Ashamed and Alone—Risk Factors for Alcohol Craving Among Depressed Emerging Adults
Bibliographic record
Abstract
AIMS: Comorbid alcohol use and depression have the highest prevalence among emerging adults and are associated with a number of consequences. Self-medication theory posits individuals with depression use alcohol to cope with their negative emotions. Preliminary work has investigated the social context of depression-related drinking and found that solitary drinking is a risky, atypical behaviour in emerging adulthood that is associated with alcohol misuse. However, it is unknown about what is unfolding in the moment that is driving depression-related drinking in solitary contexts. Accordingly, we used an experimental study to examine if shame mediated the association between depression and in-lab alcohol craving. METHODS: Emerging adults (N = 80) completed a shame induction followed by an alcohol cue exposure in either a solitary or social condition. We used moderated mediation to test hypotheses. RESULTS: Consistent with hypotheses, conditional indirect effects supported the mediation of depression and alcohol craving through shame among those in the solitary condition, but not in the social condition. There was no support for guilt as a mediator. CONCLUSION: Our study demonstrates that shame is a specific emotional experience that contributes to solitary drinking among depressed emerging adults. It is important to use these results to inform interventions that directly target solitary contexts and shame.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".