Social and Individual Factors Predicting Students' Resilience: A Multigroup Structural Equation Model

We investigated students' resilience predictors during the COVID-19 pandemic. With a two-wave longitudinal sample (n = 713) of students from Greece, Germany, and Switzerland (eighth grade in autumn 2020 and ninth grade in autumn 2021), we determined which social and individual predictors longitudinally predicted resilience before and during the COVID-19 pandemic. We identified the high likelihood of individual factors (self-esteem, self-efficacy) fostering resilience by social factors (teacher, parents, and social resources). Multigroup structural equation modeling analyses demonstrated that the adolescent population was best typified by two growth trajectory classes: a low-anxiety class characterized by a low initial level of depression/anxiety and a high-anxiety class characterized by a higher initial level of depression/anxiety. The model was gender-, migration-, and country-invariant. Overall, the model showed that teachers overlook adolescents with high anxiety or depression levels, but parents support them more. These findings highlight the necessity to pay attention to students' depression or anxiety symptoms and to satisfy their basic psychological needs, as vital prerequisites for their meaningful, coherent engagement in modern societies despite the odds.