Üniversite Öğrencilerinin Afet Risk Algısının Değerlendirilmesi

Yıl 2023, Cilt: 7 Sayı: 2, 1029 - 1051, 21.10.2023

Galip Usta

https://doi.org/10.30561/sinopusd.1257735

Öz

Risk algısı, kavramsal olarak bilişsel bir olgudur ve esasen bir bilginin işlenmesi olarak düşünülmektedir. Bilginin kavranması ve işlenmesi ise algılamanın bir göstergesidir. Gerçekleştirilen bu çalışma, üniversite öğrencilerinin sıkça zaman geçirdiği kampüs alanlarındaki afet risk algılarının tespit edilmesi amacıyla çok merkezli olarak yapılmıştır. Yapılan bu çalışmada; ölçek alt boyutları olan maruziyet, anksiyete, etki ve yönetilemezlik düzeyleri açısından cinsiyetler arasında istatistiksel olarak anlamlı bir farklılık bulunmamaktadır (p>0,05). Çalışmada; ölçek alt boyutların olan maruziyet, yönetilemezlik ve anksiyete düzeyleri açısından üniversite bölgeleri arasında istatistiksel olarak anlamlı bir farklılık bulunmamaktadır (p>0,05). Etki düzeyleri açısından üniversite bölgeleri arasında istatistiksel olarak anlamlı bir farklılık bulunmaktadır (p<0,05). Marmara bölgesinde üniversite okuyanların etki düzeyleri, Doğu Anadolu bölgesinde üniversite okuyanların etki düzeylerine göre anlamlı derecede düşüktür. Sonuç olarak; kampüs ortamlarında afet kültürünün oluşturulmasına yönelik eylem planları hazırlanmalıdır. Öğrenci katılımlı kampüs afet planları oluşturulmalıdır. Kampüs afet dirençliliğinin artırılmasına ilişkin projelere destek verilmeli ve bu projeler teşvik edilmelidir. Afet eğitimleri düzenlenmeli ve bu eğitimler tatbikatlar ile desteklenmelidir. Eğitim-Öğretime yeni başlayan öğrenciler ile tüm personellere yönelik afet eğitim oryantasyonları düzenlemelidir.

Anahtar Kelimeler

Afet Risk Yönetimi, Kampüs Afet Riski, Üniversite Öğrencileri, Risk

EVALUATION OF UNIVERSITY STUDENTS' PERCEPTION OF DISASTER RISK

Öz

Perception of risk is conceptually a cognitive phenomenon and is essentially thought of as a processing of information. Comprehension and processing of information are indicators of perception. In this study, it was carried out in a multicenter way to determine the disaster risk perceptions in the campus areas where university students often spend time. In this study, there is no statistically significant difference between the genders in terms of the scale's subdimensions of exposure, anxiety, effect and uncontrollable (p>0.05). In the study, there is no statistically significant difference between university regions in terms of exposure, uncontrollable and anxiety levels, which are the sub-dimensions of the scale (p>0.05). There is a statistically significant difference between university regions in terms of effect levels (p<0.05). The level of influence of those studying at the university in the Marmara region is significantly lower than the level of influence of those studying at the university in the Eastern Anatolia region. In conclusion, action plans should be prepared to create a disaster culture in campus environments. Campus disaster plans should be created with student participation. Projects related to increasing campus disaster resilience should be supported and these projects should be encouraged. Disaster trainings should be organized and these trainings should be supported with exercises. Disaster education orientations should be organized for new students and all personnel.

Anahtar Kelimeler

Disaster Risk Management, Campus Disaster Risk, University Students, Risk

Kaynakça

• Ahmad, D., & Afzal, M. (2020). Flood hazards and factors influencing household flood perception and mitigation strategies in Pakistan. Environmental Science and Pollution Research, 27(13), 15375–15387. https://doi.org/10.1007/s11356-020-08057-z
• Aksa, F. I., Utaya, S., Bachri, S., & Handoyo, B. (2020). The role of knowledge and fatalism in college students related to the earthquake-risk perception. Jàmbá: Journal of Disaster Risk Studies, 12(1), 1–6. doi: 10.4102/jamba.v12i1.954
• Alfieri, L., Bisselink, B., Dottori, F., Naumann, G., de Roo, A., Salamon, P., Wyser, K., & Feyen, L. (2017). Global projections of river flood risk in a warmer world. Earth’s Future, 5(2), 171–182. https://doi.org/10.1002/2016ef000485
• Andráško, I., Dolák Klemešová, K., Dolák, L., Trojan, J., & Fiedor, D. (2020). Surely it will come again. Flood threat appraisal, mitigation strategies and protection motivation in Czech communities endangered by floods. Moravian Geographical Reports, 28(3), 170–186. https://doi.org/10.2478/mgr-2020-0013
• Berghuijs, W. R., Aalbers, E. E., Larsen, J. R., Trancoso, R., & Woods, R. A. (2017). Recent changes in extreme floods across multiple continents. Environmental Research Letters, 12(11), 114035. https://doi.org/10.1088/1748-9326/aa8847
• Botzen, W. J. W., Aerts, J. C. J. H., & Van Den Bergh, J. C. J. M. (2009). Dependence of flood risk perceptions on socioeconomic and objective risk factors. Water Resources Research, 45(10), 10440. https://doi.org/10.1029/2009wr007743
• Brilly, M., & Polic, M. (2005). Public perception of flood risks, flood forecasting and mitigation. Natural Hazards and Earth System Sciences, 5(3), 345–355. https://doi.org/10.5194/nhess-5-345-2005
• Chen, Y. F., & Adefila, A. (2020). Enhancing school safety through university engagement in DRR education. International journal of Disaster Risk Reduction, 44, 101386. https://doi.org/10.1016/j.ijdrr.2019.101386
• Cohen, L., Manion, L., & Morrison, K. (2002). Research methods in education. Research Methods in Education. https://doi.org/10.4324/9780203224342
• Creswell, J. W. (2012). Educational research: planning, conducting, and evaluating quantitative and qualitative research. 650.
• Etinay, N., Egbu, C., & Murray, V. (2018). building urban resilience for disaster risk management and disaster risk reduction. Procedia Engineering, 212, 575–582. https://doi.org/10.1016/j.proeng.2018.01.074
• Gao, J., & Sang, Y. (2017). Identification and estimation of landslide-debris flow disaster risk in primary and middle school campuses in a mountainous area of Southwest China. International Journal of Disaster Risk Reduction, 25, 60–71. https://doi.org/10.1016/j.ijdrr.2017.07.012
• Gohram Khan, M., Johar, F., Ndalai Baba, A., & Bahru, J. (2017). Disaster Management Risk Perception of Local Communities. Jurnal Kemanusiaan, 15(1), 87-94. https://jurnalkemanusiaan.utm.my/index.php/kemanusiaan/article/view/120
• Gustafsod, P. E. (1998). Gender differences in risk perception: theoretical and methodological erspectives. Risk Analysis, 18(6), 805–811. https://doi.org/10.1111/j.1539-6924.1998.tb01123.x
• Henstra, D., Minano, A., & Thistlethwaite, J. (2019). Communicating disaster risk? An evaluation of the availability and quality of flood maps. Natural Hazards and Earth System Sciences, 19(1), 313–323. https://doi.org/10.5194/nhess-19-313-2019
• Jakubcová, A., Grežo, H., Hrešková, A., & Petrovič, F. (2016). Impacts of flooding on the quality of life in rural Regions of southern Slovakia. Applied Research in Quality of Life, 11(1), 221–237. https://doi.org/10.1007/s11482-014-9363-x
• Kalaycı, Ş. (2010). SPSS Uygulamalı Çok Değişkenli İstatistik Teknikler. Asil Yayın Dağıtım Ltd. Şti.
• Karasar, N. (2022). Bilimsel Araştırma Yöntemi: Kavramlar İlkeler Teknikler. Nobel Akademik Yayıncılık.
• Lavell, A., & Maskrey, A. (2014). The future of disaster risk management. 13(4), 267–280. https://doi.org/10.1080/17477891.2014.935282
• Li, M., Porter, A. L., & Suominen, A. (2018). Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective. Technological Forecasting and Social Change, 129, 285–296. https://doi.org/10.1016/j.techfore.2017.09.032
• Mallick, J., Salam, R., Amin, R., Islam, A. R. M. T., Islam, A., Siddik, M. N. A., & Alam, G. M. M. (2022). Assessing factors affecting drought, earthquake, and flood risk perception: empirical evidence from Bangladesh. Natural
• Hazards, 112(2), 1633–1656. https://doi.org/10.1007/S11069-022-05242-w
• Mills, M., Mutafoglu, K., Adams, V. M., Archibald, C., Bell, J., & Leon, J. X. (2016). Perceived and projected flood risk and adaptation in coastal Southeast Queensland, Australia. Climatic Change, 136(3–4), 523–537. https://doi.org/10.1007/S10584-016-1644-y
• Mızrak, S., & Aslan, R. (2020). Disaster risk perception of university students. Risk, Hazards & Crisis in Public Policy, 11(4), 411–433. https://doi.org/10.1002/rhc3.12202
• Parker, D. J. (2019). Disaster resilience – a challenged science, 19(1), 1–9. https://doi.org/10.1080/17477891.2019.1694857
• Pazzi, V., Morelli, S., & Bonati, S. (2020). Disaster Risk Perception Knowledge Base-A Consolidated Understanding of Disaster Risk Perception in Social Media and Crowdsourcing. Strengthening links between technologies and society for European disaster resilience, funded by the European Union’s Horizon (No. 883490)
• Peacock, W. G., Brody, S. D., & Highfield, W. (2005). Hurricane risk perceptions among Florida’s single family homeowners. Landscape and Urban Planning, 73(2–3), 120–135. https://doi.org/10.1016/j.landurbplan.2004.11.004
• Rajabi, E., Bazyar, J., Delshad, V., & Khankeh, H. R. (2022). The evolution of disaster risk management: historical approach. Disaster medicine and public health preparedness, 16(4). https://doi.org/10.1017/dmp.2021.194
• Sjöberg, L. (1996). A discussion of the limitations of the psychometric and cultural theory approaches to risk perception. Radiation Protection Dosimetry, 68(3–4), 219–225. https://doi.org/10.1093/oxfordjournals.rpd.a031868
• Slovic, P. (1997). Public perception of risk. Journal of Environmental Health, 59(9), 22–25.
• Slovic, P. (1999). Trust, emotion, sex, politics, and science: Surveying the risk- assessment battlefield. Risk Analysis, 19(4), 689–701. https://doi.org/10.1023/A:1007041821623
• Song, G. (2014). Understanding public perceptions of benefits and risks of childhood vaccinations in the United States. Risk Analysis, 34(3), 541–555. https://doi.org/10.1111/risa.12114
• Tabachnik, B. G., & Fidell, S. L. (2013). Multicollinearity and singularity. Using multivariate statistics. Boston, MA: Pearson.
• Tan, L., Guo, J., Mohanarajah, S., & Zhou, K. (2020). Can we detect trends in natural disaster management with artificial intelligence? A review of modeling practices. Natural Hazards 107(3), 2389–2417. https://doi.org/10.1007/S11069-020-04429-3
• Turner, R., Nigg, J., & Paz, D. (1986). Waiting for disaster: Earthquake watch in California. https://books.google.com/books?hl=en&lr=&id=XpVLHPidZ-QC&oi=fnd&pg=PR7&ots=vAcGKOzDkU&sig=h5N-Bft3Ip-W_EBOjxOuxNRygSk
• UNISDR. (2009). Terminology on disaster risk reduction. Geneva, Switzerland.
• United Nations. (2015). Sendai Framework for Disaster Risk Reduction 2015-2030 | UNDRR. https://www.undrr.org/publication/sendai-framework-disaster-risk-reduction-2015-2030
• United Nations Office for Disaster Risk Reduction (UNDRR). (n.d.). Retrieved 12 January 2023 from https://www.undrr.org/
• Van Niekerk, D., Nemakonde, L.D., Kruger, L. and Forbes-Genade, K. (2018), “Community-based disaster risk management”, in Rodríguez, H., Donner, W. and Trainor, J.E. (Eds), Handbook of Disaster Research, 2nd ed., Springer, Cham, 411-429.
• Vitousek, S., Barnard, P. L., Fletcher, C. H., Frazer, N., Erikson, L., & Storlazzi, C. D. (2017). Doubling of coastal flooding frequency within decades due to sea-level rise. Scientific Reports 2017 7:1, 7(1), 1–9. https://doi.org/10.1038/s41598-017-01362-7
• Wachinger, G., Renn, O., Begg, C., & Kuhlicke, C. (2013). The risk perception paradox—ımplications for governance and communication of natural hazards. Risk Analysis, 33(6), 1049–1065. https://doi.org/10.1111/J.1539-6924.2012.01942.X