Investigating school absenteeism and refusal among Australian children and adolescents using Apriori association rule mining

Abstract

Abstract Identifying and determining the multitude of reasons behind school absences of students is often challenging. This study aims to uncover the hidden reasons for school absence in children and adolescents. The analysis is conducted on a national survey that includes 2967 Australian children and adolescents aged 11–17. The Apriori association rule generator of machine learning techniques and binary logistic regression are used to identify the significant predictors of school absences. Out of 2484, 83.7% (n = 2079) aged (11–17) years children and adolescents have missed school for various reasons, 42.28% (n = 879) are (11–15) years old, 24.52% (n = 609) and 16.9% (n = 420) are 16- and 17-years old adolescents respectively. A considerable proportion of adolescents, specifically 16.4% (n = 407) and 23.4% (n = 486) of 16 and 17 years old, respectively, have selected ‘refused to say’ as their reason for not attending school. It also highlights the negative outcomes associated with undisclosed reasons for school absence, such as bullying, excessive internet/gaming, reduced family involvement, suicide attempts, and existential hopelessness. The findings of the national survey underscore the importance of addressing these undisclosed reasons for school absence to improve the overall well-being and educational outcomes of children and adolescents.