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Micro-level Factors Associated with Youth Drug Use Among an Urban at-Risk Youth Sample

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Journal of Racial and Ethnic Health Disparities Aims and scope Submit manuscript

Abstract

Background

Youth drug use has reached global epidemic proportions with unequal distribution among communities with low income, immigrants, or ethnic status.

Purpose

This study seeks to understand the association between micro-level factors and youth drug use behavior among 2693 low-income, ethnic, and immigrant youths in Pomona, CA, USA. The study uneath’s unique evidence and intervention elements necessary to resolve youth drug use in Pomona.

Methods

We used social cognitive theory as a conceptual framework, and performed correlation and multiple linear regression analysis in a cross-sectional design.

Results and Discussion

The results reveal that attitudes, perceptions, and behavior related to friends, participants, family, and adults in the participant’s life and ease of access to drugs are associated with youth drug use. Variables related to friends and participants show a relatively stronger association with youth drug use in comparison to variables related to parents and adults in participants’ lives. Equally, drug and non-drug antisocial behavior of friends and participants show a stronger association with youth drug use relative to prosocial behavior. Also, when a diverse set of predictor variables are combined together, their association to the outcome variable is stronger than that of a single variable.

Recommendations

Future interventions in Pomona should prioritize strategies which target participants and friends over activities targeting parents and adults. Interventions targeting antisocial behavior should be prioritized over prosocial behavior. Program implementers should also develop unique evidence and tools which will help parents influence the drug use behavior of youths in Pomona and similar communities.

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Data Availability

The data used is not publicly available. It could be shared with appropriate requests and specified conditions.

Code Availability

The codes would also be available after appropriate requests. The codes are publicly available.

References

  1. Nawi AM, Ismail R, Ibrahim F, Hassan MR, Manaf RRA, Amit N, Ibrahim N, Sahfurdin NS. Risk and protective factors of drug abuse among adolescents: a systematic review. BioMed Central Public Health. 2021;21:1–15.

    Article  Google Scholar 

  2. Marchand K, Liu G, Mallia E, Ow N, Glowacki K, Hastings K, Mathias S, Suterland JM, Barbic S. Impact of the COVID-19 pandemic on alcohol or drug use symptoms and service need among youth: a cross-sectional sample from British Columbia, Canada. Subst Abuse Treat Prev Policy. 2022;17(1):1–12.

    Article  Google Scholar 

  3. United Nations Office on Drugs and Crime. 2022 World Drug Report. United Nations: Office on Drugs and Crime. 2022. Retrieved from https://www.unodc.org/unodc/data-and-analysis/world-drug-report-2022.html.

  4. World Drug Report. Executive Summary Conclusions and Policy Implications. https://www.unodc.org/wdr2018/prelaunch/WDR18_Booklet_1_EXSUM.pdf.

  5. Winters KC, Lee CS. Likelihood of developing an alcohol and cannabis use disorder during youth: association with recent use and age. Drug Alcohol Depend. 2008;92(1–3):239–247. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2219953/.

  6. Centers for Disease Control and Prevention (CDC). Youth risk behavior surveillance, United States. MMWR Suppl. 2020;69(1):1–83.

  7. Centers for Disease Control and Prevention. High-risk substance use among youth. https://www.CentersforDiseaseControlandPrevention/CDC.gov/healthyyouth/substance-use/index.htm. Published 2023.

  8. Smith Battle L, Loman DG, Yoo JH, Cibulka N, Rariden C. Evidence for revising the adverse childhood experiences screening tool: a scoping review. J Child Adolesc Trauma. 2022;15(1):89–103.

    Article  PubMed  Google Scholar 

  9. Green KM, Musci RJ, Johnson RM, Matson PA, Reboussin BA, Ialongo NS. Outcomes associated with adolescent marijuana and alcohol use among urban young adults: a prospective study. Addict Behav. 2016;53:155–60.

    Article  PubMed  Google Scholar 

  10. Lardier DT, Bergeson C, Bermea AM, Herr KG, Forenza B, Garcia RP, Reid RJ. Community coalitions as action, and the sharing of resources. J Community Psychol. 2019;47(1):21–33.

    Article  PubMed  Google Scholar 

  11. Tataw DB, Rosa B. Municipal health policy development, planning and implementation: addressing youth risk factors through participatory governance. J Health Hum Serv Adm. 2011;33(4):491–533.

    PubMed  Google Scholar 

  12. Tataw DB. Assessing youth substance use rates in a municipal youth and family master plan. Longitudinal and cross-sectional trends in Pomona, Los Angeles, and United States National Samples. Manuscript under review. 2023.

  13. US Census Bureau. Census State and County Quick Facts, 2002. https://www.census.gov/quickfacts/fact/table/US/PST045221. Published 2000. Accessed 31 May 2020.

  14. US Census Bureau. American Community Survey. 1-year Estimates for 2011 and 2021. https://www.census.gov/acs/www/data/data-tables-and-tools/. Accessed 8 Jan 2023.

  15. Pomona Unified School District (PUSD). 2010 The PRIDE Risk Factor Survey Results.

  16. Los Angeles County, Department of Public Health. Data by SPA. SPA 3, 2005. Los Angeles Department of Public Health;2010.

  17. Los Angeles County, Department of Public Health.City and Community Health Profiles. Los Angeles County Department of Public Health; 2018.

  18. Neuropharmacology of New Psychoactive Substances (NPS): focus on the rewarding and reinforcing properties of Cannabimimetic and Amphetamine-Like Stimulants. Front Neurosci. 2016;10:1–21. https://www.frontiersin.org/articles/10.3389/fnins.2016.00153/full. Accessed 1 Oct 2023

  19. The Organization of American States. Emerging drugs in the Americans: new psychoactive substances, including synthetic opioids. BP2 ENG.pdf (oas.org)

  20. National Center for Drug Abuse Statistics. Drug use among youth: facts and statistics. https://drugabusestatistics.org/teen-drug-use/. Published 2023. Accessed 31 Jul 2023.

  21. Wu S, Yan S, Marsiglia FF, Perron B. Patterns and social determinants of substance use among Arizona Youth: a latent class analysis approach. Child Youth Serv Rev. 2020;110:104769.

    Article  Google Scholar 

  22. Tataw DB, Kim Suk-hee. Antisocial behavior and attitudes towards antisocial behavior after a five-year municipal youth and family master plan in Pomona, California, USA. Soc Work Public Health. 2022. https://doi.org/10.1080/19371918.2022.2072037

  23. Tataw DB, Suk-hee K, Olberding JC. Community youth risk and protective factors, five years after a municipal youth and family master plan in Pomona, California, USA. Child Youth Serv. 2023;1–34. https://doi.org/10.1080/0145935X.2023.2243439.

  24. Tataw DB. School outcomes among an urban youth sample, five years after a Municipal Youth and Family Master Plan in Pomona, California. USA: School Commun J In Press. 2023.

    Google Scholar 

  25. Kim B, Gloppen K, Rhew I, Oesterle S, Hawkins J. Effects of the communities that care prevention system on youth reports of protective factors. Prev Sci. 2015;16(5):652–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Substance Abuse and Mental Health Services Administration. Rise in prescription drug misuse and abuse impacting teens. 2023. https://www.SubstanceAbuseandMentalHealthServicesAdministration/SUBSTANCEABUSEANDMENTALHEALTHSERVICESADMINISTRATION/SAMHSA.gov/homelessness-programs-resources/hpr-resources/rise-prescription-drug-misuse-abuse-impacting-teens. Accessed 31 Jul 2023.

  27. McMillan B, Florin P, Stevenson J, Kerman B, Mitchell R. Empowerment praxis in community coalitions. Am J Community Psychol. 1995;23:699–728.

    Article  CAS  PubMed  Google Scholar 

  28. Morrison SU, Adler-Baeder F, Bub KL, Duke A. Contextualizing relationship education and adolescent attitude toward sexual behavior: considering class climate. Child Youth Care Forum. 2018;47(1):133–50.

    Article  Google Scholar 

  29. Alegria M, Shrout PE, Canino G, Alvarez K, Wang Y, Bird H, Duarte C. The effect of minority status and social context on the development of depression and anxiety: a longitudinal study of Puerto Rican descent youth. World Psychiatry. 2019;18(3):298–307. https://doi.org/10.1002/wps.20671.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Murray J, Shenderovich Y, Gardner F, Mikton C, Derzon HH, Liu J, Eisner M. Risk factors for antisocial behavior in low-and middle-income countries: a systematic review of longitudinal studies. The University of Chicago; 2018:255–363.

  31. Schonberg MA, Shaw DS. Do the predictors of child conduct problems vary by high-and low-levels of socioeconomic and neighborhood risk? Clin Child Fam Psychol Rev. 2007;10(2):101–36.

    Article  PubMed  Google Scholar 

  32. World Health Organization. Environment and health risks: a review of the influence and effects of social inequalities. 2010. https://www.euro.who.int/__data/assets/pdf_file/0003/78069/E93670.pdf. Accessed 31 May 2020.

  33. Lee LH, Kim M. Effect of work on antisocial behavior among formerly incarcerated young adults: a panel analysis. Soc Work Res. 2022;46(2):115–26.

    Article  Google Scholar 

  34. Evans S, Simons L, Simons R. Factors that influence trajectories of delinquency throughout adolescence. J Youth Adolesc. 2016;45(1):156–71. https://doi.org/10.1007/s10964-014-0197-5.

    Article  PubMed  Google Scholar 

  35. French DC, Purwono U, Shen M. Religiosity and positive religious coping as predictors of Indonesian Muslim adolescents’ externalizing behavior and loneliness. Psychol Relig Spiritual. 2022;14(2):189–99. https://doi.org/10.1037/rel0000300.

    Article  Google Scholar 

  36. Wade R, Cronholm PF, Fein JA, Forke CM, Davis MB, Harkins-Schwarz M, Pachter LM, Bair-Merritt MH. Household and community-level adverse childhood experiences and adult health outcomes in a diverse urban population. Child Abuse Negl. 2016;52:135–45.

    Article  PubMed  Google Scholar 

  37. Hall A, Perez A, West X, Brown M, Kim E, Salih Z, Aronoff S. The association of adverse childhood experiences and resilience with health outcomes in adolescents: an observational study. Glob Pediatr Health. 2021;8. https://doi.org/10.1177/2333794X20982433

  38. Rusby JC, Light JM, Crowley R, Westling E. Influence of parent-youth relationship, parental monitoring, and parent substance use on adolescent substance use onset. J Fam Psychol. 2018;32(3):310–20.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Hartney E, Susman D. What is peer pressure? Types, examples, and how to deal with peer pressure. Addiction. Published October 6, 2022. https://www.verywellmind.com/what-is-peer-pressure-22246.

  40. Choi TK, Worley MJ, Trim RS, Howard D, Brown SA, Hopfer CJ, Hewitt JK, Wall TL. Effect of adolescent substance use and antisocial behavior on the development of early adulthood depression. Psychiatry Res. 2016;238:143–9. https://doi.org/10.1016/j.psychres.2016.02.011.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Broman CL. The availability of substances in adolescence: influences in emerging adulthood. J Child Adolesc Subst Abuse. 2016;25(5):487–95.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Lipari R, Jean-Francois B. Trends in perception of risk and availability of substance use among full-time college students. Natl Center Drug Abuse Stat. 2016. https://www.SubstanceAbuseandMentalHealthServicesAdministration/SUBSTANCEABUSEANDMENTALHEALTHSERVICESADMINISTRATION/SAMHSA.gov/data/sites/default/files/report_2418/ShortReport-2418.html.

  43. Bandura A, National Institute of Mental Health. Social foundations of thought and action: a social cognitive theory. Prentice-Hall, Inc; 1986.

  44. Bandura A. Social cognitive theory for personal and social change by enabling media. In: Singhal A, Cody MJ, Rogers EM, Sabido M, editors. Entertainment-education and social change: history, research, and practice. Lawrence Erlbaum Associates Publishers; 2004. p. 75–96.

    Google Scholar 

  45. Marcantonio TL, Willis M, Rhoads KE, Hunt ME, Canan S, Jozkowski KN. Assessing models of concurrent substance use and sexual consent cues in mainstream films. J Am Coll Health. 2022;70(3):645–64.

    Article  PubMed  Google Scholar 

  46. Carlson G, Crane TE, Taylor-Piliae RE. Selecting a theoretical framework to explore the social and cognitive uncertainty that hepatitis C treatment represents for people who inject drugs. Appl Nurs Res. 2020;56. https://doi.org/10.1016/j.apnr.2020.151339

  47. Fogel J, Shlivko A. Reality television programs are associated with illegal drug use and prescription drug misuse among college students. Subst Use Misuse. 2016;51(1):62–72. https://doi.org/10.3109/10826084.2015.1082593.

    Article  PubMed  Google Scholar 

  48. Fathian-Dastgerdi Z, Eslami A-A, Ghofranipour F, Mostafavi F. Effects of a community-based substance use prevention program in Iranian adolescents (SUPPIA) using social cognitive theory. J Subst Use. 2022. https://doi.org/10.1080/14659891.2022.2157772.

    Article  Google Scholar 

  49. National Cancer Institute. Theory at a glance: application to health promotion and health behavior (2nd ed.). US Department of Health and Human Services; 2005. https://cancercontrol.cancer.gov/sites/default/files/2020-06/theory.pdf.

  50. International Survey Associates. The PRIDE Survey Reports: 2009–2010, National Summary. https://www.thepridesurveys.com. Published 2010.

  51. Metze L. The PRIDE questionnaire for grades 6–12. Validity And Reliability Study. http://www.thepridesurveys.com/supportfiles/tr99612.pdf. Published 2000.

  52. Reiland Consultants. Validity and reliability summary for the PRIDE questionnaire for grades 6–12. https://www.thepridesurveys.com/wp-content/uploads/2018/07/Validity-and-reliability-Study-2018.pdf. Published 2018.

  53. Craig JR, Emshoff J. The PRIDE questionnaire for grades 6–12. Developmental Study. http://www.thepridesurveys.com/supportfiles/tr99612.pdf. Published 1987.

  54. Adams RD. The PRIDE questionnaire for grades 6–12. 2nd developmental study. http://www.thepridesurveys.com/supportfiles/tr99612.pdf. Published 1994.

  55. Mukaka MM. Statistics corner (2012). A guide to appropriate use of correlation coefficient in medical research. Malawi Med J. 2012;24(3):69–71.

  56. Rights JD, Cole DA. Effect size measures for multilevel models in clinical child and adolescent research: new R-squared methods and recommendations. J Clin Child Adolesc Psychol. 2018;47(6):863–73.

    Article  PubMed  Google Scholar 

  57. Turney S. Coefficient of determination (R2) | Calculation & Interpretation. Scribbr. 2022. Retrieved from https://www.scribbr.com/statistics/coefficient-of-determination/.

  58. Bhandari HN, Rimal B, Pokhrel NR, Rimal R, Dahal KR, Khatri RKC. Predicting stock market index using LSTM. Science Direct. 2022:1–15.

  59. Miliano C, Margiani G, Fattore L, De Luca MA. Sales and advertising channels of new psychoactive substances (NPS): internet, social networks, and smartphone apps. Brain Sci. 2018;8(7):123.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Meyer GJ, Finn SE, Eyde LD, Kay GG, Moreland KL, Dies RR, Eisman EJ, Kubiszyn TW, Reed GM. Psychological testing and psychological assessment: a review of evidence and issues. Am Psychol. 2001;56(2):128–65. https://doi.org/10.1037/0003-066X.56.2.128.

    Article  CAS  PubMed  Google Scholar 

  61. Owens MM, Potter A, Hyatt CS, Albaugh M, Thompson WK, Jernigan T, Yuan D, Hahn S, Allgaier N, Garavan H. Recalibrating expectations about effect size: a multi-method survey of effect sizes in the ABCD study. PLoS One. 2021;16(9):e0257535.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Hayes T, Sharma M, de Los Angeles Hernandez Morales V, Brown L, Wu Di, Hernandez Morales V de L A, Di W. Using the multi-theory model (MTM) of health behavior change to explain yoga practice. Altern Ther Health Med. 2022;28(1):12–17.

  63. Jiang YH, Smith PL. Understanding and interpreting regression parameter estimates in given contexts: a Monte Carlo study of characteristics of regression and structural coefficients, effect size R squared and significance level of predictors.

  64. Loke AY, Mak Y. Family process and peer influences on substance use by adolescents. Int J Environ Res Public Health. 2013;10(9):3868–85.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Fairchild F, Hawes DJ, Frick PJ, Copeland WE, Odgers CL, Franke B, Freitag CM, De Brito SA. Conduct disorder. Nat Rev Dis Primers. 2019;5(43):1–25.

    Google Scholar 

  66. Marsiglia F, Wu S, Ayers S, Weide A. Randomized effectiveness trial of a parent and youth combined intervention on the substance use norms of Latino middle school students. J Subst Abuse Treat. 2019;97:75–83.

    Article  PubMed  Google Scholar 

  67. Singh PSJ, Azman A. Dealing with juvenile delinquency: integrated social work approach. Asian Soc Work J. 2020;5(2):32–43.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. School of Allied Health, College of Health and Human Services, Northern Kentucky University, Highland Heights, KY, USA

    David Tataw

  2. Department of Mathematics and Statistics, College of Arts and Sciences, Northern Kentucky University, Highland Heights, KY, USA

    Joseph Nolan

  3. School of Social Work, College of Health and Human Services, Northern Kentucky University, Highland Heights, KY, USA

    Suk-hee Kim

Authors
  1. David Tataw
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  2. Joseph Nolan
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  3. Suk-hee Kim
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Contributions

All authors contributed to the data analysis, literature review, and revision of different versions of the paper. The lead author was responsible for the conceptualization of the paper and participated in the data collection in partnership with industry consultants and members of the Pomona Youth and Family Master Plan.

Corresponding author

Correspondence to David Tataw.

Ethics declarations

Ethics Approval

This study was approved by the Institutional Review Board of Jackson State University, Mississippi in 2014 as an exempt study #01–31-2014 and the Institutional Review Board of Charles R. Drew University, Los Angeles in 2007 as an expedited study #07–02-003–01.

Consent to Participate

The parents of participants gave their consents and the youth voluntarily participated.

Consent for Publication

Both the parents and School District and the Pomona Youth and Family Master Plan Advisory Board consented to the publication of the findings.

Conflict of Interest

The authors declare no competing interests.

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Tataw, D., Nolan, J. & Kim, Sh. Micro-level Factors Associated with Youth Drug Use Among an Urban at-Risk Youth Sample. J. Racial and Ethnic Health Disparities (2023). https://doi.org/10.1007/s40615-023-01839-4

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  • DOI: https://doi.org/10.1007/s40615-023-01839-4

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