Patients undergoing interfacility transfers are at potentially greater risk of adverse or critical events than those in hospital, and efficient transfers play a significant role in reducing mortality and morbidity. Medical dispatchers rely on accurate estimations of transfer time in determining the most appropriate method of transportation, often either a helicopter and/or land ambulance, in situations that are characterized by high time pressure and uncertainty. In this paper, we propose the design of a datadriven decision support tool to improve dispatcher transport mode decision making. We studied the dispatch process of the air and land medical transport system in Ontario, Canada through onsite observations and developed a tool which generates transfer time estimates based on historical data. We found that dispatchers have large estimation errors, and are biased toward higher degrees of underestimation for air transfers compared with land transfers. In contrast, the proposed tool produced estimates that had significantly less error than dispatcher estimates. The estimation error for the tool was on the average 21 min less: a practically significant difference in urgent patient care. Through onsite observations and the relevant literature, we also identified factors that may influence the collaboration between the dispatcher and the tool. This research is a first attempt to study how decisions are made for interfacility medical transfers and for evaluating the accuracy of human operator estimates of these transfer times. It is also the first to demonstrate a tool's utility in comparison to existing procedures for estimating transfer times.

A growing body of research has found that distracted walking is a safety concern due to reduced situation awareness and the possibility of compromised gait performance. Distraction tasks, such as texting, browsing social media, and playing games, differ in terms of their physical and cognitive demands. However, few studies have examined whether there are differences in how physical and cognitive demands impact gait. The goal of this paper is to evaluate workload differences between four distraction tasks that represent common smartphone functions and may differ in terms of physical and cognitive demands: 1) No distraction, 2) Reading, 3) Tapping, 4) N-Back. We characterized the workload differences using three methods, a subjective workload assessment (NASA-TLX) and two physiological workload measures, pupil width and blink rate. Our results suggest that the chosen distraction tasks differ in their workload demands. While, a preliminary analysis of descriptive gait parameters failed to find significant differences between the distraction conditions, further analysis of more complex gait measures may be required to understand differences between physical and cognitive demands.

Background Two barriers to effective enrollment decisions are low health insurance literacy and lack of knowledge about how to choose a plan. To remedy these issues, digital decision aids have been used to increase the knowledge of plan options and to guide the decision process. Previous research has shown that the way information is presented in a decision aid can impact consumer choice, and existing health insurance decision aids vary in their design, content, and layout. Commercial virtual benefits counselors (VBCs) are digital decision aids that provide decision support by mimicking the guidance provided by an in-person human resources (HR) counselor, whereas more traditional HR websites provide information that requires self-directed navigation through the system. However, few studies have compared how decision processes are impacted by these different methods of providing information. Objective This study aims to examine how individuals interact with two different types of health insurance decision aids (guided VBCs that mimic conversations with a real HR counselor and self-directed HR websites that provide a broad range of detailed information) to make employer-provided health insurance decisions. Methods In total, 16 employees from a local state university completed a user study in which they made mock employer-provided health insurance decisions using 1 of 2 systems (VBC vs HR website). Participants took part in a retrospective think-aloud interview, cued using eye-tracking data to understand decision aid interactions. In addition, pre- and postexperiment measures of literacy and knowledge and decision conflict and usability of the system were also examined. Results Both the VBC and HR website had positive benefits for health insurance knowledge and literacy. Previous health insurance knowledge also impacted how individuals used decision aids. Individuals who scored lower on the pre-experiment knowledge test focused on different decision factors and were more conflicted about their final enrollment decisions than those with higher knowledge test scores. Although both decision aids resulted in similar changes in the Health Insurance Literacy Measure and knowledge test scores, perceived usability differed. Website navigation was not intuitive, and it took longer to locate information, although users appreciated that it had more details; the VBC website was easier to use but had limited information. Lower knowledge participants, in particular, found the website to be less useful and harder to use than those with higher health insurance knowledge. Finally, out-of-pocket cost estimation tools can lead to confusion when they do not highlight the factors that contribute to the cost estimate. Conclusions This study showed that health insurance decision aids help individuals improve their confidence in selecting and using health insurance plans. However, previous health insurance knowledge plays a significant role in how users interact with and benefit from decision aids, even when information is presented in different formats.

This work seeks to understand whether the unique features of a smartwatch, compared to a smartphone, mitigate or exacerbate driver distraction due to notifications, and to provide insights about drivers' perceptions of the risks associated with using smartwatches while driving. As smartwatches are gaining popularity among consumers, there is a need to understand how smartwatch use may influence driving performance. Previous driving research has examined voice calling on smartwatches, but not interactions with notifications, a key marketed feature. Engaging with notifications (e.g., reading and texting) on a handheld device is a known distraction associated with increased crash risks. Two driving simulator studies compared smartwatch to smartphone notifications. Experiment I asked participants to read aloud brief text notifications and Experiment II had participants manually select a response to arithmetic questions presented as notifications. Both experiments investigated the resulting glances to and physical interactions with the devices, as well as self-reported risk perception. Experiment II also investigated driving performance and self-reported knowledge/expectation about legislation surrounding the use of smart devices while driving. Experiment I found that participants were faster to visually engage with the notification on the smartwatch than the smartphone, took longer to finish reading aloud the notifications, and exhibited more glances longer than 1.6 s. Experiment II found that participants took longer to reply to notifications and had longer overall glance durations on the smartwatch than the smartphone, along with longer brake reaction times to lead vehicle braking events. Compared to the no device baseline, both devices increased lane position variability and resulted in higher self-reported perceived risk. Experiment II participants also considered that smartwatch use while driving deserves penalties equal to or less than smartphone use. The findings suggest that smartwatches may have road safety consequences. Given the common view among participants to associate smartwatch use with equal or less traffic penalties than smartphone use, there may be a disconnect between drivers' actual performance and their perceptions about smartwatch use while driving.

No abstract