Abstract Purpose: This study aimed to establish which determinants had an effect on frailty among acutely admitted patients, where frailty was identified at discharge. In particular, our study focused on associations of sex with frailty. Methods: A cross-sectional study was designed using a sample of 1267 people aged 65 years or older. The Tilburg Frailty Indicator (TFI), a user-friendly self-report questionnaire was used to measure multidimensional frailty (physical, psychological, social) and determinants of frailty (sex, age, marital status, education, income, lifestyle, life events, multimorbidity). Results: The mean age of the participants was 76.8 years (SD 7.5; range 65-100). The bivariate regression analyses showed that all determinants were associated with total and physical frailty, and six determinants were associated with psychological and social frailty. Using multiple linear regression analyses, the explained variances differed from 3.5% (psychological frailty) to 20.1% (social frailty), with p values < 0.001. Of the independent variables age, income, lifestyle, life events, and multimorbidity were associated with three frailty variables, after controlling for all the other variables in the model. At the level of both frailty domains and components, females appeared to be more frail than men. Conclusion: The present study showed that sociodemographic characteristics (sex, age, marital status, education, income), lifestyle, life events, and multimorbidity had a different effect on total frailty and its domains (physical, psychological, social) in a sample of acute admitted patients.
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Purpose: To examine the development of multidimensional frailty, including physical, psychological and socialcomponents, over a period of seven years. To determine the effects of sociodemographic factors (gender, age, marital status, education, income) on the development of frailty. Methods: : This longitudinal study was conducted in sample of 479 community-dwelling people aged ≥ 75 years living in the municipality of Roosendaal, the Netherlands. The Tilburg Frailty Indicator (TFI), a self-report questionnaire, was used to collect data about frailty. Frailty was assessed annually. Results: : Frailty increased significantly over seven years among the people who completed the entire TFI all years (n = 121), the average score was 3.75 (SD 2.80) at baseline and 5.05 (SD 3.18) after seven years. Regarding frailty transitions, most participants remained unchanged from their baseline status. The transition from non-frail to frail was present in 8.3% to 12.6% of the participants and 5.1% to 10.7% made a transition from frail to nonfrail. Gender (woman), age (≥80 years), marital status (not married/cohabiting), high level of education, and incomes from €601-€1800 were significantly associated with a higher frailty score. Conclusion: : This study showed that multidimensional frailty, assessed with the TFI, increased among Dutch community-dwelling people aged ≥75 years using a follow-up of seven years. Gender, age, marital status, education, and income were associated with frailty transitions. These findings provide healthcare professionals clues to identify people at increased risk of frailty, and target interventions which aim to prevent or delay frailty and its adverse outcomes, such as disability and mortality.
The recently introduced Risk SituatiOn Awareness Provision (RiskSOAP) methodology suggested an indicator to measure the distance between the configuration of a real system and its ideal version or between various system versions. It considers the (in)existence or (mal)functioning of system components, processes and connections based on a binary approach. However, in practice safety requirements can be fulfilled to some degree and each system component might have a different impact on system outcomes. This work suggests the Comparing System Configurations (COSYCO) indicator which introduces (1) the use of continuous values for the behaviour of system components, (2) the inclusion of weights according to the hierarchal system level to which each component belongs, and (3) the consideration of the outgoing connections of each component with other system components. Both RiskSOAP and COSYCO are based on the STPA hazard analysis which is a systematic technique used to define the components and the requirements that the system should ideally meet to achieve its objectives. To demonstrate the applicability and sensitivity of COSYCO, we applied it to a published case for small drones. Drones with same overall differences in the satisfaction of requirements concluded to different values when applying COSYCO, indicating the increased sensitivity of the specific indicator when compared to the RiskSOAP. We envisage that the metric proposed in this work is a first practical and realistic approach to the quantification of the distance between the optimal design and current system states as well amongst various systems and their versions over time.
De glastuinbouw in Nederland is wereldwijd toonaangevend en loopt voorop in automatisering en data-gedreven bedrijfsvoering. Voor de data-gedreven teelt wordt, naast het monitoren van de kas-parameters ook het monitoren van gewasparameters steeds meer gevraagd. De sector is daarbij vooral geïnteresseerd in niet-destructieve, contactloze en persoonsonafhankelijk monitoring van gewassen. Optische sensortechnologie, zoals spectrale afbeeldingstechnologie, kan veel waardevolle informatie opleveren over de staat van een gewas of vrucht, bijvoorbeeld over het suikergehalte, maar ook de aanwezigheid van plantziektes of insecten. Echter is dit vaak een te kostbare oplossing voor zowel de technologiebedrijven die oplossingen leveren als voor de telers zelf. In dit project onderzoeken wij de mogelijkheid om spectrale beeldvorming tegen lagere kosten te realiseren. Het beoogde resultaat is een prototype van een instrument dat tegen lage kosten met spectrale beeldvorming een of meerdere gewaseigenschappen kan kwantificeren. Realisatie van dit prototype heeft een sterke Fotonica-component (expertise Haagse Hogeschool) maakt gebruik van Machine Learning (expertise perClass) en is bedoeld voor toepassing op scout robots in de glastuinbouw (expertise Mythronics). Een betaalbare oplossing betekent in potentie voor de teler een betere controle over kwaliteit van het gewas en automatisering voor detectie van ziekte-uitbraken. Bij een succesvol prototype kan deze innovatie leiden tot betere voedselkwaliteit en minder verspilling in de glastuinbouw.
The overall purpose of this consultancy was to support the activities under the Environmental Monitoring and Assessment Programme of the UN Economic Commission for Europe (UNECE) in developing the 7th pan-European environmental assessment, an indicator based and thematic assessment, implemented jointly with the United Nations Environment Programme (UNEP) and in support of the 2030 Agenda for Sustainable Development. The series of environmental assessments of the pan-European region provide up to-date and policy-relevant information on the interactions between the environment and society. This consultancy was to:> Draft the input on drivers and developments to chapter 1.2 of the assessment related to the environmental theme “4.2 Applying principles of circular economy to sustainable tourism”.> Suggest to UNECE and UNEP the most policy relevant indicators from UNECE-environmental, SDG indicators and from other indicator frameworks such as EEA or OECD for the environmental theme for the sub-chapter 4.2.> Assess the current state, trends and recent developments and prepare the substantive part of sub-chapter 4.2 (summary - part I) and an annex (part II) with the detailed analysis and findings.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
