Kuo-Ting Huang

Extended reality (XR) technologies promise new ways of working, learning, and socializing in immersive environments. Yet this future raises critical questions about who will benefit and who may be left behind. This chapter examines the assumption that expanding access to XR is inherently beneficial, using the digital divide as a framework to interrogate this belief. Although immersive technologies offer transformative potential across education, healthcare, and the workplace, their positive impact depends on more than access alone. To address this gap, the chapter introduces the concept of “immersive readiness” – a multidimensional construct encompassing motivational, skill-based, and contextual capacities required for meaningful and beneficial XR use. This chapter argues that insufficient attention to immersive readiness risks deepening existing social inequalities, producing what we term “immersive inequality” – defined as the unequal distribution of immersive readiness necessary to benefit from XR. The chapter outlines a central tension between accelerating XR adoption and ensuring that such adoption is safe, effective, and empowering. Through this lens, it chapter highlights the societal risks of deploying XR without adequate preparation and considers implications for key sectors. By reframing inclusion around immersive readiness, the chapter proposes a pathway toward an equitable XR future that democratizes experiences rather than widening digital divides.

US cancer survivors in rural areas face significant care disparities due to limited access to supportive oncology, and although digital interventions offer a potential solution, they must be intentionally adapted to avoid widening the rural‐urban divide. This commentary proposes a conceptual, technical, and pragmatic framework to guide the development of sustainable, community‐engaged digital health interventions tailored to the unique needs of rural oncology populations.

This study investigates the psychological outcomes of digital detox among graduate students, focusing on factors influencing future detox engagement and perceived lasting benefits. It examines how post-detox psychological changes in mood, anxiety, sleep, relationships, and productivity predict willingness to engage in future detox activities and perceptions of lasting benefits. It also considers how demographic factors and prior social media experiences shape these perceptions. Mood Management Theory was employed as a theoretical framework for understanding the willingness to engage in future digital detox and its lasting benefits. Data were collected through an online survey from 114 graduate students at an American public university, recruiting social media users who had voluntarily undergone a social media detox. The findings offer implications for developing programs and interventions aimed at enhancing mood, productivity, and promoting mindful social media use. These insights can help educators and academic librarians support students during digital detox and promote well-being.

Background: Virtual reality (VR) has emerged as a promising tool in medical education, particularly for fostering critical skills such as empathy. However, how VR, combined with perspective-taking, influences affective empathy in nursing education remains underexplored. Objective: This study investigates the influence of VR and perspective-taking on affective empathy in nursing education, focusing on 4 psychological factors: perceived self-location, narrative transportation, emotional engagement, and affective empathy. Methods: A 2×2 between-subjects design was used, involving 69 nursing undergraduates from two Midwest universities. The participants engaged with a narrative-focused video game, That Dragon, Cancer, in either VR or non-VR conditions and from the perspective of either parents or clinicians. Results: VR significantly enhanced perceived self-location (P=.01), while adopting a clinician’s perspective amplified emotional engagement (P=.03). However, VR did not significantly influence narrative transportation (P=.35). An interaction effect was found between the platform and player’s perspective on narrative transportation (P=.04). Several indirect effects of media elements on affective empathy were observed via other psychological factors, though the direct effect of VR on affective empathy was not significant (P=.84). Conclusions: These findings underscore the potential of VR in medical education, suggesting that perspective-taking should be carefully considered when designing immersive learning experiences. The study advocates for broader integration of VR technologies into medical curricula to enhance instruction quality and patient-centered care.

Introduction. The metaverse is shaped significantly by spatial computing technologies, such as virtual reality (VR). However, the promise of a VR-facilitated metaverse remains unfulfilled, and public perceptions of these technologies are fluid. Therefore, this study investigates perceptions and intentions to use VR over three years, both during and after the COVID-19 pandemic. Method. We conducted three waves of cross-sectional surveys from 2020 to 2022 (N = 928), via Amazon Mechanical Turk. Analysis. Data were analysed using OLS regression and mediation-moderation analysis using Hayes’ PROCESS Model 85. Results. Respondents' perceptions of VR as both easy to use and useful predict their intentions to use the technology, with usefulness being the stronger predictor. When examining changes over time, in 2021, VR ownership was not a predictor of perceived usefulness, and it was associated with a decrease in intentions to use VR, potentially reflecting the dynamics of the hype cycle. The direct and indirect effects of COVID-19 on VR acceptance persisted throughout all three years of the study but appear to be diminishing with time. Conclusions. This study contributes to the theoretical and practical discourse on the metaverse's development, advocating for a nuanced understanding of VR's role as a critical component of this digital frontier.

The use of Artificial Intelligence (AI) in healthcare, including in caring for cancer survivors, has gained significant interest. However, gaps remain in our understanding of how such AI systems can provide care, especially for ethnic and racial minority groups who continue to face care disparities. Through interviews with six cancer survivors, we identify critical gaps in current healthcare systems such as a lack of personalized care and insufficient cultural and linguistic accommodation. AI, when applied to care, was seen as a way to address these issues by enabling real-time, culturally aligned, and linguistically appropriate interactions. We also uncovered concerns about the implications of AI-driven personalization, such as data privacy, loss of human touch in caregiving, and the risk of echo chambers that limit exposure to diverse information. We conclude by discussing the trade-offs between AI-enhanced personalization and the need for structural changes in healthcare that go beyond technological solutions, leading us to argue that we should begin by asking, ''Why personalization?''

This study explores the integration of ChatGPT into library services, as well as the perceived benefits and challenges associated with its utilization. Through qualitative research methods, including semi-structured interviews with eleven health science librarians, insights were gained. The findings highlighted the challenge of building trust in the reliability and accuracy of ChatGPT, emphasizing the need for evaluation, monitoring, and addressing data privacy concerns. Integrating generative AI ChatGPT into library systems was found to enhance efficiency and assist patrons, but technical challenges such as glitches and downtime were reported. Librarians recognized the importance of caution and transparency when delivering ChatGPT-generated results to patrons. Balancing efficiency with accuracy and security emerged as a critical consideration. This study contributes to our understanding of the integration of generative AI in health science librarianship, providing insights that can inform future research and guide practical implementations in this field.

Social media detox is recognized as an effective strategy for mitigating the negative impacts of excessive social media usage. This study explores the factors influencing graduate students’ decisions to engage in social media detox. Factors related to social media overload and general social media experience were examined as potential predictors. Data were collected using an online survey from 179 graduate students who are active on social media. The results of the study revealed a high prevalence of social media overload among graduate students, with information overload emerging as the strongest predictor of social media detox. This suggests that effectively managing the constant influx of information on social media platforms is crucial for reducing stress and promoting digital well-being among graduate students. The study provides practical implications and further research directions for promoting digital well-being and enhancing information management skills.

Background: Telehealth has been widely adopted by patients during the COVID-19 pandemic. Many social determinants of health influence the adoption. Objective: This pilot study aimed to understand the social determinants of patients’ adoption of telehealth in the context of the pandemic. Methods: A survey methodology was used to capture data from 215 participants using Amazon Mechanical Turk. The study was guided by the technology acceptance model and the social determinants of health framework. The questionnaire included technology acceptance model variables (eg, perceived usefulness [PU] and perceived ease of use [PEOU]), social determinants (eg, access to health care, socioeconomic status, education, and health literacy), and demographic information (eg, age, sex, race, and ethnicity). A series of ordinary least squares regressions were conducted to analyze the data using SPSS Statistics (IBM Corp). Results: The results showed that social determinant factors—safe neighborhood and built environment (P=.01) and economic stability (P=.05)—are predictors of the PEOU of telehealth adoption at a statistically significant or marginally statistically significant level. Furthermore, a moderated mediation model (PROCESS model 85) was used to analyze the effects of COVID-19 on the neighborhood, built environment, and economic stability. PEOU and PU significantly positively affected users’ intention to use technology for both variables. Conclusions: This study draws attention to 2 research frameworks that address unequal access to health technologies. It also adds empirical evidence to telehealth research on the adoption of patient technology. Finally, regarding practical implications, this study will provide government agencies, health care organizations, and health care companies with a better perspective of patients’ digital health use. This will further guide them in designing better technology by considering factors such as social determinants of health.