Differential Correlates of Positive and Negative Risk Taking in Adolescence


Positive risks benefit adolescent development without posing the same public safety concerns as negative risks, but little is understood about the psychological characteristics of positive risk taking. This study explored the shared and unique correlates of positive and negative risk taking in 223 adolescents (48% female) ages 16–20 years (M = 18.1; SD = 0.81). Positive and negative risk taking were both associated with higher sensation seeking. Unlike negative risk taking, positive risk taking was not associated with impulsivity or risk taking on experimental tasks. Further, positive risk taking was associated with lower reward sensitivity, higher punishment sensitivity, and greater school engagement than negative risk taking. The findings offer new insights for prevailing models of adolescent risk behavior and suggest positive risk taking may be particularly beneficial in the school context.

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Fig. 1


  1. 1.

    The positive risk taking scale was administered for the first time during the ninth wave of data collection. During this wave, the scale was only administered in the United States sample.

  2. 2.

    One item from the original eight-item Benthin scale (“vandalism”) was omitted due to low participant endorsement (<5%).


  1. Achenbach, T. M. (1991). Integrative guide for the 1991 CBCL 14-18, YSR, and TRF profiles. Burlington, VT: University of Vermont, Department of Psychiatry.

    Google Scholar 

  2. Barber, B. L., Eccles, J. S., & Stone, M. R. (2001). Whatever happened to the jock, the brain, and the princess? Young adult pathways linked to adolescent activity involvement and social identity. Journal of Adolescent Research, 16, 429–455. https://doi.org/10.1177/0743558401165002.

    Article  Google Scholar 

  3. Baumrind, D In: C. E. Irwin Jr., (Ed.) (1987). A developmental perspective on adolescent risk taking in contemporary America. Adolescent social behavior and health. New Directions for Child Development. ( No. 37. 93–125). San Francisco, CA: Jossey-Bass Social and Behavioral Sciences Series.

    Google Scholar 

  4. Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7–15. https://doi.org/10.1016/0010-0277(94)90018-3.

    Article  PubMed  Google Scholar 

  5. Benthin, A., Slovic, P., & Severson, H. (1993). A psychometric study of adolescent risk perception. Journal of Adolescence, 16, 153–168. https://doi.org/10.1006/jado.1993.1014.

    Article  PubMed  Google Scholar 

  6. Bohnert, A. M., Kane, P., & Garber, J. (2008). Organized activity participation and internalizing and externalizing symptoms: reciprocal relations during adolescence. Journal of Youth and Adolescence, 37, 239–250. https://doi.org/10.1007/s10964-007-9195-1.

    Article  Google Scholar 

  7. Brand, M., Recknor, E., Grabenhorst, F., & Bechara, A. (2007). Decisions under ambiguity and decisions under risk: correlations with executive functions and comparisons of two different gambling tasks with implicit and explicit rules. Journal of Clinical and Experimental Neuropsychology, 29, 86–99. https://doi.org/10.1080/13803390500507196.

    Article  PubMed  Google Scholar 

  8. Castellanos-Ryan, N., Parent, S., Vitaro, F., Tremblay, R. E., & Séguin, J. R. (2013). Pubertal development, personality, and substance use: a 10-year longitudinal study from childhood to adolescence. Journal of Abnormal Psychology, 122, 782–796.

    Article  Google Scholar 

  9. Cauffman, E., Shulman, E. P., Steinberg, L., Claus, E., Banich, M. T., Graham, S., & Woolard, J. (2010). Age differences in affective decision making as indexed by performance on the Iowa gambling task. Developmental Psychology, 46, 193–207. https://doi.org/10.1037/a0016128.

    Article  PubMed  Google Scholar 

  10. Clifford, M. M., Lan, W. Y., Chou, F. C., & Qi, Y. (2014). Academic risk-taking. The Journal of Experimental Education, 57, 321–338. https://doi.org/10.1080/00220973.1989.10806514.

    Article  Google Scholar 

  11. Crone, E. A., & Dahl, R. E. (2012). Understanding adolescence as a period of social-affective engagement and goal flexibility. Nature Reviews Neuroscience, 13, 636–650. https://doi.org/10.1038/nrn3313.

    Article  PubMed  Google Scholar 

  12. Crone, E. A., van Duijvenvoorde, A. C. K., & Peper, J. S. (2016). Annual research review: neural contributions to risk‐taking in adolescence—developmental changes and individual differences. Journal of Child Psychology and Psychiatry, 57, 353–368. https://doi.org/10.1111/jcpp.12502.

    Article  PubMed  Google Scholar 

  13. Darling, N. (2005). Participation in extracurricular activities and adolescent adjustment: cross-sectional and longitudinal findings. Journal of Youth and Adolescence, 34, 493–505.

    Article  Google Scholar 

  14. Dimidjian, S., Barrera, Jr., M., Martell, C., Munoz, R. F., & Lewinsohn, P. M. (2011). The origins and current status of behavioral activation treatments for depression. Annual Review of Clinical Psychology, 7, 1–38. https://doi.org/10.1146/annurev-clinpsy-032210-104535.

    Article  PubMed  Google Scholar 

  15. Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92, 1087–10101. https://doi.org/10.1037/0022-3514.92.6.1087.

    Article  PubMed  Google Scholar 

  16. Duell, N., Icenogle, G., & Steinberg, L. (2016). Adolescent decision making and risk taking. In L. Balter & C. S. Tamis-LeMonda (Eds), Child psychology: a handbook of contemporary issues (3rd ed.). New York, NY: Psychology Press/Taylor & Francis.

    Google Scholar 

  17. Duell, N., & Steinberg, L. (2019). Positive risk taking in adolescence. Child Development Perspectives, 13, 48–52. https://doi.org/10.1111/cdep.12310.

    Article  PubMed  Google Scholar 

  18. Duell, N., Steinberg, L., Icenogle, G., Chein, J., Chaudhary, N., Di Giunta, L., Dodge, K. A., Fanti, K. A., Lansford, J. E., Oburu, P., Pastorelli, C., Skinner, A. T., Sorbring, E., Tapanya, S., Uribe Tirado, L. M., Alampay, L. P., Al-Hassan, S. M., Takash, H. M. S., Bacchini, D., & Chang, L. (2018). Age patterns in risk taking across the world. Journal of Youth and Adolescence, 47, 1052–1072. https://doi.org/10.1007/s10964-017-0752-y.

    Article  PubMed  Google Scholar 

  19. Ellis, B. J., Del Giudice, M., Dishion, T. J., Figueredo, A. J., Gray, P., Griskevicius, V., Hawley, P. H., Jacobs, W. J., James, J., Volk, A. A., & Wilson, D. S. (2012). The evolutionary basis of risky adolescent behavior: implications for science, policy, and practice. Developmental Psychology, 48, 598–623. https://doi.org/10.1037/a0026220.

    Article  PubMed  Google Scholar 

  20. Ernst, M. (2014). The triadic model perspective for the study of adolescent motivated behavior. Brain and Cognition, 89, 104–111. https://doi.org/10.1016/j.bandc.2014.01.006.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Fischer, S., & Smith, G. T. (2004). Deliberation affects risk taking beyond sensation seeking. Personality and Individual Differences, 36, 527–537. https://doi.org/10.1016/S0191-8869(03)00112-0.

    Article  Google Scholar 

  22. Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: potential of the concept, state of the evidence. Review of Educational Research, 74, 59–109. https://doi.org/10.3102/00346543074001059.

    Article  Google Scholar 

  23. Fredricks, J. A., & Eccles, J. S. (2005). Developmental benefits of extracurricular involvement: do peer characteristics mediate the link between activities and youth outcomes? Journal of Youth and Adolescence, 34, 507–520. https://doi.org/10.1007/s10964-005-8933-5.

    Article  Google Scholar 

  24. Fredricks, J. A., & Eccles, J. S. (2006). Is extracurricular participation associated with beneficial outcomes? Concurrent and longitudinal relations. Developmental Psychology, 42, 698–713. https://doi.org/10.1037/0012-1649.42.4.698.

    Article  PubMed  Google Scholar 

  25. Gullone, E., & Moore, S. (2000). Adolescent risk-taking and the five-factor model of personality. Journal of Adolescence, 23, 393–407. https://doi.org/10.1006/jado.2000.0327.

    Article  PubMed  Google Scholar 

  26. Gullone, E., Moore, S., Moss, S., & Boyd, C. (2000). The adolescent risk-taking questionnaire: development and psychometric evaluation. Journal of Adolescent Research, 15, 231–250.

    Article  Google Scholar 

  27. Hendricks, J. M., Cope, V. C., & Harris, M. (2010). A leadership program in an undergraduate nursing course in Western Australia: building leaders in our midst. Nurse Education Today, 30, 252–257. https://doi.org/10.1016/j.nedt.2009.12.007.

    Article  PubMed  Google Scholar 

  28. Hoerr, T. R. (2013). Fostering grit: how do I prepare my students for the real world? ASCD Arias. Alexandria, VA.

  29. Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: guidelines for determining model fit. Electronic Journal of Business Research Methods, 6, 53–60.

    Google Scholar 

  30. Hoyt, M. A., & Kennedy, C. L. (2008). Leadership and adolescent girls: a qualitative study of leadership development. American Journal of Community Psychology, 42, 203–219. https://doi.org/10.1007/s10464-008-9206-8.

    Article  PubMed  Google Scholar 

  31. Humphreys, K. L., & Lee, S. S. (2011). Risk taking and sensitivity to punishment in children with ADHD, ODD, ADHD+ODD, and controls. Journal of Psychopathology and Behavioral Assessment, 33, 299–307. https://doi.org/10.1007/s10862-011-9237-6.

    Article  Google Scholar 

  32. Karagianni, D., & Montgomery, A. J. (2018). Developing leadership skills among adolescents and young adults: a review of leadership programmes. International Journal of Adolescence and Youth, 23, 86–98. https://doi.org/10.1080/02673843.2017.1292928.

    Article  Google Scholar 

  33. Kline, R. B. (2011). Hypothesis testing. Principles and Practice of Structural Equation Modeling. 3rd ed. (pp. 189–229). New York, NY: The Guilford Press.

    Google Scholar 

  34. Lansford, J. E., & Bornstein, M. H. (2011). Parenting attributions and attitudes in diverse cultural contexts: Introduction to the Special Issue. Parenting Science and Practice, 11, 87–101. https://doi.org/10.1080/15295192.2011.585552.

    Article  Google Scholar 

  35. Lejuez, C. W., Aklin, W. M., Zvolensky, M. J., & Pedulla, C. M. (2003). Evaluation of the Balloon Analogue Risk Task (BART) as a predictor of adolescent real-world risk-taking behaviours. Journal of adolescence, 26, 475–479.

    Article  Google Scholar 

  36. 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.

    Article  PubMed  Google Scholar 

  37. Li, Y., & Lerner, R. M. (2011). Trajectories of school engagement during adolescence: implications for grades, depression, delinquency, and substance use. Developmental Psychology, 47, 233–247. https://doi.org/10.1037/a0021307.

    Article  PubMed  Google Scholar 

  38. Meyer, D. K., & Turner, J. C. (2006). Re-conceptualizing emotion and motivation to learn in classroom contexts. Educational Psychology Review, 18, 377–390. https://doi.org/10.1007/s10648-006-9032-1.

    Article  Google Scholar 

  39. Muthén, L. K., & Muthén, B. O. (1998). Mplus User’s Guide. Eighth Edition Los Angeles, CA: Muthén & Muthén. -2017.

    Google Scholar 

  40. Perdue, N. H., Manzeske, D. P., & Estell, D. B. (2009). Early predictors of school engagement: exploring the role of peer relationships. Psychology in the Schools, 46, 1084–1097. https://doi.org/10.1002/pits.20446.

    Article  Google Scholar 

  41. Psychological Corporation. (1999). Wechsler Abbreviated Scale of Intelligence. San Antonio, TX: Psychological Corporation.

    Google Scholar 

  42. O’Neil, K. A., Conner, B. T., & Kendall, P. C. (2011). Internalizing disorders and substance use disorders in youth: comorbidity, risk, temporal order, and implications for intervention. Clinical Psychology Review, 31, 104–112. https://doi.org/10.1016/j.cpr.2010.08.002.

    Article  PubMed  Google Scholar 

  43. Rutten, E. A., Stams, G. J. J. M., Biesta, G. J. J., Schuengel, C., Dirks, E., & Hoeksma, J. B. (2007). The contribution of organized youth sport to antisocial and prosocial behavior in adolescent athletes. Journal of Youth and Adolescence, 36, 255–264. https://doi.org/10.1007/s10964-006-9085-y.

    Article  PubMed  Google Scholar 

  44. Shulman, E. P., Smith, A. R., Silva, K., Icenogle, G., Duell, N., Chein, J., & Steinberg, L. (2016). The dual systems model: review, reappraisal, and reaffirmation. Developmental Cognitive Neuroscience, 17, 103–117. https://doi.org/10.1016/j.dcn.2015.12.010.

    Article  PubMed  Google Scholar 

  45. Smith, A. R., Chein, J., & Steinberg, L. (2013). Impact of socio-emotional context, brain development, and pubertal maturation on adolescent risk-taking. Hormones and behavior, 64, 323–332.

    Article  Google Scholar 

  46. Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review, 28, 78–106. https://doi.org/10.1016/j.dr.2007.08.002.

    Article  PubMed  Google Scholar 

  47. Steinberg, L., Albert, D., Cauffman, E., Banich, M., Graham, S., & Woolard, J. (2008). Age differences in sensation seeking and impulsivity and indexed by behavior and self-report: evidence for a dual systems model. Developmental Psychology, 44, 1764–1778.

    Article  Google Scholar 

  48. Telzer, E. H., van Hoorn, J., Rogers, C. R., & Do, K. T. (2018). Social influence on positive youth development: a developmental neuroscience perspective. Advances in Child Development and Behavior, 54, 215–258.

    Article  Google Scholar 

  49. Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3, 4–70.

    Article  Google Scholar 

  50. van de Schoot, R., Lutgig, P., & Hox, J. (2012). A checklist for testing measurement invariance. European Journal of Developmental Psychology, 486-492. https://doi.org/10.1080/17405629.2012.686740

    Article  Google Scholar 

  51. Wang, M.-T., & Fredricks, J. (2014). The reciprocal links between school engagement, youth problem behaviors, and school dropout during adolescence. Child Development, 85, 722–737. https://doi.org/10.1111/cdev.12138.

    Article  PubMed  Google Scholar 

  52. Wood, A. P., Dawe, S., & Gullo, M. J. (2013). The role of personality, family influences, and prosocial risk-taking behavior on substance use in early adolescence. Journal of Adolescence, 36, 871–881. https://doi.org/10.1016/j.adolescence.2013.07.003.

    Article  PubMed  Google Scholar 

  53. Yang, F. M., & Kao, S. T. (2014). Item response theory for measurement validity. Shanghai Archives of Psychiatry, 26, 171–177.

    PubMed  PubMed Central  Google Scholar 

  54. Zuckerman, M., Eysenck, S. B., & Eysenck, H. J. (1978). Sensation seeking in England and America: cross-cultural, age, and sex comparisons. Journal of Consulting and Clinical Psychology, 46, 139–149. https://doi.org/10.1037/0022-006X.46.1.139.

    Article  PubMed  Google Scholar 

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The authors would like to thank Drs. Jason Chein and Thomas Olino for their assistance with the development of the positive risk scale and conceptual design of this study. Thanks also to the Parenting Across Cultures Study (PI: Dr. Jennifer Lansford) working group for their assistance in data acquisition.

Authors’ Contributions

ND conceived of the study, participated in its design, performed the statistical analyses, participated in interpretation of the data, and drafted the manuscript; LS helped conceive of the study, participated in its design, participated in the interpretation of the data, and helped draft the manuscript. All authors read and approved the final manuscript.


The writing of this article was supported, in part, by a postdoctoral fellowship provided by the Eunice Kennedy Shriver National Institute of Child Health and Development [T32-HD07376] through the Frank Porter Graham Child Development Institute, University of North Carolina at Chapel Hill, to Natasha Duell and by an award provided by the Klaus J. Jacobs Foundation to Laurence Steinberg.

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This manuscript’s data will not be deposited.

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Correspondence to Natasha Duell.

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The authors declare that they have no conflict of interest.

Ethical Approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the internal review board of Duke University (IRB approval 2032).

Informed Consent

Informed consent was obtained from all individual participants included in this study who were 18 years of age or older; informed parental consent and child assent were obtained for all participants under the age of 18 years.

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Appendix A

Positive and Negative Risk Taking Scale

Below are the positive and negative risk taking questionnaire items administered to participants in this study. Items 1–14 are from the positive risk taking scale. Items 15–22 are negative risk items from the Benthin Risk Perception Scale. Items 23–28 are negative risk items added for the purposes of this study. This appendix begins with the prompt and response options used in this study. Note that the following positive risk taking items were omitted from the final analyses: (1) Tried out for a team or auditioned for a play when you were not sure you would be picked; (3) Told someone the truth, even if they did not want to hear it; (5) Ran for a leadership role in school or in some other organization when you were not sure you would be picked; (6) Asked someone new on a date when you thought they might say no.

For descriptive purposes, Fig. 2 illustrates the frequency of endorsement across participant age for each of the positive and negative risk items used in the final analyses.

Prompt: Here is a list of different things you may have done at some time in the past. For each one, please indicate whether you have ever done it, and, if so, how many times you have done it in the past 6 months.

Question items and response options:

Have you ever…

(0) No (1) Yes

…How many times have you engaged in this activity during the last 6 months?

(0) None (1) Once or twice (2) 3–5 times (3) More than 5 times


  1. 1.

    Tried out for a team or auditioned for a play when you were not sure you would be picked?

  2. 2.

    Joined a new club or activity when you were not sure you would like it?

  3. 3.

    Told someone the truth, even if they did not want to hear it?

  4. 4.

    Tried a new food you thought you might not like?

  5. 5.

    Ran for a leadership role in school or in some other organization when you were not sure you would be picked?

  6. 6.

    Asked someone new on a date when you thought the person may say no?

  7. 7.

    Taken a class in a subject you knew nothing about or that seemed challenging?

  8. 8.

    Tried a new hairstyle or outfit that you were not sure others would like?

  9. 9.

    Gone to a party or social event where you did not know very many people and thought you might not have anyone to talk with?

  10. 10.

    Told a secret or shared something personal about yourself to someone?

  11. 11.

    Stood up for what you believe is right, even though you thought someone might disagree with you?

  12. 12.

    Started a friendship with someone new when you were not sure how your other friends would react?

  13. 13.

    Tried a new sport or played a sport you are not good at where you might have embarrassed yourself?

  14. 14.

    Spent time with a new group of people when you were not sure you would fit in?

  15. 15.

    Drank alcohol

  16. 16.

    Rode in a car with an intoxicated (drunk) driver

  17. 17.

    Had unprotected sex

  18. 18.

    Smoked cigarettes

  19. 19.

    Stolen from a store

  20. 20.

    Went into a dangerous part of town

  21. 21.

    Gotten into a physical fight

  22. 22.

    Threatened or injured someone with a weapon

  23. 23.

    Looked at your phone while driving a car instead of paying attention to the road?

  24. 24.

    Cheated on a homework assignment or exam even though you knew you would get in trouble if you were caught?

  25. 25.

    Decided to skip class even though you could get in trouble and fall behind on your schoolwork?

  26. 26.

    Snuck out of your house without telling your parents where you were going?

  27. 27.

    Sent sexy messages or pictures to someone?

  28. 28.

    Driven faster than the legal speed limit?

Fig. 2

Percent of sample endorsing engagement in positive and negative risks over the past 6 months, organized by age group

Appendix B

Results from Scale Development Analyses for the Positive Risk Taking Scale

An exploratory factor analysis was conducted on the 14 positive risk taking items administered in this study. Table 6 provides correlations among the 14 original items included in the positive risk taking questionnaire. Table 7 provides model fit statistics from the exploratory factor analysis of the positive risk items, which ultimately yielded a 10-item, single-factor scale. For a discussion of model fit, see Kline 2011 (pp. 193–209).

To further test the psychometric properties of the scale, a 2-parameter logistic item response theory analysis was conducted. Item response theory analysis yields two primary pieces of information: item discrimination, or how well each scale item identifies people at different levels of the trait, and item difficulty, or the probability that a person’s endorsement of a particular item is a function of them being higher in that trait (Yang and Kao 2014). Table 8 lists the item discriminations and difficulties for the positive risk taking scale items. Figure 3a depicts the item-level characteristic curves (ICC). The ICCs indicate the probability that someone will endorse an item as a function of the latent factor. Steeper S-shaped curves indicate that high positive risk taking is associated with a greater probability of endorsing an item on the scale. As a general indicator of total scale performance, Fig. 3b depicts the total information curve for the positive risk scale, which indicates how much information the scale produces about positive risk taking (Yang and Kao 2014). A bell curve centered on zero indicates the scale provides the most information about someone who is average on positive risk taking.

Finally, analyses of configural and scalar measurement invariance for age and gender were conducted. Metric invariance is not available for binary indicators (Mplus User’s Guide, p. 542). Configural invariance determines whether the same items measure positive risk taking across groups. One can assume configural invariance with adequate model fit statistics (see Hooper et al. 2008). Scalar invariance indicates equality of intercepts, which justifies the comparison of group means. Scalar invariance is established with a non-significant difference between the chi-square model fit statistics between the configural and scalar models. For a more detailed description of invariance assessments, please see van de Schoot et al. 2012 and Vandenberg and Lance 2000. For the analyses involving age, age was coded into three groups: 16–17 year-olds (20%), 18 year-olds (52%), and 19–20 year-olds (28%) to ensure comparable group sizes (otherwise 16-year-olds comprise 1.3% of the sample and 20-year-olds comprise 4.5% of the sample). Results suggested configural invariance for both age and gender, scalar invariance for age, and partial scalar invariance for gender (see Table 9). Modification indices in the Mplus output indicated that removal of one item (tried a new sport or played a sport you’re not good at when you might have embarrassed yourself) would achieve full scalar invariance for gender, as indicated by a non-significant chi-square difference between the configural and scalar models (Δχ2 = 6.955, p = 0.434). Gender was included as a covariate in all analyses and was not of primary interest in this study. Therefore, we did not remove any items from the scale.

Table 6 Correlations among positive risk items
Table 7 Model fit statistics and factor loadings for positive risk taking scale
Table 8 Item discriminations and difficulties from Item Response Theory model
Table 9 Model fit indices for analyses of configural and scalar invariance for age and gender
Fig. 3

a Item characteristic curves for items included in final, 10-item positive risk taking scale; (b) Total information curve for final, 10-item positive risk taking scale

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Duell, N., Steinberg, L. Differential Correlates of Positive and Negative Risk Taking in Adolescence. J Youth Adolescence 49, 1162–1178 (2020). https://doi.org/10.1007/s10964-020-01237-7

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  • Adolescence
  • Risk taking
  • Positive risk taking
  • School engagement
  • Dual systems