Dimensions and Categories Underlying Thinking About College Student Types

Patterns of Alcohol, Tobacco, and Substance Use Among Young Adult Peer Crowds

INTRODUCTION

The association between peer crowd identification and substance use is well documented among adolescents, but less is known about substance use among young adult peer crowds.

METHODS

This study leverages data from the Truth Initiative Young Adult Cohort Study (Wave 8, June-July 2015), a nationally representative cohort sample of young adults aged 18-34 years. The current cross-sectional analyses (conducted in 2018) focused on 1,341 individuals aged 18-24 years in this sample. Participants reported their peer crowd identification and current use of alcohol, marijuana, other drugs, and tobacco (cigarettes, little cigars/cigarillos, e-cigarettes, hookah, smokeless tobacco). Adjusted logistic regression models assessed associations between peer crowd identification and substance use.

RESULTS

In general, young adults who identified as homebody, young professional, or religious had lower odds of substance use than their counterparts. Young adults who identified as social/partier were more likely to be current users of alcohol, marijuana, any tobacco, cigarettes, and e-cigarettes than those who did not identify as social/partier. Those who identified as alternative were more likely to be current users of marijuana and other drugs than those not identified as alternative. Those who identified as country were more likely than those not identified as country to be current users of cigarettes and smokeless tobacco. Those who identified as hip hop were more likely to be current users of marijuana and e-cigarettes.

CONCLUSIONS

Peer crowd identification is associated with substance use among young adults. These findings can help identify target populations for prevention and cessation interventions and inform intervention design and delivery.

Similar but not the same: a comparison of the utility of directly rated and feature-based similarity measures for generating spatial models of conceptual data

Spatial models are employed to represent conceptual data in a wide range of fields within psychological research. In order to generate spatial models, it is necessary to first obtain empirical similarity data. A number of methods are available for collecting these data, but little effort has been made to compare their relative utility. In this article, we compare directly rated and five feature-based similarity data types in regard to their ability to be adequately represented by a spatial model (representational goodness of fit), and the ability of the representations to predict three external empirical variables (predictive validity). The results indicate that the representational goodness of fit of the feature-based similarities is noticeably superior to the directly rated similarities, and that the predictions of representations derived from common feature similarity data are substantially more likely than the predictions of all of the alternative representations. It is suggested that these findings are highly relevant to researchers employing spatial models to represent conceptual data, given that direct pairwise ratings have generally been considered the "gold standard" means of obtaining empirical similarities.