Introduction: Hip and knee osteoarthritis are associated with functional limitations, pain and restrictions in quality of life and the ability to work. Furthermore, with growing prevalence, osteoarthritis is increasingly causing (in)direct costs. Guidelines recommend exercise therapy and education as primary treatment strategies. Available options for treatment based on physical activity promotion and lifestyle change are often insufficiently provided and used. In addition, the quality of current exercise programmes often does not meet the changing care needs of older people with comorbidities and exercise adherence is a challenge beyond personal physiotherapy. The main objective of this study is to investigate the short- and long-term (cost-)effectiveness of the SmArt-E programme in people with hip and/or knee osteoarthritis in terms of pain and physical functioning compared to usual care. Methods: This study is designed as a multicentre randomized controlled trial with a target sample size of 330 patients. The intervention is based on the e-Exercise intervention from the Netherlands, consists of a training and education programme and is conducted as a blended care intervention over 12 months. We use an app to support independent training and the development of self-management skills. The primary and secondary hypotheses are that participants in the SmArt-E intervention will have less pain (numerical rating scale) and better physical functioning (Hip Disability and Osteoarthritis Outcome Score, Knee Injury and Osteoarthritis Outcome Score) compared to participants in the usual care group after 12 and 3 months. Other secondary outcomes are based on domains of the Osteoarthritis Research Society International (OARSI). The study will be accompanied by a process evaluation. Discussion: After a positive evaluation, SmArt-E can be offered in usual care, flexibly addressing different care situations. The desired sustainability and the support of the participants' behavioural change are initiated via the app through audio-visual contact with their physiotherapists. Furthermore, the app supports the repetition and consolidation of learned training and educational content. For people with osteoarthritis, the new form of care with proven effectiveness can lead to a reduction in underuse and misuse of care as well as contribute to a reduction in (in)direct costs.
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This paper introduces the Internet-of-Things (IoT) and describes its evolution from a concept proposed by Kevin Ashton in 1999 through its public emergence in 2005 in a United Nations ITU report entitled “The Internet of Things”, to the present day where IoT devices are available as off-the-shelf products from major manufacturers. Using a systematic study of public literature, the paper presents a five-phase categorisation of the development of the Internet-of-Things from its beginnings to the present day. Four mini case studies are included to illustrate some of the issues involved. Finally, the paper discusses some of the big issues facing future developers and marketers of Internet-of-Things based products ranging from artificial intelligence (AI) through to customer privacy and acceptance finishing with an optimistic assessment of the future of the Internet-of-Things.
We studied 12 smart city projects in Amsterdam, and –among other things- analysed their upscaling potential and dynamics. Here are some of our findings:First, upscaling comes in various forms: rollout, expansion and replication. In roll-out, a technology or solution that was successfully tested and developed in the pilot project is commercialised/brought to the market (market roll-out), widely applied in an organisation (organisational roll-out), or rolled out across the city (city roll-out). Possibilities for rollout largely emerge from living-lab projects (such as Climate street and WeGo), where companies can test beta versions of new products/solutions. Expansion is the second type of upscaling. Here, the smart city pilot project is expanded by a) adding partners, b) extending the geographical area covered by the solution, or c) adding functionality. This type of upscaling applies to platform projects, for example smart cards for tourists, where the value of the solution grows with the number of participating organisations. Replication is the third and most problematic type of upscaling. Here, the solution that was developed in the pilot project is replicated elsewhere (another organisation, another part of the city, or another city). Replication can be done by the original pilot partnership but also by others, and the replication can be exact or by proxy. We found that the replication potential of projects is often limited because the project’s success is highly context-sensitive. Replication can also be complex because new contexts might often require the establishment of new partnerships. Possibilities for replication exist, though, at the level of working methods, specific technologies or tools, but variations among contexts should be taken into consideration. Second, upscaling should be considered from the start of the pilot project and not solely at the end. Ask the following questions: What kind of upscaling is envisioned? What parts of the project will have potential for upscaling, and what partners do we need to scale up the project as desired? Third, the scale-up stage is quite different from the pilot stage: it requires different people, competencies, organisational setups and funding mechanisms. Thus, pilot project must be well connected to the parent organisations, else it becomes a “sandbox” that will stay a sandbox. Finally, “scaling” is not a holy grail. There is nothing wrong when pilot projects fail, as long as the lessons are lessons learned for new projects, and shared with others. Cities should do more to facilitate learning between their smart city projects, to learn and innovate faster.
