There is emerging evidence that the performance of risk assessment instruments is weaker when used for clinical decision‐making than for research purposes. For instance, research has found lower agreement between evaluators when the risk assessments are conducted during routine practice. We examined the field interrater reliability of the Short‐Term Assessment of Risk and Treatability: Adolescent Version (START:AV). Clinicians in a Dutch secure youth care facility completed START:AV assessments as part of the treatment routine. Consistent with previous literature, interrater reliability of the items and total scores was lower than previously reported in non‐field studies. Nevertheless, moderate to good interrater reliability was found for final risk judgments on most adverse outcomes. Field studies provide insights into the actual performance of structured risk assessment in real‐world settings, exposing factors that affect reliability. This information is relevant for those who wish to implement structured risk assessment with a level of reliability that is defensible considering the high stakes.
BackgroundA key factor in successfully preventing falls, is early identification of elderly with a high risk of falling. However, currently there is no easy-to-use pre-screening tool available; current tools are either not discriminative, time-consuming and/or costly. This pilot investigates the feasibility of developing an automatic gait-screening method by using a low-cost optical sensor and machinelearning algorithms to automatically detect features and classify gait patterns.MethodParticipants (n = 204, age 27 ± 7 yrs.) performed a gait test under two conditions: control and with distorted depth perception (induced by wearing special goggles). Each test consisted of 4x 3m walking at comfortable speed. Full-body 3D kinematics were captured using an optical sensor (Microsoft Xbox One Kinect). Tests were conducted in a public space to establish relatively 'natural' conditions. Data was processed in Matlab and common spatiotemporal variables were calculated per gait section. The 3D-time series data of the centre of mass for each section was used as input for a neural network, that was trained to discriminate between the two conditions.ResultsWearing the goggles affected the gait pattern significantly: gait velocity and step length decreased, and lateral sway increased compared to the control condition. A 2-layer neural network could correctly classify 79% of the gait segments (i.e. with or without distorted vision).ConclusionsThe results show that gait patterns of healthy people with distorted vision could automatically be classified with the proposed approach. Future work will focus on adapting this model for identification of specific physical risk-factors in elderly.
Background: Cardiovascular risk factors are associated with physical fitness and, to a lesser extent, physical activity. Lifestyle interventions directed at enhancing physical fitness in order to decrease the risk of cardiovascular diseases should be extended. To enable the development of effective lifestyle interventions for people with cardiovascular risk factors, we investigated motivational, social-cognitive determinants derived from the Theory of Planned Behavior (TPB) and other relevant social psychological theories, next to physical activity and physical fitness. Methods: In the cross-sectional Utrecht Police Lifestyle Intervention Fitness and Training (UP-LIFT) study, 1298 employees (aged 18 to 62) were asked to complete online questionnaires regarding social-cognitive variables and physical activity. Cardiovascular risk factors and physical fitness (peak VO2) were measured. Results: For people with one or more cardiovascular risk factors (78.7% of the total population), social-cognitive variables accounted for 39% (p < .001) of the variance in the intention to engage in physical activity for 60 minutes every day. Important correlates of intention to engage in physical activity were attitude (beta = .225, p < .001), self-efficacy (beta = .271, p < .001), descriptive norm (beta = .172, p < .001) and barriers (beta = -.169, p < .01). Social-cognitive variables accounted for 52% (p < .001) of the variance in physical active behaviour (being physical active for 60 minutes every day). The intention to engage in physical activity (beta = .469, p < .001) and self-efficacy (beta = .243, p < .001) were, in turn, important correlates of physical active behavior. In addition to the prediction of intention to engage in physical activity and physical active behavior, we explored the impact of the intensity of physical activity. The intentsity of physical activity was only significantly related to physical active behavior (beta = .253, p < .01, R2 = .06, p < .001). An important goal of our study was to investigate the relationship between physical fitness, the intensity of physical activity and social-cognitive variables. Physical fitness (R2 = .23, p < .001) was positively associated with physical active behavior (beta = .180, p < .01), self-efficacy (beta = .180, p < .01) and the intensity of physical activity (beta = .238, p < .01). For people with one or more cardiovascular risk factors, 39.9% had positive intentions to engage in physical activity and were also physically active, and 10.5% had a low intentions but were physically active. 37.7% had low intentions and were physically inactive, and about 11.9% had high intentions but were physically inactive. Conclusions: This study contributes to our ability to optimize cardiovascular risk profiles by demonstrating an important association between physical fitness and social-cognitive variables. Physical fitness can be predicted by physical active behavior as well as by self-efficacy and the intensity of physical activity, and the latter by physical active behavior. Physical active behavior can be predicted by intention, self-efficacy, descriptive norms and barriers. Intention to engage in physical activity by attitude, self-efficacy, descriptive norms and barriers. An important input for lifestyle
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Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.
Phosphorus is an essential element for life, whether in the agricultural sector or in the chemical industry to make products such as flame retardants and batteries. Almost all the phosphorus we use are mined from phosphate rocks. Since Europe scarcely has any mine, we therefore depend on imported phosphate, which poses a risk of supply. To that effect, Europe has listed phosphate as one of its main critical raw materials. This creates a need for the search for alternative sources of phosphate such as wastewater, since most of the phosphate we use end up in our wastewater. Additionally, the direct discharge of wastewater with high concentration of phosphorus (typically > 50 ppb phosphorus) creates a range of environmental problems such as eutrophication . In this context, the Dutch start-up company, SusPhos, created a process to produce biobased flame retardants using phosphorus recovered from municipal wastewater. Flame retardants are often used in textiles, furniture, electronics, construction materials, to mention a few. They are important for safety reasons since they can help prevent or spread fires. Currently, almost all the phosphate flame retardants in the market are obtained from phosphate rocks, but SusPhos is changing this paradigm by being the first company to produce phosphate flame retardants from waste. The process developed by SusPhos to upcycle phosphate-rich streams to high-quality flame retardant can be considered to be in the TRL 5. The company seeks to move further to a TRL 7 via building and operating a demo-scale plant in 2021/2022. BioFlame proposes a collaboration between a SME (SusPhos), a ZZP (Willem Schipper Consultancy) and HBO institute group (Water Technology, NHL Stenden) to expand the available expertise and generate the necessary infrastructure to tackle this transition challenge.
CRYPTOPOLIS is a project supported by EU which focuses on the financial management knowledge of teachers and the emerging field of risk management and risk analysis of cryptocurrencies. Cryptocurrency has shown to be a vital and rapidly growing component in today’s digital economy therefore there is a need to include not just financial but also crypto literacy into the schools. Beside multiple investors and traders the market is attracting an increasing number of young individuals, viewing it as an easy way to make money. A large pool of teenagers and young adults want to hop on this train, but a lack of cryptocurrency literacy, as well as financial literacy in general amongst youth, together with their inexperience with investing makes them even more vulnerable to an already high-risk investment.Therefore, we aim to increase the capacity and readiness of secondary schools and higher educational institutions to manage an effective shift towards digital education in the field of crypto and financial literacy. The project will develop the purposeful use of digital technologies in financial and crypto education for teaching, learning, assessment and engagement.
