ArticleGaceta sanitaria
Socio-economic and psychological impact of COVID-19 pandemic in a Spanish cohort BIOVAL-D-COVID-19 study protocol.
Article in Gaceta sanitaria. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Factors Associated With Job Precariousness and Material Deprivation, and Their Association With Mental Health During the COVID-19 Pandemic.Suicide & life-threatening behavior · 2026Article
- Extracellular Vesicles as a Translational Approach for the Treatment of COVID-19 Disease: An Updated Overview.Viruses · 2023Review
- Scoping review of the methodology of large health surveys conducted in Spain early on in the COVID-19 pandemic.Frontiers in public health · 2023Article
- Low Resilience Was a Risk Factor of Mental Health Problems during the COVID-19 Pandemic but Not in Individuals Exposed to COVID-19: A Cohort Study in Spanish Adult General Population.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveSARS-CoV-2 outbreak has a negative psychological impact among general population. Data comparing mental health status before and during the outbreak is needed. The BIOVAL-D-COVID-19 study assess the socio-economic and psychological impact of the COVID-19 pandemic and lockdown in a representative sample of non-institutionalized Spanish adult population, and estimate the incidence of mental health disorders, including suicidal behaviours, and possible related factors.
methodObservational longitudinal study including two online surveys: baseline survey (T0) performed during 2019 and follow-up survey (T1) conducted 12-month later. The latter included nine sections: socio-demographic, health status, mental health, employment conditions and status, material deprivation, use of healthcare services, intimate partner violence and resilience. Four of the nine sections are administered in T0 and T1 assessments. Longitudinal data analyses will estimate adjusted incidence rates of mental health disorders using Poisson regression models. Risk and protective factors will be analysed through multiple logistic regression models.
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