Age Patterns in Risk Taking Across the World
- 1.5k Downloads
Epidemiological data indicate that risk behaviors are among the leading causes of adolescent morbidity and mortality worldwide. Consistent with this, laboratory-based studies of age differences in risk behavior allude to a peak in adolescence, suggesting that adolescents demonstrate a heightened propensity, or inherent inclination, to take risks. Unlike epidemiological reports, studies of risk taking propensity have been limited to Western samples, leaving questions about the extent to which heightened risk taking propensity is an inherent or culturally constructed aspect of adolescence. In the present study, age patterns in risk-taking propensity (using two laboratory tasks: the Stoplight and the BART) and real-world risk taking (using self-reports of health and antisocial risk taking) were examined in a sample of 5227 individuals (50.7% female) ages 10–30 (M = 17.05 years, SD = 5.91) from 11 Western and non-Western countries (China, Colombia, Cyprus, India, Italy, Jordan, Kenya, the Philippines, Sweden, Thailand, and the US). Two hypotheses were tested: (1) risk taking follows an inverted-U pattern across age groups, peaking earlier on measures of risk taking propensity than on measures of real-world risk taking, and (2) age patterns in risk taking propensity are more consistent across countries than age patterns in real-world risk taking. Overall, risk taking followed the hypothesized inverted-U pattern across age groups, with health risk taking evincing the latest peak. Age patterns in risk taking propensity were more consistent across countries than age patterns in real-world risk taking. Results suggest that although the association between age and risk taking is sensitive to measurement and culture, around the world, risk taking is generally highest among late adolescents.
KeywordsAdolescents Risk taking Development Cross-national
This research was supported by an award to Laurence Steinberg from the Klaus J. Jacobs Foundation and the Eunice Kennedy Shriver National Institute of Child Health and Human Development grant RO1-HD054805.
ND conceived of the study, participated in its design, performed the statistical analyses, participated in interpretation of the data, and drafted the manuscript; LS conceived of the study, participated in its design and coordination, participated in interpretation of the data, and helped to draft the manuscript; GI participated in the study design and in interpretation of the data; JC gave final approval of the manuscript; NC was involved in the acquisition of the data and gave final approval of the manuscript; LD was involved in the acquisition of the data and gave final approval of the manuscript; KAD was involved in the acquisition of the data and gave final approval of the manuscript; KAF was involved in the acquisition of the data and gave final approval of the manuscript; JEL was involved in the acquisition of the data and gave final approval of the manuscript; PO was involved in the acquisition of the data and gave final approval of the manuscript; CP was involved in the acquisition of the data and gave final approval of the manuscript; ATS was involved in the acquisition of the data and gave final approval of the manuscript; ES was involved in the acquisition of the data and gave final approval of the manuscript; ST was involved in the acquisition of the data and gave final approval of the manuscript; LUT was involved in the acquisition of the data and gave final approval of the manuscript; LPA was involved in the acquisition of the data and gave final approval of the manuscript; SMA was involved in the acquisition of the data and gave final approval of the manuscript; HMST was involved in the acquisition of the data and gave final approval of the manuscript; LC was involved in the acquisition of the data and gave final approval of the manuscript; and DB was involved in the acquisition of the data and gave final approval of the manuscript. All authors read and approved the final manuscript.
Compliance with Ethical Standards
Conflicts of Interest
The authors declare that they have no competing interests.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- Anderson Johnson, C., Palmer, P. H., Chou, C. P., Pang, Z., Zhou, D., Dong, L., Xiang, H., Yang, P., & Xu, H., et al. (2006). Tobacco use among youth and adults in Mainland China: The china seven cities study. Public Health, 120, 1156–1169. https://doi.org/10.1016/j.puhe.2006.07.023.CrossRefPubMedGoogle Scholar
- Dahne, J., Richards, J. M., Ernst, M., Macpherson, L., & Lejuez, C. W. (2013). Assessment of risk taking in addiction research. In J. MacKillop & H. de Wit (Eds.), The Wiley-Blackwell Handbook of Addiction Psychopharmacology (pp. 209–231). Hoboken, NJ: Wiley-Blackwell. https://doi.org/10.1002/9781118384404.ch8
- Donato, F., Monarca, S., Chiesa, R., Feretti, D., Modolo, M. A., & Nardi, G. (1995). Patterns and covariates of alcohol drinking among high school students in 10 towns in Italy: A cross-sectional study. Drug and Alcohol Dependence, 37, 59–69. https://doi.org/10.1016/0376-8716(94)01053-N.CrossRefPubMedGoogle Scholar
- Duell, N., Steinberg, L., Chein, J., Al-Hassan, S. M., Bacchini, D., Lei, C., Chaudhary, N., Di Giunta, L., & Dodge, K. A., et al. (2016). Interaction of reward seeking and self-regulation in the prediction of risk taking: A cross-national test of the dual systems model. Developmental Psychology, 52, 1593–1605. https://doi.org/10.1037/dev0000152.CrossRefPubMedGoogle Scholar
- Ellis, L., & Walsh, A. (2003). Crime, delinquency, and intelligence: A review of the worldwide literature. In H. Nyborg (Ed.), The Scientific Study of General Intelligence: Tribute to Arthur J. Jensen (pp. 343–365). Kidlington, Oxford: Elsevier Science Ltd. https://doi.org/10.1016/B978-008043793-4/50054-4.CrossRefGoogle Scholar
- Fuller, E., Clifton, S., Field, N., Mercer. C. H., Prah, P., Macdowall, W., Mitchell, K., Sonnenberg, P., Johnson, A. M., & Wellings, K. (2015). Natsal-3: Key findings from Scotland. http://natcen.ac.uk/media/997277/NatSal-Scotland.pdf.
- Hendriksen, E. S., Pettifor, A., Lee, S., Coates, T. J., & Rees, H. V. (2007). Predictors of condom use among young adults in South Africa: The reproductive health and HIV research unit national youth survey. American Journal of Public Health, 97, 1–8. https://doi.org/10.2105/AJPH.2006.086009.CrossRefGoogle Scholar
- Hindelang, M. J., Hirschi, T. & Weis, J. G. (1981). Measuring delinquency. Beverly Hills, CA: Sage Publications.Google Scholar
- Hofstede, G. (2011). Dimensionalizing cultures: The Hofstede model in context. Online Readings in Psychology & Culture, 2, 1–26. https://doi.org/10.9707/2307-0919.1014.
- Kim-Spoon, J., Kahn, R., Deater-Deckard, K., Chiu, P., Steinberg, L., & King-Casas, B. (2016). Risky decision making in a laboratory driving task is associated with health risk behaviors during late adolescence but not adulthood. International Journal of Behavioral Development, 40, 58–63. https://doi.org/10.1177/0165025415577825.CrossRefPubMedGoogle Scholar
- Kline, R. B. (2011). Hypothesis testing. Principles and Practice of Structural Equation Modeling (3rd ed., pp. 189–229). New York, NY: Guilford.Google Scholar
- Lejuez, C. W., Read, J. P., Kahler, C. W., Richards, J. B., Ramsey, S. E., & Stuart, G. L., et al. (2002). Evaluation of a behavioral measure of risk taking: The balloon analogue risk task (BART). Journal of Experimental Psychology: Applied, 8, 75–84. https://doi.org/10.1037/1076-898X.8.2.75.PubMedGoogle Scholar
- Maxwell, J. A. (1996). Qualitative research design: An interactive approach. New York, NY: Sage.Google Scholar
- Osgood, D. W., & Anderson, A. (2004). Unstructured socializing and rates of delinquency. Criminology, 42, 519–549. https://doi.org/10.1111/j.1745-9125.2004.tb00528.x.CrossRefGoogle Scholar
- Piquero, A. R., Farrington, D. P., & Blumstein, A. (2003). The criminal career paradigm. In M. Tonry (Ed.), Crime and justice: A review of research (Vol 30, pp. 359–506). Chicago: University of Chicago Press.Google Scholar
- Psychological Corporation. (1999). Wechsler abbreviated scale of intelligence. San Antonio, TX: Pearson.Google Scholar
- Rahbari, L. (2016). Sexuality in Iran. In C. L. Shehan (Ed.), The Wiley Blackwell Encyclopedia of Family Studies (Vol. 4, pp. 1768–1771), Chichester, West Sussex: John Wiley & Sons.Google Scholar
- Steinberg, L. (2014). Age of Opportunity: Lessons From the New Science of Adolescence. New York: Houghton Mifflin Harcourt.Google Scholar
- Steinberg, L., Icenogle, G., Shulman, E., Breiner, K., Chein, J., & Bacchini, D., et al. (2017). Around the world, adolescence is a time of heightened sensation seeking and immature self-regulation. Developmental Science. https://doi.org/10.1111/desc.12532. Advance online publication.PubMedGoogle Scholar
- Stevenson, H. W., & Zusho, A. (2002). Adolescence in China and Japan: Adapting to a changing environment. In B. B. Brown, R. W. Larson, & T. S. Saraswathi, The World’s Youth: Adolescence in Eight Regions of the Globe, (pp. 141–170). New York, NY: Cambridge University Press.Google Scholar
- Takakura, M., Nagayama, T., Sakihara, S., & Willcox, C. (2001). Patterns of health-risk behavior among Japanese high school students. Journal of School Health, 71, 23–29. https://doi.org/10.1111/j.1746-1561.2001.tb06484.x.CrossRefPubMedGoogle Scholar
- United Nations Development Programme. (2014). Human development report. http://hdr.undp.org/en/data.
- World Health Organization. (2014). Adolescents’ health-related behaviors. http://apps.who.int/adolescent/second-decade/section4. Accessed 1 October 2016.