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Challenging Assumptions: What Do We Need to Address in Our Disaster Risk Reduction Efforts?

Published online by Cambridge University Press:  31 January 2017

Tudor A. Codreanu ,
Hanh Ngo ,
Andrew Robertson  and
Antonio Celenza
Tudor A. Codreanu*
Affiliation:
West Australian Country Health Services, Busselton Health Campus, Emergency Department, Busselton, Western Australia, Australia Discipline of Emergency Medicine, Faculty of Medicine, Dentistry, and Health Sciences, University of Western Australia, Crawley, Western Australia, Australia
Hanh Ngo
Affiliation:
Discipline of Emergency Medicine, Faculty of Medicine, Dentistry, and Health Sciences, University of Western Australia, Crawley, Western Australia, Australia
Andrew Robertson
Affiliation:
Disaster Management, Regulation, and Planning, Public Health Division, Department of Health, Government of Western Australia, Western Australia, Australia
Antonio Celenza
Affiliation:
Discipline of Emergency Medicine, Faculty of Medicine, Dentistry, and Health Sciences, University of Western Australia, Crawley, Western Australia, Australia
*
Correspondence: Tudor A. Codreanu, MD, MSc(Med), MSc (DisMed) West Australian Country Health Services Busselton Hospital, Emergency Department Locked Bag 3 Busselton 6280, Western Australia E-mail: tudor.codreanu@health.wa.gov.au
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Abstract

Introduction

Specific knowledge and skills are required, especially in the first 72 hours post-disaster, to bridge the time gap until essential services are restored and Emergency Medical Services (EMS) can focus on individuals’ needs. This study explores disaster knowledge and preparedness in the first 72 hours as a function of the individual’s engagement in discussions about disasters, and several other factors (both at personal and community/country level), as well as the entities/organizations perceived by the individual as being responsible for disaster risk reduction (DRR) education.

Methods

A prospective, cross-sectional survey of 3,829 final-year high-school students was conducted in nine countries with different levels of disaster risk and economic development. Regression analyses examined the relationship between a 72-hour disaster preparedness composite outcome (ability to make water safe for drinking, knowledge of water potability, home evacuation skill, and improvising a safe room) and a series of independent predictors.

Results

Respondents from countries with lower economic development were significantly better prepared for the first 72 hours post-disaster than those from developed countries (OR=767.45; CI=13.75-48,822.94; P=.001). While several independent predictors showed a significant main effect, combined disaster risk education (DRE) efforts, as a partnership between school and local government, had the best predictive value (OR=3.52; CI=1.48-8.41; P=.005).

Conclusions

Disaster preparedness in final-year high-school students is significantly better in developing countries. Further improvement requires a convergent effort in aligning the most effective educational policies and actions to best address the individual’s and the community needs.

CodreanuTA, NgoH, RobertsonA, CelenzaA. Challenging Assumptions: What Do We Need to Address in Our Disaster Risk Reduction Efforts?Prehosp Disaster Med. 2017;32(2):134–147.

Keywords

72-hour response preparednessdisastereducationteenagers
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 32 , Issue 2 , April 2017 , pp. 134 - 147
Copyright
© World Association for Disaster and Emergency Medicine 2017 

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Footnotes

Conflicts of interest: none

References

1. UNISDR. Making Development Sustainable: The Future of Disaster Risk Management. Global Assessment Report on Disaster Risk Reduction. Geneva, Switzerland: United Nations Office for Disaster Risk Reduction (UNISDR); 2015. http://www.preventionweb.net/english/hyogo/gar/2015/en/gar-pdf/GAR2015_EN.pdf. Accessed February 4, 2016.Google Scholar
2. UNISDR. Sendai Framework for Disaster Risk Reduction 2015 - 2030. Geneva, Switzerland: (UNISDR) UN for DRR; 2015. http://www.unisdr.org/files/43291_ sendaiframeworkfordrren.pdf. Accessed February 4, 2016.Google Scholar
3. UNISDR. Sustainable Developments Goals. Geneva, Switzerland: (UNISDR) UN for DRR; 2015. http://www.un.org/sustainabledevelopment/sustainable-development-goals/. Accessed February 4, 2016.Google Scholar
4. UNFCCC. Conference of the Parties of the United Nations Framework Convention on Climate Change. Geneva, Switzerland: Change UNF CoC; 2015. http://unfccc.int/files/ home/application/pdf/paris_agreement.pdf. Accessed February 4, 2016.Google Scholar
5. UNISDR. The Pocket GAR 2015. Making Development Sustainable: The Future of Disaster Risk Management. Geneva, Switzerland; 2015. http://www.preventionweb.net/ english/hyogo/gar/2015/en/gar-pdf/GAR15_Pocket_EN.pdf?bcsi_scan_c221d61a0ea4ff4c =0&bcsi_scan_filename=GAR15_Pocket_EN.pdf. Accessed May 3, 2016.Google Scholar
6. UNISDR. Hyogo Framework for Action (HFA) Monitor. Geneva, Switzerland; 2013-2015. www.preventionweb.net/english/hyogo/hfa-monitoring/national/?pid:73&pih:2. Accessed February 4, 2016.Google Scholar
7. Codreanu, TA, Celenza, A, Alabdulkarim, AAR. Factors associated with discussion of disasters by final year high school students: an international cross-sectional survey. Prehosp Disaster Med. 2015;30(4):365-373.Google Scholar
8. Codreanu, T, Celenza, A, Ngo, H. Disaster risk education of final year high school students requires a partnership with families and charity organizations: an international cross-sectional survey. Prehosp Disaster Med. 2016;31(3):242-254.CrossRefGoogle ScholarPubMed
9. Goepel, K. International Symposium on the Analytic Hierarchy Process Kuala Lumpur, Indonesia. Kuala Lumpur, Indonesia; 2013. http://bpmsg.com/wordpress/wp-content/uploads/2013/06/ISAHP_2013-13.03.13.Goepel.pdf. Accessed January 19, 2016.Google Scholar
10. Goepel, K. BPMSG AHP Excel template with multiple inputs. Singapore; 2013. http://bpmsg.com/new-ahp-excel-template-with-multiple-inputs/. Accessed January 19, 2016.Google Scholar
11. Goepel, K. PPMSG’s AHP online system. Rational decision making made easy. Singapore; 2014 [updated 14.05.2014]. http://bpmsg.com/academic/ahp.php. Accessed January 19, 2016.Google Scholar
12. Abdulghani, H, Ponnamperuma, G, Amin, Z. An Essential Guide to Developing, Implementing, and Evaluating Objective Structured Clinical Examination (OSCE). Singapore: World Scientific Publishing Co Pte Ltd; 2015: 224.Google Scholar
13. Federal Emergency Management Agency (FEMA). Build a kit. Washington, DS USA: FEMA; 2013. http://www.ready.gov/build-a-kit. Accessed November 12, 2013.Google Scholar
14. Tabachnick, B, Fidell, L. Using Multivariate Statistics. 6th edition. Boston, Massachusetts USA: Pearson Allyn & Beacon; 2013.Google Scholar
15. Cohen, J. Statistical Power Analysis for the Behavioral Sciences. 2nd edition. Hillsdale, New Jersey USA: Erlbaum; 1988.Google Scholar
16. Futamura, M, Hobson, C, Turner, N. Natural disasters and human security 2011. http://unu.edu/publications/articles/natural-disasters-and-human-security.html. Accessed January 19, 2016.Google Scholar
17. Enarson, E, Chakrabarti, P. Women, Gender, and Disaster: Global Issues and Initiatives. New Delhi, India: Sage Publishers; 2009: 379.Google Scholar
18. Morrow, B, Enarson, E. Hurricane Andrew through women’s eyes: issues and recommendations. Int J Mass Emerg Disasters. 1996;14(1):5-22.Google Scholar
19. Bottomley, PA, Doyle, JR. A comparison of three weight elicitation methods: good, better, and best. Omega. 2001;29(6):553-560.Google Scholar
20. von Nitzsch, R, Weber, M. The effect of attribute ranges on weights in multi-attribute utility measurement. Management Science. 1993;39(8):937-943.CrossRefGoogle Scholar
21. Fischer, G. Range sensitivity of attribute weights in multi-attribute value models. Organ Behav Hum Decis Process. 1995;62(3):252-266.Google Scholar
22. Goldstein, W, Einhorn, H. Expression theory and the preference reversal phenomenon. Psychol Rev. 1987;94:236-254.Google Scholar
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