Factors affecting the disclosure of diabetes by ethnic minority patients: a qualitative study among Surinamese in the Netherlands

<p>Abstract</p> <p>Background</p> <p>Diabetes and related complications are common among ethnic minority groups. Community-based social support interventions are considered promising for improving diabetes self-management. To access such interventions, patients need to disclose their diabetes to others. Research on the disclosure of diabetes in ethnic minority groups is limited. The aim of our study was to explore why diabetes patients from ethnic minority populations either share or do not share their condition with people in their wider social networks.</p> <p>Methods</p> <p>We conducted a qualitative study using semi-structured interviews with 32 Surinamese patients who were being treated for type 2 diabetes by general practitioners in Amsterdam, the Netherlands.</p> <p>Results</p> <p>Most patients disclosed their diabetes only to very close family members. The main factor inhibiting disclosure to people outside this group was the Surinamese cultural custom that talking about disease is taboo, as it may lead to shame, gossip, and social disgrace for the patient and their family. Nevertheless, some patients disclosed their diabetes to people outside their close family circles. Factors motivating this decision were mostly related to a need for facilities or support for diabetes self-management.</p> <p>Conclusions</p> <p>Cultural customs inhibited Surinamese patients in disclosing their diabetes to people outside their very close family circles. This may influence their readiness to participate in community-based diabetes self-management programmes that involve other groups. What these findings highlight is that public health researchers and initiatives must identify and work with factors that influence the disclosure of diabetes if they are to develop community-based diabetes self-management interventions for ethnic minority populations.</p

“This Erstwhile Unreadable Text”: Multidisciplinarity and First-Year Writing Faculty Teaching Mentoring and Support

Despite the otherwise rich multidisciplinary terrain of writing studies, the strategies most often used with first-year writing teacher teaching mentoring and support tend to remain discordantly anchored to a comparatively narrow version of writing pedagogy. I argue in this article that infusing a multidisciplinary dimension into first-year writing faculty teaching mentoring and support will enrich the ways faculty and students think, write, and talk about first-year writing. This article provides specific strategies for infusing multidisciplinary dimensions into first-year writing faculty teaching mentoring and support. Such a move is vital across nearly all contexts of first-year writing, not only where first-year writing has overtly multidisciplinary features, but also where first-year writing exists more firmly in English departments

WPAs, Writing Programs and the Common Reading Experience

Community colleges, colleges, and universities around the United States are increasingly instituting common reading programs. These often involve pre-matriculate first-year students reading a common text (or set of texts) and then, once on campus, participating in a range of related academic and/or co-curricular activities. While the goals and administrative roles of common reading experiences (CREs) vary by institution, nearly all intersect with writing programs and the work of writing program administrators (WPAs). These intersections are largely unexplored in writing studies scholarship, despite the fact that CREs are closely connected with reading and writing practices of first-year students. This article draws on three divergent WPA experiences with CREs (Duke University, Fort Lewis College, and University of Texas, Arlington) in order to explore the complexities informing how WPAs choose to productively respond to, strengthen, resist, and/or otherwise engage with the CRE

MOPSA: Multiple Output Prediction for Scalability and Accuracy

Cloud computing is entailed for elasticity, scalability, and accuracy for the multi-sharing systems; predicting resource for the multi-sharing system in an existing system is not accurate which leads to under or over-provisioning of resources and increases higher cost for on-demand resources. In this paper, we develop a prediction model called Multiple Output Prediction for Scalability and Accuracy (MOPSA). The key characteristic of this model is to improve accuracy of prediction of resources with multiple outputs in multi-sharing system by using gradient descent method. Experimental results exhibit that the proposed model improves the prediction accuracy of resources and provides scalability in multi-sharing system for minimizing cost by reducing number of on-demand resources