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Affective decision-making predictive of Chinese adolescent drinking behaviors

Published online by Cambridge University Press:  01 July 2009

LIN XIAO ,
ANTOINE BECHARA ,
L. JERRY GRENARD ,
W. ALAN STACY ,
PAULA PALMER ,
YONGLAN WEI ,
YONG JIA ,
XIAOLU FU  and
C. ANDERSON JOHNSON
LIN XIAO
Affiliation:
Department of Psychology, Brain and Creativity Institute, University of Southern California, Los Angeles, California
ANTOINE BECHARA
Affiliation:
Department of Psychology, Brain and Creativity Institute, University of Southern California, Los Angeles, California
L. JERRY GRENARD
Affiliation:
Department of Health Services, UCLA School of Public Health, Los Angeles, California
W. ALAN STACY
Affiliation:
Institute for Health Promotion and Disease Prevention Research, University of Southern California, Los Angeles, California School of Community and Global Health, Claremont Graduate University, Claremont, California
PAULA PALMER
Affiliation:
Institute for Health Promotion and Disease Prevention Research, University of Southern California, Los Angeles, California School of Community and Global Health, Claremont Graduate University, Claremont, California
YONGLAN WEI
Affiliation:
Chengdu Municipal Center for Disease Control and Prevention, Chengdu, China
YONG JIA
Affiliation:
Chengdu Municipal Center for Disease Control and Prevention, Chengdu, China
XIAOLU FU
Affiliation:
Chengdu Municipal Center for Disease Control and Prevention, Chengdu, China
C. ANDERSON JOHNSON*
Affiliation:
Institute for Health Promotion and Disease Prevention Research, University of Southern California, Los Angeles, California School of Community and Global Health, Claremont Graduate University, Claremont, California
*
*Correspondence and reprint requests to: C. Anderson Johnson, School of Community and Global Health, Claremont Graduate University, 180 E. Via Verde, Suite 100, San Dimas, California 91773. E-mail: andy.johnson@cgu.edu
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Abstract

The goal of the current investigation was to address whether affective decision making would serve as a unique neuropsychological marker to predict drinking behaviors among adolescents. We conducted a longitudinal study of 181 Chinese adolescents in Chengdu city, China. In their 10th grade (ages 15–16), these adolescents were tested for their affective decision-making ability using the Iowa Gambling Task (IGT) and working memory capacity using the Self-Ordered Pointing Test. Self-report questionnaires were used to assess academic performance and drinking behaviors. At 1-year follow-up, questionnaires were completed to assess drinking behaviors, and the UPPS Impulsive Behavior Scale was used to examine four dimensions of impulsivity: urgency, lack of premeditation, lack of perseverance, and sensation seeking. Results indicated that those adolescents who progressed to binge drinking or exhibited consistent binge drinking not only performed poorly on the IGT but also scored significantly higher in urgency compared to those who never or occasionally drank. Moreover, better IGT scores predicted fewer drinking problems and fewer drinks 1 year later after controlling for demographic variables, the previous drinking behaviors, working memory, and impulsivity. These findings suggest that deficits in affective decision making may be important independent determinants of compulsive drinking and potentially addictive behavior in adolescents. (JINS, 2009, 15, 547–557.)

Keywords

Executive functionAffective controlImpulsivityWorking memoryBinge drinkingIowa Gambling Task
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 15 , Issue 4 , July 2009 , pp. 547 - 557
Copyright
Copyright © The International Neuropsychological Society 2009

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References

REFERENCES

Anestis, M.D., Selby, E.A., & Joiner, T.E. (2007). The role of urgency in maladaptive behaviors. Behaviour Research and Therapy, 45(12), 3018–3029.Google Scholar
Aytaclar, S., Tarter, R.E., Kirisci, L., & Lu, S. (1999). Association between hyperactivity and executive cognitive functioning in childhood and substance use in early adolescence. Journal of the American Academy of Child and Adolescent Psychiatry, 38(2), 172–178.Google Scholar
Bar-On, R., Tranel, D., Denburg, N.L., & Bechara, A. (2003). Exploring the neurological substrate of emotional and social intelligence. Brain, 126(Pt 8), 1790–1800.Google Scholar
Bechara, A. (2004). The role of emotion in decision-making: Evidence from neurological patients with orbitofrontal damage. Brain Cognition, 55(1), 30–40.Google Scholar
Bechara, A., Damasio, A.R., Damasio, H., & Anderson, S.W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50(1–3), 7–15.Google Scholar
Bechara, A. & Damasio, H. (2002). Decision-making and addiction (part I): Impaired activation of somatic states in substance dependent individuals when pondering decisions with negative future consequences. Neuropsychologia, 40(10), 1675–1689.CrossRefGoogle ScholarPubMed
Bechara, A., Tranel, D., Damasio, H., & Damasio, A.R. (1996). Failure to respond autonomically to anticipated future outcomes following damage to prefrontal cortex. Cerebral Cortex, 6(2), 215–225.CrossRefGoogle ScholarPubMed
Brown, S.A., McGue, M., Maggs, J., Schulenberg, J., Hingson, R., Swartzwelder, S., Martin, C., Chung, T., Tapert, S.F., Sher, K., Winters, K.C., Lowman, C., & Murphy, S. (2008). A developmental perspective on alcohol and youths 16 to 20 years of age. Pediatrics, 121, S290–S310.Google Scholar
Centers for Disease Control and Prevention. (1999). Behavioral risk factor surveillance system survey questionnaire. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention.Google Scholar
Chaytor, N. & Schmitter-Edgecombe, M. (2004). Working memory and aging: A cross-sectional and longitudinal analysis using a self-ordered pointing task. Journal of the International Neuropsychological Society, 10(4), 489–503.Google Scholar
Colom, R., Rebello, I., Palacios, A., Juan-Espinosa, M., & Kyllonen, P.C. (2004). Working memory is (almost) perfectly predicted by g. Intelligence, 32, 277–296.CrossRefGoogle Scholar
Crone, E.A. & van der Molen, M.W. (2004). Developmental changes in real life decision making: Performance on a gambling task previously shown to depend on the ventromedial prefrontal cortex. Developmental Neuropsychology, 25(3), 251–279.CrossRefGoogle ScholarPubMed
Feldman, L., Harvey, B., Holowaty, P., & Shortt, L. (1999). Alcohol use beliefs and behaviors among high school students. The Journal of Adolescent Health, 24(1), 48–58.Google Scholar
Funahashi, S. (2006). Prefrontal cortex and working memory processes. Neuroscience, 139(1), 251–261.Google Scholar
Giedd, J.N. (2004). Structural magnetic resonance imaging of the adolescent brain. Annals of the New York Academy of Sciences, 1021, 77–85.Google Scholar
Gogtay, N., Giedd, J.N., Lusk, L., Hayashi, K.M., Greenstein, D., Vaituzis, A.C., Nugent, T.F. III, Herman, D.H., Clasen, L.S., Toga, A.W., Rapoport, J.L., & Thompson, P.M. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences of the United States of America, 101(21), 8174–8179.Google Scholar
Goudriaan, A.E., Grekin, E.R., & Sher, K.J. (2007). Decision-making and binge-drinking: A longitudinal study. Alcoholism, Clinical and Experimental Research, 31(6), 928–938.Google Scholar
Grenard, J.L., Ames, S.L., Wiers, R.W., Thush, C., Sussman, S., & Stacy, A.W. (2008). Working memory capacity moderates the predictive effects of drug-related associations on substance use. Psychology of Addictive Behaviors, 22(3), 426–432.Google Scholar
Hooper, C.J., Luciana, M., Conklin, H.M., & Yarger, R.S. (2004). Adolescents’ performance on the Iowa Gambling Task: Implications for the development of decision making and ventromedial prefrontal cortex. Developmental Psychology, 40(6), 1148–1158.CrossRefGoogle ScholarPubMed
Iacono, W.G., Carlson, S.R., Taylor, J., Elkins, I.J., & McGue, M. (1999). Behavioral disinhibition and the development of substance-use disorders: Findings from the Minnesota Twin Family Study. Development and Psychopathology, 11(4), 869–900.Google Scholar
Jarrold, C. & Towse, J.N. (2006). Individual differences in working memory. Neuroscience, 139(1), 39–50.Google Scholar
Johnson, A.C., Palmer, P.H., Chou, C.P., Pang, Z., Zhou, D., Dong, L., Xiang, H., Yang, P., Xu, H., Wang, J., Fu, X., Guo, Q., Sun, P., Ma, H., Gallaher, P.E., Xie, B., Lee, L., Fang, T., & Unger, J.B. (2006). Tobacco use among youth and adults in Mainland China: The China Seven Cities Study. Public Health, 120(12), 1156–1169.CrossRefGoogle Scholar
Johnson, C.A., Xiao, L., Palmer, P., Sun, P., Wang, Q., Wei, Y., Jia, Y., Grenard, J.L., Stacy, A.W., & Bechara, A. (2008). Affective decision-making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in 10th grade Chinese adolescent binge drinkers. Neuropsychologia, 46(2), 714–726.Google Scholar
Johnson, P., Boles, S., & Kleber, H. (2000). The relationship between adolescent smoking and drinking and likelihood estimates of illicit drug use. Journal of Addictive Diseases, 19(2), 75–81.Google Scholar
Johnston, L.D., Driessen, F.M.H.M., & Kokkevi, A. (1994). Surveying student drug misuse: A six-country pilot study. Strasbourg, France: Council of Europe.Google Scholar
Kerr, A. & Zelazo, P.D. (2004). Development of “hot” executive function: The children’s gambling task. Brain Cognition, 55(1), 148–157.Google Scholar
Killgore, W.D. & Yurgelun-Todd, D.A. (2007). Neural correlates of emotional intelligence in adolescent children. Cognitive, Affective & Behavioral Neuroscience, 7(2), 140–151.Google Scholar
Kolbe, L.J., Kann, L., & Collins, J.L. (1993). Overview of the Youth Risk Behavior Surveillance System. Public Health Reports, 108(Suppl 1), 2–10.Google Scholar
Nigg, J.T., Wong, M.M., Martel, M.M., Jester, J.M., Puttler, L.I., Glass, J.M., Adams, K.M., Fitzgerald, H.E., & Zucker, R.A. (2006). Poor response inhibition as a predictor of problem drinking and illicit drug use in adolescents at risk for alcoholism and other substance use disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 45(4), 468–475.CrossRefGoogle ScholarPubMed
O’Doherty, J., Kringelbach, M.L., Rolls, E.T., Hornak, J., & Andrews, C. (2001). Abstract reward and punishment representations in the human orbitofrontal cortex. Nature Neuroscience, 4(1), 95–102.CrossRefGoogle ScholarPubMed
Overman, W.H., Frassrand, K., Ansel, S., Trawalter, S., Bies, B., & Redmond, A. (2004). Performance on the IOWA card task by adolescents and adults. Neuropsychologia, 42(13), 1838–1851.Google Scholar
Oya, H., Adolphs, R., Kawasaki, H., Bechara, A., Damasio, A., & Howard, M.A. III. (2005). Electrophysiological correlates of reward prediction error recorded in the human prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 102(23), 8351–8356.CrossRefGoogle ScholarPubMed
Perry, W., Heaton, R.K., Potterat, E., Roebuck, T., Minassian, A., & Braff, D.L. (2001). Working memory in schizophrenia: Transient “online” storage versus executive functioning. Schizophrenia Bulletin, 27(1), 157–176.Google Scholar
Peterson, J.B., Pihl, R.O., Higgins, D., & Lee, A. (2002). Neurocognitive battery (version 2.0). Deerfield Beach, FL: Examcorp.Google Scholar
Petrides, M. (1995). Impairments on nonspatial self-ordered and externally ordered working memory tasks after lesions of the mid-dorsal part of the lateral frontal cortex in the monkey. The Journal of Neuroscience, 15(1Pt 1), 359–375.CrossRefGoogle ScholarPubMed
Petrides, M., Alivisatos, B., Meyer, E., & Evans, A.C. (1993). Functional activation of the human frontal cortex during the performance of verbal working memory tasks. Proceedings of the National Academy of Sciences of the United States of America, 90(3), 878–882.Google Scholar
Petrides, M. & Milner, B. (1982). Deficits on subject-ordered tasks after frontal- and temporal-lobe lesions in man. Neuropsychologia, 20(3), 249–262.Google Scholar
Stocco, A. & Fum, D. (2008). Implicit emotional biases in decision making: The case of the Iowa Gambling Task. Brain and Cognition, 66(3), 253–259.CrossRefGoogle ScholarPubMed
Thush, C., Wiers, R.W., Ames, S.L., Grenard, J.L., Sussman, S., & Stacy, A.W. (2008). The interactions between implicit and explicit cognition and working memory capacity in the prediction of alcohol use in at-risk adolescents. Drug and Alcohol Dependence, 94(1–3), 116–124.Google Scholar
Wagar, B.M. & Dixon, M. (2006). Affective guidance in the Iowa gambling task. Cognitive, Affective & Behavioral Neuroscience, 6(4), 277–290.Google Scholar
Wallace, J.M. Jr. & Bachman, J.G., (1993). Validity of self-reports in student-based studies on minority populations: Issues and concerns. NIDA Research Monograph, 130, 167–200.Google Scholar
Wallace, J.M. Jr., Bachman, J.G., O’Malley, P.M., Johnston, L.D., Schulenberg, J.E., & Cooper, S.M. (2002). Tobacco, alcohol, and illicit drug use: Racial and ethnic differences among U.S. high school seniors, 1976–2000. Public Health Reports, 117(Suppl 1), S67–S75.Google Scholar
White, H.R. & Labouvie, E.W. (1989). Towards the assessment of adolescent problem drinking. Journal of Studies on Alcohol, 50(1), 30–37.Google Scholar
Whiteside, S.P. & Lynam, D.R. (2001). The five factor model and impulsivity: Using a structural model of personality to understand impulsivity. Personality and Individual Differences, 30, 669–689.Google Scholar
Wonga, M.M., Klingleb, R.S., & Price, R.K. (2004). Alcohol, tobacco, and other drug use among Asian American and Pacific Islander adolescents in California and Hawaii. Addictive Behavior, 29, 127–141.Google Scholar
Xing, Y., Ji, C., & Zhang, L. (2006). Relationship of binge drinking and other health-compromising behaviors among urban adolescents in China. Journal of Adolescent Health, 39(4), 495–500.Google Scholar