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http://dx.doi.org/10.14400/JDC.2019.17.8.471

Determinants of Preventive Behavior Intention to the Particulate Matter: An Application of the Expansion of Health Belief Model  

Chung, Donghun (School of Media and Communication, Kwangwoon University)
Publication Information
Journal of Digital Convergence / v.17, no.8, 2019 , pp. 471-479 More about this Journal
Abstract
The purpose of this study was to investigate the determinants of preventive behavior intention to the particulate matter. The results based on the survey of 280 university students showed that the perceived susceptibility and barriers to the particulate matter do not have statistically significant effects on the preventive behavior intention. However, perceived severity and benefits, subjective norm, and self-efficacy to the particulate matter had statistically significant positive effects on the preventive behavior intention. The results of this study suggested that communication strategies to increase perceived severity and benefits, subjective norm and self-efficacy should be required to improve the degree of preventive behavior intention to the particulate matter of college students. It is expected to contribute explaining preventive actions against environmental hazards such as air pollution in the future.
Keywords
Perceived Severity; Perceived Benefits; Subjective Norm; Self-Efficacy; Particulate Matter;
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Times Cited By KSCI : 3  (Citation Analysis)
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1 J. Joo. (2017). Exploration of structural relations on health behavior related to particulate matter: Focused on multi-dimensional health locus of control, perceived susceptibility and severity, and health behavioral intention. Journal of the Korea Convergence Soceity, 8(11), 413-421.
2 K. Witte & M. Allen. (2000). A meta-analysis of fear appeals: Implications for effective public health campaigns. Health and Education Behavior, 27, 591-615. DOI: 10.1177/109019810002700506   DOI
3 Y. W. Kim, H. S. Lee, Y. J. Jang & H. J. Lee. (2015). 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.
4 Y. W. Kim, H. S. Lee, H. J. Lee & Y. J. Jang. (2015). A study of the public's perception and opinion formation on particulate matter risk: Focusing on the moderating effects of the perceptions toward promotional news and involvement. Korean Journal of Communication & Information, 52-91.
5 R. Cox. (2013). Enviromental communication and the public sphere(3rd ed.). Thousand Oaks, California: Sage.
6 Y. W. Kim, H. S. Lee, H. J. Lee & Y. J. Jang. (2016). A study on differences between experts and lay people about risk perceptions toward particulate matter: A focus on the utilization of mental models. Communication Theories, 12(1), 53-117.
7 H. J. Choi. (2017). Research of risk communication strategy for the enhancement of environmental risk perception and eco-friendly behavioral intention: Application of construcal-level theory on global warming and particulate matter risk message. Doctoral Dissertation, Sungkyunkwan University.
8 N. Smith & A. Leiserowitz. (2012). The rise of global warming skepticism: Exploring affective image assoications in the United States over time. Risk Anlaysis, 32(6), 1021-1032. DOI: 10.1111/j.1539-6924.2012.01801.x   DOI
9 I. M. Rosenstock. (1974). Historical origins of the health belief model. Health Education Monographs, 2(4), 328-335. https://doi.org/10.1177/109019817400200403   DOI
10 S. H. Choi. (2018). A study on the factors affecting fine dust cognition, knowledge, and attitude among college students. The Journal of the Korea Contents Association, 18(12), 281-290.   DOI
11 K. Witte, G. Meyer & D. Martell. (2001). Effective health risk messages: A step-by-step guide. Sage.
12 I. M. Rosenstock, V. Stretcher & M. Becker. (1994). The health belief model and HIV risk behavior. In R. DiClemente & J. Peterson. (ed.), Preventing AIDS: Theories and methods of behavioral intervnentions (pp. 5-22). New York: Plenum Press.
13 M. Conner & P. Norman. (1995). Predicting health behavior: Research and practice with social cognition models. buckingham: Open University Press.
14 N. K. Janz & M. H. Becker. (1984). The health belief model: A decade later. Health Education Quarterly, 11, 1-47. DOI: 10.1177/109019818401100101   DOI
15 B. K. Lee, Y. K. Sohn, L. L. Sang, M. Y. Yoon, M. H. Kim & C. R. Kim. (2014). An efficacy of social cognitive theory to predict health behavior: A meta-analysis on the health belief model studies in Korea. Journal of Public Relations, 18(2), 163-206.   DOI
16 J. A. Harrison, P. D. Mullen & L. W. Green. (1992). A meta-analysis of studies of the health belief model with adults. Health Education Research, 7, 107-116. DOI: 10.1093/her/7.1.107   DOI
17 I. Ajzen. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211. https://doi.org/10.1016/0749-5978(91)90020-T   DOI
18 V. Venkatesch & F. D. Davis. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. DOI: 10.1287/mnsc.46.2.186.11926   DOI
19 Y. W. Kim, H. N. Lee, H, I. Kim & H. J. Moon. (2017). A study on usage effect and acceptance factors of a particulate matter application (App). Journal of Public Relations, 21(4), 114-142. DOI: 10.15814/jpr.2017.21.4.114   DOI
20 N. M. AskeIson, S. Campo, J. B. Lowe, S. Smith, L. K. Dennis & J. Andsager. (2010). Using the theory of planned behavior to predict mothers' intention to vaccinate their daughters against HPV. The Journal of School Nursing, 26(3), 194-202. DOI: 10.1177/1059840510366022   DOI
21 L. A. Martin, K. B. Haskard-ZoInierek & DiMatteo. (2010). Health behavior change and treatment adherence: Evidence-based guidelines for improving healthcare. New York: Oxford University Press.
22 A. Bandura. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215.   DOI
23 V. Champion, C. S. Skinner & U. Menon. (2005). Development of a self-efficacy scale for mammography. Research in Nursing & Health, 28(4), 329-336. DOI: 10.1002/nur.20088   DOI
24 T. Gore & C. C. Bracken. (2005). Testing the theoretical design of a helath risk message: Reexamining the major tenets of the extended parallel process model. Health Education & Behavior, 32(1), 27-41. DOI: 10.1177/1090198104266901   DOI
25 S. U. Yun & J. G. Chang. (2018). A study on determinants of particulate matter prevention behavior intention based on SNS: Focused on SNS Users. Korean Journal of Communication & Information, 90, 74-98.   DOI
26 B. K. Lee, H. J. Oh, K. A. Shin & J. Y. Ko. (2008). The effect of media campaign as a cue to action on influenza prevention behavior: Extending health belief model. Korean Journal of Advertising, 10(4), 108-138. http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE02499627
27 Z. Sheng. (2015). User acceptance of mobile healthcare applications: An integrated model of UTAUT and HBM theory. The Korean Association for Policy Science, 19(3), 203-236. http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE06522193
28 S. E. Jo, H. C. Shin, S. W. Yoo & H. S. Roh. (2012). The study of factors affecting tuberculosis preventive behavior intentions: An extension of HBM with mediating effects of self-efficacy and fear. Jornal of Public Realtions, 16(1), 148-177.   DOI
29 J. S. Na. (2018). A study on the factors influencing the intention to wear a dustproof mask and effective communication planning. Master's Thesis, Hongik University.
30 E. S. Park, H. J. Oh, S. H. Kim & A. R. Min. (2018). The relationships between particulate matter risk perception, knowledge, and health promoting behaviors among college students. Journal of Korean Biological Nursing Science, 20(1), 20-29.   DOI
31 S. J. Yoo, H. J. Jeong & H. S. Park. (2010). The analysis on factors affecting the intention for H1N1 virus vaccination and the impact of negative news reports the comparison between HBM and TPB. The Korean Journal of Advertising Public Relations, 12(3), 283-319.
32 Y. W. Kim, H. S. Lee, Y. J. Jang & H. J. Lee. (2016). A cluster analysis on the risk of particulate matter: Focusing on difference of risk perception and risk related behaviors based on public segmentation. Journal of Public Relations, 20(3), 201-235. DOI : 10.15814/jpr.2016.20.3.201   DOI
33 H. S. Lee & J. H. Lim. (2015). Structural equation model analysis and AMOS 22. Seoul: Jyphyunjae.