Optimizing Research on End-of-Life Care for Seniors:The Collective New Emerging Team on End of Life Care for Seniors University of Ottawa, Institute of Palliative Care

Background: End-of-life care for seniors is an important and neglected area of research. The University of Ottawa Institute of Palliative Care has expanded its research capacity by developing a Canadian Institutes of Health Research (CIHR) funded new emerging team on end-of-life care for seniors. This initiative brings together an interdisciplinary team of researchers from palliative care and geriatrics to develop a comprehensive program of research. Methods: 1) A variety of investigators from the fields of palliative care and geriatrics and disciplines of epidemiology, medicine, nursing, psychology and social work will collaborate on the development of a research agenda focussed on end-of-life care for seniors. 2) The conceptual model for the research program consists of 4 broad interrelated domains that are congruent with the CIHR themes of health services, clinical issues, population health and psychosocial, cultural, spiritual and ethical issues; this framework will guide the research program and all studies emanating from the program. 3) Research studies will focus on 5 areas of inquiry that are central to end-of-life care for seniors: palliative end-of-life care for rural seniors, care settings, burden, role of volunteers, and delirium. Results: This new team has the potential to obtain peer-reviewed funding, recruit and train a new generation of researchers, and build a network of concerned researchers. Conclusions: The new team should ultimately contribute to an improved quality of care for seniors who are approaching death.

DiveRsity: An R package for the estimation and exploration of population genetics parameters and their associated errors

Summary: We present a new R package, diveRsity, for the calculation of various diversity statistics, including common diversity partitioning statistics (?, G) and population differentiation statistics (D, GST ', ? test for population heterogeneity), among others. The package calculates these estimators along with their respective bootstrapped confidence intervals for loci, sample population pairwise and global levels. Various plotting tools are also provided for a visual evaluation of estimated values, allowing users to critically assess the validity and significance of statistical tests from a biological perspective. diveRsity has a set of unique features, which facilitate the use of an informed framework for assessing the validity of the use of traditional F-statistics for the inference of demography, with reference to specific marker types, particularly focusing on highly polymorphic microsatellite loci. However, the package can be readily used for other co-dominant marker types (e.g. allozymes, SNPs). Detailed examples of usage and descriptions of package capabilities are provided. The examples demonstrate useful strategies for the exploration of data and interpretation of results generated by diveRsity. Additional online resources for the package are also described, including a GUI web app version intended for those with more limited experience using R for statistical analysis. © 2013 British Ecological Society.