Clinical trial informed consent statements can be modified to be easier to read without omitting critical information. Patient anxiety and satisfaction can be affected by the consent document. The generalizability of these study results is limited by the characteristics of the patient sample. Ninety percent of the sample were white women, and the mean Rapid Estimate of Adult Literacy in Medicine score was approximately 64, indicating a literacy level at or above the ninth grade.

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Rural, low-income cancer patients should be better informed about clinical trials, when applicable. Physician trust may enhance willingness to participate if clinical trials are close to home.

Institutional review boards (IRBs) and informed consent have recently come under increasing scrutiny. The provision of appropriate and understandable information and its comprehension are key elements of the informed consent process. This article examines how literacy and other factors might impact on comprehension of the information provided. Better understanding of these issues and how to best address them are crucial to allowing clinical research subjects to participate as well-informed and willing partners in scientific inquiry.

Residents of Appalachia, especially those in rural Appalachia, are generally considered to be medically underserved. In fact, cancer mortality in Appalachia, especially in rural Appalachia, is higher than it is in the remainder of the United States. Developing from the Appalachia Leadership Initiative on Cancer, the Appalachia Cancer Network (ACN) is a network of academic and community organizations that seek to conduct surveillance, intervention, and dissemination research to reduce this excess cancer burden in Appalachia. The purpose of this report is to (1) describe the approach to cancer control research in ACN, a Special Population Network, among the medically underserved of Appalachia, and (2) to put forward observations from this experience to enhance the research of other academic and community networks among underserved populations. ACN has instituted a conceptual model, organizational structure, and other methods to foster this research and to develop junior and community-based investigators. Important issues and questions related to the effectiveness of such research networks have also been articulated.

Over the past 10 years, breast cancer screening has increased greatly among women in the United States. Among women ages 50 and older, more than 56% reported having received a clinical breast exam and mammogram (X-ray images of the breast) in the 2 years preceding the 1994 National Health Interview Survey (NHIS), compared with 25% in 1987 (US. Department of Health and Human Services [DHHS], 1990). Mammography rates doubled or tripled for most ethnic groups over that period. In the past decade, the progress that has been made in breast cancer screening is striking. Although it may be impossible to demonstrate a causal relationship, the increase in screening rates surely is a result of a concerted effort by researchers, clinicians, and practitioners. The investments made

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Objective. To introduce a methodology for planning preventive health service research that takes into account geographic context. Design. Bayesian hierarchical modeling describes mammography as a function of county-level socioeconomic data and explicitly estimates the geographic variation unexplained by the county-level data. This model produces county use estimates (both NHIS-sampled and unsampled), which are aggregated for entire states. The locations of intervention research studies are examined in light of the statewide mammography utilization estimates.Data Extraction. Individual level NHIS data were merged with county-level data from the ARF.Principal Findings. State maps reveal the estimated distribution of mammography utilization and intervention research. Eighteen states with low mammography use reported no intervention research activity. County-level occupation and education were important predictors for younger women in 1993-94. In 1987, they were not predictive for any demographic group.Conclusions. Opportunities exist to improve the planning of future intervention research by considering geographic context. Modeling results suggest that the choice of predictors be tailored to both the population and the time period under study when planning interventions.