Objective: To systematically describe changes in pain and functioning in patients with osteoarthritis (OA) awaiting total joint replacement (TJR), and to assess determinants of this change. Methods: MEDLINE®, EMBASE, CINAHL® and Cochrane Database were searched through June 2008. The reference lists of eligible publications were reviewed. Studies that monitored pain and functioning in patients with hip or knee OA during the waiting list for TJR were analyzed. Data were collected with a pre-specified collection tool. Methodological quality was assessed and a best-evidence analysis was performed to summarize results. Results: Fifteen studies, of which two were of high quality, were included and involved 788 hip and 858 knee patients (mean age 59-72 and main wait 42-399 days). There was strong evidence that pain (in hip and knee OA) and self-reported functioning (in hip OA) do not deteriorate during a
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'The best place to hide a dead body is page 2 of Google search results.' For some time now the image above has been circulating online. The joke accurately introduces the core question of this essay. What is the effect of the list as the most used structure of presenting online information on the way people organize and find this information? What does it mean when people constantly use the list when dealing with information?
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Inspired by taxonomist Jack Goody’s theorizing of ‘ancient lists’ as ‘intellectual technologies’, this book analyzes listing practices in modern and contemporary formations of power, and how they operate in the installation and securing of the milieus of circulation that characterize Michel Foucault’s conception of governmentality. Propelling the list’s role in the delimitation and policing of risky and threatening elements from out of history and into a contemporary analysis of power, this work demonstrates how assemblages of computer, statistical, and list technologies first deployed by the Nazi regime continue to resonate significantly in the segmenting and constitution of a critical classification of contemporary homo sapiens: the terrorist class, or homo sacer.
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Youth care is under increasing pressure, with rising demand, longer waiting lists, and growing staff shortages. In the Netherlands, one in seven children and adolescents is currently receiving youth care. At the same time, professionals face high workloads, burnout risks, and significant administrative burdens. This combination threatens both the accessibility and quality of care, leading to escalating problems for young people and families. Artificial intelligence (AI) offers promising opportunities to relieve these pressures by supporting professionals in their daily work. However, many AI initiatives in youth care fail to move beyond pilot stages, due to barriers such as lack of user acceptance, ethical concerns, limited professional ownership, and insufficient integration into daily practice. Empirical research on how AI can be responsibly and sustainably embedded in youth care is still scarce. This PD project aims to develop practice-based insights and strategies that strengthen the acceptance and long-term adoption of AI in youth care, in ways that support professional practice and contribute to appropriate care. The focus lies not on the technology itself, but on how professionals can work with AI within complex, high-pressure contexts. The research follows a cyclical, participatory approach, combining three complementary implementation frameworks: the Implementation Guide (Kaptein), the CFIR model (Damschroder), and the NASSS-CAT framework (Greenhalgh). Three case studies serve as core learning environments: (1) a speech-to-text AI tool to support clinical documentation, (2) Microsoft Copilot 365 for organization-wide adoption in support teams, and (3) an AI chatbot for parents in high-conflict divorces. Throughout the project, professionals, clients, ethical experts, and organizational stakeholders collaborate to explore the practical, ethical, and organizational conditions under which AI can responsibly strengthen youth care services.
JIC BRO has recently launched its improved measurement methodology for OOH-advertising, BRO Next. Now this is ready, JIC BRO wants to add more realistic data to the attention-metric, as it has several areas to improve upon. Currently, benchmark data is international and not behavioral but claimed (tested on a computer screen, questions are asking a lot (too much) from consumers: e.g. ‘Please imagine that you are driving in your car…’). Therefore, JIC BRO asked a core team of human attention professionals to develop a methodology that is futureproof and can be used in any OOH-area. At the same time this project wants to develop new knowledge on attention behavior and measurements in waiting conditions.Societal issueThe needs and harms around pervasive messages in public spaces.Collaborative partnerHaystack Consulting.
