USF St. Petersburg campus Faculty Publications

Comorbidity of alcohol and gambling problems in emerging adults: A bifactor model conceptualization.

SelectedWorks Author Profiles:

Lindsey M. Rodriguez

Document Type

Article

Publication Date

2017

ISSN

1573-3602

Abstract

Addictive disorders, such as pathological gambling and alcohol use disorders, frequently co-occur at greater than chance levels. Substantive questions stem from this comorbidity regarding the extent to which shared variance between gambling and alcohol use reflects a psychological core of addictive tendencies, and whether this differs as a function of gender. The aims of this study were to differentiate both common and unique variance in alcohol and gambling problems in a bifactor model, examine measurement invariance of this model by gender, and identify substantive correlates of the final bifactor model. Undergraduates (N = 4475) from a large northwestern university completed an online screening questionnaire which included demographics, quantity of money lost and won when gambling, the South Oaks Gambling Screen, the AUDIT, gambling motives, drinking motives, personality, and the Brief Symptom Inventory. Results suggest that the bifactor model fit the data well in the full sample. Although the data suggest configural invariance across gender, factor loadings could not be constrained to be equal between men and women. As such, general and specific factors were examined separately by gender with a more intensive subsample of females and males (n = 264). Correlations with motivational tendencies, personality traits, and mental health symptoms indicated support for the validity of the bifactor model, as well as gender-specific patterns of association. Results suggest informative distinctions between shared and unique attributes related to problematic drinking and gambling.

Comments

Abstract only. Full-text article is available through licensed access provided by the publisher. Members of the USF System may access the full-text of the article through the authenticated link provided.

Language

en_US

Publisher

Springer

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Share

COinS