Digital Human Representations for Health Behavior Change: A Structured Literature Review

Organizations have increasingly begun using digital human representations (DHRs), such as avatars and embodied agents, to deliver health behavior change interventions (BCIs) that target modifiable risk factors in the smoking, nutrition, alcohol overconsumption, and physical inactivity (SNAP) domain. We conducted a structured literature review of 60 papers from the computing, health, and psychology literatures to investigate how DHRs’ social design affects whether BCIs succeed. Specifically, we analyzed how differences in social cues that DHRs use affect user psychology and how this can support or hinder different intervention functions. Building on established frameworks from the human-computer interaction and BCI literatures, we structure extant knowledge that can guide efforts to design future DHR-delivered BCIs. We conclude that we need more field studies to better understand the temporal dynamics and the mid-term and long-term effects of DHR social design on user perception and intervention outcomes

Determining the effect of human cognitive biases in social robots for human-robotm interactions

The research presented in this thesis describes a model for aiding human-robot interactions based on the principle of showing behaviours which are created based on 'human' cognitive biases by a robot in human-robot interactions. The aim of this work is to study how cognitive biases can affect human-robot interactions in the long term. Currently, most human-robot interactions are based on a set of well-ordered and structured rules, which repeat regardless of the person or social situation. This trend tends to provide an unrealistic interaction, which can make difficult for humans to relate ‘naturally’ with the social robot after a number of relations. The main focus of these interactions is that the social robot shows a very structured set of behaviours and, as such, acts unnaturally and mechanical in terms of social interactions. On the other hand, fallible behaviours (e.g. forgetfulness, inability to understand other’ emotions, bragging, blaming others) are common behaviours in humans and can be seen in regular social interactions. Some of these fallible behaviours are caused by the various cognitive biases. Researchers studied and developed various humanlike skills (e.g. personality, emotions expressions, traits) in social robots to make their behaviours more humanlike, and as a result, social robots can perform various humanlike actions, such as walking, talking, gazing or emotional expression. But common human behaviours such as forgetfulness, inability to understand other emotions, bragging or blaming are not present in the current social robots; such behaviours which exist and influence people have not been explored in social robots. The study presented in this thesis developed five cognitive biases in three different robots in four separate experiments to understand the influences of such cognitive biases in human–robot interactions. The results show that participants initially liked to interact with the robot with cognitive biased behaviours more than the robot without such behaviours. In my first two experiments, the robots (e.g., ERWIN, MyKeepon) interacted with the participants using a single bias (i.e., misattribution and empathy gap) cognitive biases accordingly, and participants enjoyed the interactions using such bias effects: for example, forgetfulness, source confusions, always showing exaggerated happiness or sadness and so on in the robots. In my later experiments, participants interacted with the robot (e.g., MARC) three times, with a time interval between two interactions, and results show that the likeness the interactions where the robot shows biased behaviours decreases less than the interactions where the robot did not show any biased behaviours. In the current thesis, I describe the investigations of these traits of forgetfulness, the inability to understand others’ emotions, and bragging and blaming behaviours, which are influenced by cognitive biases, and I also analyse people’s responses to robots displaying such biased behaviours in human–robot interactions

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

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

Feature Papers "Age-Friendly Cities & Communities: State of the Art and Future Perspectives"

The "Age-Friendly Cities & Communities: States of the Art and Future Perspectives" publication presents contemporary, innovative, and insightful narratives, debates, and frameworks based on an international collection of papers from scholars spanning the fields of gerontology, social sciences, architecture, computer science, and gerontechnology. This extensive collection of papers aims to move the narrative and debates forward in this interdisciplinary field of age-friendly cities and communities

Independent Aging with the Help of Smart Technology:Investigating the Acceptance of Ambient Assisted Living Technologies

Who takes care of our older adults? According to the European Union, smart technologies that support independent living and active aging, introduced as ‘Ambient Assisted Living’ (AAL), are the future for our aging population. Promises of AAL include saving long-term care costs, improving the quality of care, unburdening family caregivers, and increasing the older adults’ independence and overall quality of life. While the policy enthusiasm for AAL technology is high, it is unclear if the potential users of AAL are willing to embrace AAL technologies in their daily lives. This dissertation addressed this issue by focusing on the perspective of older adults and their caregivers. Using a combination of qualitative and quantitative approaches, we developed a comprehensive and theoretically grounded understanding of how and why users perceive AAL technologies in a certain way. Important factors that drive or hinder the acceptance were identified. These insights resulted in a model of AAL acceptance that was validated in a representative sample (n = 1296) of the Dutch older adult population. This dissertation contributes to a more user-driven approach in AAL research and development and has important implications for researchers, developers and policy makers alike. We hope that our results will guide future research efforts, design and policy directions in the AAL field

Children\u27s Susceptibility to Television Advertising: A Behavioral Test of Cognition and Attitude

Television\u27s alleged effects on children have been the object of considerable debate since the early 1950\u27s. The effects of television commercials, however, have been the focus of only a handful of studies. According to recent FCC figures, television commercials now comprise 20 percent--12 minutes or more per hour--of television broadcast content (Johnson, 1973). Earlier figures reported by Steiner (1963) placed commercials as the third largest content category on television, following movies and comedy-variety, but ahead of action dramas and eight other programming categories. Although content emphasis may have changed over the decade, e.g. an increase in action dramas, advertising is still a paramount content category occupying one-fifth of air time. At today\u27s viewing levels, this means the average child is exposed to approximately 100 television commercials per day (Action for Children\u27s Television, 1971)

Sustainable Value Co-Creation in Welfare Service Ecosystems : Transforming temporary collaboration projects into permanent resource integration

The aim of this paper is to discuss the unexploited forces of user-orientation and shared responsibility to promote sustainable value co-creation during service innovation projects in welfare service ecosystems. The framework is based on the theoretical field of public service logic (PSL) and our thesis is that service innovation seriously requires a user-oriented approach, and that such an approach enables resource integration based on the service-user’s needs and lifeworld. In our findings, we identify prerequisites and opportunities of collaborative service innovation projects in order to transform these projects into sustainable resource integration once they have ended

Technology and Australia's Future: New technologies and their role in Australia's security, cultural, democratic, social and economic systems

Chapter 1. Introducing technology -- Chapter 2. The shaping of technology -- Chapter 3. Prediction of future technologies -- Chapter 4. The impacts of technology -- Chapter 5. Meanings, attitudes and behaviour -- Chapter 6. Evaluation -- Chapter 7. Intervention -- Conclusion - adapt or wither.This report was commisioned by Australian Council of Learned Academies