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Testing a motivational model of delivery modality and incentives on participation in a brief alcohol intervention.

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Lindsey M. Rodriguez

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Objectives: The current research evaluated delivery modality and incentive as factors affecting recruitment into a personalized normative feedback (PNF) alcohol intervention for heavy drinking college students. We also evaluated whether these factors were differentially associated with participation based on relevance of the intervention (via participants' drinking levels). Method: College students aged 18–26 who endorsed at least one heavy drinking episode and one alcohol-related consequence in the past month (N = 2059; 59.1% female) were invited to participate in a PNF intervention study. In this 2 × 2 design, participants were randomized to: (1) complete the computer-based baseline survey and intervention procedure remotely (i.e., at a time and location of their convenience) or in person in the laboratory, and (2) receive an incentive ($30) for their participation in the baseline/intervention procedure or no incentive. Results: Consistent with hypotheses, students were more likely to participate when participation occurred remotely (OR = 1.87, p < .001) and when an incentive (OR = 1.64, p = .007) was provided. Moderation analyses suggested that incentives were only associated with higher recruitment rates among remote participants (OR = 2.10, p < .001), consistent with cognitive evaluation theory. Moreover, heavier drinkers were more likely to participate if doing so remotely, whereas drinking was not associated with likelihood of participation among in-person participants. Discussion: The present results showed a strong selection bias for participation in a web-based intervention study relative to one in which participants were required to participate in person. Results have implications for researchers recruiting college students for alcohol interventions.


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Pergamon Press

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Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.