Online knowledge-sharing platforms construct risk knowledge and provide the audience with risk-related scientific facts. We study how speakers organize narratives in past, present, and future foci to influence the audience\'s emotions through the audience\'s appraisal of motive congruency and coping potential. Empirical evidence from 210 Technology, Entertainment, Design talks about disasters from 2002 to 2018 demonstrates that emphasizing the past, present, and future in risk narrative leads to the audience\'s comments with more negative, less positive, and more positive emotions, respectively. Concrete (vs. abstract) portrayal of the risk narrative improves the audience\'s situational awareness, enhances their risk appraisal, and intensifies the impact of temporal focus on emotions, providing evidence of how temporal focus impacts. These findings demonstrate that temporal focus can effectively reduce risk overreaction or ignorance and facilitate emotion regulation in risk communication.

UNASSIGNED: The time-varying reproduction number R is a critical variable for situational awareness during infectious disease outbreaks; however, delays between infection and reporting of cases hinder its accurate estimation in real-time. A number of nowcasting methods, leveraging available information on data consolidation delays, have been proposed to mitigate this problem.
UNASSIGNED: In this work, we retrospectively validate the use of a nowcasting algorithm during 18 months of the COVID-19 pandemic in Italy by quantitatively assessing its performance against standard methods for the estimation of R.
UNASSIGNED: Nowcasting significantly reduced the median lag in the estimation of R from 13 to 8 days, while concurrently enhancing accuracy. Furthermore, it allowed the detection of periods of epidemic growth with a lead of between 6 and 23 days.
UNASSIGNED: Nowcasting augments epidemic awareness, empowering better informed public health responses.

暂无摘要。

OBJECTIVE: The goal of this study was to assess how different real-time gaze sharing visualization techniques affect eye tracking metrics, workload, team situational awareness (TSA), and team performance.
BACKGROUND: Gaze sharing is a real-time visualization technique that allows teams to know where their team members are looking on a shared display. Gaze sharing visualization techniques are a promising means to improve collaborative performance on simple tasks; however, there needs to be validation of gaze sharing with more complex and dynamic tasks.
METHODS: This study evaluated the effect of gaze sharing on eye tracking metrics, workload, team SA, and team performance in a simulated unmanned aerial vehicle (UAV) command-and-control task. Thirty-five teams of two performed UAV tasks under three conditions: one with no gaze sharing and two with gaze sharing. Gaze sharing was presented using a fixation dot (i.e., a translucent colored dot) and a fixation trail (i.e., a trail of the most recent fixations).
RESULTS: The results showed that the fixation trail significantly reduced saccadic activity, lowered workload, supported team SA at all levels, and improved performance compared to no gaze sharing; however, the fixation dot had the opposite effect on performance and SA. In fact, having no gaze sharing outperformed the fixation dot. Participants also preferred the fixation trail for its visibility and ability to track and monitor the history of their partner\'s gaze.
CONCLUSIONS: The results showed that gaze sharing has the potential to support collaboration, but its effectiveness depends highly on the design and context of use.
CONCLUSIONS: The findings suggest that gaze sharing visualization techniques, like the fixation trail, have the potential to improve teamwork in complex UAV tasks and could have broader applicability in a variety of collaborative settings.

BACKGROUND: Human mobility data have been used as a potential novel data source to guide policies and response planning during the COVID-19 global pandemic. The COVID-19 Mobility Data Network (CMDN) facilitated the use of human mobility data around the world. Both researchers and policy makers assumed that mobility data would provide insights to help policy makers and response planners. However, evidence that human mobility data were operationally useful and provided added value for public health response planners remains largely unknown.
OBJECTIVE: This exploratory study focuses on advancing the understanding of the use of human mobility data during the early phase of the COVID-19 pandemic. The study explored how researchers and practitioners around the world used these data in response planning and policy making, focusing on processing data and human factors enabling or hindering use of the data.
METHODS: Our project was based on phenomenology and used an inductive approach to thematic analysis. Transcripts were open-coded to create the codebook that was then applied by 2 team members who blind-coded all transcripts. Consensus coding was used for coding discrepancies.
RESULTS: Interviews were conducted with 45 individuals during the early period of the COVID-19 pandemic. Although some teams used mobility data for response planning, few were able to describe their uses in policy making, and there were no standardized ways that teams used mobility data. Mobility data played a larger role in providing situational awareness for government partners, helping to understand where people were moving in relation to the spread of COVID-19 variants and reactions to stay-at-home orders. Interviewees who felt they were more successful using mobility data often cited an individual who was able to answer general questions about mobility data; provide interactive feedback on results; and enable a 2-way communication exchange about data, meaning, value, and potential use.
CONCLUSIONS: Human mobility data were used as a novel data source in the COVID-19 pandemic by a network of academic researchers and practitioners using privacy-preserving and anonymized mobility data. This study reflects the processes in analyzing and communicating human mobility data, as well as how these data were used in response planning and how the data were intended for use in policy making. The study reveals several valuable use cases. Ultimately, the role of a data translator was crucial in understanding the complexities of this novel data source. With this role, teams were able to adapt workflows, visualizations, and reports to align with end users and decision makers while communicating this information meaningfully to address the goals of responders and policy makers.

Despite the gains in performance that AI can bring to human-AI teams, they also present them with new challenges, such as the decline in human ability to respond to AI failures as the AI becomes more autonomous. This challenge is particularly dangerous in human-AI teams, where the AI holds a unique role in the team\'s success. Thus, it is imperative that researchers find solutions for designing AI team-mates that consider their human team-mates\' needs in their adaptation logic. This study explores adaptive autonomy as a solution to overcoming these challenges. We conducted twelve contextual inquiries with professionals in two teaming contexts in order to understand how human teammate perceptions can be used to determine optimal autonomy levels for AI team-mates. The results of this study will enable the human factors community to develop AI team-mates that can enhance their team\'s performance while avoiding the potentially devastating impacts of their failures.
As AI becomes more autonomous, the human ability to detect and respond to their failures decreases as they become less a part of the AI’s decision-making loop. This contextual inquiry study shows how human factors are affected by and should influence the design of adaptive AI team-mates in different teaming contexts.

BACKGROUND: Drones are able to deliver automated external defibrillators in cases of out-of-hospital cardiac arrest (OHCA) but can be deployed for other purposes. Our aim was to evaluate the feasibility of sending live photos to dispatch centres before arrival of other units during time-critical incidents.
METHODS: In this retrospective observational study, the regional dispatch centre implemented a new service using five existing AED-drone systems covering an estimated 200000 inhabitants in Sweden. Drones were deployed automatically over a 4-month study period (December 2022-April 2023) in emergency calls involving suspected OHCAs, traffic accidents and fires in buildings. Upon arrival at the scene, an overhead photo was taken and transmitted to the dispatch centre. Feasibility of providing photos in real time, and time delays intervals were examined.
RESULTS: Overall, drones were deployed in 59/440 (13%) of all emergency calls: 26/59 (44%) of suspected OHCAs, 20/59 (34%) of traffic accidents, and 13/59 (22%) of fires in buildings. The main reasons for non-deployment were closed airspace and unfavourable weather conditions (68%). Drones arrived safely at the exact location in 58/59 cases (98%). Their overall median response time was 3:49 min, (IQR 3:18-4:26) vs. emergency medical services (EMS), 05:51 (IQR: 04:29-08:04) p-value for time difference between drone and EMS = 0,05. Drones arrived first on scene in 47/52 cases (90%) and the largest median time difference was found in suspected OHCAs 4:10 min, (IQR: 02:57-05:28). The time difference in the 5/52 (10%) cases when EMS arrived first the time difference was 5:18 min (IQR 2:19-7:38), p = NA. Photos were transmitted correctly in all 59 alerts. No adverse events occurred.
CONCLUSIONS: In a newly implemented drone dispatch service, drones were dispatched to 13% of relevant EMS calls. When drones were dispatched, they arrived at scene earlier than EMS services in 90% of cases. Drones were able to relay photos to the dispatch centre in all cases. Although severely affected by closed airspace and weather conditions, this novel method may facilitate additional decision-making information during time-critical incidents.

In the field of armored vehicles, up to 70% of accidents are associated with low levels of situational awareness among the occupants, highlighting the importance of situational awareness in improving task performance. In this study, we explored the mechanisms influencing situational awareness by simulating an armored vehicle driving platform with 14 levels of experimentation in terms of five factors: experience, expectations, attention, the cueing channel, and automation. The experimental data included SART and SAGAT questionnaire scores, eye movement indicators, and electrocardiographic and electrodermal signals. Data processing and analysis revealed the following conclusions: (1) Experienced operators have higher levels of situational awareness. (2) Operators with certain expectations have lower levels of situational awareness. (3) Situational awareness levels are negatively correlated with information importance affiliations and the frequency of anomalous information in non-primary tasks. (4) Dual-channel cues lead to higher levels of situational awareness than single-channel cues. (5) Operators\' situational awareness is lower at high automation levels.

Effective teamwork is essential in almost every job, and can even mean life, death, or disability in some jobs. Intraoperative neurophysiological monitoring (IONM) is a career in which effective teamwork and accurate communication are of utmost importance, yet it comes with a unique set of challenges in which to achieve those goals. Operating rooms can be very stressful environments, even if a surgical neurophysiologist (SNP) works in the same hospital every day. Often an SNP is required to travel from hospital to hospital and work with different teams each day. In addition, communication with the IONM oversight professional (IONM-P) can be challenging by nature of the telemedicine model which is becoming the most commonly applied IONM model in the United States. It is unfortunate that such critical skills are assumed and are rarely formally trained. In this article, we present evidence-based recommendations for establishing effective team function. We also provide several tools designed to help create effective and efficient teams. Teams cannot function at their best without outstanding communication, so improving teamwork also means improving communication. This article also provides several techniques for excellent communication, regardless of the situation or context.

Future airspace is expected to become more congested with additional in-service cargo and commercial flights. Pilots will face additional burdens in such an environment, given the increasing number of factors that they must simultaneously consider while completing their work activities. Therefore, care and attention must be paid to the mental workload (MWL) experienced by operating pilots. If left unaddressed, a state of mental overload could affect the pilot\'s ability to complete his or her work activities in a safe and correct manner. This study examines the impact of two different cockpit display interfaces (CDIs), the Steam Gauge panel and the G1000 Glass panel, on novice pilots\' MWL and situational awareness (SA) in a flight simulator-based setting. A combination of objective (EEG and HRV) and subjective (NASA-TLX) assessments is used to assess novice pilots\' cognitive states during this study. Our results indicate that the gauge design of the CDI affects novice pilots\' SA and MWL, with the G1000 Glass panel being more effective in reducing the MWL and improving SA compared with the Steam Gauge panel. The results of this study have implications for the design of future flight deck interfaces and the training of future pilots.