Predicting adolescent problem use of marijuana: Development and testing of a bayesian model

David H. Gustafson, Kris Bosworth, Catherine Treece, Yu Cherng Wu, Christina G.S. Palmer, D. Paul Moberg, Robert P. Hawkins

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


This paper reports on the development and testing of a risk assessment index for problem marijuana use designed to guide teenagers through an extensive computer-based support system intended to help them improve marijuana-related behaviors. Bayesian decision theory, used as the basis of the index development process, offers the advantage of building the index on subjective judgments of experts and does not require a large empirical data base. The index was found to predict an independent panel's ratings of teenager risk, and predict the marijuana use of 10th graders using self-reports of their profiles in the 7th grade. Implications for future risk assessment developments are discussed.

Original languageEnglish (US)
Pages (from-to)861-886
Number of pages26
JournalSubstance Use and Misuse
Issue number7
StatePublished - 1994


  • Decision theory
  • Development and testing
  • Marijuana
  • Prediction
  • Risk

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Health(social science)
  • Public Health, Environmental and Occupational Health
  • Psychiatry and Mental health


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