JOURNAL OF AMERICAN COLLEGE HEALTH, VOL. 62, NO. 7
Major Article
Social Networks, Substance Use, and Mental Health in College Students Michael J. Mason, PhD; Nikola Zaharakis, MS; Eric G. Benotsch, PhD
Abstract. Objectives: The relationship between social network risk (alcohol-using close friends), perceived peer closeness, substance use, and psychiatric symptoms was examined to identify risk and protective features of college students’ social context. Participants: Six hundred and seventy undergraduate students enrolled in a large southeastern university. Methods: An online survey was administered to consenting students. Results: Students with risky networks were at a 10-fold increase of hazardous drinking, 6-fold increase for weekly marijuana use, and 3-fold increase for weekly tobacco use. College students’ who feel very close to their peers were protected against psychiatric symptoms yet were at increased risk for marijuana use. Perceived closeness of peers was highly protective against psychiatric symptoms, adding a natural preventive effect for a population at great risk for mental illness. Conclusions: Results support targeting college students through network-oriented preventive interventions to address substance use as well as mental health.
social force in people’s lives. For example, extensive evidence exists to support the relationship between social networks and health outcomes, such as health status, health behaviors, and health decision-making.1,2 Recent research has thrust social networks into the popular media, with large, longitudinal studies demonstrating the far-reaching influence of distal (3 degrees of separation—your friend’s friend’s friend) network effects on various important issues such as smoking, alcohol use, depression, happiness, and obesity with adults.3 Given these and other important findings regarding the potency of networks, the need exists to increase understanding and application of peer network research across populations.
Keywords: college students, mental health, social networks, substance use
Alcohol and Other Substance Risk Researchers have identified young adulthood as a critical period for substance use, as young adults transition from a social setting with greater parental supervision and control to the freedoms enjoyed while living independently for the first time.4 Studies suggest that young adults are more likely than older adults to engage in heavy episodic drinking. The dangers of excessive alcohol use include increased involvement in fatal vehicle crashes, sexual assault, unprotected sex, violence, property damage, and increased risk of physical and mental health problems such as substance use and suicide.5–7 Young adults in general are at heightened risk for problem drinking and alcohol-related negative sequelae because of their drinking patterns; college students in particular in the United States may be most at risk for alcoholrelated negative consequences because of their higher alcohol use compared with other groups.8,9 Young adults aged 18–24 enrolled full time in college were more likely than their peers not enrolled full time to binge drink (5 or more drinks on 1 occasion) and to engage in hazardous behaviors, such as driving a vehicle while under the influence.8
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nderstanding the function of close friend networks on increasing risk for and protection against adverse outcomes has become important for the study of adolescents and college students. Social networks can be defined as relational ties or linkages between a finite number of people or entities. These links, patterns, and pathways have implications and can be structurally mapped for visual and statistical analysis. However, a close friend network is more than a structural map; it can be considered a window into ones’ values, meaning, beliefs, status, behavioral and health practices, and social roles. It is a complex, dynamic, and interactive system that represents an ongoing Dr Mason and Ms Zaharakis are with the Department of Psychiatry at Virginia Commonwealth University in Richmond, Virginia. Dr Benotsch is with the Department of Psychology at Virginia Commonwealth University in Richmond, Virginia. Copyright Ó 2014 Taylor & Francis Group, LLC 470
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Among full-time college students in 2011, 60.8% were current drinkers, 39.1% were binge drinkers, and 13.6% were heavy drinkers. Among those not enrolled full time in college, these rates were 52.0%, 35.4%, and 10.5%, respectively.10 Even more concerning is the finding that almost 1 in 5 (18.0%) college students have met alcohol abuse or dependency diagnostic criteria in the past year, significantly higher than their non–college-attending peers (15.1%).11 Not only are those enrolled full time in college drinking more than other subgroups, but also the way in which they drink puts them at high risk for alcohol-related problems. Young adults also report high rates of the use of substances other than alcohol. In a recent national survey, pastmonth illicit drug use was highest in individuals aged 18– 25 (21.4%) when compared with youth aged 12–17 (10.1%) and adults 26 and older (6.3%).10 Marijuana use is increasing in this population,10 and almost a quarter of these individuals meet Diagnostic and Statistical Manual of Mental Diseases criteria for a marijuana-use disorder.13 Illicit drug use during the college years is associated both with discontinuous enrollment/dropout and worse employment outcomes upon graduation.13,14 As with alcohol use, marijuana and other illicit drug use also has been associated with negative consequences, including both traffic and nontraffic injuries.15,16
Mental Health in College-Aged Young Adults As with substance use, young adulthood is a critical period to address mental health; nearly three-fourths of all lifetime psychiatric disorders occur by age 24.17 For example, young adults report higher rates of major depressive episodes in the past year (8.2%) than adolescents or adults older than 25 years.18 Depressed young adults have the highest rates of comorbidity with symptoms of suicidal ideation, anxiety, substance use, and other mental illness than any other age group illness.18 Among young adults with serious mental illness, only 43% received mental health treatment compared with 67% of the general adult population.18 Nationally, approximately 8% of young adults felt they needed mental health treatment but did not receive it, compared with 4% of the general adult population. Those who wanted mental health treatment but did not receive it were more likely to smoke cigarettes, use marijuana, meet criteria for marijuana abuse or dependency, and binge drink (4 or more drinks in 2 hours for women or 5 or more drinks in 2 hours for men) compared with recipients of treatment, controlling for income and health insurance.19
Peer Networks in College-Aged Young Adults Peer networks exert important effects on personal substance use and mental health symptoms. Research has consistently demonstrated the negative influences of associations with substance-using peers on adolescents’ own substance use.20 Recent research with young adults indicates social, VOL 62, OCTOBER 2014
genetic, and psychological influences. Research with young adults has demonstrated both selection and influence effects of close peer networks on marijuana use.21 Research also has shown that peer substance involvement heightens the negative impact of genetic influences on young adult substance use.22 Young adults who report being close to their substance-using peers report greater and more persistent alcohol use, whereas those who are close to low-substance-using peers report significantly lower alcohol use.23 The influence of peer networks on mental health symptoms among college students has been less studied to date; however, the available literature suggests that peer influence exerts similar effects on psychiatric problems as on substance use. Among adolescents, researchers have demonstrated that youth report higher levels of psychiatric symptoms (self-harm behaviors) when they believed their peers to also engage in these behaviors.24 The quality of relationships with peers also has been associated with psychiatric symptoms; previous researchers have reported links between closeness in peer relationships and mental health outcomes. In one study of young adults, low friendship security was related to poorer mental health outcomes, including more depressive symptoms.25 Therefore, it is important to understand the complex interplay among peer networks, mental health, and substance use among college students. Based on our previous work and this review, we hypothesized that (1) increased social network risk would be predictive of hazardous drinking, marijuana and tobacco use, and psychiatric symptoms and (2) the effects of network risk would be moderated by gender. METHODS A survey was administered to students enrolled in undergraduate psychology courses at a large southeastern university. Students in psychology courses at the university where the research was conducted are required to either participate in research studies or to complete an alternate assignment of writing a brief paper; most choose to participate in research. Students sign in to an online survey system and select the studies they are interested in; following completion of the study, the system awards course credit to participants automatically while masking participant identities from the researcher. All participating students received academic course credit for completing the survey. All surveys were completed anonymously online via a secure survey system. Data were collected from January to May 2012. A total of 688 participants completed the survey. Participants were told that the survey contained personal questions about drinking habits. All consent procedures were conducted anonymously online, and study procedures and materials were approved by the authors’ university’s Institutional Review Board. Members of all races, ethnicities, and both genders were allowed to participate in the study. Because we were specifically interested in the behaviors of young adults, data analyses were restricted to individuals who were 18–25 years of age, resulting in a sample of 670. 471
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Measures Participants completed a self-administered anonymous survey that assessed demographic information, personal substance use, peer behaviors, and mental health. All records were examined for inconsistencies and invalid responses. Missing data were omitted from analyses. Demographics Participants self-reported their age, gender, race/ethnicity, year in school, sexual orientation, and grade point average (GPA). Personal Substance Use Participants self-reported on the frequency of their use of alcohol, marijuana, and tobacco in the past month. Questions covered marijuana and alcohol use, consequences of substance use, and intention to use substances and were derived from the Centers for Disease Control and Prevention’s Youth Risk Behavior Survey (YRBS).26 The YRBS is designed to determine the prevalence of healthrisk behaviors among high school youth and has shown to be valid and reliable by gender, age, and race/ethnicity.27 Problem Drinking The Alcohol Use Disorders Identification Test (AUDIT)28 was used to identify problem drinking among participants. Participants’ self-reported on 10 items that gathered information about negative consequences related to alcohol use, including feeling guilty or sustaining injuries due to drinking. Responses range from Never to Four or more times a week on a 5-point scale. Items are summed to create a total score ranging from 0 to 40, with higher scores indicating more problem drinking; scores above 8 are considered clinically significant. A large body of research has demonstrated that the AUDIT has good validity and reliability with various populations, including college students.29 Psychiatric Symptomatology Participants completed the depression and anxiety subscales of the Brief Symptom Inventory (BSI-18),30 a wellvalidated measure of symptoms of depression and anxiety that occurred over the past week. Each subscale contained 6 items, with responses ranging from Not at all to Extremely on a 5-point scale. In the present study, we summed these 2 scales to form an aggregate measure of psychiatric symptoms. Scores ranged from 0 to 48, with higher scores indicating worse mental health. Prior research has documented good validity and reliability with a variety of populations, with Cronbach’s alphas ranging from .74 to .84.30 In this sample, the summed scale had adequate internal consistency (a D .92). 472
Social Network Risk Social network risk data were gathered using the Young Adult Social Network Assessment (YASNA), which was adapted from the Adolescent Social Network Assessment.31 The YASNA captures information on participants’ close personal friends who constitute their close peer social networks. Participants are asked questions about their 3 best friends that they spend time with at least monthly. Respondents provide anonymous information regarding frequency (Never to 4 or more times per week) and intensity (number of drinks on typical drinking occasion) of each friend’s alcohol use. Participants are asked if they have used alcohol or substances with each friend (Never to 20 or more times in past 30 days). A total score is created by summing items across friends; these scores can range from 0 to 72, with higher scores indicating greater network risk. Participants also self-reported how close they feel to each friend on a single 3-point item, ranging from Somewhat to Very close; higher scores indicate a greater degree of perceived closeness. The YASNA has acceptable reliability with a Cronbach’s alpha D .79.32
Analytic Plan Descriptive statistics were used to examine participant characteristics, network risk (alcohol use among close friends), perceived peer closeness, substance use, and psychiatric symptoms. Pearson chi-square tests were conducted to examine gender differences on substance use, psychiatric symptoms, network risk, and closeness. Logistic regression was employed to test the direct influence of race, gender, and age on network risk effects on alcohol, marijuana, tobacco use, and psychiatric symptoms. All variables were transformed into dichotomous variables to ease in interpretation. Race was encoded into white D 1 and all other D 0, as whites made up the largest subgroup (50.4%). Post hoc analyses by subgroups (African American, Latino, Asian, and other) did not yield significant differences due to sample size. Age was centered and encoded > 19 D 1 and all other D 0. Nearly 80% of the sample (78%) were either freshmen or sophomores. Therefore, we used a median split to dichotomize the age variable. Gender was encoded into female D 1 and male D 0, and closeness was encoded into close D 1 and not close D 0. Network risk was also encoded into risky D 1 and not risky D 0. Tests of moderation were conducted by creating an interaction term with gender and network risk, based upon research that supports variation of network influence by gender.30,31 We then conducted 4 separate logistic regressions using alcohol, marijuana, tobacco, and psychiatric symptoms as dependent variables, network risk and perceived closeness as predictor variables, and age, race, and gender, as covariates. JOURNAL OF AMERICAN COLLEGE HEALTH
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TABLE 1. Participant Characteristics (N D 670) Variable Gender Male Female Race/Ethnicity White African American Hispanic Asian Other Mean age Substance use AUDIT Marijuana Tobacco Social network risk BSI Closeness
%
M
SD
Min.
Max.
19.6
1.6
18
25
15.8
5.4
0
46
20.4 10.1 2.58
6.7 8.9 .68
9 0 1
42 48 3
39.0 61.0 50.4 20.2 6.4 13.5 9.4
18.1 ( weekly use) 15.7 ( weekly use)
Note. AUDIT D Alcohol Use Disorders Identification Test; BSI D Brief Symptom Inventory.
RESULTS Table 1 indicates that the sample was 61.0% female, 50.4% white, with a mean of 19.6 years of age. The sample reported hazardous alcohol use (AUDIT scores > 8); in addition, 18.1% reported using marijuana weekly and 15.7% tobacco weekly. Participants had a mean network risk of 20.4 from a range of 9 to 42, and a mean score of 10.1 for the BSI-18 (depression and anxiety scales), with a range from 0 to 48. Pearson chi-square tests between gender and substance use, psychiatric symptoms, network risk, and closeness revealed gender differences with tobacco use, x2(1, N D 724) D 20.49, p < .001, and closeness, x2(1, N D 724) D 210.41, p < .001, with females using more tobacco and perceiving more closeness compared with males. Table 2 provides results for the 3 logistic regression models run for each substance. For alcohol use, endorsing network risk (close friends that use alcohol) increased the odds of hazardous drinking (AUDIT score of 8 or more) 10-fold compared with those young adults who do not have risky networks. For marijuana use, endorsing network risk increased the odds of using marijuana 6-fold, and perceived peer closeness was also associated with increased marijuana use. For tobacco use, endorsing network risk increased the odds of using tobacco 3-fold. Being white significantly increased the risk for tobacco use, whereas being female also increased the risk of using tobacco. A marginally significant (p D .057) interaction effect was found, with gender moderating the effect of network risk on tobacco use, such that gender interacted with network risk to moderate the likelihood of using tobacco. Table 3 shows that for psychiatric symptoms, perceived peer closeness reduced the risk of psychiatric symptoms VOL 62, OCTOBER 2014
compared with young adults who did not perceive being close to their peers. No significant interaction effects were found for gender and network risk on psychiatric symptoms. COMMENT These findings extend the social network literature into the college student age group by confirming that those who have close friends who consume alcohol are at increased risk for hazardous levels of alcohol consumption, and weekly marijuana and cigarette use. These findings support that close association with users of alcohol has a generalizing effect to the use of other substances. In particular for alcohol, the effect of having drinking peers not only increases drinking, but also increases the odds of the college student being classified as a hazardous drinker. As assumed, having drinking peers was associated with increased risk of marijuana use. Further, perceived peer closeness also was associated with increased marijuana use. Relational closeness is a marker for the quality of the relationship (trust, reciprocity, etc) that contributes to the social influence of substance use, and in particular marijuana. Marijuana was found to be a more influential substance compared with alcohol and tobacco, meaning that peer effects were the strongest associated with marijuana use.32 The unique relationship between peer effects and marijuana use may arise from the fact that marijuana is still illegal in most states and therefore carries a stronger risk compared with alcohol and tobacco. A certain degree of peer closeness is likely required in order to transmit opportunity to engage in marijuana use, thus possibly implicating closeness as a social mechanism for marijuana uptake. To be sure, it is not the case that closeness among peers by itself 473
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TABLE 2. Demographics, Social Network Risk, and Perceived Closeness on Substance Use Risk (N D 670) Model 1 Variable Alcohol White Age Female Closeness Network risk Female £ Network Risk Constant Nagelkerke R2 Marijuana White Age Female Closeness Network risk Female £ Network Risk Constant Nagelkerke R2 Tobacco White Age Female Closeness Network risk Female £ Network Risk Constant Nagelkerke R2
Model 2
Model 3
OR
95% CI
OR
95% CI
OR
95% CI
1.96** 1.28 0.78
1.26, 3.05 0.78, 2.09 0.51, 1.20
1.23 1.10 0.85 1.15 19.7***
0.76, 2.00 0.65, 1.85 0.53, 1.34 0.72, 1.82 7.84, 49.4
1.16 1.01 0.25 1.07 10.6*** 3.79
0.74, 1.83 0.61, 1.67 0.46, 1.42 0.69, 1.66 3.67, 30.6 0.64, 22.2
0.13*** .033 1.67** 1.11 0.81
0.16*** .239
1.21, 2.30 0.75, 1.63 0.59, 1.13
1.10 .955 0.80 1.82** 4.69***
0.483*** .026 2.37*** 0.92 0.51***
0.77, 1.57 0.63, 1.44 0.56, 1.15 1.28, 2.59 3.23, 6.83 0.185*** .189
1.68, 3.34 0.61, 1.39 0.36, 0.71
1.70** 0.78 0.50*** 1.23 5.47***
0.438*** .087
1.17, 2.47 0.50 1.22 0.35, 0.72 0.85 1.78 3.63 8.23 0.168*** .234
1.09 .966 1.17 1.82** 6.61*** 0.58
1.71** 0.77 0.28*** 1.24 3.63*** 2.22
0.26*** .241
0.76, 1.56 0.63, 1.46 0.61, 2.24 1.28, 2.58 3.51, 12.4 0.27, 1.26
0.145*** .192
1.17, 2.49 0.50, 1.20 0.13, 0.57 0.85, 1.80 2.05, 6.43 .977, 5.05
0.223*** .241
Note. OR D odds ratio; CI D confidence interval. * p < .05; **p < .01; ***p < .001.
is associated with increased marijuana use, rather, it is the feelings of closeness among marijuana-using friends that contributes to the opportunity to use and the social influence of marijuana use.
Tobacco use was also associated with network risk among the current sample of college students, yet gender and race were only significant in the tobacco models and not with alcohol or marijuana. It is plausible that the social
TABLE 3. Demographics, Social Network Risk, and Perceived Closeness on Risk of Psychiatric Symptoms (N D 670) Model 1 Variable Psychiatric symptoms White Age Female Closeness Network risk Female £ Network Risk Constant Nagelkerke R2
Model 2
Model 3
OR
95% CI
OR
95% CI
OR
95% CI
1.10 0.84 1.17
16.11, 2.03 0.39, 1.78 0.63, 2.17
1.16 0.84 1.33 0.42* 1.47
0.62, 2.16 0.39, 1.80 0.71, 2.50 0.21, 0.83 0.79, 2.76
1.16 0.83 0.93 0.42* 0.96 1.79
0.63, 2.16 0.38, 1.78 0.34, 2.52 0.21, 0.84 0.58, 1.57 0.50, 6.35
0.069*** .002
0.066*** .031
0.084*** .034
Note. OR D odds ratio; CI D confidence interval. * p < .05; **p < .01; ***p < .001.
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influence dynamic among close friends with females is different compared with males, and that this difference is associated with increased tobacco use. This finding supports recent research on the varying effects of peer influence by gender and substance. Mason and colleagues found that white female adolescents were particularly influenced by their peers to use tobacco and marijuana, even controlling for adolescents’ own perceptions of substance use risk.32 Animal studies have also established that female adolescent brains have unique reward pathways and neural development expressions regarding nicotine use, in particular within the context of social stress, making females especially vulnerable to tobacco dependence.33,34 Although our interaction model with Gender £ Network risk on tobacco was marginally significant (p D .057), it provides promise for future research. The risk of psychiatric symptoms was associated with perceived peer closeness, in that for those students who perceive to be close to their personal network peers, psychiatric symptoms were strongly reduced. There were no gender differences with psychiatric symptoms, and so this finding appears to be equally relevant for males and females. It is logical that peer closeness is related to peer acceptance, that both are bidirectionally related to each other. Peer acceptance has been shown to be associated with improved mental health, providing support for the present study’s findings.35 This peer-based mechanism appears to have protective qualities for young adult mental health, during a critical and vulnerable period of development. There are preventive implications from these findings. Targeting social network–based interventions among college students to address substance use would be reasonable. Developing gender- and substance-specific approaches with this population would also make sense based on these findings. For example, targeting females with network-based interventions that examine tobacco use would be particularly salient. Developing an intervention that leverages the importance of peers, their role in health outcomes, and protective qualities of close peer networks would seem to fit well with this socially oriented age group. For example, Mason and colleagues have developed a social network–based intervention that is being used as a text-based delivered intervention for college students.36 This intervention has students answer questions about the level of protection and risk (substance use, illegal, high-risk behaviors) of their peer network and to reflect on ways to make adjustments to their network in order to meet their behavioral goals. Students receive feedback on the specific behaviors of peers (number of substance users, support providers, etc) and have an opportunity to reflect on time spent with peers and their desired college goals. However, because college students are transitioning into adulthood and independence, finding appropriate and sensitive methods to communicate these concepts is critical, so as to not raise defensiveness associated with the idea of peer influence with this population.
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Limitations This study has several limitations that should be noted while interpreting the findings. First, the sample was drawn from an undergraduate university setting and may not apply to young adults not nested within this type of setting. Second, the study was a cross-sectional design, limiting the ability to understand causal effects among our models. Another limitation of these data is the lack of power to further specify racial and ethnic subgroups beyond the broad categories used in our analyses. Future analyses using smaller subgroupings would be helpful to examine racial and ethnic group variation. In addition, future work would benefit from more detailed assessment of some of the constructs measured only briefly in the present study. In particular, more detailed assessment of network risk and protection as well as more detail on the quality of peer closeness variable is warranted. For example, we assessed perceptions of peer relationship closeness and perceptions of peer substance use. Creating a complete network design where peers could all report on the status of their relationship as well as report their own substance use would increase rigor for this type of study.
Conclusion The present study provides insight into college students who have risky social networks to reveal that they are at increased risk not only for hazardous alcohol use, but also for weekly marijuana and tobacco use as well. Perceived closeness of peers was highly protective against psychiatric symptoms, adding a natural preventive effect for a population at great risk for mental illness. Results support targeting young adults through network-oriented preventive interventions to address substance use as well as mental health. The present study adds to the college student network literature with specific findings about substances, and network structural components such as closeness, and the association with mental health. Peer-based interventions are not often utilized as fully as possible with college students. Future research on developing interventions that target social context and health would be warranted given these results.
FUNDING No funding was used to support this research and/or the preparation of the manuscript.
CONFLICT OF INTEREST DISCLOSURE The authors have no conflicts of interest to report. The authors confirm that the research presented in this article met the ethical guidelines, including adherence to the legal requirements, of the United States and received approval
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from the Institutional Review Board of Virginia Commonwealth University.
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non-traffic injuries. Acid Anal Prev. 2012;47:172–176. doi: 10.1016/j.aap.2012.01.002. 16. Pulido J, Barrio G, Lardelli P, Bravo MJ, Regidor E, de la Fuente L. Association between cannabis and cocaine use, traffic injuries and use of protective devices. Eur J Public Health. 2011;21:753–755. doi: 10.1093/eurpub/ckq161. 17. Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Arch Gen Psychiatry. 2005;62:593–602. doi: 10.1001/archpsyc. 62.6.593. 18. Substance Abuse and Mental Health Services Administration (SAMHSA). Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: SAMHSA; 2011. NSDUH series H-41, HHS publication no. (SMA) 11-4658. 19. Mason M, Keyser-Marcus L, Snipes D, Benotsch E, Sood B. Needing but not receiving mental health treatment: substance use correlates for young adults. Psychiatr Serv. 2013;65:871–877. 20. Chuang YC, Ennett ST, Bauman KE, Foshee VA. Relationships of adolescents’ perceptions of parental and peer behaviors with cigarette and alcohol use in different neighborhood contexts. J Youth Adolesc. 2009;38:1388–1398. doi: 10.1007/ s10964-009-9424-x. 21. Pinchevsky G, Arria A, Caldeira K, Garnier-Dykstra LM, Vincent KB, O’Grady KE. Marijuana exposure opportunity and initiation during college: parent and peer influences. Prev Sci. 2012;13:43–54. doi: 10.1007/s11121-011-0243-4. 22. Agrawal A, Balasubramanian S, Smith EK, et al. Peer substance involvement modifies genetic influences on regular substance involvement in young women. Addiction. 2010;105:1844– 1853. doi: 10.1111/j.1360-0443.2010.02993.x. 23. Cruz JE, Emery RE, Turkheimer E. Peer network drinking predicts increased alcohol use from adolescence to early adulthood after controlling for genetic and shared environmental selection. Dev Psychol. 2012;48:1390–1402. doi: 10.1037/a0027515. 24. Prinstein MJ, Heilbron N, Guerry JD, et al. Peer influence and nonsuicidal self injury: longitudinal results in community and clinically-referred adolescent samples. J Abnorm Child Psychol. 2010;38:669–682. doi: 10.1007/s10802-010-9423-0. 25. King AR, Terrance C. Best friendship qualities and mental health symptomatology among young adults. J Adult Dev. 2008;15:25–34. doi: 10.1007/s10804-007-9031-6. 26. Centers for Disease Control and Prevention. Youth Risk Behavior Survey. Available at: http://www.cdc.gov/yrbss. Published 2011. Updated January 15, 2013. Accessed July 15, 2013. 27. Brener N, Kann L, Mcmanus T, Kinchen S, Sundberg E, Ross J. Reliability of the 1999 Youth Risk Behavior Survey questionnaire. J Adolesc Health. 2002;31:336–342. 28. Babor TF, Higgings-Biddle JC, Saunders JB, Monteiro MG. The Alcohol Use Disorders Identification Test: Guidelines for Use in Primary Care. Geneva, Switzerland: World Health Organization; 2001. 29. DeMartini KS, Carey KB. Optimizing the use of the AUDIT for alcohol screening in college students. Psychol Assess. 2012;24:954–963. doi: 10.1037/a0028519. 30. Derogatis LR. Brief Symptom Inventory 18, Administration and Scoring Manual. San Antonio, TX: Pearson; 2001. 31. Mason M, Cheung I, Walker L. Substance use, social networks, and the geography of urban adolescents. Subst Use Misuse. 2004;39:1751–1777. doi: 10.1081/LSUM-200033222. 32. Mason M, Mennis J, Linker J, Bares C, Zaharakis N. Peer attitudes effects on adolescent substance use: the moderating role of race and gender. Prev Sci. 2014;15:56–64. doi: 10.1007/ s11121-012-0353-7. 33. Grebenstein P, Burroughs D, Zhang Y, LeSage MG. Sex differences in nicotine self-administration in rats during JOURNAL OF AMERICAN COLLEGE HEALTH
Social Networks, Substance Use, and Mental Health progressive unit dose reduction: implications for nicotine regulation policy. Pharmacol Biochem Behav. 2013;114–115:70–81. doi: 10.1016/j.pbb.2013.10.020. 34. Torres OV, Natividad LA, Tejeda HA, Van Weelden SA, O’Dell LE. Female rates display dose-dependent differences to the rewarding and aversive effects of nicotine in an age-, hormone-, and sex-dependent manner. Psychopharmacology. 2009;206:303–312. doi: 10.1007/s00213-009-1607-3. 35. Birkeland M, Breivik K, Wold B. Peer acceptance protects global self-esteem from negative effects of low closeness to
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parents during adolescence and early adulthood. J Youth Adolesc. 2014;43:70–80. doi: 10.1007/s10964-013-9929-1. 36. Mason M, Benotsch E, Way T, Kim H, Snipes D. Text messaging to increase readiness to change alcohol use in college students. J Prim Prev. 2014;35:47–52. doi: 10.1007/s10935-0130329-9. Received: 9 September 2013 Revised: 28 February 2014
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Major Article
Social Networks, Substance Use, and Mental Health in College Students Michael J. Mason, PhD; Nikola Zaharakis, MS; Eric G. Benotsch, PhD
Abstract. Objectives: The relationship between social network risk (alcohol-using close friends), perceived peer closeness, substance use, and psychiatric symptoms was examined to identify risk and protective features of college students’ social context. Participants: Six hundred and seventy undergraduate students enrolled in a large southeastern university. Methods: An online survey was administered to consenting students. Results: Students with risky networks were at a 10-fold increase of hazardous drinking, 6-fold increase for weekly marijuana use, and 3-fold increase for weekly tobacco use. College students’ who feel very close to their peers were protected against psychiatric symptoms yet were at increased risk for marijuana use. Perceived closeness of peers was highly protective against psychiatric symptoms, adding a natural preventive effect for a population at great risk for mental illness. Conclusions: Results support targeting college students through network-oriented preventive interventions to address substance use as well as mental health.
social force in people’s lives. For example, extensive evidence exists to support the relationship between social networks and health outcomes, such as health status, health behaviors, and health decision-making.1,2 Recent research has thrust social networks into the popular media, with large, longitudinal studies demonstrating the far-reaching influence of distal (3 degrees of separation—your friend’s friend’s friend) network effects on various important issues such as smoking, alcohol use, depression, happiness, and obesity with adults.3 Given these and other important findings regarding the potency of networks, the need exists to increase understanding and application of peer network research across populations.
Keywords: college students, mental health, social networks, substance use
Alcohol and Other Substance Risk Researchers have identified young adulthood as a critical period for substance use, as young adults transition from a social setting with greater parental supervision and control to the freedoms enjoyed while living independently for the first time.4 Studies suggest that young adults are more likely than older adults to engage in heavy episodic drinking. The dangers of excessive alcohol use include increased involvement in fatal vehicle crashes, sexual assault, unprotected sex, violence, property damage, and increased risk of physical and mental health problems such as substance use and suicide.5–7 Young adults in general are at heightened risk for problem drinking and alcohol-related negative sequelae because of their drinking patterns; college students in particular in the United States may be most at risk for alcoholrelated negative consequences because of their higher alcohol use compared with other groups.8,9 Young adults aged 18–24 enrolled full time in college were more likely than their peers not enrolled full time to binge drink (5 or more drinks on 1 occasion) and to engage in hazardous behaviors, such as driving a vehicle while under the influence.8
U
nderstanding the function of close friend networks on increasing risk for and protection against adverse outcomes has become important for the study of adolescents and college students. Social networks can be defined as relational ties or linkages between a finite number of people or entities. These links, patterns, and pathways have implications and can be structurally mapped for visual and statistical analysis. However, a close friend network is more than a structural map; it can be considered a window into ones’ values, meaning, beliefs, status, behavioral and health practices, and social roles. It is a complex, dynamic, and interactive system that represents an ongoing Dr Mason and Ms Zaharakis are with the Department of Psychiatry at Virginia Commonwealth University in Richmond, Virginia. Dr Benotsch is with the Department of Psychology at Virginia Commonwealth University in Richmond, Virginia. Copyright Ó 2014 Taylor & Francis Group, LLC 470
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Among full-time college students in 2011, 60.8% were current drinkers, 39.1% were binge drinkers, and 13.6% were heavy drinkers. Among those not enrolled full time in college, these rates were 52.0%, 35.4%, and 10.5%, respectively.10 Even more concerning is the finding that almost 1 in 5 (18.0%) college students have met alcohol abuse or dependency diagnostic criteria in the past year, significantly higher than their non–college-attending peers (15.1%).11 Not only are those enrolled full time in college drinking more than other subgroups, but also the way in which they drink puts them at high risk for alcohol-related problems. Young adults also report high rates of the use of substances other than alcohol. In a recent national survey, pastmonth illicit drug use was highest in individuals aged 18– 25 (21.4%) when compared with youth aged 12–17 (10.1%) and adults 26 and older (6.3%).10 Marijuana use is increasing in this population,10 and almost a quarter of these individuals meet Diagnostic and Statistical Manual of Mental Diseases criteria for a marijuana-use disorder.13 Illicit drug use during the college years is associated both with discontinuous enrollment/dropout and worse employment outcomes upon graduation.13,14 As with alcohol use, marijuana and other illicit drug use also has been associated with negative consequences, including both traffic and nontraffic injuries.15,16
Mental Health in College-Aged Young Adults As with substance use, young adulthood is a critical period to address mental health; nearly three-fourths of all lifetime psychiatric disorders occur by age 24.17 For example, young adults report higher rates of major depressive episodes in the past year (8.2%) than adolescents or adults older than 25 years.18 Depressed young adults have the highest rates of comorbidity with symptoms of suicidal ideation, anxiety, substance use, and other mental illness than any other age group illness.18 Among young adults with serious mental illness, only 43% received mental health treatment compared with 67% of the general adult population.18 Nationally, approximately 8% of young adults felt they needed mental health treatment but did not receive it, compared with 4% of the general adult population. Those who wanted mental health treatment but did not receive it were more likely to smoke cigarettes, use marijuana, meet criteria for marijuana abuse or dependency, and binge drink (4 or more drinks in 2 hours for women or 5 or more drinks in 2 hours for men) compared with recipients of treatment, controlling for income and health insurance.19
Peer Networks in College-Aged Young Adults Peer networks exert important effects on personal substance use and mental health symptoms. Research has consistently demonstrated the negative influences of associations with substance-using peers on adolescents’ own substance use.20 Recent research with young adults indicates social, VOL 62, OCTOBER 2014
genetic, and psychological influences. Research with young adults has demonstrated both selection and influence effects of close peer networks on marijuana use.21 Research also has shown that peer substance involvement heightens the negative impact of genetic influences on young adult substance use.22 Young adults who report being close to their substance-using peers report greater and more persistent alcohol use, whereas those who are close to low-substance-using peers report significantly lower alcohol use.23 The influence of peer networks on mental health symptoms among college students has been less studied to date; however, the available literature suggests that peer influence exerts similar effects on psychiatric problems as on substance use. Among adolescents, researchers have demonstrated that youth report higher levels of psychiatric symptoms (self-harm behaviors) when they believed their peers to also engage in these behaviors.24 The quality of relationships with peers also has been associated with psychiatric symptoms; previous researchers have reported links between closeness in peer relationships and mental health outcomes. In one study of young adults, low friendship security was related to poorer mental health outcomes, including more depressive symptoms.25 Therefore, it is important to understand the complex interplay among peer networks, mental health, and substance use among college students. Based on our previous work and this review, we hypothesized that (1) increased social network risk would be predictive of hazardous drinking, marijuana and tobacco use, and psychiatric symptoms and (2) the effects of network risk would be moderated by gender. METHODS A survey was administered to students enrolled in undergraduate psychology courses at a large southeastern university. Students in psychology courses at the university where the research was conducted are required to either participate in research studies or to complete an alternate assignment of writing a brief paper; most choose to participate in research. Students sign in to an online survey system and select the studies they are interested in; following completion of the study, the system awards course credit to participants automatically while masking participant identities from the researcher. All participating students received academic course credit for completing the survey. All surveys were completed anonymously online via a secure survey system. Data were collected from January to May 2012. A total of 688 participants completed the survey. Participants were told that the survey contained personal questions about drinking habits. All consent procedures were conducted anonymously online, and study procedures and materials were approved by the authors’ university’s Institutional Review Board. Members of all races, ethnicities, and both genders were allowed to participate in the study. Because we were specifically interested in the behaviors of young adults, data analyses were restricted to individuals who were 18–25 years of age, resulting in a sample of 670. 471
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Measures Participants completed a self-administered anonymous survey that assessed demographic information, personal substance use, peer behaviors, and mental health. All records were examined for inconsistencies and invalid responses. Missing data were omitted from analyses. Demographics Participants self-reported their age, gender, race/ethnicity, year in school, sexual orientation, and grade point average (GPA). Personal Substance Use Participants self-reported on the frequency of their use of alcohol, marijuana, and tobacco in the past month. Questions covered marijuana and alcohol use, consequences of substance use, and intention to use substances and were derived from the Centers for Disease Control and Prevention’s Youth Risk Behavior Survey (YRBS).26 The YRBS is designed to determine the prevalence of healthrisk behaviors among high school youth and has shown to be valid and reliable by gender, age, and race/ethnicity.27 Problem Drinking The Alcohol Use Disorders Identification Test (AUDIT)28 was used to identify problem drinking among participants. Participants’ self-reported on 10 items that gathered information about negative consequences related to alcohol use, including feeling guilty or sustaining injuries due to drinking. Responses range from Never to Four or more times a week on a 5-point scale. Items are summed to create a total score ranging from 0 to 40, with higher scores indicating more problem drinking; scores above 8 are considered clinically significant. A large body of research has demonstrated that the AUDIT has good validity and reliability with various populations, including college students.29 Psychiatric Symptomatology Participants completed the depression and anxiety subscales of the Brief Symptom Inventory (BSI-18),30 a wellvalidated measure of symptoms of depression and anxiety that occurred over the past week. Each subscale contained 6 items, with responses ranging from Not at all to Extremely on a 5-point scale. In the present study, we summed these 2 scales to form an aggregate measure of psychiatric symptoms. Scores ranged from 0 to 48, with higher scores indicating worse mental health. Prior research has documented good validity and reliability with a variety of populations, with Cronbach’s alphas ranging from .74 to .84.30 In this sample, the summed scale had adequate internal consistency (a D .92). 472
Social Network Risk Social network risk data were gathered using the Young Adult Social Network Assessment (YASNA), which was adapted from the Adolescent Social Network Assessment.31 The YASNA captures information on participants’ close personal friends who constitute their close peer social networks. Participants are asked questions about their 3 best friends that they spend time with at least monthly. Respondents provide anonymous information regarding frequency (Never to 4 or more times per week) and intensity (number of drinks on typical drinking occasion) of each friend’s alcohol use. Participants are asked if they have used alcohol or substances with each friend (Never to 20 or more times in past 30 days). A total score is created by summing items across friends; these scores can range from 0 to 72, with higher scores indicating greater network risk. Participants also self-reported how close they feel to each friend on a single 3-point item, ranging from Somewhat to Very close; higher scores indicate a greater degree of perceived closeness. The YASNA has acceptable reliability with a Cronbach’s alpha D .79.32
Analytic Plan Descriptive statistics were used to examine participant characteristics, network risk (alcohol use among close friends), perceived peer closeness, substance use, and psychiatric symptoms. Pearson chi-square tests were conducted to examine gender differences on substance use, psychiatric symptoms, network risk, and closeness. Logistic regression was employed to test the direct influence of race, gender, and age on network risk effects on alcohol, marijuana, tobacco use, and psychiatric symptoms. All variables were transformed into dichotomous variables to ease in interpretation. Race was encoded into white D 1 and all other D 0, as whites made up the largest subgroup (50.4%). Post hoc analyses by subgroups (African American, Latino, Asian, and other) did not yield significant differences due to sample size. Age was centered and encoded > 19 D 1 and all other D 0. Nearly 80% of the sample (78%) were either freshmen or sophomores. Therefore, we used a median split to dichotomize the age variable. Gender was encoded into female D 1 and male D 0, and closeness was encoded into close D 1 and not close D 0. Network risk was also encoded into risky D 1 and not risky D 0. Tests of moderation were conducted by creating an interaction term with gender and network risk, based upon research that supports variation of network influence by gender.30,31 We then conducted 4 separate logistic regressions using alcohol, marijuana, tobacco, and psychiatric symptoms as dependent variables, network risk and perceived closeness as predictor variables, and age, race, and gender, as covariates. JOURNAL OF AMERICAN COLLEGE HEALTH
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TABLE 1. Participant Characteristics (N D 670) Variable Gender Male Female Race/Ethnicity White African American Hispanic Asian Other Mean age Substance use AUDIT Marijuana Tobacco Social network risk BSI Closeness
%
M
SD
Min.
Max.
19.6
1.6
18
25
15.8
5.4
0
46
20.4 10.1 2.58
6.7 8.9 .68
9 0 1
42 48 3
39.0 61.0 50.4 20.2 6.4 13.5 9.4
18.1 ( weekly use) 15.7 ( weekly use)
Note. AUDIT D Alcohol Use Disorders Identification Test; BSI D Brief Symptom Inventory.
RESULTS Table 1 indicates that the sample was 61.0% female, 50.4% white, with a mean of 19.6 years of age. The sample reported hazardous alcohol use (AUDIT scores > 8); in addition, 18.1% reported using marijuana weekly and 15.7% tobacco weekly. Participants had a mean network risk of 20.4 from a range of 9 to 42, and a mean score of 10.1 for the BSI-18 (depression and anxiety scales), with a range from 0 to 48. Pearson chi-square tests between gender and substance use, psychiatric symptoms, network risk, and closeness revealed gender differences with tobacco use, x2(1, N D 724) D 20.49, p < .001, and closeness, x2(1, N D 724) D 210.41, p < .001, with females using more tobacco and perceiving more closeness compared with males. Table 2 provides results for the 3 logistic regression models run for each substance. For alcohol use, endorsing network risk (close friends that use alcohol) increased the odds of hazardous drinking (AUDIT score of 8 or more) 10-fold compared with those young adults who do not have risky networks. For marijuana use, endorsing network risk increased the odds of using marijuana 6-fold, and perceived peer closeness was also associated with increased marijuana use. For tobacco use, endorsing network risk increased the odds of using tobacco 3-fold. Being white significantly increased the risk for tobacco use, whereas being female also increased the risk of using tobacco. A marginally significant (p D .057) interaction effect was found, with gender moderating the effect of network risk on tobacco use, such that gender interacted with network risk to moderate the likelihood of using tobacco. Table 3 shows that for psychiatric symptoms, perceived peer closeness reduced the risk of psychiatric symptoms VOL 62, OCTOBER 2014
compared with young adults who did not perceive being close to their peers. No significant interaction effects were found for gender and network risk on psychiatric symptoms. COMMENT These findings extend the social network literature into the college student age group by confirming that those who have close friends who consume alcohol are at increased risk for hazardous levels of alcohol consumption, and weekly marijuana and cigarette use. These findings support that close association with users of alcohol has a generalizing effect to the use of other substances. In particular for alcohol, the effect of having drinking peers not only increases drinking, but also increases the odds of the college student being classified as a hazardous drinker. As assumed, having drinking peers was associated with increased risk of marijuana use. Further, perceived peer closeness also was associated with increased marijuana use. Relational closeness is a marker for the quality of the relationship (trust, reciprocity, etc) that contributes to the social influence of substance use, and in particular marijuana. Marijuana was found to be a more influential substance compared with alcohol and tobacco, meaning that peer effects were the strongest associated with marijuana use.32 The unique relationship between peer effects and marijuana use may arise from the fact that marijuana is still illegal in most states and therefore carries a stronger risk compared with alcohol and tobacco. A certain degree of peer closeness is likely required in order to transmit opportunity to engage in marijuana use, thus possibly implicating closeness as a social mechanism for marijuana uptake. To be sure, it is not the case that closeness among peers by itself 473
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TABLE 2. Demographics, Social Network Risk, and Perceived Closeness on Substance Use Risk (N D 670) Model 1 Variable Alcohol White Age Female Closeness Network risk Female £ Network Risk Constant Nagelkerke R2 Marijuana White Age Female Closeness Network risk Female £ Network Risk Constant Nagelkerke R2 Tobacco White Age Female Closeness Network risk Female £ Network Risk Constant Nagelkerke R2
Model 2
Model 3
OR
95% CI
OR
95% CI
OR
95% CI
1.96** 1.28 0.78
1.26, 3.05 0.78, 2.09 0.51, 1.20
1.23 1.10 0.85 1.15 19.7***
0.76, 2.00 0.65, 1.85 0.53, 1.34 0.72, 1.82 7.84, 49.4
1.16 1.01 0.25 1.07 10.6*** 3.79
0.74, 1.83 0.61, 1.67 0.46, 1.42 0.69, 1.66 3.67, 30.6 0.64, 22.2
0.13*** .033 1.67** 1.11 0.81
0.16*** .239
1.21, 2.30 0.75, 1.63 0.59, 1.13
1.10 .955 0.80 1.82** 4.69***
0.483*** .026 2.37*** 0.92 0.51***
0.77, 1.57 0.63, 1.44 0.56, 1.15 1.28, 2.59 3.23, 6.83 0.185*** .189
1.68, 3.34 0.61, 1.39 0.36, 0.71
1.70** 0.78 0.50*** 1.23 5.47***
0.438*** .087
1.17, 2.47 0.50 1.22 0.35, 0.72 0.85 1.78 3.63 8.23 0.168*** .234
1.09 .966 1.17 1.82** 6.61*** 0.58
1.71** 0.77 0.28*** 1.24 3.63*** 2.22
0.26*** .241
0.76, 1.56 0.63, 1.46 0.61, 2.24 1.28, 2.58 3.51, 12.4 0.27, 1.26
0.145*** .192
1.17, 2.49 0.50, 1.20 0.13, 0.57 0.85, 1.80 2.05, 6.43 .977, 5.05
0.223*** .241
Note. OR D odds ratio; CI D confidence interval. * p < .05; **p < .01; ***p < .001.
is associated with increased marijuana use, rather, it is the feelings of closeness among marijuana-using friends that contributes to the opportunity to use and the social influence of marijuana use.
Tobacco use was also associated with network risk among the current sample of college students, yet gender and race were only significant in the tobacco models and not with alcohol or marijuana. It is plausible that the social
TABLE 3. Demographics, Social Network Risk, and Perceived Closeness on Risk of Psychiatric Symptoms (N D 670) Model 1 Variable Psychiatric symptoms White Age Female Closeness Network risk Female £ Network Risk Constant Nagelkerke R2
Model 2
Model 3
OR
95% CI
OR
95% CI
OR
95% CI
1.10 0.84 1.17
16.11, 2.03 0.39, 1.78 0.63, 2.17
1.16 0.84 1.33 0.42* 1.47
0.62, 2.16 0.39, 1.80 0.71, 2.50 0.21, 0.83 0.79, 2.76
1.16 0.83 0.93 0.42* 0.96 1.79
0.63, 2.16 0.38, 1.78 0.34, 2.52 0.21, 0.84 0.58, 1.57 0.50, 6.35
0.069*** .002
0.066*** .031
0.084*** .034
Note. OR D odds ratio; CI D confidence interval. * p < .05; **p < .01; ***p < .001.
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influence dynamic among close friends with females is different compared with males, and that this difference is associated with increased tobacco use. This finding supports recent research on the varying effects of peer influence by gender and substance. Mason and colleagues found that white female adolescents were particularly influenced by their peers to use tobacco and marijuana, even controlling for adolescents’ own perceptions of substance use risk.32 Animal studies have also established that female adolescent brains have unique reward pathways and neural development expressions regarding nicotine use, in particular within the context of social stress, making females especially vulnerable to tobacco dependence.33,34 Although our interaction model with Gender £ Network risk on tobacco was marginally significant (p D .057), it provides promise for future research. The risk of psychiatric symptoms was associated with perceived peer closeness, in that for those students who perceive to be close to their personal network peers, psychiatric symptoms were strongly reduced. There were no gender differences with psychiatric symptoms, and so this finding appears to be equally relevant for males and females. It is logical that peer closeness is related to peer acceptance, that both are bidirectionally related to each other. Peer acceptance has been shown to be associated with improved mental health, providing support for the present study’s findings.35 This peer-based mechanism appears to have protective qualities for young adult mental health, during a critical and vulnerable period of development. There are preventive implications from these findings. Targeting social network–based interventions among college students to address substance use would be reasonable. Developing gender- and substance-specific approaches with this population would also make sense based on these findings. For example, targeting females with network-based interventions that examine tobacco use would be particularly salient. Developing an intervention that leverages the importance of peers, their role in health outcomes, and protective qualities of close peer networks would seem to fit well with this socially oriented age group. For example, Mason and colleagues have developed a social network–based intervention that is being used as a text-based delivered intervention for college students.36 This intervention has students answer questions about the level of protection and risk (substance use, illegal, high-risk behaviors) of their peer network and to reflect on ways to make adjustments to their network in order to meet their behavioral goals. Students receive feedback on the specific behaviors of peers (number of substance users, support providers, etc) and have an opportunity to reflect on time spent with peers and their desired college goals. However, because college students are transitioning into adulthood and independence, finding appropriate and sensitive methods to communicate these concepts is critical, so as to not raise defensiveness associated with the idea of peer influence with this population.
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Limitations This study has several limitations that should be noted while interpreting the findings. First, the sample was drawn from an undergraduate university setting and may not apply to young adults not nested within this type of setting. Second, the study was a cross-sectional design, limiting the ability to understand causal effects among our models. Another limitation of these data is the lack of power to further specify racial and ethnic subgroups beyond the broad categories used in our analyses. Future analyses using smaller subgroupings would be helpful to examine racial and ethnic group variation. In addition, future work would benefit from more detailed assessment of some of the constructs measured only briefly in the present study. In particular, more detailed assessment of network risk and protection as well as more detail on the quality of peer closeness variable is warranted. For example, we assessed perceptions of peer relationship closeness and perceptions of peer substance use. Creating a complete network design where peers could all report on the status of their relationship as well as report their own substance use would increase rigor for this type of study.
Conclusion The present study provides insight into college students who have risky social networks to reveal that they are at increased risk not only for hazardous alcohol use, but also for weekly marijuana and tobacco use as well. Perceived closeness of peers was highly protective against psychiatric symptoms, adding a natural preventive effect for a population at great risk for mental illness. Results support targeting young adults through network-oriented preventive interventions to address substance use as well as mental health. The present study adds to the college student network literature with specific findings about substances, and network structural components such as closeness, and the association with mental health. Peer-based interventions are not often utilized as fully as possible with college students. Future research on developing interventions that target social context and health would be warranted given these results.
FUNDING No funding was used to support this research and/or the preparation of the manuscript.
CONFLICT OF INTEREST DISCLOSURE The authors have no conflicts of interest to report. The authors confirm that the research presented in this article met the ethical guidelines, including adherence to the legal requirements, of the United States and received approval
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Mason, Zaharakis, & Benotsch
from the Institutional Review Board of Virginia Commonwealth University.
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parents during adolescence and early adulthood. J Youth Adolesc. 2014;43:70–80. doi: 10.1007/s10964-013-9929-1. 36. Mason M, Benotsch E, Way T, Kim H, Snipes D. Text messaging to increase readiness to change alcohol use in college students. J Prim Prev. 2014;35:47–52. doi: 10.1007/s10935-0130329-9. Received: 9 September 2013 Revised: 28 February 2014
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