Patterns and Predictors of Mental Workload Among Student Nurses: A Latent Profile Analysis

Background Intern nursing students are actually facing considerable psychological burdens, which impact their mental well-being and career progression. Objective This study aimed to investigate the mental workload patterns of intern nursing students and identify the factors that predict these patterns. Methods A quantitative cross-sectional study was conducted involving 302 intern nursing students from five hospitals in Guangxi, China, between November 1 and December 30, 2024. The analysis of latent profiles was performed using Mplus 8.7 software, while Pearson’s chi-squared test and logistic regression analysis were carried out using SPSS 27.0 software. Results Three patterns of mental workload of intern nursing students were identified as “low MWL-high self-rated (n=45, 14.9%)”, “moderate MWL (n=152, 50.33%)”, and “high MWL-low self-rated (n=105, 34.77%)”. Conclusion This study provided novel insights into the mental workload (MWL) patterns among intern nursing students and identified key predictors, including age, internship duration, coping strategies, educational level and monthly income. The findings highlighted the heterogeneity of MWL and provide evidence-based guidance for nursing administrators to identify groups of students with high mental workload and to develop targeted psychological interventions and management strategies.