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Does the suppression of irrelevant visual features require attentional resources? McDonald et al. (2023, Psychonomic Bulletin & Review, 30, 224-234) proposed that suppression processes are unavailable while a person is busy performing another task. They reported the absence of the PD (believed to index suppression) when two tasks were presented close together in time. We looked for converging evidence using established behavior measures of suppression. Following McDonald et al., our participants performed a rapid serial visual presentation (RSVP) task followed by a search task. For the RSVP task, participants determined whether the target digit 4 or 6 appeared within a string of other digits. The search display appeared at a lag of 2 or 8 digits after the RSVP target. Participants searched for a yellow target circle amongst nine background circles, which included a uniquely colored distractor for some trials. The main question was whether distractor suppression would occur at Lag 2, while attentional resources were still processing the RSVP target. Suppression was assessed using the captureprobe paradigm. On 30% of trials, probe letters appeared inside the colored circles and participants reported those letters. Probe recall accuracy was lower at locations with distractor colors than those with neutral colors (the baseline), suggesting proactive suppression. Critically, this difference in probe recall accuracy was similar at Lag 2 and Lag 8, suggesting that the ability to proactively suppress distractors remains intact while dual-tasking. We argue that although reactive suppression likely requires attentional resources, proactive suppression-an implicit process-does not.

[This corrects the article DOI: 10.1371/journal.pone.0332580.].

The biopsychological response patterns to digital stress have been sparsely investigated so far. Important potential stressors in modern working environments due to increased digitalization are multitasking and work interruptions. In this study protocol, we present a protocol for a laboratory experiment, in which we will investigate the biopsychological stress response patterns to multitasking and work interruptions. In total, N = 192 healthy, adult participants will be assigned to six experimental conditions in a randomized order (one single-task, three dual-task (two in parallel and one as interruption), one multitasking, and one passive control condition). Salivary alpha-amylase as well as heart rate as markers for Sympathetic Nervous System Activity, heart rate variability as measure for Parasympathetic Nervous System (PNS) activity, and cortisol as measure for activity of the hypothalamic-pituitary adrenal (HPA) axis will be assessed at six time points throughout the experimental session. Furthermore, inflammatory markers (i.e., IL-6, C-reactive protein (CRP), and secretory immunoglobulin-A) will be assessed before and after the task as well as 24 hours after it (IL-6 and CRP only). Main outcomes will be the time course of these physiological stress markers. Reactivity of these measures will be compared between the experimental conditions (dual-tasking, work interruptions, and multitasking) with the control conditions (single-tasking and passive control). With this study protocol, we present a comprehensive experiment, which will enable an extensive investigation of physiological stress-responses to multitasking and work interruptions. Our planned study will contribute to a better understanding of physiological response patterns to modern (digital) stressors. Potential risks and limitations are discussed. The findings will have important implications, especially in the context of digital health in modern working and living environments.

In this work, we consider multitasking in the context of solving multiple optimization problems simultaneously by conducting a single search process. The principal goal when dealing with this scenario is to dynamically exploit the existing complementarities among the problems (tasks) being optimized, helping each other through the exchange of valuable knowledge. Additionally, the emerging paradigm of evolutionary multitasking tackles multitask optimization scenarios by using biologically inspired concepts drawn from swarm intelligence and evolutionary computation. The main purpose of this survey is to collect, organize, and critically examine the abundant literature published so far in evolutionary multitasking, with an emphasis on the methodological patterns followed when designing new algorithmic proposals in this area (namely, multifactorial optimization and multipopulation-based multitasking). We complement our critical analysis with an identification of challenges that remain open to date, along with promising research directions that can leverage the potential of biologically inspired algorithms for multitask optimization. Our discussions held throughout this manuscript are offered to the audience as a reference of the general trajectory followed by the community working in this field in recent times, as well as a self-contained entry point for newcomers and researchers interested to join this exciting research avenue.

The current generation of young people indulges in more media multitasking behavior (e.g., instant messaging while watching videos) in their everyday lives than older generations. Concerns have been raised about how this might affect their attentional functioning, as previous studies have indicated that extensive media multitasking in everyday life may be associated with decreased attentional control. In the current study, 149 adolescents and young adults (aged 13–24years) performed speech-listening and reading tasks that required maintaining attention in the presence of distractor stimuli in the other modality or dividing attention between two concurrent tasks. Brain activity during task performance was measured using functional magnetic resonance imaging (fMRI). We studied the relationship between self-reported daily media multitasking (MMT), task performance and brain activity during task performance. The results showed that in the presence of distractor stimuli, a higher MMT score was associated with worse performance and increased brain activity in right prefrontal regions. The level of performance during divided attention did not depend on MMT. This suggests that daily media multitasking is associated with behavioral distractibility and increased recruitment of brain areas involved in attentional and inhibitory control, and that media multitasking in everyday life does not translate to performance benefits in multitasking in laboratory settings. [Display omitted] •Media multitasking (MMT) and attention was studied in young participants.•Higher levels of daily MMT were associated with distractibility.•This distractibility was paired with increased brain activity in right prefrontal regions.•Dual-task performance in laboratory settings was unaffected by MMT.

How are women entrepreneurs transforming and challenging traditional understandings of professional success in the 21st century, despite the multitasking whirlpool? What type of knowledge and skills are required in today’s digital world to develop professionally and succeed as an entrepreneur? What are the major barriers to successful entrepreneurship preventing women from realizing their full potential or stopping them from even beginning an entrepreneurial career? A current literature review (2011–2019) on women’s entrepreneurial initiatives, skills, characteristics, attributes, motives and leadership styles, documenting strategies for success and barriers confronted, indicates that not much has changed. Women entrepreneurs continue to face the multitasking whirlpool, along with the lack of financial resources, marketing skills and support services, including poor access to business networks, technology and digital markets. Despite the mass entry of women in exclusively male domains, glass ceilings have not been shattered. Then again, developed and developing nations have come to understand that women’s entrepreneurial activities contribute to socioeconomic growth and utilizing the full potential of all human resources is essential for sustainable development. Studies of the 21st century—as those of the late 20th century —continue to spotlight gender gaps in entrepreneurship as well as the so-valued career–family balance, while still arguing that further research is needed. They also agree that successful entrepreneurship requires digital skills along with the drive for innovation. The successful entrepreneur, or to use a term and concept coined by Elias G. Carayannis and McDonald R. Stewart (2013), the “distinguished entrepreneur” regardless of gender, is an innovator; a visionary; a person who predicts and shapes the future; takes initiatives; accepts change, risk and failure; learns from it; and sees what others do not see, among other things. Accordingly, this study presents snapshots of lives changed and empowered. It includes the work and narratives of “distinguished” (Carayannis & Stewart 2013) women entrepreneurs who have made a difference. Is it not time to shed some light on inspirational role models, especially those who are excelling in the startup world, the Blue Economy and the Silver Economy?

Multitasking (MT)–performing more than one task at a time–has become ubiquitous in everyday life. Understanding of how MT is learned could enable optimizing learning regimes for tasks and occupations that necessitate frequent MT. Previous research has distinguished between MT learning regimes in which all tasks are learned in parallel, single-task (ST) learning regimes in which all tasks are learned individually, and mixed learning regimes (Mix) in which MT and ST regimes are mixed. Research using simple laboratory tasks has consistently shown that MT regimes are the most efficient–the so-called dual-task practice advantage . However, it is currently unclear which learning regimes are used in everyday life, and which regime people would prefer if given a choice. To answer these questions, 72 participants completed an online survey to describe their real-life experiences of MT learning (e.g., when learning to drive), their opinions about learning MT activities, and filled out the Multitasking Preference Inventory to assess polychronicity. Descriptive statistics showed that for everyday activities, particularly learning to drive, Mix regimes were both the most used and most preferred method, whereas MT regimes were the least preferred. A potential explanation is that everyday MT tasks are typically complex, and so people prefer to learn the individual tasks first, before combining the tasks into an MT learning regime. Preference to engage in MT, as assessed by the MPI, positively correlated (Pearson’s r = .24) with preference for MT learning regimes, suggesting that individual differences in learning of complex everyday MT activities can be determined. In conclusion, everyday life multitasking activities such as learning to drive are mostly learned in Mix regimes, i.e. a combination of ST and MT training, and people’s preference to learn such activities with MT regimes increases with their level of polychronicity.