Impact of the COVID-19 pandemic on substance use among adults without children, parents, and adolescents
Bibliographic record
Abstract
Impact of the COVID-19 pandemic on alcohol and illicit substance use among adults without children, parents, and adolescents was investigated through two studies with five samples from independent ongoing U.S. longitudinal studies. In Study 1, 931 adults without children, parents, and adolescents were surveyed about the pandemic's impact on personal behavior. 19-25% of adults without children, parents, and adolescents reported an increase in alcohol or illicit substance use. In Study 2, 274 adults without children, parents, and adolescents who had been interviewed prior to the pandemic onset about alcohol and illicit substance use problems were re-interviewed after the pandemic's onset to test within-person change. The rate of alcohol or illicit substance use problems increased from pre-pandemic to post-pandemic onset from 13% to 36% among the three groups. Increase in alcohol and illicit substance use problems was positively correlated with increased depression/anxiety and household disruption, suggesting possible mechanisms for increases in substance problems. Findings in both studies held across low- and middle-income families. Findings suggest the need for communitywide policies to increase resources for alcohol and illicit substance use screening and intervention, especially for adolescents.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Longitudinal study of pandemic impacts on substance use among adults, parents and adolescents.
It studies pandemic-related substance use, not research itself.
Public health study of COVID-19 impacts on substance use across family roles.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".