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The Utility of Outcome Expectancies in the Prediction of Adolescent Gambling Behaviour

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About the Course:

The Gambling Expectancy Questionnaire (GEQ) suggests that adolescents hold a variety of positive and negative outcome expectancies related to gambling. Significant age, gender, and gambling group differences were identified on the scales of the GEQ in this study. The results provide insightful information suggesting that non-gamblers, social gamblers, at-risk gamblers, and probable pathological gamblers (PPGs) differ in the strength of their expectancies of both the positive and negative outcomes of gambling behavior. These findings were interpreted in terms of their implications for prevention, treatment, and future research.

This course is based on the reading-based online article, The Utility of Outcome Expectancies in the Prediction of Adolescent Gambling Behaviour created by Rina Gupta, Meredith A. M. Gillespie, and Jeffrey L. Derevensky


Journal of Gambling Issues

Publication Date:

Issue 19, January 2007

Course Material Authors

Course Material Authors authored the material only, and were not involved in creating this CE course. They are identified here for your own evaluation of the relevancy of the material this course is based on.

Rina Gupta
Rina Gupta, Ph.D., is a child psychologist and an assistant professor (part-time) in the School/Applied Child Psychology program at McGill University, Montreal, Quebec, Canada. She is on the editorial board of the Journal of Gambling Studies and is co-director of the McGill University Youth Gambling Research & Treatment Clinic and the International Centre for Youth Gambling Problems and High-Risk Behaviors. Her research and clinical work has been focused on understanding, preventing, and treating gambling problems in youth. Dr. Gupta has provided expert testimony before a number of government committees and national and international commissions and was the recipient of the Young Scientist Award by the National Center for Responsible Gaming.
Meredith A. M. Gillespie
Meredith Gillespie, M.A., is currently a doctoral student at McGill University's International Centre for Youth Gambling Problems and High-Risk Behaviors, Montreal, Quebec, Canada. She has received several master's and doctoral fellowships and has coauthored several papers and chapters concerning youth gambling problems.
Jeffrey L. Derevensky
Jeffrey L. Derevensky, Ph.D., is a professor of School/Applied Child Psychology, Department of Educational and Counseling Psychology, McGill University, and associate professor, Department of Psychiatry, McGill University, Montreal, Quebec, Canada. He is co-director of the McGill University Youth Gambling Research & Treatment Clinic and the International Centre for Youth Gambling Problems and High-Risk Behaviors. He is a child psychologist who has published widely in the field of youth gambling and is on the editorial board of several journals.

Course Creator

Dan Rebek, Ph.D.

Recommended For:

This course is recommended for health care professionals, especially addiction counselors, psychologists, mental health counselors, social workers, and nurses who seek knowledge about how outcome expectancies may predict adolescent gambling behavior. It is appropriate for all levels of participants' knowledge.

Course Objectives:

After taking this course, you should be able to:

  1. Describe how social cognitive models emphasize the subjective cognition implicated in behavior choice and discuss prior research involving expectancies and addictive behavior.
  2. Explain the method of the published study including participants, measures, and procedure.
  3. Identify study results including data analyses, prevalence findings, and differences between gender and age groups.
  4. Discuss study implications on the issues of outcome expectancies and gambling severity, the utility of outcome expectancies in the prediction of problem gambling, and implications for prevention and treatment.

Exam Questions

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Course Number 101553
  • 2 CE credit hours
  • NBCC: 1.25 CE credit hour

  • Reading-Based Online
Exam Fee $11.94
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