The Mediating Effects of Protective Behavioral Strategies on the Relationship between Addiction-Prone Personality Traits and Alcohol-Related Problems among Emerging Adults
Bibliographic record
Abstract
Alcohol consumption and associated harms are an issue among emerging adults, and protective behavioral strategies (PBS) are actions with potential to minimize these harms. We conducted two studies aimed at determining whether the associations of at-risk personality traits (sensation-seeking [SS], impulsivity [IMP], hopelessness [HOP], and anxiety-sensitivity [AS]) with increased problematic alcohol use could be explained through these variables’ associations with decreased PBS use. We tested two mediation models in which the relationship between at-risk personality traits and increased problematic alcohol use outcomes (Study 1: Alcohol volume; Study 2: Heavy episodic drinking and alcohol-related harms) was partially mediated through decreased PBS use. Two samples of college students participated (N1 = 922, Mage1 = 20.11, 70.3% female; N2 = 1625, Mage2 = 18.78, 70.3% female). Results partially supported our hypotheses, providing new data on a mechanism that helps to explain the relationships between certain at-risk personality traits and problematic alcohol use, as these personalities are less likely to use PBS. In contrast, results showed that AS was positively related to alcohol-related harms and positively related to PBS, with the mediational path through PBS use being protective against problematic alcohol use. This pattern suggests that there are other factors/mediators working against the protective PBS pathway such that, overall, AS still presents risks for alcohol-related harms.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".