The Relationship Between Depression and Resilience in Young Adults During the COVID-19 Pandemic
Year: 2024
Type: article
Study design: Observational Study
Abstract: Objective: This work aims to assess whether there is a causal relationship between resilience and depression in young adults during the recent COVID-19 pandemic Theoretical Framework: The COVID-19 pandemic has had a profound impact on the mental health of the world's population. Depression is a serious psychiatric condition. Young adults are particularly vulnerable to developing depression during the pandemic. Resilience is the ability to quickly return to your natural state of health after experiencing illness. Method: Sample: 762 young adults, aged between 20 and 40 years (mean = 26.38; standard deviation = 5.50), of which 199 (26.1%) were male, 559 (73.4%) %) female and 4 (0.5%) identified as others. Instruments: sociodemographic questionnaire, the Center for Epidemiological Studies - Depression Scale (CES-D) and the Connor-Davidson Resilience Scale (CD-RISC-10). Results and Discussion: The results obtained indicate that the levels of depression observed are higher than the cutoff points, indicating that the sample evaluated presented worrying levels of depression during the COVID-19 pandemic period. A moderate and significant negative correlation (rho = -0.523; p < 0.01) was observed between resilience and depression. Linear regression showed that resilience is a significant predictor that explains 28.2% of the variance in depression. Research Implications: The results presented may be useful to psychology professionals Originality/Value: These results may also be important to guide the population regarding the impacts caused by the COVID-19 pandemic.
Authors: Mariana Alves Kühne, Marcus Levi Lopes Barbosa, Thais Caroline Guedes Lucini, Camila Cristina de Oliveira, Rodrigo Rodrigues Souza, Veridiana Machado
Language: English
Topic: COVID-19 and Mental Health
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4404582959