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. Author manuscript; available in PMC: 2019 Jul 1.
Published in final edited form as: Addict Behav. 2018 Feb 14;82:23–27. doi: 10.1016/j.addbeh.2018.02.020

Student Engagement and Comfort during a Web-Based Personalized Feedback Intervention for Alcohol and Sexual Assault

Anna E Jaffe a, Kaitlin E Bountress b, Isha W Metzger c, Jessica L Maples-Keller d, Hanna T Pinsky e, William H George f, Amanda K Gilmore a
PMCID: PMC5912168  NIHMSID: NIHMS945695  PMID: 29477903

Abstract

Introduction

The purpose of this study was to investigate individual engagement and comfort during a web-based intervention for alcohol and sexual assault risk reduction.

Methods

Participants were 264 college women (aged 18–20) who reported engaging in heavy episodic drinking in the past month. Participants were randomized to either an intervention condition (alcohol, sexual assault risk reduction, or combined) or a control condition (full or minimal assessment). Participants rated their experiences during the procedures following the assessment or receipt of the intervention depending on condition. Survey usage information (e.g., time data, completion of intervention) was automatically recorded.

Results

Most participants completed the intervention as intended (in a reasonable amount of time, in private, without consuming substances). Women with a sexual assault history were most comfortable in the sexual assault risk reduction intervention, whereas women who frequently engaged in heavy episodic drinking were least comfortable in the alcohol intervention condition. Self-reported distraction was not impacted by personal relevance of the intervention, but was associated with setting of participation.

Conclusions

Results suggest that most college women completed web-based personalized feedback interventions as designed, despite minimal discomfort.

Keywords: Alcohol, Gender, Mental Health

1. Introduction

Sexual assault (SA) victimization and heavy episodic drinking (HED; 4+ drinks in 2 hours or less for women) are common among college women (Krebs et al., 2016; White & Hingson, 2014). Personalized feedback interventions, which provide students with feedback on their own behavior, their perceptions of peer behavior, and actual peer behavior to reduce erroneous overestimates of risky behaviors by peers, are effective in reducing alcohol use among college students (Kilmer, Cronce, & Larimer, 2014; White, 2006) and have demonstrated promise in reducing alcohol use and SA risk when both are targeted (Gilmore, Lewis, & George, 2015). Increasingly, Web-based personalized feedback interventions are recommended (e.g., NIAAA, 2015) given their low cost, high effectiveness, and compliance with national regulations for higher education (e.g., Title IX, Education Department General Administrative Regulations part 86). Accordingly, many universities require students to complete web-based personalized feedback interventions before they can register for classes.

As these web-based interventions become more common, unique aspects of receiving corrective feedback (which can create some discomfort to motivate change) in an online format bear consideration. For one, students may become more adept at meeting requirements without engaging in the intervention (e.g., clicking through without reading). Indeed, researchers expect a substantial portion of participants in online interventions will dropout or participate minimally (Eysenbach, 2005). This poses a threat to the effectiveness of web-based interventions – particularly those that may challenge students’ beliefs and norms. However, there has been limited research on online engagement. Existing studies focus on community participants’ voluntary interactions with web-based content (e.g., number of webpages explored, time per page; Couper et al., 2010; Murray et al., 2013; see Danaher & Seeley, 2009), and do not address how college students engage with a prescribed intervention.

Relatedly, students may complete web-based interventions in a wide range of settings, which may pose a threat to engagement with the intervention. Only one study (Lewis & Neighbors, 2015) has examined context for completing web-based interventions, and found many college students completed the intervention in public while simultaneously engaged in other activities. To our knowledge, no studies have examined context during web-based SA interventions, which involve viewing more sensitive material.

Further complicating engagement, students might experience discomfort when receiving corrective feedback. This discomfort has the potential to both motivate behavioral change and reduce intervention engagement. Reactions to feedback may differ based on alcohol use and SA history, particularly when feedback is delivered online and disengagement is only a click away. Although SARR strategies arise from a feminist context and place responsibility for SA entirely on the perpetrator, self-blame for SA is common and negative cognitions could be unintentionally activated. Though associated distress could lead to withdrawal, withstanding discomfort and completing interventions could benefit at-risk students (Gilmore et al., 2015). Therefore, it is important to examine the potential for personal history to influence intervention engagement and comfort.

1.1. Current Study

The purpose of the current study is to examine students’ experience completing web-based personalized feedback interventions for alcohol use and sexual assault risk reduction (SARR). In particular, we examined whether students completed the intervention as designed and examined process variables that could pose a threat to fidelity or effectiveness. This study first assessed participant engagement (i.e., intervention usage, distraction) and comfort during web-based personalized feedback interventions targeting alcohol use and/or SARR. Second, we examined whether personal relevance of the intervention influenced engagement and comfort. We hypothesized that participants with a SA history would be more distracted and less comfortable during SARR interventions. Similarly, we hypothesized that participants with more frequent HED would be more distracted and less comfortable during alcohol interventions. Third, we examined differences in overall engagement and comfort by the context in which participants completed the study.

2. Material and Methods

2.1. Participants

Female college students (n = 264) aged 18–20 (M = 18.78, SD = 0.74) who reported HED at least once in the past month were recruited for participation in a randomized controlled trial (see Gilmore et al., 2015). The majority of participants identified as White/Caucasian (56.1%), had been in college for less than one year (62.8%), were not a member of a sorority (61.5%), and were single (72.0%).

2.2. Measures

2.2.1. Engagement

Participant engagement was operationalized as intervention completion, time, and distraction. Intervention completion was indicated by opening a post-intervention survey. Time elapsed during the intervention was automatically collected via Javascript. Pilot testing conducted in a laboratory suggested the alcohol (16 pages; 2353 words), SARR (25 pages; 3077 words), and combined interventions (43 pages; 5244 words) could each be completed in around 5 minutes. Following intervention completion, participants self-reported how distracted (1 [Not distracted at all] to 7 [Highly distracted]) they were during the study.

2.2.2. Comfort

After completing the intervention, participants were also asked how comfortable (1 [Very uncomfortable] to 7 [Very comfortable]) they were while completing the survey.

2.2.3. Context

Participants described the setting in which they participated (coded by the second author as: private, alone; private, with someone; or public) and indicated whether they were currently under the influence of alcohol, marijuana, other, or no substances.

2.2.4. Sexual assault

The Sexual Experiences Survey (Koss et al., 2007) assessed SA since age 14, including contact, attempted penetration, and completed penetration following verbal coercion, incapacitation, threats, or physical force. Participants who endorsed any item were considered to have a SA history (=1; no history =0).

2.2.5. Frequency of heavy episodic drinking

Participants were asked about frequency of HED (“4 or more drinks containing any kind of alcohol within a 2-hour period”) in the past month ranging from zero times to every day. Frequency during the past 4 weeks was calculated based on the mid-point of the response (e.g., 3–4 times a week was estimated to be 14 episodes in the past 4 weeks; possible range = 0 to 28).

2.3. Procedures

The university Institutional Review Board approved all procedures. Participants were recruited from introductory psychology courses at a university in the Pacific Northwest for a study about “drinking and sexual behaviors.” Of 674 women who completed a screening survey, 264 were eligible (i.e., female students aged 18 to 20 who reported 1+ HED episode in the past month) and enrolled in the larger trial, which involved completing a baseline survey then being randomly assigned to either: 1) full assessment control; 2) minimal assessment control; 3) alcohol intervention; 4) SARR intervention; or 5) combined alcohol and SARR intervention (Gilmore et al., 2015). Questions about study experience were completed after the baseline assessment (for those in the assessment-only conditions) or after the intervention (for those in the intervention conditions).

2.3.1. Alcohol intervention

Developed by Neighbors et al. (2010), this intervention was designed to reduce drinking among college students using personalized normative feedback and alcohol education. Components included psychoeducation and personalized information about blood alcohol content, alcohol-related negative consequences, drinking protective behavioral strategies, and perceived drinking normative feedback.

2.3.2. SARR intervention

This intervention included components on psychoeducation and personalized information on perceived rates of sexual assault, resistance strategy choice and risk perception to a sexual assault scenario, self-protective strategies, and local resources if assaulted.

2.3.3. Combined alcohol and SARR intervention

Components of both the alcohol and SARR interventions were included in this intervention and integrated where possible. For example, alcohol-involved sexual assault statistics were presented in the sexual assault psychoeducation.

2.4. Data Analyses

Across all aims, chi-square tests (except when cell sizes fell below n = 5) and between-group analyses of variance (ANOVAs) were used to evaluate group differences in dichotomous and continuous outcomes, respectively. Pairwise comparisons were made using Fisher’s least significant difference method. Descriptive statistics and group differences were examined using SPSS v.24. Tetrachoric correlations between dichotomous variables were computed in Mplus v.8 (Muthén & Muthén, 2017).

3. Results

3.1. Descriptive Statistics

Descriptives and intercorrelations are presented in Table 1. There were no significant correlations among time spent on the intervention, distraction, and comfort, suggesting these outcomes merit separate investigation. Across all conditions, 224 (84.8%) initiated the postsurvey, including 117 (75.0%) of those in intervention conditions (indicating completion of intervention). There were no differences in intervention completion by condition, χ2(2) = 2.65, p = .266 (see Table 2). Intervention time varied greatly after eliminating outliers1 (defined as values 2.5 times the Median Absolute Deviation above or below the median for each intervention; Leys et al., 2013), with the least time spent on the SARR intervention and the most time on the combined intervention, F(2, 108) = 22.36, p < .001. Average times (see Table 2) suggest the alcohol and combined interventions appeared to be completed as designed, though the SARR intervention was completed faster than expected. Participants reported low levels of distraction (44.8% reporting no distraction at all), regardless of condition, F(4, 216) = 1.36, p = .249. Participants in the alcohol intervention reported less comfort than those in the minimal assessment, SARR, and combined condition, F(4, 215) = 3.41, p = .010.

Table 1.

Descriptive Statistics and Correlations among Study Variables.

n M (SD) or
n (%)		 Correlations
1 2 3 4 5 6 7
1. Age 261 18.78 (0.74)
2. Heavy episodic drinking frequency 264 4.48 (4.41) −.08
3. Any sexual victimization 264 160 (60.6%) .03 .12*
4. Completed intervention 264 224 (84.8%) .08 −.08 .01
5. Minutes spent on intervention (outliers removed) 111 4.84 (3.31) .01 .06 .10 n/a
6. Distraction 221 2.10 (1.32) .01 −.04 .10 n/a .02
7. Comfort 220 4.61 (2.32) −.02 .10 .10 n/a .07 −.03
8. Any substances during participation 221 19 (8.6%) −.01 .01 −.19 n/a −.12 −.11 .10
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Note: M = mean; SD = standard deviation. All dichotomous variables are coded such that 0 = No and 1 = Yes. Tetrachoric correlations between dichotomous variables were computed in Mplus. Minutes Spent on Intervention is only reported for participants assigned to an intervention condition who completed the intervention. Data for variables 6 through 8 were only available for those who completed the intervention (i.e., Completed Intervention = 1).

*

p< .05;

**

p< .01

Table 2.

Group Differences in Engagement and Comfort.

Condition Omnibus tests
across
conditions
Minimal
Assessment
(n = 53)		 Full
Assessment
(n = 54)		 Alcohol
Use
(n = 53)		 Sexual
Assault
Risk
Reduction
(n = 52)		 Combined


(n = 52)
Completed intervention n/a n/a 43 (81.1%) 39 (75.0%) 35 (67.3%) χ2(2) = 2.65
  No prior sexual assault n/a n/a 16 (80.0%) 14 (77.8%) 15 (65.2%) χ2(2) = 1.42
  History of sexual assault n/a n/a 27 (81.8%) 25 (73.5%) 20 (69.0%) χ2(2) = 1.42
Time outliers n/a n/a 0 (0%) 4 (10.3%) 2 (5.7%) (cell sizes too small)
Minutes on intervention (outliers removed) n/a n/a 4.38 (2.49)a 2.97 (1.25)a 7.42 (4.10)a F(2, 108) = 22.36***
Distraction 1.85 (1.10) 2.33 (1.48) 2.30 (1.20) 2.10 (1.55) 1.89 (1.21) F(4, 216) = 1.36
  No prior sexual assault 1.64 (1.05) 2.33 (1.43) 1.86 (1.10) 1.64 (1.08) 2.13 (1.55) F(4, 81) = 1.13
  History of sexual assault 2.00 (1.13) 2.33 (1.53) 2.54 (1.21) 2.36 (1.73) 1.70 (0.87) F(4, 130) = 1.44
  Heavy episodic drinking:
    Less than once a week 2.00 (1.09) 2.29 (1.41) 2.30 (1.33) 1.79 (1.10) 2.05 (1.43) F(4, 124) = 0.71
    At least once a week 1.68 (1.11)a 2.38 (1.58) 2.31 (0.95) 2.60 (2.03)a 1.62 (0.65) F(4, 87) = 1.83
Comfort 5.02 (2.25)a 4.22 (2.35) 3.68 (2.42)abc 5.10 (2.16)b 5.12 (2.10)c F(4, 215) = 3.41*
  No prior sexual assault 4.68 (2.51) 3.71 (2.22)a 3.36 (2.47)b 4.00 (2.75)c 5.80 (2.18)abc F(4, 81) = 2.47
  History of sexual assault 5.26 (2.05)a 4.55 (2.40)b 3.85 (2.43)ac 5.72 (1.49)bc 4.58 (1.92) F(4, 129) = 3.04*
  Heavy episodic drinking:
    Less than once a week 4.82 (2.45) 3.79 (2.41) 3.89 (2.46) 5.08 (2.32) 4.86 (2.20) F(4, 123) = 1.67
    At least once a week 5.24 (2.03)a 4.69 (2.22)b 3.23 (2.39)abcd 5.13 (1.96)c 5.54 (1.94)d F(4, 87) = 2.56*
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Note: Means (standard deviations) or n (%) are presented. Cell sizes vary slightly due to missing data. Values in a given row with the same superscript are significantly different. Bold, italicized values within a column are significantly different.

*

p < .05,

**

p < .01,

***

p < .001

3.2. Personal Relevance

3.2.1. Sexual assault history

SA history (60.6% in the current sample) was not associated with intervention completion or distraction across conditions (Table 2). Participants with a SA history reported more comfort in the SARR intervention than the alcohol or full assessment conditions, and more comfort in the minimal assessment than the alcohol intervention, F(4, 129) = 3.04, p = .020. Participants without a SA history reported significantly more comfort in the combined intervention than the full assessment, alcohol, or SARR conditions, though this omnibus test did not rise to significance, F(4, 81) = 2.47, p = .051. Within the SARR intervention, those with a SA history reported significantly more comfort than those without, F(1, 37) = 6.50, p = .015.

3.2.2. Alcohol use

HED frequency was not associated with intervention completion, completion time, distraction, or comfort (Table 1). To evaluate differences across conditions, HED frequency was dichotomized at the median (=2.5; or “2–3 times in the past month”). Omnibus tests revealed no differences in distraction across conditions. However, participants who drank at least once a week reported being least comfortable in the alcohol condition, F(4, 87) = 2.56, p = .044 (Table 2).

3.3. Context

3.3.1. Setting

Most participants (87.6%) completed the survey in private, of which 73.3% were alone. Participants with time outliers were relatively evenly distributed across conditions (Table 3). Participants reported more distraction when in private with someone than in private alone or in public, F(2, 215) = 3.52, p = .031. Setting was not associated with differences in comfort, F(2, 214) = 0.97, p = .383.

Table 3.

Engagement and Comfort by Context.

Time outliers
n (%)		 Distraction
M (SD)		 Comfort
M (SD)
Setting
  Private alone (n = 140) 2 (2.6%) 1.99 (1.26)a 4.46 (2.42)
  Private with someone (n = 51) 3 (12.0%) 2.53 (1.59)ab 4.82 (2.24)
  Public (n = 27) 1 (10.0%) 1.89 (1.01)b 5.04 (1.85)
F(2, 215) = 3.52* F(2, 214) = 0.97
Substances during intervention
  None (n = 202) 5 (4.9%) 2.14 (1.33) 4.56 (2.33)
  Any alcohol (n = 19) 1 (8.3%) 1.63 (1.21) 5.39 (1.98)
F(1, 218) = 2.61 F(1, 217) = 2.16
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Note: M = mean; SD = standard deviation. Values with the same superscript are significantly different.

*

p < .05

3.3.2. Substances

Nearly all participants (91.4%) denied substance use during the study. However, some reported being under the influence of alcohol (7.7%) or alcohol and marijuana (0.9%). Only one participant who used substances had a time outlier. Substance use was not associated with distraction, F(1, 218) = 2.61, p = .108, or comfort, F(1, 217) = 2.16, p = .144.

4. Discussion

When female college student drinkers under the age of 21 – a group at risk for alcohol use and SA – were asked to complete web-based alcohol and SARR interventions, the majority were comfortable, not distracted, in a private location, not under the influence of substances, and were engaged enough to complete the intervention. Those with a SA history reported most comfort in the SARR intervention, whereas those with more frequent HED were least comfortable in the alcohol intervention. However, participants appeared to tolerate mild discomfort well, as most participants completed the intervention, which has been associated with benefits to participants (Gilmore et al., 2015).

College women without a SA history reported the most comfort when they received personalized feedback about both alcohol and SARR. These women may recognize that college women are generally at risk for negative consequences associated with alcohol including SA (Krebs et al., 2016) and therefore may be comfortable receiving broadly applicable feedback. Contrary to expectations, participants with a SA history reported most comfort in the SARR intervention. The SARR may have been more comfortable for women with a SA history to complete (than those without) given that these women might be accustomed to considering their risk for a future assault, might already be making efforts to protect themselves, and may appreciate recommendations for SARR.

As hypothesized, participants in the alcohol intervention were significantly less comfortable than those in the assessment, SA, and combined conditions. Moreover, this effect was driven by participants with higher HED frequency; women with HED less than once a week were equally comfortable across conditions, whereas women with HED once a week or more were least comfortable in the alcohol-only intervention. Such discomfort is not necessarily problematic, as it could motivate positive changes in health-related behaviors.

Participants were instructed to complete the intervention procedures in a private setting while not consuming substances, which was effective for most participants. The rate of completing this study in private and alone (64.2%) was comparable to past personalized feedback interventions (74.5% at home, 76.7% alone; Lewis & Neighbors, 2015). Though the current study found no significant differences in comfort between settings, participants in private with someone, rather than in private alone or public, reported being most distracted.

Although using substances could impact response accuracy and intervention efficacy, substance use was not significantly associated with distraction or comfort in this study. Given that only 19 participants reported substance use in this study, the feasibility of including intoxicated participants should continue to be examined in future studies with more power. However, drinking during participation may signify heightened risk for problematic alcohol use, suggesting these participants could be important to retain in future studies.

4.1. Limitations and Future Directions

This study is not without limitations. Comfort and distraction were each assessed with a single self-report question. Lengthier measures assessing related constructs (e.g., Reaction to Research Participation Questionnaire; Newman, Willard, Sinclair, & Kaloupek, 2001) could be integrated into future evaluations of web-based interventions and supplemented by physiological assessment (e.g., eye tracking for distraction; cortisol sampling for stress/comfort). Additional variables (e.g., day-to-day stress, mental health) that might impact participant engagement and comfort could also be assessed. In addition, Bonferroni corrections were not used in this study given the preliminary nature of this research and because we were not concerned with a universal null hypothesis (Perneger, 1998). More conservative tests may be considered in replication efforts. Finally, this sample consisted primarily of White/Caucasian and Asian/Pacific Islander women, and a larger, more diverse sample should be considered in future studies.

Highlights.

  • Web-based interventions were used to target alcohol misuse and sexual assault (SA)

  • Engagement and comfort were assessed in college students

  • Most participants completed the intervention as intended (while sober, in private)

  • Frequent drinkers were least comfortable in the alcohol intervention

  • Women with a SA history were most comfortable in the SA risk reduction intervention

Acknowledgments

Role of Funding Sources

Data collection for this research was supported by grants from the National Institute on Alcohol Abuse and Alcoholism (F31AA020134) and the Alcohol and Drug Abuse Institute at the University of Washington (ADAI-0311-2) and manuscript preparation was partially supported by a grant from the National Institute on Drug Abuse (K23DA042935) awarded to the last author (AG).

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Contributors

The study was designed by AG and WG. Analyses were conducted by AJ and KB. All authors have contributed to and approved the final manuscript.

Conflict of Interest

All authors declare that they have no conflict of interest.

A portion of these results were presented at the 2016 annual meeting of the American Psychological Association in Denver, CO.

1

Four outliers were identified in the SARR condition (9.75, 11.20, 12.15, and 20.07 minutes) and two outliers were identified in the combined condition (108.30 and 289.28 minutes). After removing these outliers, time ranged from 0.63 to 8.85 minutes for the alcohol intervention, 1.00 to 5.87 minutes for the SARR intervention, and 2.33 to 15.40 minutes for the combined intervention.

References

  1. Couper MP, Alexander GL, Zhang N, Little RJ, Maddy N, Nowak MA, Johnson CC. Engagement and retention: Measuring breadth and depth of participant use of an online intervention. Journal of Medical Internet Research. 2010;12(4):e52. doi: 10.2196/jmir.1430. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Danaher BG, Seeley JR. Methodological issues in research on Web-based behavioral interventions. Annals of Behavioral Medicine. 2009;38:28–39. doi: 10.1007/s12160-009-9129-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Eysenbach G. The law of attrition. Journal of Medical Internet Research. 2005;7(1):e11. doi: 10.2196/jmir.7.1.e11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Gilmore AK, Lewis MA, George WH. A randomized controlled trial targeting alcohol use and sexual assault risk among college women at high risk for victimization. Behaviour Research and Therapy. 2015;74:38–49. doi: 10.1016/j.brat.2015.08.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Kilmer JR, Cronce JM, Larimer ME. College student drinking research from the 1940s to the future: Where we have been and where we are going. Journal of Studies on Alcohol & Drugs. 2014;75(Suppl 17):26–35. doi: 10.15288/jsads.2014.s17.26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Koss MP, Abbey A, Campbell R, Cook S, Norris J, Testa M, White J. Revising the SES: A collaborative process to improve assessment of sexual aggression and victimization. Psychology of Women Quarterly. 2007;31:357–370. doi: 10.1111/j.1471-6402.2007.00385.x. [DOI] [Google Scholar]
  7. Krebs C, Lindquist C, Berzofsky M, Shook-Sa B, Peterson K, Planty M, Widico-Stroop J. Campus climate survey validation study: Final technical report. US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics; 2016. [Google Scholar]
  8. Lewis MA, Neighbors C. An examination of college student activities and attentiveness during a web-delivered personalized normative feedback intervention. Psychology of Addictive Behaviors. 2015;29:162–167. doi: 10.1037/adb0000003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Leys C, Ley C, Klein O, Bernard P, Licata L. Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median. Journal of Experimental Social Psychology. 2013;49:764–766. doi: 10.1016/j.jesp.2013.03.013. [DOI] [Google Scholar]
  10. Muthén LK, Muthén BO. Mplus user’s guide. 8. Los Angeles, CA: Muthén & Muthén; 1998–2017. [Google Scholar]
  11. Murray E, White IR, Varagunam M, Godfrey C, Khadjesari Z, McCambridge J. Attrition revisited: Adherence and retention in a web-based alcohol trial. Journal of Medical Internet Research. 2013;15(8):e162. doi: 10.2196/jmir.2336. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. National Institute on Alcohol Abuse and Alcoholism. Planning alcohol interventions using NIAAA’s CollegeAIM Alcohol Intervention Matrix. Bethesda, MD: 2015. NIH Publication No. 15-AA-8017. Available at collegedrinkingprevention.gov/CollegeAIM. [Google Scholar]
  13. Neighbors C, Lewis MA, Atkins DC, Jensen MM, Walter T, Fossos N, Larimer ME. Efficacy of web-based personalized normative feedback: A two-year randomized controlled trial. Journal of Consulting and Clinical Psychology. 2010;78:898–911. doi: 10.1037/a0020766. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Newman E, Willard T, Sinclair R, Kaloupek D. Empirically supported ethical research practice: The costs and benefits of research from the participants’ view. Accountability in Research. 2001;8:309–329. doi: 10.1080/08989620108573983. [DOI] [PubMed] [Google Scholar]
  15. Perneger TV. What’s wrong with Bonferroni adjustments. BMJ: British Medical Journal. 1998;316:1236–1238. doi: 10.1136/bmj.316.7139.1236. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. White HR. Reduction of alcohol-related harm on United States college campuses: The use of personal feedback interventions. International Journal of Drug Policy. 2006;17:310–319. [Google Scholar]
  17. White A, Hingson R. The burden of alcohol use: Excessive alcohol consumption and related consequences among college students. Alcohol Research: Current Reviews. 2014;35:201–218. [PMC free article] [PubMed] [Google Scholar]

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