Mental health and other factors associated with the perception of the improvement of the environment after the first months of the pandemic in Latin America
Bibliographic record
Abstract
Abstract Introduction: Due to the restrictions of mobility during the first months of the pandemic, an improvement in the environment was observed, but this has not been estimated from the perspective of mental health. Aim: To determine whether mental health and other factors were associated with the perception of the improvement of the environment after the first months of the pandemic in Latin America. Methodology: Analytical and multicenter cross-sectional study. Four questions were asked about their perception of change in the environment after a quarter of the pandemic, Alpha of Cronbach: 0,96). Results: Descriptive and analytical statistics were obtained. In the multivariate analysis, an association of a greater perception of environmental change was found according to having moderate or severe stress (RPa: 1,16; IC95%: 1,05-1,28; valor p=0,003) and live in Bolivia (RPa: 1,24; IC95%: 1,10-1,40; valor p<0,001); In contrast, there was less perception of change among men. (RPa: 0,84; IC95%: 0,78-0,90; valor p<0,001), among the youngest (RPa: 0,995; IC95%: 0,992-0,998; valor p=0,003), among those living in Mexico (RPa: 0,80; IC95%: 0,69-0,93; valor p=0,003) and other Latin American countries (RPa: 0,64; IC95%: 0,43-0,98; valor p=0,039), adjusted for level of education and having anxiety. Discussion: The environment changed due to the lack of human activity, but this perception was also associated with mental health status. Conclusion: A greater perception of environmental change was associated with having moderate/severe stress and living in Bolivia; there was less perception of change among men, in younger men, depending on living in Mexico or in other Latin American countries.
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 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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".