Multidisciplinary teams are crucial in tailoring cancer care through collaborative decision-making involving several clinical specialties. The inherent complexity of clinical cases, the increasing abundance of unstructured textual data, and the time restrictions of professionals pose significant challenges to team coordination and patient care. This creates an opportunity for generative AI technologies, such as LLMs, to enhance collaborative work. Despite the growing interest in HCI research to explore LLMs in healthcare, we have yet to understand clinicians' perspectives on this emerging technology in multidisciplinary teams. Our work investigates the challenges, expectations and opportunities for LLMs in this context through a speculative approach. We leveraged the Futures Cone framework and conducted a qualitative study with 11 physicians from different cancer multidisciplinary teams. We contribute with an analysis of themes that emerged from individual interviews and a focus group, highlighting LLMs' potential to enhance and reshape multidisciplinary teams' practices. In addition, we uncover concerns and coping strategies related to LLMs' adoption and provide a set of design opportunities to inform the development of technologies for LLM-enhanced multidisciplinary teams.

Stroke survivors experience a wide range of sequelae that significantly change their lives and those of their caregivers. These changes affect relationships, professional life, and daily routines, leading to emotional distress for both. However, existing research in HCI has predominantly focused on physical and cognitive rehabilitation, neglecting the impact of stroke on emotional wellbeing. Our work explores the potential of social sensemaking technologies to support wellbeing awareness and reflection of stroke survivors and their caregivers. We developed Emotions2Us, an interactive ambient display designed to foster interdependent communication, expression, support, and reflection on emotional wellbeing among dyads. We contribute with qualitative findings from a four-week field deployment (N=8). We present an analysis of the themes that emerged from interviews with stroke survivors and caregivers, highlighting the impact of Emotions2Us on wellbeing practices and reflecting on the challenges, benefits, and opportunities of designing for social sensemaking following a stroke.

Research on robotic ostracism is still scarce and has only explored its effects on adult populations. Although the results revealed important carryover effects of robotic exclusion, there is no evidence yet that those results occur in child-robot interactions. This paper provides the first exploration of robotic ostracism with children. We conducted a study using the Robotic Cyberball Paradigm in a third-person perspective with a sample of 52 children aged between five to ten years old. The experimental study had two conditions: Exclusion and Inclusion. In the Exclusion condition, children observed a peer being excluded by two robots; while in the Inclusion condition, the observed peer interacted equally with the robots. Notably, even 5-year-old children could discern when robots excluded another child. Children who observed exclusion reported lower levels of belonging and control, and exhibited higher prosocial behaviour than those witnessing inclusion. However, no differences were found in children's meaningful existence, self-esteem, and physical proximity across conditions. Our user study provides important methodological considerations for applying the Robotic Cyberball Paradigm with children. The results extend previous literature on both robotic ostracism with adults and interpersonal ostracism with children. We finish discussing the broader implications of children observing ostracism in human-robot interactions.

Reading room conditions such as illumination, ambient light, human factors and display luminance, play an important role on how radiologists analyze and interpret images. Indeed, serious diagnostic errors can appear when observing images through everyday monitors. Typically, these occur whenever professionals are ill-positioned with respect to the display or visualize images under improper light and luminance conditions. In this work, we show that virtual reality can assist radiodiagnostics by considerably diminishing or cancel out the effects of unsuitable ambient conditions. Our approach combines immersive head-mounted displays with interactive surfaces to support professional radiologists in analyzing medical images and formulating diagnostics. We evaluated our prototype with two senior medical doctors and four seasoned radiology fellows. Results indicate that our approach constitutes a viable, flexible, portable and cost-efficient option to traditional radiology reading rooms.