Motivating Recruitment and Efficacy in Normative Feedback Interventions
Condition: Heavy Drinking
Study type: Interventional

Summary: 
      Excessive alcohol consumption among college students continues to be a serious public health
      concern associated with a wide range of negative consequences. Brief computer-based social
      norms interventions, including personalized normative feedback (PNF), have shown consistent
      effects in reducing problematic drinking in this population, and there is some evidence that
      in-lab computer-delivered interventions may be more effective than remote interventions. Most
      studies have been conducted using generous incentives which may reduce the feasibility of
      dissemination on a larger scale and may undermine trial efficacy. In accordance with NIAAA
      aims, this research aims to (a) investigate delivery modality (i.e., in lab versus remotely)
      and incentives as important factors affecting the efficacy of PNF interventions and (b)
      develop intervention strategies that facilitate wider dissemination of inexpensive
      empirically-supported brief interventions for college students, thereby reducing problem
      drinking during a high-risk time period.
    

Detailed description: 
      The current application evaluates motivational factors associated with recruitment into and
      efficacy of brief computer-delivered interventions for heavy drinking college students.
      College students are at increased risk for alcohol misuse compared to other adults, and
      development of efficacious intervention approaches is an urgent priority for NIAAA. Over the
      past several years empirical evidence has demonstrated support for computer-based
      personalized normative feedback (PNF) interventions which correct normative misperceptions of
      drinking and thereby reduce drinking behavior. Two specific questions which have remained
      largely unaddressed include whether the effectiveness of computer-based interventions depends
      on the location in which they are completed, and what is the optimal incentive structure to
      balance recruitment with motivational biases in intervention trials. A preliminary comparison
      of findings across several studies suggests that remote PNF interventions may be less
      effective than in-lab PNF interventions. However, the evidence is not conclusive because no
      study provides a direct comparison between delivery methods based on random assignment within
      the same study. This R21 recruited 498 heavy drinking college students and randomly assigned
      them to a 2 × 2 × 2 repeated measures design. Participants were randomly assigned to in-lab
      PNF, remote PNF, in-lab attention control, or remote attention control. Participants were
      also randomly assigned to receive no incentive ($0) or an incentive ($30) for participation.
      Assessments included baseline, postintervention, 3-month, and 6-month follow-ups. College
      students' motivational orientations, incentives, and typical drinking are expected to
      moderate differences between delivery methods. We expect that students who receive incentives
      for participating in intervention studies will be more likely to participate, but less likely
      to reduce drinking because they will be more likely to attribute their participation to
      extrinsic motivation. Further, students who receive computer-based PNF in the laboratory for
      no incentive are expected to exhibit the largest reductions in drinking. In contrast,
      students administered attention-control feedback remotely for an incentive ($30) are expected
      to exhibit the smallest reductions in drinking. Perceived value of intervention, retention of
      intervention content, and attribution for participation are expected to mediate incentive
      effects and differential efficacy of in-lab versus remote delivery. This research is expected
      to yield theoretical and practical improvements to feedback-based intervention strategies
      with potential to reduce drinking and related negative consequences with a stronger
      theoretical basis and at lower cost than have been previously available.
    

Intervention name(s): Personalized normative feedback
Intervention type(s): Behavioral
Intervention description(s): Information presenting perceived and actual drinking norms.
Allocation: Randomized
Intervention model: Factorial Assignment
Intervention model description: Heavy drinking college students (N=498) participated in a 2 (in-person vs. remote delivery) × 2 (compensation vs. no compensation) × 2 (PNF vs. control) design with follow-up assessments occurring remotely three and six months later.
Masking: Single (Participant)
Primary purpose: Treatment