AN INVESTIGATION OF USER INTERFACE DESIGN AND DEVELOPMENT OF A MOBILE HEALTH SYSTEM FOR INDIVIDUALS WITH DEXTERITY IMPAIRMENTS

Mobile health (mHealth) systems have a great potential to empower individuals with chronic disease and disabilities to engage in preventive self-care. Before persons with disabilities can harness the potential of mhealth, the accessibility of mhealth systems should be addressed. An innovative mHealth system called iMHere (Internet Mobile Health and Rehabilitation) has been developed at the University of Pittsburgh to support self-care and adherence to self-care regimens for individuals with spina bifida and other complex conditions who are vulnerable to secondary complications. However, the existing design of the iMHere system was not designed to accommodate users with dexterity impairments. The overall goal of this research is to design and transform an existing mHealth system to make it more usable and accessible for users with dexterity impairment. To achieve this goal, three studies were conducted: Evaluation, Design and Development, and Validation of personalization and accessibility design in mobile health apps. The first study (Evaluation) was aimed to identify the barriers of the original iMHere apps to accessibility, and to explore the necessary features that may improve users’ experiences. The second study (Design and Development) was aimed to develop innovative designs to improve the accessibility and usability of the mHealth system. The third study (Validation) was aimed to evaluate the users’ acceptance of and preferences regarding the personalized and accessible mHealth services on a smartphone. The accessible design and development model that is presented in this dissertation incorporates user-interface components related to physical presentation (widgets, visual cues) and navigation (activity flow and layout order). Personalization that provides the ability for a user to modify the appearance of content, such as the size of the icons and the color of text, are proposed as an optimal solution to address potential issues and barriers to accessibility. The importance of personalization strategies for accessibility is also discussed

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

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

Data-driven Technology Foresight: Text Analysis of Emerging Technologies

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 산업·조선공학부, 2018. 2. 박용태.This dissertation argues for new directions in the field of technology foresight. Technology foresight was formulated on the basis of qualitative and participatory research. Initially, most foresight activities were triggered by the prospect of a handful number of experts, but recent studies highlight theoretical paradigm shifts toward a more comprehensive and data-driven approach to creating shared insights on the future of emerging technologies. Much of the research up to now, however, has been descriptive in nature, and a definite method of realizing the notion has not yet been addressed in the existing literature to a large extent. To this end, we have attempted to formalize the concept of data-driven technology foresight by incorporating unconventional data sources – future-oriented web data, Wikipedia data, and scientific publication data – and different analytical tools – Latent Semantic Analysis, IdeaGraph, and Morphological Analysis. Four distinct foresight frameworks were proposed for the proactive management process of emerging technologies: impact identification, impact analysis, plan development, and technology ideation. The study was guided by the following research questions: (1) what kinds of data sources are available on the web and which of those are considered useful in foresight studies? (2) Where could we incorporate these data sources and which techniques are most suitable for the given purposes? (3) Which foresight-related fields would particularly benefit from applying a data-driven approach and what are the positive effects? The proposals outlined should be considered exploratory and open-ended. It is designed to determine the nature of the problem, rather than to offer definitive and conclusive answers. Nevertheless, the proposed scheme may well provide not just a rationale but a theoretical grounding for this newly introduced notion. This dissertation is expected to yield a foothold for the readers to better comprehend and act on this new shift in the field of technology foresight.Chapter 1 Introduction 1 1.1 Emergence of Technology Foresight 1 1.2 Towards a Data-driven Technology Foresight 3 1.3 Problem Statement 6 1.4 Dissertation Overview 8 Chapter 2 Data Sources and Methodologies 15 2.1 Data Sources 15 2.1.1 Future-oriented Web Data 15 2.1.2 Wikipedia Data 17 2.1.3 Scientific Publication Data 19 2.2 Methodologies 21 2.2.1 Latent Semantic Analysis (LSA) 21 2.2.2 IdeaGraph 25 2.2.3 Morphological Analysis (MA) 29 Chapter 3 Foresight for Impact Identification 31 3.1 Introduction 32 3.2 Emerging Technology and its Social Impacts 36 3.2.1 Distinctive Nature of Emerging Technology 36 3.2.2 Technology Assessment 39 3.3 LSA for Constructing Scenarios 43 3.4 Research Framework 44 3.4.1 Step 1: Data Collection 46 3.4.2 Step 2: Scenario Development 49 3.4.2.1 Pre-LSA: Preprocessing Future-oriented Web Data 49 3.4.2.2 LSA: Applying Latent Semantic Analysis 52 3.4.2.3 Post-LSA: Constructing Scenarios 54 3.5 Illustrative Case Study: Drone Technology 55 3.6 Discussion 65 3.6.1 Categorization of Social Impacts 65 3.6.2 Comparative Analysis 72 3.6.3 Implication for Theory, Practice, and Policy 74 3.7 Conclusion 76 Chapter 4 Foresight for Impact Analysis 79 4.1 Introduction 80 4.2 Uncertainty and Complexity 82 4.3 Data-driven Foresight Process 84 4.4 Scenario Building Beyond the Obvious 86 4.4.1 Capturing Plausibility using LSA 90 4.4.2 Capturing Creativity using IdeaGraph 92 4.5 Research Framework 93 4.5.1 Step 1. Pre-Analysis: Data Preparation 94 4.5.1.1 Target Technology Selection 94 4.5.1.2 Data Acquisition 95 4.5.1.3 Data Preprocessing 95 4.5.2 Step 2. Text Analysis: Scenario Building 96 4.5.2.1 General Glimpse using Overt Structures 96 4.5.2.2 Hidden Details using Latent Structures 98 4.5.3 Step 3. Post-Analysis: Analytical Interpretation 101 4.5.3.1 Individual Impact Scenario 101 4.5.3.2 Overall Latent Impacts 101 4.6 Illustrative Case Study: 3D Printing Technology 102 4.7 Discussion 110 4.7.1 Scenarios Beyond the Obvious 110 4.7.2 Comparative Analysis 113 4.8 Conclusion 115 Chapter 5 Foresight for Plan Development 117 5.1 Introduction 118 5.2 Theoretical Paradigm Shift 120 5.2.1 Technology-focused vs. Society-focused 120 5.2.2 Co-evolution of Technology and Society 122 5.2.3 Responsible Development 125 5.3 Methodological Paradigm Shift 127 5.3.1 Participatory Approach 127 5.3.2 Data-driven Approach 129 5.4 Rationale for using LSA 131 5.5 Research Framework 132 5.5.1 Step 1. Envisioning Social Issues 133 5.5.1.1 Collection of Future-oriented Web Data 133 5.5.1.2 Construction of Impact Scenarios 135 5.5.1.3 Conceptualization of Impact Scenarios 137 5.5.2 Step 2. Deriving Technical Solutions 138 5.5.2.1 Collection of Scientific Publication Data 138 5.5.2.2 Construction of Solution Concepts 139 5.6 Illustrative Case Study: Autonomous Vehicle 140 5.7 Discussion 149 5.7.1 Comparative Analysis 149 5.7.2 Major Strengths in Envisioning Social Impacts 152 5.7.3 Major Strengths in Overviewing Solutions 154 5.8 Conclusion 156 Chapter 6 Foresight for Technology Ideation 158 6.1 Introduction 159 6.2 Related Studies 161 6.2.1 Generating Creative Ideas 161 6.2.2 Data-driven Morphological Analysis 163 6.3 Technology Foresight using Wikipedia 165 6.3.1 Wikipedia as a Good Remedy 165 6.3.2 Preliminaries: How to Apply Wikipedia 168 6.4 Research Framework 173 6.4.1 Basic Model 174 6.4.2 Extended Model 175 6.4.2.1 Phase 1: Preliminary Phase 177 6.4.2.2 Phase 2: Dimension Development Phase 177 6.4.2.3 Phase 3: Value Development Phase 179 6.4.2.4 Phase 4: Sub-dimension Development Phase 182 6.5 Illustrative Case Study: Drone Technology 183 6.5.1 Basic Model 183 6.5.2 Extended Model 185 6.6 Comparative Analysis 193 6.6.1 Experimental Setup 193 6.6.2 Comparison of Results 195 6.7 Intrinsic Limitations of Applying Wikipedia 199 6.8 Conclusion 201 Chapter 7 Concluding Remarks 203 Bibliography 211 Appendix 236 Appendix A Result of overt and latent structures of each impact scenario 236 Appendix B Result of Wikipedia-based morphological matrix (basic model) 240 Appendix C Result of Wikipedia-based morphological matrix using superordinate seed terms (extended model) 241 Appendix D Result of Wikipedia-based morphological matrix after applying subordinate value seed terms (extended model) 243 Appendix E Result of Wikipedia-based morphological matrix after developing sub-dimensions (extended model) 247Docto

The Largest Unethical Medical Experiment in Human History

This monograph describes the largest unethical medical experiment in human history: the implementation and operation of non-ionizing non-visible EMF radiation (hereafter called wireless radiation) infrastructure for communications, surveillance, weaponry, and other applications. It is unethical because it violates the key ethical medical experiment requirement for “informed consent” by the overwhelming majority of the participants. The monograph provides background on unethical medical research/experimentation, and frames the implementation of wireless radiation within that context. The monograph then identifies a wide spectrum of adverse effects of wireless radiation as reported in the premier biomedical literature for over seven decades. Even though many of these reported adverse effects are extremely severe, the true extent of their severity has been grossly underestimated. Most of the reported laboratory experiments that produced these effects are not reflective of the real-life environment in which wireless radiation operates. Many experiments do not include pulsing and modulation of the carrier signal, and most do not account for synergistic effects of other toxic stimuli acting in concert with the wireless radiation. These two additions greatly exacerbate the severity of the adverse effects from wireless radiation, and their neglect in current (and past) experimentation results in substantial under-estimation of the breadth and severity of adverse effects to be expected in a real-life situation. This lack of credible safety testing, combined with depriving the public of the opportunity to provide informed consent, contextualizes the wireless radiation infrastructure operation as an unethical medical experiment