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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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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A 4*4 PitStop is a metaphor for the work method or format used for a pop-up professional network. The method is designed to allow work, innovation and learning to go hand in hand. This format is based on the goals and direction provided by the participating professionals themselves. With this guide, we are sharing the results with professionals who want to start their own 4*4 PitStop.
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