A longitudinal approach to understanding risk factors for problem alcohol use during the COVID‐19 pandemic
Bibliographic record
Abstract
BACKGROUND: We conducted a longitudinal study to examine person-centered heterogeneity in problem drinking risk during the 2019 Coronavirus disease (COVID-19) pandemic. We aimed to differentiate high- from low-risk subgroups of drinkers during the pandemic, to report on the longitudinal follow-up of the baseline sample reported in Wardell et al. (Alcohol Clin Exp Res, 44, 2020, 2073), and to examine how subgroups of drinkers differed on coping-related and pre-pandemic alcohol vulnerability factors. METHODS: Canadian alcohol users (N = 364) were recruited for the study. Participants completed surveys at four waves (spaced 3 months apart), with the first being 7 to 8 weeks after the COVID-19 state of emergency began in Canada. The data were analyzed using a parallel process latent growth class analysis followed by general linear mixed models analysis. RESULTS: We found evidence for three latent classes: individuals who increased drinking (class 1; n = 23), low-risk drinkers (class 2; n = 311), and individuals who decreased drinking (class 3; n = 30). Participants who increased (vs. those who decreased) problem drinking during the pandemic struggled with increasing levels of social disconnection and were also increasingly more likely to report drinking to cope with these issues. Those in the increasing class (relative to low-risk drinkers) reported increasing levels of depression during the study. Relative to low-risk drinkers, participants in the increasing class had higher pre-pandemic AUDIT scores, greater frequency of solitary drinking, and higher alcohol demand. Interestingly, participants in the decreasing class had the highest pre-pandemic AUDIT scores. CONCLUSIONS: We examined longitudinal data to identify subgroups of drinkers during the pandemic and to identify factors that may have contributed to increased problem drinking. Findings suggest that while most of the sample did not change their alcohol use, a small portion of individuals escalated use, while a small portion decreased their drinking. Identifying the vulnerability factors associated with increased drinking could aid in the development of preventative strategies and intervention approaches.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".