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. 2024 Jun 8;10(11):e32594.
doi: 10.1016/j.heliyon.2024.e32594. eCollection 2024 Jun 15.

Treatment coverage for depression in the general Spanish population and the impact of the Covid-19 pandemic

Affiliations

Treatment coverage for depression in the general Spanish population and the impact of the Covid-19 pandemic

Lea Francia et al. Heliyon. .

Erratum in

Abstract

Background: Despite the availability of effective antidepressant strategies, numerous people with depressive disorders remain untreated. The Covid-19 pandemic has affected healthcare services, especially the mental health sector. This study aims to explore the coverage of depression treatments in the general Spanish population and the impact of the Covid-19 pandemic.

Methods: We used longitudinal data (2018 and 2022) from the general Spanish population: pre-pandemic n = 1512; mean age = 65.43 years ± 14.90; 56 % females; post-pandemic n = 909; mean age = 68.00 years ± 14.24; 54 % women. The International Classification of Disease 10th edition was used to diagnose lifetime depressive episodes and severity. We explored psychological and pharmacological treatment coverage via multiple logistic regressions adjusted for 4 covariates (sex assigned at birth, education level, age, Covid-19 pandemic) for participants with a diagnosis of depression.

Results: Treatment coverage for depression in the pre-pandemic and post-pandemic samples was, respectively, 53.3 % and 51.9 %. We observed an association between severe depression and treatment coverage (OR = 2.77, 95%CI 1.05 to 7.75). We found no association between the COVID-19 pandemic and treatment coverage.

Conclusions: The pharmacological treatment coverage was associated with severe types of depression. The prevalence rates of treatment coverage were similar in the pre- and post-COVID-19 pandemic attesting to the resilience of the mental health system in Spain.

Keywords: Adults; Assessment; Depressive episode; NICE guidelines.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Graph 1
Graph 1
Predicted probabilities of being under treatment according to the severity of depression and the date of the interview.
Graph 2
Graph 2
Predicted probabilities of being under pharmacological treatment according to the severity of depression and the date of the interview.
Graph 3
Graph 3
Predicted probabilities of being under psychological treatment according to the severity of depression and the date of the interview.

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