Work-related Musculoskeletal Symptoms in Surgeons
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Introduction Surgeons are a unique group of healthcare professionals who are at risk for developing work-related musculoskeletal symptoms (WMS). The diversity of operating skills for laparoscopic and endovascular procedures impose different physical demands on surgeons, who also work under time pressure. The present study aims to examine the physical and psychosocial factors and their association with WMS among general surgeons in Hong Kong. Method A survey was conducted among surgeons working in the General Surgery departments in public hospitals of Hong Kong. Over 500 questionnaires were mailed and 135 surgeons completed the survey successfully (response rate 27%). Questions included demographics, workload, ergonomic and psychosocial factors. The relationship of these factors with WMS symptoms in the past 12 months was examined. Results Results indicated a high prevalence rate of WMS symptoms in surgeons, mainly in the neck (82.9%), low back (68.1%), shoulder (57.8%) and upper back (52.6%) regions. Sustained static and/or awkward posture was perceived as the factor most commonly associated with neck symptoms by 88.9% of respondents. Logistic regression showed the total score for physical ergonomic factors was the most significant predictor for all 4 body regions of musculoskeletal symptoms, with OR of 2.028 (95%CI 1.29–3.19) for the neck, 1.809 (1.34–2.43) for shoulder and 1.716 (1.24–2.37) for the lower back. Workstyle score was significantly associated with the symptom severity in the low back region (P = .003) but not with the other regions. Conclusion These results confirmed a strong association of physical and psychosocial factors with the musculoskeletal symptoms in surgeons. There is a potential for such musculoskeletal symptoms to escalate in the future, with rapid advances and increasing application of minimally invasive surgery.
KeywordsWork-related musculoskeletal symptoms Psychosocial Ergonomics Surgeons Laparoscopic and endovascular surgery
The authors would like to express their sincere appreciation to the BUPA Foundation for funding this research project. We would like to thank the research assistants, Silvana Lau, YY Wong, Winnie Leung and Ted Wong. Without their help, this project would not be run so smoothly. We would also like to acknowledge Mr. Raymond Chung from the Hong Kong Polytechnic University, and Ms. TJ Yiao, from the Hong Kong University for providing expert advice on statistical analysis.
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