ABSTRACT PREDICTORS OF SITUATION AWARENESS IN GRADUATE STUDENT REGISTERED NURSE ANESTHETISTS Suzanne M. Wright, Ph.D. A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University. Virginia Commonwealth University, 2009 Major Director: J. James Cotter, Ph.D. Situation awareness (SA) is defined as one’s perception of the elements of the environment, the comprehension of their meaning, and the projection of their status in the near future. Stated more simply, SA is knowing what is going on around you. The concept of SA is well known in the field of aviation which is characterized by complexity and dynamism. The discipline of anesthesia shares these same characteristics, yet the study of SA in this setting is in its infancy. Human error has been implicated in nearly 80% of all preventable medical errors. It is well documented that lack of SA frequently contributes to human error. Although the discipline of anesthesia has led the medical field in patient safety through rigorous study of human error and adverse events in the operating room, crises in anesthesia still exist. Nurse anesthetists should possess the ability to acquire and maintain SA at all times during clinical situations in the operating room, yet there are no studies examining SA in this population. Guided by Endsley’s theory of situation awareness, the purpose of this study was to provide nurse anesthesia educators with a best evidence predictor model of SA in GSRNAs for curricular implementation. The study objectives are to determine: a) the extent to which memory, cognition, and automaticity are related to situation awareness, b) the extent to which any relationship amongst memory, cognition, and automaticity mediates their relationship with situation awareness, and c) the extent to which Endsley’s theory of situation awareness is supported in the GSRNA population. After IRB approval, 71 GSRNAs were randomly selected from each of three universities chosen for this study. A non-experimental, correlational design was used to measure the relationship between memory, cognition, and automaticity and SA. Situation awareness was measured by the WOMBAT-CS, a computer-based assessment tool for evaluating SA in complex-system operators such as pilots, air traffic controllers, and anesthetists. A stepwise multiple regression was performed between the GSRNA attributes and SA scores. Beta-weights were used to identify the magnitude each relationship. Findings from this study revealed that cognition best predicts SA in the population of Graduate Student Registered Nurse Anesthetists, with the addition of memory and automaticity contributing no additional predictive value to the model. The results of this study have the potential to make a positive impact on the education and training of GSRNAs. Additionally, this study may provide foundational support for further research directed at assessing the effectiveness of high-fidelity simulated operating room environments in promoting SA in GSRNAs.

There are many current and future scenarios that require teams of air, ground or humanoid robots to gather information in complex and often dangerous environments, where it would be unreasonable or impossible for humans to be physically present [1-6]. The current state of the art involves a single robot being monitored by one or many human operators [7], but a single operator managing a team of autonomous robots is preferred as long as effective and time-efficient management of the team is maintained [8-9]. This is limited by the operator's ability to command actions of multiple robots, be aware of robot states, and respond to less important tasks, while accomplishing a primary objective defined by the application scenario. The operator's ability to multi-task could be improved with the use of a multimodal interface, using both visual and haptic feedback. This thesis investigates the use of haptic feedback in developing intuitive, shape-based interaction to maintain heads-up control and increase an operator's situation awareness (SA) while managing a robot team.In this work, the autonomous behavior of the team is modeled after a patrol and cordon scenario, where the team travels to and surrounds buildings of interest. A novel approach that involves treating the team as a moldable volume is presented, where deformations of this volume correspond to changes in team shape. During surround mode, the operator may explore or manipulate the team shape to create custom formations around a building. A spacing interaction method also allows the operator to adjust how robots are spaced within the current shape. Separate haptic feedback is developed for each method to allow the operator to "feel" the shape or spacing manipulation. During travel mode, the operator chooses desired travel locations and receives feedback to help identify how and where the team travels. RoTHSim, an experimental robot team haptic simulator, was developed and used as a test bed for single-operator management of a robot team in a multitasking reconnaissance and surveillance scenario. Using RoTHSim, a human subject experiment was conducted with 19 subjects to determine the effects of haptic feedback and task demand difficulty on levels of performance, SA and workload. Results from the experiment suggest that haptic feedback significantly improves operator performance in a reconnaissance task when task demand is higher, but may slightly increase operator workload. Due to the experimental setup, these results suggest that haptic feedback may make it easier for the operator to experience heads-up control of a team of autonomous robots. There were no significance differences on SA scores due to haptic feedback in this study.

Despite technological advances in the information security field, attacks by unauthorized individuals and groups continue to penetrate defenses. Due to the rapidly changing environment of the Internet, the appearance of newly developed malicious software or attack techniques accelerates while security professionals continue in a reactive posture with limited time for identifying new threats. The problem addressed in this study was the perceived value of threat intelligence as a proactive process for information security. The purpose of this study was to explore how situation awareness is enhanced by receiving advanced intelligence reports resulting in better decision-making for proper response to security threats. Using a qualitative case study methodology a purposeful sample of 13 information security professionals were individually interviewed and the data analyzed through Nvivo 11 analytical software. The research questions addressed threat intelligence and its impact on the security analyst's cognitive situation awareness. Analysis of the data collected indicated that threat intelligence may enhance the security analyst's situation awareness, as supported in the general literature. In addition, this study showed that the differences in sources or the lack of an intelligence program may have a negative impact on determining the proper security response in a timely manner. The implications for positive social change include providing leaders with greater awareness through threat intelligence of ways to minimize the effects of cyber attacks, which may result in increasing business and consumer confidence in the protection of personal and confidential information.

With the proliferation of cameras and advanced video analytics, situation awareness applications that automatically generate actionable knowledge from live camera streams has become an important class of applications in various domains including surveillance, marketing, sports, health care, and traffic monitoring. However, despite the wide range of use cases, developing those applications on large-scale camera networks is extremely challenging because it involves both compute- and data-intensive workloads, has latency-sensitive quality of service requirement, and deals with inherent dynamism (e.g., number of faces detected in a certain area) from the real world. To support developing large-scale situation awareness applications, this dissertation presents a distributed framework that makes two key contributions: 1) it provides a programming model that ensures scalability of applications and 2) it supports low-latency computation and dynamic workload handling through opportunistic event processing and workload distribution over different locations and network hierarchy. To provide a scalable programming model, two programming abstractions for different levels of application logic are proposed: the first abstraction at the level of real-time target detection and tracking, and the second abstraction for answering spatio-temporal queries at a higher level. The first programming abstraction, Target Container (TC), elevates target as a first-class citizen, allowing domain experts to simply provide handlers for detection, tracking, and comparison of targets. With those handlers, TC runtime system performs priority-aware scheduling to ensure real-time tracking of important targets when resources are not enough to track all targets. The second abstraction, Spatio-temporal Analysis (STA) supports applications to answer queries related to space, time, and occupants using a global state transition table and probabilistic events. To ensure scalability, STA supports bounded communication overhead of state update by providing tuning parameters for the information propagation among distributed workers. The second part of this work explores two optimization strategies that reduce latency for stream processing and handle dynamic workload. The first strategy, an opportunistic event processing mechanism, performs event processing on predicted locations to provide just-in-time situational information to mobile users. Since location prediction algorithms are inherently inaccurate, the system selects multiple regions using a greedy algorithm to provide highly meaningful information at the given amount of computing resources. The second strategy is to distribute application workload over computing resources that are placed at different locations and various levels of network hierarchy. To support this strategy, the framework provides hierarchical communication primitives and a decentralized resource discovery protocol that allow scalable and highly adaptive load balancing over space and time.

The overall aim of this thesis is to corroborate whether the Situation Awareness (SA) of older drivers is deficient to that of younger driving groups, due to the onset of age-related cognitive decrements. This is important to ascertain due to a presumed linkage between the concept and accident causation. In addition, the research undertaken to date to investigate this linkage has exclusively utilised rather artificial driving simulators and simulations. Thus there is a need for data from more ecologically valid methods. The research studies reported here have sought to preference on-road assessments (of different complexity), and to capture what information was selectively perceived, comprehended and reacted to; rather than, as in previous work, what was recalled. To achieve this, a Think aloud methodology was chosen to produce narratives of a driver s thoughts. This method was advantageously unobtrusiveness, but also flexible - it could additionally be used to compare an individual's SA to a driving performance measure, Hazard Perception. The driving-based studies undertaken found that for a relatively non-taxing route, an older driver group could produce cohesive awareness in parity with a younger driver group. However, the concepts from which that awareness was based upon drew more on general, direction based, concepts, in contrast to the younger group s focus on more specific, action based, concepts, and rearward and safety-related cues. For a more cognitively taxing route, the younger group produced significantly higher (p < 0.024) individual SA-related scores than their older counterparts. But the concepts/cues both groups relied upon remained similar - particularly in regards to the ratio of those indicative of a rearward and/or a safety-related focus. In a video-based study, however, and in contrast, the older driver group s SA scores improved sufficient to outperform a younger group, but, despite this, not for video-based scores indicative of Hazard Perception (HP). In this latter regard, age-related decrements appeared to be more influential, as the older group felt they were under time pressure during a HP test. However, the difficulty this presented appeared to advantageously bring more attention and effort to the task, which were argued as important factors for the uplift in their SA scoring. The thesis also showed that older groups judgement of the actual complexity of a driving task could potentially be deficient to that of younger driver groups. This could cause problems as incorrect perceptions could deflate the relevance and cohesiveness of information being processing. In contrast, the perceived complexity of a task could bring a rise or fall in SA score for both groups. Such results raised questions as to the impact of cognitive decrements, relative to task difficulty and related effort whilst driving. It also provided evidence that Situation Awareness, rather than being uniformly good or bad, could, like any other psychological construct, be prone to change. These aspects were drawn together in a proposed model of driving SA.

abstract: This study examined the impact of Situation Presence Assessment Method (SPAM) administration on air traffic control (ATC) students’ task workload and performance in high-fidelity ATC simulations. ATC students performed high-fidelity en-route simulations in two conditions: baseline conditions (without SPAM questions) and SPAM conditions. The data collected show that while workload in the two conditions were not significantly different, there was a trend of higher mental workload in SPAM conditions than in baseline conditions. Performance immediately following SPAM questions was revealed to be poorer than that preceding the SPAM questions and that over the equivalent time periods in the baseline conditions. The results suggest that a "Ready" signal before a SPAM question may not be enough to eliminate the impact of SPAM administration on ATC students’ workload and performance in high-fidelity en-route simulations. / Dissertation/Thesis / Masters Thesis Technology 2016

abstract: Traditional methods for detecting the status of traffic lights used in autonomous vehicles may be susceptible to errors, which is troublesome in a safety-critical environment. In the case of vision-based recognition methods, failures may arise due to disturbances in the environment such as occluded views or poor lighting conditions. Some methods also depend on high-precision meta-data which is not always available. This thesis proposes a complementary detection approach based on an entirely new source of information: the movement patterns of other nearby vehicles. This approach is robust to traditional sources of error, and may serve as a viable supplemental detection method. Several different classification models are presented for inferring traffic light status based on these patterns. Their performance is evaluated over real-world and simulation data sets, resulting in up to 97% accuracy in each set. / Dissertation/Thesis / Masters Thesis Computer Science 2016

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Purpose: The purpose of this pilot study was to describe situation awareness (SA) among licensed practical nurses (LPNs) working in direct patient care. Specific Aims: The specific aims for this study are 1) to examine SA scores, as measured by the Situation Awareness Global Assessment Technique (SAGAT), in LPNs working in direct patient care and compare to published data on SA in registered nurses (RNs), 2) to examine the relationship between SA scores and years of LPN experience, 3) to examine differences in SA scores by type of workplace setting and 4) to describe the relationship between levels of satisfaction with simulation, as measured by the Satisfaction with Simulation Experience Scale (SSES) and SA scores among LPNs. Framework: Situation Awareness Theory, as described by Endsley, was used as the framework for this study. Design: A cross-sectional, descriptive design using the Situation Awareness Global Assessment Technique was used to gather data from a convenience sample of LPNs. Results: LPNs (N=24) participated in the study and achieved an average SAGAT score of 72.6%. There were no differences in scores between those LPNs enrolled in an RN program and those who were not enrolled. Individual scores on the SAGAT were comparable or better than scores in a similar study of RNs. Conclusion: LPNs in this study demonstrated adequate situation awareness. Key Words: Situation awareness, licensed practical nurse, patient deterioration, clinical simulation

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