43 research outputs found
Music‐Based Interventions for People Living with Dementia, targeting Behavioral and Psychological Symptoms: A scoping review
IntroductionDementia care is a major public health issue worldwide. The management of behavioral and psychological symptoms (BPSD) is one of the hardest challenges in this context. Non-pharmacological strategies, like music-based interventions (Mbi), seem promising options, being considered low-risk, widely available and inclusive. This scoping review aimed at mapping all Mbi used in dementia care, targeting BPSD, and debriefing its components, structure and rationale. Music therapy and other therapeutic music activities were included.MethodsThe Arksey and O'Malley framework, Cochrane recommendations and PRISMA checklist were followed. Embase, PubMed, PsycINFO, ASSIA and Humanities Index were searched from first records until the 31st of March 2020. Snowballing process and screening of relevant journals were also undertaken. A panel of experts critically guided the evidence synthesis.ResultsOverall, 103 studies (34 RCT; 12 NRT; 40 Before/After studies and 17 Case Studies) met inclusion criteria. Basic elements of the Mbi, the rationale supporting its development and hypothesis tested were mostly underreported, thus hampering cross-study comparisons and generalizations. Despite this, available evidence indicates that: it is feasible to deliver Mbi to PwD at very different stages and in different settings - from community to the acute setting - even for non-music therapists; positive or neutral effects in BPSD are often reported but not without exception; individualization seems a critical factor mediating Mbi effects.ConclusionsDetailed intervention and research reporting are essential to interpretation, replication and translation into practice. Ten years after the publication of specific reporting guidelines, this goal is not yet fully achieved in music in dementia care
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A Critical Review of Short-Term Water Demand Forecasting Tools—What Method Should I Use?
The challenge for city authorities goes beyond managing growing cities, since as cities develop, their exposure to climate change effects also increases. In this scenario, urban water supply is under unprecedented pressure, and the sustainable management of the water demand, in terms of practices including economic, social, environmental, production, and other fields, is becoming a must for utility managers and policy makers. To help tackle these challenges, this paper presents a well-timed review of predictive methods for short-term water demand. For this purpose, over 100 articles were selected from the articles published in water demand forecasting from 2010 to 2021 and classified upon the methods they use. In principle, the results show that traditional time series methods and artificial neural networks are among the most widely used methods in the literature, used in 25% and 20% of the articles in this review. However, the ultimate goal of the current work goes further, providing a comprehensive guideline for engineers and practitioners on selecting a forecasting method to use among the plethora of available options. The overall document results in an innovative reference tool, ready to support demand-informed decision making for disruptive technologies such as those coming from the Internet of Things and cyber–physical systems, as well as from the use of digital twin models of water infrastructure. On top of this, this paper includes a thorough review of how sustainable management objectives have evolved in a new era of technological developments, transforming data acquisition and treatment.</jats:p