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Related Experiment Video

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A Cross-Domain Model for Growth in Adolescent Alcohol Expectancies.

A G Sayer, J B Willett

    Multivariate Behavioral Research
    |January 13, 2016
    PubMed
    Summary

    This study integrates individual growth modeling and covariance structure analysis to examine changes in adolescent alcohol expectancies. Findings reveal gender differences in the relationship between positive and negative expectancies during development.

    Area of Science:

    • Psychology
    • Statistics
    • Developmental Science

    Background:

    • Individual growth modeling and covariance structure analysis are powerful statistical tools.
    • Integrating these methods offers enhanced flexibility for studying individual differences in change over time.

    Purpose of the Study:

    • To demonstrate the integration of individual growth modeling and covariance structure analysis.
    • To investigate inter-individual differences in simultaneous changes in positive and negative alcohol expectancies during adolescence.
    • To examine gender differences in these developmental trajectories.

    Main Methods:

    • Utilized longitudinal data from a school-based alcohol prevention trial.
    • Employed a piecewise growth model for positive expectancies and a straight-line growth model for negative expectancies.

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  • Applied multi-sample covariance structure analysis to assess inter-relationships between changes in expectancies.

    • Main Results:

    • Individual changes in positive and negative alcohol expectancies over time were analyzed.
    • The study identified significant inter-relationships between changes in positive and negative expectancies.
    • Gender differences were observed in the pattern of these inter-relationships.

    Conclusions:

    • The integrated approach provides a robust framework for analyzing complex developmental changes.
    • Understanding the interplay between positive and negative alcohol expectancies is crucial for adolescent development.
    • The findings highlight the importance of considering gender in prevention and intervention strategies.