Income gap between male and female psychiatric nurses in China: A national survey.

Abstract

Aim: To investigate gender differences in the actual and expected income among psychiatric nurses in China.

Background: Although studies have shown that male nurses earn more than female nurses in other countries, there are no published data regarding gender income differences among psychiatric nurses in China.

Methods: We conducted a cross-sectional study involving 41 representative psychiatric hospitals in China. Demographic, income, and job-related data were analyzed using the inverse probability of treatment weighting (IPTW) based on the propensity score.

Findings: The sample included 9256 psychiatric nurses, and nearly four-fifths (79.3%) were female. Males earned slightly higher average monthly incomes than female nurses, while initial analysis showed no significant overall gender income difference (p > 0.05). Notably, most participants (92.5%) desired an income increase of at least 10%, with over half (56.2%) expressing significant dissatisfaction with their current income. After adjustment using propensity score combined with IPTW, females in the junior and mid-level groups had significantly lower income than their male counterparts (all p < 0.01), despite having different night shift patterns. However, there were no significant gender differences in actual or expected income among senior-level psychiatric nurses (p > 0.05).

Conclusion: A majority of psychiatric nurses in China express dissatisfaction with their current incomes and expect higher incomes. Male nurses earned significantly more than female nurses in the junior and mid-level professional groups, potentially due to their differences in night shifts.

Implications for nursing policy and health policy: Policymakers and hospital administrators should optimize the income structures of nurses and develop targeted policies to address the gender income gap. Improving nurse income has the potential to enhance motivation and satisfaction within the profession.