ArticleBMC nursing2025
Patterns and predictors of mental workload in intern nursing students: a latent profile analysis.
Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Associations of mindful eating and physical activity with mental workload and sleep quality in medical interns.Scientific reports · 2026Article
- Latent profiles of career locus of control and associated factors among undergraduate nursing students in China: a cross-sectional study.BMC nursing · 2026Article
- Latent profile and associated factors of digital health literacy among patients with coronary heart disease: a cross-sectional study.Frontiers in public health · 2026Article
- The Relationship Between Transition Shock and Nursing Informatics Competency in Nursing Interns: A Moderated Mediation Model of Psychological Empowerment and Teaching Hospital Grade.Journal of nursing management · 2026Article
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Authors and funding
6 authors.
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Abstract
backgroundIntern nursing students are facing considerable psychological burdens, which impact their mental well-being and career progression. Although numerous studies have explored the psychological status of intern nursing students and its influencing factors, the majority of these investigations have primarily focused on single-factor linear relationships. To date, there has been limited research analyzing the individual differences among intern nursing students.
objectiveThis study aimed to investigate the mental workload patterns of intern nursing students and identify the factors that predict these patterns.
methodsA total of 320 intern nursing students were recruited for this study via convenience sampling, 302 of whom completed the survey. A pattern of intern nursing students' mental workload was identified through a latent profile analysis of 6 items on the NASA-Task Load Index scale. The analysis of latent profiles was performed using Mplus 8.7 software, while χ2 test and logistic regression analysis were carried out using SPSS 27.0 software.
resultsThree 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%)". Age and monthly income of 3000-5000 RMB were the main predictors of low MWL-high self-rated pattern. In contrast, long internships, passive coping strategies, college degree and monthly income < 3000 RMB were predictors of moderate MWL pattern.
conclusionThis study provided novel insights into the mental workload patterns among intern nursing students. The findings highlighted the heterogeneity of MWL and provide evidence-based guidance for nursing administrators to identify groups of intern nursing students with high mental workload and to develop targeted psychological interventions and management strategies. CLINICAL TRIAL NUMBER: Not applicable.
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