Subjective Well-being, Mental Health and Concerns During the COVID-19 Pandemic: Evidence From the Global South
Bibliographic record
Abstract
COVID-19 pandemic is harming many social and economic spheres beyond physical health. The subjective well-being of the population (positive emotions and life satisfaction) and the prevalence of stressors affecting good mental health like worry, depression, and anxiety are increasing worldwide. This analysis presents evidence of subjective well-being and mental health in Colombia, South America, during the current crisis. The data for this analysis comes from an online survey released after one month of quarantine. In total, 941 adults participated in the study. Results show that women are more affected by their well-being and experience more often worry, depression, and anxiety than males. In particular, younger women and from the lower socioeconomic strata. Respondents identify three primary concerns because of the pandemic: i) financial consequences, ii) health (personal and loved one's health), and iii) productivity. Respondents are, on average, more concerned for the health of loved ones than their health. 49% of study participants report having an income reduction as a consequence of the pandemic, but women in all subgroups analyzed are more affected than males. In terms of productivity –working remotely-, educated people, and from 50+ age range, feels more productive working from home. Evidence from this analysis contributes to the broader research of the consequences of COVID-19 on the well-being of the population. Evidence comes from a country in the global South with high population ratings of subjective well-being, happiness, and life satisfaction before the pandemic. 
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".