JMIR Research Protocols
The rising prevalence of mental health concerns among students is prompting universities to explore innovative solutions to support student well-being. This paper describes the protocol for the development, implementation, and evaluation of the Willo mobile app designed to address the mental health and wellness needs of students.
Stroke 2025Augmented reality enables visualization of and interaction with both physical and virtual environments. Holograms can allow 3‐dimensional image transmission to distant sites, allowing patients to interact with providers as if in the same space. Our prior publication resulted in high satisfaction/immersion for patients interacting with Holo‐Stroke providers. Our aim here was to determine if providers assessing computed tomographic angiographies (CTAs) for large vessel occlusion would result in reliability and satisfaction.
CHI 2025
Emergency Remote Teaching (ERT) during COVID-19 offered a unique chance to study online higher education at scale, beyond traditional lab settings. Through a review of 22 empirical studies, we analyzed how online classrooms addressed different types of interaction. Our findings highlight the need for future research that centers Learner-Content interaction as a way to balance flexibility with structure—especially as ERT may continue to shape education going forward.
Communications of the ACM 2025ACM’s membership and the broader computing field remain disproportionately skewed toward certain regions and demographics, with significant underrepresentation of women, racial minorities, and people with disabilities. As global demand for computing jobs rises, addressing these gaps becomes not just an equity issue but a workforce necessity. To help drive change, organizers of the UbiComp/ISWC 2023 conference implemented targeted programs to enhance diversity and inclusion. This article outlines those initiatives, their implementation costs, and their measured outcomes, offering lessons for fostering equity in international computing conferences.
CHI 2025
Trust in autonomous vehicles varies widely among individuals, and this study uses machine learning to identify the key factors influencing young adults’ trust. Surveying over 1,400 participants, the analysis reveals that perceptions of AV risks and benefits, usability attitudes, institutional trust, prior experience, and mental models are the strongest predictors of trust—while psychosocial traits and driving styles play a lesser role. These findings underscore the need to account for individual differences when designing trustworthy AV systems.
CHI 2025
Interdisciplinary engagement across disciplines is often hindered by stylistic and conceptual differences. Drawing on Large Language Models (LLMs), this work explores how metaphor-based support can improve accessibility and engagement. A survey of early-career HCI researchers found that metaphors increased interest in STS texts, particularly for those with limited prior exposure. We propose a dialogic model of metaphor exchange to support shared understanding and critical reflection across disciplines.
CHI 2025
Explanation errors from autonomous vehicles undermine user comfort, trust, and satisfaction—particularly in unfamiliar or non-routine driving contexts. Through a driving simulator study, the work shows that even subtle inaccuracies in how AVs communicate can erode user confidence, emphasizing the need for clear, context-aware explanations to foster reliable human-machine interaction.