Occupational stress, burnout, and depression: an exploration from a network analysis perspective

Area of Science:

• Occupational health psychology
• Mental health research
• Network analysis in social sciences

Background:

• Occupational stress is a known precursor to psychological and physical health problems.
• High stress levels increase the risk of burnout and depression among workers.
• Understanding the complex relationships between these factors is crucial for effective intervention.

Purpose of the Study:

• To investigate the interrelationships between occupational stress, burnout, and depression using network analysis.
• To identify core, bridge, and upstream nodes within the occupational stress-burnout-depression network.
• To elucidate causal pathways and mediating roles in the development of depression.

Main Methods:

• Utilized network analysis, including undirected and directed graphs (Graphical Gaussian Model and Directed Acyclic Graphs - DAG).
• Collected data from 1363 participants from Beijing hospitals and a university.
• Employed validated scales: House and Rizzo's Work Stress Scale, Zung's Self-Report Depression Scale, and Maslach Burnout Inventory-General Survey.

Main Results:

• Emotional exhaustion (EE) emerged as the central 'core node' with the highest expected influence (2.11).
• Key bridging nodes included EE, specific occupational stress factors, cynicism (CY), and personal accomplishment (PA).
• DAG analysis revealed direct pathways from occupational stress to depression and indirect pathways mediated by CY and PA, supporting emotional dysregulation and burnout structural theories.

Conclusions:

• Identifying and targeting core, bridge, and upstream nodes in occupational stress networks is essential.
• These targeted interventions hold potential for preventing the onset and mitigating the progression of depression in occupational settings.
• The study highlights the utility of network analysis in understanding complex mental health dynamics in the workplace.