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Mediational Effects of Sensation Seeking on Adolescent Health Risk Behaviors

E4. White. E2. E3. Neighborhood Quality. Sexual Risk Taking. Risk Proneness. Alcohol Use . Age. E1. Altered Environment. Presaged Intention. Outcome. Perceived Closeness Between Parents . Depressive Symptoms Index. Male. Bronfenbrenner’s Ecological Transition Adolescent.

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Mediational Effects of Sensation Seeking on Adolescent Health Risk Behaviors

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E4 White E2 E3 Neighborhood Quality Sexual Risk Taking Risk Proneness Alcohol Use Age E1 Altered Environment Presaged Intention Outcome Perceived Closeness Between Parents Depressive Symptoms Index Male Bronfenbrenner’s Ecological Transition Adolescent Risk Proneness Adolescent Health Behaviors Bronfenbrenner Macrosystem Self-rated proclivity to engage in sensation seeking Bio (Cognitive Genetic) Psycho (Mental Health) Alcohol Use Sexual Behavior Adolescent Depression (CESD) Sociodemographics 3 Levels Micro(Individual)- -Sociodemographics -Race/Ethnicity -Gender -Depression Index Meso(Family)- -Parenting Scale Exo(Neighborhood) -Neighborhood Quality Scale Depression Sociodemographics Bio Psycho Social (Behavioral) Adolescent Social Child Individual Microsystem Microsystem - Child Individual Family ↓ Parent Quality Mesosystem Mesosystem – Family Parent Quality School Peers Neighborhood Quality ↓ Exosystem Model: Groups Partitioned by Mother’s Educational Attainment School Peers Exosystem - Neighborhood Neighborhood Quality • Adapted from: • Bronfenbrenner, U. (1979). The Ecology of Human Development. Cambridge, MA: Harvard University Press. • Small, S.A. & Luster, T. (1994). Adolescent sexual activity: an ecological risk-factor approach. JMF, 56:1, 181-192. Mediational Effects of Sensation Seeking on Adolescent Health Risk Behaviors by Mother’s Educational Attainment Lynn A. Agre1, N. Andrew Peterson1, James Brady1 1Rutgers University, School of Social Work, New Brunswick, NJ Bronfenbrenner’s Macrosystem/Ecosystem and Health Risk Behaviors: Effect of Altered Ecosystem & Risk Perception on Adolescent Health Behaviors Abstract Bivariate Analysis: Correlations of Predictors and Outcomes • Introduction • This study examines if self-rated risk perception (risk proneness) mediates the effects of health behavior determinants, which include depression, parenting and neighborhood quality on health behaviors. • While peer pressure could be a measure of influence, little research has explored the effect of parental education, especially maternal education as a protective factor/social support mechanism in predicting health behavior outcomes. • This research utilizes a national representative sample, the NLSY 1998 Young Adult cohort, to demonstrate the mediational role of risk proneness – how environment influences cognition – in safeguarding against adolescent deleterious health choices. • Self-rated risk proneness, in conjunction with the psychosocial and environmental factors, is evaluated in path analysis (n=1786) as a mediating step to engaging in alcohol and tobacco use and sexual behavior. • Methods • Examine how mother’s education level as a risk or protective factor/social support mechanism can predict adolescent deleterious or prosocial health behaviors through intergenerational transfer of health. • Apply path analysis to elucidate differences between and within adolescent groups by maternal educational attainment • Identify psychosocial profiles of vulnerable adolescents, at the individual, family and environmental level for targeted intervention strategies. Results • Results reveal that depressive symptoms are an underlying factor in risk proneness (higher sensation seeking likelihood) among white adolescents whose mothers have lower educational attainment, particularly females engaging in concomitant alcohol use and sexual risk taking. • However, depression has no association with risk proneness among African American adolescents whose mothers have higher educational attainment or lower educational attainment. • Yet, path analysis does demonstrate, through temporal ordering, that risk proneness (sensation seeking) is a mediator in the sequence to alcohol use and sexual risk taking among white adolescents of mothers with both higher and lower educational attainment, and among African American adolescents of mothers with lower educational attainment. • These group differences in mother’s educational attainment contribute to the development of targeted community interventions among adolescents in varied neighborhood contexts. • Correlations both significant at p < .01 and .150 and above are listed below: • Alcohol use and sexual risk taking r = .295 • Male and depressive symptoms r = -.188 • White race and neighborhood quality r = .253 • White race and risk proneness r = .208 • Neighborhood quality and depressive symptoms r = -.149; and sexual risk taking r = -.155 • Perceived parental closeness between bio-parents and sexual risk taking r = -.149 • Risk proneness and alcohol use r = .153; sexual risk taking r = .164 Model 1: Fully Saturated; Model2: Bio-Parenting; Model 3: Step-Parenting Univariate Statistics n = 4,648; Demographics of the Sample • Average age of the sample was 16.7 years, with 51.4% male and 48.4% female. • In this 1998 Young Adult Cohort, 69.9% were white, 19.8% were black and 7.2% other (Hispanic and Asian) and 3.1% missing (unidentified race). • Mean scores on the scales were as follows: Neighborhood Quality 20.1; Perceived Parental Closeness Bio-parents12.4; Step-Parents 12.4. Depressive Illness Index 3.4; Risk Proneness 10. Alcohol use 9.4; Sexual Risk Taking 7.3. Group Differences: Model 4: Step-Parents w/Hi Ed; Model 5: Both Bio and Step-parents w/Hi-Ed; Model 6: Bio Parents-Female only; Model 7: Bio-Parents-Black only; Model 8: Bio-Parents/White . Results, Discussion and Conclusions • The consistency of all the fit indices values for each of the 7 models demonstrates the robustness of this model for these data, the 1998 NLSY Young Adult Cohort. The chi-square for each of the models is low and not significant, meaning the model has good fit. • Testing the original primary model on different groups serves to validate not only the consistency of the model, but explain how different attitudes and perceptions can lead to different influences on behavioral health outcomes (such as alcohol use and sexual risk taking), for certain groups of teens by gender, race, and parenting. • Those teens who responded to the step-parenting questions, and with mothers with higher educational attainment, perceived parental closeness has no association with any other variable. Thus, because parenting quality has no influence on adolescent health risk behaviors, mother’s educational attainment emerges as an overriding influence and thus type of social support buffer. • Among female adolescents only, perceived neighborhood quality has no effect on alcohol use. For African Americans, both neighborhood quality and perceived parental closeness between mother and biological father have no relationship with sexual risk taking. Last, the model for white youth, like the a priori model, shows no path from neighborhood quality to alcohol use. • By introducing the weighting technique, particularly with respect to calculation of covariance matrix necessary to execute path analysis, never applied before to these data, in order to normalize against US population, the resulting structural equation model permits making inferences about sub-samples. Therefore, by partitioning the groups by mother’s highest grade completed, mother’s educational attainment can be tested as a protective factor in mitigating the effect of other conflicting determinants on adolescent health risk behavior. • The effects of individual, family and neighborhood quality on adolescent substance use and sexual activity are evaluated to explain the relationship of the individual adolescent to the environmental context and how these factors are associated with co-morbid mental and physical health conditions. • Understanding the mechanisms, such as how depression, sensation seeking, lack of perceived parental closeness (discord on rules) and poorer neighborhood quality elucidate the link to health risk behaviors in situ. References Aneshensel, C.S. (2005). Research in mental health: Social etiology versus social consequences. Journal of Health and Social Behavior, 46 (Sept.), 221-228. Baron, R.M., & Kenny, D.A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic and statistical consideration. Journal of Personality and Social Psychology, 51(6),173-1182. Bronfenbernner, U. (1979). The Ecology of Human Development. Harvard University Press: Cambridge, MA. Oh, H.L., & Scheuren, F.J. (1983) Weighting adjustment for unit non-response. Chap. 3 In Incomplete Data in Sample Surveys. New York, NY: Academic Press. Zuckerman, M. (2007). Sensation Seeking and Risk Behavior. Washington D.C.: American Psychological Association.

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