Journal of Cancer Survivorship

, Volume 7, Issue 3, pp 500–510 | Cite as

Factors related to decision making and substance use in adolescent survivors of childhood cancer: a presenting clinical profile

  • P. J. Hollen
  • V. L. Tyc
  • S. V. Shannon
  • S. F. Donnangelo
  • W. L. Hobbie
  • M. M. Hudson
  • M. C. O’Laughlen
  • M. E. Smolkin
  • G. R. Petroni



Adolescent survivors of childhood cancer are more vulnerable to the consequences of health risk behaviors because of the late effects of their disease and its treatment. Decision making related to risk behaviors is important as they have reached an age during which initiation of substance use risk behavior is common.


Factors associated with decision making and substance use behaviors (smoking, alcohol use, and illicit drug use) were identified among adolescent survivors of childhood cancer, the role of cognitive function was examined, and their rates of substance use behaviors were compared to a sample from the general population.


A cohort of 243 adolescent survivors, ages 14–19 years, participated who were recruited from three cancer centers (St. Jude Children’s Research Hospital, Hackensack University, and Long Beach Medical Center). A cross-sectional survey was used to assess cognitive and psychosocial factors for a presenting clinical profile to predict quality decision making and substance use behaviors. Validated measures using online data entry were obtained at the time of their annual visit for evaluation of late effects of treatment. Cancer and treatment factors were abstracted from the medical record. Eight factors (nine for substance use risk behavior) were examined in two regression models, quality decision making and substance use.


In the model to predict poor-quality decision making for this cohort, gender and risk motivation (a surrogate for resiliency to social influence) were each significant predictors, with male gender and less resiliency each associated with poor decision making. Significant predictors of lifetime substance use were older presenting age, lower resiliency to social influence, poorer abstract ability (representing executive function impairment), history of current school problems, and negative substance use risk behavior modeling by household members and closest friend; CNS-associated late effects were only marginally associated. For current substance use, three factors remained significant in this cohort: older presenting age, lower resiliency, and negative risk behavior modeling.

Implications for Cancer Survivors

Study results characterize a presenting clinical profile for adolescent survivors with poor-quality decision making regarding substance use risk behaviors that will be helpful to health professionals counseling teen survivors about the impact of risk behaviors on disease-and treatment-related late effects.


Childhood cancer Adolescents Decision making Substance use 


  1. 1.
    Klosky JL, Howell CR, Li Z, Foster RH, Mertens AC, Robison LL, et al. Risky health behavior among adolescents in the Childhood Cancer Survivor Study cohort. J Pediatr Psychol. 2012;37(6):634–46. doi:10.1093/jpepsy/jss046.PubMedCrossRefGoogle Scholar
  2. 2.
    Hollen PJ, Hobbie WL, Donnangelo SF, Shannon S, Erickson J. Substance use risk behaviors and decision-making skills among cancer-surviving adolescents. J Pediatr Oncol Nurs. 2007;24(5):264–73.PubMedCrossRefGoogle Scholar
  3. 3.
    Bauld C, Toumbourou JW, Anderson V, Coffey C, Olsson CA. Health-risk behaviors among adolescent survivors of childhood cancer. Pediatr Blood Cancer. 2005;45:706–15.PubMedCrossRefGoogle Scholar
  4. 4.
    Verrill JR, Schafer J, Vannatta K, Noll RB. Aggression, antisocial behavior, and substance abuse in survivors of pediatric cancer: possible protective effects of cancer and its treatment. J Pediatr Psychol. 2000;25(7):493–502.Google Scholar
  5. 5.
    Tercyak KP, Britto MT, Hanna KM, Hollen PJ, Hudson MM. Prevention of tobacco use among medically at-risk children and adolescents: clinical and research opportunities in the interest of public health. J Pediatr Psychol. 2008;33(2):119–32.PubMedCrossRefGoogle Scholar
  6. 6.
    Children’s Oncology Group. Long-term follow-up guidelines for survivors of childhood, adolescent, and young adults cancers. (Version 3.0, October). 2008. Retrieved July 5, 2011, from
  7. 7.
    Eslinger PJ. Conceptualizing, describing, and measuring components of executive function: a summary. In: Lyon GR, Krasnegor NA, editors. Attention, memory, and executive function. Baltimore, MD: Paul. H. Brooks; 1996. p. 367–95.Google Scholar
  8. 8.
    Geidd JN, Blumenthal J, Jeffries NO, Castellanos FX, Liu H, Zijdenbos A, et al. Brain development during childhood and adolescence: a longitudinal MRI study. Nature Neuroscience. 1999;2(10):861–3.CrossRefGoogle Scholar
  9. 9.
    Geidd JN. Structural magnetic resonance imaging of the adolescent brain. Ann N Y Acad Sci. 2004;1021:77–85.CrossRefGoogle Scholar
  10. 10.
    Geidd JN. Linking adolescent sleep, brain maturation, and behavior. J Adolesc Health. 2009;45(4):319–20.CrossRefGoogle Scholar
  11. 11.
    Kahalley LS, Robinson LA, Tyc VL, Hudson MM, Leisenring W, Stratton K, et al. Attentional and executive dysfunction as predictors of smoking within the Childhood Cancer Survivor Study cohort. Nicotine Tob Res. 2010;12(4):344–54.PubMedCrossRefGoogle Scholar
  12. 12.
    Kahalley LS, Tyc VL, Wilson SJ, Nelms J, Hudson MM, Wu S, et al. Adolescent cancer survivors’ smoking intentions are associated with aggression, attention, and smoking history. J Cancer Surviv. 2011;5:123–31.PubMedCrossRefGoogle Scholar
  13. 13.
    Kahalley LS, Robison LA, Tyc VL, Hudson MM, Leisenring W, Stratton K, et al. Risk factors for smoking among adolescent survivors of childhood cancer: a report from the Childhood Cancer Survivor Study. Pediatr Blood Cancer. 2012;58:428–34.PubMedCrossRefGoogle Scholar
  14. 14.
    Hollen PJ. A clinical profile to predict decision making, risk behaviors, clinical status, and health-related quality of life for cancer-surviving adolescents: part I. Cancer Nurs. 2000;23(4):247–57.PubMedCrossRefGoogle Scholar
  15. 15.
    Hollen PJ. A clinical profile to predict decision making, risk behaviors, clinical status, and health-related quality of life for cancer-surviving adolescents: part II. Cancer Nurs. 2000;23(5):337–43.PubMedCrossRefGoogle Scholar
  16. 16.
    Janis IL, Mann L. Decision making: a psychological analysis of conflict, choice, and commitment. New York: The Free Press; 1977.Google Scholar
  17. 17.
    Janis IL, Mann L. A theoretical framework for decision counseling. In: Janis IL, editor. Counseling on personal decisions: theory and research on short-term helping relationships. New Haven, CT: Yale University Press; 1982. p. 47–72.Google Scholar
  18. 18.
    Mann L, Harmoni R, Power C. Adolescent decision-making: the development of competence. J Adolesc. 1989;12:265–78.PubMedCrossRefGoogle Scholar
  19. 19.
    Hersey P, Blanchard KH. Management of organizational behavior: utilizing human resources. Englewood Cliffs: Prentice Hall; 1969.Google Scholar
  20. 20.
    Zackary RA. Shipley Institute of Living Scale: revised manual. Los Angeles: Western Psychological Services Publishers; 1986.Google Scholar
  21. 21.
    Hollen PJ. Psychometric properties of two instruments to measure quality decision making. Res Nurs Health. 1994;17:137–48.PubMedCrossRefGoogle Scholar
  22. 22.
    Hollen PJ, Hobbie WL, Finley SM. Testing the effects of a decision-making and risk-reduction program for cancer-surviving adolescents. Oncol Nurs Forum. 1999;26(9):1475–86.PubMedGoogle Scholar
  23. 23.
    Ryan RM, Connell JP. Perceived locus of causality and internalization: examining reasons for acting in two domains. J Pers Soc Psychol. 1989;57(5):749–61.PubMedCrossRefGoogle Scholar
  24. 24.
    Barnes GM, Welte JW. Patterns and predictors of alcohol use among 7-12th grade students in New York State. J Stud Alcohol. 1986;47(1):53–62.PubMedGoogle Scholar
  25. 25.
    Barnes GM, Welte JW, Dintcheff BA. Decline in alcohol use among 7-12th grade students in New York State, 1983–1990. Alcohol Clin Exp Res. 1993;17:797–801.PubMedCrossRefGoogle Scholar
  26. 26.
    Hoffman JH, Welte JW. Barnes GM Co-occurence of alcohol and cigarette use among adolescents. Addict Behav. 2001;26:63–78.PubMedCrossRefGoogle Scholar
  27. 27.
    Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE. Monitoring the future national survey results on drug use, 1975–2008: Volume I, Secondary school students (NIH Publication No. 09–7402). Bethesda, MD: National Institute on Drug Abuse; 2009.Google Scholar
  28. 28.
    Hollen PJ, Hobbie WL, Finley SM, Hiebert, SM. The relationship of resiliency to decision making and risk behaviors of cancer-surviving adolescents. J Pediatr Oncol Nurs. 2001;18(5):188–204.PubMedCrossRefGoogle Scholar
  29. 29.
    DiClemente RJ, Ponton LE, Hansen WB. New directions for adolescent risk prevention and health promotion research and interventions. In: DiClemente RJ, Hansen WB, Ponton LE, editors. Handbook of adolescent health risk behavior. New York: Plenum Press; 1996. p. 413–20.Google Scholar
  30. 30.
    Blakemore S, Choudhury S. Development of the adolescent brain: implications for executive function and social cognition. J Child Psychol Psychiatry. 2006;47(3):296–312.PubMedCrossRefGoogle Scholar
  31. 31.
    Beyth-Marom R, Fischhoff B, Quadrel M, Furby, B. Teaching decision making to adolescents: a critical review. In: Baron J, Brown RV, editors. Teaching decision making to adolescents. Hillsdale, NJ: Lawrence Erlbaum Associates; 1991. p. 10–46.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • P. J. Hollen
    • 1
  • V. L. Tyc
    • 2
  • S. V. Shannon
    • 3
  • S. F. Donnangelo
    • 4
  • W. L. Hobbie
    • 5
  • M. M. Hudson
    • 2
  • M. C. O’Laughlen
    • 1
  • M. E. Smolkin
    • 1
  • G. R. Petroni
    • 1
  1. 1.University of VirginiaCharlottesvilleUSA
  2. 2.St. Jude Children’s Research HospitalMemphisUSA
  3. 3.Long Beach Memorial Medical CenterLong BeachUSA
  4. 4.Hackensack University Medical CenterHackensackUSA
  5. 5.University of Pennsylvania and Children’s Hospital of PhiladelphiaPhiladelphiaUSA

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