Mental Health Impact of the COVID-19 Pandemic on Mexican Population: A Systematic Review
Bibliographic record
Abstract
The COVID-19 pandemic has had an impact on mental health in the general population, but no systematic synthesis of evidence of this effect has been undertaken for the Mexican population. Relevant studies were identified through the systematic search in five databases until December, 2021. The selection of studies and the evaluation of their methodological quality were performed in pairs. The Newcastle-Ottawa Scale (NOS) was used for study quality appraisal. The protocol of this systematic review was registered with PROSPERO (protocol ID: CRD42021278868). This review included 15 studies, which ranged from 252 to 9361 participants, with a total of 26,799 participants. The findings show that COVID-19 has an impact on the Mexican population's mental health and is particularly associated with anxiety, depression, stress and distress. Females and younger age are risk factors for development mental health symptoms. Mitigating the negative effects of COVID-19 on mental health should be a public health priority in Mexico.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".