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Journal of Nursing ›› 2023, Vol. 30 ›› Issue (20): 37-42.doi: 10.16460/j.issn1008-9969.2023.20.037

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Potential categories of recessive truancy among nursing undergraduates and decision tree analysis for its influencing factors

WANG Yang-yanga, MA Jiao-naa, YIN Feib, YANG Nanb, TIAN Lingb   

  1. a. The Second Affiliated Hospital; b. Daqing Campus, Harbin Medical University, Harbin 150086, China
  • Received:2023-04-21 Online:2023-10-25 Published:2023-11-08

Abstract: Objective To identify the potential categories of recessive truancy among nursing undergraduates and analyze the core determinants of different categories, and to provide the reference for intervention measures. Methods By convenience sampling, 687 nursing undergraduates were recruited. The Recessive Truancy Scale, Learning Motivation Scale, Learning Burnout Scale and Self-control Scale were utilized to collect data. Latent profile analysis was used to identify the potential categories, and decision tree model was used to explore the core influencing factors of different categories. Results Three potential categories of recessive truancy were identified as follows: maladaptive type(37.0%), cognitive bias type(40.2%) and deep truancy type(22.8%). Learning motivation, learning burnout and self-control could predict the potential categories,and learning motivation lay at the root node of decision tree model. Conclusion There are 3 potential categories of recessive truancy among nursing undergraduates, and learning motivation is the core influencing factor. An intervention program centering on learning motivation can improve the nursing teaching quality.

Key words: nursing undergraduate, recessive truancy, potential categories, decision tree

CLC Number: 

  • R47
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