# Abnormal intrinsic functional hubs and connectivity in nurses with occupational burnout: a resting-state fMRI study

## TL;DR

This study uses brain scans to find differences in brain activity and connections in nurses with burnout compared to healthy individuals, identifying key brain regions involved.

## Contribution

The study identifies specific brain regions and connections associated with occupational burnout using resting-state fMRI and develops a classification model for burnout detection.

## Key findings

- Burnout nurses showed decreased brain activity in the precuneus and reduced connectivity with the medial orbitofrontal cortex.
- These brain changes correlated with burnout symptoms like emotional exhaustion and personal accomplishment.
- A brain scan-based model accurately distinguished burnout from healthy controls with 85% accuracy.

## Abstract

Occupational burnout is a significant problem among nurses, linked to negative outcomes. Understanding its neurobiological basis is crucial, yet remains limited.

Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 40 female nurses with occupational burnout and 40 healthy controls. Degree centrality (DC) was calculated to identify functional hubs, and subsequent functional connectivity (FC) analysis was performed. Group differences in DC and FC were statistically compared. Their correlations with Maslach Burnout Inventory-Human Services Survey (MBI-HSS) scores were assessed, and a classification model was built using DC and FC features to distinguish between burnout and control groups.

The burnout group showed significantly decreased DC in bilateral precuneus and reduced FC between left precuneus and right medial orbitofrontal cortex (mOFC) compared to the healthy control group. These neuroimaging markers correlated with clinical burnout dimensions: precuneus DC negatively associated with emotional exhaustion and depersonalization, while precuneus-mOFC connectivity positively correlated with personal accomplishment. A linear discriminant analysis model combining DC and FC measures achieved 85% classification accuracy (sensitivity 80%, specificity 90%) in distinguishing burnout from controls.

These findings identify the precuneus and its mOFC connectivity as key neural substrates of occupational burnout, suggesting disrupted integration between self-referential processing and reward/emotion regulation systems. Our results advance understanding of burnout’s neurobiological mechanisms and demonstrate the potential of neuroimaging markers for objective burnout assessment.