From Drinking Group Norms to Individual Drinking Consequences: A Moderated Mediation Model Examining the Role of Members’ Status, Identification with the Group and with Emerging Adulthood
Bibliographic record
Abstract
BACKGROUND: Emerging adults consume alcohol most often with their peer drinking groups. Yet, little is known about the role of drinking group norms on individual members' drinking consequences, nor about the mechanisms that underlie this association. OBJECTIVES: We examined the indirect relationship between drinking group descriptive norms (perceived frequency of group heavy episodic drinking; HED) and individual drinking consequences via individual HED. We also examined key moderators, including the extent to which individuals occupied high status positions within their drinking groups, the strength of their identification with the group, and the degree to which they identified with emerging adulthood, a developmental period associated with heightened alcohol consumption. METHODS: Participants were 280 and 340 (replication study) emerging adults (18-29 years) who were recruited via an online crowdsourcing site to complete a survey. RESULTS: Across studies, higher status was associated with more individual HED and drinking consequences. Further, group identification and identification with emerging adulthood strengthened the relation between group and individual HED. Finally, the indirect relation between group HED and individual drinking consequences was significant and stronger for individuals who identified more with their drinking groups and with emerging adulthood. Conclusions/Importance: Findings contribute to a more nuanced understanding of the impact of descriptive peer norms on heavy drinking and related consequences in emerging adulthood and help identify drinking group members most at risk for internalizing descriptive group norms for HED. Key implications for prevention and intervention programming are discussed.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".