Background <p>Intern 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.</p> Objective <p>This study aimed to investigate the mental workload patterns of intern nursing students and identify the factors that predict these patterns.</p> Methods <p>A 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.</p> Results <p>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%)”. 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 &lt; 3000 RMB were predictors of moderate MWL pattern.</p> Conclusion <p>This 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.</p> Clinical trial number <p>Not applicable.</p>

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Patterns and predictors of mental workload in intern nursing students: a latent profile analysis

  • Yanmei Gan,
  • Tingting Liao,
  • Lingfang Liu,
  • Yao Du,
  • Mingjuan Guo,
  • Gaoye Li

摘要

Background

Intern 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.

Objective

This study aimed to investigate the mental workload patterns of intern nursing students and identify the factors that predict these patterns.

Methods

A 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.

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%)”. 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.

Conclusion

This 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.