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Personalized normative feedback for heavy drinking: An application of deviance regulation theory.

SelectedWorks Author Profiles:

Lindsey M. Rodriguez

Document Type

Article

Publication Date

2018

ISSN

1873-622X

Abstract

Deviance Regulation Theory (DRT) proposes that individuals regulate their behavior to be in line with the behaviors of others. Specifically, individuals desire to stand out in positive way and not stand out in a negative way. DRT has been successfully applied to encourage other health behaviors and offers a unique method to utilize both injunctive norms in combination with descriptive norms in brief alcohol interventions. This randomized controlled trial evaluated a computer-delivered, norms-based personalized feedback intervention which systematically varied the focus on whether specific drinking behaviors were described as common or uncommon (a descriptive norm), whether the drinking behaviors were healthy versus unhealthy, and whether the drinking behaviors were positively or negatively framed (an injunctive norm). Nine-hundred and fifty-nine college drinkers completed baseline, three-month, and six-month follow-up assessments. Results indicated messages focusing on unhealthy drinking behaviors, particularly when described as uncommon, were most effective in reducing drinking and alcohol-related problems over time. This research utilizes deviance regulation theory as a way of improving personalized normative feedback by elucidating how to construct messages for brief interventions based on descriptive characteristics associated with specific target drinking behaviors in combination with perceptions of prevalence and acceptability of such drinking behaviors (an injunctive norm).

Comments

Citation only. Full-text article is available through licensed access provided by the publisher. Members of the USF System may access the full-text of the article through the authenticated link provided.

Publisher

Elsevier

Creative Commons License

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

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