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How to navigate everyday distractions:
Leveraging optimal feedback to train attention control
Maria Wirzberger1,2,3, Anastasia Lado1,4, Lisa Eckerstorfer1, Ivan Oreshnikov1, Jean-Claude
Passy1, Adrian Stock1, Amitai Shenhav5 & Falk Lieder1
1Max Planck Institute for Intelligent Systems, Tübingen, Germany
2University of Stuttgart, Institute of Educational Science, Stuttgart, Germany
3LEAD Graduate School & Research Network, University of Tübingen, Germany
4Graduate Training Center for Neuroscience, Tübingen, Germany
5Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence,
Rhode Island, United States
To stay focused on their chosen tasks, people have to inhibit distractions. The underlying
attention control skills can improve through reinforcement learning, which can be accelerated
by giving feedback. We applied the theory of metacognitive reinforcement learning to develop
a training app that gives people optimal feedback on their attention control while they are
working or studying. In an eight-day field experiment with 99 participants, we investigated the
effect of this training on people’s productivity, sustained attention, and self-control. Compared
to a control condition without feedback, we found that participants receiving optimal feedback
learned to focus increasingly better (f = .08, p < .01) and achieved higher productivity scores
(f = .19, p < .01) during the training. In addition, they evaluated their productivity more
accurately (r = .12, p < .01). However, due to asymmetric attrition problems, these findings
need to be taken with a grain of salt.