Clinical trial NCT05879198: Train Your Brain: A Pilot Project to Improve Memory and Decision Making
Official title: Train Your Brain: A Pilot Project to Improve Memory and Decision Making to Improve Outcomes Among Youth
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Behavior, Health
Keywords: delay discounting
computer-based intervention
executive functioning
substance use
working memory
Lead sponsor: Henry Ford Health System
Sponsor class: OTHER
Collaborators: name: National Institutes of Health (NIH)
name: National Institute on Drug Abuse (NIDA)
First posted: 2023-05-30
Enrollment: 23
Sex: ALL
Minimum age (years): 12
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: PREVENTION

Brief summary: The goal of this clinical trial is to pilot a computer-based working memory training program to improve delay discounting (DD) and prevent substance use among at-risk adolescents in a traditionally underserved area. Results from the study will inform future efforts substance use prevention efforts targeted at youth exposed to adverse childhood experiences. Findings will also refine future models of intervention delivery in traditionally underserved communities.

The main question\[s\] it aims to answer are:

* Determine if the intervention can be delivered feasibly, acceptability, and at sufficient dosage
* Evaluate the utility of the recruitment and retention procedures as well as identify barriers to participation

Detailed description: Youth exposed to early childhood adversity are at increased risk for engaging in problematic substance use, leading to myriad negative health outcomes, including HIV exposure, injury, and impaired driving. Adolescents from low-resource communities evidence elevated rates of exposure to adverse childhood experiences, yet have limited access to evidence-based preventative interventions. Thus, there is a critical need for services that can feasibly target specific mechanisms linking early adversity to the onset and escalation of substance use in traditionally underserved communities.

One such target is delay discounting (DD), the tendency to select small, immediately available rewards at the expense of larger, delayed, rewards. DD has been linked to early substance use initiation and more frequent and severe use across adolescence. Moreover, youth exposed to early childhood adversity evidence more problematic levels of DD, indicating that DD may be a pathway by which early trauma exposure leads to drug and alcohol use.

Iterative pilot trials of approximately 10 youth participants + their parents/guardians will be conducted to examine effectiveness of procedures and initial implementation outcomes.

Research from our team suggests that computer-based interventions targeting proximal cognitive skills, specifically working memory, can improve rates of DD. Moreover, computerized interventions are highly transportable and scalable, making them ideal for dissemination in low-resource communities. The current project proposes to pilot a computer-based working memory (WM) training program to improve DD and prevent substance use among at-risk adolescents in a traditionally underserved area.

Eligibility criteria: Youth Inclusion Criteria:

1. Youth must be between the ages of 12 and 14 and have a parent/guardian willing to provide consent for their participation
2. Youth must be proficient in English in order to validly complete all assessment measures and take part in the computer-based training
3. Youth must be willing to commit to participate in two to three 20-30-minute computer-based trainings for five to seven weeks
4. Youth must be willing to take part in assessments before and immediately following the intervention as well as a confidential interview with researchers after completing the computer sessions

Youth Exclusion Criteria:

1. Currently psychotic
2. Currently suicidal or evidence active suicidal ideation
3. Currently diagnosed with a substance use disorder

Parent Inclusion Criteria:

1. Parent of child participating in intervention and willing to provide consent for themselves and their children to participate
2. Proficient in English in order to validly complete all assessment measures
3. Willing to take part in assessments

Parent Exclusion Criteria:

1. Currently psychotic
2. Currently suicidal or evidence active suicidal ideation
3. Currently diagnosed with a substance use disorder

Primary outcomes:
measure: Number of Participants With Change in Delay Discounting 5 Trial Adjusted Measure
timeFrame: Baseline, 7 weeks
measure: Change in Consideration of Future Consequences Scale
timeFrame: Baseline, 7 weeks
measure: Change in Tower of Hanoi
timeFrame: Baseline, 7 weeks
measure: Change in Letter Number Sequencing
timeFrame: Baseline, 7 weeks
measure: Change in Iowa Gambling Task
timeFrame: Baseline, 7 weeks
Secondary outcomes:
measure: Change in Youth Risk Behavior Survey
timeFrame: Baseline, 7 weeks
measure: Change in Alcohol/Marijuana Effect Expectancies
timeFrame: Baseline, 7 weeks
Other outcomes:
Locations:
city: Detroit
country: United States
facility: Downtown Boxing Gym
state: Michigan
city: Flint
country: United States
facility: Freedom Schools Collaborative
state: Michigan
Study officials:
affiliation: Henry Ford Health
name: Julia Felton
role: PRINCIPAL_INVESTIGATOR
References:
citation: Dube SR, Miller JW, Brown DW, Giles WH, Felitti VJ, Dong M, Anda RF. Adverse childhood experiences and the association with ever using alcohol and initiating alcohol use during adolescence. J Adolesc Health. 2006 Apr;38(4):444.e1-10. doi: 10.1016/j.jadohealth.2005.06.006.
citation: Afuseh E, Pike CA, Oruche UM. Individualized approach to primary prevention of substance use disorder: age-related risks. Subst Abuse Treat Prev Policy. 2020 Aug 14;15(1):58. doi: 10.1186/s13011-020-00300-7.
citation: Taylor OD. Life stressors and substance abuse in African American adolescents residing in a public housing community. Journal of Human Behavior in the Social Environment. 2015;25(4):288-303.
citation: Bolland KA, Bolland JM, Tomek S, Devereaux RS, Mrug S, Wimberly JC. Trajectories of adolescent alcohol use by gender and early initiation status. Youth & Society. 2016;48(1):3-32.
citation: Koh HK, Oppenheimer SC, Massin-Short SB, Emmons KM, Geller AC, Viswanath K. Translating research evidence into practice to reduce health disparities: a social determinants approach. Am J Public Health. 2010 Apr 1;100 Suppl 1(Suppl 1):S72-80. doi: 10.2105/AJPH.2009.167353. Epub 2010 Feb 10.
citation: Alegria M, Carson NJ, Goncalves M, Keefe K. Disparities in treatment for substance use disorders and co-occurring disorders for ethnic/racial minority youth. J Am Acad Child Adolesc Psychiatry. 2011 Jan;50(1):22-31. doi: 10.1016/j.jaac.2010.10.005. Epub 2010 Nov 18.
citation: Griskevicius V, Tybur JM, Delton AW, Robertson TE. The influence of mortality and socioeconomic status on risk and delayed rewards: a life history theory approach. J Pers Soc Psychol. 2011 Jun;100(6):1015-26. doi: 10.1037/a0022403.
citation: Lovallo WR. Early life adversity reduces stress reactivity and enhances impulsive behavior: implications for health behaviors. Int J Psychophysiol. 2013 Oct;90(1):8-16. doi: 10.1016/j.ijpsycho.2012.10.006. Epub 2012 Oct 17.
citation: MacKillop J. Integrating behavioral economics and behavioral genetics: delayed reward discounting as an endophenotype for addictive disorders. J Exp Anal Behav. 2013 Jan;99(1):14-31. doi: 10.1002/jeab.4. Epub 2012 Dec 5.
citation: Audrain-McGovern J, Rodriguez D, Epstein LH, Cuevas J, Rodgers K, Wileyto EP. Does delay discounting play an etiological role in smoking or is it a consequence of smoking? Drug Alcohol Depend. 2009 Aug 1;103(3):99-106. doi: 10.1016/j.drugalcdep.2008.12.019. Epub 2009 May 14.
citation: Felton JW, Collado A, Ingram K, Lejuez CW, Yi R. Changes in delay discounting, substance use, and weight status across adolescence. Health Psychol. 2020 May;39(5):413-420. doi: 10.1037/hea0000833. Epub 2020 Jan 9.
citation: MacKillop J, Amlung MT, Few LR, Ray LA, Sweet LH, Munafo MR. Delayed reward discounting and addictive behavior: a meta-analysis. Psychopharmacology (Berl). 2011 Aug;216(3):305-21. doi: 10.1007/s00213-011-2229-0. Epub 2011 Mar 4.
citation: Felton JW, Collado A, Ingram KM, Doran K, Yi R. Improvement of Working Memory is a Mechanism for Reductions in Delay Discounting Among Mid-Age Individuals in an Urban Medically Underserved Area. Ann Behav Med. 2019 Oct 7;53(11):988-998. doi: 10.1093/abm/kaz010.
citation: Nelson SE, Van Ryzin MJ, Dishion TJ. Alcohol, marijuana, and tobacco use trajectories from age 12 to 24 years: demographic correlates and young adult substance use problems. Dev Psychopathol. 2015 Feb;27(1):253-77. doi: 10.1017/S0954579414000650. Epub 2014 Jul 14.
citation: Grant BF, Dawson DA. Age of onset of drug use and its association with DSM-IV drug abuse and dependence: results from the National Longitudinal Alcohol Epidemiologic Survey. J Subst Abuse. 1998;10(2):163-73. doi: 10.1016/s0899-3289(99)80131-x.
citation: Dube SR, Felitti VJ, Dong M, Chapman DP, Giles WH, Anda RF. Childhood abuse, neglect, and household dysfunction and the risk of illicit drug use: the adverse childhood experiences study. Pediatrics. 2003 Mar;111(3):564-72. doi: 10.1542/peds.111.3.564.
citation: Lopez CM, Andrews AR, Chisolm AM, de Arellano MA, Saunders B, Kilpatrick DG. Racial/ethnic differences in trauma exposure and mental health disorders in adolescents. Cultur Divers Ethnic Minor Psychol. 2017 Jul;23(3):382-387. doi: 10.1037/cdp0000126. Epub 2016 Oct 27.
citation: Font SA, Maguire-Jack K. Pathways from childhood abuse and other adversities to adult health risks: The role of adult socioeconomic conditions. Child Abuse Negl. 2016 Jan;51:390-9. doi: 10.1016/j.chiabu.2015.05.013. Epub 2015 Jun 6.
citation: Primm AB, Vasquez MJ, Mays RA, Sammons-Posey D, McKnight-Eily LR, Presley-Cantrell LR, McGuire LC, Chapman DP, Perry GS. The role of public health in addressing racial and ethnic disparities in mental health and mental illness. Prev Chronic Dis. 2010 Jan;7(1):A20. Epub 2009 Dec 15.
citation: Derose KP, Gresenz CR, Ringel JS. Understanding disparities in health care access--and reducing them--through a focus on public health. Health Aff (Millwood). 2011 Oct;30(10):1844-51. doi: 10.1377/hlthaff.2011.0644.
citation: Andrulis DP. Access to care is the centerpiece in the elimination of socioeconomic disparities in health. Ann Intern Med. 1998 Sep 1;129(5):412-6. doi: 10.7326/0003-4819-129-5-199809010-00012.
citation: Onrust SA, Otten R, Lammers J, Smit F. School-based programmes to reduce and prevent substance use in different age groups: What works for whom? Systematic review and meta-regression analysis. Clin Psychol Rev. 2016 Mar;44:45-59. doi: 10.1016/j.cpr.2015.11.002. Epub 2015 Dec 15.
citation: Dixon M. Delay Discounting and Pathological Gambling. Analysis of Gambling Behavior. 2008;2(2). https://repository.stcloudstate.edu/agb/vol2/iss2/1
citation: Jarmolowicz DP, Cherry JB, Reed DD, Bruce JM, Crespi JM, Lusk JL, Bruce AS. Robust relation between temporal discounting rates and body mass. Appetite. 2014 Jul;78:63-7. doi: 10.1016/j.appet.2014.02.013. Epub 2014 Mar 17.
citation: Beauchaine TP, Ben-David I, Sela A. Attention-deficit/hyperactivity disorder, delay discounting, and risky financial behaviors: A preliminary analysis of self-report data. PLoS One. 2017 May 8;12(5):e0176933. doi: 10.1371/journal.pone.0176933. eCollection 2017.
citation: Murphy JG, MacKillop J. Relative reinforcing efficacy of alcohol among college student drinkers. Exp Clin Psychopharmacol. 2006 May;14(2):219-27. doi: 10.1037/1064-1297.14.2.219.
citation: 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.
citation: Strickland JC, Lee DC, Vandrey R, Johnson MW. A systematic review and meta-analysis of delay discounting and cannabis use. Exp Clin Psychopharmacol. 2021 Dec;29(6):696-710. doi: 10.1037/pha0000378. Epub 2020 Apr 20.
citation: Bickel WK, Koffarnus MN, Moody L, Wilson AG. The behavioral- and neuro-economic process of temporal discounting: A candidate behavioral marker of addiction. Neuropharmacology. 2014 Jan;76 Pt B(0 0):518-27. doi: 10.1016/j.neuropharm.2013.06.013. Epub 2013 Jun 24.
citation: Fernie G, Peeters M, Gullo MJ, Christiansen P, Cole JC, Sumnall H, Field M. Multiple behavioural impulsivity tasks predict prospective alcohol involvement in adolescents. Addiction. 2013 Nov;108(11):1916-23. doi: 10.1111/add.12283. Epub 2013 Aug 14.
citation: Field M, Christiansen P, Cole J, Goudie A. Delay discounting and the alcohol Stroop in heavy drinking adolescents. Addiction. 2007 Apr;102(4):579-86. doi: 10.1111/j.1360-0443.2007.01743.x. Epub 2007 Feb 15.
citation: Martinez-Loredo V, Fernandez-Hermida JR, Fernandez-Artamendi S, Carballo JL, Garcia-Cueto E, Garcia-Rodriguez O. The association of both self-reported and behavioral impulsivity with the annual prevalence of substance use among early adolescents. Subst Abuse Treat Prev Policy. 2015 Jun 10;10:23. doi: 10.1186/s13011-015-0019-0.
citation: Khurana A, Romer D, Betancourt LM, Hurt H. Working memory ability and early drug use progression as predictors of adolescent substance use disorders. Addiction. 2017 Jul;112(7):1220-1228. doi: 10.1111/add.13792. Epub 2017 Apr 19.
citation: 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.
citation: Kim-Spoon J, McCullough ME, Bickel WK, Farley JP, Longo GS. Longitudinal Associations Among Religiousness, Delay Discounting, and Substance Use Initiation in Early Adolescence. J Res Adolesc. 2015 Mar;25(1):36-43. doi: 10.1111/jora.12104.
citation: Richardson CG, Edalati H. Application of a Brief Measure of Delay Discounting to Examine the Relationship Between Delay Discounting and the Initiation of Substance Use Among Adolescents. Subst Use Misuse. 2016;51(4):540-4. doi: 10.3109/10826084.2015.1126740. Epub 2016 Mar 4.
citation: Green L, Myerson J, Lichtman D, Rosen S, Fry A. Temporal discounting in choice between delayed rewards: the role of age and income. Psychol Aging. 1996 Mar;11(1):79-84. doi: 10.1037//0882-7974.11.1.79.
citation: Steinberg L, Graham S, O'Brien L, Woolard J, Cauffman E, Banich M. Age differences in future orientation and delay discounting. Child Dev. 2009 Jan-Feb;80(1):28-44. doi: 10.1111/j.1467-8624.2008.01244.x.
citation: Johnston L, Miech R, O'Malley P, Bachman J, Schulenberg J, Patrick M. Monitoring the Future national survey results on drug use, 1975-2019: Overview, key findings on adolescent drug use. Published online 2020.
citation: Lovallo WR, Farag NH, Sorocco KH, Acheson A, Cohoon AJ, Vincent AS. Early life adversity contributes to impaired cognition and impulsive behavior: studies from the Oklahoma Family Health Patterns Project. Alcohol Clin Exp Res. 2013 Apr;37(4):616-23. doi: 10.1111/acer.12016. Epub 2012 Nov 5.
citation: Simmen-Janevska K, Forstmeier S, Krammer S, Maercker A. Does Trauma Impair Self-Control? Differences in Delaying Gratification Between Former Indentured Child Laborers and Nontraumatized Controls. Violence Vict. 2015;30(6):1068-81. doi: 10.1891/0886-6708.VV-D-13-00174. Epub 2015 Oct 5.
citation: Bledowski C, Kaiser J, Rahm B. Basic operations in working memory: contributions from functional imaging studies. Behav Brain Res. 2010 Dec 25;214(2):172-9. doi: 10.1016/j.bbr.2010.05.041. Epub 2010 Jun 1.
citation: Baddeley A. Working memory: theories, models, and controversies. Annu Rev Psychol. 2012;63:1-29. doi: 10.1146/annurev-psych-120710-100422. Epub 2011 Sep 27.
citation: Baddeley A. Working memory. Science. 1992 Jan 31;255(5044):556-9. doi: 10.1126/science.1736359.
citation: Wesley MJ, Bickel WK. Remember the future II: meta-analyses and functional overlap of working memory and delay discounting. Biol Psychiatry. 2014 Mar 15;75(6):435-48. doi: 10.1016/j.biopsych.2013.08.008. Epub 2013 Sep 13.
citation: Fabio RA, Bianco M, Capri T, Marino F, Ruta L, Vagni D, Pioggia G. Working memory and decision making in children with ADHD: an analysis of delay discounting with the use of the dual-task paradigm. BMC Psychiatry. 2020 Jun 1;20(1):272. doi: 10.1186/s12888-020-02677-y.
citation: Szuhany KL, MacKenzie D Jr, Otto MW. The impact of depressed mood, working memory capacity, and priming on delay discounting. J Behav Ther Exp Psychiatry. 2018 Sep;60:37-41. doi: 10.1016/j.jbtep.2018.03.001. Epub 2018 Mar 7.
citation: Rosenberg MD, Martinez SA, Rapuano KM, Conley MI, Cohen AO, Cornejo MD, Hagler DJ Jr, Meredith WJ, Anderson KM, Wager TD, Feczko E, Earl E, Fair DA, Barch DM, Watts R, Casey BJ. Behavioral and Neural Signatures of Working Memory in Childhood. J Neurosci. 2020 Jun 24;40(26):5090-5104. doi: 10.1523/JNEUROSCI.2841-19.2020. Epub 2020 May 25.
citation: Noble KG, McCandliss BD, Farah MJ. Socioeconomic gradients predict individual differences in neurocognitive abilities. Dev Sci. 2007 Jul;10(4):464-80. doi: 10.1111/j.1467-7687.2007.00600.x.
citation: Waber DP, De Moor C, Forbes PW, Almli CR, Botteron KN, Leonard G, Milovan D, Paus T, Rumsey J; Brain Development Cooperative Group. The NIH MRI study of normal brain development: performance of a population based sample of healthy children aged 6 to 18 years on a neuropsychological battery. J Int Neuropsychol Soc. 2007 Sep;13(5):729-46. doi: 10.1017/S1355617707070841. Epub 2007 May 18.
citation: Farah MJ, Shera DM, Savage JH, Betancourt L, Giannetta JM, Brodsky NL, Malmud EK, Hurt H. Childhood poverty: specific associations with neurocognitive development. Brain Res. 2006 Sep 19;1110(1):166-74. doi: 10.1016/j.brainres.2006.06.072. Epub 2006 Aug 1.
citation: Evans GW, Schamberg MA. Childhood poverty, chronic stress, and adult working memory. Proc Natl Acad Sci U S A. 2009 Apr 21;106(16):6545-9. doi: 10.1073/pnas.0811910106. Epub 2009 Mar 30.
citation: Bickel WK, Moody L, Quisenberry AJ, Ramey CT, Sheffer CE. A Competing Neurobehavioral Decision Systems model of SES-related health and behavioral disparities. Prev Med. 2014 Nov;68:37-43. doi: 10.1016/j.ypmed.2014.06.032. Epub 2014 Jul 6.
citation: Kenrick DT, Griskevicius V, Sundie JM, Li NP, Li YJ, Neuberg SL. Deep Rationality: The Evolutionary Economics of Decision Making. Soc Cogn. 2009 Oct 1;27(5):764-785. doi: 10.1521/soco.2009.27.5.764.
citation: Jachimowicz JM, Chafik S, Munrat S, Prabhu JC, Weber EU. Community trust reduces myopic decisions of low-income individuals. Proc Natl Acad Sci U S A. 2017 May 23;114(21):5401-5406. doi: 10.1073/pnas.1617395114. Epub 2017 Apr 11.
citation: Lawrance EC. Poverty and the Rate of Time Preference: Evidence from Panel Data. Journal of Political Economy. 1991;99(1):54-77. doi:10.1086/261740
citation: Lengua LJ, Moran L, Zalewski M, Ruberry E, Kiff C, Thompson S. Relations of growth in effortful control to family income, cumulative risk, and adjustment in preschool-age children. J Abnorm Child Psychol. 2015 May;43(4):705-20. doi: 10.1007/s10802-014-9941-2.
citation: Kidd C, Palmeri H, Aslin RN. Rational snacking: young children's decision-making on the marshmallow task is moderated by beliefs about environmental reliability. Cognition. 2013 Jan;126(1):109-14. doi: 10.1016/j.cognition.2012.08.004. Epub 2012 Oct 9.
citation: Bickel WK, Miller ML, Yi R, Kowal BP, Lindquist DM, Pitcock JA. Behavioral and neuroeconomics of drug addiction: competing neural systems and temporal discounting processes. Drug Alcohol Depend. 2007 Sep;90 Suppl 1(Suppl 1):S85-91. doi: 10.1016/j.drugalcdep.2006.09.016. Epub 2006 Nov 13.
citation: Koffarnus MN, Jarmolowicz DP, Mueller ET, Bickel WK. Changing delay discounting in the light of the competing neurobehavioral decision systems theory: a review. J Exp Anal Behav. 2013 Jan;99(1):32-57. doi: 10.1002/jeab.2. Epub 2012 Dec 5.
citation: Kane MJ, Engle RW. The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: an individual-differences perspective. Psychon Bull Rev. 2002 Dec;9(4):637-71. doi: 10.3758/bf03196323.
citation: Tiffany ST. A cognitive model of drug urges and drug-use behavior: role of automatic and nonautomatic processes. Psychol Rev. 1990 Apr;97(2):147-68. doi: 10.1037/0033-295x.97.2.147.
citation: Nielsen L, Riddle M, King JW; NIH Science of Behavior Change Implementation Team; Aklin WM, Chen W, Clark D, Collier E, Czajkowski S, Esposito L, Ferrer R, Green P, Hunter C, Kehl K, King R, Onken L, Simmons JM, Stoeckel L, Stoney C, Tully L, Weber W. The NIH Science of Behavior Change Program: Transforming the science through a focus on mechanisms of change. Behav Res Ther. 2018 Feb;101:3-11. doi: 10.1016/j.brat.2017.07.002. Epub 2017 Jul 6.
citation: Gunn RL, Gerst KR, Wiemers EA, Redick TS, Finn PR. Predictors of Effective Working Memory Training in Individuals with Alcohol Use Disorders. Alcohol Clin Exp Res. 2018 Dec;42(12):2432-2441. doi: 10.1111/acer.13892. Epub 2018 Oct 25.
citation: Houben K, Wiers RW, Jansen A. Getting a grip on drinking behavior: training working memory to reduce alcohol abuse. Psychol Sci. 2011 Jul;22(7):968-75. doi: 10.1177/0956797611412392. Epub 2011 Jun 17.
citation: Khemiri L, Brynte C, Stunkel A, Klingberg T, Jayaram-Lindstrom N. Working Memory Training in Alcohol Use Disorder: A Randomized Controlled Trial. Alcohol Clin Exp Res. 2019 Jan;43(1):135-146. doi: 10.1111/acer.13910. Epub 2018 Nov 21.
citation: Snider SE, Deshpande HU, Lisinski JM, Koffarnus MN, LaConte SM, Bickel WK. Working Memory Training Improves Alcohol Users' Episodic Future Thinking: A Rate-Dependent Analysis. Biol Psychiatry Cogn Neurosci Neuroimaging. 2018 Feb;3(2):160-167. doi: 10.1016/j.bpsc.2017.11.002. Epub 2017 Nov 21.
citation: Zhu Y, Jiang H, Su H, Zhong N, Li R, Li X, Chen T, Tan H, Du J, Xu D, Yan H, Xu D, Zhao M. A Newly Designed Mobile-Based Computerized Cognitive Addiction Therapy App for the Improvement of Cognition Impairments and Risk Decision Making in Methamphetamine Use Disorder: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2018 Jun 20;6(6):e10292. doi: 10.2196/10292.
citation: Bickel WK, Yi R, Landes RD, Hill PF, Baxter C. Remember the future: working memory training decreases delay discounting among stimulant addicts. Biol Psychiatry. 2011 Feb 1;69(3):260-5. doi: 10.1016/j.biopsych.2010.08.017. Epub 2010 Oct 20.
citation: Rass O, Schacht RL, Buckheit K, Johnson MW, Strain EC, Mintzer MZ. A randomized controlled trial of the effects of working memory training in methadone maintenance patients. Drug Alcohol Depend. 2015 Nov 1;156:38-46. doi: 10.1016/j.drugalcdep.2015.08.012. Epub 2015 Aug 24.
citation: Collado A, Felton J, Grunevski S, Doran K, Yi R. Working Memory Training Reduces Cigarette Smoking Among Low-Income Individuals With Elevated Delay Discounting. Nicotine Tob Res. 2022 Apr 28;24(6):890-896. doi: 10.1093/ntr/ntac005.
citation: Karbach J, Unger K. Executive control training from middle childhood to adolescence. Front Psychol. 2014 May 7;5:390. doi: 10.3389/fpsyg.2014.00390. eCollection 2014.
citation: Van der Molen MJ, Van Luit JE, Van der Molen MW, Klugkist I, Jongmans MJ. Effectiveness of a computerised working memory training in adolescents with mild to borderline intellectual disabilities. J Intellect Disabil Res. 2010 May;54(5):433-47. doi: 10.1111/j.1365-2788.2010.01285.x.
citation: Sweeney MM, Rass O, DiClemente C, Schacht RL, Vo HT, Fishman MJ, Leoutsakos JS, Mintzer MZ, Johnson MW. Working Memory Training for Adolescents With Cannabis Use Disorders: A Randomized Controlled Trial. J Child Adolesc Subst Abuse. 2018;27(4):211-226. doi: 10.1080/1067828X.2018.1451793. Epub 2018 Apr 10.
citation: Katz B, Shah P. The role of child socioeconomic status in cognitive training outcomes. Journal of Applied Developmental Psychology. 2017;53:139-150. doi:10.1016/j.appdev.2017.10.003
citation: Roording-Ragetlie S, Klip H, Buitelaar J, Slaats-Willemse D. Working memory training in children with neuropsychiatric disorders and mild to borderline intellectual functioning, the role of coaching; a double-blind randomized controlled trial. BMC Psychiatry. 2017 Mar 28;17(1):114. doi: 10.1186/s12888-017-1274-6.
citation: Marsch LA, Grabinski MJ, Bickel WK, Desrosiers A, Guarino H, Muehlbach B, Solhkhah R, Taufique S, Acosta M. Computer-assisted HIV prevention for youth with substance use disorders. Subst Use Misuse. 2011;46(1):46-56. doi: 10.3109/10826084.2011.521088.
citation: Weisz JR, Jensen AL, McLeod BD. Development and Dissemination of Child and Adolescent Psychotherapies: Milestones, Methods, and a New Deployment-Focused Model. In: Psychosocial Treatments for Child and Adolescent Disorders: Empirically Based Strategies for Clinical Practice, 2nd Ed. American Psychological Association; 2005:9-39.
citation: Toumbourou JW, Hemphill SA, Tresidder J, Humphreys C, Edwards J, Murray D. Mental health promotion and socio-economic disadvantage: lessons from substance abuse, violence and crime prevention and child health. Health Promot J Austr. 2007 Dec;18(3):184-90. doi: 10.1071/he07184.
citation: Lemstra M, Bennett NR, Neudorf C, Kunst A, Nannapaneni U, Warren LM, Kershaw T, Scott CR. A meta-analysis of marijuana and alcohol use by socio-economic status in adolescents aged 10-15 years. Can J Public Health. 2008 May-Jun;99(3):172-7. doi: 10.1007/BF03405467.
citation: Felton JW, Collado A, Cinader M, Lejuez CW, Chronis-Tuscano A, Yi R. Exposure to maternal depressive symptoms and growth in adolescent substance use: The mediating role of delay discounting. Dev Psychopathol. 2021 Oct;33(4):1279-1289. doi: 10.1017/S0954579420000486.
citation: Felton JW, Collado A, Shadur JM, Lejuez CW, MacPherson L. Sex differences in self-report and behavioral measures of disinhibition predicting marijuana use across adolescence. Exp Clin Psychopharmacol. 2015 Aug;23(4):265-74. doi: 10.1037/pha0000031.
citation: Felton JW, Kofler MJ, Lopez CM, Saunders BE, Kilpatrick DG. The emergence of co-occurring adolescent polysubstance use and depressive symptoms: A latent growth modeling approach. Dev Psychopathol. 2015 Nov;27(4 Pt 1):1367-83. doi: 10.1017/S0954579414001473.
citation: Collins SE, Clifasefi SL, Stanton J, The Leap Advisory Board, Straits KJE, Gil-Kashiwabara E, Rodriguez Espinosa P, Nicasio AV, Andrasik MP, Hawes SM, Miller KA, Nelson LA, Orfaly VE, Duran BM, Wallerstein N. Community-based participatory research (CBPR): Towards equitable involvement of community in psychology research. Am Psychol. 2018 Oct;73(7):884-898. doi: 10.1037/amp0000167. Epub 2018 Jan 22.
citation: Bogart LM, Uyeda K. Community-based participatory research: partnering with communities for effective and sustainable behavioral health interventions. Health Psychol. 2009 Jul;28(4):391-3. doi: 10.1037/a0016387.
citation: Elwyn G, Frosch D, Thomson R, Joseph-Williams N, Lloyd A, Kinnersley P, Cording E, Tomson D, Dodd C, Rollnick S, Edwards A, Barry M. Shared decision making: a model for clinical practice. J Gen Intern Med. 2012 Oct;27(10):1361-7. doi: 10.1007/s11606-012-2077-6. Epub 2012 May 23.
citation: Kitson A, Harvey G, McCormack B. Enabling the implementation of evidence based practice: a conceptual framework. Qual Health Care. 1998 Sep;7(3):149-58. doi: 10.1136/qshc.7.3.149.
citation: Harding GH and H. Detroit remains among nation's most violent big cities, FBI statistics show. The Detroit News. Accessed September 30, 2021. https://www.detroitnews.com/story/news/local/michigan/2021/09/27/detroit-most-violent-big-us-cities-fbiuniform- crime-report-2020/5883984001/
citation: Michigan.gov. SOM - New dashboard provides data on recent trends in drug overdoses, utilization of prevention and harm reduction services. Accessed September 29, 2021. https://www.michigan.gov/som/0,4669,7-192-29942_34762-562458--,00.html
citation: Rhyan C, Turner A, Ehrlich E, Stanik C. Access to Behavioral Healthcare in Michigan.
citation: von Bastian CC, Langer N, Jancke L, Oberauer K. Effects of working memory training in young and old adults. Mem Cognit. 2013 May;41(4):611-24. doi: 10.3758/s13421-012-0280-7.
citation: Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, Williamson D, Ryan N. Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry. 1997 Jul;36(7):980-8. doi: 10.1097/00004583-199707000-00021.
citation: Anda RF, Dong M, Brown DW, Felitti VJ, Giles WH, Perry GS, Valerie EJ, Dube SR. The relationship of adverse childhood experiences to a history of premature death of family members. BMC Public Health. 2009 Apr 16;9:106. doi: 10.1186/1471-2458-9-106.
citation: Cronholm PF, Forke CM, Wade R, Bair-Merritt MH, Davis M, Harkins-Schwarz M, Pachter LM, Fein JA. Adverse Childhood Experiences: Expanding the Concept of Adversity. Am J Prev Med. 2015 Sep;49(3):354-61. doi: 10.1016/j.amepre.2015.02.001.
citation: Pynoos RS, Steinberg AM, Layne CM, et al. Modeling constellations of trauma exposure in the National Child Traumatic Stress Network Core Data Set. Psychological Trauma: Theory, Research, Practice, and Policy. 2014;6(Suppl 1):S9-S17. doi:10.1037/a0037767
citation: Holt DD, Green L, Myerson J. Is discounting impulsive?. Evidence from temporal and probability discounting in gambling and non-gambling college students. Behav Processes. 2003 Oct 31;64(3):355-367. doi: 10.1016/s0376-6357(03)00141-4.
citation: Lopez-Nuñez C, Weidberg S, Martinez-Loredo V, Valverde IP-, Secades-Villa R, Fernández-Hermida J-R. Delay discounting and alcohol abuse among early adolescents. Drug and Alcohol Dependence. 2015;C(156):e133-e134. doi:10.1016/j.drugalcdep.2015.07.367
citation: Matusiewicz AK, Carter AE, Landes RD, Yi R. Statistical equivalence and test-retest reliability of delay and probability discounting using real and hypothetical rewards. Behav Processes. 2013 Nov;100:116-22. doi: 10.1016/j.beproc.2013.07.019. Epub 2013 Aug 14.
citation: Wechsler D. WISC-V: Administration and Scoring Manual. Published online 2014.
citation: Delis DC, Kramer JH, Kaplan E, Ober BA. CVLT-C: California Verbal Learning Test-Children's Version. Published online 1994.
citation: Delis DC, Kramer JH, Kaplan E, Holdnack J. Reliability and validity of the Delis-Kaplan Executive Function System: an update. J Int Neuropsychol Soc. 2004 Mar;10(2):301-3. doi: 10.1017/S1355617704102191. No abstract available.
citation: Bechara A. Iowa Gambling Task Professional Manual. Published online 2007.
citation: Beitz KM, Salthouse TA, Davis HP. Performance on the Iowa Gambling Task: From 5 to 89 years of age. J Exp Psychol Gen. 2014 Aug;143(4):1677-1689. doi: 10.1037/a0035823. Epub 2014 Feb 10.
citation: Smith DG, Xiao L, Bechara A. Decision making in children and adolescents: impaired Iowa Gambling Task performance in early adolescence. Dev Psychol. 2012 Jul;48(4):1180-7. doi: 10.1037/a0026342. Epub 2011 Nov 14.
citation: Soreni N, Crosbie J, Ickowicz A, Schachar R. Stop signal and Conners' continuous performance tasks: test--retest reliability of two inhibition measures in ADHD children. J Atten Disord. 2009 Sep;13(2):137-43. doi: 10.1177/1087054708326110. Epub 2009 May 8.
citation: Dennis M, Titus JC, Diamond G, Donaldson J, Godley SH, Tims FM, Webb C, Kaminer Y, Babor T, Roebuck MC, Godley MD, Hamilton N, Liddle H, Scott CK; C. Y. T. Steering Committee. The Cannabis Youth Treatment (CYT) experiment: rationale, study design and analysis plans. Addiction. 2002 Dec;97 Suppl 1:16-34. doi: 10.1046/j.1360-0443.97.s01.2.x.
citation: Tims FM, Dennis ML, Hamilton N, J Buchan B, Diamond G, Funk R, Brantley LB. Characteristics and problems of 600 adolescent cannabis abusers in outpatient treatment. Addiction. 2002 Dec;97 Suppl 1:46-57. doi: 10.1046/j.1360-0443.97.s01.7.x.
citation: Dennis ML, Dawud-Noursi S, Muck RD, McDermeit M. The need for developing and evaluating adolescent treatment models. In: Adolescent Substance Abuse Treatment in the United States: Exemplary Models from a National Evaluation Study. Haworth Press; 2003:3-34.
citation: Brown SA, Christiansen BA, Goldman MS. The Alcohol Expectancy Questionnaire: an instrument for the assessment of adolescent and adult alcohol expectancies. J Stud Alcohol. 1987 Sep;48(5):483-91. doi: 10.15288/jsa.1987.48.483.
citation: Schafer J, Brown SA. Marijuana and cocaine effect expectancies and drug use patterns. J Consult Clin Psychol. 1991 Aug;59(4):558-65. doi: 10.1037//0022-006x.59.4.558.
citation: Aarons GA, Brown SA, Stice E, Coe MT. Psychometric evaluation of the marijuana and stimulant effect expectancy questionnaires for adolescents. Addict Behav. 2001 Mar-Apr;26(2):219-36. doi: 10.1016/s0306-4603(00)00103-9.
citation: Center for Disease Control and Prevention. Youth risk behavior survey data. Retrieved June. 2015;1:2019.
citation: Bukstein OG. Disruptive behavior disorders and substance use disorders in adolescents. J Psychoactive Drugs. 2000 Jan-Mar;32(1):67-79. doi: 10.1080/02791072.2000.10400213.
citation: Aklin WM, Lejuez CW, Zvolensky MJ, Kahler CW, Gwadz M. Evaluation of behavioral measures of risk taking propensity with inner city adolescents. Behav Res Ther. 2005 Feb;43(2):215-28. doi: 10.1016/j.brat.2003.12.007.
citation: Lejuez CW, Aklin W, Daughters S, Zvolensky M, Kahler C, Gwadz M. Reliability and validity of the youth version of the Balloon Analogue Risk Task (BART-Y) in the assessment of risk-taking behavior among inner-city adolescents. J Clin Child Adolesc Psychol. 2007 Mar;36(1):106-11. doi: 10.1080/15374410709336573.
citation: Hamilton KR, Felton JW, Risco CM, Lejuez CW, MacPherson L. Brief report: The interaction of impulsivity with risk-taking is associated with early alcohol use initiation. J Adolesc. 2014 Dec;37(8):1253-6. doi: 10.1016/j.adolescence.2014.08.013. Epub 2014 Sep 29.
citation: Aarons GA. Mental health provider attitudes toward adoption of evidence-based practice: the Evidence-Based Practice Attitude Scale (EBPAS). Ment Health Serv Res. 2004 Jun;6(2):61-74. doi: 10.1023/b:mhsr.0000024351.12294.65.
citation: Aarons GA, Glisson C, Hoagwood K, Kelleher K, Landsverk J, Cafri G. Psychometric properties and U.S. National norms of the Evidence-Based Practice Attitude Scale (EBPAS). Psychol Assess. 2010 Jun;22(2):356-65. doi: 10.1037/a0019188.
citation: Larsen DL, Attkisson CC, Hargreaves WA, Nguyen TD. Assessment of client/patient satisfaction: development of a general scale. Eval Program Plann. 1979;2(3):197-207. doi: 10.1016/0149-7189(79)90094-6. No abstract available.
citation: Hosek SG, Lemos D, Harper GW, Telander K. Evaluating the acceptability and feasibility of Project ACCEPT: an intervention for youth newly diagnosed with HIV. AIDS Educ Prev. 2011 Apr;23(2):128-44. doi: 10.1521/aeap.2011.23.2.128.
citation: Olson EA, Hooper CJ, Collins P, Luciana M. Adolescents' performance on delay and probability discounting tasks: contributions of age, intelligence, executive functioning, and self-reported externalizing behavior. Pers Individ Dif. 2007 Nov;43(7):1886-1897. doi: 10.1016/j.paid.2007.06.016.
citation: Reznick JS, Morrow JD, Goldman BD, Snyder J. The onset of working memory in infants. Infancy. 2004;6(1):145-154.
citation: Luciana M, Conklin HM, Hooper CJ, Yarger RS. The development of nonverbal working memory and executive control processes in adolescents. Child Dev. 2005 May-Jun;76(3):697-712. doi: 10.1111/j.1467-8624.2005.00872.x.
citation: Simmonds DJ, Hallquist MN, Luna B. Protracted development of executive and mnemonic brain systems underlying working memory in adolescence: A longitudinal fMRI study. Neuroimage. 2017 Aug 15;157:695-704. doi: 10.1016/j.neuroimage.2017.01.016. Epub 2017 Apr 27.
citation: Fuhrmann D, Knoll LJ, Blakemore SJ. Adolescence as a Sensitive Period of Brain Development. Trends Cogn Sci. 2015 Oct;19(10):558-566. doi: 10.1016/j.tics.2015.07.008.
citation: Laube C, van den Bos W, Fandakova Y. The relationship between pubertal hormones and brain plasticity: Implications for cognitive training in adolescence. Dev Cogn Neurosci. 2020 Apr;42:100753. doi: 10.1016/j.dcn.2020.100753. Epub 2020 Jan 22.
citation: Kanwal J, Jung Y, Zhang M. Brain plasticity during adolescence: effects of stress, sleep, sex and sounds on decision making. Anat Physiol. 2016;6:e135.
citation: Bickel WK, Pitcock JA, Yi R, Angtuaco EJ. Congruence of BOLD response across intertemporal choice conditions: fictive and real money gains and losses. J Neurosci. 2009 Jul 8;29(27):8839-46. doi: 10.1523/JNEUROSCI.5319-08.2009.
citation: Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, Griffey R, Hensley M. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2011 Mar;38(2):65-76. doi: 10.1007/s10488-010-0319-7.
citation: Botvin GJ, Griffin KW, Diaz T, Scheier LM, Williams C, Epstein JA. Preventing illicit drug use in adolescents: long-term follow-up data from a randomized control trial of a school population. Addict Behav. 2000 Sep-Oct;25(5):769-74. doi: 10.1016/s0306-4603(99)00050-7.
citation: Griffin KW, Botvin GJ. Evidence-based interventions for preventing substance use disorders in adolescents. Child Adolesc Psychiatr Clin N Am. 2010 Jul;19(3):505-26. doi: 10.1016/j.chc.2010.03.005.
citation: Griffin KW, Botvin GJ, Nichols TR, Doyle MM. Effectiveness of a universal drug abuse prevention approach for youth at high risk for substance use initiation. Prev Med. 2003 Jan;36(1):1-7. doi: 10.1006/pmed.2002.1133.
citation: Pearl J. Interpretation and identification of causal mediation. Psychol Methods. 2014 Dec;19(4):459-81. doi: 10.1037/a0036434. Epub 2014 Jun 2.
citation: Valente MJ, Pelham WE, Smyth H, MacKinnon DP. Confounding in statistical mediation analysis: What it is and how to address it. J Couns Psychol. 2017 Nov;64(6):659-671. doi: 10.1037/cou0000242.
citation: VanderWeele T. Explanation in Causal Inference: Methods for Mediation and Interaction. Oxford University Press; 2015.
citation: VanderWeele TJ. Marginal structural models for the estimation of direct and indirect effects. Epidemiology. 2009 Jan;20(1):18-26. doi: 10.1097/EDE.0b013e31818f69ce.
citation: MacKinnon DP, Lockwood CM, Hoffman JM, West SG, Sheets V. A comparison of methods to test mediation and other intervening variable effects. Psychol Methods. 2002 Mar;7(1):83-104. doi: 10.1037/1082-989x.7.1.83.