Patterns and correlates of binge drinking trajectories from early adolescence to young adulthood.

Joan S. Tucker, Maria Orlando, Phyllis L. Ellickson·2003·Health Psychology

Abstract

Latent growth mixture modeling was used to identify developmental trajectories (described in terms of demographics, exposure and resistance to a pro-drug environment, and deviant behavior) of binge drinking among 5,694 individuals who completed 6 surveys from ages 13 to 23 years: nonbingers (32%); moderate stables (37%), who had consistently low levels of bingeing; steady increasers (16%), who increased from the lowest to highest level of bingeing; adolescent bingers (9%), whose early rise in bingeing was followed by a decrease to a moderate level; and early highs (6%), who decreased from the highest level of bingeing to a moderate level. Results show considerable diversity in binge drinking patterns and the correlates of bingeing across trajectory classes.

Cites (49)

  1. Alternative Ways of Assessing Model Fit
    Browne, Michael W., Cudeck, Robert · 1992 · Sociological Methods & Research
  2. Comparative fit indexes in structural models.
    Bentler, P. M. · 1990 · Psychological Bulletin
  3. Significance tests and goodness of fit in the analysis of covariance structures.
    P. M. Bentler, Douglas G. Bonett · 1980 · Psychological Bulletin
  4. Testing Structural Equation Models.
    Clogg, Clifford C., Bollen, Kenneth A., Long, J. Scott · 1995 · Social Forces
  5. Monitoring the future: National Results on Adolescent Drug Use: Overview of Key Findings, 2008: (560352009-001)
    Johnston, Lloyd D., O'Malley, Patrick M., Bachman, Jerald G., Schulenberg, John E. · 2009 · PsycEXTRA Dataset
  6. Alternative ways of assessing model fit
    Mairéad Browne · 1993 · Medical Entomology and Zoology
  7. Statistically based tests for the number of common factors
    James H. Steiger · 1980 · Medical Entomology and Zoology
  8. Analyzing developmental trajectories: A semiparametric, group-based approach.
    Nagin, Daniel S. · 1999 · Psychological Methods
  9. Comparative Fit Indices in Structural Models
    Peter M. Bentler · 1990 · eScholarship (California Digital Library)
  10. Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm
    Muthén, Bengt, Shedden, Kerby · 1999 · Biometrics

Show all 49 references

Cited by (14)

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    Kuntsche, Emmanuel, Knibbe, Ronald, Gmel, Gerhard, Engels, Rutger · 2005 · Clinical Psychology Review
  2. Trajectories of Alcohol and Drug Use and Dependence From Adolescence to Adulthood: The Effects of Familial Alcoholism and Personality.
    Chassin, Laurie, Flora, David B., King, Kevin M. · 2004 · Journal of Abnormal Psychology
  3. Rewarding, stimulant, and sedative alcohol responses and relationship to future binge drinking
    King, Andrea C., de Wit, Harriet, McNamara, Patrick J., Cao, Dingcai · 2011 · Archives of General Psychiatry
  4. Adult outcomes of binge drinking in adolescence: findings from a UK national birth cohort
    Viner, R M, Taylor, B · 2007 · Journal of Epidemiology and Community Health
  5. Decision making and binge drinking: a longitudinal study
    Goudriaan, Anna E., Grekin, Emily R., Sher, Kenneth J. · 2007 · Alcoholism: Clinical and Experimental Research

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How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Patterns and correlates of binge drinking trajectories from early adolescence to young adulthood. https://app.cochat.ai/papers/10.1037//0278-6133.22.1.79
The paper
Tucker, J. S., Orlando, M., & Ellickson, P. L. (2003). Patterns and correlates of binge drinking trajectories from early adolescence to young adulthood. Health Psychology. https://doi.org/10.1037//0278-6133.22.1.79

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