Understanding School Anxiety in Italian Adolescence through an Artificial Neural Network: Influence of Social Skills and Coping Strategies

Autor: Francisco Manuel Morales-Rodríguez, Juan Pedro Martínez-Ramón, Manuel Alejandro Narváez Peláez, Catalda Corvasce
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Children, Vol 10, Iss 10, p 1688 (2023)
Druh dokumentu: article
ISSN: 2227-9067
DOI: 10.3390/children10101688
Popis: School anxiety depends on multiple factors that occur directly or indirectly in the teaching–learning process, such as going to the blackboard in class or reporting low grades at home. Other factors that influence school climate are social skills and coping strategies. That said, the aim of this research was to analyze the sources of school anxiety, coping strategies, and social skills in Italian secondary school students through an artificial neural network. For this purpose, a quantitative and ex post facto design was used in which the Inventory of School Anxiety (IAES), the Coping Scale for Children (EAN), and the Questionnaire for the Evaluation of Social Skills student version (EHS-A) were administered. The results showed that cognitive avoidance and behavioral avoidance coping strategies, together with the lack of social skills in students, are the variables that contributed the most to school anxiety scores in the artificial neural network. The conclusions revolve around the need to develop primary prevention programs.
Databáze: Directory of Open Access Journals