Driving technology has progressed significantly since the introduction of anti-lock braking and cruise control decades ago. Current driver assist features can alert drivers of oncoming vehicles and even take control to keep the vehicle centered within its lane. The level of trust that people place in automation can impact how they monitor and accept these automated systems. Previous research has shown several performance outcomes associated with improper calibrations of trust in automation. However, there is still a need to examine trust in the context of advanced driving technologies. Research has yet to sufficiently investigate factors influencing trust in assistive driving features. The current study was designed to examine whether changes to the driving environment might influence levels of trust in various driver assist features. In addition, this study sought to evaluate if individual characteristics might also influence automation trust. A sample of 166 participants completed a series of hypothetical driving vignettes describing both high and low complexity environments using five different driver assist features. It was hypothesized that trust in driving technologies would be related to scenario complexity, and that trust would vary across driving features (forward collision warning, cruise control, lane centering assist, adaptive cruise/traffic jam assist, and fully automated driving). Results showed that trust was significantly higher in low complexity than in high complexity scenarios. Furthermore, trust significantly varied across the five driver assist features. Findings also revealed that propensity to trust technology moderated the relationship between trust and driving feature manipulations. Similarly, dispositional trust in three of the five unique driving feature moderated the relationship between trust and scenario complexity. These findings have implications for the design and acceptance of autonomous systems, especially automated/assistive driving technologies, as well as other remotely operated vehicles.

A significant amount of research has investigated the underlying neural mechanisms that enable the direction of attention throughout a search array. The biased competition model (Desimone & Duncan, 1995) proposes that an attentional template (the neural instantiation of the search target) is created when the target representation in visual working memory (VWM) is communicated to frontal regions which then bias early visual areas to attend to target features. Despite this, much of the current work focuses solely on the target representation in VWM, which is only one small part of the attentional template according to biased competition. Thus, I used functional connectivity analyses, to examine theta-gamma coupling across the brain, to validate the biased competition model and add to recent work that focuses exclusively on VWM. My results show that frontal to posterior theta-gamma phase-amplitude coupling is a measure of the attentional template. Greater phase-amplitude coupling was consistently observed on trials in which attention, as measured by early search eye movements, was directed towards the target rather than a distractor and was associated with superior target recognition. These findings demonstrate that frontal to posterior biasing of early visual areas is a critical neural mechanism of the attentional template.

Older adults tend to under-utilize digital technology and online services that can yield substantial benefits to their health and wellbeing. Addressing this problem requires determining robust and consistent predictors of older adults' technology use. Also, few studies have examined older adults who are elite users of digital technology, who may provide insights into how individuals can prepare to become competent users of future technologies as they age. To address these gaps in the technology and aging literature, this dissertation offers (1) large-scale machine learning analyses, (2) longitudinal perspectives, (3) age group comparisons across the adult life span, (4) the novel recruitment of elite, older users of digital technology, and (5) the development and validation of a technology use scale focused on current innovations. In Study 1, data from the Health and Retirement Study were used. Machine learning classified Internet users versus non-users with an accuracy of ~80%. Across a 14-year span, results largely supported current models of aging and technology use. Age, cognition, and socioeconomics emerged as the most robust and consistent predictors of Internet use from competition with hundreds of variables. In Study 2, the outcome variable was expanded to include nine domains of technology use. Elite, older users exhibited many markers of successful aging, including higher levels of cognition, socioeconomics, and self-efficacy. Across studies, results suggested that skills needed to engage with technology at a basic level differ slightly from those needed to reach higher levels of technology use. Specifically, poor episodic long-term memory may pose a barrier to basic technology use among older adults (e.g., assessing the Internet), while better short-term memory is required to achieve elite-level technology use. These results highlight the potential value of exposure to new technology at a younger age – when there are fewer barriers of entry (e.g., cognitive limitations) and a foundation of technology use principles can be developed and built upon across adulthood.

Emotional design elements have recently been added to the research in cognitive load and multimedia learning (Um et al., 2012). One aspect of eliciting positive emotions is to use anthropomorphic design, which has been found to increase learning performance (Um et al., 2012; Plass et al., 2014; Park et al., 2015; Schneider et al., 2018). The current research aimed to investigate three design factors in three studies: anthropomorphism in verbal and visual design, single-frame or multi-frame illustrations, and realism of the anthropomorphic visual design. The first study confirmed that the anthropomorphic verbal and visual materials were perceived as anthropomorphic by the target population. In the second and third study, college students were tested on their learning performance, affective status, intrinsic motivation, metacognitive abilities, and cognitive load levels. The second study investigated whether learning from single-frame or multi-frame illustrations along with verbal presentation of information would impact learning performance, cognitive load, metacognition, affective and motivational experiences. The role of spatial ability was also considered. Results indicated no significant differences among the groups. However, higher spatial ability resulted in higher intrinsic motivation for individuals studying with single-frame but not multi-frame illustrations. Additionally, lower spatial ability led to higher metacognition. In the third study, realism (no anthropomorphism, low fidelity, and high fidelity) of the humanlike visual illustrations and anthropomorphic language were studied. College students' learning performances were measured by comprehension and transfer tests, and intrinsic motivation, affect, and cognitive load levels were measured by self-report measurements. Overall, it was found that the humanlike visual design and the degree of fidelity of the visual design did not impact learning performance, affective status, and motivation. However, the number of interesting details (seductive details) remembered about the anthropomorphic design elements mediated the relationship between the type of design and learning performance. Using anthropomorphic language along with realistic illustrations resulted in higher seductive details recall performance, which in turn, predicted higher learning performance on both transfer and comprehension tests. Results were discussed considering Cognitive Load Theory and Cognitive-Affective Theory of Learning with Media.

This research examined how information regarding a robot teammate's reliability and the consequences for mistakes made by a robot in its task influence reliance on the robot by a human teammate. Of interest in this research was the notion of appropriate reliance: relying on a robot teammate's decisions when it is performing well and not relying on its decisions when it is performing poorly. An experiment was conducted in which participants interacted with an autonomous robot teammate while performing a cordon and search operation within a virtual reality simulation environment. Participants were responsible for monitoring the perimeter of a search area while their robot teammate searched the area for target objects. The robot's reliability shifted between 90% (good) or 10% (poor) based on the environment it was currently searching. Participants were assigned to one of four experimental groups that differed according to: (a) the information they were provided about the robot teammate's reliability and which factors influenced it (minimal information or complete information), and (b) the specific consequences for the robot missing target objects during its search (low risk or high risk). Findings indicated that participants provided with complete reliability information relied more appropriately on the robot's decisions (i.e., participants relied more when the robot performed well and relied less when it was performing poorly) than participants who did not receive this information. Appropriate reliance was not, however, affected by the consequences for mistakes made on the robot's task. These results provide support for the notion that informing individuals of the factors influencing a robot's reliability helps them to rely more appropriately on its decisions.

Insomnia is a sleep disorder which is classified by one's persistent inability to fall asleep or maintain sleep. One common yet controversial approach to treating insomnia is sleep hygiene education (SHE). Sleep hygiene is defined as behaviors that promote quality sleep. SHE is typically provided through as a paper sheet containing a list of recommendations, and the findings regarding its efficacy are mixed. Providing insomnia sufferers with a SHE treatment modality that offers practice, feedback, and motivation may be effective at treating insomnia. Therefore, the first goal of the present study is to examine the efficacy of a game-based SHE intervention. After using the game-based intervention for 30 days, participants had significant improvement in overall sleep quality, as well as numerous subcategories of sleep quality. Participants also had a significant decrease in state levels of anxiety. Moreover, previous research has found that certain personality traits are related to one's propensity to achieve a flow state, which is the experience of colloquially "being in the zone" when completing a task or activity. Therefore, the second goal of the study was to examine whether personality predicted flow propensity. Personality was not found predict flow propensity. Finally, a third goal of the study was to examine whether one's propensity for flow predicted sleep improvement. In other words, it was expected that those with a higher propensity for flow would experience better treatment outcomes due to their ability to engage more with the intervention. However, flow propensity was not found to predict sleep improvement. The study's findings collectively demonstrate the efficacy of a game-based treatment approach to insomnia, regardless of individual differences. Recommendations for future research directions are provided.

With the onset of globalization, the economic contexts and working conditions within many countries are changing, presenting new challenges' for governments, organizations, and workers. Amid these challenges, concerns about personal finances are prevalent among employees and detrimental to workers' health, well-being, and families. Research on how this financial stress affects employees at work is lacking. In this thesis, I propose an appraisal-based model of financial stress whereby actual income and expenses are related to perceptions of income adequacy to afford wants and needs. These adequacy perceptions are, in turn, related to financial strain, representing a heightened negative affective state regarding one's financial situation. I hypothesize that, through a drain in emotional resources, financial strain will negatively predict life satisfaction by potentially inhibiting participation in healthy, enjoyable behaviors. I argue that this drain in emotional resources will also inhibit successful task performance and restrict participation in discretionary citizenship behaviors. Data from two working samples provide support for the hypothesized financial stress model and establish preliminary evidence of construct validity for new financial stress scales. In a prospective investigation, financial strain fully mediated the effects of income adequacy on subsequent life satisfaction, but was not related to job performance. Instead, perceived income adequacy to afford wants had a direct negative relationship with both task performance and citizenship behaviors at work, while income adequacy to afford needs had a positive direct effect on organizational citizenship behaviors. This work resolves many conceptual inconsistencies about financial stress in the literature, and contributes to the understanding of how income perceptions and financial stress might influence psychological resources and work motivation. This work has important implications for how organizations manage employees who may be experiencing low income adequacy and high financial strain. Finally, there are several meaningful opportunities for future research that would substantially build upon existing theory and evidence in this new area of financial stress and work.

The purpose of this study is to determine under what conditions multiple minimally intrusive physiological sensors can be used together and validly applied for use in areas which rely on adaptive systems including adaptive automation and augmented cognition. Specifically, this dissertation investigated the physiological transitions of operator state caused by changes in the level of taskload. Three questions were evaluated including (1) Do differences exist between physiological indicators when examined between levels of difficulty? (2) Are differences of physiological indicators (which may exist) between difficulty levels affected by spatial ability? (3) Which physiological indicators (if any) account for variation in performance on a spatial task with varying difficulty levels? The Modular Cognitive State Gauge model was presented and used to determine which basic physiological sensors (EEG, ECG, EDR and eye-tracking) could validly assess changes in the utilization of two-dimensional spatial resources required to perform a spatial ability dependent task. Thirty-six volunteers (20 female, 16 male) wore minimally invasive physiological sensing devices while executing a challenging computer based puzzle task. Specifically, participants were tested with two measures of spatial ability, received training, a practice session, an experimental trial and completed a subjective workload survey. The results of this experiment confirmed that participants with low spatial ability reported higher subjective workload and performed poorer when compared to those with high spatial ability. Additionally, there were significant changes for a majority of the physiological indicators between two difficulty levels and most importantly three measures (EEG, ECG and eye-tracking) were shown to account for variability in performance on the spatial task.

Previous research has highlighted key taxonomic factors that have been found to influence human performance on vigilance tasks. However, previous literature has focused on research conducted in laboratory settings but has not examined vigilance tasks in remote environments. The present dissertation addresses this gap in the literature by examining human performance on a remote vigilance task, as well as workload and stress associated with the task. Qualitative data were collected to further understand the environment and distractions that participants experienced. Across three experiments, 372 participants were asked to complete a vigilance task and answer surveys pertaining to stress, workload, and ambient distractions. Experiment one manipulated the taxonomic factors of event rate and signal discrimination. Next, experiment two manipulated the taxonomic factors of event rate and source complexity. Finally, experiment three manipulated the taxonomic factors of event rate and task type. Across all three experiments, results identified significant differences in performance for the low and high event rate conditions, which are consistent with previous findings. Furthermore, signal discrimination type, source complexity, and task type (i.e., sensory vs. cognitive) resulted in significant differences between groups on measures of performance. All three experiments reported changes in perceived stress and increases in perceived workload. Ambient distractions, when they occurred, did impact performance, but only for experiment two. Overall, this study provides further support for several facets of the vigilance taxonomy and attempts to understand the impact of remote environments and ambient distractions on vigilance performance. Thus, these findings are advancing our understanding of the vigilance taxonomy and how environmental effects may influence human performance.

Past research has shown that there is a relationship between body posture and cognitive processes. However, postures used with technological devices has not been studied more extensively. The purpose of this study was to examine posture effects when using a mobile device on interpretation bias, mood, and physical tension. Each participant was randomly assigned one of three conditions: sitting slumped, sitting upright, or lying down. Participants were asked to complete the Scrambled Sentences Task (SST), a task of unscrambling emotional and neutral sentences, to measure their interpretation bias. Additional questions were asked to measure the participant's physical tension and mood. Results suggested no significant differences in interpretation bias depending on posture. There was no significant difference in the performance of unscrambling emotional sentences compared to neutral ones for sitting slumped and sitting upright. When lying down, participants unscrambled fewer neutral sentences compared to emotional ones. Physical tension was found to be a mediator for the relationship between posture (slumped and upright) and mood. The results of this study provide insight of possible confounding variables influencing the relationship between posture and mood.It additionally showed that emotional content is processed differently compared to neutral content when lying down. Further research is needed to understand how physical tension caused by posture being altered when using mobile device affects psychological well-being.