Joseph B. Lyons

The Influence of Neuroticism, Extraversion and Openness on Stress Responses

The present research moved beyond focusing on negative dispositions to investigate the influence of positive aspects of personality, namely extraversion and openness, on stress responses including appraisals, affect and task performance. Challenge appraisals occur when stressor demands are deemed commensurate with coping resources, whereas threat appraisals occur when demands are believed to outweigh coping resources. We examined the unique influence of personality on stress responses and the mediating role of appraisals. Personality was assessed, and then participants (N = 152) were exposed to a validated math stressor. We found unique effects on stress responses for neuroticism (high threat and negative affect and low positive affect), extraversion (high positive and low negative affect) and openness (high positive and low negative effect and better performance). Mediation analyses revealed that neuroticism indirectly worsened performance, through threat appraisals, and that openness indirectly increased positive affect through lower threat. These findings highlight the importance of investigating multiple aspects of personality on stress responses and provide an avenue through which stress responses can be changed-appraisals. Only by more broad investigations can interventions be tailored appropriately for different individuals to foster stress resilience.

The Relationship of Engagement and Job Satisfaction in Working Samples

ABSTRACT The present study explored the factor structure of engagement and its relationship with job satisfaction. The authors hypothesize that work engagement comprises 3 constructs: vigor, dedication, and absorption. Using structural equation modeling, the authors analyze data from 3 archival data sets to determine the factor structure of engagement. In addition, they examine the hypothesis that engagement and job satisfaction are separate but related constructs, using structural equation modeling and hierarchical regression. The authors test models in which engagement and job satisfaction items loaded onto a single latent variable and 1 in which they loaded onto 2 separate variables. Results from the confirmatory factor analysis indicate engagement has 3 factors. In addition, confirmatory factor analysis and hierarchical regressions indicate engagement and job satisfaction are separate constructs. Last, hierarchical regressions demonstrated the constructs have different relationships with the areas of work–life scale. Implications for theory and research are discussed.

Human-human reliance in the context of automation.

Objective: The current study examined human–human reliance during a computer-based scenario where participants interacted with a human aid and an automated tool simultaneously. Background: Reliance on others is complex, and few studies have examined human–human reliance in the context of automation. Past research found that humans are biased in their perceived utility of automated tools such that they view them as more accurate than humans. Prior reviews have postulated differences in human–human versus human–machine reliance, yet few studies have examined such reliance when individuals are presented with divergent information from different sources. Method: Participants (N = 40) engaged in the Convoy Leader experiment. They selected a convoy route based on explicit guidance from a human aid and information from an automated map. Subjective and behavioral human–human reliance indices were assessed. Perceptions of risk were manipulated by creating three scenarios (low, moderate, and high) that varied in the amount of vulnerability (i.e., potential for attack) associated with the convoy routes. Results: Results indicated that participants reduced their behavioral reliance on the human aid when faced with higher risk decisions (suggesting increased reliance on the automation); however, there were no reported differences in intentions to rely on the human aid relative to the automation. Conclusion: The current study demonstrated that when individuals are provided information from both a human aid and automation, their reliance on the human aid decreased during high-risk decisions. Application: This study adds to a growing understanding of the biases and preferences that exist during complex human–human and human–machine interactions.

Trustworthiness and IT Suspicion: An Evaluation of the Nomological Network

Objective: The authors evaluated the validity of trust in automation and information technology (IT) suspicion by examining their factor structure and relationship with decision confidence. Background: Research on trust has burgeoned, yet the dimensionality of trust remains elusive. Researchers suggest that trust is a unidimensional construct, whereas others believe it is multidimensional. Additionally, novel constructs, such as IT suspicion, have yet to be distinguished from trust in automation. Research is needed to examine the overlap between these constructs and to determine the dimensionality of trust in automation. Method: Participants (N = 72) engaged in a computer-based convoy scenario involving an automated decision aid. The aid fused real-time sensor data and provided route recommendations to participants who selected a route based on (a) a map with historical enemy information, (b) sensor inputs, and (c) automation suggestions. Measures for trust in automation and IT suspicion were administered after individuals interacted with the automation. Results: Results indicated three orthogonal factors: trust, distrust, and IT suspicion. Each variable was explored as a predictor of decision confidence. Distrust and trust evidenced unique influences on decision confidence, albeit at different times. Higher distrust related to less confidence, whereas trust related to greater confidence. Conclusion: The current study found that trust in automation was best characterized by two orthogonal dimensions (trust and distrust). Both trust and distrust were found to be independent from IT suspicion, and both distrust and trust uniquely predicted decision confidence. Application: Researchers may consider using separate measures for trust and distrust in future studies.

Accounting for the human in cyberspace: Effects of mood on trust in automation

The present study examined the effects of mood on trust in automation over time. Participants (N = 72) were induced into either a positive or negative mood and then completed a computer-based task that involved the assistance of an automated aid. Results indicated that mood had a significant impact on initial trust formation, but this impact diminishes as time and interaction with the automated aid increases. Implications regarding trust propensity and trustworthiness are discussed, as well as the dynamic effects of trust over time.

Understanding predictors of engagement within the military.

The current study explored organizational antecedents of employee engagement in a military organization. A survey was administered to junior military personnel assessing leadership effectiveness, role clarity, organizational culture, and peer group interactions as predictors of engagement. Leaderships influence on engagement was expected to be partially mediated by role clarity and organizational culture. Engagement was predicted to fully mediate the relationship between the aforementioned variables and turnover intentions. Results indicated that leaderships influence on engagement was fully mediated by role clarity and organizational culture. In addition, engagement fully mediated the relationship between all variables and turnover intentions.

Engineering Trust in Complex Automated Systems

We studied the transparency of automated tools used during emergency operations in commercial aviation. Transparency (operationalized as increasing levels of explanation associated with an automated tool recommendation) was manipulated to evaluate how transparent interfaces influence pilot trust of an emergency landing planning aid. We conducted a low-fidelity study in which commercial pilots interacted with simulated recommendations from NASA’s Emergency Landing Planner (ELP) that varied in their associated levels of transparency. Results indicated that trust in the ELP was influenced by the level of transparency within the human–machine interface of the ELP. Design recommendations for automated systems are discussed.

Transparency in a Human-Machine Context: Approaches for Fostering Shared Awareness/Intent

Advances in autonomy have the potential to reshape the landscape of the modern world. Yet, research on human-machine interaction is needed to better understand the dynamic exchanges required between humans and machines in order to optimize human reliance on novel technologies. A key aspect of that exchange involves the notion of transparency as humans and machines require shared awareness and shared intent for optimal team work. Questions remain however, regarding how to represent information in order to generate shared awareness and intent in a human-machine context. The current paper will review a recent model of human-robot transparency and will propose a number of methods to foster transparency between humans and machines.

Adaptive performance: a criterion problem

Purpose – The purpose of this paper is to present an empirical examination of the convergent validity of the two foremost measurement methods used to assess adaptive performance: subjective ratings and objective task scores. Predictors of adaptive performance have been extensively examined, but limited research attention has been directed at adaptability itself as a validated construct within the job performance domain. Due to this neglect, it is unclear if researchers can generalize findings across criterion measurement methods.Design/methodology/approach – Teams of five (275 individuals) performed a computer‐based task that involved a series of disruptions requiring an adaptive response. In addition to post‐disruption task scores, subjective self‐ and peer‐ratings of adaptive performance were collected.Findings – Results did not indicate strong support for the convergent validity of subjective and objective measures. Although the measures were significantly related (r=0.47, p < 0.001) and shared a relat...

Trust-Based Analysis of an Air Force Collision Avoidance System:

This case study analyzes the factors that influence trust and acceptance among users (in this case, test pilots) of the Air Force’s Automatic Ground Collision Avoidance System. Our analyses revealed that test pilots’ trust depended on a number of factors, including the development of a nuisance-free algorithm, designing fly-up evasive maneuvers consistent with a pilot’s preferred behavior, and using training to assess, demonstrate, and verify the system’s reliability. These factors are consistent with the literature on trust in automation and could lead to best practices for automation design, testing, and acceptance.