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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Feb 25, 2026
Date Accepted: Aug 18, 2026

The final, peer-reviewed published version of this preprint can be found here:

Generative AI Use, Perceived Usefulness, Perceived Risk, and Physician Burnout and Fulfillment Among Chinese Physicians: Mixed Methods Multiregional Study

Guo D, Zhao Y, Yang T, Bao X, Huang P

Generative AI Use, Perceived Usefulness, Perceived Risk, and Physician Burnout and Fulfillment Among Chinese Physicians: Mixed Methods Multiregional Study

J Med Internet Res 2026;28:e94155

DOI: 10.2196/94155

PMID: 42727068

Generative artificial intelligence use, perceived usefulness, perceived risk, and physician burnout and fulfillment: A mixed-methods multi-regional study in China

  • Dan Guo; 
  • Yanan Zhao; 
  • Tingkun Yang; 
  • Xingyu Bao; 
  • Ping Huang

ABSTRACT

Background:

As generative artificial intelligence (GenAI) becomes increasingly prevalent, its impact on physician mental health has garnered significant attention, yet empirical evidence remains limited.

Objective:

This study aims to investigate how the usage of GenAI, perceived usefulness (PU) and perceived risk (PR) influence physicians’ burnout and fulfillment.

Methods:

A mixed-methods design was employed, integrating a quantitative survey of physicians across four regions in China with in-depth qualitative interviews to elucidate the underlying psychological mechanisms. A mixed-methods approach was adopted to provide a comprehensive understanding of the impact of GenAI on physicians. The quantitative component involved a cross-sectional survey of 961 physicians recruited from four distinct regions across China. The survey instrument captured data on demographic and professional characteristics, socioeconomic status, AI usage frequency, PU and PR. Semi-structured interviews with 10 doctors were used for in-depth mining.

Results:

Quantitative analysis revealed no direct correlation between AI usage frequency and burnout. However, PU positively predicted professional fulfillment (OR=1.55, 95%CI:1.20-1.99), whereas PR was a significant positive predictor of burnout (OR=1.86, 95%CI:1.52-2.27). Stratified analysis showed that for physicians working ≥ 3 night shifts per week, AI usage was associated with a substantially higher risk of burnout (OR = 4.21, 95% CI: 2.83–7.32). The qualitative findings further found that the benefits of using AI may be offset by the additional burden. The PU of AI may improve the sense of professional fulfillment by improving the self-efficacy, while the risk of AI may increase burnout due to unclear boundaries of responsibilities and rights and challenges to professional identity.

Conclusions:

AI revolution in medicine is as much a psychological transition as it is a technological one. To prevent professional burnout, healthcare systems must move beyond simple efficiency metrics and proactively address the cognitive burdens and identity challenges faced by clinicians, ensuring that AI serves as an empowering partner rather than a source of professional strain.


 Citation

Please cite as:

Guo D, Zhao Y, Yang T, Bao X, Huang P

Generative AI Use, Perceived Usefulness, Perceived Risk, and Physician Burnout and Fulfillment Among Chinese Physicians: Mixed Methods Multiregional Study

J Med Internet Res 2026;28:e94155

DOI: 10.2196/94155

PMID: 42727068

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