A key contribution of human factors engineering is the concept of workload: a construct that represents the relationship between an operator’s cognitive resources, the demands of their task, and performance. Understanding workload can lead to improvements in safety and performance for people working in critical environments, particularly within action teams. Recently, there has been interest in considering how the workload of a team as a whole may differ from that of an individual, prompting investigation into team workload as a distinct team-level construct. In empirical research, team-level workload is often considered as the sum or average of individual team members' workloads. However, the intrinsic characteristics of action teams—such as interdependence and heterogeneity—challenge this assumption, and traditional methods of measuring team workload might be unsuitable. This dissertation delves into this issue with a review of empirical work in action teams, pinpointing several gaps. Next, the development of a testbed is described and used to address two pressing gaps regarding the impact of interdependence and how team communications relate to team workload states and performance. An experiment was conducted with forty 3-person teams collaborating in an action team task. Results of this experiment suggest that the traditional way of measuring workload in action teams via subjective questionnaires averaged at the team level has some major shortcomings, particularly when demands are elevated, and action teams are highly interdependent. The results also suggested that several communication measures are associated with increases in demands, laying the groundwork for team-level communication-based measures of team workload. The results are synthesized with findings from the literature to provide a way forward for conceptualizing and measuring team workload in action teams.

Proper allocation of attention while driving is imperative to driver safety, as well as the safety of those around the driver. There is no doubt that in-vehicle alerts can effectively direct driver attention. In fact, visual, auditory, and tactile alert modalities have all shown to be more effective than no alert at all. However, research on in-vehicle alerts has primarily been limited to single-hazard scenarios. The current research examines the effects of in-vehicle alert modality on driver attention towards simultaneously occurring hazards. When a driver is presented with multiple stimuli simultaneously, there is the risk that they will experience alert masking, when one stimulus is obscured by the presence of another stimulus. As the number of concurrent stimuli increases, the ability to report targets decreases. Meanwhile, the alert acts as another target that they must also process. Recent research on masking effects of simultaneous alerts has shown masking to lead to breakdowns in detection and identification of alarms during a task, outlining a possible cost of alert technology. Additionally, existing work has shown auditory alerts to be more effective in directing driver attention, resulting in faster reaction times (RTs) than visual alerts. Multiple Resource Theory suggests that because of the highly visual nature of driving, drivers may have more auditory resources than visual resources available to process stimuli without becoming overloaded. Therefore, it was predicted that auditory alerts would be more effective in allowing drivers to recognize both potential hazards, measured though reduced brake reaction times and increased accuracy during a post-drive hazard observance question. The current study did not support the hypothesis. Modality did not result in a significant difference in drivers’ attention to simultaneously occurring hazards. The salience of hazards in each scenario seemed to make the largest impact on whether participants observed the hazard. Though the hypothesis was not supported, there were several limitations. Additionally, and regardless, the study results did point to the importance of further research on simultaneously occurring hazards. These scenarios pose a risk to drivers, especially when their attention is allocated to only one of the hazards.

Cyber operations are a complex sociotechnical system where humans and computers are operating in an environments in constant flux, as new technology and procedures are applied. Once inside the network, establishing a foothold, or beachhead, malicious actors can collect sensitive information, scan targets, and execute an attack.Increasing defensive capabilities through cyber deception shows great promise by providing an opportunity to delay and disrupt an attacker once network perimeter security has already been breached. Traditional Human Factors research and methods are designed to mitigate human limitations (e.g., mental, physical) to improve performance. These methods can also be used combatively to upend performance. Oppositional Human Factors (OHF), seek to strategically capitalize on cognitive limitations by eliciting decision-making errors and poor usability. Deceptive tactics to elicit decision-making biases might infiltrate attacker processes with uncertainty and make the overall attack economics unfavorable and cause an adversary to make mistakes and waste resources. Two online experimental platforms were developed to test the Sunk Cost Fallacy in an interactive, gamified, and abstracted version of cyber attacker activities. This work presents the results of the Cypher platform. Offering a novel approach to understand decision-making and the Sunk Cost Fallacy influenced by factors of uncertainty, project completion and difficulty on progress decisions. Results demonstrate these methods are effective in delaying attacker forward progress, while further research is needed to fully understand the context in which decision-making limitations do and do not occur. The second platform, Attack Surface, is described. Limitations and lessons learned are presented for future work.

Human operators are more prone to errors under high-workload conditions. However, error-commission research in cognitive science has been limited to studying behavior in single-choice reaction time tasks, which do not represent the complex multitasking scenarios faced in the real-world. In the current paper, prior evidence for a cognitive error-monitoring mechanism was applied toward predictions for how humans would react after making errors in a more ecologically valid multitasking paradigm. Previous work on neural and behavioral indices of error-monitoring strongly supports the idea that errors are distracting and can deplete attentional resources. Therefore, it was predicted that after committing an error, if a subject is subsequently presented with two simultaneously initiated task alerts (a conflict trial), they would be more likely to miss their response opportunity for one task and stay tunneled on the other task that originally caused the error. Additionally, it was predicted that this effect would dissipate after several seconds (under different lag conditions), making the error cascade less likely when subsequent tasks are delayed before presentation. A Multi-Attribute Task Battery was used to present the paradigm and collect post-error and post-correct performance measures. The results supported both predictions: Post-error accuracy was significantly lower as compared to post-correct accuracy (as measured through post-trial error rates). Post-trial error rates were also higher at shorter lags and dissipated over time, and the effects of pre-conflict performance on post-trial error rates was especially noticeable at shorter lags (although the interaction was not statistically significant). A follow-up analysis also demonstrated that following errors (as opposed to following correct trials), participants clicked significantly more on the task that originally caused the error (regardless of lag). This continued task-engagement further supports the idea that errors lead to a cognitive tunneling effect. The study provides evidence that in a multitasking scenario, the human cognitive error-monitoring mechanism can be maladaptive, where errors beget more errors. Additionally, the experimental paradigm provides a bridge between concepts originating in highly controlled methods of cognitive science research and more applied scenarios in the field of human factors.

ABSTRACT Billions of dollars are spent annually on urine specimen collection and analysis as they are critical clinical components vital to human health. The mid-stream clean catch (MSCC) process is the gold standard of ambulatory urine specimen collection for clinical diagnosis of urinary tract infections (UTI). The MSCC process is over 60 years old and is plagued by ridiculously high specimen contamination rates. The MSCC has resisted numerous attempts aimed at improving it. The purpose of this study was to determine if utilizing the concepts of Human Systems Engineering (HSE) could improve the urine specimen collection process. HSE concepts were not only targeted toward the problems, they were also used in the quest to develop effective solutions. Results obtained demonstrate that HSE concepts, when applied to urine specimen collection, can and do make a difference in terms of specimen quality and patient satisfaction. One low cost easily implemented targeted HSE-informed intervention effort resulted in a specimen contamination rate reduction of 16.6%. A second targeted HSE-informed intervention involving the redesign of the specimen cup, its instruction set, and additional sign placement made it three times less likely for participants to provide a contaminated MSCC sample. The redesigned specimen cup automatically captures and isolates an initial void sample from an MSCC sample, both derived from one continuously provided patient specimen. Clinical utility comes in the form of improved MSCC specimen quality and a separated initial void available for analysis using Nucleic Acid Amplification Testing (NAAT) or other test protocols. Capturing and isolating both an initial void and an MSCC at the same time allows for a more complete diagnostic workup utilizing a higher quality MSCC without requiring the patient to follow two different protocols to urinate into two different specimen cups. The redesigned specimen cup also provides for automatic overflow prevention, incorporates a new ergonomic grip, and a saddle adapter that provides affordances for both women and men in terms of urine capture and the reduced likelihood of urinating on one’s self.

Communications between air traffic controllers and pilots are critical to national airspace traffic management. Measuring communications in real time made by pilots and air traffic controllers has the potential to predict human error. In this thesis a measure for Deviations from Closed Loop Communications is defined and tested to predict a human error event, Loss of Separation (LOS). Six retired air traffic controllers were recruited and tested in three conditions of varying workload in an Terminal Radar Approach Control Facility (TRACON) arrival radar simulation. Communication transcripts from simulated trials were transcribed and coding schemes for Closed Loop Communication Deviations (CLCD) were applied. Results of the study demonstrated a positive correlation between CLCD and LOS, indicating that CLCD could be a variable used to predict LOS. However, more research is required to determine if CLCD can be used to predict LOS independent of other predictor variables, and if CLCD can be used in a model that considers many different predictor variables to predict LOS.

Despite the prevalence of teams in complex sociotechnical systems, current approaches to understanding workload tend to focus on the individual operator. However, research suggests that team workload has emergent properties and is not necessarily equivalent to the aggregate of individual workload. Assessment of communications provides a means of examining aspects of team workload in highly interdependent teams. This thesis set out to explore how communications are associated with team workload and performance under high task demand in all-human and human–autonomy teams in a command and control task. A social network analysis approach was used to analyze the communications of 30 different teams, each with three members operating in a command and control task environment of over a series of five missions. Teams were assigned to conditions differentiated by their composition with either a naïve participant, a trained confederate, or a synthetic agent in the pilot role. Social network analysis measures of centralization and intensity were used to assess differences in communications between team types and under different levels of demand, and relationships between communication measures, performance, and workload distributions were also examined. Results indicated that indegree centralization was greater in the all-human control teams than in the other team types, but degree centrality standard deviation and intensity were greatest in teams with a highly trained experimenter pilot. In all three team types, the intensity of communications and degree centrality standard deviation appeared to decrease during the high demand mission, but indegree and outdegree centralization did not. Higher communication intensity was associated with more efficient target processing and more successful target photos per mission, but a clear relationship between measures of performance and decentralization of communications was not found.

The choices of an operator under heavy cognitive load are potentially critical to overall safety and performance. Such conditions are common when technological failures arise, and the operator is forced into multi-task situations. Task switching choice was examined in an effort to both validate previous work concerning a model of task overload management and address unresolved matters related to visual sampling. Using the Multi-Attribute Task Battery and eye tracking, the experiment studied any influence of task priority and difficulty. Continuous visual attention measurements captured attentional switches that do not manifest into behaviors but may provide insight into task switching choice. Difficulty was found to have an influence on task switching behavior; however, priority was not. Instead, priority may affect time spent on a task rather than strictly choice. Eye measures revealed some moderate connections between time spent dwelling on a task and subjective interest. The implication of this, as well as eye tracking used to validate a model of task overload management as a whole, is discussed.