Depressive symptoms in higher education students during the COVID-19 pandemic: the role of containment measures.

BACKGROUND: Students are a vulnerable group for the indirect impact of the COVID-19 pandemic, particularly their mental health. This paper examined the cross-national variation in students' depressive symptoms and whether this can be related to the various protective measures implemented in response to the initial stage of the COVID-19 outbreak. METHODS: Student data stem from the COVID-19 International Student Well-being Study, covering 26 countries during the first wave of the COVID-19 pandemic. Country-level data on government responses to the COVID-19 pandemic were retrieved from the Oxford COVID-19 Tracker. Multilevel analyses were performed to estimate the impact of the containment and economic support measures on students' depressive symptoms (n = 78 312). RESULTS: School and workplace closures, and stay-at-home restrictions were positively related to students' depressive symptoms during the COVID-19 pandemic, while none of the economic support measures significantly related to depressive symptoms. Countries' scores on the index of these containment measures explained 1.5% of the cross-national variation in students' depressive symptoms (5.3%). This containment index's effect was stable, even when controlling for the economic support index, students' characteristics, and countries' epidemiological context and economic conditions. CONCLUSIONS: Our findings raise concerns about the potential adverse effects of existing containment measures (especially the closure of schools and workplaces and stay-at-home restrictions) on students' mental health.

Cumulative (Dis)Advantage and the Matthew Effect in Life-Course Analysis.

To foster a deeper understanding of the mechanisms behind inequality in society, it is crucial to work with well-defined concepts associated with such mechanisms. The aim of this paper is to define cumulative (dis)advantage and the Matthew effect. We argue that cumulative (dis)advantage is an intra-individual micro-level phenomenon, that the Matthew effect is an inter-individual macro-level phenomenon and that an appropriate measure of the Matthew effect focuses on the mechanism or dynamic process that generates inequality. The Matthew mechanism is, therefore, a better name for the phenomenon, where we provide a novel measure of the mechanism, including a proof-of-principle analysis using disposable personal income data. Finally, because socio-economic theory should be able to explain cumulative (dis)advantage and the Matthew mechanism when they are detected in data, we discuss the types of models that may explain the phenomena. We argue that interactions-based models in the literature traditions of analytical sociology and statistical mechanics serve this purpose.