Following exposure to trauma, stress reactions are initially adaptive. However, some individuals’ psychological response can become maladaptive with long-lasting impairment to functioning. Most people with initial symptoms of stress recover, and thus it is important to distinguish individuals who are at risk of continuing difficulties so that resources are allocated appropriately. Investigations of predictors of PTSD development have largely focused on relational and combat-related trauma, with very limited research looking at natural disasters. This study assessed the nature and severity of psychological difficulties experienced in 101 people seeking treatment following exposure to a significant earthquake that killed 185 people. Peritraumatic dissociation, posttraumatic stress symptoms, symptoms of anxiety, symptoms of depression, and social isolation were assessed. Descriptive analyses revealed the sample to be a highly impaired group, with particularly high levels of posttraumatic stress symptoms. Path analysis was used to determine whether the experience of some psychological difficulties predicted experience of others. As hypothesised, peritraumatic dissociation was found to predict posttraumatic stress symptoms and symptoms of anxiety. Posttraumatic stress symptoms then predicted symptoms of anxiety and symptoms of depression. Depression and anxiety were highly correlated. Contrary to expectations, social isolation was not significantly related to any other psychological variables. These findings justify the provision of psychological support following a natural disaster and suggest the benefit of assessing peritraumatic dissociation and posttraumatic stress symptoms soon after the event to identify people in need of monitoring and intervention.
INTRODUCTION: There is little research on the role of creative arts and craft in disaster recovery. This article reports findings about the emergent role of crafting from research conducted after the 2010–2011 series of earthquakes in Christchurch and surrounding districts in Aotearoa New Zealand. In particular, the article focuses on the significance and differing interpretations of the notion of place expressed by participants through their craftwork, in this case led by women and mediated by the post-earthquake geographic and temporal context. METHOD: This qualitative research included nine individual interviews and five focus group interviews with crafters from Christchurch and surrounding districts. There were 35 participants in total, 33 were women. Applied thematic analysis was used to code the data and identify themes. These themes included connection to place, the symbolism of craft, the healing experience of craft groups and places for women. The notion of place was evident across all three themes. FINDINGS: The findings from the research demonstrate differing ways in which the significance of place was reflected in the craftwork. Participants interpreted the concept of place in descriptive, symbolic, and therapeutic ways. IMPLICATIONS: More understanding about the way creative endeavours like crafting can be used to help ameliorate the impact of natural disasters is needed. Social work practitioners are encouraged to explore place-based wellbeing during their work with service users and to include aspects of artistry, craft and creativity.
When disasters and crises, both man-made and natural, occur, resilient higher education institutions adapt in order to continue teaching and research. This may necessitate the closure of the whole institution, a building and/or other essential infrastructure. In disasters of large scale the impact can be felt for many years. There is an increasing recognition of the need for disaster planning to restructure educational institutions so that they become more resilient to challenges including natural disasters (Seville, Hawker, & Lyttle, 2012).The University of Canterbury (UC) was affected by seismic events that resulted in the closure of the University in September 2010 for 10 days and two weeks at the start of the 2011 academic year This case study research describes ways in which e-learning was deployed and developed by the University to continue and even to improve learning and teaching in the aftermath of a series of earthquakes in 2010 and 2011. A qualitative intrinsic embedded/nested single case study design was chosen for the study. The population was the management, support staff and educators at the University of Canterbury. Participants were recruited with purposive sampling using a snowball strategy where the early key participants were encouraged to recommend further participants. Four sources of data were identified: (1) documents such as policy, reports and guidelines; (2) emails from leaders of the colleges and academics; (3) communications from senior management team posted on the university website during and after the seismic activity of 2010 and 2011; and (4) semi-structured interviews of academics, support staff and members of senior management team. A series of inductive descriptive content analyses identified a number of themes in the data. The Technology Acceptance Model 2 (Venkatesh & Davis, 2000) and the Indicator of Resilience Model (Resilient Organisations, 2012) were used for additional analyses of each of the three cases. Within the University case, the cases of two contrasting Colleges were embedded to produce a total of three case studies describing e-learning from 2000 - 2014. One contrast was the extent of e-learning deployment at the colleges: The College of Education was a leader in the field, while the College of Business and Law had relatively little e-learning at the time of the first earthquake in September 2010. The following six themes emerged from the analyses: Communication about crises, IT infrastructure, Availability of e-learning technologies, Support in the use of e-learning technologies, Timing of crises in academic year and Strategic planning for e-learning. One of the findings confirmed earlier research that communication to members of an organisation and the general public about crises and the recovery from crises is important. The use of communication channels, which students were familiar with and already using, aided the dissemination of the information that UC would be using e-learning as one of the options to complete the academic year. It was also found that e-learning tools were invaluable during the crises and facilitated teaching and learning whilst freeing limited campus space for essential activities and that IT infrastructure was essential to e-learning. The range of e-learning tools and their deployment evolved over the years influenced by repeated crises and facilitated by the availability of centrally located support from the e-Learning support team for a limited set of tools, as well as more localised support and collaboration with colleagues. Furthermore, the reasons and/or rate of e-learning adoption in an educational institution during crises varied with the time of the academic year and the needs of the institution at the time. The duration of the crises also affected the adoption of e-learning. Finally, UC’s lack of an explicit e-learning strategy influenced the two colleges to develop college-specific e-learning plans and those College plans complemented the incorporation of e-learning for the first time in the University’s teaching and learning strategy in 2013. Twelve out of the 13 indicators of the Indicators of Resilience Model were found in the data collected for the study and could be explained using the model; it revealed that UC has become more resilient with e-learning in the aftermath of the seismic activities in 2010 and 2011. The interpretation of the results using TAM2 demonstrated that the adoption of technologies during crises aided in overcoming barriers to learning at the time of the crisis. The recommendations from this study are that in times of crises, educational institutions take advantage of Cloud computing to communicate with members of the institution and stakeholders. Also, that the architecture of a university’s IT infrastructure be made more resilient by increasing redundancy, backup and security, centralisation and Cloud computing. In addition, when under stress it is recommended that new tools are only introduced when they are essential.
