Senshu University

要旨 【目的】 メディカルラリーはチーム医療や多職種連携を体験的に学ぶシミュレーション教育である。本研究では，メディカルラリー参加前後でのアンケートを通じて，医療系学生における救急医療への興味や多職種連携への理解に及ぼす教育的効果を検証した。 【方法】 参加学生110名のうち，事前・事後アンケートに回答した45名を対象とした。アンケートでは，「救急医療への興味」，「他職種の役割や知識・技術の理解」，「他職種との連携の必要性」を5段階リッカート尺度で調査し，参加前後の変化を評価した。 【結果】 「他職種の役割や知識・技術の理解」では，肯定的回答が34%から51%に増加し，否定的回答は42%から7%に減少した。一方，「救急医療への興味」および「多職種連携の必要性」については，有意な変化を認めなかった。 【結語】 メディカルラリーは，多職種連携の理解を深める有効な教育手法であることが示唆された。一方で，救急医療に対する興味の変化は限定的であり，その教育効果をより正確に評価するためには，対象層や募集方法を考慮した検討が必要である。

ABSTRACT User incentives influence decision‐making in credit markets; however, the influence of incentives on the credit relevance of International Financial Reporting Standards (IFRS) remains unexplored. This study examines how competition among credit rating agencies in Japan, where firms can choose between single or multiple ratings when issuing bonds, shapes their incentives. The findings reveal that competition‐driven incentives to build and maintain reputational capital enhance agencies' efforts to gather, process, and effectively use IFRS data. This study highlights the role of user incentives, particularly those arising from competition, in shaping the impact of IFRS adoption on credit markets.

We propose Interactive-SmartClerk, a robot system that recommends items to first-time customers by emulating a store clerk. Providing satisfactory recommendations to first-time customers is challenging because of the cold-start problem: prior knowledge of their preferences is limited. Interactive-SmartClerk addresses this problem by asking customers about their preferences for a small number of items. Even with only a few preference samples, the system can recommend items that match a customer’s tastes. In particular, it can capture individual preferences that diverge from general trends, enabling recommendations that differ from current trends. In this study, we configured Interactive-SmartClerk to recommend three dresses from a dataset of 100 dress images. We collected preference data from 647 participants via crowdsourcing. Evaluation showed that Interactive-SmartClerk outperformed a baseline system that always recommends the most commonly preferred dresses. We also found that Interactive-SmartClerk adapted to the preferences of minority users who favored less popular dresses. A case study using a robot demonstrated the system’s ability to recommend suitable dresses to people with diverse preferences.

Abstract In light of the escalating global polycrisis—a convergence of environmental, social, and mental health crises—this paper explores the potential of mindfulness-based approaches for fostering human and planetary wellbeing and sustainability. We specifically investigate the linkages between Mindfulness-Based Stress Reduction (MBSR) and sustainability, and how they can be strengthened to support transformative education. Drawing on interviews with key informants and in-depth case studies of innovative courses, we assess historical connections and current developments, as well as the needs, gaps, and opportunities for adapting existing approaches to sustainability contexts. What is the curriculum of the present moment, in a situation where the whole world has become the hospital? Based on our findings, we identify possibilities and principles for modifying, expanding, upscaling, and transforming mindfulness-based practices, interventions, and curricula—offering pathways that other training institutions can draw on. We synthesize our results into a “taxonomy of mindfulness-sustainability integration,” outlining key features and ethical considerations at different levels. Finally, we caution against protocolizing mindfulness and instead emphasize its non-instrumental dimensions—embodiment, emergence, and relationality—for finding a path of hope, joyful engagement, and meaningful transformation towards sustainability that is grounded in the inextricable connection between our inner lives and the living planet.

This workshop aims to support early-career researchers in the field of Human-Agent Interaction (HAI), especially those from non-native English-speaking backgrounds. Despite increasing global engagement, many talented researchers face challenges in presenting their work internationally due to language barriers and limited opportunities. By providing a platform to present research in English in a supportive and peer-driven environment, this workshop will foster accessibility, visibility, and confidence among participants. Presentations will be followed by extended and moderated Q&A sessions to encourage inclusive discussion. The workshop also invites guest talks from early-career researchers who exemplify innovative HAI research, promoting role models for the next generation. Overall, the workshop seeks to lower entry barriers and empower underrepresented voices in the global HAI community.

This study explores an unexplored area in robot-robot interaction: human perception of robots when multiple robots interact. The authors developed cart-type and tabletop robots that communicates using unintelligible audio. The authors hypothesized that auditory interaction, similar to dialogue influences human impressions. In a preliminary online survey, participants viewed videos of the robots in the dialog condition (the cart-type robot responding to the tabletop robot's vocalizations) or non-dialog condition (the cart-type robot acting alone). Preliminary survey showed that the dialog condition was rated higher, especially the perception of robot purposefulness and the perception of relationships between robots. These results suggest that auditory interactions can have an impact on human impressions and foster a sense of intentionality and relational understanding between robots.