Predictors of Patterns of Alcohol-Related Blackouts Over Time in Youth From the Collaborative Study of the Genetics of Alcoholism: The Roles of Genetics and Cannabis.

OBJECTIVE: Alcohol-related blackouts (ARBs) are anterograde amnesias related to heavy alcohol intake seen in about 50% of drinkers. Although a major determinant of ARBs relates to blood alcohol concentrations, additional contributions come from genetic vulnerabilities and possible impacts of cannabis use disorders (CUDs). We evaluated relationships of genetics and cannabis use to latent class trajectories of ARBs in 829 subjects from the Collaborative Study of the Genetics of Alcoholism (COGA). METHOD: The number of ARBs experienced every 2 years from subjects with average ages of 18 to 25 were entered into a latent class growth analysis in Mplus, and resulting class membership was evaluated in light of baseline characteristics, including CUDs. Correlations of number of ARBs across assessments were also compared for sibling pairs versus unrelated subjects. RESULTS: Latent class growth analysis identified ARB-based Classes 1 (consistent low = 42.5%), 2 (moderate low = 28.3%), 3 (moderate high = 22.9%), and 4 (consistent high = 6.3%). A multinomial logistic regression analysis within latent class growth analysis revealed that baseline CUDs related most closely to Classes 3 and 4. The number of ARBs across time correlated .23 for sibling pairs and -.10 for unrelated subjects. CONCLUSIONS: Baseline CUDs related to the most severe latent ARB course over time, even when considered along with other trajectory predictors, including baseline alcohol use disorders and maximum number of drinks. Data indicated significant roles for genetic factors for alcohol use disorder patterns over time. Future research is needed to improve understanding of how cannabis adds to the ARB risk and to find genes that contribute to risks for ARBs among drinkers.

Drinking Patterns Across Spring, Summer, and Fall in 462 University Students.

BACKGROUND: Student heavy drinking and associated problems are common at most universities and fluctuate throughout the calendar year, with marked increases during celebrations. Most studies of student drinking are limited to the academic year itself, and relatively few focus specifically on special heavy drinking events. Even fewer studies include drinking during summer break and subsequent school return. METHODS: In the context of an experimental protocol, beginning in January 2014, alcohol-related characteristics were evaluated 8 times over 55 weeks for 462 college freshmen, including periods that incorporated a campus festival, summer, and school return. Baseline predictors of drinking quantities over time included demography, substance use patterns, as well as environmental and attitudinal characteristics. Product-moment correlations evaluated relationships between baseline characteristics and subsequent quantities, and simultaneous entry regression analyses evaluated which characteristics most robustly predicted usual and maximum drinks over time. RESULTS: Maximum drinks per occasion increased 18% from the early spring (4/8/14 to 5/6/14) to the campus festival period (5/7/14 to 6/3/14), decreased 29% in the summer (7/8/14 to 8/5/14), and increased 31% on school return (10/7/14 to 11/4/14). The most robust predictors of higher quantities in regression analyses included items from each of the 3 major domains with the most consistent results seen for most baseline alcohol-related items and descriptive drinking norms (R(2) = 0.20 to 0.31). CONCLUSIONS: These data demonstrate important changes in students' drinking during the calendar year, including expected large increases during the month of a 1-day festival, large decreases over the summer, and resumption of relatively high quantities upon return to school.

The Low Level of Response to Alcohol-Based Heavy Drinking Prevention Program: One-Year Follow-Up.

OBJECTIVE: Heavy drinking is common on college campuses, with a marked increase from high school to freshman year. Programs addressing heavy campus drinking often personalize prevention protocols to fit a student's demography and prior drinking characteristics. Few efforts have individualized approaches to address a person's vulnerability through his or her low level of response (low LR) to alcohol. METHOD: This article describes the recently completed 55-week outcome in drinking quantities and problems for the >90% of 500 participants in a prevention program at a U.S. university (62% female, mean age = 18 years) who completed a 4-week series of 50-minute videos delivered via the Internet. We evaluated whether, for low LRs, participation in an educational approach that focused on a low LR (the LR-based [LRB] condition) was associated with better outcomes than a state-of-the-art (SOTA) general education or with a no-intervention control condition. RESULTS: Using a mixed-design analysis of variance and focusing on the most closely ethnically matched high and low LR pairs, students with low LRs in the LRB condition demonstrated the greatest decreases in usual and maximum drinks over the 55 weeks, especially when compared with closely ethnically matched students with high LRs. Low LR controls showed the highest drinking values over time. CONCLUSIONS: This study underscores the potential importance of targeting a person's specific preexisting vulnerability toward heavy drinking when he or she enters college. The approach can be used in a relatively inexpensive protocol of video education sessions delivered via the Internet.

The impact of focusing a program to prevent heavier drinking on a pre-existing phenotype, the low level of response to alcohol.

BACKGROUND: Heavy drinking is common during transitions from high school to college. Optimal programs for diminishing risks for high alcohol consumption often tailor the approach to the specific needs of students. This study describes the results of an Internet-based prevention protocol that tailors the information to the risk associated with a pre-existing phenotype, the Low level of Response (Low LR) to alcohol. METHODS: Using stratified random assignment, 454 freshmen with Low and High LR values were assigned to 2 education groups (LR-based where all examples were given the context of the Low LR model of heavy drinking or a State Of The Art (SOTA) Group where the same lessons were taught but without an emphasis on LR) or a no-intervention Control Group. Individuals in the 2 education groups viewed 50-minute online videos once per week for 4 weeks. Changes in drinking patterns were assessed at Baseline, 4 weeks, and 8 weeks using a 2 (LR status) by 3 (education group) by 3 (time points) analysis of variance, with additional tests for ethnicity and sex. RESULTS: Low LR participants tended to decrease their usual (p < 0.06) and maximum (p < 0.05) drinks per occasion most prominently when assigned to the LR-based protocol, while those with High LRs improved more in the SOTA Group. The most robust differences were seen when controlling for ethnicity. The effect sizes were small to medium. CONCLUSIONS: These results support the advantages of carrying out prevention via the Internet and in tailoring the approach to a pre-existing phenotype.