Task Performance Research Articles

The Impact of Different Interruptions on Perceived Stress: Developing a Multimodal Measurement for Early Detection

This study presents the experimental findings investigating the effect of different interruptions on stress levels and validates indicators for interruption detection based on machine learning. Data were collected from one hundred and four subjects across simulated office-like tasks (i.e., writing and problem-solving) by four interruption types (i.e., distraction, intrusion, break, and multitasking). Behavioral data (RT and error rate), physiological signals (HR and EDR), and subjective ratings were recorded. Features based on ANOVA were extracted and entered into the classification models as inputs to examine how well different variables could be used to evaluate interruptions. Different stress outcomes were found on objective and subjective measures by interruption type. Also, we found that a combination of physiological signals, behavioral data, and subjective ratings provides the best accuracy. Additionally, the results suggest that task performance is a more reliable indicator than subjective ratings for interruption measurement and classification. This study uses methods that could be adapted for office workers, and the results provide preliminary support for developing an early interruption detection system. The methods employed in this research may benefit office staff, and the results offer preliminary support for developing an early interruption detection system to enhance worker health and company productivity.

Toward a better understanding of self‐regulation promoting interventions: When performance management and job crafting meet

AbstractOrganizations utilize self‐regulation promoting interventions to empower employees in managing challenges and resources autonomously. However, there is limited understanding of how these interventions impact employee task performance and innovative behavior, as well as which processes are critical for their effectiveness. Therefore, a field experiment was conducted to examine the effects of two self‐regulation promoting interventions—the Productivity Measurement and Enhancement Systems intervention (ProMES), a job crafting intervention, and their combination—on individual employee performance and innovation through selected process variables. We collected data before, during, and after the interventions over 16 weeks among 123 employees across three experimental and one control group. Consistent with predictions, participants of the ProMES intervention reported a higher level of perceived team climate, which consequently contributed to greater individual innovative behavior. Participants in the job crafting intervention exhibited an increase in job crafting behaviors, which consequently increased innovative behavior and task performance. Unexpectedly, the combined intervention yielded negative effects on both innovative behavior and task performance. The findings suggest that while self‐regulation promoting interventions increase favorable outcomes through different mechanisms their combination may impair relevant processes and, more generally, overwhelm employees.

Media multitasking: Performance differences between younger and older adults and the role of working memory

We examined the effects of media multi- vs. single-tasking on performance in a scenario that resembled the media multitasking requirement of many contemporary office workplaces.Older (n = 117, Mage = 70.99 years, SD = 5.18) and younger adults (n = 109, Mage = 22.86, SD = 3.93) performed a repetitive computer-based reading task (Task 1) that, in the multitasking condition, was repeatedly interrupted by news app messages that the participants had to read for comprehension (Task 2). In the single-tasking condition, the messages appeared after Task 1 was completed. In both conditions, participants afterwards answered questions about the message content. Performance in Task 1 was poorer in the multi- than in the single-tasking condition, but there was no evidence of greater multitasking costs in the older compared to the younger adults. Regarding Task 2, there was no indication of multitasking costs in any age group, but older adults showed poorer comprehension, regardless the task requirements. This effect of age was mediated via working memory updating abilities. Thus, the way information is commonly presented in social media, that is, usually bit-by-bit and not ordered by topic, seems to disadvantage older readers due to poorer updating abilities.All in all, the results provide some indication that, in terms of task accuracy, older adults do not appear to be at a disadvantage compared to younger adults when it comes to coping with the multitasking demands of digitalized societies.

Reduced sensitivity to future consequences underlies gambling decision in cerebellar ataxia

IntroductionPrevious research has identified that people with cerebellar ataxia (CA) showed impaired reward-related decision-making in the Iowa Gambling Task (IGT). To investigate the mechanisms underlying this impairment, we examined CA participants' combination of performance in the IGT, which predominantly tests reward seeking, and the modified IGT (mIGT), which mainly assesses punishment avoidance. MethodsFifty participants with CA and one hundred controls completed the IGT and mIGT. Task performance in each of the five twenty-trial blocks was compared between groups and the learning rates were assessed with simple linear regressions. Each participant's IGT score and mIGT score were compared. ResultsCA participants performed worse than controls in both the IGT and the mIGT, especially in the last block (IGT: −0.24 ± 10.05 vs. 3.88 ± 10.31, p = 0.041; mIGT: 2.72 ± 7.62 vs. 8.65 ± 8.64, p < 0.001). In contrast to the controls, those with CA did not significantly improve their scores over time in either task. Controls performed better in the mIGT than the IGT, while CA participants' scores in the two tasks showed no significant difference. IGT and mIGT performance did not correlate with ataxia severity or depressive symptoms. ConclusionIndividuals with CA showed impaired performance in both the IGT and mIGT, which indicates disruption in both short-term reward seeking and short-term punishment avoidance. Therefore, these results suggest that reduced sensitivity to long-term consequences drives the risky decision-making in CA.

Balancing Human Likeness in Social Robots: Impact on Children’s Lexical Alignment and Self-disclosure for Trust Assessment

While there is evidence that human-like characteristics in robots could benefit child-robot interaction in many ways, open questions remain about the appropriate degree of human likeness that should be implemented in robots to avoid adverse effects on acceptance and trust. This study investigates how human likeness, appearance and behavior, influence children’s social and competency trust in a robot. We first designed two versions of the Furhat robot with visual and auditory human-like and machine-like cues validated in two online studies. Secondly, we created verbal behaviors where human likeness was manipulated as responsiveness regarding the robot’s lexical matching. Then, 52 children (7-10 years old) played a storytelling game in a between-subjects experimental design. Results show that the conditions did not affect subjective trust measures. However, objective measures showed that human likeness affects trust differently. While low human-like appearance enhanced social trust, high human-like behavior improved children’s acceptance of the robot’s task-related suggestions. This work provides empirical evidence on manipulating facial features and behavior to control human likeness in a robot with a highly human-like morphology. We discuss the implications and importance of balancing human likeness in robot design and its impacts on task performance, as it directly impacts trust-building with children.

WSM-MIL: a weakly supervised segmentation method with multiple instance learning for C elegans image

Recently, image analysis techniques have been introduced to automate nematode information assessment. In image analysis-based nematode information assessment, the initial step involves detecting and segmenting C. elegans from microscopic images and network-based methods have been investigated. However, training a network for C. elegans image segmentation is typically associated with the labor-intensive process of pixel-level mask labeling. To address this challenge, we introduced a weakly supervised segmentation method using multiple instance learning (WSM-MIL). The proposed multi-instance weakly supervised segmentation method comprises three key components: a backbone network, a detection branch, and a segmentation branch. In contrast to fully supervised pixel-level annotation, we opted for weakly supervised bounding box-level annotation. This approach reduces the labour cost of annotation to some extent. The approach offers several advantages, such as simplicity, an end-to-end architecture, and good scalability. We conducted experiments comparing the proposed network with benchmark methods, and the results showed that the network exhibits competitive performance in the image segmentation task of C. elegans. The results of this study provide an effective method in the field of biological image analysis, as well as new ideas for solving complex segmentation tasks. The method is not only applicable to the study of C. elegans but also has wide applicability in biological image segmentation problems in other fields.

How do visual, auditory and motor dual-tasking each affect swallowing and chewing function?

It can be challenging to perform a second task at the same time as swallowing. The study aimed to investigate the effect of visual, auditory and motor dual-tasking on swallowing and chewing function in healthy young adults. Right-handed healthy adults without any psychological and cognitive problems were included in the study. Swallowing was evaluated based on the dysphagia limit in different liquid textures such as water and nectar consistencies, and chewing was evaluated by the Test of Masticating and Swallowing Solids. For the second task, visual and auditory performance was assessed using reaction time, and the motor performance was assessed using a bilateral tapping task. Assessments were performed in two steps: baseline and dual-task. For baseline, all evaluation methods were applied individually. After completing the baseline assessment, dual-task assessment were carried out the following day. For dual-task assessment, the swallowing and chewing tasks were performed simultaneously with visual, auditory and motor tasks. Results showed a significant decrease in dysphagia limit in the nectar consistency, and significant increase in chewing time, visual reaction time and tapping rate (right-left) when compared to baseline and dual-task conditions (χ2(3) = 9.61, p = .02; χ2(3) = 9.02, p = .02; χ2(3) = 28.09, p < .001; χ2(3) = 28.97, p < .001; χ2(3) = 21.56, p < .001, respectively). However, there were no differences in dysphagia limit in the water and auditory reaction time compared to baseline and dual-task conditions (χ2(3) = 3.18, p = .36; χ2(3) = 2.56, p = .50, respectively). Results shedding light on how simultaneous dual tasks can influence swallowing and chewing. Dual-tasking cause a decrease in both swallowing/chewing and the visual/motor performances. These results may provide valuable information for designing interventions or strategies aimed at improving or maintaining optimal swallowing and chewing during in various populations during daily life.

The cognitive cost of going the extra mile: How striving for improvement relates to cognitive performance.

Organizations are increasingly expecting individuals to engage in task proactivity, that is, to find better ways of doing their job. While prior research has demonstrated the benefits of task proactivity, little is known about its cognitive costs. To investigate this issue, we build theory on how task proactivity affects end-of-day cognitive performance. We propose that task proactivity involves deviating from established ways of working and engaging in cognitively demanding activities requiring high levels of mental effort, which manifest as an erosion of end-of-day cognitive performance. In two daily diary studies, we found that individuals engaging in task proactivity experience lower end-of-day cognitive performance (Study 1 over five consecutive workdays: n = 163, k = 701; Study 2 with multiple daily assessments over seven consecutive workdays: n = 93, k = 471), even when controlling for task performance (Study 1) and beginning-of-day cognitive performance (Study 2). In two experiments, we then show that simulating task proactivity results in greater mental effort and lower routineness but not in greater ego depletion (Study 3: N = 318 and Study 4: N = 319) or increased self-control demands, -effort, or -motivation (Study 4). This provides support for our proposed cognitive pathway. Our findings enhance our understanding of the cognitively demanding nature of task proactivity and provide empirical support for its cognitive costs using a mental fatigue lens. They also suggest that the impact of a cognitively demanding activity like task proactivity may persist throughout the day and carry over to other tasks involving cognitive performance. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Facial emotion recognition function and white matter microstructural alterations in drug-naive, comorbidity-free autism.

Individuals with autism spectrum disorder have deficits in facial emotion recognition and white matter microstructural alterations. Nonetheless, most previous studies were confounded by different variables, such as psychiatric comorbidities and psychotropic medications used by ASD participants. Also, it remains unclear how exactly FER deficits are related to white matter microstructural alterations in ASD. Accordingly, we aimed to investigate the FER functions, white matter microstructure, and their relationship in drug-naive and comorbidity-free ASD individuals. 59 ASD individuals and 59 typically developed individuals were included, where 46 ASD and 50 TD individuals completed FER tasks. Covariance analysis showed scores were lower in both basic and complex FER tasks in the ASD group. Tract-Based Spatial Statistics showed FA values in widespread white matter fibers were lower in the ASD group than in the TD group, including forceps major and forceps minor of the corpus callosum, anterior thalamic radiation, corticospinal tract, cingulum, inferior frontal-occipital fasciculus, inferior longitudinal fasciculus, superior longitudinal fasciculus. Moreover, in the TD group but not the ASD group, the performance in the complex FER task was negatively correlated with the FA value in some white matter fibers, including forceps major of the corpus callosum, ATR, CT, cingulum, IFOF, ILF, SLF. Our study suggests children with ASD may experience deficits in facial emotion recognition and exhibit alterations in white matter microstructure. More importantly, our study indicates that white matter microstructural alterations may be involved in FER deficits in children with ASD.

Getting value out of working memory through strategic prioritisation; implications for storage and control.

Working memory is an active system responsible for "the temporary maintenance and processing of information in the support of cognition and action" (Baddeley et al., 2021). In keeping with this, a growing body of research has explored the close links between working memory and attention, and how these might be harnessed to impact performance and possibly improve working memory efficiency. This is theoretically and practically important, given that working memory is a central hub in complex cognition yet is extremely capacity- and resource-limited. We review work carried out over the last ten years or so looking at how high 'value' items in working memory can be strategically prioritised through selective attention, drawing principally from visual working memory paradigms with young adult participants, while also discussing how the core effects extend to different task domains and populations. A consistent set of core findings emerges, with improved memory for items that are allocated higher 'value' but no change in overall task performance, and a recency advantage regardless of point allocation when items are encountered sequentially. Value-directed prioritisation is effortful, under top-down strategic control, and appears to vary with perceptual distraction and executive load. It is driven by processes operating during encoding, maintenance, and retrieval, though the extent to which these are influenced by different features of the task context remain to be mapped out. We discuss implications for working memory, attention, and strategic control, and note some possible future directions of travel for this promising line of research.

Rigidity‐Tunable Materials for Soft Engineering Systems

Engineering systems that leverage the flexibility and softness of soft materials have been fostering revolutionary progress and broad interest across various applications. The inherently flexible mechanical properties of these materials lay the groundwork for engineering systems that can adapt comparably to biological organisms, enabling them to adjust to unpredictable environments effectively. However, alongside the positive benefits of softness, these systems face challenges such as low durability, continuous energy demands, and compromised task performance due to the inherently low stiffness of soft materials. These limitations pose significant obstacles to the practical impact of soft engineering systems in the real world beyond innovative concepts. This review presents a strategy that employs materials with variable stiffness to balance adaptability advantages with the challenge of low rigidity. The developments are summarized in materials capable of stiffness modulation alongside their applications in electronics, robotics, and biomedical fields. This focus on stiffness modulation at the material unit level is a critical step toward enabling the practical application of soft engineering systems in real‐world scenarios.

Training-induced changes in population receptive field properties in visual cortex: Impact of eccentric vision training on population receptive field properties and the crowding effect.

This study aimed to investigate the impact of eccentric-vision training on population receptive field (pRF) estimates to provide insights into brain plasticity processes driven by practice. Fifteen participants underwent functional magnetic resonance imaging (fMRI) measurements before and after behavioral training on a visual crowding task, where the relative orientation of the opening (gap position: up/down, left/right) in a Landolt C optotype had to be discriminated in the presence of flanking ring stimuli. Drifting checkerboard bar stimuli were used for pRF size estimation in multiple regions of interest (ROIs): dorsal-V1 (dV1), dorsal-V2 (dV2), ventral-V1 (vV1), and ventral-V2 (vV2), including the visual cortex region corresponding to the trained retinal location. pRF estimates in V1 and V2 were obtained along eccentricities from 0.5° to 9°. Statistical analyses revealed a significant decrease of the crowding anisotropy index (p = 0.009) after training, indicating improvement on crowding task performance following training. Notably, pRF sizes at and near the trained location decreased significantly (p = 0.005). Dorsal and ventral V2 exhibited significant pRF size reductions, especially at eccentricities where the training stimuli were presented (p < 0.001). In contrast, no significant changes in pRF estimates were found in either vV1 (p = 0.181) or dV1 (p = 0.055) voxels. These findings suggest that practice on a crowding task can lead to a reduction of pRF sizes in trained visual cortex, particularly in V2, highlighting the plasticity and adaptability of the adult visual system induced by prolonged training.

Oculomotor behavior can be adjusted on the basis of artificial feedback signals indicating externally caused errors.

Whether a saccade is accurate and has reached the target cannot be evaluated during its execution, but relies on post-saccadic feedback. If the eye has missed the target object, a secondary corrective saccade has to be made to align the fovea with the target. If a systematic post-saccadic error occurs, adaptive changes to the oculomotor behavior are made, such as shortening or lengthening the saccade amplitude. Systematic post-saccadic errors are typically attributed internally to erroneous motor commands. The corresponding adaptive changes to the motor command reduce the error and the need for secondary corrective saccades, and, in doing so, restore accuracy and efficiency. However, adaptive changes to the oculomotor behavior also occur if a change in saccade amplitude is beneficial for task performance, or if it is rewarded. Oculomotor learning thus is more complex than reducing a post-saccadic position error. In the current study, we used a novel oculomotor learning paradigm and investigated whether human participants are able to adapt their oculomotor behavior to improve task performance even when they attribute the error externally. The task was to indicate the intended target object among several objects to a simulated human-machine interface by making eye movements. The participants were informed that the system itself could make errors. The decoding process depended on a distorted landing point of the saccade, resulting in decoding errors. Two different types of visual feedback were added to the post-saccadic scene and we compared how participants used the different feedback types to adjust their oculomotor behavior to avoid errors. We found that task performance improved over time, regardless of the type of feedback. Thus, error feedback from the simulated human-machine interface was used for post-saccadic error evaluation. This indicates that 1) artificial visual feedback signals and 2) externally caused errors might drive adaptive changes to oculomotor behavior.

Modeling Human-Like Acquisition of Language and Concepts

Humans acquire language and related concepts in a trajectory over a lifetime. Concepts for simple interaction with the world are learned before language. Later, words are learned to name these concepts along with structures needed to represent larger meanings. Eventually, language advances to where it can drive the learning of new concepts. Throughout this trajectory a language processing capability uses architectural mechanisms to process language using the knowledge already acquired. We assume that this growing body of knowledge is made up of small units of form-meaning mapping that can be composed in many ways, suggesting that these units are learned incrementally from experience. In prior work we have built a system to comprehend human language within an autonomous robot using knowledge in such units developed by hand. Here we propose a research program to develop the ability of an artificial agent to acquire this knowledge incrementally and autonomously from its experience in a similar trajectory. We then propose a strategy for evaluating this human-like learning system using a large benchmark created as a tool for training deep learning systems. We expect that our human-like learning system will produce better task performance from training on only a small subset of this benchmark.

Transformational leadership and follower performance: Relational and motivational bases of leader behaviors

AbstractBased on criticisms and recommendations in the literature made particularly in the last decade, this study focuses on the basic assumptions of transformational leadership (TL) theory such as “follower transformation,” “conceptual differences between the sub‐dimensions of TL” and “performance beyond expectations.” In this regard, it hypothesizes that while individualized consideration and idealized influence sub‐dimensions of TL affect followers' perceptions about the quality of their relationships with their leaders, the inspirational motivation and intellectual stimulation sub‐dimensions are mostly motivational (i.e., person‐organization fit and self‐efficacy), and that these sub‐dimensions enhance follower performance (i.e., organizational citizenship behaviors and task performance) through these specified mechanisms. It also hypothesizes that the quality of leader‐member exchanges moderates the influences of the motivational aspects of TL on follower performance. These hypotheses were tested and confirmed by analyzing the data from 222 leader–follower pairs from the private security sector. Theoretical and practical implications of the findings are discussed and suggestions for future research are provided. This article hopes to motivate future studies to clarify the TL theory and to further support its development.

The Impact of Transformational Leadership Styles on Task Performance and Psychological Capital: a Study on College Teachers in China

The Impact of Transformational Leadership Styles on Task Performance and Psychological Capital: a Study on College Teachers in China

Embodying Human-Like Modes of Balance Control Through Human-In-the-Loop Dyadic Learning

In this paper, we explore how humans and AIs trained to perform a virtual inverted pendulum (VIP) balancing task converge and differ in their learning and performance strategies. We create a visual analogue of disoriented IP balancing, as may be experienced by pilots suffering from spatial disorientation, and train AI models on data from human subjects performing a real-world disoriented balancing task. We then place the trained AI models in a dyadic human-in-the-loop (HITL) training setting. Episodes in which human subjects disagreed with AI actions were logged and used to fine-tune the AI model. Human subjects then performed the task while being given guidance from pretrained and dyadically fine-tuned versions of an AI model. We examine the effects of HITL training on AI performance, AI guidance on human performance, and the behavior patterns of human subjects and AI models during task performance. We find that in many cases, HITL training improves AI performance, AI guidance improves human performance, and after dyadic training the two converge on similar behavior patterns.

RPG: Rotation Technique in VR Locomotion using Peripheral Gaze

Locomotion is an important task in many virtual reality (VR) applications. Locomotion requires two different directional settings for: (1) translation to a target, and (2) body rotation. Conventional locomotion methods mostly make use of the hand-held controller for such directional control. The controller-based directional setting may not be natural, as in real life, humans set directions with the gaze, often together with the head/body rotation. Note that the view direction is independently and naturally controlled by the head (or gaze) direction. In this paper, we propose to use the peripheral gaze for body rotation, seamlessly together with the foveal gaze for the view control, so that the two tasks practically do not interfere with one another. In the comparative study, the peripheral gaze showed similar task performance to the controller-based rotation but with reduced VR sickness and improved usability.

The effect of VR on fine motor performance by older adults: a comparison between real and virtual tasks

Virtual Reality (VR) technology has the potential to support the aging population and improve testing of daily abilities to detect functional decline. In multiple research studies, VR performance of participants has been assessed by measuring time to complete test, but the effect of learning how to use the VR system and differences between real and virtual environments have been understudied, especially for fine motor tasks. In this study, 20 older adults ages 65–84 performed a task that required fine motor skills in real-life and then in a VR replica of the same task. All participants completed the task in each setting with no difficulties. A clear learning effect was observed in VR, which was attributed to learning how to use the device itself. Still, participants could not reach the same level of performance (time) in VR as in real-life. Participants rated the VR task more mentally and physically demanding than in real-life, as well as more stressful, but with an overall low cognitive demand. In an exploratory cluster analysis, participants with an average age of 69 years old had more technological devices, found the VR system more usable and realistic than participants in the group with an average of 76 years old. This study demonstrated that VR influences time to complete a fine motor task, and that learning effects related to the system could be confounded with actual task performance if not properly considered in VR studies with older adults.

Sensory integration for neuroprostheses: from functional benefits to neural correlates.

In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation-elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.