Trajectories of College Alcohol Involvement and Their Associations with Later Alcohol Use Disorder Symptoms

Prince, Mark A.; Read, Jennifer P.; Colder, Craig R.

doi:10.1007/s11121-018-0974-6

Cited by 36 publications

(23 citation statements)

References 43 publications

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“…Preventing and/or helping students to cope effectively with stressful life events might also reduce AUD incidence by an additional 15.0%. This is consistent with the findings of Prince, Read and Colder [49] in which relatively small absolute differences in alcohol consumption in the first semester of college predicted large differences in alcohol-related consequences post-graduation. Similarly, Read et al [50] observed that trauma and post-traumatic stress at matriculation predicted alcohol consequences at the end of the school year.…”

Section: Main Findingssupporting

confidence: 91%

“…Thus college mental health prevention efforts could be more selective regarding the students targeted for intervention as well as the exposures targeted, thus optimizing limited resources. Our findings, along with those of others [49], suggest that future AUD can be predicted in the first year of college with reasonable precision and this early detection could be beneficial for college counselors to implement timely preventive strategies. Several promising interventions have been evaluated in this regard for college students [57][58][59].…”

Section: Clinical and Policy Implicationssupporting

confidence: 78%

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A risk algorithm that predicts alcohol use disorders among college students

Benjet

Kiekens

Ebert

et al. 2021

Eur Child Adolesc Psychiatry

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The first year of college may carry especially high risk for onset of alcohol use disorders. We assessed the oneyear incidence of alcohol use disorders (AUD) among incoming first year students, predictors of AUDincidence, prediction accuracy and population impact. A prospective cohort study of first-year college students (baseline: N=5,843; response rate=51.8%; 1-year follow-up: n=1,959; conditional response rate=41.6%) at a large university in Belgium was conducted. AUD were evaluated with the AUDIT and baseline predictors with the Composite International Diagnostic Interview Screening Scales (CIDI-SC). The one-year incidence of AUD was 3.9% (SE=0.4). The most important individual-level baseline predictors of AUD incidence were being male (OR=1.53; 95% CI = 1.12 -2.10), a break-up with a romantic partner (OR=1.67; 95% CI = 1.08 -2.59), hazardous drinking (OR=3.36; 95% CI = 1.31 -8.63), and alcohol use characteristics at baseline (ORs between 1.29 and 1.38). Multivariate cross-validated prediction (cross-validated AUC=0.887) show that 55.5% of incident AUD cases occurred among the 10% of students at highest predicted risk (20.1% predicted incidence in this highest-risk subgroup). Four out of five students with incident AUD would hypothetically be preventable if baseline hazardous drinking were to be eliminated along with a reduction of one standard deviation in alcohol use characteristics scores, and another 15.0% would potentially be preventable if all 12-month stressful events were eliminated. Screening at college entrance is a promising strategy to identify students at risk of transitioning to more problematic drinking and AUD, thus improving the development and deployment of targeted preventive interventions.

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Section: Main Findingssupporting

confidence: 91%

Section: Clinical and Policy Implicationssupporting

confidence: 78%

A risk algorithm that predicts alcohol use disorders among college students

Benjet

Kiekens

Ebert

et al. 2021

Eur Child Adolesc Psychiatry

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“…Alcohol misuse is considered to be a serious condition with important negative consequences at a personal and societal level [1,2,3,4]. Numerous studies have emphasized that excessive alcohol use may establish a solid basis for general heavy drinking patterns, binge-drinking episodes, and further development of alcohol use disorder (AUD) in adulthood [5,6,7,8]. In AUD, a substantial number of patients respond to treatment by accomplishing individual goals such as controlled drinking or total abstinence [9].…”

Section: Introductionmentioning

confidence: 99%

Cue-Elicited Anxiety and Alcohol Craving as Indicators of the Validity of ALCO-VR Software: A Virtual Reality Study

Ghiţă

Hernández-Serrano

Fernández-Ruiz

et al. 2019

JCM

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Background: This study is part of a larger project aiming to develop a virtual reality (VR) software to be implemented as a clinical tool for patients diagnosed with alcohol use disorder (AUD). The study is based on previous research in which we identified factors that elicit craving for alcohol in a sample of AUD patients, and which led to the development of a virtual reality software to be used in cue exposure treatments of alcohol use disorder (ALCO-VR). The main objective of this study was to test the effectiveness of ALCO-VR to elicit cue-induced craving and anxiety responses among social drinkers (SD) and AUD patients. Our secondary objective was to explore which responses (cue-induced craving or anxiety) can best differentiate between AUD patients and the SD group. Method: Twenty-seven individuals (13 AUD patients and 14 SD) participated in this study after giving written informed consent. Their anxiety and alcohol craving levels were measured by different instruments at different stages of the procedure. The VR equipment consisted of Oculus Rift technology, and the software consisted of the ALCO-VR platform. Results: Our data indicate that the ALCO-VR software can elicit responses of anxiety and alcohol craving, especially in the group of AUD patients. The cue-induced anxiety response differentiated AUD patients and the SD group better than the cue-induced craving response. Conclusions: The general interest in applying new technologies to the assessment and treatment of mental health disorders has led to the development of immersive real-life simulations based on the advantages of VR technology. Our study concluded that the ALCO-VR software can elicit anxiety and craving responses and that cue-induced anxiety responses can distinguish between AUD and SD groups better than cue-induced craving. The data on craving and anxiety were assessed consistently by different instruments. In addition, we consider that ALCO-VR is able to ecologically assess cue-induced anxiety and alcohol craving levels during exposure to VR alcohol-related environments.

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“…Heavy episodic drinking (defined as 4+/5 + alcohol drinks in a single occasion for women/men) tends to peak between ages 18 and 25, with approximately 33% of U.S. college students and 28% of noncollege same aged peers reporting heavy episodic drinking in the past two weeks (Schulenberg et al, 2018). These patterns of drinking are associated with a range of acute consequences (Hingson et al, 2017), including poor academic and career outcomes (Jennison, 2004) and an increased likelihood of developing an alcohol use disorder in the future (Prince et al, 2019). Heavy drinking often co‐occurs with other health‐risk behaviors which increases risk for health problems and early mortality (Myint et al, 2009).…”

Section: Shared Behavioral Economic Risk Factors For Maladaptive Eating and Risky Drinkingmentioning

confidence: 99%

Identifying Patterns of Alcohol Use and Obesity‐Related Factors Among Emerging Adults: A Behavioral Economic Analysis

Buscemi

Acuff

Minhas

et al. 2021

Alcoholism Clin & Exp Res

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Background: Although heavy alcohol consumption and maladaptive eating behaviors have been shown to co-occur among college students, less is known about the co-occurrence of these behaviors in a more diverse community-dwelling, emerging adult sample. The purpose of this study was to: (i) identify classes of emerging adults by their reported alcohol consumption patterns, food addiction symptoms, and body mass index; and (ii) determine whether these classes differed on indices of behavioral economic reinforcer pathology (e.g., environmental reward deprivation, impulsivity, alcohol demand).Method: Emerging adult participants were recruited as part of a study on risky alcohol use (n = 602; 47% white, 41.5% Black; mean age = 22.63, SD = 1.03). Participants completed questionnaires on alcohol and food-related risk factors and underwent anthropometric assessment.Results: Latent profile analysis suggested a four-profile solution: a moderate alcohol severity, overweight profile (Profile 1; n = 424, 70.4%), a moderate alcohol severity, moderate food addiction + obese profile (Profile 2; n = 93, 15.4%), a high alcohol severity, high food addiction + obese profile (Profile 3; n = 44, 7.3%), and a high alcohol severity, overweight profile (Profile 4; n = 41, 6.8%). Individuals in Profile 1 reported significantly lower levels of environmental reward deprivation than either Profile 2 or 3, and participants in Profile 3 reported significantly higher environmental reward deprivation than those in Profile 4 (p < 0.001). Profile 4 demonstrated significantly higher alcohol demand intensity and O max and lower demand elasticity than Profile 1, Profile 2, or Profile 3. Profile 4 also demonstrated significantly greater proportionate substance-related reinforcement than Profile 1 (p < 0.001) and Profile 2 (p = 0.004).Conclusion: Maladaptive eating patterns and alcohol consumption may share common risk factors for reinforcer pathology including environmental reward deprivation, impulsivity, and elevated alcohol demand.

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Trajectories of College Alcohol Involvement and Their Associations with Later Alcohol Use Disorder Symptoms

Cited by 36 publications

References 43 publications

A risk algorithm that predicts alcohol use disorders among college students

A risk algorithm that predicts alcohol use disorders among college students

Cue-Elicited Anxiety and Alcohol Craving as Indicators of the Validity of ALCO-VR Software: A Virtual Reality Study

Identifying Patterns of Alcohol Use and Obesity‐Related Factors Among Emerging Adults: A Behavioral Economic Analysis

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