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OBJECTIVE: An up-to-date and thorough literature review is needed to identify factors that influence driver situation awareness (SA) during control transitions in conditionally automated vehicles (AV). This review also aims to ascertain SA components required for takeovers, aiding in the design and evaluation of human-vehicle interfaces (HVIs) and the selection of SA assessment methodologies. BACKGROUND: Conditionally AVs alleviate the need for continuous road monitoring by drivers yet necessitate their reengagement during control transitions. In these instances, driver SA is crucial for effective takeover decisions and subsequent actions. A comprehensive review of influential SA factors, SA components, and SA assessment methods will facilitate driving safety in conditionally AVs but is still lacking. METHOD: A systematic literature review was conducted. Thirty-four empirical research articles were screened out to meet the criteria for inclusion and exclusion. RESULTS: A conceptual framework was developed, categorizing 23 influential SA factors into four clusters: task/system, situational, individual, and nondriving-related task factors. The analysis also encompasses an examination of pertinent SA components and corresponding HVI designs for specific takeover events, alongside an overview of SA assessment methods for conditionally AV takeovers. CONCLUSION: The development of a conceptual framework outlining influential SA factors, the examination of SA components and their suitable design of presentation, and the review of SA assessment methods collectively contribute to enhancing driving safety in conditionally AVs. APPLICATION: This review serves as a valuable resource, equipping researchers and practitioners with insights to guide their efforts in evaluating and enhancing driver SA during conditionally AV takeovers.

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OBJECTIVE: The goal of this study was to assess how different real-time gaze sharing visualization techniques affect eye tracking metrics, workload, team situation 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. CONCLUSION: The results showed that gaze sharing has the potential to support collaboration, but its effectiveness depends highly on the design and context of use. APPLICATION: 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.

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Fatigue and stress are critical variables that impair railway train drivers' safety performance, and individual differences may influence these effects. This study investigates how fatigue and stress affect high-speed train drivers' human error and the role of individual differences. We hypothesised that situation awareness (SA) mediates the effects of fatigue and stress on human error, and individual differences (age and work experience) moderate these effects. We surveyed 1,391 male drivers from eight Chinese railway bureaus and used PROCESS Macro for data analysis. The results revealed that fatigue and stress increased human error, directly and indirectly through SA. Age and work experience moderated the effect of fatigue and stress on SA, respectively. Older drivers had better SA under high fatigue, while more experienced drivers had better SA under high stress. These findings can inform more tailored safety management strategies to lower human error and enhance the safety of high-speed train operations.

A cross-sectional survey of 1,391 high-speed train drivers in China indicated that fatigue and stress amplify human error by impairing situation awareness (SA). Age and work experience were observed to moderate the impact of fatigue and stress on SA, respectively. These insights guide the advancement of safety management strategies.

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Situation awareness (SA) is an important non-technical skill for nurses. Nurses interact directly with patients and review their clinical signs. If we improve nurses' SA, they will likely detect clinical changes and prevent patient harm. A clinical endeavor that can benefit from improved nurses' SA is the prevention of Healthcare-Acquired Urinary Tract Infection (HAUTI). Electronic Health Records contain comprehensive nursing assessment data that researchers can use to analyze trends and provide a context-based understanding of the infection risk factors. We conducted a study that involved extracting nursing assessment data and preparing it for supervised learning algorithms and predicting HAUTI. In this paper, we share the methods we used to prepare the data for supervised learning algorithms and present the challenges related to data missingness.

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PURPOSE: Medical errors may be occasionally explained by inattentional blindness (IB), i.e., failing to notice an event/object that is in plain sight. We aimed to determine whether age/experience, restfulness/fatigue, and previous exposure to simulation education may affect IB in the anesthetic/surgical setting. METHODS: In this multicentre/multinational study, a convenience sample of 280 anesthesiologists watched an attention-demanding video of a simulated trauma patient undergoing laparotomy and (independently/anonymously) recorded the abnormalities they noticed. The video contained four expected/common abnormalities (hypotension, tachycardia, hypoxia, hypothermia) and two prominently displayed unexpected/rare events (patient's head movement, leaky central venous line). We analyzed the participants' ability to notice the expected/unexpected events (primary outcome) and the proportion of expected/unexpected events according to age group and prior exposure to simulation education (secondary outcomes). RESULTS: Anesthesiologists across all ages noticed fewer unexpected/rare events than expected/common ones. Overall, younger anesthesiologists missed fewer common events than older participants did (P = 0.02). There was no consistent association between age and perception of unexpected/rare events (P = 0.28), although the youngest cohort (< 30 yr) outperformed the other age groups. Prior simulation education did not affect the proportion of misses for the unexpected/rare events but was associated with fewer misses for the expected/common events. Self-perceived restfulness did not impact perception of events. CONCLUSION: Anesthesiologists noticed fewer unexpected/rare clinical events than expected/common ones in an attention-demanding video of a simulated trauma patient, in keeping with IB. Prior simulation training was associated with an improved ability to notice anticipated/expected events, but did not reduce IB. Our findings may have implications for understanding medical mishaps, and efforts to improve situational awareness, especially in acute perioperative and critical care settings.

RéSUMé: OBJECTIF: Les erreurs médicales peuvent parfois s'expliquer par la cécité d'inattention, soit le fait de ne pas remarquer un événement/objet qui est à la vue de tous et toutes. Notre objectif était de déterminer si l'âge/l'expérience, le repos/la fatigue et l'exposition antérieure à l'enseignement par simulation pouvaient affecter la cécité d'inattention dans le cadre de l'anesthésie/chirurgie. MéTHODE: Dans cette étude multicentrique/multinationale, un échantillon de convenance de 280 anesthésiologistes ont visionné une vidéo exigeant l'attention portant sur un patient de trauma simulé bénéficiant d'une laparotomie et ont enregistré (de manière indépendante/anonyme) les anomalies qu'ils et elles ont remarquées. La vidéo contenait quatre anomalies attendues/courantes (hypotension, tachycardie, hypoxie, hypothermie) et deux événements inattendus/rares bien en vue (mouvement de la tête du patient, fuite du cathéter veineux central). Nous avons analysé la capacité des participant·es à remarquer les événements attendus/inattendus (critère d'évaluation principal) et la proportion d'événements attendus/inattendus selon le groupe d'âge et l'exposition antérieure à l'enseignement par simulation (critères d'évaluation secondaires). RéSULTATS: Les anesthésiologistes de tous âges ont remarqué moins d'événements inattendus/rares que d'événements attendus/courants. Globalement, les anesthésiologistes plus jeunes ont manqué moins d'événements courants que leurs congénères plus âgé·es (P = 0,02). Il n'y avait pas d'association constante entre l'âge et la perception d'événements inattendus ou rares (P = 0,28), bien que la cohorte la plus jeune (< 30 ans) ait surpassé les autres groupes d'âge. La formation antérieure par simulation n'a pas eu d'incidence sur la proportion d'inobservation des événements inattendus ou rares, mais a été associée à moins de cécité d'inattention envers les événements attendus ou courants. Le repos perçu n'a pas eu d'impact sur la perception des événements. CONCLUSION: Les anesthésiologistes ont remarqué moins d'événements cliniques inattendus/rares que d'événements attendus/courants dans une vidéo exigeant l'attention portant sur la simulation d'un patient traumatisé, ce qui s'inscrit dans la cécité d'inattention. La formation préalable par simulation était associée à une meilleure capacité à remarquer les événements anticipés/attendus, mais ne réduisait pas la cécité d'inattention. Nos résultats peuvent avoir des implications pour la compréhension des accidents médicaux et les efforts visant à améliorer la conscience situationnelle, en particulier dans les contextes de soins périopératoires aigus et de soins intensifs.

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INTRODUCTION: Managing obstetric shoulder dystocia requires swift action using correct maneuvers. However, knowledge of obstetric teams' performance during management of real-life shoulder dystocia is limited, and the impact of non-technical skills has not been adequately evaluated. We aimed to analyze videos of teams managing real-life shoulder dystocia to identify clinical challenges associated with correct management and particular non-technical skills correlated with high technical performance. MATERIAL AND METHODS: We included 17 videos depicting teams managing shoulder dystocia in two Danish delivery wards, where deliveries were initially handled by midwives, and consultants were available for complications. Delivery rooms contained two or three cameras activated by Bluetooth upon obstetrician entry. Videos were captured 5 min before and after activation. Two obstetricians assessed the videos; technical performances were scored as low (0-59), average (60-84), or high (85-100). Two other assessors evaluated non-technical skills using the Global Assessment of Team Performance checklist, scoring 6 (poor) to 30 (excellent). We used a spline regression model to explore associations between these two score sets. Inter-rater agreement was assessed using interclass correlation coefficients. RESULTS: Interclass correlation coefficients were 0.71 (95% confidence interval 0.23-0.89) and 0.82 (95% confidence interval 0.52-0.94) for clinical and non-technical performances, respectively. Two teams had low technical performance scores; four teams achieved high scores. Teams adhered well to guidelines, demonstrating limited head traction, McRoberts maneuver, and internal rotation maneuvers. Several clinical skills posed challenges, notably recognizing shoulder impaction, applying suprapubic pressure, and discouraging women from pushing. Two non-technical skills were associated with high technical performance: effective patient communication, with teams calming the mother and guiding her collaboration during internal rotational maneuvers, and situation awareness, where teams promptly mobilized all essential personnel (senior midwife, consultant, pediatric team). Team communication, stress management, and task management skills were not associated with high technical performance. CONCLUSIONS: Videos capturing teams managing real-life shoulder dystocia are an effective tool to reveal challenges with certain technical and non-technical skills. Teams with high technical performance are associated with effective patient communication and situational awareness. Future training should include technical skills and non-technical skills, patient communication, and situation awareness.

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Situation awareness (SA) is important in many demanding tasks (e.g. driving). Assessing SA during training can indicate whether someone is ready to perform in the real world. SA is typically assessed by interrupting the task to ask questions about the situation or asking questions after task completion, assessing only momentary SA. An objective and continuous means of detecting SA is needed. We examined whether neurophysiological sensors are useful to objectively measure Level 3 SA (projection of events into the future) during a driving task. We measured SA by the speed at which participants responded to SA questions and the accuracy of responses. For EEG, beta and theta power were most sensitive to SA response time. For fNIRS, oxygenated haemoglobin (HbO) was most sensitive to accuracy. This is the first evidence to our knowledge that neurophysiological measures are useful for assessing Level 3 SA during an ecologically valid task.

We examine whether neurophysiological sensors are useful to objectively measure Level 3 situation awareness (SA) prediction during a driving task. EEG theta and beta, and fNIRS oxygenated haemoglobin were most sensitive to SA accuracy. This is evidence that neurophysiological measures can be used to assess hazard prediction (Level 3 SA).

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The driver's takeover time is crucial to ensure a safe takeover transition in conditional automated driving. The study aimed to construct a prediction model of driver's takeover time based on individual characteristics, external environment, and situation awareness variables. A total of 18 takeover events were designed with scenarios, non-driving-related tasks, takeover request time, and traffic flow as variables. High-fidelity driving simulation experiments were carried out, through which the driver's takeover data was obtained. Fifteen basic factors and three dynamic factors were extracted from individual characteristics, external environment, and situation awareness. In this experiment, these 18 factors were selected as input variables, and XGBoost and Shapely were used as prediction methods. A takeover time prediction model (BM + SA model) was then constructed. Moreover, we analyzed the main effect of input variables on takeover time, and the interactive contribution made by the variables. And in this experiment, the 15 basic factors were selected as input variables, and the basic takeover time prediction model (BM model) was constructed. In addition, this study compared the performance of the two models and analyzed the contribution of input variables to takeover time. The results showed that the goodness of fit of the BM + SA model (Adjusted_R2) was 0.7746. The XGBoost model performs better than other models (support vector machine, random forest, CatBoost, and LightBoost models). The relative importance degree of situation awareness variables, individual characteristic variables, and external environment variables to takeover time gradually reduced. Takeover time increased with the scan and gaze durations and decreased with pupil area and self-reported situation awareness scores. There was also an interaction effect between the variables to affect takeover time. Overall, the performance of the BM + SA model was better than that of the BM model. This study can provide support for predicting driver's takeover time and analyzing the mechanism of influence on takeover time. This study can provide support for the development of real-time driver's takeover ability prediction systems and optimization of human-machine interaction design in automated vehicles, as well as for the management department to evaluate and improve the driver's takeover performance in a targeted manner.

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By conducting a mixed-design experiment using simplified accident handling tasks performed by two-person teams, this study examined the effects of automation function and condition (before, during, and after malfunction) on human performance. Five different and non-overlapping functions related to human information processing model were considered and their malfunctions were set in a first-failure way. The results showed that while the automation malfunction impaired task performance, the performance degradation for information analysis was more severe than response planning. Contrary to other functions, the situation awareness for response planning and response implementation tended to increase during malfunctioning and decrease after. In addition, decreased task performance reduced trust in automation, and malfunctions in earlier stages of information processing resulted in lower trust. Suggestions provided for the design and training related to automation emphasise the importance of high-level cognitive support and the benefit of involving automation error handling in training.

The effects of automation function and malfunction on human performance are important for design and training. The experimental results in this study revealed the significance of high-level cognitive support. Also, introducing automation error handling in training can be helpful in improving situation awareness of the teams.

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Robot-Assisted Minimally Invasive Surgery (RAMIS) marks a paradigm shift in surgical procedures, enhancing precision and ergonomics. Concurrently it introduces complex stress dynamics and ergonomic challenges regarding the human-robot interface and interaction. This study explores the stress-related aspects of RAMIS, using the da Vinci XI Surgical System and the Sea Spikes model as a standard skill training phantom to establish a link between technological advancement and human factors in RAMIS environments. By employing different physiological and kinematic sensors for heart rate variability, hand movement tracking, and posture analysis, this research aims to develop a framework for quantifying the stress and ergonomic loads applied to surgeons. Preliminary findings reveal significant correlations between stress levels and several of the skill-related metrics measured by external sensors or the SURG-TLX questionnaire. Furthermore, early analysis of this preliminary dataset suggests the potential benefits of applying machine learning for surgeon skill classification and stress analysis. This paper presents the initial findings, identified correlations, and the lessons learned from the clinical setup, aiming to lay down the cornerstones for wider studies in the fields of clinical situation awareness and attention computing.

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AIM: The aim of this study was to: (1) use cognitive task analysis to describe final year nursing students situation awareness in recognising, responding and escalating care of deteriorating patients in ward settings; and (2) make recommendations for training and practice. DESIGN: A mixed methods cognitive task analysis with a convergent triangulation design. METHOD: Data collection involved observations of 33 final year nursing students in simulated deteriorating patient scenarios and retrospective cognitive interviews. A process tracing technique was applied to identify the cues to deterioration participants perceived; how cue perception altered as situational demands increased; the extent that participants made connections between perceived cues and reached a situational understanding; and the factors that influenced and constrained participants situation awareness. Qualitative and quantitative findings are woven together and presented using descriptive statistics, illustrative quotations and timeline extractions. RESULTS: The median cue perception was 65.4% and 57.6% in the medical and surgical scenarios, respectively. Perception was negatively influenced by incomplete vital sign monitoring as situations escalated; limited physical assessments; passive scanning behaviours; poor task automaticity; and excessive cognitive demands. Incomplete perception, poor cue integration and underdeveloped mental models influenced situational understanding. Escalation calls did not always accurately reflect situations and a reporting mindset was evident. Clinical exposure to deteriorating patients was described as variable and opportunistic. REPORTING METHOD: The study is reported in accordance with the Good Reporting of a Mixed Methods Study (GRAMMS) checklist. PATIENT OR PUBLIC CONTRIBUTION: Patients and public were not involved in this research.

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The Philips Visual Patient Avatar, a user-centered visualization technology, offers an alternative approach to patient monitoring. Computer-based simulation studies indicate that it increases diagnostic accuracy and confidence, while reducing perceived workload. About three months after the technology's integration into clinical practice, we conducted an assessment among anesthesia providers to determine their views on its strengths, limitations, and overall perceptions. This single-center qualitative study at the University Hospital of Zurich examined anesthesia providers' perceptions of the Philips Visual Patient Avatar after its implementation. The study included an online survey to identify medical personnel's opinions on the technology's strengths and areas for improvement, which were analyzed using thematic analysis. A total of 63 of the 377 invited anesthesia providers (16.7%) responded to the survey. Overall, 163 comments were collected. The most prevalent positive themes were good presentation of specific parameters (16/163; 9.8%) and quick overview/rapid identification of problems (15/163; 9.2%). The most common perceived area for improvement was the ability to adjust the visualization thresholds of Visual Patient Avatar, which represent the physiological upper and lower vital-sign limits (33/163; 20.3%). The study showed that users consider Philips Visual Patient Avatar a valuable asset in anesthesia, allowing for easier identification of underlying problems. However, the study also revealed a user desire for the ability to freely adjust the thresholds of the Visual Patient Avatar by the handling caregivers, which were fixed to the departmental standard during the study.

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Situational Awareness (SA) assessment is of paramount importance in various domains, with particular significance in the military for safe aviation decision-making. It involves encompassing perception, comprehension, and projection levels in human beings. Accurate evaluation of SA statuses across these three levels is crucial for mitigating human false-positive and false-negative rates in monitoring complex scenarios in the aviation context. This study proposes a comprehensive comparative analysis by involving two types of physiological records: electroencephalogram (EEG) signals and brain electrical activity mapping (BEAM) images. These two modalities are leveraged to automate precise SA evaluation using both conventional machine learning and advanced deep learning techniques. Benchmarking experiments reveal that the BEAM-based deep learning models attain state-of-the-art performance scores of 0.955 for both SA perception and comprehension levels, respectively. Conversely, the EEG signals-based manual feature extraction, selection, and classification approach achieved a superior accuracy of 0.929 for the projection level of SA. These findings collectively highlight the potential of deploying diverse physiological records as valuable computational tools for enhancing SA evaluation throughout aviation decision-making safety.

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Lack of situation awareness (SA) is the primary cause of human errors when operating forklifts, so determining the SA level of the forklift operator is crucial to the safety of forklift operations. An EEG recognition approach of forklift operator SA in actual settings was presented in order to address the issues with invasiveness, subjectivity, and intermittency of existing measuring methods. In this paper, we conducted a field experiment that mimicked a typical forklift operation scenario to verify the differences in EEG states of forklift operators with different SA levels and investigate the correlation of multi-band combination features of each brain region of forklift operators with SA. Based on the sensitive EEG combination indexes, Support Vector Mechanism was used to construct a forklift operator SA recognition model. The results revealed that there were differences between forklift operators with high and low SA in the θ, α, and ß frequency bands in zones F, C, P, and O; combined EEG indicators θ/ß, (α + θ)/(α + ß), and θ/(α + ß) in zones F, P, and C were significantly correlated with SA; the recognition accuracy of the model reached 88.64% in the case of combined EEG indicators of zones C & F & P as input. It could provide a reference for SA measurement, contributing to the improvement of SA.

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Healthcare today is the prerogative of teams rather than of individuals. In acute care domains such as anaesthesia, intensive care, and emergency medicine, the work is complex and fast-paced, and the team members are diverse and interdependent. Three decades of research into the behaviours of high-performing teams provides us with clear guidance on team training, demonstrating positive effects on patient safety and staff wellbeing. Here we consider team performance through the lens of situation awareness. Maintaining situation awareness is an absolute requirement for safe and effective patient management. Situation awareness is a dynamic process of perceiving cues in the environment, understanding what they mean, and predicting how the situation may evolve. In the context of acute clinical care, situation awareness can be improved if the whole team actively contributes to monitoring the environment, processing information, and planning next steps. In this narrative review, we explore the concept of situation awareness at the level of the team, the conditions required to maintain team situation awareness, and the relationship between team situation awareness, shared mental models, and team performance. Our ultimate goal is to help clinicians create the conditions required for high-functioning teams, and ultimately improve the safety of clinical care.

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AIM: To examine the components of visual attention that maintain situational awareness during simulation training in undergraduate nursing students with different instruction levels. BACKGROUND: Eye-tracking can provide deep insight into the nurses' attention during simulated practice. Knowing which gaze patterns promote situational awareness can significantly improve nurse instruction. DESIGN: A comparative observational study investigated the role of visual attention on the performance quality, psychophysiological parameters (vital signs, anxiety and stress) and socioemotional competencies (cognitive workload, motivation and self-efficacy) of nursing students with various experience levels. METHODS: Thirty nursing students divided into two groups according to their academic level: first cycle (n=14) and second-cycle (n=16) faced a clinical simulation scenario to resolve a cardiorespiratory arrest event. Eye tracking-based analysis required the selection of six areas of interest. The monitorization of vital signs included measuring blood pressure, heart rate, respiratory rate and oxygen saturation before and after the simulation practice. Participants completed the socioemotional questionnaire (NASA-TLX). They answered the state subscale of the State-Trait Anxiety Inventory (STAI), the Visual Analogue Scale (VAS) of stress, the Situational Motivation Scale (SIMS) and the Baessler and Schwarzer General Self-Efficacy Scale. RESULTS: The first-cycle group displayed higher vital sign scores than the second cycle, apart from the post-simulation respiratory rate. All physiological parameters increased in mean value after the clinical simulation, except oxygen saturation. Anxiety was the only parameter in the socioemotional domain to present a statistically significant difference between the groups. First-year nursing students showed greater anxiety, stress, mental workload, identified regulation and intrinsic motivation, while second-year students showed higher levels of amotivation, external regulation and perceived self-efficacy. Eye-tracking data (revisits, gaze and duration of fixations) exhibited statistically significant differences depending on the area of interest in both groups (p =. 05). The performance outcomes showed a negative and moderate association with gaze the total number of gazes in the second-cycle group (rho = -0.640, p = 0.010). CONCLUSION: Eye-tracking-based analysis can help to predict performance quality while maintaining situational awareness during nursing instruction.

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This study aimed to investigate the effect of a looming visual cue on situation awareness and perceived urgency in response to a takeover request (TOR), and to explore the underlying mechanisms of this effect through three experiments. In Experiment 1, the optimal size and speed of a red disk were determined, which were effective in capturing looming motion and conveying the urgency of the situation. The results indicated that both looming speed and size ratio had significant effects on situation awareness and perceived urgency. In Experiment 2, the effects of looming stimuli were compared with dimming stimuli, and the results showed that the looming visual cue was more effective in promoting perceived urgency and situation awareness. The results also indicated that the looming visual cue attracted more visual attention than the dimming visual cue, in line with previous studies. Experiment 3 utilized a driving simulator to test the effectiveness of the looming visual cue in promoting fast and appropriate responses to TORs in complex driving scenarios. The results showed that the looming visual cue was more effective in promoting perceived urgency and enhancing situation awareness, especially in highly complex driving situations. Overall, the findings suggest that the looming visual cue is a powerful tool for promoting fast and appropriate responses to TORs and enhancing situation awareness, particularly in complex driving scenarios. These results have important implications for designing effective TOR systems and improving driver safety on the road.

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OBJECTIVE: The effects of three prototypical designs of energy consumption displays on energy-specific situation awareness were examined. BACKGROUND: Energy efficiency is crucial for the sustainability of technical systems. However, without accurate situation awareness of energy dynamics (energy dynamics awareness, EDA) it can be challenging for humans to optimize the use of energy resources of electric vehicles (EVs) through their behavior. METHOD: We examined three prototypical energy display designs that varied by their informational value to support EDA. Furthermore, we investigated the differential effects on EDA measured by (1) a newly constructed scale (experienced EDA), (2) estimating energy consumption, and (3) identifying efficient trips in an online experiment. Participants (N = 82) watched standardized driving scenes (videos) of EV trips presenting the energy displays. RESULTS: We found a strong effect of display type on experienced EDA, with the trace display being the most supportive. The EDA scale showed excellent internal consistency. The consumption estimation and efficient trip identification indicators were not affected by the display type. CONCLUSION: The study indicates that experienced EDA is immediately affected by displays with higher information value, but performance might need more time and training. More research is needed to investigate the cognitive processes related to EDA and to examine how distinct display elements enhance EDA. APPLICATION: Results from this research can be used as guidance for the design of energy displays, especially in EVs. The EDA scale can be used as an evaluation measure in the human-centered design process of energy displays.

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BACKGROUND: Viscoelastic hemostatic assays, such as rotational thromboelastometry (ROTEM) or thromboelastography, enable prompt diagnosis and accelerate targeted treatment. However, the complex interpretation of the results remains challenging. Visual Clot-a situation awareness-based visualization technology-was developed to assist clinicians in interpreting viscoelastic tests. OBJECTIVE: Following a previous high-fidelity simulation study, we analyzed users' perceptions of the technology, to identify its strengths and limitations from clinicians' perspectives. METHODS: This is a mixed qualitative-quantitative study consisting of interviews and a survey. After solving coagulation scenarios using Visual Clot in high-fidelity simulations, we interviewed anesthesia personnel about the perceived advantages and disadvantages of the new tool. We used a template approach to identify dominant themes in interview responses. From these themes, we defined 5 statements, which were then rated on Likert scales in a questionnaire. RESULTS: We interviewed 77 participants and 23 completed the survey. We identified 9 frequently mentioned topics by analyzing the interview responses. The most common themes were "positive design features," "intuitive and easy to learn," and "lack of a quantitative component." In the survey, 21 respondents agreed that Visual Clot is easy to learn and 16 respondents stated that a combination of Visual Clot and ROTEM would help them manage complex hemostatic situations. CONCLUSIONS: A group of anesthesia care providers found Visual Clot well-designed, intuitive, and easy to learn. Participants highlighted its usefulness in emergencies, especially for clinicians inexperienced in coagulation management. However, the lack of quantitative information is an area for improvement.

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Drivers must actively supervise automation as it can only function in limited conditions. A failure to supervise the system has negative consequences in terms of missed requests to take over control and may cause crashes or jeopardize safety. The objective of this study is to determine the effect of a novel, 3M (Mistakes, Mentoring, and Mastery) training program on drivers' behavior while using level 2 driving automation systems. To achieve this, 36 participants were assigned randomly to three different training programs (3M training, User manual, and Placebo) and drove through scenarios on a fixed-based driving simulator. The results showed that drivers in the 3M training group took back control more effectively when the driving automation system reached its limits compared to drivers who received User manual or Placebo training. Drivers in the 3M training Group also had higher situation awareness and improved trust in automation. The results indicate that an interactive approach to training with regards to vehicle automation can help drivers more safely interact with automation systems.

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