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Reducing Interruptions at Work: A Large-Scale Field Study of FlowLight


Züger, Manuela; Corley, Christopher; Meyer, André; Li, Boyang; Fritz, Thomas; Shepherd, David; Augustine, Vinay; Francis, Patrick; Kraft, Nicholas; Snipes, Will (2017). Reducing Interruptions at Work: A Large-Scale Field Study of FlowLight. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, Colorado, USA, 6 May 2017 - 11 May 2017, 61-72.

Abstract

Due to the high number and cost of interruptions at work, several approaches have been suggested to reduce this cost for knowledge workers. These approaches predominantly focus either on a manual and physical indicator, such as headphones or a closed office door, or on the automatic measure of a worker's interruptibilty in combination with a computer-based indicator. Little is known about the combination of a physical indicator with an automatic interruptibility measure and its long-term impact in the workplace. In our research, we developed the FlowLight, that combines a physical traffic-light like LED with an automatic interruptibility measure based on computer interaction data. In a large-scale and long-term field study with 449 participants from 12 countries, we found, amongst other results, that the FlowLight reduced the interruptions of participants by 46%, increased their awareness on the potential disruptiveness of interruptions and most participants never stopped using it.

Abstract

Due to the high number and cost of interruptions at work, several approaches have been suggested to reduce this cost for knowledge workers. These approaches predominantly focus either on a manual and physical indicator, such as headphones or a closed office door, or on the automatic measure of a worker's interruptibilty in combination with a computer-based indicator. Little is known about the combination of a physical indicator with an automatic interruptibility measure and its long-term impact in the workplace. In our research, we developed the FlowLight, that combines a physical traffic-light like LED with an automatic interruptibility measure based on computer interaction data. In a large-scale and long-term field study with 449 participants from 12 countries, we found, amongst other results, that the FlowLight reduced the interruptions of participants by 46%, increased their awareness on the potential disruptiveness of interruptions and most participants never stopped using it.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:11 May 2017
Deposited On:09 May 2017 09:39
Last Modified:04 Jun 2017 18:49
Publisher:ACM
Series Name:CHI '17
Free access at:Official URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1145/3025453.3025662
Official URL:http://dl.acm.org/citation.cfm?doid=3025453.3025662
Other Identification Number:merlin-id:14802

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