DASS42 report: Caradeux Camp, Port au Prince, Haiti.

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1 DASS42 report: Caradeux Camp, Port au Prince, Haiti. Potangaroa R, Martinez A. UNITEC, New Zealand Abstract The involvement and understanding of communities is at the heart of a resilient humanitarian approach in post disaster reconstruction. This paper describes the outcomes from the second of two ethnographically based surveys of residents from Caradeux camp in Port au Prince, Haiti to understand who were most affected by the earthquake disaster that occurred on January A quality of life survey called a DASS42 survey was completed at Caradeux Camp by the IFRC camp socialization team. In all 108 surveys were completed with 18 later being filtered out based on an extremely severe check developed by one of the authors. The final number consisted of 61 female and 29 male respondents, 90 in total. This data was analysed using an EXCEL spreadsheet and characterized based on the DASS42 severity table and conclusions and implications for recovery shelter programnes proposed. Both papers touch on the key issue of when is enough, enough? And the need for operational necessity against information rigour. Keywords: Quality of Life, survey, recovery shelter

2 1. Introduction Needs assessment and community participation are critically linked to effective targeting of relief and recovery assistance. Target populations must be identified on the basis of actual need, and beneficiary consultation and participation is essential for effective targeting. 1 Thus, the involvement and understanding of communities seems to be at the heart of any humanitarian approach but is it at the heart of a resilient response? Resilience has many meanings in post disaster reconstruction. The resilience approach identifies the resources and adaptive capacity that a community can utilise to overcome the problems that may result from change. The approach builds upon the inherent capacities of a community, rather than only relying on external interventions to overcome vulnerabilities. 2 And appears to have at least 3 characteristics as follows: A buffer capacity: the community is able to absorb a disaster (Adger, 2000) A bounce back capacity: the community is able to quickly return to its original state.(folke, 2006) An adaptive capacity: the community returns to a better state than prior to the disaster (Maguire and Hagan, 2007). All 3 aspects involve a response from communities and the conclusion as stated by Lyons et is that In short, participation is essential when defining needs, converging vested interests, getting accurate information on the ground, mobilizing resources and positioning problems accurately all key to effective design and planning. 3 Hence, people need to be at the centre of relief and recovery assistance but how is that to be achieved? This paper examines the use of the DASS42 Quality of Life (QoL) tool in Caradeux Camp to understand how such a tool involves a community and addresses this perceived need people "centreness" for design and planning. 1 Building Resilient Communities: Risk Management and Response to Natural Disasters through Social Funds and Community-Driven Development Operations The World Bank 2008 pg 88 2 Assessing a community s capacity to manage change: A resilience approach to social assessment Brigit Maguire and Sophie Cartwright May 2008 pg i 3 Building Back Better Delivering people-centred housing reconstruction at scale Edited by Michal Lyons and Theo Schilderman with Camillo Boano; Practical Action Pub pg x.

3 2. What is the DASS42 and what does it measure? The DASS42 measures Quality of Life (QoL) and is administered as a 42 question survey. It was developed at the University of New South Wales, in Sydney Australia for use by non professionals (Lovibond, 1995). It is a set of three self-report scales designed to measure the negative emotional states of depression, anxiety and stress and was constructed not merely as another set of scales to measure conventionally defined emotional states, but to further the process of defining, understanding, and measuring the ubiquitous and clinically significant emotional states usually described as depression, anxiety and stress (DASS, 2006). Thus, it is meant for the common condition of people rather than any acute clinical condition and perhaps more importantly was intended for use by non psychiatric professionals. The characteristics of high scorers on each DASS scale are as follows: Depression scale: self-disparaging, dispirited, gloomy, blue, convinced that life has no meaning or value, pessimistic about the future, unable to experience enjoyment or satisfaction, unable to become interested or involved, slow, lacking in initiative. Anxiety scale: apprehensive, panicky, tremble, shaky, aware of dryness of the mouth, breathing difficulties, pounding of the heart, sweatiness of the palms, worried about performance and possible loss of control. Stress scale: over-aroused, tense, unable to relax, touchy, easily upset, irritable, easily startled, nervy, jumpy, fidgety, and intolerant of interruption or delay. 3. The severity table The useful aspect of the DASS42 over other QoL tools is it s severity table (refer to table 1 below). This table allows characterization of responses without the need for a before and after survey or necessarily a control group as it commonly required. This allows operational application from first surveys which makes the DASS42 a useful survey tool for disaster/emergency related work. The severity table can also be used for comparisons within a data set and in this pilot it was gender and age. Other categories relevant to the programme could have been selected and used. In addition, comparisons between seeming different programmes could be done, say between the impact of a wash programne and a shelter programme in different locations within the disaster affected zone. Table 1: The DASS42 Severity Index Table (Devilly, 2005). Depression Anxiety Stress Normal Mild Moderate Severe Extremely Severe

4 4. The role of QoL surveys There are two approaches that QoL tools can be applied in post disaster situations. The first is to show a change in the QoL of beneficiaries after some intervention such as shelter though as indicated earlier it could be any intervention. The second way is to connect it to another data base and by indicating those with low QoL provide the basis for review of the database to ascertain answers and hence directions for programmes to address or correct. The DASS42 is one of 38 such Quality of Life tools.(sharpe et al, 2005) and the usefulness of such tools are to provide an approximate measure of the right things is more meaningful than an exact measure of the wrong things as stated by Malcolm (2006) and supported by others (Hallam, 1998). Polletti perhaps puts it best with the comment that such approaches aims for better (as opposed to perfect) information with which to make a case for plausible (as opposed to proven) associations (Polletti, 2004).Thus, the use of the DASS42 (or any QoL tool) is not to show absolute quantitative differences but rather to select the those with lower QoL within the beneficiary population and hence the second approach above. However, much of this academic research is written from a non operational basis but where that operational basis exists than the first approach above becomes practical if not desirable. The only issue is how long after the intervention should the survey take place? Experience suggests that for shelter after one week but preferably before 1 month after the intervention so that the effect of the shelter intervention is still relevant. 5. Disaster models The most commonly used disaster model is the 4R model which can also come in a 3R and a 5R form (MCDEM, 2004). The R s represent the different disaster phases such as Reduction, Readiness, Response and Recovery with a sometimes a 5 th R for Reconstruction. It is a linear model with one phase linking into the next but is often depicted as a circle linking back on itself or as a spiral suggesting a new reduced vulnerability for future disasters. However, operational staff and especially those field workers dealing with affected families find such a model limiting and other models such as the Disaster Life Continuum are more widely understood if not used (EMA, 2003). In such a model, decisions and planning prior to the disaster was made in the context of the family and the community and society that support the family as shown in figure 1a. When the disaster occurs, the community and social context together with the family context is shattered as shown in figure 1b. Consequently, those affected experience two general forms of reaction usually depression (related to a preoccupation and fixation of how things were before the disaster) followed by anxiety and despair about the future. These states link into the DASS42 with the stress being the contextual measure as shown in figure 1c. What is interesting about this is that people cannot be in an extremely severe state of anxiety and depression (as defined by the severity table above) at the same time and this is the basis for the filtering of

5 data mentioned earlier. Interestingly, the time to move from this depressed state to an anxious one is a direct measure of the resilience of people. In terms of shelter programmes, emergency shelter is provided during this state of depression but recovery t shelters should not start till those affected have moved to the anxious condition and at that point are looking to resolve what is ahead. Invariably, people are ready for such shelter much faster than it can be provided operationally. Figure 1a Figure 1b Depression Stress Anxiety

6 working in the field the DASS42 quantifies it with females being one severity level higher for all 3 of the DASS42 scales. Other DASS42 surveys in Indonesia (12 locations), India (6 locations), Sri Lanka (3 locations), Pakistan (6 locations) had similar results with some of those results being years after the disaster. Samoa (4 locations) was the only post disaster survey were males appeared to be more affected than females but after 9 months this difference had all but disappeared. Table 2: DASS42 Overall Results Females (61) Males (29) Depression 15.7 Moderate 12.6 Mild Anxiety 16.3 Severe 14.0 Moderate Stress 14.9 Mild 13.6 Normal In terms of age it is clear that those over 50 years of age are significantly more affected than other age groups as shown in table 3 below. They are typically one severity level above other age groups. Note that children (those under 18 years) were not surveyed though the DASS42 can be used for 12 years olds. Thus, the situation for children remains as a special case. Nonetheless, the results do appear to stand for age groups above 18 years. Table 3: DASS42 Results for Age. Age (in years) Number Depression Anxiety Stress Less than Mild 11.9 Moderate 11.2 Normal 30 to Normal 10.1 Moderate 9.3 Normal 40 to Mild 11.5 Moderate 10.7 Normal Moderate 18.0 Severe 17.3 Mild TOTAL = Recommendations for further consideration What does this mean for a shelter programme? The results suggest the following considerations: 1) Priority should be given to female head of households and to households with family members 50 years or over. The 5o years is not a definitive age and perhaps those in the 45 years and above should be included. 2) It would appear that those affected are concerned about the future and consequently shelter response need to demonstrate how they can address future issues and consequently be more enabling and adaptive and in the long term sustainable. For example, how can the t shelter be extended for family or be modified for a business. Training is becoming another possibility with local providers available to link into

7 professional level 1, 2 or 3 qualifications. This is an invitation for innovative solutions beyond solely the provision of a shelter. 3) Use the impact on females (rather than males) to measure the effectiveness of a shelter programme. Moreover, the DASS42 would/could feed directly into any Logframe considerations for monitoring and evaluation (in real time) of shelter provision. 4) The present results are based on 90 surveys and it would be beneficial to the programme to increase the coverage and also consider what other aspects of the programme are core to achievement of a successful shelter programme. The DASS42 survey is a particularly useful tool for targeting shelter programs in disasters and emergency situations involving large populations. The use of the severity table, the Disaster Life Continuum Model and its ability to provide practical results based on one survey without the need for a before and after study make it a functional tool. Architects and engineers accustomed to the quantitative aspects of building should consider the need to quantitatively measure qualitative aspects of their projects. The difference between the quantitative and qualitative is the difference between a house and a home. And while building shelter programs work to produce the first, it is the second that people desire. References Adger W N (2000) Social and ecological resilience: are they related? Progress in Human Geography, 24: DASS (2006) Depression Anxiety Stress Scales (DASS) Psychology Foundation of Australia Devilly G (2005) Depression Anxiety Stress Scale 42 (DASS 42) Lovibond & Lovibond (1995). Viewed 26 April Emergency Management Australia (EMA) (2003). Recovery Management: Context of Recovery; EMA Institute, Mt Macedon August 2003 pp51 Folke C (2006) Resilience: the emergence of a perspective for social-ecological systems analyses. Global Environmental Change, 16: Hallam A (1998) Evaluating Humanitarian Assistance Programmes in Complex Emergencies. Relief and Rehabilitation Network September 1998 pp 13 of pp128 Lovibond S. Lovibond, P (1995). Manual for the Depression Anxiety Stress Scales. (2nd. Ed.) Sydney: Psychology Foundation.

8 Maguire B & Hagan P (2007) Disasters and communities: understanding social resilience. The Australian Journal of Emergency Management, 22: Malcolm M-J (2006) Ripples in the pond: assessing the impact of a growing Not for Profit management programme in NZ and the Pacific. Unitec NZ Graduate Diploma in Not for Profit Management 2006 conference. Ministry of Civil Defence Emergency Management (MCDEM) (2004). National CDEM Strategy pub. by the NZ Govt pp14-16 Polletti T (2004) Inter-Agency Health Evaluations in Humanitarian Crises. A Background Issues Paper. London School of Hygiene and Tropical Medicine March 2004 pp41 of 57. Sharpe A, Smith J (2005). Measuring the Impact of Research on Well-being: A Survey of Indicators of Well-being. Centre for the Study of Living Standards CSLS Research Report Number February, 2005 pp 119