Structural Racism, Reward Related Decision Making and Substance Use Risk

NCT ID: NCT06221839

Last Updated: 2025-12-29

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

72 participants

Study Classification

OBSERVATIONAL

Study Start Date

2026-01-31

Study Completion Date

2026-07-31

Brief Summary

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The goal of this observational study, which has a pilot phase (R61) and a second, larger phase (R33), is to learn about the impact of indicators of structural racism (SR) on substance use risk in Puerto Rican adolescents living in the mainland US and in Puerto Rico. To do this, we will look at how indicators of SR relate to brain structure, brain function during reward-related choices, belief in a just world, and substance use risk indicators in Puerto Rican adolescents living in the mainland US (mostly in New York) and in Puerto Rico (mostly in San Juan). We are currently focused on the R61 (pilot) phase. This pilot phase aims to answer the question: Is there a relationship between indicators of SR and brain structure, brain function during reward-related decision making, and belief in a just world? If we are able to establish a relationship between SR indicators and outcomes, we will continue to the second phase of the study at that time.

We will be collecting data from a total of 72 adolescents and their parents; n=36 in NY; n=36 in PR). Participation in the research study will include: 1. an interview with the parent or caregiver (approximately 2.5 hours) regarding the child's demographics, mental health symptoms, past experiences, the parent or caregiver's relationship with the child, as well as cultural values and acculturation; 2. an interview with the child (approximately 2.5 hours) regarding the child's past experiences, their current beliefs, personality traits and mental health symptoms; 3. an MRI scan for the child including task-based, structural and resting-state functional connectivity (approximately 1 hour).

Detailed Description

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Substance use disorders (SUDs) are common, and are associated with significant impairment and public health costs (Behavioral health trends in the United States: Results from the 2014 National Survey on Drug Use and Health 2015). Adolescence is a key developmental period involving significant neurodevelopmental changes and is a critical risk period for the initiation of substance use and related negative outcomes, including substance use problems in adulthood (Andrews, Ahmed, \& Blakemore, 2021; Blakemore, 2012; Dawson, Goldstein, Chou, Ruan, \& Grant, 2008; Gray \& Squeglia, 2018; Guttmannova et al., 2011; Irons, Iacono, \& McGue, 2015; McCabe et al, 2022). Improved understanding of the neurocognitive mechanisms of substance use risk could lead to novel approaches to prevention.

The effects of structural racism (SR) are harmful. Between 50-75% of minoritized populations in the US report discriminatory treatment (Lee, Perez, Boykin, \& Mendoza-Denton, 2019), and experiences of ethnoracial discrimination during childhood and adolescence are associated with increased substance use in youth (e.g. Benner, Wang, Shen, Boyle, Polk, \& Cheng, 2018). While the impact of interpersonal discrimination on substance use risk in youth is important, it focuses on perceptions of experiences rather than the ways that minoritized individuals are systematically disadvantaged. Thus, we plan to measure the impact of indicators of structural racism on substance use risk, while controlling for experiences of discrimination, to determine the impact of SR indicators over and above individual experiences. Structural factors impact SUD risk: The impact of SR indicators on adolescent substance use risk is currently unknown, however, ethnoracial inequities have been documented in structural indices associated with increased substance use risk, including ethnoracial inequities in 1) household income in the US (Rivenbark et al, 2019), 2) high school dropout rates (Maynard, Salas-Wright, \& Vaughn, 2015; Townsend, Flisher, \& King, 2007), and 3) neighborhood violence (Fagan, Wright, \& Pinchevsky, 2014; Lambert, Brown, Phillips, \& Ialongo, 2004). Thus, generating a composite of indicators of SR using racial differences in census tract level income and educational attainment, and precinct level murder rates will provide an SR measure relevant for adolescent substance use risk.

Structural factors impact brain development. Neighborhood-level structural factors have been shown to impact brain structure and function (Maxwell, Taylor, \& Barch, 2022; Taylor, Cooper, Jackson, \& Barch, 2020), suggesting it is plausible that SR is related to neurodevelopmental changes. Neuroscience informs structural change. Results from neuroscience have influenced policy, e.g. child tax credits (e.g. Vickers, Zamani-Hank, \& Margerison, 2022) and court decisions, e.g. juvenile sentencing practices (e.g. Miller v. Alabama SC. 2012). Thus, neuroscience plays an important role in motivating and shaping structural-level changes, particularly for children and adolescents, underlining the importance of examining neural correlates of SR indicators.

Individual Differences in Reward-Related Decision Making Can Contribute to Substance Use Risk. Mechanisms by which greater exposure to SR could increase substance use are not known. Individuals with SUDs tend to have to prefer smaller, sooner over larger, later rewards - i.e. steeper delay discounting, compared to individuals without SUDs or related problems (e.g. Amlung, Vedelago, Acker, Balodis, \& MacKillop, 2017.). Steeper delay discounting has been interpreted as a sign of maladaptive impulsivity (Amlung, Vedelago, Acker, Balodis, \& MacKillop, 2017). However, learning to wait for larger, later rewards is theorized to emerge developmentally alongside a belief in a just world, as it is only sensible to wait for larger rewards if people get what they deserve (Lerner \& Miller, 1978). Belief in a just world relates to reward related decision making; both 1) exposure to unjust scenarios and 2) reduced belief in a just world is associated with steeper delay discounting (Lerner \& Miller, 1978). Thus, growing up in an unjust environment with high levels of SR, may promote steeper delay discounting. Steeper delay discounting may help secure available rewards in unjust environments. However, given the well-established link between steeper delay discounting and SUDs (Amlung, Vedelago, Acker, Balodis, \& MacKillop, 2017), when the reward is a substance, and immediate use is chosen over long-term health outcomes, this adaptation to the environment could increase the odds of risky substance use (Kim-Spoon et al, 2019). Improved understanding of how SR leads to increased substance use risk could inform novel prevention/intervention efforts at the structural level. For example, if steeper delay discounting moderates the relationship between higher levels of SR indicators and increased substance use risk, interventions could target 1) structural inequality, particularly the indicators measured, and 2) reward related decision making (Stein et al, 2016) to reduce the harmful effects of SR (Stein et al, 2016).

Protective Factors: Structural \& Family-Level Protective Factors. Area level protective factors may buffer the negative effects of SR on substance use risk, including the availability of churches and the percentage of minority owned businesses. The number of neighborhood churches per capita have been associated with lower likelihood of SUDs (Stockdale et al, 2007). Similarly, the number of minority-owned businesses in a neighborhood has a positive effects. For example, an increased number of Latine-owned businesses relates to reduced property crime rates (Stansfield, 2014). Thus, we will examine if the number of local, churches and Latine-owned businesses in the area buffers the effect of SR indicators on neural structure and function. Family-level processes, such as higher parental monitoring, parent-child communication and familism are associated with reduced substance use risk in Latine youth (Pokhrel, Unger, Wagner, Ritt-Olson, \& Sussman, 2008; German, Gonzales, \& Dumka, 2009). Examining the buffering effect of familial-level factors on the relationship between SR and neurodevelopment will inform if targeting family processes can help protect against the negative impact of SR.

The Boricua Youth Study, an opportunity: The Boricua Youth Study (BYS) started in 2000 with the goal of learning more about the mental health of Puerto Rican youth living in two contexts: San Juan, Puerto Rico, and the South Bronx, New York. Longitudinal data were collected over 3 Waves, between 2001-2004. The original youth participants of the BYS now have children, allowing a second generation of BYS to participate in research. Thus, working with BYS is an opportunity to: 1) measure SR indicators in two distinct contexts and 2) isolate the impact of SR indicators on substance use, by controlling for familial factors. This study will generate separate measures of SR indicators, with particular relevance to substance use risk-related outcomes, for Puerto Rican youth living in two contexts: in the US mainland and in PR. Thus, we will be able to 1) compare the structure of SR indicators between the two contexts; 2) determine if certain SR indices contribute more to substance use risk in one site than another. Intergenerational transference of substance use is well established. Furthermore, it is possible that familial history of SUD could influence youths' delay discounting choices, as has been found empirically (Dougherty et al, 2014). Therefore, to isolate the impact of SR indicators on brain structure, delay discounting related brain activity, and SUD risk, it is crucial to account for familial SUD risk factors. Other large datasets do not have prospectively captured data regarding familial SUD risk factors. Therefore, working with the BYS-ECHO will add key complementary information by enabling us to directly control for prospectively captured familial SUD risk factors, e.g. parental SUD and impulsivity.

R61 Specific Aims: Proof of Concept of relationship of indicators of SR with Neurocognitive Mechanisms: We will invite 72 children (aged 11-14, 50% female, 50% from SBx, 50% from PR), to provide home address history (last 5 yrs), substance use risk, belief in a just world and magnetic resonance imaging (MRI) for brain structure and DD-related brain function. Higher levels of SR indicators will relate to: Aim 1, Hypothesis 1 (H1): adolescent brain structure: lower grey matter volume of superior frontal, dorsal lateral and medial prefrontal cortices; Aim 2, H2: Steeper DD and less DD-related activity in dorsal medial prefrontal and anterior cingulate cortices, ventral striatum and insula; Aim 3, H3: Reduced belief in a just world. A moderate effect size association (r \> 0.30) found for H1, H2, or H3 will justify progression to the R33 phase.

Conditions

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Structural Racism Substance Use Risk

Keywords

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Adolescent Behavior Reward Related Decision Making fMRI

Study Design

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Observational Model Type

COHORT

Study Time Perspective

CROSS_SECTIONAL

Eligibility Criteria

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Inclusion Criteria

1. The adolescent participant is a biological or non-biological child of a member of the original Boricua Youth Study (BYS) sample.
2. The adolescent is between the ages of 11 to 14.5 at the time of recruitment, and 11 to \<15 at the time of study participation.
3. If the parent/caregiver is not an original BYS member, they have provided a consent to contact form.
4. Parent/caregiver is between the ages of 18-64.5 at the time of recruitment and 18 to \<65 at the time of study participation

Exclusion Criteria

1. Major neurological disorder (e.g. seizure disorder) or cognitive impairment (e.g., moderate to severe Autism Spectrum Disorder, Intellectual Disability)
Minimum Eligible Age

11 Years

Maximum Eligible Age

14 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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National Institute on Drug Abuse (NIDA)

NIH

Sponsor Role collaborator

Columbia University

OTHER

Sponsor Role lead

Responsible Party

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Tamara Sussman

Assistant Clinical Professor of Medical Psychology (in Psychiatry)

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Tamara J. Sussman, PhD

Role: PRINCIPAL_INVESTIGATOR

Columbia University

Central Contacts

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Tamara J. Sussman, PhD

Role: CONTACT

Phone: 646-774-6048

Email: [email protected]

References

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Lee RT, Perez AD, Boykin CM, Mendoza-Denton R. On the prevalence of racial discrimination in the United States. PLoS One. 2019 Jan 10;14(1):e0210698. doi: 10.1371/journal.pone.0210698. eCollection 2019.

Reference Type BACKGROUND
PMID: 30629706 (View on PubMed)

Amlung M, Vedelago L, Acker J, Balodis I, MacKillop J. Steep delay discounting and addictive behavior: a meta-analysis of continuous associations. Addiction. 2017 Jan;112(1):51-62. doi: 10.1111/add.13535. Epub 2016 Sep 1.

Reference Type BACKGROUND
PMID: 27450931 (View on PubMed)

Andrews JL, Ahmed SP, Blakemore SJ. Navigating the Social Environment in Adolescence: The Role of Social Brain Development. Biol Psychiatry. 2021 Jan 15;89(2):109-118. doi: 10.1016/j.biopsych.2020.09.012. Epub 2020 Sep 17.

Reference Type BACKGROUND
PMID: 33190844 (View on PubMed)

Benner AD, Wang Y, Shen Y, Boyle AE, Polk R, Cheng YP. Racial/ethnic discrimination and well-being during adolescence: A meta-analytic review. Am Psychol. 2018 Oct;73(7):855-883. doi: 10.1037/amp0000204. Epub 2018 Jul 19.

Reference Type BACKGROUND
PMID: 30024216 (View on PubMed)

Dawson DA, Goldstein RB, Chou SP, Ruan WJ, Grant BF. Age at first drink and the first incidence of adult-onset DSM-IV alcohol use disorders. Alcohol Clin Exp Res. 2008 Dec;32(12):2149-60. doi: 10.1111/j.1530-0277.2008.00806.x. Epub 2008 Sep 30.

Reference Type BACKGROUND
PMID: 18828796 (View on PubMed)

Dougherty DM, Charles NE, Mathias CW, Ryan SR, Olvera RL, Liang Y, Acheson A. Delay discounting differentiates pre-adolescents at high and low risk for substance use disorders based on family history. Drug Alcohol Depend. 2014 Oct 1;143:105-11. doi: 10.1016/j.drugalcdep.2014.07.012. Epub 2014 Jul 23.

Reference Type BACKGROUND
PMID: 25096271 (View on PubMed)

Fagan AA, Wright EM, Pinchevsky GM. The protective effects of neighborhood collective efficacy on adolescent substance use and violence following exposure to violence. J Youth Adolesc. 2014 Sep;43(9):1498-512. doi: 10.1007/s10964-013-0049-8. Epub 2013 Oct 30.

Reference Type BACKGROUND
PMID: 24170438 (View on PubMed)

German M, Gonzales NA, Dumka L. Familism Values as a Protective Factor for Mexican-origin Adolescents Exposed to Deviant Peers. J Early Adolesc. 2009 Feb;29(1):16-42. doi: 10.1177/0272431608324475.

Reference Type BACKGROUND
PMID: 21776180 (View on PubMed)

Guttmannova K, Bailey JA, Hill KG, Lee JO, Hawkins JD, Woods ML, Catalano RF. Sensitive periods for adolescent alcohol use initiation: predicting the lifetime occurrence and chronicity of alcohol problems in adulthood. J Stud Alcohol Drugs. 2011 Mar;72(2):221-31. doi: 10.15288/jsad.2011.72.221.

Reference Type BACKGROUND
PMID: 21388595 (View on PubMed)

Irons DE, Iacono WG, McGue M. Tests of the effects of adolescent early alcohol exposures on adult outcomes. Addiction. 2015 Feb;110(2):269-78. doi: 10.1111/add.12747. Epub 2014 Oct 27.

Reference Type BACKGROUND
PMID: 25251778 (View on PubMed)

Kim-Spoon J, Lauharatanahirun N, Peviani K, Brieant A, Deater-Deckard K, Bickel WK, King-Casas B. Longitudinal pathways linking family risk, neural risk processing, delay discounting, and adolescent substance use. J Child Psychol Psychiatry. 2019 Jun;60(6):655-664. doi: 10.1111/jcpp.13015. Epub 2019 Feb 27.

Reference Type BACKGROUND
PMID: 30809804 (View on PubMed)

Lambert SF, Brown TL, Phillips CM, Ialongo NS. The relationship between perceptions of neighborhood characteristics and substance use among urban African American adolescents. Am J Community Psychol. 2004 Dec;34(3-4):205-18. doi: 10.1007/s10464-004-7415-3.

Reference Type BACKGROUND
PMID: 15663207 (View on PubMed)

Lerner MJ, & Miller, DT. Just world research and the attribution process: Looking back and ahead. Psychological bulletin, 1978; 85(5).

Reference Type BACKGROUND

Maxwell MY, Taylor RL, Barch DM. Relationship Between Neighborhood Poverty and Externalizing Symptoms in Children: Mediation and Moderation by Environmental Factors and Brain Structure. Child Psychiatry Hum Dev. 2023 Dec;54(6):1710-1722. doi: 10.1007/s10578-022-01369-w. Epub 2022 May 21.

Reference Type BACKGROUND
PMID: 35596841 (View on PubMed)

Maynard BR, Salas-Wright CP, Vaughn MG. High school dropouts in emerging adulthood: substance use, mental health problems, and crime. Community Ment Health J. 2015 Apr;51(3):289-99. doi: 10.1007/s10597-014-9760-5. Epub 2014 Jul 17.

Reference Type BACKGROUND
PMID: 25030805 (View on PubMed)

McCabe SE, Schulenberg JE, Schepis TS, McCabe VV, Veliz PT. Longitudinal Analysis of Substance Use Disorder Symptom Severity at Age 18 Years and Substance Use Disorder in Adulthood. JAMA Netw Open. 2022 Apr 1;5(4):e225324. doi: 10.1001/jamanetworkopen.2022.5324.

Reference Type BACKGROUND
PMID: 35363270 (View on PubMed)

Miller v. Alabama SC. 2012.

Reference Type BACKGROUND

Pokhrel P, Unger JB, Wagner KD, Ritt-Olson A, Sussman S. Effects of parental monitoring, parent-child communication, and parents' expectation of the child's acculturation on the substance use behaviors of urban, Hispanic adolescents. J Ethn Subst Abuse. 2008;7(2):200-13. doi: 10.1080/15332640802055665.

Reference Type BACKGROUND
PMID: 19042806 (View on PubMed)

Rivenbark JG, Copeland WE, Davisson EK, Gassman-Pines A, Hoyle RH, Piontak JR, Russell MA, Skinner AT, Odgers CL. Perceived social status and mental health among young adolescents: Evidence from census data to cellphones. Dev Psychol. 2019 Mar;55(3):574-585. doi: 10.1037/dev0000551.

Reference Type BACKGROUND
PMID: 30802108 (View on PubMed)

Stansfield R. Safer cities: A macro-level analysis of recent immigration, Hispanic-owned businesses, and crime rates in the United States. Journal of Urban Affairs. 2014;36(3):503-18.

Reference Type BACKGROUND

Stein JS, Wilson AG, Koffarnus MN, Daniel TO, Epstein LH, Bickel WK. Unstuck in time: episodic future thinking reduces delay discounting and cigarette smoking. Psychopharmacology (Berl). 2016 Oct;233(21-22):3771-3778. doi: 10.1007/s00213-016-4410-y. Epub 2016 Aug 23.

Reference Type BACKGROUND
PMID: 27553824 (View on PubMed)

Stockdale SE, Wells KB, Tang L, Belin TR, Zhang L, Sherbourne CD. The importance of social context: neighborhood stressors, stress-buffering mechanisms, and alcohol, drug, and mental health disorders. Soc Sci Med. 2007 Nov;65(9):1867-81. doi: 10.1016/j.socscimed.2007.05.045. Epub 2007 Jul 5.

Reference Type BACKGROUND
PMID: 17614176 (View on PubMed)

Taylor RL, Cooper SR, Jackson JJ, Barch DM. Assessment of Neighborhood Poverty, Cognitive Function, and Prefrontal and Hippocampal Volumes in Children. JAMA Netw Open. 2020 Nov 2;3(11):e2023774. doi: 10.1001/jamanetworkopen.2020.23774.

Reference Type BACKGROUND
PMID: 33141160 (View on PubMed)

Townsend L, Flisher AJ, King G. A systematic review of the relationship between high school dropout and substance use. Clin Child Fam Psychol Rev. 2007 Dec;10(4):295-317. doi: 10.1007/s10567-007-0023-7.

Reference Type BACKGROUND
PMID: 17636403 (View on PubMed)

Vickers EKH, K.; Zamani-Hank, Y.; Margerison, C. Did Cash Transfers from the 2021 Child Tax Credit Expansion Improve Maternal and Infant Health? A Policy Brief 2022

Reference Type BACKGROUND

Behavioral health trends in the United States: Results from the 2014 National Survey on Drug Use and Health Center for Behavioral Health Statistics and Quality, 2015 Contract No.: (HHS Publication No. SMA 15- 4927, NSDUH Series H-50).

Reference Type BACKGROUND

Other Identifiers

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1R61DA058985

Identifier Type: NIH

Identifier Source: secondary_id

View Link

8499

Identifier Type: OTHER

Identifier Source: secondary_id

AAAV4120

Identifier Type: -

Identifier Source: org_study_id