The Internet as a Unique News Source

Presents findings from a survey conducted in May and June 2004. Looks at the use of the Internet for news coverage and images not available in the mainstream media. Includes reaction to the new experience of war images online

Predicting Alzheimer's risk: why and how?

Because the pathologic processes that underlie Alzheimer's disease (AD) appear to start 10 to 20 years before symptoms develop, there is currently intense interest in developing techniques to accurately predict which individuals are most likely to become symptomatic. Several AD risk prediction strategies - including identification of biomarkers and neuroimaging techniques and development of risk indices that combine traditional and non-traditional risk factors - are being explored. Most AD risk prediction strategies developed to date have had moderate prognostic accuracy but are limited by two key issues. First, they do not explicitly model mortality along with AD risk and, therefore, do not differentiate individuals who are likely to develop symptomatic AD prior to death from those who are likely to die of other causes. This is critically important so that any preventive treatments can be targeted to maximize the potential benefit and minimize the potential harm. Second, AD risk prediction strategies developed to date have not explored the full range of predictive variables (biomarkers, imaging, and traditional and non-traditional risk factors) over the full preclinical period (10 to 20 years). Sophisticated modeling techniques such as hidden Markov models may enable the development of a more comprehensive AD risk prediction algorithm by combining data from multiple cohorts. As the field moves forward, it will be critically important to develop techniques that simultaneously model the risk of mortality as well as the risk of AD over the full preclinical spectrum and to consider the potential harm as well as the benefit of identifying and treating high-risk older patients

The Internet and the Iraq War

Presents findings from a survey conducted in March 2003. Looks at how supporters and opponents of the war are using the Internet differently, and how Americans are using email to debate, express concerns, and show their patriotism

Hierarchical models for semi-competing risks data with application to quality of end-of-life care for pancreatic cancer

Readmission following discharge from an initial hospitalization is a key marker of quality of health care in the United States. For the most part, readmission has been used to study quality of care for patients with acute health conditions, such as pneumonia and heart failure, with analyses typically based on a logistic-Normal generalized linear mixed model. Applying this model to the study readmission among patients with increasingly prevalent advanced health conditions such as pancreatic cancer is problematic, however, because it ignores death as a competing risk. A more appropriate analysis is to imbed such studies within the semi-competing risks framework. To our knowledge, however, no comprehensive statistical methods have been developed for cluster-correlated semi-competing risks data. In this paper we propose a novel hierarchical modeling framework for the analysis of cluster-correlated semi-competing risks data. The framework permits parametric or non-parametric specifications for a range of model components, including baseline hazard functions and distributions for key random effects, giving analysts substantial flexibility as they consider their own analyses. Estimation and inference is performed within the Bayesian paradigm since it facilitates the straightforward characterization of (posterior) uncertainty for all model parameters including hospital-specific random effects. The proposed framework is used to study the risk of readmission among 5,298 Medicare beneficiaries diagnosed with pancreatic cancer at 112 hospitals in the six New England states between 2000-2009, specifically to investigate the role of patient-level risk factors and to characterize variation in risk across hospitals that is not explained by differences in patient case-mix

Research and Indigenous Librarianship in Canada

Peer ReviewedThis thought piece provides helpful information about ethical research practices related to research involving Indigenous peoples so that academic librarians (both Indigenous and non-Indigenous) are better informed about the complex issues that exist and arise in such endeavours. Woven throughout the paper are guidance and strategies to avoid causing harm when doing research with Indigenous peoples and communities, such as misrepresenting Indigenous peoples, cultures, and epistemologies. A brief account of the legacy of a long history of unethical research practices conducted by Western researchers who extracted Indigenous knowledge speaks to why Indigenous peoples do not trust academic research projects. Researchers need to question their own motives when they consider conducting research with Indigenous peoples and to respect that we want to be involved in our own solutions and in research that utilizes Indigenous values, with the goal that “nothing [is done] about us without us.” Key to building relationships and finding success in the research undertaken are an in-depth understanding of Indigenous protocols, values, and ways of knowing, as well as evidence of the researcher making a long-term commitment to the research and the community. Further, such an understanding provides an access point for librarians to contribute to the decolonization of library services while supporting Indigenous researchers

The importance of easy access to online information resources for aboriginal researchers

Deborah Lee Indigenous Studies Portal Librarian and Team Leader University of Saskatchewan Librar