Introduction : the importance of method in the study of the ‘Political Internet’

In this introduction, we outline our understanding of the ‘political Internet’ and present the methodologically focused approach that we take to the topic in this volume. We then discuss the growing social and political relevance of the Internet and examine the characteristics of the contemporary ‘Web 2.0’ Internet, before outlining the general methodological challenges and opportunities that it presents for researchers. We argue that three key characteristics of online political information in the Web 2.0 era shape and constrain any study of the political Internet. These characteristics are (1) extremely large volume, (2) heterogeneity and (3) plasticity. We contend that this combination creates what we term a ‘dynamic data deluge’ for social scientists, which makes distinguishing and recording meaningful information generated by the political Internet a methodologically challenging endeavour. We then discuss how the chapters collected here attempt to make sense of the dynamic data deluge that the political Internet presents. In the course of doing so, we build a picture of what distinguishes social media from earlier types of digital communication and discuss how social media content can be assimilated and processed by social science. We touch on epistemological concerns arising from this discussion before outlining the structure of the book and providing details of the individual contributions

Relative risk of diabetes, dyslipidaemia, hypertension and the metabolic syndrome in people with severe mental illnesses: Systematic review and metaanalysis

<p>Abstract</p> <p>Background</p> <p>Severe mental illnesses (SMI) may be independently associated with cardiovascular risk factors and the metabolic syndrome. We aimed to systematically assess studies that compared diabetes, dyslipidaemia, hypertension and metabolic syndrome in people with and without SMI.</p> <p>Methods</p> <p>We systematically searched MEDLINE, EMBASE, CINAHL & PsycINFO. We hand searched reference lists of key articles. We employed three search main themes: SMI, cardiovascular disease, and each cardiovascular risk factor. We selected cross-sectional, case control, cohort or intervention studies comparing one or more risk factor in both SMI and a reference group. We excluded studies without any reference group. We extracted data on: study design, cardiovascular risk factor(s) and their measurement, diagnosis of SMI, study setting, sampling method, nature of comparison group and data on key risk factors.</p> <p>Results</p> <p>Of 14592 citations, 134 papers met criteria and 36 were finally included. 26 reported on diabetes, 12 hypertension, 11 dyslipidaemia, and 4 metabolic syndrome. Most studies were cross sectional, small and several lacked comparison data suitable for extraction. Meta-analysis was possible for diabetes, cholesterol and hypertension; revealing a pooled risk ratio of 1.70 (1.21 to 2.37) for diabetes and 1.11 (0.91 to 1.35) of hypertension. Restricting SMI to schizophreniform illnesses yielded a pooled risk ratio for diabetes of 1.87 (1.68 to 2.09). Total cholesterol was not higher in people with SMI (Standardized Mean Difference -0.10 (-0.55 to 0.36)) and there were inconsistent data on HDL, LDL and triglycerides with some, but not all, reporting lower levels of HDL cholesterol and raised triglyceride levels. Metabolic syndrome appeared more common in SMI.</p> <p>Conclusion</p> <p>Diabetes (but not hypertension) is more common in SMI. Data on other risk factors were limited by poor quality or inconsistent research findings, but a small number of studies show greater prevalence of the metabolic syndrome in SMI.</p