., & Berry, D. C. (2004). Understanding the relationship between repetition priming and mere exposure. British Journal of Psychology, 95(4), 467-487.
12. Cha, E. S., Doswell, W. M., Kim, K. H., Charron-Prochownik, D., & Patrick, T. E. (2007). Evaluating the theory of planned behavior to explain intention to engage in premarital sex amongst Korean college students. International Journal of Nursing Studies, 44(7), 1147-1157.
13. Chandran, S., & Menon, G. (2004). When a day means more than a year. Journal of Consumer Research, 31(2), 375-389.
14. Chaiken, S., & Maheswaran, D. (1994). Heuristic processing can bias systematic processingt. Journal of personality and social psychology, 66(3), 460.
15. Chaiken, S., & Trope, Y. (Eds.). (1999). Dual-process theories in social psychology. NY: Guilford Press.
16. Cho, D. C., & Chung, K. H. (2017, April 4). Fine dust, penetrates brain through olfactory nerve… Ways to discharge? SBS News. Retrieved 8/9/19 from https://news.sbs.co.kr/news/endPage.do?news_id=N1004129436
17. Cho, J., Park, D., & Lee, H. E. (2014). Cognitive factors of using health apps. Journal of Medical Internet Research, 16(5), e125.
18. Cho, J., Lee, H. E., & Quinlan, M. (2015). Complementary relationships between traditional media and health apps among American college students. Journal of American College Health, 63(4), 248-257.
19. Choi, S. H. (2018). A study on the factors affecting fine dust cognition, knowledge, and attitude among college students. Journal of the Korea Contents Association, 18(12), 281-290.
20. Duarte, R., Escario, J. J., & Sanagustin, M. V. (2017). The influence of the family, the school, and the group on the environmental attitudes of European students. Environmental Education Research, 23(1), 23-42.
21. Dunwoody, S., & Griffin, R. J. (2015), Risk information seeking and processing model. In H. Cho, T. Reimer, and K. A. McComas (Eds.), SAGE Handbook of Risk Communication (pp.102-115). Thousand Oaks, CA: Sage Publications.
22. Ejeta, L. T., Ardalan, A., & Paton, D. (2015). Application of behavioral theories to disaster and emergency health preparedness. PLoS currents, 7.
23. Ferrer, R. A., Klein, W. M., Persoskie, A., Avishai-Yitshak, A., & Sheeran, P. (2016). The tripartite model of risk perception. Annals of Behavioral Medicine, 50, 1–11.
24. Ford, J. L. (2018). Revisiting high-reliability organizing. Corporate Communications: An International Journal, 23(2), 197-211.
25. Frazzetto, G. (2013). How We Feel. London: Doubleday.
26. Grasso, K. L., & Bell, R. A. (2015). Understanding health information seeking. Journal of Health Communication, 20(12), 1406-1414.
27. Griffin, R. J., Dunwoody, S., & Neuwirth, K. (1999). Proposed model of the relationship of information seeking and processing to the development of preventive behaviors. Environmental Research, 80, 230-S245.
28. Griffin, R. J., Dunwoody, S., & Yang, Z. J. (2012). Testing the robustness of a risk information processing model. Communication Yearbook, 36, 323–362.
29. Greenwald, A. G., & Banaji, M. R. (1995). Implicit social cognition. Psychological Review, 102, 4-27
30. Gu, X., Liu, Q., Deng, F., Wang, X., Lin, H., Guo, X., & Wu, S. (2019). Association between particulate matter air pollution and risk of depression and suicide. The British Journal of Psychiatry, 1-12.
31. Hamid, P. N. (1973). Exposure frequency and stimulus preference. British Journal of Psychology, 64(4), 569-577.
32. Han, H., Kim, Y., & Kum, H. (2017). A study on the PR strategies based on the situational theory of publics: Focusing on particulate matter issues. Korean Journal of Journalism & Communication Studies, 61(3), 222-254.
33. Hine, D. W., Marks, A. D., Nachreiner, M., Gifford, R., & Heath, Y. (2007). Keeping the home fires burning. Journal of Environmental Psychology, 27(1), 26-32.
34. Hoffman, M. L. (1986). Affect, cognition and motivation, in handbook of motivation and cognition, R. M. Sorrentino and E. T. HIggins (Eds.), Foundations of social behavior (pp. 244-280), NY: Guilford.
35. Huang, J., & Yang, Z. J. (2018). Risk, affect, and policy support. Asian Journal of Communication, 28(3), 281-297.
36. Huurne, E. T., & Gutteling, J. (2008). Information needs and risk perception as predictors of risk information seeking. Journal of Risk Research, 1(7), 847-862.
37. Jones, C., Hine, D. W., & Marks, A. D. (2017). The future is now. Risk Analysis, 37(2), 331-341.
38. Jung, H.-S., Kim, M.-K., Yeo, Y.-J., Jeon, J.-A., Kim, M.-K., Woo, S.-H., & Choi, J.-Y. (2017). A study of social problem and social cohesion in Korea with policy recommendations. Korea Institute for Health and Social Affairs.
39. Jwa, B., Yun, M.-Y., Paek H.-J., (2013). Media, risk characteristics, and risk perceptions: The context of carcinogenic hazards. Journal of Public Relations, 17(4), 72-109.
40. Kahlor, L., Dunwoody, S., Griffin, R. J., Neuwirth, K., & Giese, J. (2003). Studying heuristic-systematic processing of risk communication. Risk Analysis. An International Journal, 23(2), 355-368.
41. Kahlor, L., Dunwoody, S., Griffin, R. J., & Neuwirth, K. (2006). Seeking and processing information about impersonal risk. Science communication, 28(2), 163-194.
42. Kahlor, L. (2010). PRISM. Health Communication, 25(4), 345-356.
43. Kang, C. S. (2018). Fine dust used to be more serious in the past… Reasons for the present fuss. JoongAng Ilbo. Retrieved 8/9/19 from https://news.joins.com/article/22484596
44. Kim, H. S. (2019, January 17). Has it become worse or better than the past?. Yonhap News. Retrieved 8/9/19 from https://www.yna.co.kr/view/AKR20190117053800502
45. Kim, J.-N., & Grunig, J. E. (2011). Problem solving and communicative action. Journal of Communication, 61, 120-149.
46. Kim, J. N., Shen, H., & Morgan, S. E. (2011). Information behaviors and problem chain recognition effect. Health Communication, 26(2), 171-184.
47. Kim, J. N., Ni, L., Kim, S. H., & Kim, J. R. (2012). What makes people hot?. Journal of Public Relations Research, 24(2), 144-164.
48. Kim, Y. J., Njite, D., & Hancer, M. (2013). Anticipated emotion in consumers’ intentions to select eco-friendly restaurants. International Journal of Hospitality Management, 34, 255-262.
49. Kim, Y.-W., Lee, H.-S., Lee, H.-J., Lee, H.-J., & Jang, Y.-J. (2015a). A study of the public’s perception and opinion formation on particulate matter risk. Korean Journal of Communication & Information, 72, 52-91.
50. Kim, Y.-W., Lee, H.-S., Jang, Y.-J., & Lee, H.-J. (2015b). How does media construct particulate matter risks?: a news frame and source analysis on particulate matter risks, Korean Journal of Journalism & Communication Studies, 59(2), 121-154.
51. Kim, S., & Cha, H. (2016). The effect of responsibility attribution message and emotion on the policy support and health behavior in obesity circumstance: an application of attribution theory and theory of planned behavior. Korean Journal of Journalism & Communication Studies, 60(2), 369-398.
52. Kim, Y.-W., Lee, H.-S., Lee, H.-J. & Jang, Y.-J. (2016). A Study on differences between experts and lay people about risk perceptions toward particulate matter. Communication Theories, 12(1), 53-117.
53. Kim, Y.-W., Lee, H., Kim, H., & Moon, H. (2017a). A study on usage effect and acceptance factors of a particulate matter application (App). Journal of Public Relations, 21(4), 114-142.
54. Kim, Y.-W., Lee, H. Lee, H., Kim, H. (2017b). A study on the environmental risk Information seeking and processing model about particulate matter. Korean Journal of Communication Studies, 25(2), 5-44.
55. Kim, Y., Kim, Y., & Kim, S. (2018a). Risk seeking and processing on climate change. Korean Journal of Journalism & Communication Studies, 62(5), 72-106.
56. Kim, Y.-W., Lee, H., Kim, H., & Moon, H. (2018b). Exploring message strategies for encouraging coping behaviors against particulate matter. Korean Journal of Communication & Information, 92, 7-44.
57. Kiviniemi, M. T., & Ellis, E. M. (2014). Worry about skin cancer mediates the relation of perceived cancer risk and sunscreen use. Journal of Behavioral Medicine, 37, 1069-1074.
58. Kiviniemi, M. T., Voss-Humke, A. M., & Seifert, A. L. (2007). How do I feel about the behavior?. Health Psychology, 26, 152-158.
59. Kiviniemi, M. T., Jandorf, L., & Erwin, D. O. (2014). Disgusted, embarrassed, annoyed. Annals of Behavioral Medicine, 48(1), 112-119.
60. Kiviniemi, M. T., Ellis, E. M., Hall, M. G., Moss, J. L., Lillie, S. E., Brewer, N. T., & Klein, W. M. (2018). Mediation, moderation, and context. Psychology & health, 33(1), 98-116.
61. Klasko-Foster, L. B., Kiviniemi, M. T., Jandorf, L. H., & Erwin, D. O. (2019). Affective components of perceived risk mediate the relation between cognitively-based perceived risk and colonoscopy screening. Journal of Behavioral Medicine, 1-10.
62. Kye, S. Y., & Park, K. (2018). Factors affecting online health information seeking by channels. Korean Journal of Health Education and Promotion, 35(2), 1-11.
63. Lang, A., & Yegiyan, N. S. (2008). Understanding the interactive effects of emotional appeal and claim strength in health messages. Journal of Broadcasting & Electronic Media, 52, 432-447.
64. Lawton, R., Conner, M., & Parker, D. (2007). Beyond cognition. Health psychology, 26(3), 259-267.
65. Lee, S. A. (2019, March 6). Artificial lungs exposed to fine dust turns coal-black in one day. JoongAng Ilbo. Retrieved from 12/8/19 https://news.joins.com/article/23402710
66. Lee, H.-H., Kim, E.-J., & Lee, M.-K. (2003). A validation study of Korea positive and negative affect schedule. Korean Journal of Clinical Psychology, 22(4), 935-946.
67. Lee, S. Y., & Hawkins, R. P. (2016). Worry as an uncertainty-associated emotion. Health Communication, 31(8), 926-933.
68. Lee, J.-Y. Ju, D.-H., Shin, J.-W., & Paek, H.-J. (2019). The effects of fine dust mobile app information presentation format on risk perception, intention to use app, and preventive behavioral intention. Journal of Public Relations, 23(2), 111-140.
69. Lee, Y.A. Lee, N.-G., & Lee, H.-J. (2013). Risk perception of Korean. Paju: Nanam.
70. Lobb, A. E., Mazzocchi, M., & Traill, W. B. (2007). Modelling risk perception and trust in food safety information within the theory of planned behaviour. Food Quality and Preference, 18(2), 384-395.
71. Lu, X., Xie, X., & Liu, L. (2015). Inverted U-shaped model. Judgment & Decision Making, 10(3). 219-224.
72. Ministry of Environment (2016). You will see it when you know it properly. What is Particulate Matter?. Retrieved 8/9/19 from http://www.me.go.kr/smg/web/board/read.do?menuId=826&boardId=630010&boardMasterId=282&condition.hideCate=1
73. 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.
74. Mullan, B., Wong, C., & Kothe, E. (2013). Predicting adolescent breakfast consumption in the UK and Australia using an extended theory of planned behaviour. Appetite, 62, 127-132.
75. Myrick, J. G., & Oliver, M. B. (2015). Laughing and crying. Health Communication, 30(8), 820-829.
76. Na, E. (2010). Media Psychology, Seoul: Hannarae.
77. Nabi, R. L. (2002). Anger, fear, uncertainty, and attitudes. Communication Monographs, 69, 204-216.
78. Nelson, L. D., Spence, P. R., & Lachlan, K. A. (2009). Learning from the media in the aftermath of a crisis. Electronic News, 3(4), 176-192.
79. Noh, G. Y., Lee, S. Y., & Choi, J. (2016). Exploring factors influencing smokers’ information seeking for smoking cessation. Journal of Health Communication, 21(8), 845-854.
80. Oh, D. Y., & Choi, M. (2016). Effects of audiences’ quality evaluation and satisfaction of media health information on the use of information. Korean Journal of Communication Studies, 24(2), 181-209.
81. Paek, H. J., Bae, B. J, Hove, T., & Yu, H. (2011). Theories into practice. Internet Research, 21(1), 5-25.
82. Park, S. H. (2018a). Correlation between the harmfulness of fine dust and climate change. Korea Environmental Industry & Technology Institute.
83. Park, S. H. (2018b). Causes of fine dust occurrence and countermeasures. Korea Environmental Industry & Technology Institute.
84. Park, H. S., & Lee, J. M. (2016). A validation study of Korean version of PANAS-Revised. Korean Journal of Psychology: General, 35(4), 617-641.
85. Parkinson, J., Russell-Bennett, R., & Previte, J. (2018). Challenging the planned behavior approach in social marketing. European Journal of Marketing, 52(3/4), 837-865.
86. Pedersen, S., Grønhøj, A., & Thøgersen, J. (2015). Following family or friends. Social norms in adolescent healthy eating. Appetite, 86, 54-60.
87. Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion. NY: Springer-Verlag.
88. Previte, J., Russell, Bennett, R., & Parkinson, J. (2015). Shaping safe drinking cultures. International Journal of Consumer Studies, 39(1), 12-24.
89. Pun, V. C., Manjourides, J., & Suh, H. (2016). Association of ambient air pollution with depressive and anxiety symptoms in older adults. Environmental Health Perspectives, 125(3), 342-348.
90. Ramirez, A. S., Freres, D., Martinez, L. S., Lewis, N., Bourgoin, A., Kelly, B. J., & Hornik, R. C. (2013). Information seeking from media and family/friends increases the likelihood of engaging in healthy lifestyle behaviors. Journal of Health Communication, 18(5), 527-542.
91. Research Institute for Healthcare Policy (2016, May. 4). 'Particulate matter' is the one that the public health risks that people are the most afraid of. Retrieved 8/9/19 from http://www.rihp.re.kr/news/press-release/?mod=document&uid=1757
92. Rhee, J. W., & Kim, S.-H. (2018). News frames in the coverage of fine-dust disaster. Korean Journal of Journalism & Communication Studies, 62(4), 125-158.
93. Rimal, R. N., & Real, K. (2003). Perceived risk and efficacy beliefs as motivators of changes. Human Communication Research, 29(3), 370-399.
94. Robinson, N. G., White, K. M., Hamilton, K., & Starfelt, L. C. (2016). Predicting the sun-protective decisions of young female Australian beachgoers. Journal of Health Psychology, 21(8), 1718-1727.
95. Rosenstock, I. M. (1974). Historical origins of the health belief model. Health Education Monographs, 2(4), 328-335.
96. Rosenstock, I. M., Strecher, V. J., & Becker, M. H. (1988). Social learning theory and the health belief model. Health Education Quarterly, 15(2), 175-183.
97. Seoul Metropolitan Council (2019, April). Public opinion poll regarding state of fine-dust mask-wearing. Retrieved 8/9/19 from https://opengov.seoul.go.kr/council/18004939
98. Stephens, K. K., Barrett, A. K., & Mahometa, M. J. (2013). Organizational communication in emergencies. Human Communication Research, 39(2), 230-251.
99. Stevens, J. (1996). Applied multivariate statistics for the social sciences. NJ: Lawrence Erlbaum Associates
100. Slovic, P. (1987). Perception of risk. Science, 236(4799), 280-285.
101. Slovic, P., Finucane, M. L., Peters, E., & MacGregor, D. G. (2004). Risk as analysis and risk as feelings. Risk Analysis, 24(2), 311-322.
102. So, J., Kim, S. and Cohen, H. (2017), Message fatigue. Communication Monographs, 84(1), 5-29.
103. Straub, R. O. (2012). Health psychology. New York, NY: Worth Publishers.
104. Strecher, V. J., & Rosenstock, I. M. (1997). The health belief model. in A. Baum, S. Newman, J. Weinman, C. McManus, & R. West. (Eds.). Cambridge handbook of psychology, health and medicine (pp. 113-117). Cambridge, UK: Cambridge University Press.
105. Tajfel, H., & Turner, J. C. (1986). The social identity of intergroup relations. In S. Worchel & W. G. Austin (Eds.), Psychology of intergroup relations(pp. 7-24). Chicago, IL: Nelson-Hall.
106. Turner, J. C., Hogg, M. A., Oakes, P. J., Reicher, S. D., & Wetherell, M. S. (1987). Rediscovering the social group. Oxford, UK: Blackwell.
107. Vainio, A., Paloniemi, R., & Varho, V. (2017). Weighing the risks of nuclear energy and climate changer. Risk Analysis, 37(3), 557-569.
108. Wahlberg, A. A., & Sjoberg, L. (2000). Risk perception and the media. Journal of Risk Research, 3(1), 31-50.
109. Wei, J., Zhao, M., Wang, F., Cheng, P., & Zhao, D. (2016). An empirical study of the Volkswagen crisis in China. Risk Analysis, 36(1), 114-129.
110. Whitmarsh, L. (2008). Are flood victims more concerned about climate change than other people?. Journal of Risk Research, 11(3), 351-374.
111. Wiegman, O., & Gutteling, J. M. (1995). Risk appraisal and risk communication. Basic and Applied Social Psychology, 16(1-2), 227-249.
112. Woo, J. P. (2012). Professor Woo Jong-pil's concept and understanding of structural equation modelling. Seoul: Hannaharae.
113. Witte, K. (1992). Putting the fear back into fear appeals. Communication Monographs, 59, 329-349.
114. Wu, X., Qi, W., Hu, X., Zhang, S., & Zhao, D. (2017). Consumers’ purchase intentions toward products against city smog. Natural Hazards, 88(1), 611-632.
115. Van Cappellen, P., Rice, E. L., Catalino, L. I., & Fredrickson, B. L. (2018). Positive affective processes underlie positive health behaviour change. Psychology & Health, 33(1), 77-97.
116. Xu, Z., Shan, J., Li, J., & Zhang, W. (2019). Extending the theory of planned behavior to predict public participation behavior in air pollution control. Journal of Environmental Planning and Management, 1-20.
117. Yan, J., Wei, J., Zhao, D., Vinnikova, A., Li, L., & Wang, S. (2018). Communicating online diet-nutrition information and influencing health behavioral intention. Journal of Health Communication, 23(7), 624-633.
118. Yang, Z. J., Aloe, A. M., & Feeley, T. H. (2014). Risk information seeking and processing model. Journal of Communication, 64(1), 20-41.
119. Yoo, S., Park, K., & Na, E. (2010). The effect of psychological reactance and fear of Influenza A(H1N1) message on the preventive behavioral intention. Korean Journal of Journalism & Communication Studies, 54(3), 27-53.
120. Yang, J. Z., & Huang, J. (2019). Seeking for Your Own Sake. Environmental Communication, 13(5), 603-616.
121. Yang, R., Wei, J., Lu, L., & Li, L. (2019). Air pollution and green consumption of consumers in china’s urban areas. Human and Ecological Risk Assessment, 1-23.
122. Yun, S. U., & Chang, J. G. (2018). A study on determinants of particulate matter prevention behavior intention based on SNS. Korean Journal of Communication and Information, 90, 74-98.
123. Zajonc, R. B. (1968). Attitudinal effects of mere exposure. Journal of Personality and Social Psychology Monographs, 9(2), 1-27.
124. Zajonc, R. B., & Markus, H. (1982). Affective and cognitive factors in preferences. Journal of Consumer Research, 9(2), 123-131.

부록
1. 강찬수 (2018). 옛날 미세먼지 더 심했는데··· 요즘 이렇게 난리치는 이유. <중앙일보>. Retrieved 8/9/19 from https://news.joins.com/article/22484596
2. 계수연·박기호 (2018). 온라인 채널별 건강정보 검색에 영향을 미치는 요인. <보건교육건강증진학회지>, 35권 2호, 1-11.
3. 김수진·차희원 (2016). 비만의 책임귀인 메시지와 감정이 정책지지와 건강행동의도에 미치는 영향. <한국언론학보>, 60권 2호, 369-398.
4. 김영욱·이현승·이혜진·장유진 (2015a). 미세먼지 위험에 대한 수용자의 인식과 의견 형성에 관한 연구. <한국언론정보학보>, 통권 72호, 52-91.
5. 김영욱·이현승·장유진·이혜진 (2015b). 언론은 미세먼지 위험을 어떻게 구성하는가?. <한국언론학보>, 59권 2호, 121-154.
6. 김영욱·이현승·이혜진·장유진 (2016). 미세먼지 위험에 대한 전문가와 일반인의 인식차이와 커뮤니케이션 단서 탐색. <커뮤니케이션 이론>, 12권 1호, 53-117.
7. 김영욱·이하나·김혜인·문현지 (2017a). 미세먼지 어플리케이션 이용 효과 및 수용 요인에 대한 연구. <홍보학 연구>, 21권 4호, 114-142.
8. 김영욱·이현승·이혜진·김혜인 (2017b). 미세먼지 위험에 대한 공중들의 정보탐색과 처리에 대한 연구. <커뮤니케이션학 연구>, 25권 2호, 5-44.
9. 김영욱·김영지·김수현 (2018a). 기후변화에 대한 위험 정보 추구 및 처리 연구. <한국언론학보>, 62권 5호, 72-106.
10. 김영욱·이하나·김혜인·문현지 (2018b). 미세먼지 대응 행동 촉진을 위한 메시지 구성 전략 탐색. <한국언론정보학보>, 통권 92호, 7-44.
11. 김희선 (2019, 1, 17). 과거보다 악화됐나, 개선됐나. <연합뉴스>. Retrieved 8/9/19 from https://www.yna.co.kr/view/AKR20190117053800502
12. 나은영 (2010). <미디어심리학>. 서울: 한나래.
13. 박세환 (2018a). <미세먼지의 유해성과 기후변화와의 상관관계>. 한국환경산업기술원.
14. 박세환 (2018b). <미세먼지 발생원인 및 대응정책 이슈>. 한국환경산업기술원.
15. 박홍석·이정미 (2016). 정적 정서 부적정서 척도 (PANAS) 의 타당화. <한국심리학회지 : 일반>, 35권 4호, 617-641.
16. 서울특별시의회 (2019, 4). <미세먼지 마스크 착용실태에 대한 여론조사>. Retrieved 8/9/19 from https://opengov.seoul.go.kr/council/18004939
17. 오대영·최믿음 (2016). 수용자의 미디어 건강정보 품질 인식, 만족도가 이용에 미치는 영향. <커뮤니케이션학 연구>, 24권 2호, 181-209.
18. 우종필 (2012). <우종필 교수의 구조방정식 모델 개념과 이해>. 서울: 한나래.
19. 유선욱·박계현·나은영 (2010). 신종플루 메시지에 대한 심리적 반발과 공포감이 예방행동의도에 미치는 영향. <한국언론학보>, 54권 3호, 27-53.
20. 윤승욱·장준갑 (2018). SNS를 기반으로 한 미세먼지 예방 행위의도 결정요인에 관한 연구: SNS 이용자들을 중심으로. <한국언론정보학보>, 통권 90호, 74-98.
21. 의료정책연구소 (2016. 5. 4). 국민들이 가장 두려워하는 공중보건 위험요소로 ‘미세먼지’ 꼽아. Retrieved 8/9/19 from http://www.rihp.re.kr/news/press-release/?mod=document&uid=1757
22. 이소아 (2019, 3, 6). 미세먼지 노출된 인공 폐 하루만에 새까매졌다. <중앙일보>. Retrieved 8/9/19 from https://news.joins.com/article/23402710
23. 이영애·이나경·이현주 (2013). <한국인의 위험지각>. 파주: 나남.
24. 이준영·주도희·신지원·백혜진 (2019). 미세먼지 어플리케이션의 정보 제시 형식이 위험인식, 앱 사용 의도, 예방 행동 의도에 미치는 영향. <홍보학 연구>, 23권 2호, 111-140.
25. 이준웅·김성희 (2018). 미세먼지 재해 보도의 프레임 분석. <한국언론학보>, 62권 4호, 125-158.
26. 이현희·김은정·이민규 (2003). 한국판 정적 정서 및 부정적 감정 척도의 타당화 연구. <Korean Journal of Clinical Psychology>, 22권 4호, 935-946.
27. 정해식·김미곤·여유진·전진아·김문길·우선희·최준영 (2017). <사회통합 실태 진단 및 대응 방안 연구 (IV) - 사회문제와 사회통합>. 한국보건사회연구원.
28. 조동찬·정구희 (2017. 04. 04). 미세먼지, 후각신경 통해 뇌에 침투...배출 방법 없나?. <SBS NEWS>. Retrieved 8/9/19 from https://news.sbs.co.kr/news/endPage.do?news_id=N1004129436
29. 좌보경·윤문영·백혜진 (2013). 미디어, 지각된 위험 특성, 위험 인식의 관계에 대한 연구-발암물질 위험 이슈를 중심으로. <홍보학 연구>, 17권 4호, 72-109.
30. 최승혜 (2018). 대학생의 미세먼지 인식, 지식, 태도에 영향을 주는 요인에 대한 연구. <한국콘텐츠학회논문지>, 18권 12호, 281-290.
31. 한혁·김영욱·금현섭 (2017). 공중상황이론을 바탕으로 한 PR 전략 연구. <한국언론학보>, 61권 3호, 222-254.
32. 환경부 (2016). <바로 알면 보인다. 미세먼지, 도대체 뭘까>. Retrieved 8/9/19 from http://www.me.go.kr/smg/web/board/read.do?menuId=826&boardId=630010&boardMasterId=282&condition.hideCate=1