Citation

Kong G, Tsai J, Krishnan-Sarin S, Cavallo DA, Hoff RA, Steinberg MA, Rugle L, Potenza MN. J. Addict. Med. 2014; 8(6): 421-430.

Affiliation

From the Department of Psychiatry (GK, JT, SK-S, DAC, RAH, and MNP), Department of Epidemiology (RAH), and Child Study Center (MNP), Yale University School of Medicine, New Haven, CT; Veterans Affairs New England Mental Illness, Research, Education, and Clinical Center (JT), West Haven, CT; Connecticut Council on Problem Gambling (RAH and MAS), Guilford, CT; and Problem Gambling Services (LR), Middletown, CT.

Copyright

(Copyright © 2014, American Society of Addiction Medicine, Publisher Lippincott Williams and Wilkins)

DOI

10.1097/ADM.0000000000000074

PMID

25275877

Abstract

OBJECTIVES:: To identify subtypes of adolescent gamblers based on the 10 Diagnostic and Statistical Manual of Mental Disorders, fourth edition criteria for pathological gambling and the 9 Diagnostic and Statistical Manual of Mental Disorders, fifth edition criteria for gambling disorder and to examine associations between identified subtypes with gambling, other risk behaviors, and health/functioning characteristics.

METHODS:: Using cross-sectional survey data from 10 high schools in Connecticut (N = 3901), we conducted latent class analysis to classify adolescents who reported past-year gambling into gambling groups on the basis of items from the Massachusetts Gambling Screen. Adolescents also completed questions assessing demographic information, substance use (cigarette, marijuana, alcohol, and other drugs), gambling behaviors (relating to gambling formats, locations, motivations, and urges), and health/functioning characteristics (eg, extracurricular activities, mood, aggression, and body mass index).

RESULTS:: The optimal solution consisted of 4 classes that we termed low-risk gambling (86.4%), at-risk chasing gambling (7.6%), at-risk negative consequences gambling (3.7%), and problem gambling (PrG) (2.3%). At-risk and PrG classes were associated with greater negative functioning and more gambling behaviors. Different patterns of associations between at-risk and PrG classes were also identified.

CONCLUSIONS:: Adolescent gambling classifies into 4 classes, which are differentially associated with demographic, gambling patterns, risk behaviors, and health/functioning characteristics. Early identification and interventions for adolescent gamblers should be sensitive to the heterogeneity of gambling subtypes.

Language: en