Types Of Distraction Research Articles

Influence of Distraction Factors on Performance in Laparoscopic Surgery in Immersive Virtual Reality: Study Protocol of a Cross-Over Trial in Medical Students and Residents-DisLapVR.

Working in an operating room (OR) is physically and mentally challenging: the operation itself demands the surgeon's full attention, while time and cost efficiency constraints, daily planning, and emergency care interfere with the procedure. Thus, multitasking becomes an integral surgical competence. This study aims to examine the effect of disruptions during surgery in a highly immersive virtual reality (IVR) operation environment combined with a virtual reality (VR) laparoscopy simulator. This study aims to identify distractions in the OR and their importance in the clinical setting. An IVR environment was created using a high-resolution, stereoscopic 360° video of the OR. Different distractions were identified, classified as auditory, visual, or audio-visual, and recorded accordingly. The surrounding was combined with a VR laparoscopic simulator. Participants-medical students and surgical residents-received proficiency-based training in basic laparoscopic skills and were blinded to the aim of the experiment. Following a cross-over design, each participant received a unique order of virtual distraction factors while performing tasks on the laparoscopic simulator. During the experiment, subjective passing of time, stress, heart rate, and visually induced motion sickness are recorded. After the experiment, validated questionnaires for usability, immersion, and stress were completed, as well as subjective evaluation of the distractions. The questionnaires used included the system usability scale, Self-Assessment Manikin score, National Aeronautics and Space Administration Task Load Index, and the immersion rating scale as described by Nichols. Performance in the laparoscopic tasks in relation to distractions will be evaluated by the Wilcoxon test and ANOVA for continuous variables. Subgroup analyses in regard to age, gender, and expertise (medical students vs surgical residents) are planned. The described trial started in August 2022 and is ongoing. By July 2024, a total of 30 medical students and 9 surgeons have completed the study. We present a study protocol aiming to identify the impact of different disruptions in OR during laparoscopic training in IVR. Hence, it may lead to an improved awareness of distractions and facilitate accommodations toward an improved work environment. Prior research leads to the hypothesis that the performance of a more experienced surgeon is less impacted by distractions than the performance of inexperienced surgeons and medical students. Furthermore, we investigate which type of distraction has the largest impact on performance. With this knowledge, specific multitasking training can be devised, which may be particularly useful in medical education, for which VR might play a leading role. Additionally, workplace surroundings in the OR can be optimized with this knowledge. German Registry for Clinical Trials DRKS00030033; https://drks.de/search/en/trial/DRKS00030033. DERR1-10.2196/59014.

Effects of two types of distractions on ratings of perceived exertion and affective response during acute high-intensity cycling exercise for fair cardiorespiratory fitness level in men

Effects of two types of distractions on ratings of perceived exertion and affective response during acute high-intensity cycling exercise for fair cardiorespiratory fitness level in men

Prevalence and predictors of driver distractions in Cyprus: An observational study

ObjectiveDriver distractions are a significant contributor to road accidents and fatalities worldwide. The present research investigated the prevalence of observable driver distractions on both sides of Nicosia, as well as exploring the effect of drivers’ characteristics and time-related variables on their prevalence. MethodsRoadside observations were conducted at eight randomly selected locations in the city of Nicosia, Cyprus. Four of these sites were located in the area of Nicosia controlled by the Republic of Cyprus, and the other four were in the area that is referred to as the Turkish Republic of Northern Cyprus (TRNC) by its administration. ResultsA total of 16,070 drivers were observed, with 8,948 being in the Republic of Cyprus (South) and 7,122 in the Turkish-controlled section of Nicosia (North). A slightly higher proportion of drivers were observed driving distracted in the South (28.0%) than was found in the northern part of the city (25.7%). The most commonly observed secondary tasks in the South were using headphones (9.2%), talking to a passenger (8.1%) and using a mobile 0.4%, 3.7% talking and 2.7% texting). In contrast, the most commonly observed secondary tasks in the North were talking to passengers (10.2%), wearing headphones (8.4%) and using a mobile 0.6% for talking and 2.5% for texting). Gender-related differences were found for a number of different distractions (i.e., talking to passengers, drinking, and handheld mobile phone conversations), and age emerged as a significant predictor for most secondary tasks, including talking to passengers, smoking, hands-free mobile phone use, handheld mobile phone use, texting/keying numbers, drinking and engagement in any type of distraction (all distractions combined). The overall pattern for age was that middle-aged and older drivers were less likely to be distracted than younger drivers. ConclusionsA relatively high proportion of drivers on both sides of Nicosia were engaged in a secondary task while driving. These findings clearly indicate that younger drivers are more likely to drive distracted, which probably contributes to their higher crash rates.

Mobile phone conversation during nighttime driving: Effects on driving behavior

Objectives This study aims to investigate the impact of mobile phone use (specifically, conversation), considering various use modes, on driving behavior at night. Mobile phone use is a source of driver distraction and has been associated with increased accident risk. Driving at night also entails higher accident risk and severity compared to daytime driving. Several studies have investigated the impact of mobile phone use on driving behavior; however, only a few have explored the differences between the different use modes. Most present studies involved daytime driving, although mobile phone use at night is equally if not more prevalent. Method A driving simulator experiment was designed in which 55 participants drove under nighttime simulator conditions, in different road environments (urban and rural) and under different types of distraction: no distraction, handheld, wired earphone, and speaker mode. The drives were performed during late afternoon and evening hours to resemble nighttime conditions both in the simulator and in the actual environment. Participants also completed a questionnaire for collection of different types of data. Results Results highlight the effect of mobile phone use on driving behavior, through specific indicators. Mobile phone use resulted in reduced 85th percentile driving speed and 85th percentile acceleration and increased reaction time and lateral deviation. However, safer stopping distance was observed in rural roads. Parameters relative to mobile phone use familiarity and exposure were found to mitigate mobile phone use effects. Conclusions Mobile phones affect driving behavior at night in a similar manner to that noted in several different studies considering daytime driving. The hands-free regulation should be revisited, because driver distraction also occurred under this particular use mode. Further research is required considering mobile phone use familiarity and exposure and effects of mobile phone use, because the latter is reduced with an increase in the former. Stopping distance, an understudied but more immediate surrogate measure of road safety, was increased with mobile phone use, mainly as a result of the risk compensation behavior that drivers adopt, indicating that more research is required in this field.

Investigating work-related distraction’s impact on male taxi driver safety: A hazard-based duration model

With the increasing use of phone-based ride-hailing apps, concerns have arisen regarding road safety and driver distraction. Despite the recognized safety risks of driver distraction, limited research has explored how distractions from various ride-hailing systems affect drivers in the taxi industry. To close this gap, the current research utilized a driving simulator experiment involving 51 male taxi drivers in two road environments (urban street and motorway) and three distracted driving conditions (no distraction, auditory distraction via radio dispatching system, and visual-manual distraction via mobile application). A car-following scenario with sudden brake events was incorporated into the experiments because this is a typical safety–critical situation where attention will determine the outcome. The collected performance indicators include brake reaction time, time headway, and car-following distance. The grouped random parameters Weibull accelerated failure time model was applied to model the duration data under different road conditions. The brake reaction time and time headway are dependent variables, while the car-following distance is a covariate in the models. The results indicate that although taxi drivers show longer brake reaction time when distracted by mobile app and radio system, this does not necessarily equate with greater risk or reduced safety since they compensate for the risk of rear-end crashes by maintaining a longer time headway. In general, taxi drivers’ brake reaction time and time headway are more profoundly affected by mobile apps when distracted in both urban and motorway scenarios. This highlights the elevated risks associated with such technologies. In addition, significant interaction effects revealed the observed heterogeneity, which suggests that drivers’ personal characteristics influence the relationship between distraction type and driving performance. This research provides valuable insights for designing safer ride-hailing operations and systems.

Identifying the causal effects of driver distraction on hazardous actions at intersections based on propensity score weighting

Distracted driving is a threat to traffic safety that can result in more traffic crashes. Although previous studies have been conducted to explore the relationship between driver distraction and hazardous driving actions, few studies are available to identify the causation between them. Thus, the study intended to evaluate the causal effects of distraction on hazardous driving actions at intersections based on the crash data extracted from the Crash Report Sampling System (2021–2022). The multinomial logit model was employed to reveal the factors contributing to driver distraction. Then, propensity score weighting was adopted to balance the factor distributions between distraction and non-distraction cases to identify the causal effects on hazardous actions. Results indicated that 1) the propensity of distraction is relevant to factors such as the driver’s age, gender, vehicle type, speed limit, area, weather, and light condition, 2) driver distraction can significantly increase the probability of risky actions including speeding, running red lights, failing to obey stop signs, failing to yield, following too closely, and 3) the causal effects show great diversity for different distraction types. The findings serve to understand the influence mechanism of distraction on specific crash risks and develop countermeasures to reduce distraction and hazardous driving actions.

Augmented Recognition of Distracted Driving State Based on Electrophysiological Analysis of Brain Network.

In this study, we propose an electrophysiological analysis-based brain network method for the augmented recognition of different types of distractions during driving. Driver distractions, such as cognitive processing and visual disruptions during driving, lead to distinct alterations in the electroencephalogram (EEG) signals and the extracted brain networks. We designed and conducted a simulated experiment comprising 4 distracted driving subtasks. Three connectivity indices, including both linear and nonlinear synchronization measures, were chosen to construct the brain network. By computing connectivity strengths and topological features, we explored the potential relationship between brain network configurations and states of driver distraction. Statistical analysis of network features indicates substantial differences between normal and distracted states, suggesting a reconfiguration of the brain network under distracted conditions. Different brain network features and their combinations are fed into varied machine learning classifiers to recognize the distracted driving states. The results indicate that XGBoost demonstrates superior adaptability, outperforming other classifiers across all selected network features. For individual networks, features constructed using synchronization likelihood (SL) achieved the highest accuracy in distinguishing between cognitive and visual distraction. The optimal feature set from 3 network combinations achieves an accuracy of 95.1% for binary classification and 88.3% for ternary classification of normal, cognitively distracted, and visually distracted driving states. The proposed method could accomplish the augmented recognition of distracted driving states and may serve as a valuable tool for further optimizing driver assistance systems with distraction control strategies, as well as a reference for future research on the brain-computer interface in autonomous driving.

COGNITIVE DRIVER ACTION RECOGNITION

Operating an automobile is a multifaceted endeavor, demanding unwavering focus and attention from the driver. Distracted driving, encompassing any behavior that diverts the driver's concentration away from the road, poses a grave threat to road safety. Alarming statistics reveal that approximately 1.35 million lives are tragically lost each year due to road traffic accidents, inflicting significant economic ramifications, with road traffic crashes costing most nations an estimated 3% of their gross domestic product. The primary objective of our project is to put in place an exhaustive process for identifying potentially dangerous driving behaviors and discerning appropriate driving practices in light of this disappointing reality. By utilizing a wide range of machine learning models, we aim to correctly classify the given photos into discrete groups that correlate to various types of driver distraction. Furthermore, our work goes beyond simple classification; it also aims to perform a comparison analysis of different Machine Learning Models in order to determine how well they perform and how accurate they are in the context of cognitive driver action detection. This all-encompassing strategy demonstrates our dedication to improving traffic safety and lowering the possibility of collisions and injuries to other drivers. Key Words: Transfer learning, Deep learning, Image classification, Distracted driving, TensorFlow.

Virtual Reality Distraction for Needle-Related Pain and Distress in Children: A Multicenter Randomized Controlled Trial.

This international multicenter randomized controlled trial aimed to compare the effectiveness of virtual reality (VR) distraction with an identical non-VR game in reducing needle-related pain and anxiety in children undergoing venous blood draw. The study involved 304 children aged 5-9 years undergoing a blood draw procedure, randomly allocated to one of three groups: VR distraction, non-VR distraction, and control group (usual care). The distraction task was based on the Multiple Object Tracking (MOT) paradigm, and the game was identical in design and gameplay for both VR and non-VR distraction groups. The primary outcome was self-reported pain intensity using the Faces Pain Scale-Revised (FPS-R). Secondary outcomes included child distress, attention/distraction to the blood draw, and parent and medical staff satisfaction with procedure. Analyses were conducted using analysis of variance and multivariable linear regression models. The results showed that VR distraction and non-VR distraction performed similarly, showing large effect sizes compared with standard care. There was no significant difference between the two types of distraction. The study's findings suggest that VR and non-VR distraction are similarly effective in reducing needle-related pain and anxiety in children undergoing venous blood draw. This is the first well-powered study comparing modern VR distraction with an identical task displayed on a smartphone or monitor screen. The study's results have important implications for using VR in clinical settings and suggest that investing in expensive VR equipment for acute pain management may not be necessary. The study protocol was pre-registered on Open Science Framework at https://osf.io/frsyc.

Brain morphological changes and functional neuroanatomy related to cognitive and emotional distractors during working memory maintenance in post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is associated with abnormalities in the processing and regulation of emotion as well as cognitive deficits. This study evaluated the differential brain activation patterns associated with cognitive and emotional distractors during working memory (WM) maintenance for human faces between patients with PTSD and healthy controls (HCs) and assessed the relationship between changes in the activation patterns by the opposing effects of distraction types and gray matter volume (GMV). Twenty-two patients with PTSD and twenty-two HCs underwent T1-weighted magnetic resonance imaging (MRI) and event-related functional MRI (fMRI), respectively. Event-related fMRI data were recorded while subjects performed a delayed-response WM task with human face and trauma-related distractors. Compared to the HCs, the patients with PTSD showed significantly reduced GMV of the inferior frontal gyrus (IFG) (p < 0.05, FWE-corrected). For the human face distractor trial, the patients showed significantly decreased activities in the superior frontal gyrus and IFG compared with HCs (p < 0.05, FWE-corrected). The patients showed lower accuracy scores and slower reaction times for the face recognition task with trauma-related distractors compared with HCs as well as significantly increased brain activity in the STG during the trauma-related distractor trial was observed (p < 0.05, FWE-corrected). Such differential brain activation patterns associated with the effects of distraction in PTSD patients may be linked to neural mechanisms associated with impairments in both cognitive control for confusable distractors and the ability to control emotional distraction.

Vertebral Artery Injury in Cervical Spine Fracture Dislocation: An Observational Study in a Tertiary Care Center.

The incidence of traumatic vertebral artery injury (VAI) associated with cervical spine trauma varies widely in published trauma series. The primary aim of this study was to determine the incidence of traumatic VAIin patients who suffered cervical spine injuries by means of routine magnetic resonance imaging, and the secondary objective was to identify any associations with injury mechanism, level ofinjury, and neurologic injury severity. Materials and methods: A retrospective review was conducted on 96 patients who suffered cervical spine fracture dislocation with or without an associated spinal cord injury (SCI) in Indian Spinal Injuries Center (ISIC), New Delhi, Indiafrom January 2013 to April 2023. Cervical magnetic resonance imaging (MRI) was used to diagnose VAI. Patient's age, sex, cervical injury level, mechanism of injury, neurologic level of injury, association with foraminal fracture, facet dislocation,and clinical sequelae of vertebral artery injury were analyzed. In this study, of 96 patients who met the inclusion criteria, 18 patients (18.75%) had VAI on the MRI study. Thirteen (72.22%) of the eighteen patients had right-sided injuries, four (22.22%) had left-sided injuries, and one (5.55%) had bilateral injuries. There was an associated SCI in every VAI patient. VAI was significantly more common in patients who had ASIA A (61%, n = 11) and ASIA B (22%, n = 4)injuries, and no VAI was noted in neurologically intact patients (p<0.001). The incidence of VAI was higher in the flexion distraction type of injury (n = 12, 66%).The most commonly involved cervical spine injury level was C5-C6 (27%, n = 5), followed by 22% (n = 4) at C4-C5 and C6-C7 levels. About 27.8% (n = 5) of VAI was associated with foraminal fractures, and 72% (n = 13) of VAI was associated with facet dislocations, of which 44% (n = 8) were bifacetal and 28% (n = 5) were unifacetal dislocations. On clinical symptoms, only one (5.56%) patient had a headache, and 17 (94.4%) had no clinical features due to VAI. The incidence of traumatic vertebral artery disease is not very uncommon and requires careful and meticulous screening and management. Otherwise, complications like pseudoaneurysm, neurologic deficit, late-onset hemorrhage, infarction, and death can happen. Mostly, it is associated with high-velocity injuries and neurological injuries. MRI can be used as a good screening tool, which can be aided by a CT angiogram or digital subtraction angiographyfor confirmation. Proper pre-operative evaluation of vascular injury in cervical spine fracture dislocation is very important for patient counseling, patient management, and surgical planning.

How Games Help Us Research Age-Related Memory Changes

Working memory is the ability to hold information in our minds for a short time, often while we work on it. We need it for schoolwork, solving problems, and many aspects of life. Some people can hold more information in mind than others, and as we get older the amount we can hold tends to decline. If we understand what limits working memory and how working memory changes with age, we can figure out ways to improve it. A person’s ability to focus on relevant information and ignore distraction seems to be important. Our research group looked at how well people can ignore different types of distraction, which might limit their working memory. To sample a large number of people with a range of abilities, we used a game played by 29,631 people. The results gave us clues about how our ability to ignore distraction affects our working memory, and we identified a specific type of distraction that seems to particularly affect working memory in older adults.

Features of virtual reality impact effectiveness of VR pain alleviation therapeutics in pediatric burn patients: A randomized clinical trial.

Key features of virtual reality (VR) that impact the effectiveness of pain reduction remain unknown. We hypothesized that specific features of the VR experience significantly impact VR's effectiveness in reducing pain during pediatric burn dressing care. Our randomized controlled trial included children 6 to 17 years (inclusive) who were treated in the outpatient clinic of an American Burn Association-verified pediatric burn center. Participants were randomly assigned (1:1:1) to active VR (playing the VR), passive VR (immersed in the same VR environment without interactions), or standard-of-care. On a scale from 0 to 100, participants rated overall pain (primary outcome) and features of the VR experience (game realism, fun, and engagement). Path analysis assessed the interrelationships among these VR key features and their impact on self-reported pain scores. From December 2016 to January 2019, a total of 412 patients were screened for eligibility, and 90 were randomly assigned (31 in the active VR group, 30 in the passive VR group, and 29 in the standard-of-care group). The current study only included those in the VR groups. The difference in median scores of VR features was not statistically significant between the active (realism, 77.5 [IQR: 50-100]; fun, 100 [IQR: 81-100]; engagement, 90 [IQR: 70-100]) and passive (realism, 72 [IQR: 29-99]; fun, 93.5 [IQR: 68-100]; engagement, 95 [IQR: 50-100]) VR distraction types. VR engagement had a significant direct (-0.39) and total (-0.44) effect on self-reported pain score (p<0.05). Key VR features significantly impact its effectiveness in pain reduction. The path model suggested an analgesic mechanism beyond distraction. Differences in VR feature scores partly explain active VR's more significant analgesic effect than passive VR. Trial Registration: ClinicalTrials.gov Identifier: NCT04544631.

Validity across four common street-crossing distraction indicators to predict pedestrian safety

BackgroundMultiple distraction indicators have been applied to measure street-crossing distraction but their validities in predicting pedestrian safety are poorly understood.MethodsBased on a video-based observational study, we compared the validity of four commonly used distraction indicators (total duration of distraction while crossing a street, proportion of distracted time over total street-crossing time, duration of the longest distraction time, and total number of distractions) in predicting three pedestrian safety outcomes (near-crash incidence, frequency of looking left and right, and speed crossing the street) across three types of distraction (mobile phone use, talking to other pedestrians, eating/drinking/smoking). Change in Harrell’s C statistic was calculated to assess the validity of each distraction indicator based on multivariable regression models including only covariates and including both covariates and the distraction indicator.ResultsHeterogeneous capacities in predicting the three safety outcomes across the four distraction indicators were observed: 1) duration of the longest distraction time was most predictive for the occurrence of near-crashes and looks left and right among pedestrians with all three types of distraction combined and talking with other pedestrians (Harrell’s C statistic changes ranged from 0.0310 to 0.0335, P < 0.05), and for the occurrence of near-crashes for pedestrians involving mobile phone use (Harrell’s C statistic change: 0.0053); 2) total duration of distraction was most predictive for speed crossing the street among pedestrians with the combination and each of the three types of distraction (Harrell’s C statistic changes ranged from 0.0037 to 0.0111, P < 0.05), frequency of looking left and right among pedestrians distracted by mobile phone use (Harrell’s C statistic change: 0.0115), and the occurrence of near-crash among pedestrians eating, drinking, or smoking (Harrell’s C statistic change: 0.0119); and 3) the total number of distractions was the most predictive indicator of frequency of looking left and right among pedestrians eating, drinking, or smoking (Harrell’s C statistic change: 0.0013). Sensitivity analyses showed the results were robust to change in grouping criteria of the four distraction indicators.ConclusionsFuture research should consider the pedestrian safety outcomes and type of distractions to select the best distraction indicator.

Analysis of the Probability of Driving Distraction for Motorcycle Riders in Medan City

Driving distractionis an activity carried out while driving that causes a division of concentration which can increase the risk of an accident. This research was conducted to determine the probability of motorcyclists engaging in driving distraction according to predetermined conditions. The types of distraction studied were the distraction of using cellphones and talking to passengers. Questionnaires were distributed and direct observations were carried out to obtain the results of mapping driving distraction among motorcyclists in the city of Medan. The results of data analysis using the logit and Probit models show that when driving is distracted using a cellphone is significantly influenced by the variables Driving Time, Weather, Driving Speed, Road Conditions, and Route Type. Meanwhile, distraction from talking to passengers is significantly influenced by the variables weather, driving speed and traffic situation. The conditions that have the most potential for driving distraction to occur are: driving situation in the morning, sunny weather, low speed, road conditions without potholes, smooth traffic situation, 1 lane 2 lane 2 direction undivided type, and quiet road shoulder situation.

Psychophysiological Markers of Auditory Distraction: A Scoping Review

ABSTRACT Short-term memory can be disrupted by task-irrelevant sound. Auditory distraction has been globally studied under the lens of two main phenomena: the deviation effect and the changing-state effect. Yet, it remains unclear whether they rely on common cerebral mechanisms and, concomitantly, what psychophysiological responses they can trigger. This scoping review provides a state of knowledge regarding psychophysiological indices of auditory distraction. Records published between 2001 and 2021 on the deviation effect and the changing-state effect with psychophysiological measures were extracted from PubMed, ERIC, PsycNet, Web of Science, and ScienceDirect. Records investigating task-relevant sounds, as well as those that failed to observe performance disruption, or to include a control condition or a concurrent cognitive task, were excluded from the review. The Revised Cochrane risk-of-bias tool for randomized trials was used for bias evaluation. Fifteen records were reviewed, mainly characterized by randomization, measurement and selection of results biases. Some markers were specific to the distraction type, but nonspecific responses were also found. Overall, we outline the main markers used to index auditory distraction, present their meaning for understanding underpinning mechanisms, and discuss implications and knowledge gaps that need to be filled to fully exploit psychophysiology for auditory distraction research.

Distracted driving recognition based on functional connectivity analysis between physiological signals and perinasal perspiration index

Automatic detection of distracted driving is essential to ensure safety of drivers. In this paper, a novel set of features were extracted from thermal and physiological signals in order to detect and recognize distraction of drivers. Thermal video data which measured the temperature of different areas of the face, heart rate, breathing rate and behavioural signals were used while various types of distractions including cognitive, emotional and sensory-motor were applied to the subjects. The proposed discriminator features were extracted by different functional connectivity methods between the perinasal perspiration extracted from thermal images of the face and physiological variables of heart rate and breathing rate. After feature extraction, binary classification methods were applied to detect the distractions. The results showed that using functional connectivity features significantly increased the accuracy of distraction detection system (up to 99.16% with a highly acceptable F1 score of 0.99). Hence, the proposed model significantly improved (p-value<0.001) the detection of driver’s distraction compared to previous studies. Functional connectivity between perinasal perspiration and breathing signals was the most informative feature for distraction detection purpose. This feature set explained almost all modulations in physiological changes by distractions. For the first time, we designed a system capable of recognizing types of distractions including sensory-motor, cognitive, emotional distractions and also normal state. We used the same feature set to recognize different types of distractions by using three-class and four-class classifiers. The suggested methods distinguished three types of distractions with the best accuracy of 81.94% related to cognitive, sensory-motor distraction and no-distraction states. We also tried to discriminate two types of cognitive distractions, analytic and mathematical distractions. The recognition system classified two types of cognitive distractions with an accuracy of 91.78%. The results suggest that there is important and complementary information in the connectivity between facial temperature signals and physiological variables for distraction detection and recognition.

Did COVID-19 mandates influence driver distraction Behaviors? A case study in New Jersey

The global pandemic, Coronavirus (COVID), impacts almost everything, and human driving behavior is no exception. Since its breakdown in March 2020, transportation researchers have pondered on this matter to investigate the impact of COVID on drivers' travel behavior. Most of these studies are self-reported surveys, 'before and during' crash analyses, and short-duration observational studies. With a wider scope from an observational lens, we aim to investigate the impact of COVID-19 on drivers' distraction behaviors from an extensive observational database of distracted driving in New Jersey. A moving observational vehicle equipped with mounted cameras was utilized to collect the drivers' behavior across the high crash corridors and important highways in New Jersey. Samples collected during the COVID mandates and the post-COVID period were analyzed to assess the impact of COVID on drivers' distraction behavior at various temporal setups and roadway geometry. The results indicate a significant increase in cellphone use, eating, and fidgeting/grooming during the post-COVID period. However, behaviors like radio/reaching objects and talking to passengers decreased significantly after COVID. Utilizing the Mann-Whitney U test, this study conducted significance tests to identify the impacts of various temporal and geometric roadway features on each distraction type. Summer season, toll roads and roads with no signal had reduced distraction during the post-COVID compared to the COVID period. Both COVID and post-COVID period showed significant patterns of change of driver behavior within the temporal variables and road geometry. This research's findings would enable comprehension of human behavioral change for COVID mandates.

Effects of cognitive load on perceived internal and external distraction and their relationship with attentional control

ABSTRACT People are assumed to differ in their susceptibility to distraction, depending on their attentional control abilities. Accordingly, susceptibility to internal distraction (in terms of self-generated task-irrelevant thoughts) and to external distraction (in terms of task-irrelevant environmental stimuli) are considered two facets of a global attention-distractibility factor. While it is plausible that these two constructs overlap to some extent, susceptibility to internal and external distraction may nevertheless differ across situations. We thus investigated whether objective changes in external stimulation (manipulated by the presence versus absence of concurrent irrelevant speech) differentially affect perceived external and internal distraction during an ongoing task, and how both distraction types are related to attentional control. In Experiment 1, we used a working-memory task as ongoing task, in Experiment 2, we used a less demanding lexical-decision task. Results of both experiments consistently showed that perceived external distraction was increased whereas perceived internal distraction was decreased under irrelevant speech. Interestingly, attentional control was weakly positively related with perceived external distraction under irrelevant speech conditions. These results highlight that mutual dependencies between internal and external distraction experiences may be more complex than hitherto assumed.

A d factor? Understanding trait distractibility and its relationships with ADHD symptomatology and hyperfocus.

People differ substantially in their vulnerability to distraction. Yet, many types of distractions exist, from external stimulation to internal thoughts. How should we characterize individual differences in their distractibility? Two samples of adult participants (total N = 1220) completed a large battery of questionnaires assessing different facets of real-world distractibility. Latent modeling revealed that these measures could be explained by three correlated-yet-distinct factors: external distraction, unwanted intrusive thoughts, and mind-wandering. Importantly, about 80% of the total variance in these three factors could be explained by a single higher-order factor (d) that could be construed in terms of a person's general distractibility, and this general distractibility model was replicated across the two samples. We then applied the general distractibility model to understand the nature of ADHD symptomatology and hyperfocus (an intense state of long-lasting and highly focused attention). d was substantially associated with self-reported ADHD symptoms. Interestingly, d was also positively associated with hyperfocus, suggesting that hyperfocus may, to some degree, reflect attention problems. These results also show marked consistencies across the two samples. Overall, the study provides an important step toward a comprehensive understanding of individual differences in distractibility and related constructs.