Kids Alive! Support for Children of Parents with Cancer: An Exemplar Program for Children of Parents with Cancer

Cancer in a parent or caregiver is an event that affects the whole family. The roles and responsibilities of the diagnosed parent, as well as those of each family member, are affected at the time of diagnosis and throughout the progression of the illness. According to the American Cancer Society, there will be an estimated 1,665,540 new cancer cases diagnosed and 585,720 cancer deaths in 2014. This staggering statistic means there are a number of cancer diagnoses that will directly affect thousands of parents and their children. Past research suggests this upheaval in the system is particularly stressful on children and can lead to a number of responses including anxiety, depression, distress, and other negative reactions. Despite the large number of parents and caregivers diagnosed with cancer in the United States each year, there are relatively few support groups aimed at supporting children affected by parental cancer. Support groups provide opportunities to serve this population in a number of advantageous ways by providing safety, support, and a sense of community. Additionally, support groups allow this population of young people to express their fears and worries, connect to others going through similar circumstances, and explore their parent's diagnosis in a context that is helpful and developmentally appropriate. Past research has found that children who do not receive support during this life-changing event can be negatively affected throughout the life span. On the other hand, this event can be a time to build a child's resilience and provide the structure through which they may thrive in adversity. Support groups offer the opportunity to address this difficult event and lead to positive results. Kids Alive! is one such group that has been proactive in support for children of parents diagnosed with cancer since 1995. Kids Alive!, a support group that runs out of Porter Hospital in Denver Colorado, uses Joseph Campbell's Hero's Journey to structure monthly groups. The Hero's Journey, described in Campbell's The Hero with a Thousand Faces (1949), focuses on a set pattern that all heroes must go through during their journey towards an ultimate victory and self-discovery. Kids Alive! incorporates this journey into a curriculum aimed at helping children explore their thoughts and feelings around their parent's cancer and leads to a realization that they are not alone on this journey. Over the course of eight months, children in Kids Alive! receive support and solidarity that leads to life-changing experiences and an understanding of what a diagnosis of cancer in a parent can mean. Kids Alive! consists of professionals and volunteers who take time to recognize and support this underserved population. The program has led to positive outcomes for nearly two decades and consistently increases the numbers of children and families served. The purpose of this paper is to describe the Kids Alive! program as an exemplar program that addresses these problems by utilizing protective factors research has found in this population. Further, this paper will discuss areas of future research while providing the model of an effective program aimed at serving an important population. Additionally, the model of Kids Alive! will be described through this paper in a way that allows for other oncology settings to consider this relatively simple program that provides consistently positive results.

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.