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Individual-focused approaches to the prevention of
college student drinking.
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| Article Type: | Report |
| Subject: |
Drinking of alcoholic beverages
(Research) College students (Alcohol use) College students (Research) |
| Authors: |
Cronce, Jessica M. Larimer, Mary E. |
| Pub Date: | 09/22/2011 |
| Publication: | Name: Alcohol Research & Health Publisher: U.S. Government Printing Office Audience: Academic; Professional Format: Magazine/Journal Subject: Health Copyright: COPYRIGHT 2011 U.S. Government Printing Office ISSN: 1535-7414 |
| Issue: | Date: Fall, 2011 Source Volume: 34 Source Issue: 2 |
| Topic: | Event Code: 310 Science & research |
| Product: | Product Code: E197500 Students, College |
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| Accession Number: | 275974730 |
| Full Text: |
As detailed by Johnston and colleagues (2009), the majority of
young adults, in particular college students, consume alcohol. Moreover,
a substantial proportion of those who consume alcohol misuse it,
engaging in heavy episodic drinking, (1) which directly and indirectly
contributes to a host of harmful consequences (O'Malley and
Johnston 2002; Perkins 2002). The rates of heavy drinking peak at ages
21 or 22 (Johnston et al. 2009), suggesting that most college students
mature out of heavy drinking. Nevertheless, the harm they experience as
a result of heavy drinking, such as poor academic and work performance
or serious physical injury, may irrevocably alter students' natural
developmental trajectories. In an effort to prevent or mitigate such
long-term harm, myriad prevention programs have been developed to reduce
college student drinking by targeting individual factors associated with
alcohol use and misuse, including alcohol expectancies, drinking
motives, perceived norms, and natural ambivalence regarding behavior
(Baer 2002; Presley et al. 2002). A wealth of research has been devoted
to evaluating the efficacy of these preventive interventions. The
purpose of this article is to provide a comprehensive summary of the
current state of the science with regard to individual-focused
preventive interventions whose efficacy in reducing alcohol use and
alcohol-related problems has been evaluated in the college student
population using randomized controlled trials. Conclusions from earlier
reviews in this area are described briefly, with greater focus given to
summarizing evidence accumulated in the past 3 years (2007-2010). INDIVIDUAL-FOCUSED PREVENTIVE INTERVENTIONS: SPECIFIC COMPONENTS AND EVIDENCE OF EFFICACY Previous Reviews Larimer and Cronce (2002, 2007) conducted qualitative reviews of research published between 1984 and early 2007 that evaluated the efficacy of individual preventive interventions aimed at college students. Both reviews noted a dearth of support for educational or awareness models, including information-based and values-clarification approaches, whereas there was evidence of efficacy for skills-based interventions, including self-monitoring/assessment, alcohol expectancy challenge (AEC), and multicomponent skills training. Moreover, both reviews documented strong empirical support for brief motivational interventions (BMIs) delivered via mail, online, or in person. As the name implies, in-person BMIs are brief (i.e., typically delivered over one or two sessions) and focus on enhancing motivation and commitment to change problematic behavior. To this end, BMIs often provide personalized feedback regarding the client's drinking and related consequences, alcohol expectancies, and drinking motives; when delivered alone in the absence of a trained facilitator, this personalized feedback component is referred to as a personalized feedback intervention (PFI). BMIs and PFIs often additionally include general alcohol information (i.e., alcohol education) and alcohol-specific coping and harm-reduction skills. PFIs typically include personalized normative feedback (PNF), which compares the client's self-reported drinking behavior to the average drinking behavior of a specific reference group (e.g., typical student, typical female). PNF encourages clients to explore and enhance discrepancies between their perception of their own drinking as "typical" and the actual drinking behaviors of their peers--that is, that the majority of students drink moderately, often significantly less than the individual receiving the intervention. Like PFIs, PNF can be delivered as a stand-alone intervention in the absence of in-person contact. Larimer and Cronce (2007) independently detailed empirical evidence supporting normative reeducation interventions, in particular computer-administered or in-person PNF interventions, that produced reductions in drinking and/or consequences mediated through changes in normative perceptions. Complementing the qualitative reviews by Larimer and Cronce (2002, 2007), Carey and colleagues (2007) conducted a quantitative review evaluating 62 randomized clinical trials of 98 alcohol interventions for college students published during roughly the same time period (i.e., 1985 to early 2007). This meta-analysis similarly supported the efficacy of individual-focused alcohol interventions in reducing the quantity and frequency of alcohol use and alcohol-related negative consequences. The investigators further noted that significant intervention effects on indices of alcohol consumption peaked before the 6-month followup and that subsequently emerging effects on alcohol-related negative consequences lasted through long-term followup (ranging from 1 to 3.75 years). Specifically, Carey and colleagues (2007) concluded that individual interventions that used motivational interviewing techniques, included personalized feedback on alcohol expectancies and drinking motives with normative reeducation components, and included decisional balance exercises demonstrated greater efficacy in reducing alcohol-related consequences than did various comparison groups. This combination of intervention components is common to intervention approaches patterned after the Brief Alcohol Screening and Intervention for College Students (BASICS) program (Dimeff et al. 1999). Review of Recent Individual-Focused Preventive Intervention Studies In the years since the publication of the reviews by Carey and colleagues (2007) and Larimer and Cronce (2002, 2007), numerous studies of individual-focused preventive interventions for college student drinking have been published. Of these, 36 studies evaluating 56 unique interventions, met criteria for inclusion in this review (see the tables for details). Studies were identified via a comprehensive search of electronic databases, including PsycINFO and MEDLINE (for a list of search terms used, see Larimer and Cronce 2007), covering the period from late 2007 to early 2010. Additional studies were identified indirectly (e.g., they were referenced in the introduction section of one of the identified studies), and as-yet-unpublished studies were provided directly by authors. Studies were included if they used a randomized controlled trial approach--that is, if they randomly assigned individual participants (or intact groups) to one of two or more experimental conditions, including at least one active intervention and an ostensibly inert control (e.g., assessment only) group. Although the number of studies meeting inclusion criteria suggests that a meta-analysis may be warranted, a qualitative approach was selected for this review to facilitate more rapid communication with key stakeholders concerning the current state of alcohol prevention. (2) However, intervention effect sizes are reported for relevant outcomes in all studies that included effect size estimates in the original report or provided sufficient postintervention data to calculate between-group estimates (see tables). Within-group effect size estimates also are provided for studies wherein significant within-person reductions in alcohol use or consequences were evident. Many of the studies included in this review evaluate the efficacy of multicomponent BMIs, many of which were adapted from the BASICS program. Most of these BMIs incorporated a PFI with PNF. Some studies evaluated one or more PFI/PNF interventions delivered alone, without the benefit of a trained intervention facilitator. Interventions were delivered via various modalities, including in-person group and individual sessions, mailed printed material, and Web-based content. In addition, some interventions were conducted in special settings (i.e., primary care, in the student's home before entering college) or targeted high-risk student subpopulations (i.e., mandated/sanctioned students, freshmen, or athletes). Stand-Alone PFI/PNF Interventions. A total of 17 studies evaluated the impact of 14 unique PFIs/PNF and 4 PNF-only interventions implemented via written material, mail, computer, Web, or electronic diary on college student drinking (see table 1). Of 14 PFI/PNF interventions evaluated, 6 were associated with reductions in drinking but not drinking-related consequences relative to the comparison condition at followup. One PFI/PNF intervention (Doumas and Andersen 2009) was associated with reduced drinking-related consequences as well as alcohol use. Four additional PFI/PNF interventions were associated with significant within-person reductions in alcohol use and/or consequences across assessment periods, but between-group differences were not evident. Of four PNF-only interventions evaluated, three resulted in reductions in drinking outcomes at followup. The remaining PNF-only intervention had no effects on these outcomes but was associated with reductions in perceived drinking norms and increased readiness/preparation for behavior change. In-Person BMIs. The literature review also identified 17 studies evaluating 20 unique in-person BMIs (individual and group), most of which incorporated PFI and/or PNF (see table 2). Of these interventions, 13 were associated with reductions in drinking, alcohol-related negative consequences, and/or associated psychopathology, and three interventions exhibited a protective effect against the onset of or increase in alcohol use and/or related consequences. One of these studies (Schaus et al. 2009) demonstrated a sleeper effect of the intervention, with short-term reductions in drinking and subsequently emerging reductions in consequences. Also note that another of these studies (Doumas and Hannah 2008) was not specifically aimed at college students but targeted young adults (ages 18 to 24) who were employed; however, 75 percent of the sample concurrently was enrolled in school. This study found that BMI combined with PFI was equivalent to PFI alone in reducing drinking-related variables. Finally, one of these studies (Hansson et al. 2007) specifically evaluated intervention gains between the 12-month and 24-month followup and found an advantage for a BMI combined with coping skills over either component alone. A quantitative comparison of changes from baseline to the 12-month followup was not presented. However, figures displaying group means suggest a potential short- term effect of the BMI-only condition in reducing estimated blood alcohol concentrations (BACs), which, if counted, would bring the above total support for BMI conditions from 13 to 14. * Findings of studies evaluating BMI in specialized settings and high-risk subpopulations suggest that primary care is an effective venue for delivery of this type of intervention (Schaus et al. 2009). * Group BMI or BMI enhanced with parental coaching is effective in reducing drinking among college freshmen (Turrisi et al. 2009; Wood et al. 2010). * BMI is effective for nonmandated high-risk drinkers (Doumas and Hannah 2008; Stahlbrandt et al. 2007). * Studies involving students who had been mandated to participate in the interventions documented benefits of BMIs (Carey et al. 2009; White et al. 2007), in particular for females (Carey et al. 2009) and those who received additional services, including coping skills, problem solving, and stress management training, in the context of a student assistance program (Amaro et al. 2009). Another study (Carey et al. 2010) additionally found greater benefit of BMI participation in reducing alcohol consumption among female mandated students compared with two separate multicomponent educational programs; however, reductions in the BMI were similar to assessment only. Participation in any of the three interventions was associated with short-term reductions in alcohol consumption among male mandated students. Other Preventive Approaches. Additional studies evaluated other specific alcohol interventions, in most cases comparing these approaches to other active interventions (e.g., BMI or PFI/PNF) (see table 3). Two studies published in the time period evaluated included alcohol expectancy challenge (AEC) protocols, which generally are considered to be more skills based than motivational in nature. Lau-Barraco and Dunn (2008) evaluated a single-session, gender-specific in vivo (experiential) AEC. In contrast, Wood and colleagues (2007) assessed a two-session mixed-gender in vivo AEC, both alone and in combination with a BMI involving a PFI/PNF component. Both AEC interventions resulted in reductions in alcohol use but not alcohol consequences. Two other studies (Glindemann et al. 2007; Thombs et al. 2007) investigated the efficacy of BAC feedback, another cognitive--behavioral skills-based approach used to intervene with college students. One of these studies (Glindemann et al. 2007) demonstrated a positive effect of the intervention (i.e., reductions in BACs), whereas the other (Thombs et al. 2007) reported a potential inadvertent opposite (i.e., iatrogenic) effect--that is, an increase in BACs. These mixed findings may be related to differences between the two studies in terms of the timing of the feedback (i.e., immediate versus delayed) and use of incentives to promote lower BACs (i.e., a $100 cash raffle for participants with BACs lower than 0.05 percent in the study by Glindemann and colleagues [2007]). Four studies evaluated alcohol education either as a stand-alone intervention (see Thadani et al. 2009) or as a comparison intervention for PFI/PNF interventions with or without BMI. These studies generally found increases in alcohol knowledge among the students receiving the intervention. However, the interventions generated equivocal or negative effects on alcohol use and related consequences because they detected no group differences and/or lacked an assessment-only control group. Finally, eight studies tested nine unique multicomponent, education-focused programs, which included general alcohol information as well as elements typically associated with efficacious BMI and PFI/PNF interventions, such as personalized feedback, normative reeducation, challenge of positive drinking expectancies, and tips for harm reduction. Just over one-half of these programs were associated with reductions in drinking and/or alcohol consequences, whereas the remainder (i.e., Alcohol 101 Plus [Carey et al. 2009]; an in-person, facilitator-led program [Cimini et al. 2009]; AlcoholEdu for College, 2006 version [Croom et al. 2008]; and Alcohol 101 [Lau-Barraco and Dunn 2008]) produced equivocal results. Of note, because the effective multicomponent education programs (e.g., AlcoholEdu, 2007 version; AlcoholEdu for College; AlcoholEdu for Sanctions; and College Alc) included BMI and PFI/PNF elements, it is impossible to disentangle the effect of education alone from the effects of these efficacious components. INDIVIDUAL-FOCUSED PREVENTIVE INTERVENTIONS: CONCLUSIONS AND FUTURE RESEARCH In summary, studies published between 2007 and early 2010 provide consistent support for the efficacy of brief, personalized, individual motivational feedback (i.e., BMI with PFI/PNF) interventions and stand-alone PFI/PNF interventions. These studies also provide support for the efficacy of AEC interventions, although less consistent, and offer mixed support for BAC feedback. These conclusions are in line with previous reviews (Carey et al. 2007; Larimer and Cronce 2002, 2007). Also consistent with previous reviews, there was an absence of support for programs solely including alcohol education, although multicomponent alcohol education--focused programs, which combine educational elements with BMI, PFI, and PNF components, had greater, albeit mixed, support. Although the balance of the evidence supports the efficacy of PFI/PNF-only interventions, additional research on these interventions is necessary to identify the elements and/or modalities that are associated with behavior change and to determine for whom in-person BMI is more (or less) efficacious compared with PFI/PNF-only interventions. The lack of intervention effects in a few of the BMI and PFI/PNF studies may reflect the potential absence (or ineffective delivery) of necessary intervention components or the presence of potential moderators of intervention effects (e.g., mandated student status). Additional research also needs to establish the efficacy of these brief interventions in reducing long-term risk. Thus, it may be necessary to modify and evaluate existing interventions and/or evaluate the effects of supplemental interventions in order to extend their short-term effects and enhance or prolong their impact on negative drinking consequences. Recent findings (Carey et al. 2007; Schaus et al. 2009) suggesting longer-term emergent effects on alcohol-related consequences, particularly in response to in-person BMIs (Carey et al. 2007), indicate that the addition of longer-term follow-up assessments will be necessary to achieve this. Finally, additional research is needed to evaluate the efficacy of BMIs in combination with other interventions, including interventions targeting environmental change, parenting practices, or psychiatric comorbidity. Ultimately, multiple intervention strategies may be necessary to produce lasting effects on college student drinking and related harm. Unfortunately, key stakeholders (e.g., college administrators, campus health professionals) face numerous barriers when trying to implement efficacious individual-focused alcohol interventions. For example, with the exception of commercially available programs, such as e-Chug or AlcoholEdu, the measures and feedback programs used in most intervention protocols are not easily accessible or not immediately useable. For those seeking to implement the BASICS approach (Dimeff et al. 1999), a published manual and measures are available. However, campus personnel may not have adequate resources (e.g., the expertise to train and supervise therapists, access to programs that can generate personalized feedback, or access to campus specific normative drinking data) to implement the program with sufficient fidelity. Many of these barriers can be overcome by pairing health and counseling personnel with faculty in academic departments who may have experience with program evaluation and implementation. Word processing and spreadsheet/database programs generally available to campus personnel can be used to generate basic personalized feedback. Distance-learning methods currently used to disseminate some evidence-based public health interventions (e.g., video- or Web-based conferencing of initial training and ongoing clinical supervision) could be adapted to support implementation of BMI protocols. Implementation of routine alcohol screening in campus health centers could be used to gather normative data for use in PFI/PNF and to identify students appropriate for intervention. Barriers to intervention implementation also necessitate additional research into increasing the reach of evidence-based approaches. This includes research related to training of providers and assessment of fidelity for in-person interventions, methods to improve impact and portability of Web-based or mailed/written interventions, and research on adaptation of efficacious interventions so they are appropriate for young adults from different cultural backgrounds and in contexts outside the traditional, mainstream college setting. To date, young adults in the workplace, community-college settings, tribal colleges and universities, historically Black colleges and universities, and other minority-serving institutions have been substantially underrepresented in efficacy trials of BMIs and related interventions. Careful consideration and the development of meaningful community partnerships to support the bidirectional learning necessary to adapt and implement efficacious brief prevention approaches in these settings are needed. ACKNOWLEDGEMENTS This research was supported through funding from the National Institute on Alcohol Abuse and Alcoholism (T32--AA--007455, Psychology Training in Alcohol Research). FINANCIAL DISCLOSURE The authors declare that they have no competing financial interests. REFERENCES Amaro, H.; Ahl, M.; Matsumoto, A.; et al. Trial of the university assistance program for alcohol use among mandated students. Journal of Studies on Alcohol and Drugs (Suppl.16):45-56, 2009. PMID: 19538912 Baer, J.S. Student factors: Understanding individual variation in college drinking. Journal of Studies on Alcohol (Suppl. 14):40-53, 2002. PMID: 12022729 Bersamin, M.; Paschall, M.J.; Fearnow-Kenney, M.; and Wyrick, D. Effectiveness of a web-based alcohol-misuse and harm-prevention course among high- and low-risk students. Journal of American College Health 55:247-254, 2007. PMID: 19319331 Bewick, B.M.; Trusler, K.; Mulhern, B.; ET AL. 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Individual and situational factors that influence the efficacy of personalized feedback substance use interventions for mandated college students. Journal of Consulting and Clinical Psychology 77:88-102, 2009. PMID: 19170456 National Institute on Alcohol Abuse and Alcoholism (NIAAA). NIAAA Council approves definition of binge drinking. NIAAA Newsletter 3:3, 2004. Neighbors, C.; Lee, C.M.; Lewis, M.A.; et al. Internet-based personalized feedback to reduce 21st birthday drinking: A randomized controlled trial of an event-specific prevention intervention. Journal of Consulting and Clinical Psychology 77:51-63, 2009. PMID: 19170453 O'Malley, P.M., and Johnston, L.D. Epidemiology of alcohol and other drug use among American college students. Journal of Studies on Alcohol (Suppl. 14):23-39, 2002. PMID: 12022728 Perkins, H.W. Surveying the damage: A review of research on consequences of alcohol misuse in college populations. Journal of Studies on Alcohol (Suppl. 14):91-100, 2002. PMID: 12022733 Presley, C.A.; Meilman, P.W.; and Leichliter, J.S. College factors that influence drinking. Journal of Studies on Alcohol (Suppl. 14):82-90, 2002. PMID: 12022732 Saitz, R.; Palfai, T. P.; Freedner, N.; et al. Screening and brief intervention online for college students: The iHealth study. Alcohol and Alcoholism 42:28-36, 2007. PMID: 17130139 Schaus, J.F.; Sole, M.L.; McCoy, T.P.; et al. Alcohol screening and brief intervention in a college student health center: A randomized controlled trial. Journal of Studies on Alcohol and Drugs (Suppl. 16): 131-141, 2009. PMID: 19538921 Stahlbrandt, H.; Johnsson, K.O.; and Berglund, M. Two-year outcome of alcohol interventions in Swedish university halls of residence: A cluster randomized trial of a brief skills training program, twelve-step-influenced intervention, and controls. Alcoholism: Clinical and Experimental Research 31:45 8-466, 2007. PMID: 17295713 Thadani, V.; Huchting, K.; and LaBrie, J. Alcohol-related information in multi-component interventions and college students' drinking behavior. Journal of Alcohol and Drug Education 53:31-51, 2009. The Century Council. Alcohol 101 Plus [computer software]. Washington, DC: The Century Council, 2003. Available at: http://www.alcohol101plus.org/. Thombs, D.L.; Olds, R.S.; Osborn, C.J.; et al. Outcomes of a technology-based social norms intervention to deter alcohol use in freshman residence halls. Journal of American Colege Health 55:325-332, 2007. PMID: 17517544 Turrisi, R.; Larimer, M.E.; Mallett, K.A.; et al. A randomized clinical trial evaluating a combined alcohol intervention for high-risk college students. Journal of Studies on Alcohol and Drugs 70:555-567, 2009. PMID: 19515296 Walters, S.T., and Neighbors, C. Feedback interventions for college alcohol misuse: What, why and for whom? Addictive Behaviors 30:1168-1182, 2005. PMID: 15925126 Walters, S.T.; Vader, A.M.; Harris, T.R.; et al. Dismantling motivational interviewing and feedback for college drinkers: A randomized clinical trial. Journal of Consulting and Clinical Psychology 77:64-73, 2009. PMID: 19170454 Wechsler, H.; Dowdall, G.W.; Davenport, A.; and Rimm, E.B. A gender-specific measure of binge drinking among college students. American Journal of Public Health 85:982-985, 1995. PMID: 7604925 Weitzel, J.A.; Bernhardt, J.M.; Usdan, S.; et al. Using wireless handheld computers and tailored text messaging to reduce negative consequences of drinking alcohol. Journal of Studies on Alcohol and Drugs 68:534-537, 2007. PMID: 17568957 White, H.R. Reduction of alcohol-related harm on United States college campuses: The use of personal feedback interventions. International Journal of Drug Policy 17:310-319, 2006. White, H.R.; Mun, E.Y.; Morgan, T.J. Do brief personalized feedback interventions work for mandated students or is it just getting caught that works? Psychology of Addictive Behaviors 22:107-116, 2008. PMID: 182982236 White, H.R.; Mun, E.Y.; Pugh, L.; and Morgan, T.J. Long-term effects of brief substance use interventions for mandated college students: Sleeper effects of an in-person personal feedback intervention. Alcoholism: Clinical and Experimental Research 31:1380-1391, 2007. PMID: 17550361 Wood, M.D.; Capone, C.; Laforge, R.; et al. Brief motivational intervention and alcohol expectancy challenge with heavy drinking college students: A randomized factorial study. Addictive Behaviors 32:2509-2528, 2007. PMID: 17658696 Wood, M.D.; Fairlie, A.M.; Fernandez, A.C.; et al. Brief motivational and parent interventions for college students: A randomized factorial study. Journal of Consulting and Clinical Psychology 78:349-361, 2010. PMID: 20515210 (1) The National Institute on Alcohol Abuse and Alcoholism (NIAAA) defines binge or heavy episodic drinking as the consumption of an amount of alcohol leading to a blood alcohol concentration (BAC) of 0.08 percent, which, for most adults, would be reached by consuming five drinks for men or four for women over a 2-hour period (NIAAA 2004). Wechsler and colleagues (1995) similarly denote a binge episode as consumption of five or more drinks for men and four or more drinks for women but do not stipulate a bounded time frame during which consumption must occur or link the episode to a particular BAC. The latter definition by Wechsler and colleagues (1995) was used most frequently across the studies reviewed here. (2) Both meta-analytic (quantitative) and qualitative reviews seek to combine findings from multiple studies addressing a shared research hypothesis (e.g., that a particular type of intervention will reduce alcohol use and/or consequences). In a meta-analysis, findings are combined via a common measure of effect size (e.g., Cohen's d), and conclusions are based on a weighted average of all of the effect sizes. By comparison, a qualitative approach is more inductive, and conclusions summarize the balance of the evidence based on an additive evaluation of the separate studies. Jessica M. Cronce, Ph.D., and Mary E. Larimer, Ph.D. Jessica M. Cronce, Ph.D., is a senior postdoctoral fellow, and Mary E. Larimer, Ph.D., is a professor in the Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington. Table 1 Studies Assessing the Efficacy of Stand/Alone PFI/PNF
Interventions Compared With Assessment Only or Other Interventions
Intervention
Study Conditions
PFI/PNF vs. assessment only
Bewick et 1. Web-based PFI/PNF *
al. (2008) 2. Assessment only
Doumas & 1. Web-based PFI/PNF (e-Chug) *
Andersen 2. Assessment only
(2009)
Geisner, 1. Mailed PFI/PNF with general tips
et al. 2. Assessment only
(2007)
Hustad et 1. Web-based PFI/PNF (e-Chug) *
al. (2010) 2. Multicomponent alcohol education-focused
program (AlcoholEdu)
3. Assessment only
Weitzel et 1. PFI/PNF only
al. (2007) 2. Assessment only
PFI/PNF vs. waitlist control
White et 1. PFI/PNF (within person *)
al. (2008) 2. Waitlist control (received PFI with PNF based on
baseline assessment at first followup) (within
person *)
PFI/PNF vs. alcohol education
Doumas & 1. Web-based PFI/PNF *
Haustveit 2. Alcohol education
(2008)
Doumas et 1. Web-based PFI/PNF *
al. (2009) 2. Web-based alcohol education (Judicial Educator)
Minimal PFI/PNF vs. enhanced PFI/PNF
Saitz et 1. Minimal Web-based PFI/PNF (within person *)
al. (2007) 2. Enhanced Web-based PFI/PNF (within person *)
PFI/PNF vs. BMI
Butler et 1. In-person BMI with PFI
al. (2009) 2. Computerized PFI alone *
3. Assessment only
Doumas & 1. BMI with Web-based PFI/PNF
Hannah 2. Web-based PFI/PNF only *
(2008) 3. Assessment only
Mun et al. 1. BMI with PFI/PNF
(2009) 2. Written PFI/PNF only
Walters et 1. BMI with PFI/PNF
al. (2009) 2. BMI without PFI/PNF
3. Web-based PFI/PNF only
4. Assessment only
White et 1. BMI with PFI/PNF
al. (2007) 2. Written PFI/PNF only (within person *)
PNF-only vs. assessment only
Lewis et 1. Gender-specific computerized PNF *
al. (2007 2. Gender-neutral computerized PNF *
3. Assessment only
Lewis et 1. 21st birthday card with PNF
al. (2008) 2. Assessment only
Neighbors 1. 21st birthday card with PNF *
et al. 2. Assessment only
(2009)
Student Population
Outcome (Intervention Effect Follow-up
Study Condition) Sizes Period
PFI/PNF vs. assessment only
Bewick et Reduced drinks per d = 0.29 12 weeks
al. (2008) drinking occasion
(1)
Doumas & Among high-risk 3 months
Andersen drinkers:
(2009) Reduced frequency of d = 0.85
intoxication (1)
Reduced alcohol d = 0.80
consequences (1)
Geisner, Reduced perceived d = 0.60 1 month
et al. drinking norms (1)
(2007) No group difference
with respect to
alcohol use or
consequences (1, 2)
Hustad et Reduced typical and ds = 0.54 to 0.85 1 month
al. (2010) peak drinking (1)
Reduced typical and ds = 0.59 to 0.75
peak drinking (2)
Reduced alcohol d = 0.56
consequences (2)
Weitzel et Reduced drinks per N/A 2 weeks
al. (2007) drinking day during
the intervention
period, but not at
followup (1)
PFI/PNF vs. waitlist control
White et Mandated/sanctioned 2 months
al. (2008) students: and 7
No group differences months
(1, 2)
Within-person Within-person ds:
comparisons:
Reduced drinking ds = 0.23, 0.28 2 months
frequency (1, 2)
Reduced heavy d = 0.29
drinking episodes
(1)
Reduced peak BAC ds = 0.24, 0.28
(1, 2)
Reduced alcohol d = 0.23
consequences (2)
Reduced drinking ds = 0.24, 0.28 7 months
frequency (1, 2)
Reduced peak BAC (2) d = 0.22
Reduced alcohol ds = 0.20, 0.19
consequences (1, 2)
PFI/PNF vs. alcohol education
L
Doumas & Among high-risk 6 weeks
Haustveit drinkers: and 3
(2008) Reduced weekly [[eta.sub.p.sup.2] months
drinking quantity = 0.14
(1)
Reduced peak drinking [[eta.sub.p.sup.2]
quantity (1) = 0.15
Reduced frequency of [[eta.sub.p.sup.2]
intoxication (1) = 0.20
* Drinking reductions
were positively
associated with
reductions in
perceived norms for
typical student
drinking
Doumas et Mandated/sanctioned 30 days
al. (2009) students:
Reduced weekly [[eta.sub.p.sup.2]
drinking quantity = 0.07
(1)
Reduced peak drinking [[eta.sub.p.sup.2]
quantity (1) = 0.08
Reduced frequency of [[eta.sub.p.sup.2]
intoxication (1) = 0.07
* Changes in drinking
were mediated via
reductions in
perceived norms
for alcohol
consumption
Minimal PFI/PNF vs. enhanced PFI/PNF
Saitz et High-risk drinking
al. (2007) freshmen:
No group differences 1 month
(1, 2)
Within-person
comparisons:
Reduced AUDIT scores
(1, 2)
Reduced quantity
drinks per week
(women; 1, 2)
Reduced heavy
drinking episodes
(women; 1, 2)
PFI/PNF vs. BMI
Butler et Reduced frequency of [[eta.sub.p.sup.2] 4 weeks
al. (2009) typical drinking = 0.13
(1, 2)
Reduced quantity of [[eta.sub.p.sup.2]
typical drinking = 0.17
(1, 2)
Reduced frequency of [[eta.sub.p.sup.2]
binge drinking = 0.15
(1, 2)
Doumas & Among high-risk 30 days
Hannah drinkers:
(2008) Reduced weekend [[eta.sub.p.sup.2]
alcohol use (1, 2) = 0.07
Reduced peak drinking [[eta.sub.p.sup.2]
quantity (1, 2) = 0.05
Reduced frequency of [[eta.sub.p.sup.2]
intoxication (1, 2) = 0.04
Mun et al. No group differences 15 months
(2009) (1, 2)
Walters et Reduced alcohol use d = 0.54 6 months
al. (2009) and problems (1)
No group differences
on alcohol use or
consequences (2, 3, 4)
White et Mandated/sanctioned N/A 4 months
al. (2007) students: d = 0.27 15 months
No group differences
(1, 2)
Protective effect
against increases in
alcohol consequences
(1)
Within-person Within-person ds: 15 months
comparisons:
Reduced quantity d = 0.28
drinks per week (1)
Reduced peak BAC d = 0.36, 0.19
(1, 2)
Reduced alcohol d = 0.39
consequences (1)
PNF-only vs. assessment only
Lewis et Reduced quantity N/A 5 months
al. (2007 drinks per week (1)
Reduced drinking
frequency (1)
Reduced drinking
frequency (2)
Lewis et Reduced normative [[eta.sub.p.sup.2] 1 -week
al. (2008) misperceptions (1) = 0.07
No group differences
with respect to
alcohol use or
consequences (1,2)
Neighbors Reduced BAC on 21st d = 0.33 4 days
et al. birthday (1) post-
(2009) * Intervention was birthday
more effective
among those with
baseline intentions
to reach higher
BACs
NOTE: Mun et al. (2009) reported the outcome of subsequent analyses
related to the efficacy of Interventions originally reported In White
et al. (2007); as such, these Interventions are not Included In the
total count of unique interventions provided in the text.
Intervention conditions followed by an "*" indicates the specific
intervention was associated with reductions, or exhibited a
protective effect against, relevant behavioral outcomes (e.g.,
quantity or frequency of alcohol consumption; alcohol/related
negative consequences). Effect sizes reported Include Cohen's d
(Cohen, 1988), which denotes the standardized difference between the
mean of the Intervention and comparisons groups and eta squared
([eta]2), which denotes the proportion of total variability In the
dependent variable attributable to the effect of the Independent
variable, or partial eta squared ([eta] p2). According to Cohen's
(1988, 1992) definitions of effect size, small, medium, and large
effects for dare considered to be In the 0.20, 0.50, and 0.80 ranges,
respectively, and for [eta]2 and [eta] p2 are 0.01, 0.06, and 0.14,
respectively. N/A = effect size estimate not available.
Table 2 Studies Assessing the Efficacy of In-Person BMIs
Intervention
Study Conditions
BMI vs. assessment only
Amaro et 1. In-person BMI with PFI
al. (2009) plus indicated
cognitive--behavioral
interventions *
2. Counseling services as
usual
LaBrie et 1. Group BMI *
al. (2008) 2. Assessment only
LaBrie et 1. Group BMI
al. (2009) 2. Assessment only
BMI vs. PFI/PNF only
Butler et 1. In-person BMI with
al. (2009) PFI *
2. Computerized PFI alone
3. Assessment only
Doumas & 1. BMI with Web-based
Hannah PFI/PNF *
(2008) 2. Web-based PFI/PNF
only
3. Assessment only
Mun et al. 1. BMI with PFI/PNF
(2009) 2. Written PFI/PNF only
Walters et 1. BMI with PFI/PNF *
al. (2009) 2. BMI without PFI/PNF
3. Web-based PFI/PNF
only
4. Assessment only
White et 1. BMI with PFI/PNF *
al. (2007) 2. Written PFI/PNF only
BMI vs. other interventions
Carey et 1. In-person BMI with PNF *
al. (2009) 2. Multicomponent alcohol
education-focused
program (Alcohol 101 Plus)
Carey et 1. In-person BMI with
al. (2010) PFI/PNF *
2. Multicomponent alcohol
education--focused
program (Alcohol 101 Plus)
3. Multicomponent alcohol
education--focused
program (AlcoholEdu
for Sanctions)
4. Waitlist control
Cimini et 1. Group BMI
al. (2009) 2. Interactive peer theatrical
presentation
3. In-person alcohol
education
Hansson et 1. BMI(possible *; refer to
al. (2007) article)
2. Coping skills training
3. BMI + coping skills
training *
Schaus et 1. BMI with PNF *
al. (2009) 2. Alcohol education
Stahlbrandt 1. Modified group
et al. BASICS-based BMI *
(2007) 2. 12-step focused group
3. Assessment only
Turrisi et 1. Parent-based intervention
al. (2009) (PMI)
2. BMI with PFI/PNF *
3. PMI + BMI *
4. Assessment only
Wood et 1. BMI with PFI/PNF *
al. (2007) 2. Alcohol expectancy
challenge (AEC)
3. BMI with PFI/PNF + AEC
4. Assessment only
Wood et 1. BMI with PFI/PNF *
al. (2010) 2. Parent-based intervention
(PMI)
3. BMI + PMI *
4. Assessment only
Student Population
Outcome (Intervention Effect Follow-up
Study Condition) Sizes Period
BMI vs. assessment only
Amaro et Mandated/sanctioned
al. (2009) students:
Reduced weekday d = 1.06 6 months
alcohol use (1)
Reduced alcohol d = 0.65
consequences (1)
Increased use of d = 1.98 10 weeks
protective
behavioral
strategies (1)
LaBrie et Freshmen women:
al. (2008) Reduced typical d = 0.34
drinking (1)
Reduced d = 0.42
heavy-episodic
drinking (1)
* Intervention was
more effective for
those with higher
social and
enhancement
drinking motives
LaBrie et Freshmen women: 6 months
al. (2009) No group differences
(1, 2)
BMI vs. PFI/PNF only
Butler et Reduced frequency of [[eta].sub.p.sup.2] 4 weeks
al. (2009) typical drinking = 0.13
(1, 2)
Reduced quantity of [[eta].sub.p.sup.2]
typical drinking = 0.17
(1, 2)
Reduced frequency of [[eta].sub.p.sup.2]
binge drinking = 0.15
(1, 2)
Doumas & Among high-risk
Hannah drinkers:
(2008) Reduced weekend [[eta].sub.p.sup.2] 30 days
alcohol use (1, 2) = 0.07
Reduced peak drinking [[eta].sub.p.sup.2]
quantity (1, 2) = 0.05
Reduced frequency of [[eta].sub.p.sup.2]
intoxication (1, 2) = 0.04
Mun et al. No group differences 15 months
(2009) (1, 2)
Walters et Reduced alcohol use d = 0.54 6 months
al. (2009) and problems (1)
No group differences
on alcohol use or
consequences
(2, 3, 4)
White et Mandated/sanctioned 4 months
al. (2007) students: N/A 15 months
No group differences
(1, 2)
Protective effect d = 0.27
against increases
in alcohol
consequences (1)
Within-person Within-person ds:
comparisons:
Reduced quantity d = 0.28 15 months
drinks per week (1)
Reduced peak BAC d = 0.36, 0.19
(1, 2)
Reduced alcohol d = 0.39
consequences (1)
BMI vs. other interventions
Carey et Mandated/sanctioned
al. (2009) students:
Reduced alcohol use ds = 0.21 to 0.38 1 month
(various indices)
among women only (1)
Carey et Mandated/sanctioned N/A 1 month
al. (2010) students:
Reduced alcohol use
(various indices)
among men (1, 2, 3)
No group differences
on problems among
men (1, 2, 3, 4)
Reduced alcohol use
without group
differences among
women (1, 2, 3, 4)
Reduced problems
without group
differences among
women (1, 3, 4)
Women in (1)
experienced greater
reductions in
alcohol use
relative to (2, 3)
Cimini et Mandated/sanctioned 6 months
al. (2009) students:
No group differences
(1, 2, 3)
Hansson et Reduced alcohol ds = 0.52 to 0.60 12-24
al. (2007) psychopathology (3) months
Reduced drinking ds = 0.42 to 0.72
consequence
scores (3)
Reduced estimated d = 0.49
BACs (3)
Schaus et Reduced typical ds = 0.27-0.41 3 and 6
al. (2009) drinking (1) months
Reduced peak ds = 0.25-0.36
drinking (1)
Reduced typical ds = 0.28-0.35
BAC (1)
Reduced peak BAC (1) ds = 0.37-0.49
Reduced frequency of ds = 0.42-0.50
intoxication (1)
Reduced alcohol ds = 0.23-0.29 6 and 9
problems (1) months
Stahlbrandt Among high-risk d = 0.27 2 years
et al. drinkers:
(2007) Reduced AUDIT
scores (1)
Turrisi et Reduced typical ds = 0.14-0.20 10 months
al. (2009) drinking (3)
Reduced peak ds = 0.17-0.26
drinking (3)
Reduced alcohol ds = 0.13-0.20
consequences (3)
* Changes in drinking
were mediated via
reductions in
perceived
descriptive and
injunctive norms
for alcohol
Reduced peak BAC (2) d = 0.16
Reduced number of ds = 0.16-0.18
drinks/weekend (2)
Wood et Reduced total alcohol ds = 0.16-0.25 1 month,
al. (2007) use (1) 3 months,
Reduced total alcohol ds = 0.01-0.20 and 6
use (2) months
Reduced heavy ds = 0.18-0.26
episodic
consumption (1)
Reduced heavy ds = 0.00-0.22
episodic
consumption (2)
Reduced alcohol ds = 0.29-0.33
consequences (1)
Wood et Protective effect
al. (2010) against:
Initiating heavy hs = 0.02-0.22 10 months
episodic and
consumption (1) 22 months
Experiencing onset hs = 0.07-0.15
alcohol
consequences (1)
Experiencing onset N/A
alcohol
consequences (3)
NOTE: conditions followed by an "*" indicates the specific
intervention was associated with reductions, or exhibited a
protective effect against, relevant behavioral outcomes (e.g.,
quantity or frequency of alcohol consumption; alcohol/related
negative consequences). Mun et al. (2009) and LaBrie et al. (2009)
both reported the outcome of subsequent analyses related to the
efficacy of interventions originally reported in White et al. (2007)
and LaBrie et al. (2008), respectively; as such, these interventions
are not included in the total count provided in the text. Effect
sizes reported include Cohen's d(Cohen, 1988), which denotes the
standardized difference between the mean of the intervention and
comparisons groups, Cohen's h(Cohen, 1988), which denotes the
difference between two proportions, and eta squared ([eta]p2), which
denotes the proportion of total variability in the dependent variable
attributable to the effect of the independent variable, or partial
eta squared ([eta]p2). According to Cohen's (1988, 1992) definitions
of effect size, small, medium, and large effects for d and h are
considered to be in the 0.20, 0.50, and 0.80 ranges, respectively,
and for [eta]2 and [eta]p2 are 0.01, 0.06, and 0.14, respectively.
N/A = effect size estimate not available.
Table 3 Studies Assessing the Efficacy of Other Preventive
Interventions
Intervention
Study Conditions
Alcohol expectancy challenge
Lau-Barraco 1. Alcohol expectancy
and Dunn challenge (AEC) *
(2008) 2. Multicomponent alcohol
education-focused
program (Alcohol 101)
3. Assessment only
Wood et 1. BMI with PFI/PNF
al. (2007) 2. Alcohol expectancy
challenge (AEC) *
3. BMI with PFI/PNF + AEC
4. Assessment only
Blood alcohol concentration (BAC) feedback
Glindemann 1. BAC feedback *
et al. 2. Assessment only
(2007)
Thombs et 1. BAC feedback
al. (2007) 2. BAC feedback +
normative re-education
Alcohol education
Doumas & 1. Web-based PFI with PNF
Haustveit 2. Alcohol education
(2008)
Doumas et 1. Web-based PFI with PNF
al. (2009) 2. Internet-based alcohol
education (Judicial
Educator)
Schaus et 1. BMI with PNF
al. (2009) 2. Alcohol education
Thadani et 1. Alcohol education
al. (2009) 2. Assessment only
Multicomponent, education-focused interventions
Bersamin 1. Multicomponent alcohol
et al. education-focused program
(2007) (College Alc) *
2. Assessment only
Carey et 1. In-person BMI with PNF
al. (2009) 2. Multicomponent alcohol
education-focused program
(Alcohol 101 Plus)
Carey et 1. In-person BMI with
al. (2010) PFI/PNF
2. Multicomponent alcohol
education-focused program
(Alcohol 101 Plus) *
3. Multicomponent alcohol
education-focused program
(AlcoholEdu for
Sanctions) *
4. Waitlist control
Cimini et 1. Group BMI
al. (2009) 2. Interactive peer theatrical
presentation
3. In-person multicomponent
alcohol education-focused program
Croom et 1. Multicomponent alcohol
al. (2008) education-focused program
(AlcoholEdu for
College)
2. Assessment only
Hustad et 1. Web-based PFI with PNF
al. (2010) (e-Chug)
2. Multicomponent alcohol
education-focused program
(AlcoholEdu for College) *
3. Assessment only
Lau-Barraco 1. Alcohol expectancy
and Dunn challenge (AEC)
(2008) 2. Multicomponent alcohol
education-focused program
(Alcohol 101)
3. Assessment only
Lovecchio 1. Multicomponent alcohol
et al. education-focused program
(2010) (AlcoholEdu) *
2. Assessment only
Student Population
Outcome
(Intervention Effect Follow-up
Study Condition) Sizes Period
Alcohol expectancy challenge
Lau-Barraco Reduced quantity of ds = 0.30 to 0.35 1 month
and Dunn drinks per
(2008) week (1)
Reduced frequency ds = 0.34 to 0.36
of binge
drinking (1)
Wood et Reduced total ds = 0.16-0.25 1 month,
al. (2007) alcohol use (1) 3 months,
Reduced total ds = 0.01-0.20 and 6
alcohol use (2) months
Reduced heavy ds = 0.18-0.26
episodic
consumption (1)
Reduced heavy ds = 0.00-0.22
episodic
consumption (2)
Reduced alcohol ds = 0.29-0.33
consequences (1)
Blood alcohol concentration (BAC) feedback
Glindemann Lower BACs (1) d = 0.31 Unspecified
et al. Increased d = 0.20
(2007) percentage of
individuals with a
BAC <.08 g % (1)
Thombs et Increased observed d = 0.30 Next day
al. (2007) mean BAC (2) follow-up,
aggregated
across
participants
over 2-year
project
period
Alcohol education
Doumas & Among high-risk
Haustveit drinkers:
(2008) Reduced weekly [[eta].sub.p.sup.2] 6 weeks and
drinking = 0.14 3 months
quantity (1)
Reduced peak [[eta].sub.p.sup.2]
drinking = 0.15
quantity (1)
Reduced frequency [[eta].sub.p.sup.2]
of intoxication = 0.20
(1)
* Drinking
reductions were
positively
associated with
reductions in
perceived norms
for typical
student drinking
Doumas et Mandated/sanctioned
al. (2009) students:
Reduced weekly [[eta].sub.p.sup.2] 30 days
drinking quantity = 0.07
(1)
Reduced peak [[eta].sub.p.sup.2]
drinking quantity = 0.08
(1)
Reduced frequency [[eta].sub.p.sup.2]
of intoxication = 0.07
(1)
* Changes in
drinking were
mediated via
reductions in
perceived norms
for alcohol
consumption
Schaus et Reduced typical ds = 0.27-0.41 3 months and
al. (2009) drinking (1) 6 months
Reduced peak ds = 0.25-0.36
drinking (1)
Reduced typical ds = 0.28-0.35
BAC (1)
Reduced peak ds = 0.37-0.49
BAC (1)
Reduced frequency ds = 0.42-0.50
of intoxication
(1)
Reduced alcohol ds = 0.28-0.29 6 months and
problems (1) 9 months
Thadani et Freshmen women: d = 0.73 6 months
al. (2009) Increased alcohol
knowledge (1)
No group
differences on
alcohol use or
consequences
(1, 2)
Multicomponent, education-focused interventions
Bersamin Freshmen: 3 months
et al. Reduced heavy d = 0.15
(2007) episodic
consumption (1)
Carey et Mandated/sanctioned
al. (2009) students:
Reduced alcohol use ds = 0.21 to 0.38 1 month
(various indices)
among women
only (1)
Carey et Mandated/sanctioned
al. (2010) students:
Reduced alcohol use NA 1 month
(various indices)
among men
(1, 2, 3)
No group
differences on
problems among
men (1, 2, 3, 4)
Reduced alcohol use
without group
differences among
women
(1, 2, 3, 4)
Reduced problems
without group
differences among
women (1, 3, 4)
Women in (1)
experienced
greater
reductions in
alcohol use
relative to
(2, 3)
Cimini et Mandated/sanctioned 6 months
al. (2009) students:
No group
differences
(1, 2, 3)
Croom et Increased alcohol d = 0.52 6 weeks'
al. (2008) knowledge (1) post-
Lower participation d = 0.12 matriculation
in drinking
games (1)
Less likely to use N/A
safer sex
strategies (1)
No group
differences with
respect to
alcohol use or
consequences
(1, 2)
Hustad et Reduced typical ds = 0.54 to 0.85 1 month
al. (2010) and peak
drinking (1)
Reduced typical ds = 0.59 to 0.75
and peak
drinking (2)
Reduced alcohol d = 0.56
consequences (2)
Lau-Barraco Reduced quantity ds = 0.30 to 0.35 1 month
and Dunn of drinks per
(2008) week (1)
Reduced frequency ds = 0.34 to 0.36
of binge
drinking (1)
Lovecchio Increased alcohol d = 0.11 1 month
et al. knowledge (1)
(2010) Decreased d = 0.28
responsible
drinking
behavior (1)
Protective effect
against:
Increased alcohol d = 0.59
consequences (1)
Increased d = 0.65
accepting
others'
drinks (1)
Increased positive d = 0.07
alcohol
expectancies (1)
NOTE: conditions followed by an "*" indicates the specific
intervention was associated with reductions, or exhibited a
protective effect against, relevant behavioral outcomes (e.g.,
quantity or frequency of alcohol consumption; alcohol-related
negative consequences). Effect sizes reported include Cohen's d
(Cohen, 1988), which denotes the standardized difference between the
mean of the intervention and comparisons groups, Cohen's h (Cohen
1988), which denotes the difference between two proportions, and eta
squared ([eta]2), which denotes the proportion of total variability
in the dependent variable attributable to the effect of the
independent variable, or partial eta squared ([eta]p2). According to
Cohen's (1988, 1992) definitions of effect size, small, medium, and
large effects for d and h are considered to be in the 0.20, 0.50, and
0.80 ranges, respectively, and for [eta]2 and [eta]p2 are 0.01, 0.06,
and 0.14, respectively. NA = effect size estimate not available. |
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