Human Factors最新文献

ObjectiveThis study evaluated the effectiveness of age simulation gloves in replicating age-related declines in hand function.BackgroundCommercially available age simulation gloves are increasingly used. However, their ability to replicate age-related physical decline remains largely unverified.MethodTwenty healthy adults (mean age: 26.8 years) completed assessments under three conditions: with no glove, using a Cambridge Simulation Glove (CG), and using the CG combined with tremor simulation (TS). Grip and pinch strength (Biometrics electronic dynamometer and pinch meter), gross (Box and Block Test) and fine (Grooved Pegboard Test) motor dexterity, hand function (Southampton Hand Assessment Procedure), postural tremor (MetaMotionC accelerometers), tactile sensitivity (Semmes-Weinstein Monofilaments), and usability (System Usability Scale) were evaluated. Performance with glove conditions was compared against normative data of older adults if available.ResultsGrip strength and gross and fine motor dexterity declined in both glove conditions, aligning with normative ageing values. However, pinch strength and functional performance did not show consistent replication of normative ageing. Usability scores were below acceptable thresholds for both gloves. While the addition of tremor simulation increased peak frequency consistent with ageing, it did not replicate the rise in amplitude.ConclusionOverall, the gloves partially replicated age-related hand function decline. Improvements in pinch force, tremor fidelity, and ergonomic design are needed to enhance realism and usability in educational, clinical, and design contexts.ApplicationFindings can guide in selecting or improving age simulation tools to better support age inclusive product development and assessment.

ObjectiveWe evaluated the sensitivity and calibration of users when estimating the reliability of an automated decision support system as exposure to the system and the saliency of errors varied.BackgroundAlthough users are typically sensitive when estimating the reliability of an automated system, it is not known how exposure to a system or error saliency influences the estimate. Viewpoints of the "leaky integrator" and "intuitive statistician" suggest competing outcomes regarding estimates over time.MethodsParticipants identified matching images of MegaBlocks with assistance from an automated system. Participants experienced three levels of reliability and three levels of exposure (number of trials). They provided estimates of reliability, trust, and confidence in their estimates for each system. In Experiment 2, the saliency of false alarms and misses was manipulated. In Experiment 3, the saliency of these error types was matched.ResultsReliability estimates were sensitive to true reliability but were lower with more salient errors. Exposure had no impact on the estimates of reliability or trust. Trust and confidence in the estimate of reliability increased with true reliability.ConclusionsEstimates of reliability are generally sensitive to the true reliability of a system, although they can be hindered by memory limitations and/or saliency effects. Estimates of reliability are made very quickly and do not tend to change with exposure.ApplicationsTraining users on a new system may not require extensive exposure, but early interactions with a system should accurately represent the amount and types of errors that the system will make.

ObjectiveTo examine whether adding well designed visual patterns to labels can increase efficiency of searching for labelled items.BackgroundErrors of substitution can occur when selecting among similarly appearing items, especially under adverse conditions and time pressure.MethodTwo consecutive studies investigated effects of adding visual patterns to simulated labels in a visual search task. Both studies attempted to objectively design distinctive patterns, based on normative constraints. Study 1 compared response times and accuracy for target items comprising Text+Patterns, Text-Only, or Pattern-Only, involving searching for target items (based on working memory recollection) within an array of distractors. Study 2 additionally addressed memorability and spatial frequency content of patterns.ResultsStudy 1 indicated longer response times for simulated labels without patterns. No significant effects were found due to spatial frequency of patterns, nor to Pattern-Only versus Text+Patterns. Study 2 also showed longer response times and more errors for non-patterned labels. Weaker evidence was found to support improved performance for lower effective spatial bandwidth content of patterns.ConclusionsEvidence was found for decreased response times, and possibly fewer errors, when searching for target labels containing redundant information using potentially familiar visual patterns. The need exists for objective tools for normatively designing such patterns, potentially based on spatial frequency content.ApplicationsIn addition to label reading in general, medication labels may particularly benefit from adding patterned labels, to assist paramedics, pharmacists, nurses, anaesthesiologists, as well as lay consumers.

ObjectiveThis systematic review evaluates the use of cognitive load measurement methods in usability testing across diverse software interfaces. It provides guidance for researchers and practitioners by proposing a framework for selecting appropriate cognitive load measurement techniques.BackgroundCognitive Load Theory offers insights into software usability by addressing users' mental effort during task performance. Although cognitive load measurement methods are increasingly used in usability testing, no comprehensive analysis has focused specifically on various software interfaces.MethodWe systematically analysed 87 experimental studies published between 2001 and 2025. Databases searched included IEEE, ACM, ScienceDirect, SpringerLink, and Scopus. Inclusion criteria focused on studies applying cognitive load measurement to usability testing for different types of software interfaces.ResultsCognitive load measurement methods were categorised as subjective (e.g., NASA-TLX and self-reports) or objective (e.g., EEG, eye-tracking, dual-task paradigms, and physiological sensors). The most frequently used methods were performance measures (19%), NASA-TLX (12%), and eye fixations (11%). Commonly evaluated platforms included websites, virtual reality systems, and productivity tools. Each method's applicability, strengths, and limitations were identified.ConclusionThe review synthesises the relative merits of cognitive load measurement methods in usability evaluations and introduces a framework to guide the selection of techniques based on interface type and evaluation goals.ApplicationThe proposed framework operationalises CLT to support targeted, user-centred usability testing. It facilitates the selection of effective cognitive load measurement strategies, enhancing evaluation accuracy and informing better software design.

ObjectiveTo assess the efficiency of rough auditory alarms in capturing attention during a piloting-like task under high mental workload that may induce inattentional deafness.BackgroundUnder high mental workload and stress, pilots may experience inattentional deafness, leading them to miss critical auditory warnings. This results from early inhibition of the primary auditory cortex by prefrontal areas, shifting auditory processing oscillations from gamma to alpha frequencies. Recent studies suggest that roughness-an auditory perceptual feature of natural alarm signals generated by amplitude-modulated sounds in the 30-150 Hz range-could attract attention at early perceptual stages. Auditory roughness could sustain alarm detection under cognitive load.MethodTwenty-seven participants underwent a demanding dual-task protocol. They simultaneously performed the Multi-Attribute Task Battery and an auditory oddball task including rough and non-rough targets. Participants also provided subjective ratings of the target sounds and of their perceived workload during the task.ResultsRough targets were detected more efficiently with higher hit rates and no cost to false alarm rate, reaction time, or primary task performance. Accordingly, participants rated rough alarms as more urgent, unpleasant, and salient. Overall workload was unchanged, but frustration and mental demand were lower and performance higher in the rough condition.ConclusionThis study provides promising evidence that rough auditory alarms enhance detection and help prevent inattentional deafness without degrading primary-task performance. Consistent with an effective alarm profile, roughness increased salience and perceived urgency.ApplicationIntegrating rough auditory warnings into cockpits could enhance alarm detection in cognitively demanding situations, improving safety.

ObjectiveExplore the under-investigated display attribute of head-mounted display (HMD) opacity and its relationship with display clutter and environment clutter in real-world nautical navigation tasks.BackgroundEffect of overlay clutter is a prominent factor of HMD research, but there are many factors to displaying information, and the role of opacity has seen little empirical investigation.MethodThirty participants performed a realistic nautical navigation task in a virtual environment with obstacles, navigating a small speedboat that rendered navigational information that replicated an HMD interface. The display interface was manipulated by the amount of information present (clutter) and the level of opacity. Environmental obstacles were varied in their number. Participants were evaluated on completion time of the tasks, proximity to obstacles, and mental demand.ResultsParticipants performed the task faster when there were more islands, especially in transparent displays. Hazard proximity increased when the environment had more islands and while navigating highly cluttered displays. Increased proximity to hazards occurred only when the display was opaque and highly cluttered. Mental demand followed the same pattern as completion time.ConclusionThe study revealed preliminary findings that high-cluttered environments should be navigated with more transparent displays and less display clutter.ApplicationThe data from the study highlights the relationship between display opacity, display clutter, and environmental clutter. This provides a foundation upon which more work can ask more complex questions about these relationships and how they can impact navigational efficiency.

ObjectiveThis study investigated whether individual differences in multi-tasking ability (MTa) modulate the benefit and cost of supervising imperfect automation on performance, workload, situation awareness, stress, and trust in simulated air traffic control (ATC).BackgroundAutomation is rarely perfectly reliable, and automation failures can have significant detrimental effects. Prior work established that MTa can modulate the benefit of perfectly reliable automation. However, it is unknown whether MTa influences the cost of supervising imperfect automation.MethodsMTa was indexed using a latent factor from three cognitive tasks completed by 113 undergraduate students. Participants completed two ATC blocks: one without automation (manual) and one with automated assistance for accepting incoming aircraft, handing-off outgoing aircraft, and conflict detection (violations of minimum separation). Conflict detection automation was perfectly reliable. Automation highlighting aircraft needing acceptance and hand-off was imperfect, missing 30% of events (the "unreliable" trials).ResultsLower-MTa participants obtained greater performance benefits to aircraft hand-off from reliable-automation but suffered greater costs from unreliable automation compared to manual hand-off, relative to higher-MTa participants. Situation awareness was improved by automation provision, and workload reduced, although MTa did not vary these effects. Stress reduction with automation, compared to manual, was greater for lower-MTa compared to higher-MTa participants. Higher-MTa participants calibrated trust across the different reliability of ATC tasks more effectively.ConclusionMTa can lead to differentiated effects of imperfect automation on aircraft hand-off, perceived stress and trust.ApplicationMTa may warrant consideration in personnel hiring and role selection for work contexts where automation reliability is volatile.

ObjectiveTo develop and validate a computational framework that infers individualized attention strategies and latent distraction states to support personalized modeling of multitasking behavior and intervention.BackgroundDriver distraction from in-vehicle systems is a growing safety concern. However, the level of distraction is often latent and varies significantly across individuals. Existing models typically overlook these differences, limiting their effective use for personalized interventions.MethodWe introduce a Partially Observable Semi-Markov Decision Process (POSMDP) to model hidden attentional dynamics and attention allocation decisions. Using behavioral data, including glance behavior, velocity, and pupillometry, from a high-fidelity driving simulator with 18 participants, we estimate personalized reward functions that reflect each driver's subjective valuation of secondary task utility versus safety cost.ResultsThe method accurately infers distraction states and recovers participant-specific utility weights governing the trade-off between secondary task benefit and driving cost. Compared to a well-established 2-s glance rule, it improves detection of distraction events and reveals individual variability in attention strategies. Some drivers exhibit highly conservative profiles, while others assign greater value to secondary tasks, even under high distraction. Counterfactual simulations show how perceived task importance could modulate visual attention behavior across individuals.ConclusionOur POSMDP-based framework provides an interpretable and individualized account of driver attention allocation, capturing both latent states and behavioral variability.ApplicationThis model enables the development of personalized, risk-sensitive driver assistance systems that adapt to individual attention strategies, enhancing road safety through context-aware, graded interventions.

ObjectiveThe objective of this study is to empirically test a computational model of interruptions processes and effects, and to compare an alternative model to determine which best explains interruption and response decision making.BackgroundInterruptions in safety-critical environments (e.g., hospitals) can lead to an increased risk of error for the person being interrupted (the interruptee) but may be necessary for the person doing the interrupting (the interrupter) to maintain safety. Little research has considered the perspective of both the interrupter and interruptee.MethodWe tested a computational model of interruption and response decision processes through an experiment where participants (n = 312) worked as a nurse in a simulated clinical team. We examined how task progress, time remaining, and time pressure influenced decisions and compared the model with an alternative that allowed the effects of time pressure to be non-monotonic.ResultsUsing Bayesian hierarchical modeling, we found that a non-monotonic model best explained interruption decisions. Participants were biased toward interrupting, with time pressure only influencing decisions when it was very high. Contrastingly, the monotonic model best explained response decisions. Participants were more likely to accept interruptions as the interrupter's time pressure increased in comparison to their own.ConclusionTime pressure has a non-monotonic influence on interruption decisions, but a monotonic influence on response decisions.ApplicationFindings can inform interventions to consider the interruptions process from the perspective of both the interrupter and interruptee. Interventions could focus on training workers to more accurately assess time pressure when making interruption decisions.

ObjectiveThis research investigated effects for new traffic markings on the user behaviour of motorcycle riders.BackgroundAcross motorised vehicles, motorcycles represent the most vulnerable road users.MethodA road sign and traffic markings were installed at six trial sites. Data from video cameras at each site provided measures of rider behaviour in relation to speed, road position, brake use, and use of the traffic markings, before and after installations. Throughout this research 4652 motorcycle riders travelled through the sites. Of these 1542 riders were analysed in more detail to investigate the effects of the road safety intervention on rider behaviour.ResultsAt five sites speed was reduced by a significant margin. At four sites there were significant improvements in road position at the final traffic marking. At five of the trial sites on the apex of a bend, there were significant improvements in road position. Braking behaviour decreased at two of the trial sites. For use of the traffic markings a significant increase was observed across all the trial sites. Across the behaviour measures, the changes were still present 4 weeks later. At a comparison site no changes in behaviour were observed.ConclusionThe findings provide evidence of improved rider behaviour which are placed in reference to the Safe System principles for road safety and casualty reduction.ApplicationThis research has generated international interest for installing the road sign and traffic markings in other regions and contributes to the Scottish Government's Road Safety Framework to 2030 by reducing motorcycle casualties.