Social Media And Health: Implications For Primary Health Care Providers

This report is the second deliverable of the ?Digital Inclusion and Social Knowledge Media for Health: Frameworks and Roadmaps? project. The first discussed the concept of social and digital exclusion whilst this report focuses on the emerging phenomenon of social media. The report outlines current knowledge on the users and usages of social media for health and goes on to discuss social media in the context of a continuing focus (ref. D1.1) on the areas of mental health, smoking cessation and teenage lifestyles. The report concludes with an outline of an approach to a ?social media strategy? and with suggestions for directions for future research

Playlab: Telling Stories with Technology (workshop summary)

This one-day workshop explores how playful interaction can be used to develop technologies for public spaces and create temporal experiences

Graphical Markov models, unifying results and their interpretation

Graphical Markov models combine conditional independence constraints with graphical representations of stepwise data generating processes.The models started to be formulated about 40 years ago and vigorous development is ongoing. Longitudinal observational studies as well as intervention studies are best modeled via a subclass called regression graph models and, especially traceable regressions. Regression graphs include two types of undirected graph and directed acyclic graphs in ordered sequences of joint responses. Response components may correspond to discrete or continuous random variables and may depend exclusively on variables which have been generated earlier. These aspects are essential when causal hypothesis are the motivation for the planning of empirical studies. To turn the graphs into useful tools for tracing developmental pathways and for predicting structure in alternative models, the generated distributions have to mimic some properties of joint Gaussian distributions. Here, relevant results concerning these aspects are spelled out and illustrated by examples. With regression graph models, it becomes feasible, for the first time, to derive structural effects of (1) ignoring some of the variables, of (2) selecting subpopulations via fixed levels of some other variables or of (3) changing the order in which the variables might get generated. Thus, the most important future applications of these models will aim at the best possible integration of knowledge from related studies.Comment: 34 Pages, 11 figures, 1 tabl

Computer programs and documentation

Various statistical tests that were used to check out random number generators are described. A total of twelve different tests were considered, and from these, six were chosen to be used. The frequency test, max t test, run test, lag product test, gap test, and the matrix test are included