Personality and Substance Use Behaviors Associations of the Big Five traits with adolescent substance use, demonstrated through analysis of the MOFAM data.

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Personality and Substance Use Behaviors Associations of the Big Five traits with adolescent substance use, demonstrated through analysis of the MOFAM data set By: Zia Choudhury Mentors: Dr. Bucholz, Dr. Duncan, Dr. Grant

What are the Big Five? Descriptive model of personality using 5 overarching clusters of traits, or “Factors” Openness to experience → novelty-seeking, preference for variety Conscientiousness → highly deliberate, self-disciplined Extraversion → gregarious, excitement-seeking Agreeableness → considerate, cooperative Neuroticism → anxious, emotionally unintelligent Each factor encompasses many traits e.g.) Agreeableness High on A → Cooperative: i.e. empathetic, trusting, deferent in social situations Low on A → Competitive: i.e. suspicious of others, Machiavellian Empirically discovered through brute force factor analysis of known traits Seen as more descriptive than predictive Factors are too broad, more specific trait measures generally better at modeling behavior

MOFAM approach and significance Designed to be comparable to twin-family studies Epidemiological sample of families, i.e. using Missouri birth records Phone interview and self-assessment questionnaire covering SU topics, psychiatric info, family environment, etc (personality assessment included in SAQ only) Index children aged 13, 15, 17, or 19 at first interview Prospective design, offspring interviewed every 2 years Intentional oversample of African American families High risk sampling design Designated high risk (HR) if mother reports child’s father as excessive drinker at a screening interview; otherwise low risk (LR) Designated recurrent drunk driving (RDD) if father has 2 or more DUI’s on driving record RaceEAAATotal LR HR RDD Total RaceEAAATotal LR HR RDD Total Family Enrollment Adolescent Enrollment Note: approx 380 adolescents submitted SAQ’s with incomplete information (most notably in the personality sections) or failed to submit an SAQ at all; those adolescents were omitted from the analysis

Personality assessed with an 60 item questionnaire 12 items for each factor Items were statements about the subject to which the subject gave an agree score on a 5-point Likert scale e.g. “I often feel tense and jittery” 1-strongly disagree, 2-disagree, 3-neutral, 4-agree, 5-strongly agree Scores for the 12 items of each factor were summed, respectively N.B. The questionnaire used in the study (i.e. adapted from Costa et. al. (1989)) is only a valid measure of a given factor when all twelve items are answered; thus subjects with missing items were not included in the analyses Range of scores for each factor subdivided into quartiles Dummy variables for each factor quartile were created, indicating whether a subject was high or low on each of the five factors e.g. Subject “x”: O→85 th percentile, C→20 th, E →68 th, A→35 th, N→99 th O →4 th quartile, C→1 st, E→3 rd, A→2 nd, N→4 th  O,  C,  E,  A,  N Methodology 1

Methodology 2 Atheoretical approach 50+ outcome variables based on both the SAQ and interview were initially involved Ranged from exposure variables (e.g. “tried EtOH”) to frequency measures (e.g. “smoked >100 cigarettes”) to problem measures (e.g. “Alcohol Dependence Diagnosis”) Selected outcome variables regressed against personality dummy variables, an African American vs non-AA variable, a high age vs low age variable, the HR and RDD variables, and gender. Personality variables tested against other predictor variables for correlations; personality variables tested against other personality variables for correlations. No significant correlations were found (i.e. all correlations <0.25) Four outcomes of interest: 1.pot_freq: self-assessment of subject’s cannabis use over the past year: 0→no exposure; 1→ exposure, but not in past year; 2→use 50 times in past year 2.cig_freq: self-assessment of subject’s lifetime cigarette use: 0→no exposure; 1→ single exposure; 2→use 100 times 3.Symptoms: interview assessment of the # of AA and AD symptoms from which the subject suffers: 0→no exposure; 1→exposure to EtOH, but no symptoms; 5→ 1 or more symptoms 4.Binge: interview assessment of the subject’s binge drinking over the past year: 0→ no exposure; 1→exposure to EtOH, but no binging in the past year; 2→binge 50 times in past year

Frequency of Cannabis and Cigarette use Variable  Freq Can  Freq Can  Freq Cig  Freq Cig  Agreeableness  Agreeableness  Neuroticism  Extraversion  Age  Age AA Male HR RDD Table of relative risk associations between personality/demographic factors and the frequency of cannabis and cigarette use. “  Freq Can” denotes subjects that are above the 50 times per year threshold for cannabis use, “  Freq Can” denotes subjects below that threshold; “  Freq Cig” denotes subjects that are above the 100 times per lifetime threshold for cigarette use, “  Freq Cig denotes subjects below that threshold. Key + : rr > 1 - : rr < 1 + : p < : p < 0.10 In every model the baseline comparison group is those subjects with 0 exposure to the substance in question.

Presence of AD and AA symptoms and Frequency of Binge Drinking Variable1+ SymNo sym  Freq Binge  Freq Binge  Agreeableness  Agreeableness  Extraversion  Age  Age AA Male HR RDD Table of relative risk associations between personality/demographic factors and the presence of AA and AD symptoms and frequency of binge drinking. “1+ Sym” denotes subjects that have tried alcohol and have at least one symptom of alcohol dependence or alcohol abuse (DSM IV criteria), “No Sym” denotes subjects that have tried alcohol but have no symptoms; “  Freq Binge” denotes subjects that are above the 50 times per year threshold for binge drinking, “  Freq Cig” denotes subjects below that threshold that have binge drank in the past year. Key + : rr > 1 - : rr < 1 + : p < : p < 0.10 In every model, the baseline comparison group is those subjects who have 0 exposure to the substance in question.

Conclusions & Further Questions Assumptions that Big Five not predictative called into question Big Five should be assessed more in-depth in future studies (i.e. logic behind over AA sample in MOFAM) Is Big Five profile indicative of a third variable (e.g. personality pathology)? Change over time?