Prevalence of depression and anxiety in Colombia: What happened during Covid-19 pandemic?
Bibliographic record
Abstract
The COVID-19 pandemic has impacted the well-being of millions of people around the globe. The evidence has shown that during the COVID-19 pandemic, the mental health of the population was affected, which means that there is an extra demand to implement different actions to mitigate and treat mental health disorders result of the pandemic. According to the literature it was expected that the prevalence of mental health disorders, such as anxiety and depression increased by 25 per cent worldwide, and Colombia was not the exception. However, there is not clear evidence on how much this increase might be. This study aims to estimate the prevalence of anxiety and depression for female and male adolescents and adults in Colombia before and during the COVID-19 pandemic. It estimated the potential increase of the prevalence in each group as a result of the COVID-19 pandemic in 2020. We used the Individual Registry of Health Services Delivery data from 2015-2021 to estimate the observed prevalence of anxiety and depression in Colombia for female and male adults. In addition, using the National Mental Health Survey 2015, we simulated the prevalence of anxiety and depression for adolescents (12 to 17 years) and adults (18 or older) in 2015 and using a static Monte Carlo simulation process we estimated the expected prevalence of depression and anxiety for each group from 2016 to 2021. The results of the analysis using revealed an important increase in the observed prevalence of depression and anxiety for adults and adolescents and men and women between 2015 and February 2020. When we simulated different scenarios using as a base line the National Mental Health Survey and estimated the prevalence of depression and anxiety for female and male adults and adolescents, we found that the prevalence of depression and anxiety has had an important increase in the last five years for all groups and had an important increase during 2020. This increase was greater for women compared to men, and adolescents than adults. Our results show the number of people who need potential attention from the health system in Colombia and highlight the importance to think about how to avoid and detect potential cases of anxiety and depression especially in female adolescents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".