Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-25T04:02:52.475Z Has data issue: false hasContentIssue false
  • English
  • Français

Past trauma and future choices: differences in discounting in low-income, urban African Americans

Published online by Cambridge University Press:  21 February 2018

Carissa van den Berk-Clark ,
Joel Myerson ,
Leonard Green  and
Richard A. Grucza
Carissa van den Berk-Clark*
Affiliation:
Department of Family and Community Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA
Joel Myerson
Affiliation:
Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
Leonard Green
Affiliation:
Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
Richard A. Grucza
Affiliation:
Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
*
Author for correspondence: Carissa van den Berk-Clark, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Exposure to traumatic events is surprisingly common, yet little is known about its effect on decision making beyond the fact that those with post-traumatic stress disorder are more likely to have substance-abuse problems. We examined the effects of exposure to severe trauma on decision making in low-income, urban African Americans, a group especially likely to have had such traumatic experiences.

Method

Participants completed three decision-making tasks that assessed the subjective value of delayed monetary rewards and payments and of probabilistic rewards. Trauma-exposed cases and controls were propensity-matched on demographic measures, treatment for psychological problems, and substance dependence.

Results

Trauma-exposed cases discounted the value of delayed rewards and delayed payments, but not probabilistic rewards, more steeply than controls. Surprisingly, given previous findings that suggested women are more affected by trauma when female and male participants’ data were analyzed separately, only the male cases showed steeper delay discounting. Compared with nonalcoholic males who were not exposed to trauma, both severe trauma and alcohol-dependence produced significantly steeper discounting of delayed rewards.

Conclusions

The current study shows that exposure to severe trauma selectively affects fundamental decision-making processes. Only males were affected, and effects were observed only on discounting delayed outcomes (i.e. intertemporal choice) and not on discounting probabilistic outcomes (i.e. risky choice). These findings are the first to show significant differences in the effects of trauma on men's and women's decision making, and the selectivity of these effects has potentially important implications for treatment and also provides clues as to underlying mechanisms.

Keywords

African Americansdelayed outcomesdiscountingsex differencetrauma
Type
Original Articles
Information
Psychological Medicine , Volume 48 , Issue 16 , December 2018 , pp. 2702 - 2709
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alegria, M, Fortuna, LR, Lin, JY, Norris, FH, Gao, S, Takeuchi, DT et al. (2013). Prevalence, risk, and correlates of posttraumatic stress disorder across ethnic and racial minority groups in the United States. Medical Care 51, 1114–1123.Google Scholar
American Psychiatric Association (2000). DSM-IV-TR: Diagnostic and Statistical Manual of Mental Disorders, Text Revision. Washington, DC: American Psychiatric Association.Google Scholar
Amlung, M, Petker, T, Jackson, J, Balodis, I and MacKillop, J (2016). Steep discounting of delayed monetary and food rewards in obesity: a meta-analysis. Psychological Medicine 46, 2423–2434.Google Scholar
Audrain-McGovern, J, Rodriguez, D, Epstein, LH, Cuevas, J, Rodgers, K and Wileyto, EP (2009). Does delay discounting play an etiological role in smoking or is it a consequence of smoking? Drug and Alcohol Dependence 103, 99–106.Google Scholar
Bickel, WK, Jarmolowicz, DP, Mueller, ET, Koffarnus, MN and Gatchalian, KM (2012). Excessive discounting of delayed reinforcers as a trans-disease process contributing to addiction and other disease-related vulnerabilities: emerging evidence. Pharmacological Therapy 134, 287–297.Google Scholar
Bickel, WK, MacKillop, J, Madden, GJ, Odum, AL and Yi, R (2015). Experimental manipulations of delay discounting & related processes: an introduction to the special issue. Journal of the Experimental Analysis of Behavior 103, 1–9.Google Scholar
Breslau, N and Kessler, RC (2001). The stressor criterion in DSM-IV posttraumatic stress disorder: an empirical investigation. Biological Psychiatry 50, 699–704.Google Scholar
Breslau, N, Kessler, RC, Chilcoat, HD, Schultz, LR, Davis, GC and Andreski, P (1998). Trauma and posttraumatic stress disorder in the community: the 1996 Detroit Area Survey of Trauma. Archives of General Psychiatry 55, 626–632.Google Scholar
Daniel, TO, Stanton, CM and Epstein, LH (2013). The future is now: comparing the effect of episodic future thinking on impulsivity in lean and obese individuals. Appetite 71, 120–125.Google Scholar
Danielson, CK, Amstadter, AB, Dangelmaier, RE, Resnick, HS, Saunders, BE and Kilpatrick, DG (2009). Trauma-related risk factors for substance abuse among male versus female young adults. Addictive Behaviors 34, 395–399.Google Scholar
Dennhardt, AA and Murphy, JG (2011). Associations between depression, distress tolerance, delay discounting, and alcohol-related problems in European American and African American college students. Psychology of Addictive Behaviors 25, 595–604.Google Scholar
DeWit, DJ, Adlaf, EM, Offord, DR and Ogborne, AC (2000). Age at first alcohol use: a risk factor for the development of alcohol disorders. American Journal of Psychiatry 157, 745–750.Google Scholar
Du, W, Green, L and Myerson, J (2002). Cross-cultural comparisons of discounting delayed and probabilistic rewards. The Psychological Record 52, 479–492.Google Scholar
Goldmann, E, Aiello, A, Uddin, M, Delva, J, Koenen, K, Gant, LM et al. (2011). Pervasive exposure to violence and posttraumatic stress disorder in a predominantly African American Urban Community: the Detroit Neighborhood Health Study. Journal of Traumatic Stress 24, 747–751.Google Scholar
Green, L and Myerson, J (2004). A discounting framework for choice with delayed and probabilistic rewards. Psychological Bulletin 130, 769–792.Google Scholar
Green, L and Myerson, J (2013). How many impulsivities? A discounting perspective. Journal of the Experimental Analysis of Behavior 99, 3–13.Google Scholar
Heron, M (2016). Deaths: leading causes for 2014. National Vital Statistic Reports 65, 1–96.Google Scholar
Hesselbrock, M, Easton, C, Bucholz, KK, Schuckit, M and Hesselbrock, V (1999). A validity study of the SSAGA – a comparison with the SCAN. Addiction 94, 1361–1370.Google Scholar
Imas, A, Kuhn, MA and Mironova, V (2015). A history of violence: field evidence on trauma, discounting and present bias. CESifo Working Paper, No. 5338.Google Scholar
Jacobsen, LK, Southwick, SM and Kosten, TR (2001). Substance use disorders in patients with posttraumatic stress disorder: a review of the literature. American Journal of Psychiatry 158, 1184–1190.Google Scholar
Kessler, RC, Sonnega, A, Bromet, E, Hughes, M and Nelson, CB (1995). Posttraumatic stress disorder in the national comorbidity survey. Archives of General Psychiatry 52, 1048–1060.Google Scholar
Kilpatrick, DG, Acierno, R, Saunders, B, Resnick, HS, Best, CL and Schnurr, PP (2000). Risk factors for adolescent substance abuse and dependence: data from a national sample. Journal of Consulting and Clinical Psychology 68, 19−30.Google Scholar
Kucharska, J (2017). Sex differences in the appraisal of traumatic events and psychopathology. Psychological Trauma: Theory, Research, Practice, and Policy 9, 575–582.Google Scholar
Leuven, E and Sianesi, B (2015). PSMATCH2: stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Statistical Software Components. Available at https://ideas.repec.org/c/boc/bocode/s432001.html.Google Scholar
Li, J-Z, Li, S and Liu, H (2011). How has the Wenchuan earthquake influenced people's intertemporal choices? Journal of Applied Social Psychology 41, 2739–2752.Google Scholar
Maccallum, F and Bonanno, GA (2016). The economics of losing a loved one: delayed reward discounting in prolonged grief. Clinical Psychological Science 4, 683–690.Google Scholar
MacKillop, J and Kahler, CW (2009). Delayed reward discounting predicts treatment response for heavy drinkers receiving smoking cessation treatment. Drug and Alcohol Dependence 104, 197–203.Google Scholar
MacKillop, J, Amlung, MT, Few, LR, Ray, LA, Sweet, LH and Munafò, MR (2011). Delayed reward discounting and addictive behavior: a meta-analysis. Psychopharmacology 216, 305–321.Google Scholar
MacKillop, J, Weafer, J, Gray, JC, Oshri, A, Palmer, A and de Wit, H (2016). The latent structure of impulsivity: impulsive choice, impulsive action, and impulsive personality traits. Psychopharmacology 233, 3361–3370.Google Scholar
Madden, GJ and Bickel, WK (2010). Impulsivity: The Behavioral and Neurological Science of Discounting. Washington, DC: American Psychological Association.Google Scholar
Mejía-Cruz, D, Green, L, Myerson, J, Morales-Chainé, S and Nieto, J. (2016). Delay and probability discounting by drug-dependent cocaine and marijuana users. Psychopharmacology 233, 2705–2714.Google Scholar
Mole, TB, Irvine, MA, Worbe, Y, Collins, P, Mitchell, SP, Bolton, S et al. (2015). Impulsivity in disorders of food and drug misuse. Psychological Medicine 45, 771–782.Google Scholar
Myerson, J and Green, L (1995). Discounting of delayed rewards: models of individual choice. Journal of the Experimental Analysis of Behavior 64, 263–276.Google Scholar
Myerson, J, Green, L and Warusawitharana, M (2001). Area under the curve as a measure of discounting. Journal of the Experimental Analysis of Behavior 76, 235–243.Google Scholar
Myerson, J, Green, L, van den Berk-Clark, C and Grucza, RA (2015). Male, but not female, alcohol-dependent African Americans discount delayed gains more steeply than propensity-score matched controls. Psychopharmacology 232, 4493–4503.Google Scholar
Ouimette, PE and Read, J (2014). Trauma and Substance Abuse: Causes, Consequences, and Treatment of Comorbid Disorders. Washington, DC: American Psychological Association.Google Scholar
Pivovarova, E, Tanaka, G, Tang, M, Bursztajn, HJ and First, MB (2016). Is helplessness still helpful in diagnosing posttraumatic stress disorder? Journal of Nervous and Mental Disease 204, 3–8.Google Scholar
Pulcu, E, Trotter, PD, Thomas, EJ, McFarquhar, M, Juhasz, G, Sahakian, BJ et al. (2014). Temporal discounting in major depressive disorder. Psychological Medicine 44, 1825–1834.Google Scholar
Rosenbaum, PR and Rubin, DB (1983). The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41–55.Google Scholar
Sheffer, CE, Christensen, DR, Landes, R, Carter, LP, Jackson, L and Bickel, WK (2014). Delay discounting rates: a strong prognostic indicator of smoking relapse. Addictive Behaviors 39, 1682–1689.Google Scholar
Simmen-Janevska, K, Forstmeier, S, Krammer, S and Maercker, A (2015). Does trauma impair self-control? Differences in delaying gratification between former indentured child laborers and nontraumatized controls. Violence and Victims 30, 1068–1081.Google Scholar
Snider, SE, LaConte, SM and Bickel, WK (2016). Episodic future thinking: expansion of the temporal window in individuals with alcohol dependence. Alcoholism: Clinical and Experimental Research 40, 1558–1566.Google Scholar
Tolin, DF and Foa, EB (2006). Sex differences in trauma and posttraumatic stress disorder: a quantitative review of 25 years of research. Psychological Bulletin 132, 959–992.Google Scholar