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COH-FIT. Collaborative Outcomes study on Health and Functioning during Infection Times.

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VIDEO

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The project of research COH-FIT (Collaborative Outcomes study on Health and Functioning during Infection Times) is the world's largest study on the physical and mental impact of the pandemic. Anyone can contribute via its website.

It involves 200 international researchers who aim to collect information from more than 100,000 people on six continents. The University of Navarra participates through the group 'Mind-Brain' of the Institute for Culture and Society (ICS).

The survey COH-FIT will be in place throughout the pandemic and for up to one year after the end of the pandemic, with the goal to monitor progress. Information is sought anonymously from adults and, with parental consent and financial aid , from adolescents and children aged six years and older. 

COH-FIT aims to identify which individuals are at greater and lesser risk of experiencing physical and mental health problems during the pandemic and at different levels of physical distancing measures, and to identify risk and protective factors that will enable the design of prevention and intervention programmes, both for the current and future pandemics.

The results will be presented to the national and international academic community , with the goal to help develop targeted interventions for people at particularly high risk.

COH-FIT is supported by organisations such as the World Psychiatric Association, the European Network for Mental Illness Prevention and Mental Health Promotion (ECNP Network) and the Association for Child and Adolescent Mental Health (ACAMH), among others.

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* This project, with issue of transcript 0011-3638-2020-000010 has been funded by the Government of Navarra, department de Salud, through the call for projects of research in Health Sciences related to the pandemic produced by the SASRS-Cov-2 virus in 2020.

Aplicaciones anidadas

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Aplicaciones anidadas

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Main researcher

Gonzalo Arrondo

garrondo@unav.es
group Mind-brain ,  

 

CVN

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 With the support of: