54 research outputs found

    The fungal skin microbiota of healty and dermatoses-affected areas in HIV-positive and HIV-negative children

    Get PDF
    The purpose of the study is to investigate the Candida, Malassezia, Saccharomyces, and Debaryomyces species composition in dermatoses-affected and healthy skin samples from HIV-positive and HIV-negative children.Цель исследования – изучить видовой состав грибов рода Candida, Malassezia, Saccharomyces и Debaryomyces в соскобах с участков кожи, пораженных дерматозом, и неизмененных у ВИЧ-положительных и ВИЧ-отрицательных детей

    Care robots in residential homes for elderly people: an ethical examination of deception, care, and consent

    Get PDF
    We are facing a dire social problem: although life expectancy is increasing, time spent living independently is not, meaning that the eldercare sector is experiencing a worrying shortfall of nursing staff - a problem which is only getting worse. Robots designed for caring purposes – carebots – present a possible solution: they can perform some of the work which has been hitherto undertaken by human nurses. But their introduction is not without problems. This thesis examines some pertinent questions relating to the introduction of carebots into residential homes for elderly people. Chapter 1 examines what robots are, and provides a way in which we can differentiate between robots of different types, helping us to understand what ethical issues are at stake for different types of robot. Chapter 2 focuses on what deception consists of, and discusses why deception and lying are often seen as impermissible. Chapter 3 discusses different types of robo-deception, and analyses both the likelihood and the normative significance of their occurring. Chapter 4 is a study of a particular form of robo-deception, which I call fake compassion. This is when robots appear to care for patients when in fact they do not: I examine the extent to which this is morally problematic. Chapter 5 examines dignity: what it is, and why it is important. Chapter 6 focuses on consent: its importance in different spheres, and how consent-seeking can promote autonomy, bodily integrity, dignity, and trust. Chapter 7 builds on the previous two chapters, and demonstrates that it is ethically essential that carebots (and human nurses) obtain patients' consent prior to providing care, because failing to do so can reduce their dignity, and these reductions can be cumulative and devastating. This thesis is not merely an interesting thought experiment or a work of science fiction; rather, it is a real-world necessity that carebots take appropriate actions which promote the dignity and best interests of patients: our grandparents, parents, and in time, us and our descendants

    Unveiling AI Aversion: Understanding Antecedents and Task Complexity Effects

    Get PDF
    Artificial Intelligence (AI) has generated significant interest due to its potential to augment human intelligence. However, user attitudes towards AI are diverse, with some individuals embracing it enthusiastically while others harbor concerns and actively avoid its use. This two essays\u27 dissertation explores the reasons behind user aversion to AI. In the first essay, I develop a concise research model to explain users\u27 AI aversion based on the theory of effective use and the adaptive structuration theory. I then employ an online experiment to test my hypotheses empirically. The multigroup analysis by Structural Equation Modeling shows that users\u27 perceptions of human dissimilarity, AI bias, and social influence strongly drive AI aversion. Moreover, I find a significant difference between the simple and the complex task groups. This study reveals why users avert using AI by systematically examining the factors related to technology, user, task, and environment, thus making a significant contribution to the emerging field of AI aversion research. Next, while trust and distrust have been recognized as influential factors shaping users\u27 attitudes towards IT artifacts, their intricate relationship with task characteristics and their impact on AI aversion remains largely unexplored. In my second essay, I conduct an online randomized controlled experiment on Amazon Mechanical Turk to bridge this critical research gap. My comprehensive analytic approach, including structural equation modeling (SEM), ANOVA, and PROCESS conditional analysis, allowed me to shed light on the intricate web of factors influencing users\u27 AI aversion. I discovered that distrust and trust mediate between task complexity and AI aversion. Moreover, this study unveiled intriguing differences in these mediated relationships between subjective and objective task groups. Specifically, my findings demonstrate that, for objective tasks, task complexity can significantly increase aversion by reducing trust and significantly decrease aversion by reducing distrust. In contrast, for subjective tasks, task complexity only significantly increases aversion by enhancing distrust. By considering various task characteristics and recognizing trust and distrust as vital mediators, my research not only pushes the boundaries of the human-AI literature but also significantly contributes to the field of AI aversion

    Robots in Nursing - False Rhetoric or Future Reality?: How might robots contribute to hospital nursing in the future? A qualitative study of the perspectives of roboticists and nurses

    Get PDF
    Introduction. The challenge of the global nursing shortage coupled with a rising healthcare demand prompts consideration of technology as a potential solution. Technology in the form of robots is being developed for healthcare applications but the potential role in nursing has not been researched in the UK. Methods A three-phased qualitative study was undertaken: interviews with 5 robotic developers (Phase 1); nine focus groups /interviews with 25 hospital Registered Nurses (RN) in Phase 2, and 12 nurse leaders in four focus groups (Phase 3). Data was analysed using framework analysis for Phase 1 and reflexive thematic analysis for Phase 2 and 3 data based on the Fundamentals of Care framework. Results Roboticist interviews confirmed that a taxonomy of potential robotic automation was a useful tool for discussing the role of robots. In Phase 2, RNs described activities that robots might undertake and commented on those which they should not. RNs more readily agreed that robots could assist with physical activities than relational activities. Six potential roles that robots might undertake in future nursing practice were identified from the data and which have been labelled as advanced machine, social companion, responsive runner, helpful co-worker, proxy nurse bot, and feared substitute. Three cross-cutting themes were identified: • a fear of the future; • a negotiated reality and • a positive opportunity. In phase 3, nurse leaders considered the RN results and four themes were identified from their discussions: • First impressions of robot in nursing; • The essence of nursing; • We must do something and • Reframing the future. Conclusions Robots will be a future reality in nursing, playing an assistive role. Nursing must become technically proficient and engage with the development and testing of robots. Nurse leaders must lead policy development and reframe the narrative from substitution to assistance. A number of navigational tools have been developed including a taxonomy of nursing automation and the six robotic roles which may be useful to inform future debate in nursing

    Examining Cognitive Empathy Elements within AI Chatbots for Healthcare Systems

    Get PDF
    Empathy is an essential part of communication in healthcare. It is a multidimensional concept and the two key dimensions: emotional and cognitive empathy allow clinicians to understand a patient’s situation, reasoning, and feelings clearly (Mercer and Reynolds, 2002). As artificial intelligence (AI) is increasingly being used in healthcare for many routine tasks, accurate diagnoses, and complex treatment plans, it is becoming more crucial to incorporate clinical empathy into patient-faced AI systems. Unless patients perceive that the AI is understanding their situation, the communication between patient and AI may not sustain efficiently. AI may not really exhibit any emotional empathy at present, but it has the capability to exhibit cognitive empathy by communicating how it can understand patients’ reasoning, perspectives, and point of view. In my dissertation, I examine this issue across three separate lab experiments and one interview study. At first, I developed AI Cognitive Empathy Scale (AICES) and tested all empathy (emotional and cognitive) components together in a simulated scenario against control for patient-AI interaction for diagnosis purposes. In the second experiment, I tested the empathy components separately against control in different simulated scenarios. I identified six cognitive empathy elements from the interview study with first-time mothers, two of these elements were unique from the past literature. In the final lab experiment, I tested different cognitive empathy components separately based on the results from the interview study in simulated scenarios to examine which element emerges as the most effective. Finally, I developed a conceptual model of cognitive empathy for patient-AI interaction connecting the past literature and the observations from my studies. Overall, cognitive empathy elements show promise to create a shared understanding in patients-AI communication that may lead to increased patient satisfaction and willingness to use AI systems for initial diagnosis purposes

    Development and evaluation of a novel virtual agent-based app for patients with colorectal cancer: A mixed methods study

    Get PDF
    Background and aim: Information support is an integral part of cancer care, but its provision can be problematic in busy health settings. The aim of this project was to develop and evaluate a health app to facilitate the provision of information support in newly diagnosed patients with colorectal cancer (CRC). Instead of delivering information using text, three animated embodied virtual agents (VAs) were deployed. The VAs were formulated after patients’ treating clinicians (male oncologist, female nurse and female pharmacist) to explore the role of familiarity, which has not been addressed in previous research. Study methods: A multi-stage development process was followed for the app, which was provided to the study participants before the beginning of their treatment. A convergent parallel mixed methods design involving pre- and post-exposure questionnaires (adapted versions of the Toronto Information Needs Questionnaire and the System Usability Scale), app usage data and semi-structured interviews was deployed to evaluate the intervention. Results and discussion: The app was acceptable by the end users and had a good degree of usability (mean System Usability Scale score=73.89). The information content was appropriate and met patients’ demands to a moderate extent; this was because patients utilised other information sources (e.g., printed material) to address their needs. Incorporating supportive functions such as a medicinal calendar in addition to the information content emerged as an important aspect. The inclusion of VAs was deemed to be appropriate. The VAs fostered a sense of presence, added trustworthiness to the information content and were perceived as more interactive than reading text. Having a VA representing a familiar clinician was favoured by most users. The vast majority of patients perceived the VAs as cartoon figures and suggested that they should be improved to look realistic in order to give the impression of having an exchange with a real person. Natural voices were preferred over synthetic speech. Conclusion: VA-based mHealth interventions are an acceptable way of supporting patients with CRC. Appropriate consideration should be given to the requirements of the intended user audience to design acceptable interventions that reflect their needs
    corecore