Extended abstracts on Human factors in computing systems. CHI Conference最新文献

Introducing technology support in a complex, team-based work setting requires a study of teamwork effects on technology use. In this paper, we present our initial analysis of team communications in a trauma resuscitation setting, where we deployed a digital checklist to support trauma team leaders in guiding patient care. By analyzing speech transcripts, checklist interaction logs, and videos of 15 resuscitations, we identified several tensions that arose from the use of a checklist in a team-based process with multi-step tasks. The tensions included incorrect markings of in-progress tasks as completed, failure to mark completed tasks due to missed communications, failure to record planned tasks, and difficulties in recording dynamic values. From these findings, we discuss design implications for checklist design for dynamic, team-based activities.

Communities in Indian Country experience severe behavioral health inequities [11, 12]. Based on recent research investigating scalable behavioral health interventions and therapeutic best practices for Native American (NA) communities, we propose ARORA, a social and emotional learning intervention delivered over a networked mobile game that uses geosocial gaming mechanisms enhanced with augmented reality technology. Focusing on the Navajo community, we take a community-based participatory research approach to include NA psychologists, community health workers, and educators as co-designers of the intervention activities and gaming mechanisms. Critical questions involve operation of the application across low-infrastructure landscapes as well scalability of design practices to be inclusive of the many diverse NA cultural communities in Indian Country.

A significant number of young Americans are vulnerable to excess weight gain, especially during the college years. While technology-based weight loss interventions have the potential to be very engaging, short-term approaches showed limited success. In our work we aim to better understand the impact of long-term, multimodal, technology-based weight loss interventions, and study their potential for greater effect among college students. In this paper we lay the basis for our approach towards a multimodal health intervention for young adults: we present formative work based on interviews and a design workshop with 26 young adults. We discuss our intervention at the intersection of user feedback, empirical evidence from previous work, and behavior change theory.

We describe the challenges of deploying a digital checklist for medical emergencies during an in-the-wild design and evaluation study. The in-the-wild approach allowed for many design iterations to meet the requirements of a safety-critical setting, while also providing lessons for designing in the wild. We faced two major challenges: working with research coordinators as study mediators and adapting training strategies to busy user schedules. We discuss these challenges and approaches to addressing them.

In this ongoing study, we aim to redesign an existing dynamic digital checklist application (app) for trauma resuscitations in a regional trauma center. The design followed an iterative, user-centered approach. Trauma team physician leaders and research coordinators at the center participated in a survey and usability study to provide feedback for improving the user interface. Proper optimization of the user experience is necessary for future adoption of the digital checklist. This study lays the groundwork for in situ use and evaluation of the checklist by trauma team members.

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as "black-boxes" due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user's data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

We describe a pilot study of designing and evaluating a digital checklist for medical emergencies based on participation of medical-expert researchers who used the checklist during actual trauma resuscitations. The participation of the researchers revealed challenges and insights for designing in the wild, as well as next steps for using our emerging technology in real scenarios.

Clinical Decision Support Systems (CDSS) are tools that assist healthcare personnel in the decision-making process for patient care. Although CDSSs have been successfully deployed in the clinical setting to assist physicians, few CDSS have been targeted at professional nurses, the largest group of health providers. We present our experience in designing and testing a CDSS interface embedded within a nurse care planning and documentation tool. We developed four prototypes based on different CDSS feature designs, and tested them in simulated end-of-life patient handoff sessions with a group of 40 nurse clinicians. We show how our prototypes directed nurses towards an optimal care decision that was rarely performed in unassisted practice. We also discuss the effect of CDSS layout and interface navigation in a nurse's acceptance of suggested actions. These findings provide insights into effective nursing CDSS design that are generalizable to care scenarios different than end-of-life.

Robots have potential to provide assistance to healthcare providers in daily caregiving tasks. The healthcare providers' acceptance of assistive robots will mediate the success or failure of implementation of robotic systems in care settings. It is essential to understand why and how providers would accept implementation of a robot in their daily work routines. We identified caregiving tasks with which healthcare providers would or would not accept assistance from a personal robot (Willow Garage's PR2). We also explored preferences for human or robot assistance. The healthcare providers we interviewed were quite open to the idea of receiving robot assistance for certain tasks.

We present the design, development and an initial study changes and adaptations related to navigation that take place in the brain, by incorporating an Audio-Based Environments Simulator (AbES) within a neuroimaging environment. This virtual environment enables a blind user to navigate through a virtual representation of a real space in order to train his/her orientation and mobility skills. Our initial results suggest that this kind of virtual environment could be highly efficient as a testing, training and rehabilitation platform for learning and navigation.