DOI QR코드

DOI QR Code

Latent Profile Analysis of High School Students' Fire Safety Awareness

  • Lee, Soon-Beom (Gunsan Jeil High School) ;
  • Kim, Eun-Mi (Education Assignment Institute, Jeonbuk National University) ;
  • Kong, Ha-Sung (Dept. of Fire Protection and Disaster Prevention, Woosuk Univ)
  • Received : 2021.10.27
  • Accepted : 2021.11.05
  • Published : 2021.12.31

Abstract

The purpose of this study is to analyze the types of latent profiles of high school students' fire safety awareness and to identify the characteristics of related variables. For this purpose, a survey was conducted from March 22 to May 25, 2021 for 1054 high school students (male; 569, female; 485) in 3 cities, in Jeollabuk-do. The latent profile was analyzed using a scale consisting of 4 sub-factors: 'fire prevention', 'fire preparedness', 'indirect fire response', and 'direct fire response'. It was checked whether there were differences according to the inter-individual differences of the latent group. As a result of the analysis, fire safety awareness of high school students was classified into three latent profiles. The three groups were named 'High Perception Type', 'Moderate Perception Type', and 'Low Perception Type' according to their types. In fire safety awareness, there is a significant difference in the individual differences according to the gender and academic achievement of the latent profile. These results are meaningful as the first study to analyze the latent profile of high school students' fire safety awareness, and it is also meaningful to provide a useful basis for the contents and methods of customized fire safety education by identifying the tendencies of spontaneous groups and their fire safety awareness.

Keywords

References

  1. National Fire Agency. "If There is a Fire, Evacuate First," https://blog.naver.com.
  2. Kyunghyang Newspaper. "In 4 out of 10 large fires, the cause of the fire could not be found," http://news.khan.co.kr.
  3. Ministry of Education, Confirmation and Presentation of the 2015 Revised Curriculum Summary and Each Statement, pp. 151, 2015.
  4. National Fire Agency, Behavior Change Model and Safety Awareness Index Development Study, pp. 78-79, 2007.
  5. H. W. Kim and M. S. Lee, "A Study on the Development of the Measuring Scale of Safety Consciousness," Journal of Korean Society for Health Education and Promotion, Vol. 19, No. 1, pp. 87-107, 2002.
  6. M. H. Jeong and I. S. Park, "Fire Safety Consciousness Indicators Development and National Fire Safety Consciousness Research," Fire Sci. Eng., Vol. 29, No. 4, pp. 89-94, 2015. DOI: http://dx.doi.org/10.7731/KIFSE.2015.29.4.089
  7. S. T. Lanza, B. L. Rhoades, R. L. Nix, and M. T. Greenberg, "Modeling the interplay of multilevel risk factors for future academic and behavior problems: A person-centered approach," Development and psychopathology, Vol. 22, No. 2, pp. 313-335, 2010. https://doi.org/10.1017/S0954579410000088
  8. J. Huh, N. R. Riggs, D. Spruijt-Metz, C. P. Chou, Z. Huang, and M. Pentz, "Identifying patterns of eating and physical activity in children: a latent class analysis of obesity risk," Obesity, Vol. 19, No. 3, pp. 652-658, June 2011. https://doi.org/10.1038/oby.2010.228
  9. S. B. Lee and H. S. Kong, "Development and Validation of Fire Safety Awareness Scale for High School Students," in Proc. 7th International Integrated Conference & Concert on Convergence (IICCC), pp.4-6, July 22-24, 2021.
  10. B. Muthen and L. K. Muthen, "Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes," Alcoholism: Clinical and Experimental Research, Vol. 24, No. 6, pp. 882-891, 2000. https://doi.org/10.1111/j.1530-0277.2000.tb02070.x
  11. K. Nylund, T. Asparouhov and B. Muthen, "Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study," Structural Equation Modeling, Vol. 14, No. 4, pp. 535-569, 2007. https://doi.org/10.1080/10705510701575396
  12. H. W. Marsh, K. T. Hau, and Z. Wen, "In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler's(1999) findings," Structural Equation Modeling, Vol. 11, No. 3, pp. 320-341, 2004. https://doi.org/10.1207/s15328007sem1103_2
  13. E. M. Kim, The Importance and Implementation of General High School Students' Subject Selection Criteria, Ph.D. Thesis. Jeonbuk National University, 2021.
  14. B. O. Muthen, Latent variable analysis. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social science, Thousand Oaks, CA: Sage, pp. 345-368, 2004.
  15. J. R. Hipp and D. J. Bauer, "Local solutions in the estimation of growth mixture models," Psychological Methods, Vol. 11, pp. 36-53, 2006. https://doi.org/10.1037/1082-989X.11.1.36
  16. E. L. Merz and S. C. Roesch, "A latent profile analysis of the Five Factor Model of personality: modeling trait interactions," Personality and Individual Differences, Vol. 51, No. 8, pp. 915-919, 2011. https://doi.org/10.1016/j.paid.2011.07.022
  17. E. Ko, S.H. Hong, and J. Cha, "A Study on the Efficiency of Evacuation Guidance and Non-evacuation Guidance in Case of Fire," International Journal of Advanced Culture Technology (IJACT), Vol. 8, No. 1, pp. 243-247, 2020. DOI https://doi.org/10.17703/IJACT.2020.8.1.243