Background and aims: Alcohol use disorder (AUD), since the release of DSM-V, is conceptualized and studied as a unidimensional construct. However, previous research has identified clusters of AUD symptoms related to excessive consumption/tolerance, loss of control/social dysfunction and withdrawal/craving that have shown differential genetic risks, personality associations and predictive ability. Although past 'variable-centered' (e.g. factor-analytic) studies have demonstrated the importance of these clusters, the current study aimed to examine how these clusters commonly manifest using a 'person-centered' approach (e.g. latent class).
Design: Cross-sectional in-person assessment.
Setting: Indiana, USA.
Participants: A convenience sample of 1390 young adults (mean age = 21.43, SD = 2.47) recruited for an over-representation of alcohol problems (65% with AUD).
Measurements: Latent class analysis (LCA) was conducted on 23 criteria from the Semi-Structured Interview on the Genetics of Alcoholism (SSAGA) that align with DSM-V AUD symptoms. Identified latent classes were characterized using multinomial regressions to examine the association of class and measures of alcohol use, other externalizing psychopathology, internalizing problems and personality.
Findings: LCA results identified a 'Low Problems' class (34% of sample), a 'Heavy Consumption' class (26%) characterized by high endorsement probabilities of essentially only consumption/tolerance symptoms, a 'Consumption and Loss of Control' class (31%) characterized by endorsing consumption/tolerance and loss of control/social dysfunction symptoms, and finally a 'Consumption, Loss of Control and Withdrawal' class (9%) characterized by high endorsement probabilities of all symptom clusters. Multinomial regression results indicated an increasing spectrum of severity in terms of psychological impairment.
Conclusions: AUD appears to manifest as different clusters of symptoms at different severity levels.
Keywords: alcohol use disorder; classification; diagnosis; etiology; heterogeneity; latent class analysis.
© 2021 Society for the Study of Addiction.