RECENT developments in the treatment of cancer have produced significant changes in the natural history of childhood malignancies. With increasing numbers of pediatric patients surviving cancer, it is important to identify factors which contribute to the long-term psychological adjustment of these children. In the past, the role of the clinician treating a child with cancer was limited to offering support to grieving family members, providing palliative care to the child, and helping the family to prepare for a death. With the advent of more effective surgery, radiation therapy, and chemotherapy the prognosis has shifted from inevitable gloom to guarded hope. Clinicians are now in the fortunate position of being able to consider the long-range adjustment issues these patients face.In the past there was little effort to study the survivors of pediatric cancer, simply because there were few to study. However, there have been efforts to examine the impact of some major side-effects of cancer treatment which bear on long-term adjustment. For example, attention has been focused on the impact of central nervous system irradiation on the neuropsychological functioning of children with acute leukemia (Soni et aL, 1975;Mclntosh et al., 1976). Research continues in this area, but the patients under study represent only one type of cancer and are often still under active treatment for their disease. Other studies have explored the longterm medical side-effects of treatment for childhood cancer, including the risk of second tumors among survivors (Li and Stone, 1976) and health of progeny of pediatric cancer survivors (Li and Jaffe, 1974), but they only briefly explored psychological adjustment issues. One recent paper focused on psychological responses of adult patients said to be cured of advanced cancer (Kennedy et al., 1976) and more such studies are anticipated. The potential disruption of important developmental stages during childhood, however, makes the evaluation of psychological .re^zi^te of pediatric cancer a complex, important, and relatively unresearched territory.The current investigation is one part of a comprehensive study of long-term survivors of pediatric cancer. A computerized survivor registry lists nearly 800 living survivors of childhood cancer, defmed as having disease onset prior to age 18 years and currently at least 60 months beyond initial diagnosis. The registry is complete in •Requests for reprints to: Gerald P. Koocher

No abstract

Government agencies often face trade-offs in developing initiatives that address a public good given competing concerns of various constituent groups. Efforts to construct data warehouses that enable data mining of citizens' personal information obtained from other organizations (including sister agencies) create a complex challenge, since privacy concerns may vary across constituent groups whose priorities diverge from agencies' e-government goals. In addition to privacy concerns, participating government agencies' priorities related to the use of the information may also be in conflict. This article reports on a case study of the Integrated NonFiler Compliance System used by the California Franchise Tax Board for which data are collected from federal, state, and municipal agencies and other organizations in a data mining application that aims to identify residents who under-report income or fail to file tax returns. This system pitted the public good (ensuring owed taxes are paid) against citizen concerns about privacy. Drawing on stakeholder theory, the authors propose a typology of four stakeholder groups (data controllers, data subjects, data providers, and secondary stakeholders) to address privacy concerns and argue that by ensuring procedural fairness for the data subjects, agencies can reduce some barriers that impede the successful adoption of e-government applications and policies. The article concludes that data controllers can reduce adoption and implementation barriers when e-government data mining applications rely on data shared across organizational boundaries: identify legitimate stakeholders and their concerns prior to implementation; enact procedures to ensure procedural fairness when data are captured, shared, and used; explain to each constituency how the data mining application helps to ensure distributive fairness; and continue to gauge stakeholders' responses and ongoing concerns as long as the application is in use.

No abstract