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Indicated prevention for incoming freshmen: personalized normative feedback and high-risk drinking
Melissa A Lewis1, Clayton Neighbors, Laura Oster-Aaland
1Department of Psychiatry and Behavioral Sciences, Box 354694, University of Washington, Seattle, WA 98105-6099, USA. lewisma@u.washington.edu
Personalized normative feedback (PNF) effectively reduced alcohol consumption and misperceptions of typical drinking behaviors among freshmen. This computer-based intervention, tailored to freshmen-specific and gender-specific norms, shows promise for college alcohol prevention strategies.
Area of Science:
- Public Health
- Psychology
- Higher Education
Background:
- College freshmen often exhibit high-risk drinking behaviors.
- Misperceptions of peer drinking norms contribute to excessive alcohol consumption.
- Targeted interventions are needed to address freshman alcohol use.
Purpose of the Study:
- To evaluate the efficacy of a computerized, freshmen-specific personalized normative feedback (PNF) intervention.
- To determine if gender-specific PNF is more effective than gender-neutral PNF.
- To reduce alcohol consumption and normative misperceptions among high-risk drinking freshmen.
Main Methods:
- A randomized controlled trial with 316 freshmen.
- Intervention groups received gender-specific PNF, gender-neutral PNF, or assessment only.
- Measures included perceived drinking norms and self-reported drinking behavior.
Main Results:
- Students demonstrated significant normative misperceptions regarding freshmen drinking.
- Perceptions of same-sex peers' drinking correlated positively with personal riskier drinking.
- PNF intervention groups showed reduced perceptions of typical drinking and personal consumption compared to the control group.
Conclusions:
- Computer-based, freshmen-specific PNF is an effective strategy for reducing alcohol consumption.
- Gender-specific PNF may offer a promising approach for college alcohol prevention.
- Addressing normative misperceptions is key to reducing freshman drinking behaviors.
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