Burnout crisis in Chinese radiology: will artificial intelligence help?

Area of Science:

• Radiology
• Medical Informatics
• Occupational Health

Background:

• Radiology staff in China experience high rates of occupational burnout.
• There is a need to investigate quantitative methods for mitigating this burnout.
• Artificial intelligence (AI) software is increasingly adopted in medical imaging.

Purpose of the Study:

• To assess the correlation between artificial intelligence (AI) software usage and occupational burnout among radiology professionals in China.
• To identify factors influencing burnout in radiology departments.

Main Methods:

• A cross-sectional online survey was conducted among 522 radiologists and technicians across 68 public hospitals in China (February-July 2024).
• Data were collected using general information questionnaires, the Maslach Burnout Inventory-Human Services Survey (MBI-HSS), and a custom AI usage questionnaire.
• Multiple linear regression analysis was performed to examine correlations, controlling for general information variables.

Main Results:

• 74.5% of respondents used AI, with 48.3% using it for over 12 months; 25.5% had not adopted AI.
• Radiologists showed higher AI usage (82.0%) compared to technicians (59.9%).
• Burnout signs were present in 65.9% of respondents. Duration of AI use showed a significant negative correlation with burnout (r = -0.112, p < 0.05).
• Key factors influencing burnout included salary satisfaction, night shifts, AI usage duration, weekly hours, having children, and professional rank (all p < 0.05).

Conclusions:

• Artificial intelligence (AI) software demonstrates potential in mitigating occupational burnout among radiology staff.
• Increased duration of AI software usage is associated with reduced burnout severity, especially for radiologists.
• Encouraging AI adoption in radiology can help prevent and alleviate burnout in Chinese healthcare settings.