Reducing Stigma toward Sexual Minorities: Acceptance-Based versus Traditional Safe Zone Training.

Homophobia continues to exist in society. Homonegative attitudes are often implicit and can be acquired without direct training, which makes them particularly resistant to change. Relational Frame Theory (RFT) is a behavior analytic account of learning processes and can explain these processes of indirect learning. RFT also suggests therapeutic processes for dismantling stigma using a therapy model named Acceptance and Commitment Therapy (ACT). This paper reviews previous research on traditional multicultural training, and addresses its shortcomings. Specifically, this paper makes the argument that traditional models encourage experiential avoidance and thus further perpetuate the processes that maintain stigma. While a handful of studies have examined stigma interventions using ACT, no ACT studies have been completed specifically on the stigma towards gay and lesbian individuals. This paper concludes with a research proposal for such a study.

Everyone Has Their Scars: Meaning Making In a Burn Survivor Support Group.

In the Burn Care literature, there is little on the lived experiences of burn support group members, the perceived benefits of burn support groups for the members, and even less on the meaning the survivors make of the support they receive. In order to provide effective services and to meet the psychosocial needs of burn survivors, it is important to understand the influence a support group has on its members as well as the personal experiences of those individuals who attend these groups. The purpose of this study was to explore the meaning that burn survivors make in a burn survivor support group. A non-random, purposeful convenience sample of six self-identified burn survivors was interviewed using a guided in-depth interview technique to explore their experiences in the support group. Key informant interviews and group observations served to triangulate the data collected in the individual interviews. The experiences of the group's members coalesced around five main themes: acceptance of self, perspective change, value of community, reciprocity, and structural meaning making components. The findings demonstrated the overall positive impact the support group had on psychosocial recovery. Additionally, analysis suggested that the meaning making process experience included Post Traumatic Growth and highlighted the importance of community in psychosocial recovery. Burn survivors reported unique growth opportunities that allowed them to integrate their injury into their identity within an encouraging and safe environment. Certain factors, such as improving group attendance, were addressed and both survivors and support staff generated suggestions for reaching others in need of support.

Fail-Safe Testing of Web Applications

This dissertation introduces an approach to generate tests to test fail-safe behavior for web applications. We apply the approach to a commercial web application. We build models for both behavioral and mitigation requirements. We create mitigation tests from an existing functional black box test suite by determining failure type and points of failure in the test suite and weaving required mitigation based on weaving rules to generate a test suite that tests proper mitigation of failures. A genetic algorithm (GA) is used to determine points of failure and type of failure that needs to be tested. Mitigation test paths are woven into the behavioral test at the point of failure based on failure specific weaving rules. A simulator was developed to evaluate choice of parameters for the genetic algorithm. We showed how to tune the fitness function and performed tuning experiments for GA to determine what values to use for exploration weight and prospecting weight. We found that higher defect densities make prospecting and mining more successful, while lower mitigation defect densities need more exploration. We compare efficiency and effectiveness of the approach. First, the GA approach is compared to random selection. The results show that the GA performance was better than random selection and that the approach was robust when the search space increased. Second, we compare the GA against four coverage criteria. The results of comparison show that test requirements generated by a genetic algorithm (GA) are more efficient than three of the four coverage criteria for large search spaces. They are equally effective. For small search spaces, the genetic algorithm is less effective than three of the four coverage criteria. The fourth coverage criteria is too weak and unable to find all defects in almost all cases. We also present a large case study of a mortgage system at one of our industrial partners and show how we formalize the approach. We evaluate the use of a GA to create test requirements. The evaluation includes choice of initial population, multiplicity of runs and a discussion of the cost of evaluating fitness. Finally, we build a selective regression testing approach based on types of changes (add, delete, or modify) that could occur in the behavioral model, the fault model, the mitigation models, the weaving rules, and the state-event matrix. We provide a systematic method by showing the formalization steps for each type of change to the various models.