Disaster Management: Enabling Resilience

Abstract

The current "resilience gap" is how it can be enabled in reality from its apparent idealistic grounding? This chapter accepts that a first step should be the establishment of a suitable metric for resilience measurement. It then describes the theoretical construct for using Quality of Life Models and develops one particular model, namely the DASS42. It does this with 7 case studies that cover a decade of work in various post disaster situations. The case studies seek to highlight the operational contexts and issues encountered to reach this "reality" of enabling resilience; and the lessons learnt trying.

Psychometric evaluation of disaster impact

“…For example, the Afghanistan data reveal no consistent relationship between age and quality of life after the disaster. Contrary to the findings of past research on other communities, older respondents did not report consistently higher levels of depression, anxiety or stress, with the exception of a single outlier in the Herat region (Phifer and Norris, 1989; Phifer, 1990; Potangaroa et al , 2015). Even though Afghanistan has been regularly censured by international organisations as one of the least hospitable countries in the world for the elderly, age was a poor predictor of the quality of life impact of the flooding (HelpAge International, 2015).…”

“…Potangaroa et al (2015) in particular have made use of the DASS in a disaster context in Pakistan, China, Haiti, Christchurch, the Philippines and Indonesia. They successfully focussed on using the DASS-42 as a tool for identifying which demographics were the most affected by disasters and evaluating the outcome of aid programmes.…”

“…It is robust and designed to be administrable by non-professional staff (Lovibond and Lovibond, 1996). It can be effectively conducted in approximately 15 min by a practiced administrator (Potangaroa et al , 2015).…”

“…The DASS-42 indirectly measures depression (sad, "empty" affect, accompanied by somatic and cognitive changes leading to loss of function), anxiety (apprehension, worries about loss of control or ability) and stress (overarousal, characterised by touchiness, irritability or jumpiness), via the frequency with which respondents experience physical and psychological phenomena. The DASS was used because it has been used to measure psychological well-being in a variety of contexts, including past disasters as a resilience indicator (Antony et al, 1998;Mujeeb and Zubair, 2012;American Psychiatric Association, 2013;Santosa et al, 2014;Potangaroa et al, 2015;Aslam and Kamal, 2016). Potangaroa et al (2015) in particular have made use of the DASS in a disaster context in Pakistan, China, Haiti, Christchurch, the Philippines and Indonesia.…”

“…The DASS was used because it has been used to measure psychological well-being in a variety of contexts, including past disasters as a resilience indicator (Antony et al, 1998;Mujeeb and Zubair, 2012;American Psychiatric Association, 2013;Santosa et al, 2014;Potangaroa et al, 2015;Aslam and Kamal, 2016). Potangaroa et al (2015) in particular have made use of the DASS in a disaster context in Pakistan, China, Haiti, Christchurch, the Philippines and Indonesia. They successfully focussed on using the DASS-42 as a tool for identifying which demographics were the most affected by disasters and evaluating the outcome of aid programmes.…”