Health symptoms may be influenced, supported, or even controlled via a lighting control system which includes personal lighting conditions and personal factors (health characteristics). In order to be effective, this lighting control system requires both continuous information on the lighting and health conditions at the individual level. A new practical method to determine these continuous personal lighting conditions has been developed: location-bound estimations (LBE). This method was validated in the field in two case studies; comparisons were made between the LBE and location-bound measurements (LBM) in case study 1 and between the LBE and person-bound measurements (PBM) in case study 2. Overall, the relative deviation between the LBE and LBM was less than 15%, whereas the relative deviation between the LBE and PBM was 32.9% in the best-case situation. The relative deviation depends on inaccuracies in both methods (i.e., LBE and PBM) and needs further research. Adding more input parameters to the predictive model (LBE) will improve the accuracy of the LBE. The proposed first approach of the LBE is not without limitations; however, it is expected that this practical method will be a pragmatic approach of inserting personal lighting conditions into lighting control systems.
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Research demonstrated a large variety regarding effects of light (e.g. health, performance, or comfort effects). Since human health is related to each individual separately, the lighting conditions around these individuals should be analysed individually as well. This paper provides, based on a literature study, an overview identifying the currently used methodologies for measuring lighting conditions in light effect studies. 22 eligible articles were analysed and this resulted in two overview tables regarding the light measurement methodologies. In 70% of the papers, no measurement details were reported. In addition, light measurements were often averaged over time (in 84% of the papers) or location level (in 32% of the papers) whereas it is recommended to use continuous personal lighting conditions when light effects are being investigated. Conclusions drawn in light effect studies based on personal lighting conditions may be more trusting and valuable to be used as input for an effect-driven lighting control system.
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Background: Advanced statistical modeling techniques may help predict health outcomes. However, it is not the case that these modeling techniques always outperform traditional techniques such as regression techniques. In this study, external validation was carried out for five modeling strategies for the prediction of the disability of community-dwelling older people in the Netherlands. Methods: We analyzed data from five studies consisting of community-dwelling older people in the Netherlands. For the prediction of the total disability score as measured with the Groningen Activity Restriction Scale (GARS), we used fourteen predictors as measured with the Tilburg Frailty Indicator (TFI). Both the TFI and the GARS are self-report questionnaires. For the modeling, five statistical modeling techniques were evaluated: general linear model (GLM), support vector machine (SVM), neural net (NN), recursive partitioning (RP), and random forest (RF). Each model was developed on one of the five data sets and then applied to each of the four remaining data sets. We assessed the performance of the models with calibration characteristics, the correlation coefficient, and the root of the mean squared error. Results: The models GLM, SVM, RP, and RF showed satisfactory performance characteristics when validated on the validation data sets. All models showed poor performance characteristics for the deviating data set both for development and validation due to the deviating baseline characteristics compared to those of the other data sets. Conclusion: The performance of four models (GLM, SVM, RP, RF) on the development data sets was satisfactory. This was also the case for the validation data sets, except when these models were developed on the deviating data set. The NN models showed a much worse performance on the validation data sets than on the development data sets.
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The Nutri-Score front-of-pack label, which classifies the nutritional quality of products in one of 5 classes (A to E), is one of the main candidates for standardized front-of-pack labeling in the EU. The algorithm underpinning the Nutri-Score label is derived from the Food Standard Agency (FSA) nutrient profile model, originally a binary model developed to regulate the marketing of foods to children in the UK. This review describes the development and validation process of the Nutri-Score algorithm. While the Nutri-Score label is one of the most studied front-of-pack labels in the EU, its validity and applicability in the European context is still undetermined. For several European countries, content validity (i.e., ability to rank foods according to healthfulness) has been evaluated. Studies showed Nutri-Score's ability to classify foods across the board of the total food supply, but did not show the actual healthfulness of products within different classes. Convergent validity (i.e., ability to categorize products in a similar way as other systems such as dietary guidelines) was assessed with the French dietary guidelines; further adaptations of the Nutri-Score algorithm seem needed to ensure alignment with food-based dietary guidelines across the EU. Predictive validity (i.e., ability to predict disease risk when applied to population dietary data) could be re-assessed after adaptations are made to the algorithm. Currently, seven countries have implemented or aim to implement Nutri-Score. These countries appointed an international scientific committee to evaluate Nutri-Score, its underlying algorithm and its applicability in a European context. With this review, we hope to contribute to the scientific and political discussions with respect to nutrition labeling in the EU.
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The objective of this study is to investigate the heart rate (HR) accuracy measured at the wrist with the photoplethysmography (PPG) technique with a Fitbit Charge 2 (Fitbit Inc) in wheelchair users with spinal cord injury, how the activity intensity affects the HR accuracy, and whether this HR accuracy is affected by lesion level.
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This chapter presents the currently not established and identifies design requirements for new systems to address this challenge and provide directions for possible improvement. As a result, this chapter introduces the concept of SamenMarkt®, a participatory system in which multi-agent system technology enables distributed price negotiation, distribution and communication between producers, retailers and consumers.
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This research investigates the integration of stakeholders' values into the digital frameworks of Collective Management Organizations (CMOs) within the Dutch music copyright system. Utilizing Q methodology, the study captures diverse perspectives from composers, lyricists, publishers, and CMO representatives on values, value tensions, norms, and system requirements. A pilot study with four experts tested data collection methods and refined the study design for a larger, follow-up study involving 30 participants. Preliminary findings, based on factor analysis of participant rankings of 30 statements, reveal two distinct perspectives: one focused on "Fairness and Accountability," emphasizing trust-building and equitable treatment, and the other on "Technological Efficiency and Transparency," prioritizing clear information, verification mechanisms, and advanced IT systems. Qualitative insights from participant interviews provide nuanced understanding, highlighting the importance of transparency in royalty processes, balanced application of technology, and equitable royalty distribution in the digital age. This research contributes to the modernization of copyright management systems offering a conceptual model adaptable to other creative (Intellectual Property) industries
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Background: Digital health is well-positioned in low and middle-income countries (LMICs) to revolutionize health care due, in part, to increasing mobile phone access and internet connectivity. This paper evaluates the underlying factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Objective: The objective of this study is to identify the current digital health projects and studies being carried out in Pakistan, as well as the key stakeholders involved in these initiatives. We aim to follow a mixed-methods strategy and to evaluate these projects and studies through a strengths, weaknesses, opportunities, and threats (SWOT) analysis to identify the internal and external factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Methods: This study aims to evaluate digital health projects carried out in the last 5 years in Pakistan with mixed methods. The qualitative and quantitative data obtained from field surveys were categorized according to the World Health Organization’s (WHO) recommended building blocks for health systems research, and the data were analyzed using a SWOT analysis strategy. Results: Of the digital health projects carried out in the last 5 years in Pakistan, 51 are studied. Of these projects, 46% (23/51) used technology for conducting research, 30% (15/51) used technology for implementation, and 12% (6/51) used technology for app development. The health domains targeted were general health (23/51, 46%), immunization (13/51, 26%), and diagnostics (5/51, 10%). Smartphones and devices were used in 55% (28/51) of the interventions, and 59% (30/51) of projects included plans for scaling up. Artificial intelligence (AI) or machine learning (ML) was used in 31% (16/51) of projects, and 74% (38/51) of interventions were being evaluated. The barriers faced by developers during the implementation phase included the populations’ inability to use the technology or mobile phones in 21% (11/51) of projects, costs in 16% (8/51) of projects, and privacy concerns in 12% (6/51) of projects.
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Valuation judgement bias has been a research topic for several years due to its proclaimed effect on valuation accuracy. However, little is known on the emphasis of literature on judgement bias, with regard to, for instance, research methodologies, research context and robustness of research evidence. A synthesis of available research will establish consistency in the current knowledge base on valuer judgement, identify future research opportunities and support decision-making policy by educational and regulatory stakeholders how to cope with judgement bias. This article therefore, provides a systematic review of empirical research on real estate valuer judgement over the last 30 years. Based on a number of inclusion and exclusion criteria, we have systematically analysed 32 relevant papers on valuation judgement bias. Although we find some consistency in evidence, we also find the underlying research to be biased; the methodology adopted is dominated by a quantitative approach; research context is skewed by timing and origination; and research evidence seems fragmented and needs replication. In order to obtain a deeper understanding of valuation judgement processes and thus extend the current knowledge base, we advocate more use of qualitative research methods and scholars to adopt an interpretative paradigm when studying judgement behaviour.
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Background: Increasing health literacy (HL) in children could be an opportunity for a more health literate future generation. The aim of this scoping review is to provide an overview of how HL is conceptualized and described in the context of health promotion in 9–12-year-old children. Methods: A systematic and comprehensive search for ‘health literacy’ and ‘children’ and ‘measure’ was performed in accordance with PRISMA ScR in PubMed, Embase.com and via Ebsco in CINAHL, APA PsycInfo and ERIC. Two reviewers independently screened titles and abstracts and evaluated full-text publications regarding eligibility. Data was extracted systematically, and the extracted descriptions of HL were analyzed qualitatively using deductive analysis based on previously published HL definitions. Results: The search provided 5,401 original titles, of which 26 eligible publications were included. We found a wide variation of descriptions of learning outcomes as well as competencies for HL. Most HL descriptions could be linked to commonly used definitions of HL in the literature, and some combined several HL dimensions. The descriptions varied between HL dimensions and were not always relevant to health promotion. The educational setting plays a prominent role in HL regarding health promotion. Conclusion: The description of HL is truly diverse and complex encompassing a wide range of topics. We recommend adopting a comprehensive and integrated approach to describe HL dimensions, particularly in the context of health promotion for children. By considering the diverse dimensions of HL and its integration within educational programs, children can learn HL skills and competencies from an early age.
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