Gambling and the Reasoned Action Model: Predicting Past Behavior, Intentions, and Future Behavior

Ethan Dahl, Michael J. Tagler, Zachary P. Hohman

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Gambling is a serious concern for society because it is highly addictive and is associated with a myriad of negative outcomes. The current study applied the Reasoned Action Model (RAM) to understand and predict gambling intentions and behavior. Although prior studies have taken a reasoned action approach to understand gambling, no prior study has fully applied the RAM or used the RAM to predict future gambling. Across two studies the RAM was used to predict intentions to gamble, past gambling behavior, and future gambling behavior. In study 1 the model significantly predicted intentions and past behavior in both a college student and Amazon Mechanical Turk sample. In study 2 the model predicted future gambling behavior, measured 2 weeks after initial measurement of the RAM constructs. This study stands as the first to show the utility of the RAM in predicting future gambling behavior. Across both studies, attitudes and perceived normative pressure were the strongest predictors of intentions to gamble. These findings provide increased understanding of gambling and inform the development of gambling interventions based on the RAM.

Original languageEnglish
Pages (from-to)101-118
Number of pages18
JournalJournal of Gambling Studies
Issue number1
StatePublished - Mar 1 2018


  • Behavioral intention
  • Gambling
  • Perceived behavioral control
  • Predicting behavior
  • Reasoned Action Model


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