Task absorption and job demands: exploring task performance through neural and pupillary data

Juyumaya, Jesus; Leal, Andrea · 2025 · Crossref

DOI: 10.31117/neuroscirn.v8i2.390

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Summary

This paper outlines a proposed experimental study investigating the relationship between task characteristics, episodic absorption, and performance, grounded in the Job Demands-Resources (JD-R) theory. The research is motivated by the increasing cognitive demands of modern work environments, where employees must process substantial data and make real-time decisions. Absorption, defined as a temporary state of deep attentional engagement akin to "flow," is hypothesized to enhance task efficiency and performance. The study aims to address the gap in understanding how specific task designs influence this cognitive state by utilizing objective neural and physiological markers rather than relying solely on self-reported measures. The proposed methodology employs a between-subjects experimental design with 28 participants, primarily administrative and managerial workers. Participants will perform a modified n-back task, adapted into a calendar scheduling exercise, under four conditions varying by labor demand (amount of information to retain) and labor resource (viewing time allotted). Data collection involves simultaneous electroencephalography (EEG) using a 32-channel mobile system and eye-tracking via a Pupil-Core headset. The study focuses on two primary physiological indicators: pupillary dynamics, which reflect cognitive effort and attentional shifts, and the P300 event-related potential wave, a neural marker associated with attentional processing and working memory updates. Task performance will be evaluated based on accuracy in scheduling meetings without overlaps and adherence to time constraints. The study tests three main hypotheses. First, it posits that absorption positively influences task performance and output. Second, it predicts that episodes of absorption will correlate with increased P300 wave activation and distinct pupillary responses. Third, it hypothesizes that task characteristics significantly impact the frequency of absorption episodes, specifically expecting that high job demands coupled with high resources will result in frequent absorption, whereas combinations of high demands with low resources or low demands with high resources will lead to fewer episodes. The analysis will utilize Python and SPSS to examine regression models and psychometric evaluations of the Utrecht Engagement Scale. The significance of this research lies in its potential to provide empirical evidence linking task design to cognitive engagement through neurocognitive insights. By identifying the conditions that foster absorption, the findings could inform the design of work environments and tasks that promote sustained attentional engagement. This approach offers practical applications for organizational practices, suggesting that aligning job demands with adequate resources can optimize employee productivity, well-being, and performance. Additionally, the study highlights the potential for neurofeedback-based training as a tool to enhance focus and engagement in dynamic work settings.

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Topics

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• neuro workload indices
• workload measurement

Information type

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• Empirical Findings: physiological data
• Theoretical Contribution: theory or model