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As many services convert to digital based on human-machine communication technology, older adults face considerable challenges. With the goal to identify ways to design digital services that are easier for older adults to use, this paper uses the strategy of making self-ordering kiosks more similar to the original version (i.e., paper menu) focusing on three familiarity design approaches: representation, manipulation, and organization. A 2 (skeuomorphic vs. flat design) x 2 (hierarchical vs. linear navigation structure) between-subject design experiment was conducted with individuals aged over 65 years (N = 60). Participants perceived that the skeuomorphic design was easier to use compared to the flat design, and the linear navigation structure increased perceived self-efficacy, usefulness, and intention to use compared to the hierarchical navigation structure. Participants also completed the tasks more quickly in the skeuomorphic design (vs. flat design) and linear navigation structure (vs. hierarchical structure) conditions. Interaction effects suggest that the task completion time was further reduced when skeuomorphic design was used with a linear navigation structure. Furthermore, fewer people requested assistance when they used a linear navigation structure. Serial multiple mediation results showed that the influence of linear navigation structure on intention to use was mediated by perceived self-efficacy and usefulness. • Skeuomorphic design offers better user experience for seniors than the flat one. • Linear navigation structure offers better user experience for seniors than the hierarchical one. • Combining skeuomorphism and linear structure decreases the task completion time. • The effect of linear navigation structure on intention to use is mediated by self-efficacy and perceived usefulness. [ABSTRACT FROM AUTHOR]

At present, ubiquitous learning has been becoming an important learning style for college students. However, the current studies on ubiquitous learning mostly focus on aspects such as communication and data interaction methods, while ignoring students' academic emotions. In this paper, we propose an individual adaptive ubiquitous learning paradigm that focuses on college students' academic emotions. The paradigm collects and analyses students' academic emotions to grasp student's individual characteristics. Then, the adaptive planning and adjusting learning contents is beneficial for improving students' academic emotions and enhancing the ubiquitous learning effects, initiative and concentration. In this study, the 2-year-long comparative experiments and tracking analyses were conducted from four aspects: academic grades, average study hours in after-school spare time, academic emotions status and classroom participation. The experimental results show that the individual adaptive ubiquitous learning paradigm proposed in this paper has significant positive effects and impacts on college students' learning outcomes, initiative, engagement and academic emotions. • An individual adaptive ubiquitous learning paradigm considering the impact of academic emotions is proposed. • The paradigm focuses on academic emotions to adaptively adjust individual learning content. • Academic emotions analysis and adjustment algorithms are designed to improve learning outcomes. [ABSTRACT FROM AUTHOR]

The increasing usage of social media networks has raised concerns about the growing frequency of cyberbullying incidents. The definition of cyberbullying lacks universal consensus, yet according to several authors, cyberbullying is characterized by aggressive, repetitive, and intentional communication among peers. However, existing cyberbullying detection datasets often focus solely on classifying texts as aggressive or non-aggressive, neglecting the other cyberbullying aspects, thus hindering research progress. This paper proposes a framework for designing a new dataset incorporating all four aspects of cyberbullying to address this gap. The text messages are sourced from a real dataset, while the users' data is generated synthetically. The resulting dataset contains messages exchanged randomly among different pairs of users, thus inculcating repetition. Additionally, the degree of peerness, defined and calculated to measure the likelihood of two users being peers, is used. The intent of harm is quantified as a numeric value using the ratios of aggression and repetition. As a result, the proposed dataset encompasses all four aspects of cyberbullying by providing repeated aggressive messages among users along with quantitative values of the degree of peerness and intent to harm. The proposed dataset is adaptable, with adjustable threshold values for peerness, repetition, and intent to harm, offering flexibility for various applications. The paper concludes by presenting the results of some baseline machine-learning methods on the proposed dataset. • Generation of a semi-synthetic dataset for automatic cyberbullying detection. • The dataset includes all aspects of cyberbullying: aggression, repetition, intent to harm, and occurrence among peers. • Presentation of baseline results on the proposed dataset. [ABSTRACT FROM AUTHOR]

This paper delves into the realm of virtual assistants (VAs) and their pivotal role in shaping user acceptance of voice shopping. VAs, initially tailored for voice interactions on smartphones, have permeated diverse consumer devices, revolutionizing user experience through conversational interfaces. However, the reluctance to embrace voice shopping persists due to safety apprehensions stemming from users' lack of confidence in VAs. The paper centers on anthropomorphism, emphasizing the human-like attributes of VAs, and its direct correlation with users' sense of safety. The study explores user perceptions of VAs in voice shopping, particularly focusing on anthropomorphic aspects like social presence, human-like voice, and friendliness. The investigation highlights their impact on perceived safety, word-of-mouth, and voice shopping acceptance. Analyzing prominent VAs—Alexa, Google Home, and Siri—the study identifies two fundamental factors influencing voice shopping acceptance: the humanity embedded in the VA's voice and the perceived safety it offers. Feeling secure during VA interactions significantly increases safety perception, fostering greater acceptance of VAs for shopping purposes. Additionally, the human-like qualities in the VA's voice positively influence users' perceived friendliness and safety, augmenting trust and overall acceptance of this technology. • The humanization of virtual assistants enables the generation of user confidence. • Perceived security in these assistants promotes active word-of-mouth transmission. • Perceived security enhances the intention to engage in voice shopping using virtual assistants. • The perceived humanity is manifested through the interplay of human-like voice, social presence, and friendliness. [ABSTRACT FROM AUTHOR]

Numerous studies have examined the utility of virtual reality (VR) technologies in the transportation and logistics sector. However, no systematic and comprehensive review of this research area has been performed. This need is addressed in this paper by reviewing publications on the development and applications of VR technologies in the four main categories of transportation and logistics: air, maritime, railway, and road. A clustering analysis of 200 papers on VR in transport and logistics published from 2010 to 2023 has been performed. It identifies six clusters of research: operator training in routine procedures, operator training in incident handling, simulation of carriers, design of traffic infrastructure and carriers, psychological studies on transportation and logistics operators or associated parties, and treatment of illness related to transportation and logistics. Based on the review and the clustering analysis, the paper proposes directions for future research on the development of VR and its applications in transportation and logistics. • A review of 200 peer-reviewed VR papers published from 2010 to 2023 is conducted. • The papers are from 4 main categories of logistics: air, marine, railway and road. • Six clusters of research are identified from a clustering analysis of the papers. • Directions for future VR research in transportation and logistics are proposed. [ABSTRACT FROM AUTHOR]

Social networking sites (SNSs) provide users with ample opportunities to share their own information and participate in social browsing to get to know others. Drawing upon signaling theory, this paper investigated how and to what extent recommendation letters' content information (breadth and depth) and external information (field and relationship) affect career mobility. Based on the open data from LinkedIn, this paper adopted the Latent Dirichlet Allocation (LDA) method to capture the breadth and depth of the recommendation letter, and used elaboration likelihood model to test our model. The results show that both content information and external information of the recommendation letter have significant positive impacts on the career mobility. In addition, the social network size shown converse moderating effects between recommendation letter content information and career mobility. This paper extends the boundaries of signaling theory by creatively using machine learning methods to measure textual signals (i.e., recommendation letter). The research results provide practical implications for personal career development and firm talent management. • The central and peripheral information of recommendation letter are positively related to career mobility. • Social network size has converse moderating effects on central information of recommendation letter and career mobility. • Machine learning method to measure the breadth and depth of recommendation letter. [ABSTRACT FROM AUTHOR]

Although the metaverse is still in the early stages of development and implementation, it has the potential to revolutionize the way how businesses can interact with customers through both the virtual and real world. In particular, service industries are already exploring the opportunity to utilize the metaverse to provide more immersive, interactive and engaging customer experiences. However, the holistic overview of the future applications, opportunities, and challenges of a metaverse in the context of service industries from academic and expert perspectives is limited. By employing a multi-perspective approach, this study looks into these unexplored aspects of the metaverse in the context of service industries through informed and multifaceted narratives by leading academics and experts from cross-disciplinary backgrounds from media and communication, education, hospitality, financial services, retail, tourism and healthcare. The main opportunities identified include the development of new experiences, the introduction of novel inter-world interactions, and new business-consumer relations within the metaverse. The key challenges covered include current technological boundaries, limitations of the experiences in the metaverse, health issues, and data privacy, security, and legal issues. The paper concludes with formulating future research agendas and presenting contributions to literature and implications for practice. • It explores future applications, opportunities, challenges, and research agenda of the metaverse in service industries. • Opportunities include new experiences development, novel inter-world interactions, and new business-consumer relations. • Key Challenges are technological boundaries, limited experiences, health, data privacy, security, and legal issues. • The paper concludes with formulating future research agendas and presenting contributions to literature and practice. [ABSTRACT FROM AUTHOR]

The buyer-seller relationship in live streaming commerce is crucial especially in service failure situations, yet it has been underexplored. In this paper, we reconceptualized the relationship between consumers and sellers in live streaming commerce as "parasocial guanxi", which consists of ganqing (emotional attachment), xinren (trust) and reciprocal value. The effects of parasocial guanxi on consumer dissatisfaction and complaint intention in service failure situations were further investigated based on the expectation confirmation theory. Our study involved 425 valid questionnaires and employed the partial least squares structural equation method (PLS-SEM). The findings are mixed: on one side, parasocial guanxi acts as a buffer, mitigating dissatisfaction and complaint intention in the face of product or service problems and reducing the impact of disconfirmation on consumer dissatisfaction. On the other side, it may also increase the likelihood of dissatisfied consumers complaining. Furthermore, the buffering effect weakens as consumers make more frequent purchases. The findings have important theoretical and practical implications for understanding the buyer-seller relationship in live streaming commerce. • This paper reconceptualized the buyer-seller relationship in live streaming commerce as "parasocial guanxi". • The effects of parasocial guanxi in service failure situations were investigated. • Parasocial guanxi has a buffering effect in alleviating consumers' dissatisfaction and complaint intention. • Meanwhile, parasocial guanxi can increase the likelihood of dissatisfied consumers to complain. • The effects of parasocial guanxi vary across different demographic groups. [ABSTRACT FROM AUTHOR]

Machine learning and learning analytics are powerful tools that not only support researchers in the detailed measurement and enhancement of learning processes in various learning environments, but also enable the aggregation and synthesis of evidence regarding effective educational practices. This paper describes the development and application of machine learning algorithms aimed at semi-automatic selection of abstracts for a meta-analysis on the effects of simulation-based learning in higher education. The goal was to reduce the workload while also maintaining the transparency and objectivity of the selection process. The algorithms were trained, validated, and tested on a set of 3187 studies on simulation-based learning found in medical and educational databases collected before April 2018. Subsequently, they were utilized to classify abstracts for a follow-up meta-analysis consisting of 2373 studies (published between 2018 and 2020). The aim of training the algorithms was to predict studies' abstract eligibility based on words and combinations of words used in these abstracts. The application of the algorithms reduced the number of studies that had to be manually screened from 2373 to 711. A total of 458 studies from automatically selected abstracts were included in the full-text screening, indicating the high precision of the algorithms (also compared to the performance of human raters). We conclude that machine learning algorithms can be trained and used to classify abstracts for their eligibility, significantly reducing the workload for the researchers without diminishing objectivity and quality when updating systematic literature reviews with or without a meta-analysis. • Machine learning algorithms can be used to classify abstracts for their eligibility. • Machine learning can significantly reduce the workload without compromising quality, when updating meta-analysis. • Some machine learning algorithms can outperform human raters in precision. [ABSTRACT FROM AUTHOR]

Workplace cyberbullying is a significant problem in higher education institutions. This paper examines faculty self-reports based on victimization, coping, gender, and the Big 5 Personality traits. A cross-sectional survey was distributed via Qualtrics to obtain the perceptions of 179 faculty members. Prevalence results indicated that faculty victims experienced cyberbullying from colleagues/peers, administrators, staff, students, and external members. Results also demonstrate that university faculty are unaware of resources to address cyberbullying. The study found evidence of gender differences in cyberbullying victimization in higher education. Agreeableness and neuroticism were also related to experiencing workplace cyberbullying. The article concludes with a discussion of the study's implications and potential areas of future research. • Most faculty experienced cyberbullying from colleagues/peers, administrators, and students. • Cyberbullied faculty are not likely to report the incident, which make it difficult to be addressed in the future. • Females are more likely to experience cyberbullying across relationship types in comparison to male faculty members. • The personality traits of agreeableness and neuroticism related to workplace cyberbullying. [ABSTRACT FROM AUTHOR]

Our contemporary society demands highly qualified professionals in all sectors, and education serves as the keystone for achieving this goal. While educational institutions are diligently preparing their students to thrive in this context, emphasizing inclusivity across all demographics is crucial. An essential group in this regard comprises students with Intellectual and Developmental Disabilities (IDDs), who require tailored tasks, content, and activities to facilitate their learning. A crucial consideration is facilitating their success in education, and in this context, Learning Analytics (LA) emerges as a potential solution. LA aims to optimize students' learning experiences by gathering and analyzing their data in order to facilitate better interventions. However, it is imperative to ascertain whether LA has been effectively utilized with IDD students. To address this issue, this research project proposes a Systematic Literature Review, considering six of the most relevant scientific works sources, and identifying 364 studies. These studies underwent meticulous filtering and evaluation, resulting in 28 records which specifically address the use of LA with IDD students. Insights gained from the review indicate that the application of LA in the learning experiences of IDD students is viable. However, it necessitates careful consideration of factors such as students' difficulties and special characteristics, learning contexts, and the available resources to construct effective learning interventions. • Students with intellectual and developmental disabilities (IDD) must be included in education and require adaptivity. • Learning Analytics (LA) has proven successful in diverse contexts and it could be applied to students with IDD. • Determining LA applicability for IDD students and exploring implementation necessitate a Systematic Literature Review. • An SLR is carried out with 6 relevant sources, 364 imported and 28 selected papers that show LA application is possible. • LA facilitates the learning adaptions in activities, contents, environments and feedback for students with IDD. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the influence of various advertising channels on consumers' value perceptions of luxury brands, with a specific focus on the potential negative effects of TikTok on luxury advertising. Using an experimental design, four studies were conducted to rigorously examine these research questions. Study 1 reveals that, compared to traditional media, TikTok advertising has a more adverse impact on consumers' value perceptions of luxury brands. In Study 2, the mediating role of psychological distance is identified as the underlying mechanism explaining how media types in luxury advertising affect value perceptions. Study 3(a) highlights significant disparities in the number of online reviews and "likes" for different review types. Additionally, Study 3(b) discovers that self-deprecating online reviews can significantly increase the value perception of luxury brands on TikTok. This study contributes both theoretically and practically to the field of luxury marketing management, offering insights into the nuanced dynamics of luxury advertising across diverse media channels. Furthermore, it provides valuable suggestions for future research within the realm of luxury marketing, particularly in the context of social media. • Advertising on TikTok may diminish consumers' value perceptions of luxury brands. • Psychological distance explains TikTok's negative effects on value perception. • TikTok users prefer exploring self-deprecating reviews, when watching luxury ads. • Self-deprecating reviews enhance TikTok users' value perception of luxury brands. [ABSTRACT FROM AUTHOR]

Most prior work on online reviews assumes that the value of reviews for consumers lies only in providing information about the product or the consumer's experience with the product. Yet, consumers also post and interact with pseudo-reviews, defined as reviews that describe exaggerated product experiences while trying to be entertaining. To address the nature and consequences of pseudo-reviews, this study develops a framework for understanding their value and how they affect consumer decision-making. First, we define how pseudo-reviews differ from other types of reviews. Then, we empirically examine how pseudo-reviews moderate the relationship between online review valence (how positive or negative the review is) and purchase intention. Finally, using a dual-processing theoretical lens, we examine how pseudo-reviews affect consumer decision-making through systematic and affective processing. We test our model through two experiments. The first study finds that pseudo-reviews reduce the impact of review valence on purchase intention when compared to genuine reviews. The second study shows that pseudo-reviews affect uncertainty and amusement, and these, in turn, affect purchase intention. We discuss the implications of pseudo-reviews for theory and practice. • Previous studies on online reviews often ignore the amusement value of online reviews. • The paper focuses on pseudo-reviews and develops a framework to understand their influence on consumer decisions. • For positive reviews, pseudo-reviews decrease the positive effect of review valence on purchase intention. • Pseudo-reviews affect consumer decisions by increasing both uncertainty and amusement. [ABSTRACT FROM AUTHOR]

This paper examines the use of Augmented Reality Smart Glasses (ARSGs) in order-picking tasks in warehouses and explores their impact on workers' well-being. While previous research has primarily focused on the performance advantages of ARSGs, this study provides a new perspective by investigating the human factor and perceptions of worker well-being in two empirical studies. The results corroborate previous findings that ARSGs enhance order-picking efficiency by improving workers' speed and reducing error rates. Additionally, the results reveal that using ARSGs directly increases perceptions of well-being compared to traditional support tools. However, contrary to expectations, ARSG use does not generally lead to higher job satisfaction or perceived productivity enhancements for all workers. Technology savviness is identified as a crucial individual factor that shapes these effects, with tech-savvy workers benefiting more from ARSG use. Overall, this research underscores the importance of tailoring ARSG implementation to the specific needs and characteristics of the workforce and highlights the need for further investigation into the beneficiaries of ARSG technology. • Augmented reality smart glasses (ARSGs) improve efficiency in order-picking tasks, enhancing speed and reducing error rates. • ARSG use directly increases workers' perceptions of well-being compared to traditional support tools. • This is driven by increased job satisfaction and perceived productivity, but only for workers with high technology savviness. [ABSTRACT FROM AUTHOR]

While the study of offline prosocial behavior has a long tradition, much less information is available about how these behaviors manifest and change in the digital environment, and little is known about their background. This paper evaluates differences by age and gender in a variety of attitudes and beliefs during adolescence and studies their influence on the online prosocial behavior emitted and received. A cross-sectional study was performed with 1299 participants aged between 14 and 20 from the Region of Madrid (Spain). The Spanish adaptation of the Online Prosocial Behavior Scale and a selection of items from various studies on attitudes and beliefs regarding altruism, direct and indirect reciprocity, social responsibility, and the perception of the subjective norm were administered. The results suggest that female adolescents maintain higher altruism, social responsibility, and indirect reciprocity than males, and that the older age group (18–20 years old) has higher scores in altruism, social responsibility, and direct reciprocity. Together with altruism, the subjective norm, social responsibility, and indirect reciprocity positively influence the online prosocial behavior emitted by adolescents. Indirect reciprocity, the subjective norm and altruism also influence the feeling of receiving online prosocial behaviors from others. Knowing the extent to which adolescents hold prosocial beliefs and which of these beliefs may favor prosocial online behaviors can be beneficial when promoting such beliefs and fostering more positive online conduct, as well as lessening cyberbullying, online hate and any other manifestation of aggressive behavior online. • Social networks constitute a space for the socialization of prosocial behavior in adolescence. • Beliefs about altruism, social responsibility, and indirect reciprocity favor the emission of online prosocial behavior. • Beliefs about altruism and indirect reciprocity favor greater perception of receiving prosocial behaviors online. • The prosocial subjective norm favors both the emission and reception of online prosocial behaviors. • Direct reciprocity does not seem to influence the emission and reception of online prosocial behaviors. [ABSTRACT FROM AUTHOR]

Augmented Reality (AR) is an emerging concept that impacts many disciplines, such as business, marketing, tourism, gaming, human–computer interaction, and manufacturing. Surprisingly, many scholarly and practical discussions overlook the fundamental primary factors that distinguish AR from other concepts, namely, that it involves a computing device that integrates virtual content into a consumer's perception of the real world in a specific context. The current article addresses this gap in the literature by proposing the 4C framework (based on the 4Cs: consumer, content, context, and computing device; pronounced: foresee) that highlights the importance of, and interplay among these four factors. Building on configurational theory, the framework calls for the systematic identification of additional AR-relevant factors across the 4Cs. Scholars can use this framework to systematically identify research gaps and variables of interest. Practitioners across various disciplines can employ the framework to systematically assess, communicate, and develop AR use cases. • The 4C framework highlights four unique characteristics of AR: Consumer, Content, Context, and Computing Device. • Engagement with AR derives from an alignment of the 4 Cs. • The paper advances theory by using the lens of complexity theory to explain how to engage consumers in AR experiences. • The framework offers significant implications for managers and scholars. • It allows systematic approaches to assess, communicate, and develop AR applications across various disciplines. [ABSTRACT FROM AUTHOR]

Over the last decade, Educational Data Mining (EDM) and Learning Analytics (LA) have evolved enormously as interrelated research areas and disciplines. Many researchers interested in these areas may wonder why there are two different communities, whether they are the same concept or not, and the differences between them, which is key information for designing their research and publication strategies. To address this, we conducted a systematic review of academic papers about the differences between LA and EDM following the Preferred Reporting Method for Systematic Reviews (PRISMA) guidelines. We selected 10 research works and identified 11 differences. Our conclusions are that, although both use the same data and share similar goals and interests, EDM and LA are different research communities with different origins and focuses, with their respective conferences and journals. However, there is active collaboration between the two communities and their members often tend to publish in both fields' conferences and journals. Additionally, none of the differences are apparently large enough to conclude that LA and EDM follow different paths for improving the teaching-learning process, but rather the opposite. Following a common future line, it seems that the two "sister" communities are working together with the same perspective, along with some "cousin" communities such as AIED (Artificial Intelligence in Education), L@S (Learning at Scale), Learning Science (LS), etc. in the same area that could be called Educational Data Science (EDS). We propose using the term EDS to integrate both LA and EDM with all these related communities. [Display omitted] • Educational Data Mining (EDM) and Learning Analytics (LA) are interrelated and sometimes interchanged terms. • Five original differences between EDM and LA have been identified. • Other six new differences have emerged since these initial five differences. • The term Educational Data Science (EDS) is proposed to integrate EDM and LA. [ABSTRACT FROM AUTHOR]

Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its roots in two theoretical models of the comprehension process (i.e., the Construction-Integration model and the Landscape model), and the new version leverages state-of-the-art Large Language models, more specifically ChatGPT, to have a better contextualization of the text and a simplified construction of the underlying graph model. Besides showcasing the usage of the model, the study introduces three in-depth psychological validations that argue for the model's adequacy in modeling reading comprehension. In these studies, we demonstrated that AMoC is in line with the theoretical background proposed by the Construction-Integration and Landscape models, and it is better at replicating results from previous human psychological experiments than its predecessor. Thus, AMoC v4.0 can be further used as an educational tool to, for example, help teachers design better learning materials personalized for student profiles. Additionally, we release the code from AMoC v4.0 as open source in a Google Collab Notebook and a GitHub repository. • Introduce the Automated Model of Comprehension version 4.0 that integrates state-of-the-art Large Language models - ChatGPT. • Perform 3 in-depth psychological validation studies to support the model's adequacy in modeling reading comprehension. • AMoC v4.0 aligns with theoretical frameworks, namely Construction-Integration and Landscape models. • The model outperforms its predecessor and replicates results from human psychological experiments. • AMoC v4.0 can serve as an educational tool for designing personalized learning materials. [ABSTRACT FROM AUTHOR]

Burnout among esports players is a serious issue affecting competitive and professional players. The present study investigated the relationship between resilience, coping, and burnout among esports players using network analysis. Esports players (N = 453; M age = 23.0 years, SD = 4.18; in the top 40% of in-game rank) who competed in one of seven popular team-based esports completed the Connor-Davidson Resilience Scale (CD-RISC-10), Coping Functions Questionnaire (CFQ; assessing problem-focused, emotion-focused, and avoidance coping), and Athlete Burnout Scale (ABO-S; assessing a reduced sense of accomplishment, physical exhaustion, and negative feelings towards esport). Responses were assessed with Least Absolute Shrinkage and Selection Operator regularised partial correlations (EBICglasso). Findings showed a distinct network of resilience factors, coping skills, and symptoms of burnout. More specifically, resilience factors were negatively associated with symptoms of burnout and positively associated with problem-focused, emotion-focused, and avoidance coping. Problem-focused coping had a strong expected influence on the network and was positively associated with multiple resilience factors. Moreover, avoidance coping had a strong influence on the network but was positively associated with multiple symptoms of burnout. Finally, a reduced sense of accomplishment (burnout) was negatively associated with multiple resilience factors and positively associated with avoidance coping. The combined results of the present study suggest that resilience and coping are important factors for understanding burnout among esports players. • This is the first paper to use a Network Analysis to explore burnout, resilience, and coping among esports players. • Resilience factors were negatively associated with symptoms of burnout. • Resilience factors were positively associated with problem-focused coping. • Avoidance coping was positively associated with symptoms of burnout. [ABSTRACT FROM AUTHOR]

As social robots are increasingly designed with sophisticated simulations of human skills, it becomes essential to understand boundary conditions of people's engagement of them as mindful actors. The present paper reports a comprehensive secondary analysis of six studies (total N = 967) on the relationship between mind perception (evaluation of mental capacities) and mind ascription (explicit assignment of a mind-having status) when people consider a humanoid robot in different scenarios. Results indicate there is a context-independent, moderate link between perceptions of affective mental capacity (i.e., ability to feel emotion) and explicit mind ascription. We further found hints for a weak relationship between perceptions of reality-interaction capacity (i.e., sensory and agentic abilities) and decisions to ascribe mind that may need larger samples in order to be validated. Perceptions of social-moral capacities (i.e., evaluations of people and goals) were not a significant predictor of mind ascription. Overall, these findings highlight the pivotal role played by robots' display of affective engagement with the world for the acceptance of robots as mindful "beings" in human spheres. • Mind perception in robots does not mean people assign them a mindful being status. • Dimensionality of mind perception allows for various drivers of mind ascription. • Six studies uniformly show that perceived affective capacity is the primary correlate. • Perceptions of basic but not higher-order agency may be a secondary correlate. • Long-established position of denied mindfulness in robots is called into question. [ABSTRACT FROM AUTHOR]

Avatars and social robots offer new opportunities for communication and raise questions about how trust is built and maintained in hybrid social interactions. We wonder what kind of trust people build with these technologies, especially where they are no longer simply tools but rather partners in interactions and affective exchanges involving vulnerability and reciprocity. Following the PRISMA guidelines, we conducted a systematic review on how trust in humans and technology can be shaped by social touch, which is the bodily contact occurring between two or more parties that express and share affective signals. Based on the n = 15 papers that meet the inclusion criteria, the evidence on the power of social touch to facilitate trust appears limited. Especially in the realm of technology-mediated interactions, mixed and inconclusive results emerge in different social contexts. Individual differences and neurophysiological correlates that could shed light on the effects between touch and trust are rarely investigated. Our positive proposal is that future studies should overcome the divisive conceptualisation of trustor and trustee, and rather explore the phenomenon of trust as a two-person bridge built in synergy between the parties. Outlining some key directions for future research, we discuss the extant solutions and applications of technology-mediated social touch, delving into the sensory and contextual factors that make it similar but different to unmediated social touch. We propose that if social touch were to be effective in promoting trust in specific technologies, this would have important consequences on various application domains such as telecommunication, healthcare, and education. • Trust in a specific technology is crucial when the technology is not only a tool but also a social partner. • Social touch has the power to make us feel connected to others and potentially help us build trust. • Evidence on the effects of mediated or unmediated social touch on trust is limited, mixed and inconclusive. • Future research on mediated interactions should delve into the sensory and contextual aspects of social touch to boost trust. • We need new ways of interacting through mediated social touch, tailored to the specificities of technology and human parties. [ABSTRACT FROM AUTHOR]

Every day we trust other individuals as we engage in social interactions in which various desirable outcomes depend on others acting the way we hope, or they have indicated. Trust extends beyond specific individuals, however, as we might trust unknown others – individuals, institutions, corporations, and governments. Some also say that we trust various artifacts, such as machines. But what is the basis of trust, and can we really trust technology? Trust is intimately connected to the notion ethos from the study of rhetoric and human persuasion, which is often used to describe various characteristics of the speaker, the audience, the relationship between the speaker and the audience, and the wider context in which communication and interaction occurs. In this article I explore to what degree machines can be considered to have ethos, and consequently whether ethos is a useful concept for understanding persuasive and credibility-related situations in HMI and by extension key aspects of human-machine trust. This allows us to draw on a long lineage of research from, for example, rhetoric, communication studies, and cognitive and social psychology to better understand the usefulness – or not – of using the notion of trust to describe our relationship with machines. • Trust in machines partly parallels trust in humans, institutions, and artifacts. • Ethos, from rhetoric, relates to credibility and trust in human-machine interaction. • This paper explores if machines can have ethos, and how this relates to trust. • Machine ethos is about perceived credibility and not the machine's ethics. • Examining ethos enriches understanding of trust and design in HMI. [ABSTRACT FROM AUTHOR]

In recent years, university students have reported increased symptoms of stress and anxiety, which can negatively impact their mental well-being and academic performance. However, many students do not seek or receive support for these challenges. With recent technological advances in intelligent agents and their expanding capabilities, there is a potential for intelligent agents to extend and complement mental health care interventions and enhance access to care. Recognizing that there are many further steps to developing user-centred evidence-based approaches for mental health challenges, as a first step to developing effective interventions using intelligent agents, it is important to identify design elements and functionalities that are perceived as engaging and useful by students. In this paper, we present the findings of an online survey with 1054 undergraduate students to explore students' perceptions of, and preferences for, using different types of intelligent agents (e.g., virtual agents, social robots, etc.) to support their mental well-being, specifically to cope with feelings of stress and anxiety in social situations typically encountered within a university context (e.g., engaging in a group discussion, delivering presentations, expressing opinions, etc.). Students were asked to complete a questionnaire to explore their experience of stress and anxiety in the university context, as well as their perceptions of, and preferences for using different intelligent agents as assistive tools to cope with such feelings. The results provide insights into different design elements as well as social and technical capabilities to consider when designing intelligent agents to help address stress and anxiety among university students. • We surveyed 1054 undergraduate students on using intelligent agents to manage anxiety. • Public speaking was reported as the most anxiety-provoking situation at university. • Students preferred animal-like robots and conversational agents to cope with anxiety. • Intelligent agents would help manage anxiety by providing personalized coaching. • We discuss design implications for intelligent agents supporting students' anxiety. [ABSTRACT FROM AUTHOR]

With the exponential growth of new technology, it is timely that social psychologists continue to develop new and effective solutions to old but existing problems, including prejudice. One such solution is virtual reality (VR). This critical review examines VR as a promising new media tool to reduce prejudice and improve intergroup relations. Unlike traditional prejudice reduction strategies, VR provides researchers with a high degree of experimental control and flexibility. However, VR prejudice reduction research is in its infancy, and a myriad of challenges have emerged, including the: i) difficulty of cross-study comparisons and navigation of existing literature due to lack of standardized VR methodologies; ii) limitations of adapting traditional prejudice reduction strategies into VR; and iii) the lack of measurement of behaviors. This paper critically evaluates each of these limitations and, in doing so, proposes a new working framework incorporating two dimensions, the: i) VR input device, and ii) level of interactivity and mobility in the VR environment. This framework attempts to address the lack of standardization of immersion and presence in current VR research by helping guide future VR researchers to better identify the type of research they are conducting, evaluate existing research findings, and thus make cross-comparisons in VR prejudice reduction findings more meaningful. • Highlights three main limitations of current VR prejudice reduction strategies. • Conceptual framework is developed to standardize the immersion and presence in VR. • Solutions to address the limitations of VR prejudice research is proposed. • Call attention to the importance of VR as a research tool to measure prejudice. • Future directions of VR prejudice reduction research are outlined. [ABSTRACT FROM AUTHOR]