Alcohol’s Effects on the Bystander Decision-Making Model: A Systematic Literature Review
Bibliographic record
Abstract
To decrease rates of sexual assault victimization, young people are encouraged to become involved when they see questionable sexual situations (i.e., be a prosocial bystander). Several factors can facilitate or inhibit intervention, including alcohol use. To inform bystander prevention programs that aim to address alcohol's impact on bystanders, the current study reviewed research focused on alcohol use and bystander decision making. In December 2022, the authors searched published studies from six major electronic databases. Empirical articles were deemed eligible if they examined alcohol and the bystander decision-making model within the context of sexual assault, were based in the United States or Canada, and not an intervention study; 32 studies were included in the final review. Across 32 studies published between 2015-2022, 12 assessed the proximal effects of alcohol on bystander constructs and the additional studies examined the distal effects of alcohol on bystander constructs. Alcohol use appeared to impede earlier steps of the bystander decision-making model; however, alcohol use was associated with impeding and facilitating bystander decision making at the latter half of the model. Overall, alcohol use appears to be negatively rather than positively associated with bystander constructs. Bystander intervention programs may want to move beyond the narrative of alcohol as a risk factor for sexual assault and discuss how alcohol impairs a bystanders' ability to recognize risk. More work is needed to ensure researchers assess alcohol consistently and with similar methods (number of drinks, subjective intoxication) to increase generalizability of findings to prevention programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".