Smartphone Application-based Medical Devices: Twenty-first Century Data Democratization or Anarchy?

Self-Testing for Dementia: A Phenomenological Analysis of Fear

Following the growing economic relevance of mobile health (mHealth) and the increasing global prevalence of dementia, self-testing apps for dementia and mild neurocognitive disorder (MCD) have been developed and advertised. The apps' promise of a quick and easy tool has been criticized in the literature from a variety of angles, but as we argue in this article, the celebratory characterization of self-testing also stands in disbalance to the various kinds of fears that may be connected to taking the test. By drawing on Sara Ahmed's phenomenological theory on emotions and by referring to illustrative experiences from two users with a particular dementia self-testing app, we explore four dimensions of fear derived from phenomenology: performative, ontological, embodied, and temporal dimensions. We argue that fear (1) motivates one to take the self-test and to try to take control over one's health; (2) is shaped by and shapes the ways in which we make sense of ourselves and others as cognitively deficient; (3) constructs and is constructed by our differently embodied presence in the world; and that (4) testing makes a fearful future self as cognitively deficient more tangible. In outlining these different dimensions of fear, this article expands the understanding of the meaning of experiencing self-testing in comparison to the mostly quantitative literature on this topic.

Towards a Democratization of Data in the Context of Industry 4.0

Data-driven transparency in end-to-end operations in real-time is seen as a key benefit of the fourth industrial revolution. In the context of a factory, it enables fast and precise diagnoses and corrections of deviations and, thus, contributes to the idea of an agile enterprise. Since a factory is a complex socio-technical system, multiple technical, organizational and cultural capabilities need to be established and aligned. In recent studies, the underlying broad accessibility of data and corresponding analytics tools are called “data democratization”. In this study, we examine the status quo of the relevant capabilities for data democratization in the manufacturing industry. (1) and outline the way forward. (2) The insights are based on 259 studies on the digital maturity of factories from multiple industries and regions of the world using the acatech Industrie 4.0 Maturity Index as a framework. For this work, a subset of the data was selected. (3) As a result, the examined factories show a lack of capabilities across all dimensions of the framework (IT systems, resources, organizational structure, culture). (4) Thus, we conclude that the outlined implementation approach needs to comprise the technical backbone for a data pipeline as well as capability building and an organizational transformation.

Mobile learning acceptance in social distancing during the COVID-19 outbreak: The mediation effect of hedonic motivation

M‐learning is a trending field in educational organizations, companies, and also for individual study. However, in some regions the ampleness of the phenomenon is not quantifiable or comparable due to the lack of an adequate framework and reliable metrics. Our research intends to make a little light by assessing the degree of m‐learning adoption in students at a moment when face‐to‐face education moved suddenly online due to the COVID‐19 outbreak's rapid and unpredictable spread. A new model relying on the Unified Theory of Acceptance and Use of Technology (UTAUT) was built to investigate and explain relationships between constructs. It reveals the key factors affecting technology adoption by considering hedonic motivation a mediator instead of an exogenous variable as in UTAUT2. Based on an analysis of 311 higher education learners, the way how performance expectancy, effort expectancy, social influence, and facilitating conditions influence directly or indirectly the behavioral intention is researched. The analysis was conducted employing partial least squares structural equation modeling. The strongest relationship is between hedonic motivation and behavioral intention followed by the one between perceived effectiveness and hedonic motivation. Age, gender, and experience moderate the model's relationships. Research contributes to theory development by successfully adjusting the original UTAUT model. Results indicate that universities may offer learners an enjoyable m‐learning experience by activating social support groups and inserting gameplay elements into the learning system.

Development and Usability Testing of the Society for Pediatric Anesthesia Pedi Crisis Mobile Application

When life-threatening, critical events occur in the operating room, the fast-paced, high-distraction atmosphere often leaves little time to think or deliberate about management options. Success depends on applying a team approach to quickly implement well-rehearsed, systematic, evidence-based assessment and treatment protocols. Mobile devices offer resources for readily accessible, easily updatable information that can be invaluable during perioperative critical events. We developed a mobile device version of the Society for Pediatric Anesthesia 26 Pediatric Crisis paper checklists-the Pedi Crisis 2.0 application-as a resource to support clinician responses to pediatric perioperative life-threatening critical events. Human factors expertise and principles were applied to maximize usability, such as by clustering information into themes that clinicians utilize when accessing cognitive aids during critical events. The electronic environment allowed us to feature optional diagnostic support, optimized navigation, weight-based dosing, critical institution-specific phone numbers pertinent to emergency response, and accessibility for those who want larger font sizes. The design and functionality of the application were optimized for clinician use in real time during actual critical events, and it can also be used for self-study or review. Beta usability testing of the application was conducted with a convenience sample of clinicians at 9 institutions in 2 countries and showed that participants were able to find information quickly and as expected. In addition, clinicians rated the application as slightly above "excellent" overall on an established measure, the Systems Usability Scale, which is a 10-item, widely used and validated Likert scale created to assess usability for a variety of situations. The application can be downloaded, at no cost, for iOS devices from the Apple App Store and for Android devices from the Google Play Store. The processes and principles used in its development are readily applicable to the development of future mobile and electronic applications for the field of anesthesiology.