Estimated blood alcohol concentration correlation with self-reported negative consequences among college students using alcohol.

Turner, James C.; Bauerle, Jennifer; Shu, Jianfen

doi:10.15288/jsa.2004.65.741

Cited by 27 publications

(18 citation statements)

References 19 publications

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“…In addition, this formula does not account for variations in alcohol metabolism. However,BAC calculations have been found to be comparable in accuracy to in vivo breath tests of alcohol concentration (Carey & Hustad, 2002) and to correlate strongly with alcohol use and alcohol-related consequences in college student samples (Borsari et al, 2001; Turner et al, 2004). Thus, while estimated PBAC was imperfect, we feel it was an appropriate proxy measure for PBAC.…”

Section: Discussionmentioning

confidence: 93%

An experimental test of assessment reactivity within a web-based brief alcohol intervention study for college students

Fazzino

Rose

Helzer

2016

Addictive Behaviors

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Objective Web-based brief alcohol intervention (WBI) programs have efficacy in a wide range of college students and have been widely disseminated to universities to address heavy alcohol use. In the majority of efficacy studies, web-based research assessments were conducted before the intervention. Web-based research assessments may elicit reactivity, which could inflate estimates of WBI efficacy. The current study tested whether web-based research assessments conducted in combination with a WBI had additive effects on alcohol use outcomes, compared to a WBI only. Methods Undergraduate students (n= 856) from universities in the United States and Canada participated in this online study. Eligible individuals were randomized to complete 1) research assessments + WBI or 2) WBI-only. Alcohol consumption, alcohol-related problems, and protective behaviors were assessed at one-month follow up. Results Multiple regression using 20 multiply imputed datasets indicated there were no significant differences at follow up in alcohol use, alcohol-related problems, or protective behaviors used when controlling for variables with theoretical and statistical relevance. A repeated measures analysis of covariance revealed a significant decrease in peak estimated blood alcohol concentration in both groups, but no differential effects by randomized group. There were no significant moderating effects from gender, hazardous alcohol use, or motivation to change drinking. Conclusions Web-based research assessments combined with a web-based alcohol intervention did not inflate estimates of intervention efficacy when measured within-subjects. Our findings suggest universities may be observing intervention effects similar to those cited in efficacy studies, although effectiveness trials are needed.

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Section: Discussionmentioning

confidence: 93%

An experimental test of assessment reactivity within a web-based brief alcohol intervention study for college students

Fazzino

Rose

Helzer

2016

Addictive Behaviors

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“…This method has well-established psychometric properties and allows for the collection of reliable drinking data over a specifi ed period (Sobell and Sobell, 1992). From the TLFB data, typical and peak estimated BAC levels were calculated for each participant using the following equation: BAC = [(number of drinks / 2) × (GC / weight in lb)] − (.016 × hours of drinking)], where GC is a gender constant: 9.0 for women and 7.5 for men (Turner et al, 2004).…”

Section: Methodsmentioning

confidence: 99%

Screening for High-Risk Drinking in a College Student Health Center: Characterizing Students Based on Quantity, Frequency, and Harms

Schaus

Sole

McCoy

et al. 2009

J. Stud. Alcohol Drugs Suppl.

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ABSTRACT. Objective: This study examined characteristics of students who presented to a college health center and screened positive for the 5/4 defi nition of high-risk drinking (fi ve or more drinks in a row for men, or four or more drinks in a row for women, on at least one occasion in the past 2 weeks) and analyzed the students' data according to their reporting of alcohol-related harms. Method: Secondary analysis of data obtained for an intervention study to reduce high-risk drinking in college students was used. Data on alcohol use and alcohol-related harms were obtained from Web-based Healthy Lifestyle Questionnaires and 30-day alcohol recall diaries (Timeline Followback calendar). Students (N = 363; 52% female) were classifi ed as nonheavy, heavy, and heavy and frequent drinkers, based on their self-reported alcohol use. Alcohol-related harms were measured using the Rutgers Alcohol Problem Index and eight additional items derived from the Drinker Inventory of Consequences-2L. Results: Students in the nonheavy, heavy, and heavy and frequent groups had mean Rutgers Alcohol Problem Index scores of 10, 14, and 23, respectively. The heavy-and-frequent drinking group comprised 20% of the sample but experienced 31% of the total harms. Conclusions: The 5/4 screening question accurately identifi ed college students presenting to a college health center who were already experiencing signifi cant alcoholrelated harms. The addition of a frequency question (drinking 3 or more days per week) to the 5/4 screening question provided a simple method for identifying those students at highest risk and in greatest need of intervention. (J. Stud. Alcohol Drugs, Supplement No. 16, 34-44, 2009)

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“…Patrick et al (2013) suggest that reliance on traditional binge drinking criteria obscures meaningful variation in how much youth drink and may miss important distinctions between levels of drinking and consequences experienced (see also Turner, Bauerle, & Shu, 2004). In fact, several studies have shown that youth drink much more beyond the traditional binge drinking threshold (Patrick et al, 2013; Read et al, 2008; White et al, 2006), which highlights the need to move beyond traditional binge drinking criteria to identify at-risk drinkers.…”

Section: Introductionmentioning

confidence: 99%

Do drinking motives distinguish extreme drinking college students from their peers?

White

Anderson

Ray

et al. 2016

Addictive Behaviors

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Objective The literature highlights the need to move beyond the traditional heavy episodic (“binge”) drinking criteria when trying to identify at-risk college drinkers. Thus, recent attention has focused on more extreme levels of drinking. This study examines whether drinking motives can distinguish college student extreme drinkers from lighter drinkers. Method We used data from 3,518 college student current drinkers (63.4% women) who participated in eight different studies at five different college campuses across the United States; a subsample of these students was followed up at 6 months post baseline. At baseline and follow-up, drinkers were divided into three groups: nonbinge drinkers (less than 4 drinks for women and 5 for men on their maximum drinking occasion), binge drinkers (4–7 drinks for women; 5–9 for men), and extreme drinkers (8+ for women and 10+ for men). Results At baseline, extreme drinkers, compared to nonbinge and binge drinkers, reported greater social, enhancement, and coping motives, as well as greater quantity and frequency of drinking per week and more alcohol-related problems. Those who were not extreme drinkers at baseline and later became extreme drinkers at follow-up reported significantly greater increases in social and enhancement motives, compared to those who remained nonextreme drinkers. Those who were extreme drinkers at baseline and reduced their drinking 6 months later, compared to those who remained extreme drinkers, reported greater reductions in enhancement and coping motives. Conclusions Focusing on drinking motives might be an efficacious target for preventive intervention programs to reduce extreme drinking among college students.

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Estimated blood alcohol concentration correlation with self-reported negative consequences among college students using alcohol.

Cited by 27 publications

References 19 publications

An experimental test of assessment reactivity within a web-based brief alcohol intervention study for college students

An experimental test of assessment reactivity within a web-based brief alcohol intervention study for college students

Screening for High-Risk Drinking in a College Student Health Center: Characterizing Students Based on Quantity, Frequency, and Harms

Do drinking motives distinguish extreme drinking college students from their peers?

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