Progressive Elaboration and Cross-Validation of a Latent Class Typology of Adolescent Alcohol Involvement in a National Sample

Abstract

ABSTRACT. Objective:Most studies of adolescent drinking focus on single alcohol use behaviors (e.g., high-volume drinking, drunkenness) and ignore the patterning of adolescents' involvement across multiple alcohol behaviors. The present latent class analyses (LCAs) examined a procedure for empirically determining multiple cut points on the alcohol use behaviors in order to establish a typology of adolescent alcohol involvement. Method: LCA was carried out on six alcohol use behavior indicators collected from 6,504 7th through 12th graders who participated in Wave I of the National Longitudinal Study of Adolescent Health (AddHealth). To move beyond dichotomous indicators, a "progressive elaboration" strategy was used, starting with six dichotomous indicators and then evaluating a series of models testing additional cut points on the ordinal indicators at progressively higher points for one indicator at a time. Analyses were performed on one random half-sample, and confirmatory LCAs were performed on the second random half-sample and in the Wave II data. Results: The final model consisted of four latent classes (never or non-current drinkers, low-intake drinkers, non-problem drinkers, and problem drinkers). Confirmatory LCAs in the second random half-sample from Wave I and in Wave II support this four-class solution. The means on the four latent classes were also generally ordered on an array of measures reflecting psychosocial risk for problem behavior. Conclusions: These analyses suggest that there may be four different classes or types of alcohol involvement among adolescents, and, more importantly, they illustrate the utility of the progressive elaboration strategy for moving beyond dichotomous indicators in latent class models. (J. Stud. Alcohol Drugs, 76, 419-429, 2015)

Identifying typical trajectories in longitudinal data: modelling strategies and interpretations

“…As described, these criteria are applied sequentially on models with increasing numbers of classes using the same dataset. It has been suggested that cross-validation should be used instead [26]. This would involve fitting the model with a given number of classes on a subset of the data, followed by using the selected model on the remaining data and assessing its goodness of fit.…”

One explanation to rule them all? Identifying sub‐groups of non‐drinking Swedish ninth graders

“…While researchers have assessed the collectivity of declining drinking trends in a growing number of studies, little attention has been paid to disaggregate adolescent ‘non‐drinkers’ into more nuanced sub‐groups. Researchers have repeatedly identified diverse classes of drinkers, based on a range of factors including motivations, level of drinking and parenting factors , but non‐drinkers have generally been treated as a homogenous group. It is likely that there are as many different types of non‐drinkers as there are drinkers, especially given the recent trend towards non‐drinking as the majority behaviour among adolescents.…”

Stressful life events influence transitions among latent classes of alcohol use.

“…Latent class analysis (LCA) is an example of a person-centered approach that classifies qualitatively different groups of individuals by identifying latent homogeneous subgroups (i.e., classes) of individuals who have a high likelihood of providing similar response patterns across a set of items and determines each individual’s probability of being a member in each of the classes (Auerbach & Collins, 2006; McCutcheon, 1987). LCA has been used to derive typologies of alcohol users in previous work (Auerbach & Collins, 2006; Beseler, Taylor, Kraemer, & Leeman, 2012; Connell, Gilreath, & Hansen, 2009; Donovan & Chung, 2015; Hoyland, Rowatt, & Latendresse, 2017; Kuvaas, Dvorak, Pearson, Lamis, & Sargent, 2014; Rist, Glöckner-Rist, & Demmel, 2009; Smith & Shevlin, 2008). Although these studies have found anywhere from three to six classes of alcohol use, most have found three or four (Auerbach & Collins, 2006; Hoyland et al, 2017; Kuvaas et al, 2014).…”

“…Although these studies have found anywhere from three to six classes of alcohol use, most have found three or four (Auerbach & Collins, 2006; Hoyland et al, 2017; Kuvaas et al, 2014). Notably, Donovan and Chung (2015) deciphered empirically meaningful item-response thresholds for alcohol use indicators to be used in LCA and subsequently identified four prototypical patterns of alcohol use in a nationally representative sample of adolescents, consisting of abstainers, low-intake drinkers, nonproblem drinkers, and problem drinkers . These same four patterns were identified in the same sample 1 and 13 years later, indicating a need to address the extent to which individuals continue to demonstrate the same pattern across time (Donovan & Chung, 2015; Hoyland et al, 2017).…”