Examining the impact of early college experiences on the cumulative number of alcohol-related consequences

Serious harm reduction protective behavioral strategies reduce consequences associated with alcohol-induced blackouts in college students

OBJECTIVE

Alcohol-induced blackouts (AIBs) have been associated with increased alcohol-related consequences. Serious harm reduction (SHR) protective behavioral strategies may reduce consequences when students are drinking heavily. We examined whether SHR weakened the relationship between AIBs and a) total consequences and b) serious consequences (e.g., sexual assault) only.

METHODS

Students were eligible if they were aged 18-22  years, in their second or third year of college, reported drinking 4 + drinks on a typical Friday or Saturday, experienced ≥ 1 AIB in the past semester, owned an iPhone, and were willing to wear a sensor for 3  days each weekend. Students (N = 79, 55.7 % female, 86.1 % White, Mage = 20.1) wore sensors and completed daily diaries over four consecutive weekends (852 total surveys; 89.9 % completion rate). Linear multilevel models were conducted to test for moderating effects of SHR.

RESULTS

SHR weakened the association between AIBs and total consequences. At low (-1 SD) SHR, days with an AIB had an additional 1.46 consequences compared to days without an AIB, on average. At high (+1 SD) SHR, days with an AIB had an additional 0.94 consequences compared to days without an AIB, on average. SHR did not change the association between AIBs and serious consequences.

CONCLUSIONS

Students experienced approximately 50% more consequences on nights when they had an AIB and used below average numbers of SHR compared to nights when they had an AIB and used above average numbers of SHR. These findings suggest that student drinking interventions should include SHR to reduce harm associated with drinking and AIBs.

Transdermal alcohol concentration features predict alcohol-induced blackouts in college students

BACKGROUND

Alcohol-induced blackouts (AIBs) are common in college students. Individuals with AIBs also experience acute and chronic alcohol-related consequences. Research suggests that how students drink is an important predictor of AIBs. We used transdermal alcohol concentration (TAC) sensors to measure biomarkers of increasing alcohol intoxication (rise rate, peak, and rise duration) in a sample of college students. We hypothesized that the TAC biomarkers would be positively associated with AIBs.

METHODS

Students were eligible to participate if they were aged 18-22 years, in their second or third year of college, reported drinking 4+ drinks on a typical Friday or Saturday, experienced ≥1 AIB in the past semester, owned an iPhone, and were willing to wear a sensor for 3 days each weekend. Students (N = 79, 55.7% female, 86.1% White, Mage = 20.1) wore TAC sensors and completed daily diaries over four consecutive weekends (89.9% completion rate). AIBs were assessed using the Alcohol-Induced Blackout Measure-2. Logistic multilevel models were conducted to test for main effects.

RESULTS

Days with faster TAC rise rates (OR = 2.69, 95% CI: 1.56, 5.90), higher peak TACs (OR = 2.93, 95% CI: 1.64, 7.11), and longer rise TAC durations (OR = 4.16, 95% CI: 2.08, 10.62) were associated with greater odds of experiencing an AIB.

CONCLUSIONS

In a sample of "risky" drinking college students, three TAC drinking features identified as being related to rising intoxication independently predicted the risk for daily AIBs. Our findings suggest that considering how an individual drinks (assessed using TAC biomarkers), rather than quantity alone, is important for assessing risk and has implications for efforts to reduce risk. Not only is speed of intoxication important for predicting AIBs, but the height of the peak intoxication and the time spent reaching the peak are important predictors, each with different implications for prevention.

A Dual-Process Decision-Making Model Examining the Longitudinal Associations Between Alcohol-Induced Blackouts and Alcohol Use Disorder Risk Among College Student Drinkers

OBJECTIVE

The purpose of this study was to use a dual-process decision-making model to examine the longitudinal associations between alcohol-induced blackouts (blackouts) and alcohol use disorder (AUD) risk symptoms among college student drinkers.

METHOD

Undergraduate drinkers (N = 2,024; 56% female; 87% White; 5% Hispanic) at a large northeastern university completed online surveys each semester during their first (Time [T] 1, T2), second (T3, T4), third (T5, T6), and fourth (T7, T8) years of college (87% retention across the study). Path analyses were examined testing the longitudinal associations between T1 willingness to experience a blackout, T1 intentions to avoid a blackout, T2-T8 drinking, T2-T8 blackouts, and T8 AUD risk symptoms. Hypotheses 1 and 2 tested the associations between T1 willingness, T1 intentions, T2-T8 drinking, and T2-T8 blackouts. Hypothesis 3 tested the associations between T2-T8 drinking, T2-T8 blackouts, and T8 AUD risk symptoms.

RESULTS

Students experienced an average of 8 (SD = 8) blackouts during college. Approximately 1,514 (88.8%) participants reported experiencing 1 of 8 AUD risk symptoms. T1 willingness was positively associated with T2-T8 blackouts. T2-T8 drinking and T2-T8 blackouts were positively associated with T8 AUD risk symptoms. T1 willingness significantly indirectly affected T8 AUD risk symptoms through its association with T2-T8 blackouts.

CONCLUSIONS

Results estimated that, on average, college student drinkers experienced eight blackouts across 4 years of college, and 88% of participants reported experiencing at least one symptom of AUD in the last semester of college. Willingness to experience a blackout influenced students' AUD risk symptoms through the number of blackouts they experienced throughout college.

Does it really matter that I do not remember my night? Consequences related to blacking out among college student drinkers

BACKGROUND

Alcohol-induced blackouts (AIBs) are experienced frequently by college student drinkers and are more likely to occur on days with high-intensity drinking (HID; 8+ for females/10+ for males) than non-HID days. Research suggests that AIBs are associated with experiencing other alcohol-related consequences (ARCs), including more serious ARCs (SARCs; e.g., legal and sexual consequences), but we do not know whether individuals experience more ARCs and more SARCs on occasions when they black out than when they do not black out. This study examines the associations between AIBs and the total number of both ARCs and SARCs.

METHODS

Students (N = 462, 51.7% female, 87.7% White, Mage  = 20.1) were assessed across 6 weekends via e-surveys (80%-97% response rate). Multilevel models were used to test for main effects, controlling for drinking (HID or estimated blood alcohol concentration; eBAC) and sex.

RESULTS

Drinking days when an AIB was experienced were associated with more total ARCs (b = 3.54, 95% CI: 3.10, 3.99) and more SARCs (b = 0.77, 95% CI: 0.60, 0.95) per day than non-AIB days. The more frequently a person experienced an AIB, the more total ARCs (b = 5.33, 95% CI: 4.40, 6.25) and SARCs (1.05, 95% CI: 0.80, 1.30) they reported on average.

CONCLUSION

Alcohol-induced blackout days were associated with higher levels of harm than non-AIB days, even at the same levels of drinking. Interventions that focus on reducing the occurrence of AIBs and factors that contribute to them, in addition to reducing alcohol consumption, may help reduce total harm associated with drinking among college students.

Alcohol-induced blackouts among college student drinkers: A multilevel analysis

OBJECTIVE

To identify factors (manner of drinking, combined alcohol and other substance use, physiology) that are associated with alcohol-induced blackouts (AIBs) over and above estimated blood alcohol concentration (eBAC).

METHODS

Students (N = 462, 51.7 % female, 87.7 % White, Mage = 20.1) were assessed across 6 weekends via e-surveys (80-97 % response rate). eBAC was calculated using standard number of drinks, drinking duration, sex, and weight. Three-level multilevel models (days, weeks, persons) were conducted to test for main effects, controlling for eBAC.

RESULTS

Protective behavioral strategies (PBS) were associated with decreased odds of AIBs on the daily (OR = 0.64, 95 % CI: 0.53, 0.77), weekly (OR = 0.84, 95 % CI: 0.72, 0.98), and person-levels (OR = 0.62, 95 % CI: 0.51, 0.74). Combined cannabis with alcohol was associated with increased odds of AIBs on the weekly (OR = 2.13, 95 % CI 1.13, 4.07) and person-levels (OR = 3.56, 95 % CI 1.60, 7.93). People who more frequently played drinking games (OR = 1.41, 95 % CI: 1.12, 1.77), pregamed (OR = 1.55, 95 % CI: 1.19, 2.03), and showed higher tolerance (OR = 1.22, 95 % CI: 1.08, 1.37) showed increased risk of AIBs, over and above eBAC levels.

CONCLUSION

We identified a number of daily-, weekly-, and person-level factors that uniquely contribute to the prediction of AIBs even at equivalent eBACs. Many of these factors were behavioral, suggesting that they may serve as malleable prevention targets for AIBs in college student drinkers.

Validation of the Alcohol-Related Sexual Consequences Scale in Swedish University Students

BACKGROUND

Alcohol-related sexual consequences are common in college students. A newly developed 41-item Alcohol-Related Sexual Consequences Scale has recently been evaluated in at-risk young adults in the U.S. The current study aims to validate the Scale in Swedish college students.

METHODS

The occurrence of alcohol-related sexual consequences was assessed by birth gender, relationship status, gender identity/sexual orientation, and age. Negative binomial regression was used to assess convergent and divergent validity.

RESULTS

On average, 5.4 (SD 5.1) alcohol-related sexual consequences were experienced past three months. Greater scores were reported in singles, LGBTQ (Lesbian, Gay, Bisexual, Transgender, Queer/Questioning), and younger students. All sex-related covariates showed robust associations with alcohol-related sexual consequences while most alcohol-related covariates were not associated (e.g., convergent validity). All alcohol-related covariates showed robust associations with alcohol consequences while most sex-related covariates were not associated (e.g., divergent validity). In the full model predicting alcohol-related sexual consequences, being a woman, single, and younger were identified as independent predictors.

CONCLUSIONS

This newly developed scale assessing alcohol-related sexual consequences could be used in both epidemiological studies and intervention studies targeting at-risk students.