Alcohol use commonly begins during high school, increases and peaks in the early twenties, and then decreases during young adulthood as individuals transition into adult work and social roles. The peak in alcohol use trajectories during the early twenties is particularly pronounced for college students. Although many heavy drinking college students mature out of this behavior, some develop patterns of heavy drinking that continue into adulthood and which may lead to serious health and/or developmental problems, such as alcohol use disorder. Heavy episodic drinking (HED), or women/men consuming four/five or more drinks in a row, is the most widely used indicator of heavy college drinking, and has been shown to predict an array of negative consequences across multiple domains. However, research is increasingly showing that some students drink at levels far beyond this threshold on many occasions. Recent findings have also demonstrated that drinking in specific contexts, such as when pregaming, is associated with HED and can be particularly risky. This dissertation sought to advance research on heavy college drinking by demonstrating the need for researchers to better differentiate among levels of drinking and to more fully consider the effects of HED in certain situations, such as before going out (Pregame HED) and during the daytime (Day Drinking). Data came from the University Life Study which followed first-year, first-time, full-time college students under the age of 21 at a large, land grant university (N = 736, M = 18.44 years old, SD = .43 years). Students were selected using a stratified random sampling technique that resulted in a balanced sample in regard to gender (50.8% female) and four major race/ethnicity groups (25.1% Hispanic/Latinx, 15.7% African American non-Hispanic [NH], 23.3% Asian American/Pacific Islander NH, 27.4% European American NH, and 8.5% multiracial NH). A longitudinal measurement-burst design was used in which students completed a longer web-based survey and up to 14 consecutive web-based daily surveys in each of their first seven semesters (3 years) of college.Paper 1 introduces the concept of Pregame HED, or getting drunk before going out, and tested whether students were more likely to engage in high-intensity drinking (HID; i.e., double the HED threshold) and risky behaviors and whether they experienced more negative consequences on Pregame HED days than on days they consumed a more moderate amount of drinks while pregaming (N = 4,454 drinking days nested within N = 521 students who reported drinking on at least one occasion in Semesters 4-7 when data on pregaming were available). Multilevel models nesting days within semesters within persons contrasted Pregame HED days, that is, days students got drunk before going out, with drinking days on which they consumed a more moderate amount of alcohol while pregaming. Pregame HED was reported by 41% of drinkers and on 15% of drinking days and 38% of pregaming days. Students were more likely to engage in HID and to use illegal drugs and experienced more negative consequences on Pregame HED days than on Moderate Pregaming days. Similar to past research, students were more likely to engage in HID, experience negative consequences, play drinking games, and mix alcohol with energy drinks on Moderate Pregaming days than on Non-Pregaming drinking days.Paper 2 introduces the concept of Day Drinking, or drinking that begins during the daytime (i.e., between 6:00 AM and 3:45 PM), and tested whether students were more likely to engage in HED, HID, and risky behaviors and whether they experienced more negative consequences on Day Drinking days than on days drinking began during the evening or nighttime (N = 7,549 drinking days nested within 618 student drinkers). Day Drinking was reported by 50% of drinkers and on 9% of drinking days across the study. Results of multilevel models nesting days within semesters within persons showed that students were more likely to engage in HED and HID, play drinking games, and use illegal drugs on Day Drinking days than on Nighttime-Only drinking days. Students who reported Day Drinking more frequently were more likely to report HED, HID, mixing alcohol with energy drinks, and negative consequences of alcohol use on drinking days across the study.Paper 3 tested whether three novel risky drinking indicators (HID, Day Drinking, and Pregame HED) predicted medium-term health, legal, and academic consequences, beyond associations with HED (N = 473 student drinkers). Logistic and negative binomial regressions tested whether risky drinking behaviors earlier in college predicted consequences several years later by fourth year of college. Results showed that Pregame HED in the middle of college predicted greater alcohol-related problems and a hazardous and harmful pattern of drinking, independent of HED, in fourth year. First-year HID independently predicted a hazardous and harmful pattern of drinking in fourth year, whereas first-year Day Drinking was not independently associated with any of the four outcomes. Supplemental analyses demonstrated that Pregame HED and HID provided greater specificity in predicting medium-term consequences than HED, and HED provided greater sensitivity.Taken together, this dissertation highlights how common these three extreme, yet understudied, risky drinking behaviors were among the traditionally-aged, full-time students in this multi-ethnic sample from a large, land grant university. This work demonstrates the importance of better differentiating among levels of alcohol consumption and of considering the context in which heavy drinking occurs. By only using single, dichotomous indicators of risky drinking (i.e., HED or any pregaming), researchers fail to capture much of the unique variance that predicts both acute and distal outcomes. It is argued that by using the three novel indicators of risky drinking assessed here (i.e., Pregame HED, Day Drinking, and HID) in conjunction with the broader and more widely used HED and any pregaming indicators, researchers will be able to better identify nuances in the associations between risky college drinking and its correlates and consequences, such as whether particular correlates and consequences are more a result of the amount of alcohol consumed or whether it is the situation in which it is consumed that is particularly conducive to that behavior or consequence. This dissertation illustrated this type of nuanced association by showing that the amount of alcohol consumed while pregaming predicted the number of negative consequences students experienced, whereas students likelihood of playing drinking games was predicted by pregame drinking more generally, regardless of amount. Future work could use a similar analytic technique to assess nuances in other correlates and consequences of risky college drinking.

This book is the first to introduce applied behavioral, social, and health sciences researchers to a new analytic method, the time-varying effect model (TVEM). It details how TVEM may be used to advance research on developmental and dynamic processes by examining how associations between variables change across time. The book describes how TVEM is a direct and intuitive extension of standard linear regression; whereas standard linear regression coefficients are static estimates that do not change with time, TVEM coefficients are allowed to change as continuous functions of real time, including developmental age, historical time, time of day, days since an event, and so forth. The book introduces readers to new research questions that can be addressed by applying TVEM in their research. Readers gain the practical skills necessary for specifying a wide variety of time-varying effect models, including those with continuous, binary, and count outcomes. The book presents technical details of TVEM estimation and three novel empirical studies focused on developmental questions using TVEM to estimate age-varying effects, historical shifts in behavior and attitudes, and real-time changes across days relative to an event. The volume provides a walkthrough of the process for conducting each of these studies, presenting decisions that were made, and offering sufficient detail so that readers may embark on similar studies in their own research. The book concludes with comments about additional uses of TVEM in applied research as well as software considerations and future directions. Throughout the book, proper interpretation of the output provided by TVEM is emphasized. Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences is an essential resource for researchers, clinicians/practitioners as well as graduate students in developmental psychology, public health, statistics and methodology for the social, behavioral, developmental, and public health sciences.

One in three adults has engaged in binge drinking at least once in the previous month, and one in five teenagers has experienced drunkenness by age 15. Harmful patterns of alcohol consumption have far-reaching consequences for individuals, society and the economy.

Alcohol is the most commonly used substance by the American population, according to annual reports from the Substance Abuse and Mental Health Services Administration (SAMHSA). While drinking behaviors vary considerably across the lifespan, consumption of alcohol during any developmental period has been consistently associated with harmful consequences. The likelihood of experiencing these consequences rises dramatically with participation in heavy episodic or high-intensity drinking--risky drinking behaviors often observed during adolescence and young adulthood. The definition for heavy episodic drinking (HED) by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) has been widely accepted in substance use research since its introduction in 2004, and studies have often utilized the HED criteria of consuming four/five or more drinks in one sitting for women/men as the highest threshold of drinking behavior. Current substance use researchers have identified a more extreme pattern of alcohol consumption called high-intensity drinking (HID), where individuals report drinking two to three times the heavy episodic drinking threshold, resulting in increased likelihood of alcohol-related consequences beyond those associated with HED. Many studies have begun investigation into HED and HID in adult participants; however, less research has focused on effects of these risky drinking patterns in adolescence. The present study was a secondary analysis of the National Longitudinal Study of Adolescent and Adult Health (Add Health), and utilized data collected during Waves I and II, which comprised the adolescent developmental period. The analytic sample (N = 4,480) was weighted with the grand sample weight provided from Add Health in Wave II and included students who were, on average: 15.89 years old (SD = 1.61), 50.6% male, and 66.7% White. An innovative statistical technique, the Time Varying Effect Model (TVEM), was used to analyze trends across adolescence and elicit specific periods where the influences of risky drinking patterns were most detrimental on educational success. Descriptive plots demonstrated very little change in current academic achievement from a student's first semester GPA 2.89 (95% CI = 2.78 -- 3.00) to a student's last semester GPA of 2.90 (95% CI = 2.82 -- 2.99). A measure of risky drinking, the number of alcoholic beverages that students reported drinking during a typical drinking event, increased fairly linearly across age with average number of drinks per event peaking at age 19 (M = 6.90; 95% CI = 6.13 -- 7.67). When examining the time-varying effect of the typical number of drinks during a single drinking occasion on current semester achievement, the relationship was significant from the beginning of adolescence at age 12 ([beta] = -0.03; 95% CI = -0.07 -- -0.02) to age 13 ([beta] = -0.02; 95% CI = -0.03 -- -0.0003), and again from age 15 ([beta] = -0.01; 95% CI = -0.02 -- -0.0001) to age 19 ([beta] = -0.01; 95% CI = -0.02 -- -0.0002). Visual analysis of the differences between drinking patterns indicated that during semesters that students engaged in HED or HID, they reported lower grades than peers who abstained from drinking or only drank socially. These differences were wide at younger ages but as students aged, the gap lessened until approximately age 15, when only students reporting HID were differentially affected in their achievement. Results from this study can inform school-based prevention programming and interventions targeted toward the adolescent population. The results may also be useful for parents when monitoring their children's behavior and the messaging they provide to their teenagers about alcohol use.

This book explores the extent of underage drinking across Europe and North America, as well as our current understanding of factors that increase the risk of this behaviour and potentially effective evidence-based approaches to prevent underage drinking.

This instructive manual presents a pragmatic and clinically proven approach to the prevention and treatment of undergraduate alcohol abuse. The BASICS model is a nonconfrontational, harm reduction approach that helps students reduce their alcohol consumption and decrease the behavioral and health risks associated with heavy drinking. Including numerous reproducible handouts and assessment forms, the book takes readers step-by-step through conducting BASICS assessment and feedback sessions. Special topics covered include the use of DSM-IV criteria to evaluate alcohol abuse, ways to counter student defensiveness about drinking, and obtaining additional treatment for students with severe alcohol dependency. Note about Photocopy Rights: The Publisher grants individual book purchasers nonassignable permission to reproduce selected figures, information sheets, and assessment instruments in this book for professional use. For details and limitations, see copyright page.