Background: Modern modeling techniques may potentially provide more accurate predictions of dichotomous outcomes than classical techniques. Objective: In this study, we aimed to examine the predictive performance of eight modeling techniques to predict mortality by frailty. Methods: We performed a longitudinal study with a 7-year follow-up. The sample consisted of 479 Dutch community-dwelling people, aged 75 years and older. Frailty was assessed with the Tilburg Frailty Indicator (TFI), a self-report questionnaire. This questionnaire consists of eight physical, four psychological, and three social frailty components. The municipality of Roosendaal, a city in the Netherlands, provided the mortality dates. We compared modeling techniques, such as support vector machine (SVM), neural network (NN), random forest, and least absolute shrinkage and selection operator, as well as classical techniques, such as logistic regression, two Bayesian networks, and recursive partitioning (RP). The area under the receiver operating characteristic curve (AUROC) indicated the performance of the models. The models were validated using bootstrapping. Results: We found that the NN model had the best validated performance (AUROC=0.812), followed by the SVM model (AUROC=0.705). The other models had validated AUROC values below 0.700. The RP model had the lowest validated AUROC (0.605). The NN model had the highest optimism (0.156). The predictor variable “difficulty in walking” was important for all models. Conclusions: Because of the high optimism of the NN model, we prefer the SVM model for predicting mortality among community-dwelling older people using the TFI, with the addition of “gender” and “age” variables. External validation is a necessary step before applying the prediction models in a new setting.
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Artificial Intelligence (AI) offers organizations unprecedented opportunities. However, one of the risks of using AI is that its outcomes and inner workings are not intelligible. In industries where trust is critical, such as healthcare and finance, explainable AI (XAI) is a necessity. However, the implementation of XAI is not straightforward, as it requires addressing both technical and social aspects. Previous studies on XAI primarily focused on either technical or social aspects and lacked a practical perspective. This study aims to empirically examine the XAI related aspects faced by developers, users, and managers of AI systems during the development process of the AI system. To this end, a multiple case study was conducted in two Dutch financial services companies using four use cases. Our findings reveal a wide range of aspects that must be considered during XAI implementation, which we grouped and integrated into a conceptual model. This model helps practitioners to make informed decisions when developing XAI. We argue that the diversity of aspects to consider necessitates an XAI “by design” approach, especially in high-risk use cases in industries where the stakes are high such as finance, public services, and healthcare. As such, the conceptual model offers a taxonomy for method engineering of XAI related methods, techniques, and tools.
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The adoption of electric autonomous vehicles (EAVs) is set to revolutionize airport ground operations. Airports are increasingly developing new autonomous innovation strategies to meet sustainability goals and address future challenges, such as shifting labor markets, evolving working conditions, and the growing impact of digitalization [1]. The traditional business model, in which manufacturers sell vehicles to operators (ground handlers), may no longer be relevant. The increasing complexity and advancement of EAVs will drive up costs, making the ownership model less appealing and shifting the focus from product-oriented to service-oriented models. This paper aims to provide a conceptual framework for potential business models for the implementation of EAVs in airport airside operations.
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Abstract: Existing frailty models have enhanced research and practice; however, none of the models accounts for the perspective of older adults upon defining and operationalizing frailty. We aim to propose a mixed conceptual model that builds on the integral model while accounting for older adults’ perceptions and lived experiences of frailty. We conducted a traditional literature review to address frailty attributes, risk factors, consequences, perceptions, and lived experiences of older adults with frailty. Frailty attributes are vulnerability/susceptibility, aging, dynamic, complex, physical, psychological, and social. Frailty perceptions and lived experience themes/subthemes are refusing frailty labeling, being labeled “by others” as compared to “self-labeling”, from the perception of being frail towards acting as being frail, positive self-image, skepticism about frailty screening, communicating the term “frail”, and negative and positive impacts and experiences of frailty. Frailty risk factors are classified into socio-demographic, biological, physical, psychological/cognitive, behavioral, and situational/environmental factors. The consequences of frailty affect the individual, the caregiver/family, the healthcare sector, and society. The mixed conceptual model of frailty consists of interacting risk factors, interacting attributes surrounded by the older adult’s perception and lived experience, and interacting consequences at multiple levels. The mixed conceptual model provides a lens to qualify frailty in addition to quantifying it.
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BACKGROUND: Older adults want to preserve their health and autonomy and stay in their own home environment for as long as possible. This is also of interest to policy makers who try to cope with growing staff shortages and increasing health care expenses. Ambient assisted living (AAL) technologies can support the desire for independence and aging in place. However, the implementation of these technologies is much slower than expected. This has been attributed to the lack of focus on user acceptance and user needs.OBJECTIVE: The aim of this study is to develop a theoretically grounded understanding of the acceptance of AAL technologies among older adults and to compare the relative importance of different acceptance factors.METHODS: A conceptual model of AAL acceptance was developed using the theory of planned behavior as a theoretical starting point. A web-based survey of 1296 older adults was conducted in the Netherlands to validate the theoretical model. Structural equation modeling was used to analyze the hypothesized relationships.RESULTS: Our conceptual model showed a good fit with the observed data (root mean square error of approximation 0.04; standardized root mean square residual 0.06; comparative fit index 0.93; Tucker-Lewis index 0.92) and explained 69% of the variance in intention to use. All but 2 of the hypothesized paths were significant at the P<.001 level. Overall, older adults were relatively open to the idea of using AAL technologies in the future (mean 3.34, SD 0.73).CONCLUSIONS: This study contributes to a more user-centered and theoretically grounded discourse in AAL research. Understanding the underlying behavioral, normative, and control beliefs that contribute to the decision to use or reject AAL technologies helps developers to make informed design decisions based on users' needs and concerns. These insights on acceptance factors can be valuable for the broader field of eHealth development and implementation.
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Phd Thesis Higher professional education aims to prepare graduates for the complexity of professional practices. The development of conceptual understanding is important to deal adequately with this complexity, especially in an unstructured professional domain such as international business. The aim of this dissertation is to investigate the concept conceptual understanding in this professional domain, how it can be measured, what it looks like, how it changes, and in what ways it differs between students. The dissertation comprises five empirical studies for which data collection took place at a university of applied sciences in the Netherlands.
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We present the Stargazing Live! program comprising a planetarium experience and supporting lesson activities for pre-university physics education. The mobile planetarium aims to inspire and motivate learners using real telescope data during the experience. Learners then consolidate their learning by creating conceptual models in the DynaLearn software. During development of the program, content experts and stakeholders were consulted. Three conceptual model lesson activities have been created: star properties, star states and the fusion-gravity balance. The present paper evaluates the planetarium experience plus the star properties lesson activity in nine grade 11 and 12 classes across three secondary schools in the Netherlands. Learners are very positive about the planetarium experience, but they are less able to link the topics in the planetarium to the curriculum. The conceptual modelling activity improves the learners understanding of the causal relationship between the various stellar properties. Future work includes classroom testing of the star states and fusion-gravity balance lessons.
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Accurate modeling of end-users’ decision-making behavior is crucial for validating demand response (DR) policies. However, existing models usually represent the decision-making behavior as an optimization problem, neglecting the impact of human psychology on decisions. In this paper, we propose a Belief-Desire-Intention (BDI) agent model to model end-users’ decision-making under DR. This model has the ability to perceive environmental information, generate different power scheduling plans, and make decisions that align with its own interests. The key modeling capabilities of the proposed model have been validated in a household end-user with flexible loads
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Objectives: The aim of this scoping review was threefold: 1. to identify existing definitions of oral frailty and similar terms in gerodontology literature; 2. to assess the oral frailty definitions and analyze whether these are well formulated on a conceptual level; and 3. in the absence of existing definitions meeting the criteria for good conceptual definitions, a new conceptual definition of oral frailty will be presented. Methods: A search was performed in electronic databases and internet search engines. Studies explaining or defining oral frailty or similar terms were of interest. A software-aided procedure was performed to screen titles and abstracts and identify definitions of oral frailty and similar terms. We used a guide to assess the quality of the oral frailty definitions on methodological, linguistic, and content-related criteria. Results: Of the 1,528 screened articles, 47 full-texts were reviewed. Thirteen of these contained seven definitions of oral frailty and ten definitions of similar terms. We found that all definitions of oral frailty contain the same or equivalent characteristics used to define the concepts of ’oral health’, ’deterioration of oral function’, and ’oral hypofunction’. Between the seven definitions, oral frailty is described with a different number and combination of characteristics, resulting in a lack of conceptual consistency. None of the definitions of oral frailty met all criteria. Conclusion: According to our analysis, the current definitions of oral frailty cannot be considered ’good’ conceptual definitions. Therefore, we proposed a new conceptual definition: Oral frailty is the age-related functional decline of orofacial structures.
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The presentation of management information on screens and paper is aimed at the initiation of control actions in order to bring about predefinied goals. The terms and concepts used in this control information can be interptreted in different ways. It is of vital importance that adequate definitions for these terms and concepts are provided, because of the area of tension betrween those that control and those being controlled. The creation of a common conceptual framework and the maintenance of concepts and definitions can be supported by the construction of an organization-specific lexicon and the use of modern IT tools.
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