Effect of laparoscopic handle size on surgical performance: A randomized crossover trial.

Laparoscopic instrument handles design and dimensions are crucial to determine the configuration of surgeons' hand grip and, therefore, can have a deleterious effect on overall surgical efficiency and surgeons' comfort. The aim of this study is to investigate the impact of laparoscopic handle size and hand surface area on surgical task performance. A single-blind, randomized crossover trial was carried out with 29 novice medical students. Participants performed three simulated tasks in "black box" simulators using two scissor-type handles of different sizes. Surgical performance was assessed by the number of errors and time required to complete each task. Hand anthropometric data were measured using a 3D scanner. Execution time was significantly higher when cutting and suturing tasks were performed with the smaller handle. In addition, hand surface area was positively correlated with peg transfer task time when performed with the standard handle and was correlated with cutting task time in small and standard handle groups. We also found positive correlations between execution time and the number of errors executed by larger-handed participants. Our findings indicate that laparoscopic handle size and hand area influence surgical performance, highlighting the importance of considering hand anthropometry variances in surgical instrument design.

Multitasking across the lifespan in different task contexts.

We assessed lifespan development of multitasking in a sample of 187 individuals aged 8-82 years. Participants performed a visuo-spatial working memory (VSWM) task together with either postural control or reaction time (RT) tasks. Using criterion-referenced testing we individually adjusted difficulty levels for the VSWM task to control for single-task differences. Age-differences in single-task performances followed U-shaped patterns with young adults outperforming children and older adults. Multitasking manipulations yielded robust performance decrements in VSWM, postural control and RT tasks. Presumably due to our adjustment of VSWM challenges, costs in this task were small and similar across age groups suggesting that age-differential costs found in earlier studies largely reflected differences already present during single-task performance. Age-differences in multitasking costs for concurrent tasks depended on specific combinations. For VSWM and RT task combinations increases in RT were the smallest for children but pronounced in adults highlighting the role of cognitive control processes. Stabilogram diffusion analysis of postural control demonstrated that long-term control mechanisms were affected by concurrent VSWM demands. This interference was pronounced in older adults supporting concepts of compensation or increased cognitive involvement in sensorimotor processes at older age. Our study demonstrates how a lifespan approach can delineate the explanatory scope of models of human multitasking.

The Impact of Dual-Tasks and Disease Severity on Posture, Gait, and Functional Mobility among People Living with Dementia in Residential Care Facilities: A Pilot Study.

Gait speed and timed-up-and-go (TUG) predict cognitive decline, falls, and mortality. Dual-tasks may be useful in cognitive screening among people living with dementia (PWD), but more evidence is needed. This cross-sectional study aimed to compare single- and dual-task performance and determine the influence of dementia severity on dual-task performance and interference. Thirty PWD in two residential care facilities (Age: 81.3 ± 7.1 years; Montreal Cognitive Assessment: 10.4 ± 6.0 points) completed two trials of single- (feet apart) and dual-task posture (feet apart while counting backward), single- (walk 4 m) and dual-task gait (walk 4m while naming words), and single- (timed-up-and-go (TUG)), and dual-task functional mobility (TUG while completing a category task) with APDM inertial sensors. Dual-tasks resulted in greater sway frequency, jerk, and sway area; slower gait speed; greater double limb support; shorter stride length; reduced mid-swing elevation; longer TUG duration; reduced turn angle; and slower turn velocity than single-tasks (ps < 0.05). Dual-task performance was impacted (reduced double limb support, greater mid-swing elevation), and dual-task interference (greater jerk, faster gait speed) was related to moderate-to-severe compared to mild PWD. Moderate-to-severe PWD had poorer dynamic stability and a reduced ability to appropriately select a cautious gait during dual-tasks than those with mild PWD, indicating the usefulness of dual-tasks for cognitive screening.

Optimizing Human-Robot Teaming Performance through Q-Learning-Based Task Load Adjustment and Physiological Data Analysis.

The transition to Industry 4.0 and 5.0 underscores the need for integrating humans into manufacturing processes, shifting the focus towards customization and personalization rather than traditional mass production. However, human performance during task execution may vary. To ensure high human-robot teaming (HRT) performance, it is crucial to predict performance without negatively affecting task execution. Therefore, to predict performance indirectly, significant factors affecting human performance, such as engagement and task load (i.e., amount of cognitive, physical, and/or sensory resources required to perform a particular task), must be considered. Hence, we propose a framework to predict and maximize the HRT performance. For the prediction of task performance during the development phase, our methodology employs features extracted from physiological data as inputs. The labels for these predictions-categorized as accurate performance or inaccurate performance due to high/low task load-are meticulously crafted using a combination of the NASA TLX questionnaire, records of human performance in quality control tasks, and the application of Q-Learning to derive task-specific weights for the task load indices. This structured approach enables the deployment of our model to exclusively rely on physiological data for predicting performance, thereby achieving an accuracy rate of 95.45% in forecasting HRT performance. To maintain optimized HRT performance, this study further introduces a method of dynamically adjusting the robot's speed in the case of low performance. This strategic adjustment is designed to effectively balance the task load, thereby enhancing the efficiency of human-robot collaboration.

Automation function and malfunction: effects on human performance in accident handling tasks.

By conducting a mixed-design experiment using simplified accident handling tasks performed by two-person teams, this study examined the effects of automation function and condition (before, during, and after malfunction) on human performance. Five different and non-overlapping functions related to human information processing model were considered and their malfunctions were set in a first-failure way. The results showed that while the automation malfunction impaired task performance, the performance degradation for information analysis was more severe than response planning. Contrary to other functions, the situation awareness for response planning and response implementation tended to increase during malfunctioning and decrease after. In addition, decreased task performance reduced trust in automation, and malfunctions in earlier stages of information processing resulted in lower trust. Suggestions provided for the design and training related to automation emphasise the importance of high-level cognitive support and the benefit of involving automation error handling in training.

The effects of automation function and malfunction on human performance are important for design and training. The experimental results in this study revealed the significance of high-level cognitive support. Also, introducing automation error handling in training can be helpful in improving situation awareness of the teams.

Effects of noise exposure on stress hormone changes during task performance in young Korean men: quasi-experimental study.

Numerous studies have suggested that noise exposure might be associated with changes in stress hormone levels. However, quantitative evidence for these effects in humans is rare and remains controversial. This study aimed to investigate the acute effects of exposure to noise and its different levels on stress hormone changes in task performance. Quasi-experimental noise exposure environment was established for 90 male university student volunteers in their twenties, and each was exposed to different noise levels during task performance. The stress hormones tested included cortisol, adrenocorticotropic hormone (ACTH), adrenaline, and noradrenaline. A one-way ANOVA was performed to investigate differences in hormone levels measured in the three groups according to the noise exposure levels (35, 45, or 75 dB). Analysis of covariance (ANCOVA) was used to adjust for confounding factors that might affect hormone levels. After adjusting for confounders, significant exposure-dependent differences were found in hormone levels in salivary cortisol, serum cortisol, serum ACTH, and serum adrenaline. The amount of hormonal increase in 75 dB exposure group compared to 35 or 45 dB groups was detected. Similar results were also seen in the rate of change analysis. Our findings indicate that short-term noise exposure during task performance elevates stress hormone levels. Further, the extent of stress hormone alterations varies with noise exposure levels. Changes in hormone levels are an objective measure that may be used to identify health effects and stress responses in various noise environments.

Wagers for work: Decomposing the costs of cognitive effort.

Some aspects of cognition are more taxing than others. Accordingly, many people will avoid cognitively demanding tasks in favor of simpler alternatives. Which components of these tasks are costly, and how much, remains unknown. Here, we use a novel task design in which subjects request wages for completing cognitive tasks and a computational modeling procedure that decomposes their wages into the costs driving them. Using working memory as a test case, our approach revealed that gating new information into memory and protecting against interference are costly. Critically, other factors, like memory load, appeared less costly. Other key factors which may drive effort costs, such as error avoidance, had minimal influence on wage requests. Our approach is sensitive to individual differences, and could be used in psychiatric populations to understand the true underlying nature of apparent cognitive deficits.

Task demand mediates the interaction of spatial and temporal attention.

Psychophysical studies typically test attentional mechanisms in isolation, but in everyday life they interact to optimize human behavior. We investigated whether spatial and temporal attention interact in two orientation discrimination experiments that vary in task demand. We manipulated temporal and spatial attention separately and conjointly with well-established methods for testing each spatial or temporal attention. We assessed sensitivity (d') and reaction time for every combination of spatial and timing cues, each of which was valid, neutral, or invalid. Spatial attention modulated sensitivity (d') and speed (reaction time) across temporal attention conditions. Temporal attention modulated sensitivity and speed under high- but not low- task demands. Furthermore, spatial and temporal attention interacted for the high-demand task. This study reveals that task demand matters; in a simple task spatial attention suffices to improve performance, whereas in a more demanding task both spatial and temporal attention interact to boost performance, albeit in a subadditive fashion.

Impacts of decision support systems on cognition and performance for intelligence-gathering path planning.

Decision Support Systems (DSS) are tools designed to help operators make effective choices in workplace environments where discernment and critical thinking are required for effective performance. Path planning in military operations and general logistics both require individuals to make complex and time-sensitive decisions. However, these decisions can be complex and involve the synthesis of numerous tradeoffs for various paths with dynamically changing conditions. Intelligence collection can vary in difficulty, specifically in terms of the disparity between locations of interest and timing restrictions for when and how information can be collected. Furthermore, plans may need to be changed adaptively mid-operation, as new collection requirements appear, increasing task difficulty. We tested participants in a path planning decision-making exercise with scenarios of varying difficulty in a series of two experiments. In the first experiment, each map displayed two paths simultaneously, relating to two possible routes for the two available trucks. Participants selected the optimal path plan, representing the best solution across multiple routes. In the second experiment, each map displayed a single path, and participants selected the best two paths sequentially. In the first experiment, utilizing the DSS was predictive of adoption of more heuristic decision strategies, and that strategic approach yielded more optimal route selection. In the second experiment, there was a direct effect of the DSS on increased decision performance and a decrease in perceived task workload.

Explainability does not mitigate the negative impact of incorrect AI advice in a personnel selection task.

Despite the rise of decision support systems enabled by artificial intelligence (AI) in personnel selection, their impact on decision-making processes is largely unknown. Consequently, we conducted five experiments (N = 1403 students and Human Resource Management (HRM) employees) investigating how people interact with AI-generated advice in a personnel selection task. In all pre-registered experiments, we presented correct and incorrect advice. In Experiments 1a and 1b, we manipulated the source of the advice (human vs. AI). In Experiments 2a, 2b, and 2c, we further manipulated the type of explainability of AI advice (2a and 2b: heatmaps and 2c: charts). We hypothesized that accurate and explainable advice improves decision-making. The independent variables were regressed on task performance, perceived advice quality and confidence ratings. The results consistently showed that incorrect advice negatively impacted performance, as people failed to dismiss it (i.e., overreliance). Additionally, we found that the effects of source and explainability of advice on the dependent variables were limited. The lack of reduction in participants' overreliance on inaccurate advice when the systems' predictions were made more explainable highlights the complexity of human-AI interaction and the need for regulation and quality standards in HRM.

Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units.

Weaning patients from ventilation in intensive care units (ICU) is a complex task. There is a growing desire to build decision-support tools to help clinicians during this process, especially those employing Artificial Intelligence (AI). However, tools built for this purpose should fit within and ideally improve the current work environment, to ensure they can successfully integrate into clinical practice. To do so, it is important to identify areas where decision-support tools may aid clinicians, and associated design requirements for such tools. This study analysed the work context surrounding the weaning process from mechanical ventilation in ICU environments, via cognitive task and work domain analyses. In doing so, both what cognitive processes clinicians perform during weaning, and the constraints and affordances of the work environment itself, were described. This study found a number of weaning process tasks where decision-support tools may prove beneficial, and from these a set of contextual design requirements were created. This work benefits researchers interested in creating human-centred decision-support tools for mechanical ventilation that are sensitive to the wider work system.

AI and the transformation of industrial work: Hybrid intelligence vs double-black box effect.

It is uncertain how the application of artificial intelligence (AI) technology transforms industrial work. We address this question from the perspective of cognitive systems, which, in this case, includes considerations of AI and process transparency, resilience, division of labor, and worker skills. We draw from a case study on glass tempering that includes a machine-vision-based quality control system and an advanced automation process control system. Based on task analysis and background literature, we develop the concept of hybrid intelligence that implies balanced AI transparency that supports upskilling and resilience. So-called fragmented intelligence, in turn, may result from the combination of the complexity of advanced automation along with the complexity of the process physics that places critical emphasis on expert knowledge. This combination can result in the so-called "double black box effect", given that designing for understandability for the line workers might not be feasible: expert networks are needed for resilience.

Investigating the impact of greenery elements in office environments on cognitive performance, visual attention and distraction: An eye-tracking pilot-study in virtual reality.

The human-nature connection is one of the main aspects determining supportive and comfortable office environments. In this context, the application of eye-tracking-equipped Virtual Reality (VR) devices to support an evaluation on the effect of greenery elements indoors on individuals' efficiency and engagement is limited. A new approach to investigate visual attention, distraction, cognitive load and performance in this field is carried out via a pilot-study comparing three virtual office layouts (Indoor Green, Outdoor Green and Non-Biophilic). 63 participants completed cognitive tasks and surveys while measuring gaze behaviour. Sense of presence, immersivity and cybersickness results supported the ecological validity of VR. Visual attention was positively influenced by the proximity of users to the greenery element, while visual distraction from tasks was negatively influenced by the dimension of the greenery. In the presence of greenery elements, lower cognitive loads and more efficient information searching, resulting in improved performance, were also highlighted.

Impact of repetitive mouse clicking on forearm muscle fatigue and mouse aiming performance.

Exercise induced performance fatigue has been shown to impair many aspects of fine motor function in the distal upper limb. However, most fatiguing protocols do not reflect the conditions experienced with computer use. The purpose of this study was to determine how a prolonged, low-force mouse clicking fatigue protocol impacts performance fatigue of the distal upper limb for gamers and non-gamers. Participants completed a total of 1 h of mouse clicking at 5 clicks per second. Muscle fatigue and performance were intermittently assessed. RMS amplitude increased for the forearm flexors throughout the fatigue protocol. Accuracy decreased following the first bout of clicking and returned to baseline values after 40-min. EDC and ECU displayed the greatest muscle activity while aiming, producing 11.4% and 12.9% of MVC, respectively. These findings indicate that mouse clicking may not result in performance fatigue, however, high levels of extensor activity may explain common injuries among gamers.

Equivalent weight: Application of the assessment method on real task conducted by railway workers wearing a back support exoskeleton.

Commonly used risk indexes, such as the NIOSH Lifting Index, do not capture the effect of exoskeletons. This makes it difficult for Health and Safety professionals to rigorously assess the benefit of such devices. The community requires a simple method to assess the effectiveness of back-support exoskeleton's (BSE) in possibly reducing ergonomic risk. The method introduced in this work is termed "Equivalent Weight" (EqW) and it proposes an interpretation of the effect built on the benefit delivered through reduced activation of the erector spinae (ES). This manifests itself as an apparent reduction of the lifted load perceived by the wearer. This work presents a pilot study where a practical application of the EqW method is used to assess the ergonomic risk in manual material handling (MMH) when using a back support exoskeleton (StreamEXO). The results are assessed by combining observational measurements from on-site testing with five different workers and quantitative measures of the muscle activity reduction achieved during laboratory evaluation with ten workers. These results will show that when lifting, lowering, and carrying a 19 kg load the StreamEXO can reduce risk by up to two levels (from "high" to "low") in the target sub-tasks. The Lifting index (LI) was reduced up to 64% when examining specific sub-tasks and the worker's movement conduction.

Analysis of driver behavior at grade-separated intersections to support design.

Understanding driver behaviors in varied traffic scenarios is critical to the design of safe and efficient roadways and traffic control device. This research presents an analysis of driver cognitive workload, situation awareness (SA) and performance for three different scenarios, including a standard intersection and contraflow grade-separated intersections (C-GSI) and quadrant GSI (Q-GSI) with lane assignment sign manipulations. The study used a simulator-based driving experiment with application of the NASA Task Load Index and Situation Awareness Global Assessment Technique to assess the influence of the scenarios on driver behavioral responses. The findings reveal challenges for drivers navigating the C-GSI, characterized by diminished SA and elevated workload. These states were associated with behaviors such as delayed lane changes, missed opportunities for appropriate lane changes, heightened acceleration behavior within deceleration segments, and frequent speeding. In contrast, while drivers in the Q-GSI scenario faced elevated workloads, their SA remained steady, largely due to lane-specific signs facilitating early lane changes. Although the Q-GSI led to increased speed variability and slight increases in deceleration, the use of supplementary speed signage revealed a promising alternative to the S-intersection. Correlation analysis highlighted a significant relationship between mental workload and acceleration responses, indicating that increased acceleration was associated with higher mental workload. In addition, a significant negative correlation between driver perceived performance and absolute lane deviations indicated that drivers with higher self-assessed performance were more accurate in lane-keeping. The study underscores the need for GSIs and signage designs that support driver SA, manage cognitive workload to improve driver performance and increase road safety.

Operator selection for human-automation teaming: The role of manual task skill in predicting automation failure intervention.

Humans working in modern work systems are increasingly required to supervise task automation. We examined whether manual aircraft conflict detection skill predicted participants' ability to respond to conflict detection automation failures in simulated air traffic control. In a conflict discrimination task (to assess manual skill), participants determined whether pairs of aircraft were in conflict or not by judging their relative-arrival time at common intersection points. Then in a simulated air traffic control task, participants supervised automation which either partially or fully detected and resolved conflicts on their behalf. Automation supervision required participants to detect when automation may have failed and effectively intervene. When automation failed, participants who had better manual conflict detection skill were faster and more accurate to intervene. However, a substantial proportion of variance in failure intervention was not explained by manual conflict detection skill, potentially reflecting that future research should consider other cognitive skills underlying automation supervision.

An exploratory study of the practical impact of the COVID-19 pandemic on nursing tasks in clinical settings.

AIMS: To identify and compare new or increased nursing tasks in South Korea during the pandemic, categorized by hospital type and department. BACKGROUND: Although COVID-19 is no longer considered a global public health emergency, the threat of novel infectious diseases remains. Reflecting on the COVID-19 pandemic is essential to prepare effectively for future outbreaks. METHODS: This cross-sectional exploratory study, following the STROBE checklist, included 948 registered nurses with more than a year of clinical experience currently working in various hospitals. Questionnaires gathered demographic data, work characteristics, and the frequency of nursing task performance. Statistical analysis encompassed descriptive and inferential methods. RESULTS: The most common new or increased nursing task across all hospital types was 'Access control for family caregivers.' General wards prioritized tasks related to family caregivers, while specialized units like ICU and ER focused on infection control. CONCLUSION: Understanding how COVID-19 has impacted nursing tasks is crucial for gaining insights into efficient resource allocation, targeted education, and policy formulation during similar public health crises. The pandemic has given rise to new family caregiver-related tasks in the nursing profession. Consequently, continuous nursing research is essential for establishing guidelines and fostering a supportive work environment, which is crucial for the successful implementation of these tasks.

Effects of executive load on crashes and near-crashes for young versus older drivers.

With the increasing use of infotainment systems in vehicles, secondary tasks requiring executive demand may increase crash risk, especially for young drivers. Naturalistic driving data were examined to determine if secondary tasks with increasing executive demand would result in increasing crash risk. Data were extracted from the Second Strategic Highway Research Program Naturalistic Driving Study, where vehicles were instrumented to record driving behavior and crash/near-crash data. executive and visual-manual tasks paired with a second executive task (also referred to as dual executive tasks) were compared to the executive and visual-manual tasks performed alone. Crash/near-crash odds ratios were computed by comparing each task condition to driving without the presence of any secondary task. Dual executive tasks resulted in greater odds ratios than those for single executive tasks. The dual visual-manual task odds ratios did not increase from single task odds ratios. These effects were only found in young drivers. The study shows that dual executive secondary task load increases crash/near-crash risk in dual task situations for young drivers. Future research should be conducted to minimize task load associated with vehicle infotainment systems that use such technologies as voice commands.

Effectiveness of stress arousal reappraisal and stress-is-enhancing mindset interventions on task performance outcomes: a meta-analysis of randomized controlled trials.

Stress arousal reappraisal (SAR) and stress-is-enhancing (SIE) mindset interventions aim to promote a more adaptive stress response by educating individuals about the functionality of stress. As part of this framework, an adaptive stress response is coupled with improved performance on stressful tasks. The goal of this meta-analysis is to evaluate the effectiveness of these interventions on task performance. The literature search yielded 44 effect sizes, and a random-effects model with Knapp-Hartung adjustment was used to pool them. The results revealed an overall small significant improvement in task performance (d = 0.23, p < 0.001). The effect size was significantly larger for mixed interventions (i.e., SAR/SIE mindset instructions combined with additional content, k = 5, d = 0.45, p = 0.004) than SAR-only interventions (k = 33, d = 0.22, p < 0.001) and SIE mindset-only interventions (k = 6, d = 0.18, p = 0.22) and tended to be larger for public performance tasks than cognitive written tasks (k = 14, d = 0.34, p < 0.001 vs. k = 30, d = 0.20, p = 0.002). Although SAR and SIE mindset interventions are not "silver bullets", they offer a promising cost-effective low-threshold approach to improve performance across various domains.