Health-related quality of life in Chinese medical staff: a latent profile analysis

Objective: To investigate subgroups of health-related quality of life (HRQoL) in the Chinese medical staff and identify the demographic factors associated with these profiles. Methods: 574 Chinese medical staff were surveyed online. HRQoL was measured by using the 36-Item Short Form Health Survey, Version 2. Latent profile analysis (LPA) was used to identify the profiles of HRQoL. The associations between HRQoL profiles and covariates were assessed using multinomial logistic regression. Results: Three HRQoL profiles were developed: low HRQoL at 15.6%, moderate HRQoL at 46.9%, and high HRQoL at 37.6%. Multinomial logistic regression showed night shift times, aerobic exercise conditioning, and personality type significantly predicted the profile membership. Conclusion: Our findings develop earlier approaches that only used total scores to evaluate this group's HRQoL and help them with tailored interventions to promote better HRQoL.

Automated summary

This study aimed to investigate subgroups of health-related quality of life (HRQoL) in Chinese medical staff and identify the demographic factors associated with these profiles. A sample of 574 Chinese medical staff completed an online survey. Results revealed three profiles of HRQoL: low HRQoL at 15.6%, moderate HRQoL at 46.9%, and high HRQoL at 37.6%. Multinomial logistic regression analysis showed that night shift times, aerobic exercise conditioning, and personality type significantly predicted profile membership. These findings highlight the importance of tailored interventions to promote better HRQoL among medical staff.