Drug use as a coping style to social isolation by COVID-19 pandemic and its effects on the adherence to safety guidelines in Mexico
Bibliographic record
Abstract
Introduction: in response to the pandemic originated by COVID-19, governments placed in practice a series of safety guidelines recommended by the World Health Organization (WHO). In Mexico, one of the decisive actions to prevent the disease's spread was social isolation or lockdown. These rigorous proceedings could increase stress experience or other mental health disorders. One of the coping mechanisms used to avoid stress includes drug use. Objective: the study's goal was to evaluate the relationship between drug use (alcohol, tobacco, and cannabis) and adherence to safety guidelines. Method: the association between the variables was assessed with a series of surveys indicating adherence to safety guidelines and drug use, 475 Mexican participants (56.5% females and 43.4% males) completed the study. Results: the results suggest that most participants had low drug abuse levels before and during social isolation. There was a significant decrease in tobacco, alcohol, and cannabis use in both females and males. Upon analyzing guideline adherence, low alcohol use correlated with the safety behavior scale, while tobacco and cannabis correlated with the preventive behavior scale. Discussion: the current Mexican sample had not used drugs to cope during social isolation.
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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 | 0.000 | 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 | 0.001 | 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".