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Socio-economic and psychological impact of COVID-19 pandemic in a Spanish cohort BIOVAL-D-COVID-19 study protocol.
Miranda-Mendizabal, Andrea; Recoder, Silvia; Sebastian, Ester Calbo; Casajuana Closas, Marc; Leiva Ureña, David; Manolov, Rumen; Matilla Santander, Nuria; Forero, Carlos G; Castellví, Pere.
Afiliación
  • Miranda-Mendizabal A; Department of Medicine, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Barcelona, Spain.
  • Recoder S; Department of Basic Sciences, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Barcelona, Spain.
  • Sebastian EC; Hospital Universitari Mútua Terrassa, Terrassa, Barcelona, Spain.
  • Casajuana Closas M; Institut Universitari de Investigació en Atenció Primaria Jordi Gol, Barcelona, Spain.
  • Leiva Ureña D; Departament of Psychology, Universitat de Barcelona, Barcelona, Spain.
  • Manolov R; Departament of Psychology, Universitat de Barcelona, Barcelona, Spain.
  • Matilla Santander N; Karolinska Instituten, Stockholm, Sweden.
  • Forero CG; Department of Medicine, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Barcelona, Spain. Electronic address: cgarciaf@uic.es.
  • Castellví P; Department of Medicine, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Barcelona, Spain.
Gac Sanit ; 36(1): 70-73, 2022.
Article en En | MEDLINE | ID: mdl-34836679
OBJECTIVE: SARS-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. METHOD: Observational 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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Etiology_studies / Health_economic_evaluation / Observational_studies / Prognostic_studies / Risk_factors_studies Aspecto: Determinantes_sociais_saude / Patient_preference Límite: Adult / Humans Idioma: En Revista: Gac Sanit Asunto de la revista: SAUDE PUBLICA Año: 2022 Tipo del documento: Article País de afiliación: España Pais de publicación: España

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Etiology_studies / Health_economic_evaluation / Observational_studies / Prognostic_studies / Risk_factors_studies Aspecto: Determinantes_sociais_saude / Patient_preference Límite: Adult / Humans Idioma: En Revista: Gac Sanit Asunto de la revista: SAUDE PUBLICA Año: 2022 Tipo del documento: Article País de afiliación: España Pais de publicación: España