Pilot Study Using Neurofeedback as a Tool to Reduce Surgical Resident Burnout
- 3 October 2020
- journal article
- conference paper
- Published by Ovid Technologies (Wolters Kluwer Health) in Journal of the American College of Surgeons
- Vol. 232 (1), 74-80
- https://doi.org/10.1016/j.jamcollsurg.2020.08.762
Abstract
Background Burnout is prevalent among surgical residents. Neurofeedback is a technique to train the brain in self-regulation skills. We aimed to assess the impact of neurofeedback on the cognitive workload and personal growth areas of surgery residents with burnout and depression. Study Design Fifteen surgical residents with burnout (Maslach Burnout Inventory [MBI] score > 27) and depression (Patient Health Questionnaire–9 Depression Screen [PHQ-9] score >10), from 1 academic institution, were enrolled and participated in this institutional review board-approved prospective study. Ten residents with more severe burnout and depression scores were assigned to receive 8 weeks of neurofeedback treatments, and 5 others with less severe symptoms were treated as controls. Each participant's cognitive workload (or mental effort) was assessed initially, and again after treatment via electroencephalogram (EEG) while the subjects performed n-back working memory tasks. Analysis of variance (ANOVA) tested for significance between the degree of change in the treatment and control groups. Each subject was also asked to rate changes in growth areas, such as sleep and stress. Results Both groups showed high cognitive workload in the pre-assessment. After the neurofeedback intervention, the treatment group showed a significant (p < 0.01) improvement in cognitive workload via EEG during the working memory task. These differences were not noted in the control group. There was significant correlation between time (NFB sessions) and average improvement in all growth areas (r = 0.98) Conclusions Residents demonstrated high levels of burnout, correlating with EEG patterns indicative of post-traumatic stress disorder. There was a notable change in cognitive workload after the neurofeedback treatment, suggesting a return to a more efficient neural network.Keywords
Funding Information
- University of North Carolina
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