**5. Conclusions and discussions**

The objective of this project lies in two folds: one is to undertake a comprehensive systematic analysis of the scientific literature on coastal hazards to identify the factors contributing to hazard vulnerability, the other is to explore the utility of meta-analysis method in the research of vulnerability. Therefore, based on the eight East and Southeast Asia countries, a meta-analysis methodology is applied, including the development of a system for coding information, statistical characterization, and the synthesis of key findings.

Reviewing the historical routine it could be seen that in mid 1990s to early 2000s, the qualitative meta-analysis got a booming development. In that period, from the very beginning of application in nursing research(Beecher 1955) and psychology research(Glass 1976), these methods have been employed in many research areas. In fact the quantitative meta-analysis also progressed and even developed into a relative complete system with key parameters measuring the quality of analysis. By examining the dynamics that go beyond individual studies, in this meta-analysis we are aiming to extrapolate from lessons learnt (from the case studies and previous works), and to contribute to the body of knowledge about the driving forces and dynamics of the vulnerability to natural hazards. During the process of meta-analysis, technique issues are also addressed.

### **5.1 Sample size of the collected literature**

The decision of how many studies should be included in a meta-analysis is always a hot spot of argument. Some researchers think that the inclusion of all studies, following an exhaustive literature search, could help to prevent the exclusion of important information or views, and thus strengthens the findings because they are generated from a broader base(Sherwood 1999; Jones 2004). On the other hand, some argue that in any kind of qualitative research, overly large sample sizes tended to impede deep analysis and threaten the interpretive validity of findings(Sandelowski, Docherty et al. 1997). Also Paterson et al.

• There is a clear gap between conceptual and theoretical work and empirically based case studies where deployment of or even reference to particular conceptual

• Second, partly as a result of the existing gap, there seems no clear pattern or causal structure emerging from the reviewed researches, with all the factors interwoven in a complicated way. Interpretations of how these factors interact to produce social vulnerability to coastal hazards in different environmental, historical, and social

• Third and most importantly, there are mismatches between causal factors of social vulnerability and the recommendations for its reduction and management. With most of the recommendations do not target the underlying factors but rather focusing on

This work highlights the urgent need for a multi-scaled and multi-disciplined research approach that addresses the gaps between field-based case studies, larger-scale vulnerability assessments, conceptual frameworks and theory, and the implications for policy and

The objective of this project lies in two folds: one is to undertake a comprehensive systematic analysis of the scientific literature on coastal hazards to identify the factors contributing to hazard vulnerability, the other is to explore the utility of meta-analysis method in the research of vulnerability. Therefore, based on the eight East and Southeast Asia countries, a meta-analysis methodology is applied, including the development of a system for coding information, statistical characterization, and the synthesis of key findings. Reviewing the historical routine it could be seen that in mid 1990s to early 2000s, the qualitative meta-analysis got a booming development. In that period, from the very beginning of application in nursing research(Beecher 1955) and psychology research(Glass 1976), these methods have been employed in many research areas. In fact the quantitative meta-analysis also progressed and even developed into a relative complete system with key parameters measuring the quality of analysis. By examining the dynamics that go beyond individual studies, in this meta-analysis we are aiming to extrapolate from lessons learnt (from the case studies and previous works), and to contribute to the body of knowledge about the driving forces and dynamics of the vulnerability to natural hazards. During the

The decision of how many studies should be included in a meta-analysis is always a hot spot of argument. Some researchers think that the inclusion of all studies, following an exhaustive literature search, could help to prevent the exclusion of important information or views, and thus strengthens the findings because they are generated from a broader base(Sherwood 1999; Jones 2004). On the other hand, some argue that in any kind of qualitative research, overly large sample sizes tended to impede deep analysis and threaten the interpretive validity of findings(Sandelowski, Docherty et al. 1997). Also Paterson et al.

frameworks are rare.

short-term relief.

**5. Conclusions and discussions** 

process of meta-analysis, technique issues are also addressed.

**5.1 Sample size of the collected literature** 

practice.

contexts are still largely idiosyncratic.

(2001) suggest that working with more than 100 studies may be "overly ambitious", and recommend focusing the research question more tightly(Paterson, Thorne et al. 2001).

The field of Sandelowski's study was health and nursing, in which there were relatively fewer uncertainties and the topics mainly focused on the effectiveness of certain remedies, the environment around the illness and the impacts of some external factors to the therapies. For more complex issues that involve many uncertainties, more studies are required in order to ensure a complete and comprehensive analysis.

Furthermore, if a "purposive sampling or saturation techniques" brought out by Booth (2001) is employed in a meta-analysis(Booth 2001), a criteria would be set up even implicitly. Then a bias in sampling would be inevitable. Although every meta-analysis has some inherent bias by virtue of the inclusion/exclusion criteria and the methods chosen to review the literature(Rosenthal and DiMatteo 2001), in this study the bias is minimized as possible.

Based on the above consideration, for the process of sampling, the method of (Suri 1999) was applied. According to this method, the search for additional literature can be terminated once the stage of data-redundancy is reached where every additional case included in the synthesis is likely to tell the same story rather than provide a new perspective. Preliminary content analysis was used to determine redundancy.
