The Relationship between Emotional Intelligence and ...

The Relationship between Emotional Intelligence and Abuse of Alcohol, Marijuana, and Tobacco among College Students Edith Claros, Ph.D., MSN, RN School of Nursing Massachusetts College of Pharmacy & Health Sciences & Manoj Sharma, MBBS, MCHES, Ph.D. University of Cincinnati

ABSTRACT This study examined the relationship between emotional intelligence (El), alcohol, marijuana, and tobacco use. A correlation analysis was used to explore the relationship between El and the use of alcohol, marijuana, and tobacco among college students (n - 199). El abilities (perception, utilization, understanding, andregulation ofemotions) were measured in college students who completed the valid and reliable Schutte Self Report Inventory (SSRI), the Alcohol Use Disorders Identification Test (AUDIT), the Fagerström Test for Nicotine Dependence (FTND), and the Marijuana Screening Inventory (MSI). The results demonstrated that El constructs (Perception, Utilization, Regulation, and Management of Emotion) scores were significant predictors of alcohol and marijuana use. An association between the El and cigarette smoking was not supported by this study.

EMOTIONAL INTELLIGENCE AND ABUSE OF ALCOHOL

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BACKGROUND The use of alcohol and illicit substances among youth have been studied by many (Diala, Muntaner, & Walrath, 2004; Dube, Feliti, Dong, Chapman, Giles et al., 2003; Gordon, Kinlock, & Battjes, 2004). Substance abuse in youth contributes to internalizing and other psychosocial impairment that sets the foundation for potential and subsequent drug and alcohol use in adulthood (National Survey on Drug Use and Health [NSDUH], (2006); King, Meehan, Trim, & Chassin, 2007). The National Adolescent Health Information Center (NAHIC, 2007) reported that the use of substances, such as alcohol, marijuana, and cigarettes, has tripled for adolescents and young adults in all racial and ethnic groups. Marijuana, for example, is the most frequently abused illicit drug in the United States, mostly among adolescents 12-years and older. Its use accounts for one third of the most mentioned abused drug in drug-related emergencies in emergency departments nationwide (National Institute on Drug Abuse [NIDA], 2007). Similarly, cigarette smoking among ages 18 to 25 is 39.5% (Substance Abuse and Mental Health Services Administration [SAMHSA], 2005). The early use of illicit drugs increases risky behaviors that can lead to: contracting or transmitting sexually transmitted

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diseases, crime and violence, and chronic substance abuse and dependence (Burrow-Sanchez, 2006; Guiao, Blakemore, & Boswell-Wise, 2004; Miller, Naimi, Brewer, & Everett-Jones, 2007; Nanda, & Konnur, 2006). In the United States between 1998 and 2001, among 18 to 24 year old college students that drank or were binge drinkers, there was a significant increase in deaths, which out proportioned the increase in that population (Hingson, Heeren, Winter, & Weschler, 2005; Weschler, et al, 2002). Similarly, the Centers for Disease Control and Prevention (CDC, 2005) reported that the leading cause of motor vehicle-crash-related deaths among adolescents is associated with alcohol. The yearly cost of substance abuse often includes multiple treatments through medical and detoxification efforts, criminal prosecutions, school dropouts, and lack of productivity (Adrian, 2001; Compton, & Volkow, 2006). Little is known regarding the total cost of substance abuse to the health care system, but the National Drug Intelligence Center (2011) reported the cost of substance use to be at $193 billion in 2007. Researchers continue to explore ways in which to understand the underpinnings of substance abuse (Burrow-Sanchez, 2006; Dooley & Prause, 2006; Hampson, Andrews, & Barckley, 2008;


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HoUist & McBroom, 2006) and other risk behaviors among populations. They have focused attention to the application of social theories (Cooper, May, Soderstrom, & Jarjoura, 2009) and the linkages of theoretical perspectives in human behavior. There is limited research on the theory of emotional intelligence (El) (Bar-On, 2006; Goleman, 1995; Salovey & Mayer, 1990) as it relates to substance use and other risky behaviors among freshmen college students. Mayer and Salovey (1997) defined El as a subset of social intelligence that includes the ability of the individuals to recognize, manage, understand the emotions in others, and to utilize this information to guide their thoughts and actions (Mayer & Salovey, 1997). El principles such as social competence, self-awareness, impulse control, and empathy were identified as necessary characteristics of leaders in the work place, essential to success, and they may provide a framework to safeguard youth against risky behaviors (Bar-On, 2006; Goleman, 1995; Mayer & Salovey, 1997). El has been linked to decreased risk behaviors, improved relationships, and feelings of well-being (Afifi, Cox, & Katz, 2007; Petrides et al., 2006; Schutte et al., 2002). However, research examining the ability to identify, understand, use, and manage

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emotions, and applyfindingsto substance abuse among young adults, is limited. Young adulthood is an important period in which to examine relations between emotions and substance use because: (a) risky behaviors and experimentation that started in adolescence may be prevalent at this time; (b) there is independence ñôm parental control, there are life Stressors including problems at school, with family, and in extracurricular activities, which may generate emotional responses or coping mechanisms that can lead to adverse resolutions including substance use, violence, and other self-destructive behaviors and; (c) promising findings in the literature indicate that individuals with high emotional intelligence preserve positive mood states and self-esteem attributes that help regulate emotions and counteract some of the perils of everyday life (Brackett, Mayer, & Warner, 2004; Schutte, Malouff, Simunek, McKenley, & Hollander, 2002). The use of alcohol, marijuana, and tobacco are most prevalent among young adults. Few studies link emotional intelligence with cigarette smoking and alcohol use (Trinidad & Anderson, 2002; Trinidad, Unger, Chou, Azen, & Anderson, 2004; Trinidad, Unger, Chou, & Anderson, 2005) but do not include marijuana use, thus creating a gap in the literature. This


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Study sought to establish the relationship between emotional intelligence and the use of the three most commonly used substances: alcohol, marijuana, and cigarettes among a college student sample. Purpose of the Study The purpose of this study was to explore the relationship between emotional intelligence and alcohol, marijuana use, and cigarette use among young adults in a selected college student sample, aged 18 to 20 years. Previous research indicated that individuals with high emotional intelligence are more likely to report greater feelings of well-being (Schutte et al, 2002); exhibit greater performance outcomes (Carmeli & Josman, 2006); higher self-esteem (Fernandez-Berrocal et al., 2006); and increased resistance to the use of alcohol and tobacco (Trinidad & Anderson, 2002). This study examined the following research questions: 1. Is there a relationship between emotional intelligence and high risk behaviors of alcohol abuse, marijuana use, and cigarette smoking among young adults aged 18 - 20? 2.

Which emotional intelligence constructs are most influential in predicting high risk behaviors of substance abuse, alcohol, marijuana, and cigarette smoking among young adults?

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METHODS Participants A convenience sample of 199 college students in a Massachusetts urban city, ages 18 to 20 years, male and female of mixed ethnicity, participated in this study. The participants were recruited from the Student Success Center at a community college in a medium-sized metropolitan area after all ethical and proper clearances were obtainedfiômthe research office at the College. IRB permission was obtained and approved for this study. Participants in the study were given an informed consent form. Participants were informed of the proposed use of the data, benefits and risks of participating in the study, and confidentiality rights. Additionally, participants were informed of their right to obtain personal and collective results, once the data had been analyzed. The participants received a coded packet that contained the questionnaires and a copy of the informed consent. The students were informed that the questionnaires would take approximately 30 minutes to complete and that the purpose of these tests was to assess emotional intelligence, and to survey the use of alcohol, marijuana, and tobacco intake. All participants completed the questionnaires at the time given and received


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a $10.00 gift certificate to the college bookstore as a token of their participation in the study. Data Collection Process Students were administered the paper and pencil form of the Schutte Self Report Inventory (SSRI), along with the alcohol use disorders identification test (AUDIT), the Fagerström Test for nicotine dependence (FTND), and the marijuana use assessment scale (MSI). Demographical data were collected separately using the demographics and the Clinical Trial Network (CTN), a brief questionnaire form given to the participants prior to commencing the battery of tests. Instruments Schutte Self Report Inventory (SSRI) The construct of emotional intelligence was measured using the SSRI. The SSRI is comprised of 33 items designed to measure the individual's ability to problem solve situations of emotional charge, using the Salovey and Mayer (1990) model of emotional intelligence. The SSRI is a Likert type scale in which respondents rate themselves regarding emotions, or reactions associated with emotions, on a scale of 1 to 5, with 1 representing "strongly disagree" and 5 representing "strongly agree" (Schutte et a l , 1998, p. 169). The SSRI has been deemed both

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a valid and reliable scale (a = .93) (Brackett & Mayer, 2003, p. 5); (a = .90) as well as a valid and reliable overall score by Gardner and Quaker (2010). Scores on the S SRI were calculated by adding up all scores for items 1 through 33 of the scale. Items 5, 28, and 33 were scored by reversed coding. To reverse code these items, the scores 1 to 5 were changed to 5 to 1; 4 to 2, and 2 to 4. These items indicated lower El competency.

Simply stated, a 5

response to an item meant the opposite of a 5 response to the remaining items on the scale. Scores ranged from a minimum of 33 to a maximum of 165, with the higher score indicating distinctiveness of emotional intelligence. Calculated means and standard deviations from the SSRI in multiple samples of participants provide information of central tendency and distribution for the various groups. In this way, the means from other samples on the total scale score can be compared. Alcohol Use Disorders Identification Test (AUDIT)

The AUDIT is a self-report questionnaire developed by the World Health Organization (WHO) for establishing a standardized tool for the assessment and screening of excessive use of alcohol. There are 10 questions composing three domains: hazardous alcohol use; dependence symptoms; and harmful


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alcohol use (Babor et al., 2001). Each question has a possibility for five responses rangingfiôm0 to 4, indicating "never," "less than monthly," "monthly," and "weekly" (p. 31). Scores on the AUDIT can be obtained by entering a number (based on the participant's response) for each question to the far right column. A total score of 8 or more will indicate hazardous and harmful alcohol use, and possible dependence. The AUDIT internal consistency reliability was tested using the Cronbach's alpha against the seven constructs and was determined to be 0.81. The Marijuana Screening Inventory (MSI)

The MSI is a 31-item marijuana specific screening, paper and pencil scale developed to conform to the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). The scale consists of self-report questions that require "yes" or "no" answers (Alexander & Leung, 2004, p. 328). All "yes" responses are added for all 31 items for a total individual score. The MSI internal consistency reliability was tested using Cronbach's alpha against the seven constructs and determined to be 0.94.

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The Fagerström Test for Nicotine Dependence (FTND) The FTND (Heatherton et al., 1991) is a self-reported sixitem test designed to assess pattems of nicotine use and dependence. Construct validity of the FTND in the literature shows a Cronbach's alpha established at 0.61 and varying in other studies fi-om 0.56 to 0.67 (Richardson & Ratner, 2005, p. 698). The scale has been used for tobacco treatment planning purposes and for prognostic decision-making (Heatherton et al., 1991). The FTND construct validity in this study was .407, well below the acceptable cutoff of .70. Since the construct for this measure has been problematic, historically, and it is still widely used in the literature, it was retained for all inferential analyses in this study. Methods of Data Analysis This study utilized a multiple regression analysis using the SPSS vl5.0 to determine if there were significant relationships between El scores and scores on the substance use and abuse measures. A simultaneous regression was used to determine if there were significant relationships between El scores on the SSRI, and scores on the AUDIT alcohol use scale. Thus, the scores on the clusters of the SSRI were regressed against the total score on the AUDIT. The same statistical procedure was


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Utilized in determining correlations between El scores on the SSRI and scores on the Marijuana Screening Inventory (MSI) and between the scores on the FTND, the nicotine dependence scale. Bivariate correlations were computed through the Pearson product moment correlation coefficient.

RESULTS Demographic data of the study sample revealed that the majority of the sample was male (119, 59.8%). Eighty-one participants (40.7%) were 18 years of age, 63 participants (31.7%) were 19 years of age, and 54 participants (27.1 %) were 20 years of age. Thirty participants (15.1%) indicated ethnicity of Latino (of Spanish) origin. Thirty-seven participants (18.6%) indicated ethnicity as Latino (not of Spanish) origin. Because of the complexity in classifying the diverse identifications within the Hispanic/Latino population living in the U.S. (Amaro & Zambrana, 2000), this category of ethnicity has been combined as one Latino group in this study. Additional demographic characteristics were reported under the classification of race, and included participants from American Indian or Alaskan Native, Asian, Black or African American, Native Hawaiian or Pacific Islander descent, and White.

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Cronbach's alphas to check the internal consistency reliability of the seven variable constructs were used. Cronbach's alpha values for each variable construct are as follows: (a) SSRIperceive = 0.70, (b) SSRI-utilize = 0.66, (c) SSRI-regulate = 0.82, (d) SSRI-manage = 0.68, (e) AUDIT = 0.81, (f) MSI = 0.94 and (g) FTND = -0.52. A Cronbach's alpha value of 0.70 or above was considered acceptable in this study. SSRI-Utilize and SSRI-Manage were close in value to the .70 cutoff and were not of concern for violation of construct reliability in this study. Table 1 summarizes the descriptive statistics for latent variable constructs derived from study instrumentation. Table 2 summarizes the results for the AUDIT scores regressed on the four constructs of the SSRI. One of the constructs SSRI manage is significant. Table 3 summarizes the multiple regression results for MSI scores regressed on independent predictors of SSRI-perceive, SSRI-utilize, SSRIregulate, and SSRI-manage. Regression analysis found that SSRI-perceive was not a statistically significant predictor of the AUDIT score. Low scores on the SSRI-perceive were associated with high-risk behaviors of marijuana use (r = -.172). Likewise, findings indicated that low scores on the SSRI-regulate were associated with high-


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