Depression, post-traumatic stress, anxiety, and fear of COVID-19 in the general population and health-care workers: prevalence, relationship, and explicative model in Peru

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Abstract

Background

This study has two aims. First, determine the fit of the fear model to COVID-19, anxiety, and post-traumatic stress in the general population and health-care workers. Second, determine which model best explains the relationship between depression and the triad of fear, anxiety, and post-traumatic stress in both groups.

Method

A cross-sectional study was conducted using self-reported questionnaires for anxiety, fear of COVID-19, depression, and post-traumatic stress. Information was collected from adults living in Lima, the capital and the most populous city in Peru. The explanatory models were evaluated using a structural equation model.

Results

A total of 830 participants were included, including general population ( n = 640) and health-care workers ( n = 190). A high overall prevalence of depressive symptoms (16%), anxiety (11.7%), and post-traumatic stress (14.9%) were identified. A higher prevalence of depressive, anxious, or stress symptoms was identified in the general population (28.6%) compared to health-care workers (17.9%). The triad model of fear of COVID-19, anxiety, and stress presented adequate goodness-of-fit indices for both groups. A model was identified that manages to explain depressive symptoms in more than 70% of the general population and health-care workers, based on the variables of the triad (CFI = 0.94; TLI = 0.94; RMSEA = 0.06; SRMR = 0.06). In the general population post-traumatic stress mediated the relationship between anxiety and depression (β = 0.12; 95%CI = 0.06 to 0.18) which was significant, but the indirect effect of post-traumatic stress was not significant in health care workers (β = 0.03; 95%CI = − 0.11 to 0.19).

Limitations

The prevalence estimates relied on self-reported information. Other variables of interest, such as intolerance to uncertainty or income level, could not be evaluated.

Conclusions

Our study proposes and tests one model that explains more than 70% of depressive symptoms. This explanatory model can be used in health contexts and populations to determine how emotional factors can affect depressive symptoms.

Related collections

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Highlights • At least one in five healthcare professionals report symptoms of depression and anxiety. • Almost four in 10 healthcare workers experience sleeping difficulties and/or insomnia. • Rates of anxiety and depression were higher for female healthcare workers and nursing staff. • Milder mood symptoms are common and screening should aim to identify mild and sub-threshold syndromes.

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Author and article information

Contributors

Anthony Copez-Lonzoy: anthonycopez22@gmail.com

Journal

Journal ID (nlm-ta): BMC Psychiatry

Journal ID (iso-abbrev): BMC Psychiatry

Title: BMC Psychiatry

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-244X

Publication date (Electronic): 17 September 2021

Publication date PMC-release: 17 September 2021

Publication date Collection: 2021

Volume: 21

Electronic Location Identifier: 455

Affiliations

[1 ]GRID grid.441978.7, ISNI 0000 0004 0396 3283, Escuela de Medicina, , Universidad César Vallejo, ; Trujillo, Peru

[2 ]Instituto Peruano de Orientación Psicológica, Lima, Peru

[3 ]GRID grid.441908.0, ISNI 0000 0001 1969 0652, Unidad de Investigación en Bibliometría, , Universidad San Ignacio de Loyola, ; Lima, Peru

[4 ]Asociación Peruana de Profesionales de las Adicciones, Lima, Peru

[5 ]GRID grid.11100.31, ISNI 0000 0001 0673 9488, CRONICAS Center of Excellence in Chronic Diseases, , Universidad Peruana Cayetano Heredia, ; Lima, Peru

[6 ]Departamento de Psiquiatría, Hospital Nacional Guillermo Almenara Irigoyen, Lima, Peru

[7 ]GRID grid.10800.39, ISNI 0000 0001 2107 4576, Departamento Académico de Psiquiatría, , Universidad Nacional Mayor de San Marcos, ; Lima, Peru

Article

Publisher ID: 3456

DOI: 10.1186/s12888-021-03456-z

PMC ID: 8445782

PubMed ID: 34530803

SO-VID: 52e78f58-38bc-462e-9444-e52899d7f680

License:

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