ArticlePloS one2023
Mental workload task modeled on office work: Focusing on the flow state for well-being.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This research aimed to objectively evaluate the optimal state of desk work (flow state) through physiological measurements and use the data to support workers' mental health and well-being. We suppose that the flow state evaluation in real-time can contribute to a concentrated work environment, improved work efficiency, and stabilize worker's minds. This study reports on the development of the mental task modeled on daily work for the physiological measurement experiment. In the first phase of the research, a field survey was conducted with 55 desk workers to understand the details of their jobs and develop suitable mental tasks. Further, the relationship between daily work content and subjective stress was clarified. In the second phase, based on the results of the field survey, a task inducing the flow state was developed for practical use. Through empirical experiments with 35 participants (22 adults and 13 students), the developed task was evaluated for its usefulness and possible issues by examining the relationships among subjective assessment, task performance, degree of flow state, and individual characteristics. The study results showed that the proposed mental task developed in this study constitutes practical work that can be used for concentrated and goal-directed efforts. The task also demonstrated the property of inducing a flow state. Further, the results suggest that it is necessary to adjust the task difficulty level and implement effective feedback methods to induce the flow state more effectively.
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