The Attention-Related Driving Errors Scale (ARDES) is a self-report measure of individual differences in driving inattention. ARDES was originally developed in Spanish (Argentina), and later adapted to other countries and languages. Evidence supporting the reliability and validity of ARDES scores has been obtained in various different countries. However, no study has been conducted to specifically examine the measurement invariance of ARDES measures across countries, thus limiting their comparability. Can different language versions of ARDES provide comparable measures across countries with different traffic regulations and cultural norms? To what extent might cultural differences prevent researchers from making valid inferences based on ARDES measures? Using Alignment Analysis, the present study assessed the approximate invariance of ARDES measures in seven countries: Argentina (n = 603), Australia (n = 378), Brazil (n = 220), China (n = 308). Spain (n = 310), UK (n = 298), and USA (n = 278). The three-factor structure of ARDES scores (differentiating driving errors occurring at Navigation, Manoeuvring and Control levels) was used as the target theoretical model. A fixed alignment analysis was conducted to examine approximate measurement invariance. 12.3 % of the intercepts and 0.8 % of the item-factor loadings were identified as non-invariant, averaging 8.6 % of non-invariance. Despite substantial differences among the countries, sample recruitment or representativeness, study results support resorting to ARDES measures to make comparisons across the country samples. Thus, the range of cultures, laws and collision risk across these 7 countries provides a demanding assessment for a cultural-free inattention while-driving. The alignment analysis results suggest that ARDES measures reach near equivalence among the countries in the study. We hope this study will serve as a basis for future cross-cultural research on driving inattention using ARDES.

Face masks, recently adopted to reduce the spread of COVID-19, have had the unintended consequence of increasing the difficulty of face recognition. In security applications, face recognition algorithms are used to identify individuals and present results for human review. This combination of human and algorithm capabilities, known as human-algorithm teaming, is intended to improve total system performance. However, prior work has shown that human judgments of face pair similarity-confidence can be biased by an algorithm's decision even in the case of an error by that algorithm. This can reduce team effectiveness, particularly for difficult face pairs. We conducted two studies to examine whether face masks, now routinely present in security applications, impact the degree to which this cognitive bias is experienced by humans. We first compared the influence of algorithm's decisions on human similarity-confidence ratings in the presence and absence of face masks and found that face masks more than doubled the influence of algorithm decisions on human similarity-confidence ratings. We then investigated if this increase in cognitive bias was dependent on perceived algorithm accuracy by also presenting algorithm accuracy rates in the presence of face masks. We found that making humans aware of the potential for algorithm errors mitigated the increase in cognitive bias due to face masks. Our findings suggest that humans reviewing face recognition algorithm decisions should be made aware of the potential for algorithm errors to improve human-algorithm team performance.

Research suggests that novice drivers are most susceptible to errors when detecting and responding to hazards. If this were true, then hazard training should be effective in improving novice drivers' performance. However, there is limited evidence to support this effectiveness. Much of this research has overlooked a fundamental aspect of psychological research: theory. Although four theoretical frameworks were developed to explain this process, none have been validated. We proposed a theoretical framework to more accurately explain drivers' behavior when interacting with hazardous situations. This framework is novel in that it leverages support from visual attention and driving behavior research. Hazard-related constructs are defined and suitable metrics to evaluate the stages in hazard processing are suggested. Additionally, individual differences which affect hazard-related skills are also discussed. This new theoretical framework may explain why the conflicts in current hazard-related research fail to provide evidence that training such behaviors reduces crash risk. Future research is necessary to empirically test this framework.

Detecting dangerous driving scenarios has been shown to be affected by driving experience, risk-taking or risk perception, and visual search. Given that the results are largely mixed, it is important to understand which individual differences affect drivers' hazard perception abilities. Three hundred ninety-eight drivers recruited throughout the USA participated in an online study by completing a hazard perception video task, two visual perception tasks, and surveys. A latent structural equation model was evaluated finding that visual perception skills and knowledge of traffic laws predicted hazard perception skills. Unlike much of the existing literature, driving experience and risk perception did not predict hazard perception skills. Additionally, the results of a latent structural equation mediation model revealed that driving experience did not mediate the relationship between hazard perception skills and knowledge of traffic laws. These results may prove useful in redesigning training programs and targeting the most susceptible individuals to decrease crash risks.

Encountering dangerous situations while driving is ubiquitous. Existing research suggest that specific populations such as, novice drivers are more prone to errors in detecting and responding to driving hazards. Hazard perception training programs have been developed in attempts to improve or accelerate the acquisition of such skills. However, drivers’ attitudes and knowledge regarding vulnerable populations and hazard perception training programs remain largely unknown. Three-hundred-five participants completed an online survey assessing their beliefs about influential factors affecting hazard detection and response, perceived usefulness and preferred types of training programs, and self-assessment of driving skills. Although many existing training programs are computer-based, participants preferred on-road hazard perception training. Such findings may assist in improving existing programs, which currently fail to show nearand far-transfer effects. Similarly, novice drivers reported being most likely to engage in training programs – possibly linked to their reported high value of the usefulness of such programs and awareness of their vulnerability to commit errors. Although autonomous vehicles should mitigate these errors, researchers and government officials suggest automated vehicles will not be commercially available for 10 years. Therefore, the results of the present study provide insight into drivers’ beliefs about dangerous situations, which may prove useful in developing and improving training programs aimed at mitigating crash risk.

Research suggests that drivers diagnosed with Attention-deficit/hyperactivity disorder (ADHD) are at increased risk of involvement in motor vehicle crashes due to inattention and impulsive behaviours. However, the behavioural characteristics of ADHD drivers which lead to a crash is not well understood. Therefore, the goal for this study was to evaluate the driving performance of individuals diagnosed with ADHD when they took their prescribed stimulant medication compared to when they refrained from taking their medication and a control condition. Forty-four participants (27 diagnosed with ADHD, 17 not diagnosed with ADHD) completed four simulated drives. ADHD drivers, when medicated, had similar pre-crash driving performance (velocity, brake force, steering movement, and lane offset) as the control condition. Conversely, when not medicated, ADHD drivers had significantly different driving performance compared to the medication and control conditions. These results highlight the importance that ADHD drivers take their medication, and noncompliance could be detected via in-vehicle safety systems.

Mind wandering is a poorly understood phenomenon that can undermine driving safety. Driving performance measures have been found to be associated with mind wandering (e.g., steering wheel movements, standard deviation of lateral position, and speed variation). However, no one measure can fully describe the driver behavior associated with mind wandering. Therefore, in this paper we explore the effect of mind wandering on nine steering measures with data collected from a study that included nine drivers over two sessions of driving over five days. Participants were periodically probed to report their attentional state–whether they were mind wandering or focusing on the task. We used two dimensionality-reduction techniques—Principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE)—to visualize the dimensions underlying the nine measures. Comparing PCA to t-SNE highlights the benefits of t-SNE in revealing the fine structure that differentiates driving behavior. These visualizations show that a) driver engagement increased during roadway curve segments, and b) mind wandering manifests itself through several types of steering behavior.

Driver distraction is a persistent threat to traffic safety. External distraction has been examined extensively, but few studies have focused on internal distraction such as mind wandering. Equivocal results from the few existing studies are likely due, at least in part, to different experimental methods. Mind wandering is commonly assessed using either a self-caught or probe-caught method. The current investigation sought to better understand the effects of mind wandering on driving performance using the self-caught method and the probecaught method. In the Self-Caught Experiment, lateral control measures such as, lateral position variability and steering reversal rate were greater when drivers reported on-task thoughts versus mind wandering. In the Probe-Caught Experiment, these results were not replicated using the traditional probe-caught analysis. Instead, when analyzing the results of the Probe-Caught Experiment in a similar manner as the Self-Caught Experiment, the results were replicated. These results highlight methodological concerns in detecting mind wandering while driving. Additional research is needed to determine which method should be employed in future studies.

Mind wandering is a pervasive threat to transportation safety, potentially accounting for a substantial number of crashes and fatalities. In the current study, mind wandering was induced through completion of the same task for 5 days, consisting of a 20-min monotonous freeway-driving scenario, a cognitive depletion task, and a repetition of the 20-min driving scenario driven in the reverse direction. Participants were periodically probed with auditory tones to self-report whether they were mind wandering or focused on the driving task. Self-reported mind wandering frequency was high, and did not statistically change over days of participation. For measures of driving performance, participant labeled periods of mind wandering were associated with reduced speed and reduced lane variability, in comparison to periods of on task performance. For measures of electrophysiology, periods of mind wandering were associated with increased power in the alpha band of the electroencephalogram (EEG), as well as a reduction in the magnitude of the P3a component of the event related potential (ERP) in response to the auditory probe. Results support that mind wandering has an impact on driving performance and the associated change in driver's attentional state is detectable in underlying brain physiology. Further, results suggest that detecting the internal cognitive state of humans is possible in a continuous task such as automobile driving. Identifying periods of likely mind wandering could serve as a useful research tool for assessment of driver attention, and could potentially lead to future in-vehicle safety countermeasures.

Long-term working memory (LT-WM; Ericsson and Kintsch, 1995) theory claims that the "transient portion of working memory is not necessary for continued comprehension" (pp. 225-226) and that "reading can be completely disrupted for over 30 s with no observable impairment of subsequent text comprehension" (p. 232). Follow-up research testing claims made by LT-WM report conflicting, indirect evidence for and against the theory. The goal for this research was to use individual differences in working memory capacity (WMC) to provide support for or against the theory that activation of information in working memory is necessary for successful comprehension of text. By extension, this tests predictions made by Ericsson and Kintsch's (1995) LT-'WM theory. Thirty six participants with either high or low WMC (18 in each group) read prompts while interrupted or not interrupted (control), then answered recognition and comprehension questions. We found that interruptions disrupted both the recognition and comprehension of text following interrupted reading for individuals with low WMC, but not for individuals with high WMC. These results support the view that the activation of information in working memory is necessary for successful recognition and comprehension of information and argue against LT-WM theory. We also provide initial evidence that working memory capacity may have a greater effect for interrupted reading compared to uninterrupted reading.

Mind wandering while performing various tasks has been shown to increase errors and impair task performance (Smallwood, McSpadden, & Schooler, 2008). Performance decrements elicited by mind wandering occur when attention necessary for the primary task is diverted to task-unrelated thoughts. While these results remain consistent in various domains, it is less understood how driving performance is affected by mind wandering. He Becic, Lee, and McCarley (2011) used a self-caught method to detect mind wandering, finding that variability in vehicle velocity decreased during states of mind wandering compared to attentive states. Other studies using a probe method to detect mind wandering have found that speed was greater during mind wandering (Yanko & Spalek, 2014), or that speed and speed variability were lower during mind wandering (Bencich, Gamboz, Coluccia, & Brandimonte, 2014) compared to attentive states. Although these studies provide some insight about the performance decrements and associated consequences of engaging in mind wandering while driving, the extent that mind wandering affects driving performance is not fully understood. The goal for this research was to further investigate differences in driving performance during mind wandering and attentive states. Participants performed two simulated driving scenarios and were instructed to indicate when they noticed they were just mind wandering (He et al., 2011; Smallwood & Schooler, 2015) by pressing a button on the steering wheel. Episodes of mind wandering were classified as 10 seconds before a button press with a three second buffer and, for comparison, instances of attentiveness relative to mind wandering episodes were classified as 10 seconds after a button press with a three second buffer (He et al., 2011). The results from linear mixed effects models showed that steering reversal rate, lane deviation, and lateral position were significantly greater during attentive states compared to states of mind wandering. These results may best be explained by Michon’s (1985) proposal that driving is a hierarchical task consisting of three levels. The first level includes basic operational control (e.g., speed and lane maintenance), while the higher-order levels are tactical (e.g., interacting with other vehicles, lane changing, etc.) and strategic (e.g., navigation, planning, and decision making). Our data suggest that mind wandering affected but did not necessarily disrupt driving performance. However, the present study only investigated basic operational-level metrics. Mind wandering may be more likely to negatively influence the detection of critical events and hazards–deviations from routine behaviors associated with higher level components of the driving task (i.e., tactical and strategic). For example, Yanko and Spalek (2014) reported that when participants were mind wandering they responded more slowly to critical events while driving. Further research is needed to determine whether the negative effects of mind wandering are more likely to occur within these higher order components of the driving tasks.

This reply is in response to Delaney and Ericsson (2016), who argue that the results of our recent research (Foroughi, Werner, Barragán, & Boehm-Davis, 2015) can be explained by Ericsson and Kintsch's (1995) long-term working memory (LTWM) theory. Our original work was designed to test the prediction made by LTWM theory that interruptions of up to 30 s in duration would not disrupt reading performance. We conducted the work following the method and outcome measures recommended by Ericsson and Kintsch (1995). Our data were clear: interruptions disrupted reading comprehension. We believe that these data do not support predictions made by LTWM theory. Although we appreciate Delaney and Ericsson's (2016) comments, we are unsure how best to move forward because it appears that some of their comments are not consistent with the published work on LTWM theory. Because of the inconsistent and contradictory claims surrounding LTWM theory, the theory does not appear to be falsifiable, or is in danger of becoming unfalsifiable. Creating and testing theory is vital for the advancement of psychological science, but it appears that testing predictions made by LTWM would be very difficult, if not impossible, given the fluid state of the theory. (PsycINFO Database Record

Objective: The goal for this study was to develop an English translation of the Attention-Related Driving Errors Scale (ARDES-US) and to determine its potential relationship with driver history and other demographic variables.Background: Individual differences in performance on vigilance and cognitive tasks are well documented, but less is known about susceptibility to attention-related errors while driving. The ARDES has been developed and administered in both Spanish and Chinese but to our knowledge has never been administered or examined in an English-speaking population.Method: Two hundred ninety-six English-speaking individuals completed a series of self-report measures, including the ARDES-US, Attention-Related Cognitive Errors Scale, Mindful Attention Awareness Scale, and Cognitive Failures Questionnaire.Results: A confirmatory factor analysis using maximum-likelihood estimates with robust standard errors revealed results largely consistent with previous versions of the ARDES, namely, the ARDES-Spain and ARDES-Argentina. Additionally, a number of new results emerged. Specifically, women, drivers who received traffic tickets within the previous 2 years, and those with a lower level of education all had a greater propensity toward self-reported driver inattention as measured by the ARDES-US. Further analyses revealed that these findings were independent of age, years of driving experience, and driving frequency.Conclusion: These results suggest that the ARDES-US is a valid and reliable measure of driver inattention with an English-speaking American sample.Application: Potential applications of the ARDES-US include identifying individuals who are at greater risk of attention-related errors while driving and suggesting individually tailored training and safety countermeasures.

Previous research suggests that being interrupted while reading a text does not disrupt the later recognition or recall of information from that text. This research is used as support for Ericsson and Kintsch's (1995) long-term working memory (LT-WM) theory, which posits that disruptions while reading (e.g., interruptions) do not impair subsequent text comprehension. However, to fully comprehend a text, individuals may need to do more than recognize or recall information that has been presented in the text at a later time. Reading comprehension often requires individuals to connect and synthesize information across a text (e.g., successfully identifying complex topics such as themes and tones) and not just make a familiarity-based decision (i.e., recognition). The goal for this study was to determine whether interruptions while reading disrupt reading comprehension when the questions assessing comprehension require participants to connect and synthesize information across the passage. In Experiment 1, interruptions disrupted reading comprehension. In Experiment 2, interruptions disrupted reading comprehension but not recognition of information from the text. In Experiment 3, the addition of a 15-s time-out prior to the interruption successfully removed these negative effects. These data suggest that the time it takes to process the information needed to successfully comprehend text when reading is greater than that required for recognition. Any interference (e.g., an interruption) that occurs during the comprehension process may disrupt reading comprehension. This evidence supports the need for transient activation of information in working memory for successful text comprehension and does not support LT-WM theory.

Many studies have found gender differences in mental rotation ability in young adults when completing mental rotation tests on paper and pencil (e.g., Peters et al., 1995; Vandenberg & Kuse, 1978). Two previous studies have been unable to replicate these findings when testing mental rotation ability inside of a virtual environment (Parsons et al., 2004; Rizzo et al., 2001). We created a new virtual mental rotation test (VMRT) based on a full, validated test of mental rotation ability (MRT-A; Peters et al., 1995) that 128 participants (79 females) completed while wearing an Oculus Rift DK1. Our data replicate previous findings of paper and pencil tests of mental rotation ability: men scored approximately one standard deviation higher ( d = .90) than women.