High Mental Workload Research Articles

Revealing driver psychophysiological response to emergency braking in distracted driving based on field experiments

Purpose The purpose of this paper is to characterize distracted driving by quantifying the response time and response intensity to an emergency stop using the driver’s physiological states. Design/methodology/approach Field tests with 17 participants were conducted in the connected and automated vehicle test field. All participants were required to prioritize their primary driving tasks while a secondary nondriving task was asked to be executed. Demographic data, vehicle trajectory data and various physiological data were recorded through a biosignalsplux signal data acquisition toolkit, such as electrocardiograph for heart rate, electromyography for muscle strength, electrodermal activity for skin conductance and force-sensing resistor for braking pressure. Findings This study quantified the psychophysiological responses of the driver who returns to the primary driving task from the secondary nondriving task when an emergency occurs. The results provided a prototype analysis of the time required for making a decision in the context of advanced driver assistance systems or for rebuilding the situational awareness in future automated vehicles when a driver’s take-over maneuver is needed. Originality/value The hypothesis is that the secondary task will result in a higher mental workload and a prolonged reaction time. Therefore, the driver states in distracted driving are significantly different than in regular driving, the physiological signal improves measuring the brake response time and distraction levels and brake intensity can be expressed as functions of driver demographics. To the best of the authors’ knowledge, this is the first study using psychophysiological measures to quantify a driver’s response to an emergency stop during distracted driving.

GAMBARAN BEBAN KERJA MENTAL DENGAN PRODUKTIVITAS KERJA PADA DRIVER OJEK ONLINE DI KOTA MEDAN

Online motorcycle taxis are one of the public transportations that are currently being used more and more because they are considered effective, besides that online motorcycle taxi drivers must always be ready under any circumstances and conditions to deliver and serve consumers so that it can cause work stress both physically and psychologically (mentally). A high workload will affect the performance and productivity of online motorcycle taxis, many factors cause the high mental workload experienced by online motorcycle taxis. The purpose of this study is to describe the mental workload of online motorcycle taxi drivers in Medan City. This research is a type of descriptive research using a qualitative approach in the form of a interviews. The sample was taken, namely some online motorcycle taxi drivers in the city of Medan. The results of the study show an overview of the workload and work productivity of online motorcycle taxi drivers in Medan City which is relatively low with increasing employee productivity. It was concluded that the description of Workload with Work Productivity on Gojek Online Drivers in Medan City is relatively low so that it supports increasing work productivity for online Gojek drivers because of the motivation from the family for drivers to continue to be enthusiastic at work.c

Mental Workload Analysis Using NASA-TLX Method on Customer Service Employees in Strategist Informa Social Media Division (PT Home Center Kawan Lama)

Kawan Lama Group has been established since 1955 and until now has several business fields engaged in the Retail, Industrial, Food and Beverage, Service, Property and E-commerce sectors. For more than half a century, Kawan Lama continues to grow and develop to employ more than 40,000 employees. Kawan Lama Group's vision is more than just a family business, we are a business for families. Our mission is to bring values to a better life through business development and sustainable growth. PT. Home Center Kawan Lama or Informa is a furniture company starting from home furniture, office furniture, to commercial space furniture. Informa provides more than 35,000 quality items that can meet the needs of customers to have their dream furniture. The NASA-TLX method was developed by Sandra. G Hart from NASA-Ames Research Center and Lowell E. Staveland from San Jose State University in 1981. This method performs multidimensional measurements by considering weights and grades. The level of the first factor relates to the work performed, while the other three factors relate to the subject. The average WWL (weighted workload) mental workload of customer service employees prior to the proposed work shift improvement, application of music therapy and motivation is the morning shift of 76.78, the afternoon shift of 77.97 and the night shift of 80. Average Results WWL (weighted workload) mental workload of employees in the morning, afternoon and evening shifts shows a high mental workload. The morning, afternoon and evening shifts have significant differences in physical needs, mental needs, time requirements, performance, stress levels and average WWL (weighted workload).

Subjective and objective assessments of mental workload for UAV operations.

Unmanned Aerial Vehicles (UAVs) have created safety problems for the publics. Assessments of the mental workload for UAV operations are essential to realize the causes of UAV accidents. To test the following hypotheses: i. mission difficulty in UAV operation affects both subjective and objective measures of mental workload; ii. mission difficulty affects number of failures in UAV operation. Fourteen male adults participated as UAV operators after attending a UAV training course. They performed four flight missions of different difficulty levels. During their flight missions, their heart rate and inter-beat interval (IBI) were collected. Upon completing each flight mission, the participants gave subjective ratings of mental workload using three commonly adopted assessment tools. The time of flight and number of failures in flight operations were also recorded. The results showed that mission difficulty affected the scores of all three assessment tools significantly. Mission difficulty also affected number of failures and IBI significantly. The scores of the three assessment tools were highly correlated (ρ= 0.7 to 0.83, p < 0.001) with one another. The results of the three subjective ratings were also consistent with that of the IBI data. High mental workload in UAV operation could lead to poor flight performance.

Noise exposure and mental workload: Evaluating the role of multiple noise exposure metrics among surface miners in the US Midwest

This study examined associations between metrics of noise exposure and mental workload. In this cross-sectional study, five occupational noise metrics computed from full-shift dosimetry were evaluated among surface mine workers in the US Midwest. Mental workload was evaluated using a modified, raw NASA-TLX and clustered with a k-means clustering algorithm. Mixed effects logistic regression and Bayesian Kernel Machine Regression (BKMR) was utilized for analysis. Average noise exposure, the difference between peak and mean noise exposure, and the number of peaks >135 dB were each strongly associated with mental workload, while the kurtosis and standard deviation of noise throughout a shift were not. An exposure-response relationship between average noise exposure and mental workload may exist, with elevated risk of high mental workload beginning at 80 dBA. These results suggest that high noise exposure may be an independent risk factor of high mental workload, and impulse events and the difference between the peak and mean noise exposure may have interactive effects with average noise exposure.

Mental Workload, Occupational Fatigue and Musculoskeletal Disorders of Forestry Professionals

Musculoskeletal disorders (MSD) comprise one of the most important occupational health issues in forestry professions. The purpose of the study was to examine the association among musculoskeletal disorders, antrhopometric and personal data, mental workload and occupational fatigue in forest professionals in northern Iran by means of the Nordic Musculoskeletal Questionnaire (NMQ), the National Aeronautics and Space Administration Task Load Index (NASA-TLX), and the Swedish Occupational Fatigue Inventory (SOFI). More than eight out of every ten subjects reported at least one MSD symptom during the past 12 months, with lower back (72.5%), feet and ankles (49%) and neck (41.2%) being the more frequently affected body regions. Similar MSD prevalences were reported for the period of seven days prior to data collection. Both the mental workload (grand mean 73.18±7.54) and occupational fatigue (grand mean 106.20±24.53) achieved high scores. MSD prevalence was found to be correlated with the SOFI score and the NASA-TLX score during the last year and seven days prior to data collection, respectively.Overall, the study results confirm the very demanding nature of the forest professions, which are characterized by high MSD prevalence, increased occupational fatigue and high mental workload. Given the small-scale forestry characteristics in the study area, taking measures such as introducing vocational training and promoting the use of personal protective equipment are some first necessary steps for the local forestry workforce.

Mental Workload Evaluation for PMM Outbound Student in X University (Unix) Using NASA-TLX Method

Program Mahasiswa Merdeka (PMM) is one of the MBKM program. This program allows student to study in different university and majors. It was attended by students of Engineering Faculty from UNIX in State and Private University throughout Indonesia. By participating PMM, the student have overload credits because they have to finish double credit from homebased and destination university. This condition affects the burden on students both physically and mentally. This mental burden of students has an impact on student achievement academically, so the mental burden analysis is needed. In this study, an evaluation of the mental workload was carried out using the NASA-TLX approach. The result found that in general 75% of students experienced a very high workload. The percentage of students who take PMM in State University as much as 50% is in the category of high mental workload and 50% is very high category. The percentage of students who take PMM in Private University is 25% in the very high category and 75% is in the high category. From this study, UNIX can have some consideration about providing the brief (tips and tricks) before PMM for student mental preparation and choosing the Private University for destination university.

Investigating mental workload-induced changes in cortical oxygenation and frontal theta activity during simulated flights

Monitoring pilots’ cognitive states becomes increasingly important in aviation. Physiological measurement can detect increased mental workload (MWL) even before performance declines. Yet, changes in MWL are rarely varied systematically and few studies control for confounding effects of other cognitive states. The present study targets these shortcomings by analysing the effects of stepwise increased MWL on cortical activation, while controlling for mental fatigue (MF). 35 participants conducted a simulated flight with an incorporated adapted n-back and monitoring task. We recorded cortical activation with concurrent EEG and fNIRS measurement, performance, self-reported MWL and MF. Our results show the successful manipulation of MWL without confounding effects of MF. Higher task difficulty elicited higher subjective MWL ratings, performance decline, higher frontal theta activity and reduced frontal deoxyhaemoglobin (Hbr) concentration. Using both EEG and fNIRS, we could discriminate all induced MWL levels. fNIRS was more sensitive to tasks with low difficulty, and EEG to tasks with high difficulty. Our findings further suggest a plateau effect for high MWL that could present an upper boundary to individual cognitive capacity. Our results highlight the benefits of physiological measurement in aviation, both for assessment of cognitive states and as a data source for adaptive assistance systems.

The effect of mental schema evolution on mental workload measurement: an EEG study with simulated quadrotor UAV operation

Objective. Mental workload is the result of the interactions between the demands of an operation task, the environment in which the task is performed, and the skills, behavior and perception of the performer. Working under a high mental workload can significantly affect an operator’s ability to choose optimal decisions, judgments and motor actions while operating an unmanned aerial vehicle (UAV). However, the effect of mental schema, which reflects the level of expertise of an operator, on mental workload remains unclear. Here, we propose a theoretical framework for describing how the evolution of mental schema affects mental workload from the perspective of cognitive processing. Approach. We recruited 51 students to participate in a 10-day simulated quadrotor UAV flight training exercise. The EEG power spectral density (PSD)-based metrics were used to investigate the changes in neural responses caused by variations in the mental workload at different stages of mental schema evolution. Main results. It was found that the mental schema evolution influenced the direction and change trends of the frontal theta PSD, parietal alpha PSD, and central beta PSD, which are EEG indicators of mental workload. Initially, before the mental schema was formed, only the frontal theta PSD increased with increasing task difficulty; when the mental schema was initially being developed, the frontal theta PSD and the parietal alpha PSD decreased with increasing task difficulty, while the central beta PSD increased with increasing task difficulty. Finally, as the mental schema gradually matured, the trend of the three indicators did not change with increasing task difficulty. However, differences in the frontal PSD became more pronounced across task difficulty levels, while differences in the parietal PSD narrowed. Significance. Our results describe the relationship between the EEG PSD and the mental workload of UAV operators as the mental schema evolved. This suggests that EEG activity can be used to identify the mental schema and mental workload experienced by operators while performing a task, which can not only provide more accurate measurements of mental workload but also provide insights into the development of an operator’s skill level.

Why do nursing students leave bachelor program? Findings from a qualitative descriptive study

BackgroundOver the past few years, the phenomenon of “nursing student attrition” has been unevenly studied. Investigators often focused on independent predictors as age, family obligations, final grade of high school, demanding physical and mental workload and others. Specifically, just a few studies applied qualitative methods to better comprehend the very needs of first year students enrolled in a bachelor’s degree in nursing sciences (BSN), to sustain their learning process and define effective strategies to reduce student drop-out.MethodsWe conducted a qualitative descriptive study. Thirty-one nursing students at Verona University were interviewed using a semi-structured guide. Data analysis was performed according to a descriptive approach by Sandelowski & Barroso (2000).ResultsA total number of 31 students were interviewed. The most recurrent themes regarding the reasons behind BSN drop-out were: understanding that they were not suited to be nurses, perception of missing/lack of psychological, physical and practical resources needed to successfully cope with both nursing school and the nursing profession, inconsistencies between the image of the profession and the reality of the job, feelings of disappointment for the experiences of internship, perceived lack of support from the clinical teacher while going through difficult experiences.ConclusionsWe can consider a part of these drop-out decisions normal, even physiological when students come to realise that they are not suited for the nursing profession. However, it’s important to guide nursing students with adequate counselling in order to give them the essential tools to cope with the training and the future as health professionals.

Evaluating mental workload during multitasking in simulated flight.

BackgroundPilots must process multiple streams of information simultaneously. Mental workload is one of the main issues in man–machine interactive mode when dealing with multiple tasks. This study aimed to combine functional near‐infrared spectroscopy (fNIRS) and electrocardiogram (ECG) to detect changes in mental workload during multitasking in a simulated flight.MethodsTwenty‐six participants performed three multitasking tasks at different mental workload levels. These mental workload levels were set by varying the number of subtasks. fNIRS and ECG signals were recorded during tasks. Participants filled in the national aeronautics and space administration task load index (NASA‐TLX) scale after each task. The effects of mental workload on scores of NASA‐TLX, performance of tasks, heart rate (HR), heart rate variability (HRV), and the prefrontal cortex (PFC) activation were analyzed.ResultsCompared to multitasking in lower mental workload conditions, participants exhibited higher scores of NASA‐TLX, HR, and PFC activation when multitasking in high mental workload conditions. Their performance was worse during the high mental workload multitasking condition, as evidenced by the higher average tracking distance, smaller number of response times, and longer response time of the meter. The standard deviation of the RR intervals (SDNN) was negatively correlated with subjective mental workload in the low task load condition and PFC activation was positively correlated with HR and subjective mental workload in the medium task load condition.ConclusionHR and PFC activation can be used to detect changes in mental workload during simulated flight multitasking tasks.

Pengaruh Mental Work Load dan Gejala Post-Traumatic Stress Disorder (PTSD) Terhadap Kinerja Petugas Rescue di PT Freeport Indonesia

The purpose of this study is to analyze the relationship between mental workload and Post-Traumatic Stress Disorder (PTSD) symptoms to the performance of PTFI rescue officers. The analysis includes descriptive analysis, bivariate analysis using Chi Square test, and Structural Equation Model (SEM) analysis using Partial Least Squares (PLS) program. The calculation of the data shows that PTFI rescue officers have a high overall mental workload perception, the prevalence of PTSD symptoms is 10.48%, and the overall average performance is appraised as meet expectations. The results of the SEM-PLS analysis shows that mental workload has a significant effect on performance (p-values 0.045 sig.5%) and PTSD symptoms have no effect on performance (p-values 0.885 sig.5%) but has a significant effect on mental workload (p-values 0.026 sig.5%). The Chi Square test shows a significant correlation between the predictor of assignment location with PTSD symptoms (p-values 0.019 sig.5%) and performance (p-values 0.032 sig.5%). The managerial implications then proposed to obtain healthy mental and optimal productivity of PTFI rescue officers, including handling PTSD symptoms, facilitating coping strategies, analyzing the influence of competence to mental workload, implement structured program to deal with traumatic events exposure, measuring the stress level, and measuring behavioral elements that support employees' perceptions as citizen of the organization. Keywords: mental workload, performance, PTSD symptoms, rescue officer

Analysis of Student Mentality with Rating Scale Mental Effort on Online Lecturing

Online lectures are distance learning carried out by all students and teachers who are in separate locations and involve multiple platforms in the implementation of online lectures. The problems experienced by students related to online lectures such as difficulties in using technology, and understanding the material so that it triggers a high mental workload from each student. This study aims to analyze the mental workload of industrial engineering students at Telkom University, Bandung. This study uses the Rating Scale Mental Effort (RSME) method to determine the mental workload related to the use of technology in online lectures. In the results of measuring mental workload, using a questionnaire distributed to students with 48 respondents. Based on the results obtained, the indicator that received the highest average RSME value reached 83.75, on the work anxiety indicator. Therefore, it is necessary to improve online learning and further research.

EEG Based Dynamic Functional Connectivity Analysis in Mental Workload Tasks With Different Types of Information.

The accurate evaluation of operators' mental workload in human-machine systems plays an important role in ensuring the correct execution of tasks and the safety of operators. However, the performance of cross-task mental workload evaluation based on physiological metrics remains unsatisfactory. To explore the changes in dynamic functional connectivity properties with varying mental workload in different tasks, four mental workload tasks with different types of information were designed and a newly proposed dynamic brain network analysis method based on EEG microstate was applied in this paper. Six microstate topographies labeled as Microstate A-F were obtained to describe the task-state EEG dynamics, which was highly consistent with previous studies. Dynamic brain network analysis revealed that 15 nodes and 68 pairs of connectivity from the Frontal-Parietal region were sensitive to mental workload in all four tasks, indicating that these nodal metrics had potential to effectively evaluate mental workload in the cross-task scenario. The characteristic path length of Microstate D brain network in both Theta and Alpha bands decreased whereas the global efficiency increased significantly when the mental workload became higher, suggesting that the cognitive control network of brain tended to have higher function integration property under high mental workload state. Furthermore, by using a SVM classifier, an averaged classification accuracy of 95.8% for within-task and 80.3% for cross-task mental workload discrimination were achieved. Results implies that it is feasible to evaluate the cross-task mental workload using the dynamic functional connectivity metrics under specific microstate, which provided a new insight for understanding the neural mechanism of mental workload with different types of information.

Mental State Detection Using Riemannian Geometry on Electroencephalogram Brain Signals.

The goal of this study was to implement a Riemannian geometry (RG)-based algorithm to detect high mental workload (MWL) and mental fatigue (MF) using task-induced electroencephalogram (EEG) signals. In order to elicit high MWL and MF, the participants performed a cognitively demanding task in the form of the letter n-back task. We analyzed the time-varying characteristics of the EEG band power (BP) features in the theta and alpha frequency band at different task conditions and cortical areas by employing a RG-based framework. MWL and MF were considered as too high, when the Riemannian distances of the task-run EEG reached or surpassed the threshold of the baseline EEG. The results of this study showed a BP increase in the theta and alpha frequency bands with increasing experiment duration, indicating elevated MWL and MF that impedes/hinders the task performance of the participants. High MWL and MF was detected in 8 out of 20 participants. The Riemannian distances also showed a steady increase toward the threshold with increasing experiment duration, with the most detections occurring toward the end of the experiment. To support our findings, subjective ratings (questionnaires concerning fatigue and workload levels) and behavioral measures (performance accuracies and response times) were also considered.

Facing successfully high mental workload and stressors: An fMRI study.

The present fMRI study aimed at highlighting patterns of brain activations and autonomic activity when confronted with high mental workload and the threat of auditory stressors. Twenty participants performed a complex cognitive task in either safe or aversive conditions. Our results showed that increased mental workload induced recruitment of the lateral frontoparietal executive control network (ECN), along with disengagement of medial prefrontal and posterior cingulate regions of the default mode network (DMN). Mental workload also elicited an increase in heart rate and pupil diameter. Task performance did not decrease under the threat of stressors, most likely due to efficient inhibition of auditory regions, as reflected by a large decrement of activity in the superior temporal gyri. The threat of stressors was also accompanied with deactivations of limbic regions of the salience network (SN), possibly reflecting emotional regulation mechanisms through control from dorsal medial prefrontal and parietal regions, as indicated by functional connectivity analyses. Meanwhile, the threat of stressors induced enhanced ECN activity, likely for improved attentional and cognitive processes toward the task, as suggested by increased lateral prefrontal and parietal activations. These fMRI results suggest that measuring the balance between ECN, SN, and DMN recruitment could be used for objective mental state assessment. In this sense, an extra recruitment of task‐related regions and a high ratio of lateral versus medial prefrontal activity may represent a relevant marker of increased but efficient mental effort, while the opposite may indicate a disengagement from the task due to mental overload and/or stressors.

Analisis Beban Kerja pada Operator Bagian Produksi dengan Menggunakan Metode NASA-TLX (Task Load Index) di PT. Ujong Neubok Dalam

Operator workload in a company can be grouped into low or high workloads. Operators feel the workload is low if each activity is carried out easily and safely so that it does not exceed the operator's capabilities. Meanwhile, a heavy workload is felt when the work exceeds the operator's ability limit which can cause fatigue and work accidents. PT Ujong Neubok Dalam is a company that produces Crude Palm Oil (CPO) and kernels. In the production section, there are workstations such as loading rump, sterilization, digester and press, clarification, and others. The production target is 270 tons/day of Fresh Fruit Bunches (FFB) which are produced into CPO. The demand for production targets resulted in complaints and discomfort felt by the production department operator. The purpose of this study was to analyze the workload and workload indicators of production operators using the NASA-TLX method. From the calculation results of 17 operators, the mental workload that is classified as high is felt by 7 operators with an average Weighted Workload (WWL) of 81-89, while 10 operators are classified as high mental workloads with a WWL value of 78-67. Of the 6 NASA-TLX indicators, 3 indicators have the highest mental workload values, namely physical needs (KF), effort (U), and work performance (PK) with details of the average value of 248 - 260.

The Continuous Matching Task (CMT) – real-time procedural stimulus generation for adaptive testing of attention

The Continuous Matching Task (CMT) is a novel paradigm designed to measure sustained attention and alertness. It is a special type of Continuous Performance Task (CPT) that utilizes truly continuous stimulus material. Stimuli are generated in real-time by a procedural algorithm which also enables adaptive testing. The task is highly flexible and can be used in either single or dual-task configurations that also allow for task mixing. The functionality of the algorithm and applications are presented. The viability of the CMT is tested and results are compared with similar tasks, i.e. Stroop-Task and Conner’s CPT (CCPT), as well as self-reports of ADHD in adults in a Multi-Trait-Multi-Method approach in a sample of N = 122 participants. Self-reports and measurements of heart rate variability during testing are analyzed to infer and compare mental workload during tasks. Overall, variants of the CMT induce a higher mental workload than the other tasks, and employing the dual-task CMT with adaptive difficulty resulted in the highest reliability and validity. Results indicate that the CMT is primarily a measure of alertness and processing speed and benefits from adaptive testing.

Mental Workload Estimation Based on Physiological Features for Pilot-UAV Teaming Applications.

Manned-Unmanned Teaming (MUM-T) can be defined as the teaming of aerial robots (artificial agents) along with a human pilot (natural agent), in which the human agent is not an authoritative controller but rather a cooperative team player. To our knowledge, no study has yet evaluated the impact of MUM-T scenarios on operators' mental workload (MW) using a neuroergonomic approach (i.e., using physiological measures), nor provided a MW estimation through classification applied on those measures. Moreover, the impact of the non-stationarity of the physiological signal is seldom taken into account in classification pipelines, particularly regarding the validation design. Therefore this study was designed with two goals: (i) to characterize and estimate MW in a MUM-T setting based on physiological signals; (ii) to assess the impact of the validation procedure on classification accuracy. In this context, a search and rescue (S&R) scenario was developed in which 14 participants played the role of a pilot cooperating with three UAVs (Unmanned Aerial Vehicles). Missions were designed to induce high and low MW levels, which were evaluated using self-reported, behavioral and physiological measures (i.e., cerebral, cardiac, and oculomotor features). Supervised classification pipelines based on various combinations of these physiological features were benchmarked, and two validation procedures were compared (i.e., a traditional one that does not take time into account vs. an ecological one that does). The main results are: (i) a significant impact of MW on all measures, (ii) a higher intra-subject classification accuracy (75%) reached using ECG features alone or in combination with EEG and ET ones with the Adaboost, Linear Discriminant Analysis or the Support Vector Machine classifiers. However this was only true with the traditional validation. There was a significant drop in classification accuracy using the ecological one. Interestingly, inter-subject classification with ecological validation (59.8%) surpassed both intra-subject with ecological and inter-subject with traditional validation. These results highlight the need for further developments to perform MW monitoring in such operational contexts.

Mobile Phone Use during Gait: The Role of Perceived Prioritization and Executive Control.

(1) Background: Mobile phone use during gait is associated with adverse health outcomes, namely increased risk of pedestrian injury. Healthy individuals can voluntarily prioritize concurrent task performance, but the factors underlying the impact of phone use during walking remain largely unknown. Thus, the objective of this work was to evaluate the relationship between subjective (perceived) prioritization, cognitive flexibility and dual-task performance when using a mobile phone during walking. (2) Methods: Thirty young participants walked for one minute with and without reading or texting on a mobile phone, as well as reading or texting while sitting. Walking performance (kinematics) was recorded, as well as phone use (text comprehension, text read/written), mental workload, perceived prioritization (visual analog scale), and cognitive flexibility (trail-making test). (3) Results: Texting while walking was associated with larger decreases in gait speed, larger gait variability, higher mental workload, and lower text comprehension compared to reading. Perceived prioritization was associated with walking dual-task costs (DTCs) (r = 0.39–0.42, p < 0.04) when texting, and better cognitive flexibility was associated with lower gait DTCs when texting (r = 0.55, p = 0.002) but not reading. (4) Conclusions: The context-dependent link between perceived prioritization, cognitive flexibility, and walking DTCs promotes our understanding of the factors underlying texting-while-walking performance. This could identify individuals who are more prone to dual-task interference in this increasingly common and dangerous task.