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Matthias Weigl

Researcher at Ludwig Maximilian University of Munich

Publications -  129
Citations -  3428

Matthias Weigl is an academic researcher from Ludwig Maximilian University of Munich. The author has contributed to research in topics: Medicine & Workload. The author has an hindex of 29, co-authored 107 publications receiving 2693 citations. Previous affiliations of Matthias Weigl include University of Bonn & Technische Universität München.

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Beyond top‐down and bottom‐up work redesign: Customizing job content through idiosyncratic deals

TL;DR: In this article, task i-deals customizing job content are suggested as a third approach to work redesign, and they are tested in two studies conducted in the United States and Germany using structural equation modeling.
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Work engagement accumulation of task, social, personal resources: A three-wave structural equation model

TL;DR: In this article, the authors investigated gain spirals between employees' engagement and their task, social, and personal resources, focusing on the key resources of job control, positive work relationships, and active coping behavior.
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The association of workflow interruptions and hospital doctors' workload: a prospective observational study.

TL;DR: Frequent workflow interruptions may be linked with increased workload in doctors and healthcare environments need to be better designed to reduce unnecessary interruptions and distractions so that hospital doctors can manage clinical work efficiently and safely.
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Virtual reality-based simulators for spine surgery: a systematic review.

TL;DR: To establish further adaptation of VR-based simulators in spinal surgery, future evaluations need to improve the study quality, apply long-term study designs, and examine non-technical skills, as well as multidisciplinary team training.

The moderating effects of job control and selection, optimization, and compensation strategies on the age-work ability relationship

TL;DR: In this paper, the authors investigated the effects of age, job control, and the use of successful aging strategies called selection, optimization, and compensation (SOC) in predicting work ability and found that the negative relationship between age and work ability was weakest for employees with high job control and high use of SOC strategies.