How to reduce carbon emissions and contribute to climate change mitigation? For years the carbon-intensive travel industry has been struggling with this question. Research has addressed the relation between climate change and tourism (e.g., Gössling et al 2015; Becken, 2013; Gössling, 2010; Gössling et al 2010; Bows et al, 2009). Their work produced models and measurement methods, and recommended mitigation policies and actions (Scott, 2011; Dwyer et al, 2010; Gössling et al 2010; McKercher, 2010). Major industry players have since adopted carbon reduction measures in their CSR policies (Thomas Cook group, 2015; TUI Group, 2015). However, the bulk of the travel industry consists of SMEs that typically have limited resources available for CSR. CARMACAL may offer a solution for the sector at large. CARMACAL is a user-friendly application that enables tour operators to accurately measure the complete carbon footprint of their tour packages and integrate carbon management in their business (CSTT, 2016a). The industry acknowledged its relevance: in April 2016 CARMACAL won the WTTC Tourism for Tomorrow Innovation Award
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In this document, we provide the methodological background for the Safety atWork project. This document combines several project deliverables as defined inthe overall project plan: validation techniques and methods (D5.1.1), performanceindicators for safety at work (D5.1.2), personal protection equipment methods(D2.1.2), situational awareness methods (D3.1.2), and persuasive technology methods(D4.1.2).
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Psychologists, psycholinguists, and other researchers using language stimuli have been struggling for more than 30 years with the problem of how to analyze experimental data that contain two crossed random effects (items and participants). The classical analysis of variance does not apply; alternatives have been proposed but have failed to catch on, and a statistically unsatisfactory procedure of using two approximations (known as F 1 and F 2) has become the standard. A simple and elegant solution using mixed model analysis has been available for 15 years, and recent improvements in statistical software have made mixed models analysis widely available. The aim of this article is to increase the use of mixed models by giving a concise practical introduction and by giving clear directions for undertaking the analysis in the most popular statistical packages. The article also introduces the djmixed add-on package for SPSS, which makes entering the models and reporting their results as straightforward as possible.
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The pressure on the European health care system is increasing considerably: more elderly people and patients with chronic diseases in need of (rehabilitation) care, a diminishing work force and health care costs continuing to rise. Several measures to counteract this are proposed, such as reduction of the length of stay in hospitals or rehabilitation centres by improving interprofessional and person-centred collaboration between health and social care professionals. Although there is a lot of attention for interprofessional education and collaborative practice (IPECP), the consortium senses a gap between competence levels of future professionals and the levels needed in rehabilitation practice. Therefore, the transfer from tertiary education to practice concerning IPECP in rehabilitation is the central theme of the project. Regional bonds between higher education institutions and rehabilitation centres will be strengthened in order to align IPECP. On the one hand we deliver a set of basic and advanced modules on functioning according to the WHO’s International Classification of Functioning, Disability and Health and a set of (assessment) tools on interprofessional skills training. Also, applications of this theory in promising approaches, both in education and in rehabilitation practice, are regionally being piloted and adapted for use in other regions. Field visits by professionals from practice to exchange experiences is included in this work package. We aim to deliver a range of learning materials, from modules on theory to guidelines on how to set up and run a student-run interprofessional learning ward in a rehabilitation centre. All tested outputs will be published on the INPRO-website and made available to be implemented in the core curricula in tertiary education and for lifelong learning in health care practice. This will ultimately contribute to improve functioning and health outcomes and quality of life of patients in rehabilitation centres and beyond.
