Human Factors最新文献

{"title":"Investigating the Independent and Combined Effects of Startle and Surprise in a Simulated Flight Task.","authors":"Alexandre Duchevet, Jean-Paul Imbert, Jérémie Garcia, Benoît Lamirault, Mickaël Causse","doi":"10.1177/00187208251342100","DOIUrl":"https://doi.org/10.1177/00187208251342100","url":null,"abstract":"<p><p>ObjectiveWe aimed to characterize the impact of startle and surprise, both independently and in combination, on subjective feelings, behavior (task performance and gaze behavior), and several physiological parameters.BackgroundThe effects of startle and surprise are known to affect pilots' cognitive performance, with potential impact on safety. Startle and surprise can occur either together or independently, yet no studies have experimentally distinguished their specific effects.MethodParticipants (<i>n</i> = 45) were each assigned to one of the three conditions while performing the MATB-II task. In the startle condition, participants were subjected to an expected loud sound. In the surprise condition, an unexpected reverse video effect was applied to the experimental interface. In the combination condition, participants were exposed to both stimuli simultaneously.ResultsSurprise was associated with an increase in skin conductance without affecting performance. In contrast, startle was marked by a decline in performance on the communication sub-task, increased skin conductance and heart rate, and a narrowing of attention. When startle and surprise were combined, the results mirrored those of startle alone but included a stronger feeling of startle and surprise, and a more prolonged heart rate increase.ConclusionStartle and surprise combined yielded more numerous significant effects on subjective, behavioral, and physiological measures than startle and surprise independently.ApplicationIdentifying the specific impacts of startle and surprise could pave the way for their automatic detection using artificial intelligence. Safety could be enhanced through the design of specific countermeasures to help the crew cope with such states.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"187208251342100"},"PeriodicalIF":2.9,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Drowsy Driver Break Taking During Long Drives.","authors":"John G Gaspar, Brian Tefft, Cher Carney, William J Horrey","doi":"10.1177/00187208241293707","DOIUrl":"10.1177/00187208241293707","url":null,"abstract":"<p><p>ObjectiveThe current study investigated the factors that predict drowsy drivers' decisions regarding whether to take breaks versus continue driving during long simulator drives.BackgroundDriver drowsiness contributes to substantial numbers of motor vehicle crashes, injuries, and deaths. Previous research has shown that taking a nap and consuming caffeine can temporarily mitigate drowsiness and enable continued safe driving.MethodNinety drivers completed a 150-mile highway drive in a driving simulator after a day of partial sleep restriction. Drivers passed several simulated rest areas where they could take breaks. To replicate drivers' motivation to reach their destination safely but also quickly, drivers were told that they would be paid more for completing the simulated drive faster but would forfeit their payment if they crashed.ResultsBreak taking was predicted by drivers' self-ratings of drowsiness and by the severity of lane departures. However, even at the highest levels of drowsiness, most drivers bypassed simulated rest areas without stopping. In comparing self-rated drowsiness to drowsiness measured by eye closures, drivers often under- and over-estimate their own level of drowsiness.ConclusionDrowsy drivers use their own self-assessed drowsiness when deciding whether to take breaks. These self-assessments are often incorrect, and even when drivers rate themselves as severely drowsy they are unlikely to stop to rest during long drives.ApplicationThe findings reveal the need for effective drowsy driving countermeasures to motivate drivers to stop to take breaks. Results underscore the need to educate and/or motivate drivers to respond sooner to warning signs of drowsiness.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"503-517"},"PeriodicalIF":2.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142513878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Integrated Electroencephalography and Eye-Tracking Analysis Using eXtreme Gradient Boosting for Mental Workload Evaluation in Surgery.","authors":"Somayeh B Shafiei, Saeed Shadpour, James L Mohler","doi":"10.1177/00187208241285513","DOIUrl":"10.1177/00187208241285513","url":null,"abstract":"<p><p>ObjectiveWe aimed to develop advanced machine learning models using electroencephalogram (EEG) and eye-tracking data to predict the mental workload associated with engaging in various surgical tasks.BackgroundTraditional methods of evaluating mental workload often involve self-report scales, which are subject to individual biases. Due to the multidimensional nature of mental workload, there is a pressing need to identify factors that contribute to mental workload across different surgical tasks.MethodEEG and eye-tracking data from 26 participants performing Matchboard and Ring Walk tasks from the da Vinci simulator and the pattern cut and suturing tasks from the Fundamentals of Laparoscopic Surgery (FLS) program were used to develop an eXtreme Gradient Boosting (XGBoost) model for mental workload evaluation.ResultsThe developed XGBoost models demonstrated strong predictive performance with <i>R</i>² values of 0.82, 0.81, 0.82, and 0.83 for the Matchboard, Ring Walk, pattern cut, and suturing tasks, respectively. Key features for predicting mental workload included task average pupil diameter, complexity level, average functional connectivity strength at the temporal lobe, and the total trajectory length of the nondominant eye's pupil. Integrating features from both EEG and eye-tracking data significantly enhanced the performance of mental workload evaluation models, as evidenced by repeated-measures t-tests yielding <i>p</i>-values less than 0.05. However, this enhancement was not observed in the Pattern Cut task (repeated-measures t-tests; <i>p</i> > 0.05).ConclusionThe findings underscore the potential for machine learning and multidimensional feature integration to predict mental workload and thereby improve task design and surgical training.ApplicationThe advanced mental workload prediction models could serve as instrumental tools to enhance our understanding of surgeons' cognitive demands and significantly improve the effectiveness of surgical training programs.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"464-484"},"PeriodicalIF":2.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11936844/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Exploratory Study of Contextual Control Modes in Teamwork.","authors":"Connor Kannally, Abhinay Paladugu, Renske Nijveldt, Luke McSherry, Martijn IJtsma","doi":"10.1177/00187208241292669","DOIUrl":"10.1177/00187208241292669","url":null,"abstract":"<p><p>ObjectiveThis study investigated the relationship between human team member contextual control and team performance under time constraints.BackgroundContextual control modes, which describe different strategies for action selection in dynamic environments, characterize how humans maintain performance under variable demands. Control modes have not yet been studied in teamwork settings. Modeling of the cross-level interaction between team members' control modes and emerging team behaviors can improve understanding of effective teamwork in dynamic environments.MethodA human-subjects study explored the relationship between individual contextual control and team performance. Questionnaires about contextual control were used to elicit individual control modes. Analysis compared team members' control modes and investigated how control modes changed under varying time pressures.ResultsParticipant's control modes differed in their look ahead horizon, the extensiveness of prior action evaluation, and their prior experience. Many team members shifted control modes during trials, resulting in both convergence and divergence of paired control modes. No effects on communication rate were found due to changes in team members' control modes, but partially significant findings may suggest that the control mode divergence affects performance.ConclusionTeams can operate in multiple control mode configurations that change dynamically according to context. Further research with an increased sample size is warranted to analyze how time constraints influence team members' control modes and overall teaming processes and whether divergence of team control mode is favorable under time pressures.ApplicationFurther study of contextual control in teams may help improve team design to better support teams in coping with time constraints in dynamic environments.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"409-426"},"PeriodicalIF":2.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142513876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Takeover Request Time and Warning Modality on Trust in L3 Automated Driving.","authors":"Yu Wu, Xiaoyu Yao, Fenghui Deng, Xiaofang Yuan","doi":"10.1177/00187208241278433","DOIUrl":"10.1177/00187208241278433","url":null,"abstract":"<p><p>ObjectiveThis study investigated the effects of four takeover request (TOR) times and seven warning modalities on performance and trust in automated driving on a mildly congested urban road scenario, as well as the relationship between takeover performance and trust.BackgroundTakeover is crucial in L3 automated driving, where human-machine codriving is employed. Establishing trust in takeover scenarios among drivers can enhance the acceptance of autonomous vehicles, thereby promoting their widespread adoption.MethodUsing a driving simulator, data from 28 participants, including collision counts, takeover time (ToT), electrodermal activity (EDA) data, and self-reported trust scores, were collected and analyzed primarily using Generalized Linear Mixed Models (GLMM).ResultsCollisions during the takeover undermined participants' trust in the autonomous driving system. As TOR time increased, participants' trust improved, and the longer TOR time did not lead to participant confusion. There was no significant relationship between warning modality and trust. Furthermore, the combination of three warning modalities did not exhibit a notable advantage over the combination of two modalities.ConclusionThe study examined the effects of TOR time and warning modality on trust, as well as preliminarily explored the potential association between takeover performance, including collisions and ToT, and trust in autonomous driving takeovers.ApplicationResearchers and designers of automotive interactions were given referenceable TOR time and warning modality by this study, which extended the autonomous driving takeover scenarios. These findings contributed to boosting drivers' confidence in transferring control to the automated system.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"427-444"},"PeriodicalIF":2.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142115510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Impact of the Physical Environment on Robotic-Assisted Surgery Outcomes and Processes: A Scoping Review.","authors":"Sara Kennedy, Patrick Fuller, Jackie S Cha, Alfredo M Carbonell, Qi Luo, Anjali Joseph","doi":"10.1177/00187208251333907","DOIUrl":"https://doi.org/10.1177/00187208251333907","url":null,"abstract":"<p><p>ObjectiveThe purpose of this scoping review is to identify physical environmental facilitators and barriers related to performing robotic-assisted surgery (RAS) in operating rooms (ORs).BackgroundAs new robotic surgery technology is developed and brought to market, there is a need to understand how existing and future operating rooms are adapted and designed to support patient safety, surgical workflow, and teamwork. This review will focus on literature related to physical environment factors that impact workflow and communication, as well as the adoption of RAS technology.MethodThe scoping review search was conducted during November 2022, following the PRISMA guidelines. An independent reviewer screened articles for inclusion and exclusion and two independent reviewers completed a quality appraisal was on the included articles.ResultsOf the 9325 texts screened, 28 articles were included for analysis. The primary physical environment and outcome variables were extracted and synthesized under the following categories: RAS process or task-related, environmental features, environmental qualities, and staff or patient outcomes.ConclusionThe physical environment of the OR, such as OR layout, OR size, environmental noise, and dedicated robotic ORs played a significant role in efficiency and workflow outcomes for RAS, as well as workload measures, staff and patient safety, and surgical performance.ApplicationSince there are minimal evidence-based resources available for the application of RAS, this review provides distinct connections between RAS outcomes and specific environmental features for considerations among design researchers, architects, human factors professionals, hospital administrators, and practitioners to aid in decision making during and after implementation of RAS technology.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"187208251333907"},"PeriodicalIF":2.9,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144057731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Exploratory Study on Auditory Experience in Electric Vehicles: Understanding User Characteristics and Driving Contexts Through Real-Driving Experiments.","authors":"Yein Song, Dain Kim, Jane Lee, Myung Hwan Yun","doi":"10.1177/00187208251335149","DOIUrl":"https://doi.org/10.1177/00187208251335149","url":null,"abstract":"<p><p>ObjectiveThis study investigated how user characteristics and driving context influence auditory experiences (AX) in electric vehicles (EVs), identifying distinct user types and their specific auditory needs and evaluation.BackgroundElectric vehicles (EVs) present unique opportunities for designing auditory experiences (AX) due to their quiet operation characteristics and acoustic vehicle alert systems (AVAS).MethodForty participants conducted real-driving experiments with an EV, experiencing sounds at low, medium, and high speeds. We applied systematic analysis combining topic modeling (BERTopic) and qualitative coding of think-aloud interviews and statistical analysis of questionnaire responses.ResultsFour user types were segmented by attitude (Dynamic vs. Conservative) and car type (EV vs. ICV owners). Text analysis revealed varying frequencies of concerns across user types regarding driving contexts, functional aspects, and affective aspects of AX. Statistical analysis showed significant differences among user types in sporty preferences and perceptions of affective properties (Sporty, Stylish, Comfort, and Calm). Driving contexts significantly influenced perceived Stylish and Calm characteristics.ConclusionThis study provides empirical evidence and design implications for customized AX in EVs design based on user characteristics and driving contexts.ApplicationThe findings can guide the development of personalized AX systems in EVs, enhancing both user satisfaction and safety through context-aware and user-centered design approaches.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"187208251335149"},"PeriodicalIF":2.9,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144053643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of Lower Degree Automation Reliability on Higher Degree Automation Failure Detection in Simulated Air Traffic Control.","authors":"Vanessa K Bowden, Isabella Gegoff, Philippe J Kilpatrick, Shayne Loft","doi":"10.1177/00187208251335536","DOIUrl":"https://doi.org/10.1177/00187208251335536","url":null,"abstract":"<p><p>ObjectiveTo determine how lower degree of automation (DOA) reliability impacts human response to a single higher-DOA failure in simulated air traffic control conflict detection.BackgroundHigher-DOA systems apply higher levels of automation to later stages of human information processing. Higher-DOA typically results in better routine performance, and lower-DOA with better automation failure response. If both are provided and lower-DOA is reliable, it could support higher DOA failure detection.MethodParticipants (<i>N</i> = 192) received a combination of lower-DOA and/or higher-DOA. Lower-DOA highlighted aircraft conflicts and near-misses, leaving participants to manually resolve conflicts. Higher-DOA resolved conflicts. Automation failed once. Participants were provided one of four types of automation: lower-DOA, where lower-DOA failed (L_F); higher-DOA, where higher-DOA failed (H_F); both lower- and higher-DOA, where only higher-DOA failed (LH_F); or both lower- and higher-DOA, where both failed (L_FH_F).ResultsWhen only the higher-DOA component of combined lower- and higher-DOA failed (LH_F), participants detected the automation failure 23.6s faster and more accurately (miss rate = -.08) compared to higher-DOA only (H_F). However, more participants missed the automation failure when lower-DOA failed (L_F = +.42; L_FH_F = +.15), compared to the H_F condition.ConclusionsReliable lower-DOA can support higher DOA failure detection when both are presented. However, poorer automation failure detection with lower-DOA failure suggests participants over-relied on aircraft highlighting to direct attention to potential conflicts.ApplicationsProviding both lower- and higher-DOA together could be beneficial when higher-DOA fails but lower-DOA remains reliable, but conversely, detrimental if lower-DOA also fails.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"187208251335536"},"PeriodicalIF":2.9,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144041959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Whole-Body Vibrations on Electrovibration Perception Varies with Target Stimulus Duration.","authors":"Jan D A Vuik, Daan M Pool, Celal Umut Kenanoglu, Yasemin Vardar","doi":"10.1177/00187208251326662","DOIUrl":"https://doi.org/10.1177/00187208251326662","url":null,"abstract":"<p><p>ObjectiveThis study investigates the impact of whole-body vibrations caused by external vehicle perturbations, such as aircraft turbulence, on the perception of electrovibration displayed on touchscreens.BackgroundElectrovibration is a promising technology for providing tactile feedback on future touchscreens, potentially addressing usability challenges in vehicle cockpits. However, its performance under dynamic conditions, such as whole-body vibrations caused by turbulence, remains largely unexplored.MethodWe measured the absolute detection thresholds of 24 human participants for short (0.2 s) and long (0.5 s) duration electrovibration stimuli displayed on a touchscreen. These measurements were taken in the absence and presence of two types of turbulence motion (Gaussian and Multisine) generated by a motion simulator. Concurrently, we recorded participants' applied contact force and finger displacements.ResultsElectrovibration stimuli displayed on vehicle cockpit touchscreens were more reliably perceived with a 0.5-s duration than a 0.2-s duration, both in the presence and absence of turbulence. Both turbulence types led to increased vibration-induced finger displacements and scan speeds in the direction of turbulence, as well as higher applied forces and force fluctuation rates. Gaussian turbulence significantly elevated perception thresholds, but only for short-duration electrovibration stimuli.ConclusionThe findings indicate that whole-body vibrations impair the perception of short-duration electrovibration stimuli, primarily due to unintentional finger movements and increased fluctuations in applied normal force.ApplicationOur findings offer valuable insights for the future design of touchscreens with tactile feedback in vehicle cockpits.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"187208251326662"},"PeriodicalIF":2.9,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144053943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Cognitive Engagement on Physical Performance and Perceived Workload During Isometric Exertions of Index Finger.","authors":"Sidharajsinh Jadeja, Pranav Madhav Kuber, Ehsan Rashedi","doi":"10.1177/00187208251332777","DOIUrl":"10.1177/00187208251332777","url":null,"abstract":"<p><p>ObjectiveThe influence of varying cognitive loading was examined at a moderate level of 25% maximum voluntary contractions (MVC) in a static task.BackgroundRepetitive low-intensity tasks can lead to fatigue, eventually reducing task performance. This study explores the benefits of providing additional cognitive loading during breaks and while performing intermittent tasks on fatigue progression.MethodsIntermittent isometric abductions of the index finger were performed by six male and female subjects for four experimental conditions including passive rest and added cognitive load in the form of an arithmetic task. Both subjective and objective measures of discomfort, muscle activity, physical and mental task performance, muscle capacity, and task demands were compared across genders and conditions.ResultActive breaks with cognitive engagement reduced fatigue compared to passive rest in terms of muscle activity, capacity, and physical demand. Moreover, moderate cognitive demand in concurrence with physical task showed most favorable results as subjects showed lowest perceived fatigue (1.66/10), physical demand (30/100), and muscle activity (0.184 volts) as well as highest muscle capacity retention (92.4%). Further addition of concurrent cognitive demand at a high level showed similar perceived fatigue (1.67/10) and physical demand (32/100) but demonstrated higher muscle activity (0.239 volts) and lower muscle capacity retention (89.9%).ApplicationsFindings demonstrate importance of tailoring cognitive demands based on gender and occupational settings, with moderate mental tasks during breaks offering the most favorable results overall, enhancing recovery and reducing muscle activity without compromising task performance.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"187208251332777"},"PeriodicalIF":2.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144050364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}