Top

Published in:

01-07-2021

Acceptance of Drug Use Mediates Future Hard Drug Use Among At-Risk Adolescent Marijuana, Tobacco, and Alcohol Users

Authors: Christopher Cappelli, Susan L. Ames, Bin Xie, James Russell Pike, Alan W. Stacy

Published in: Prevention Science | Issue 5/2021

Abstract

Alternative high school (AHS) students typically report higher levels of alcohol and other drug use compared to students attending traditional high schools. Greater use of such drugs as heroin, methamphetamines, and cocaine in this at-risk population may be driven, in part, by a greater latitude of acceptance toward substance use in general, which may accelerate the transition from gateway drugs to hard drugs. Seven hundred seventy-seven adolescents (mean age 16.6; 56% female) were recruited from alternative high schools throughout Southern California. To understand the factors that may lead AHS students to use hard drugs, a model was tested in order to determine if AHS students’ latitude of acceptance toward substance use was a mediator between the relationship of past use of gateway drugs and future use of hard drugs. Latitude of acceptance was found to be a statistically significant mediator of future hard drug use (b = 0.03, 95% confidence intervals = 0.01 to 0.05) among gateway drug users. An individual’s latitude of acceptance to various drug use behaviors may be consistent with societal norms. However, after exposure to, or use of, gateway drugs, attitudes that are more permissive toward hard drug use may be encountered, the acceptance of hard drugs may expand, and the use of hard drugs may escalate. Interventions designed to reduce the use of hard drugs among at-risk youth may be more persuasive by crafting messages that are within the latitude of acceptance of the target population and prevent the acceptance of hard drug use.

Four hundred forty-seven participants completed the Time 2 assessment and 449 participants completed the Time 3 assessment.

Results are substantively similar when analysis with imputed dataset excludes students who reported hard drug use at baseline (BootCI, 0.009–0.015).

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control (pp. 11–39). Berlin: Springer.CrossRef

Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84, 888–918. https://doi.org/10.1037/0033-2909.84.5.888.CrossRef

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior: Prentice-Hall.

Ajzen, I., & Fishbein, M. (2000). Attitudes and the attitude-behavior relation: Reasoned and automatic processes. European Review of Social Psychology, 11, 1–33. https://doi.org/10.1080/14792779943000116.CrossRef

Allen, J. P., Chango, J., Szwedo, D., Schad, M., & Marston, E. (2012). Predictors of susceptibility to peer influence regarding substance use in adolescence. Child Development, 83, 337–350. https://doi.org/10.1111/j.1467-8624.2011.01682.x.CrossRefPubMed

Allison, P. D. (2001). Missing data. Thousand Oaks: Sage University.

Ames, S. L., Franken, I. H., & Coronges, K. (2006). Implicit cognition and drugs of abuse. In R. W. Wiers & A. W. Stacy (Eds.), Handbook of implicit cognition and addiction (pp. 363–378). Thousand Oaks: SAGE Publications.CrossRef

Ames, S. L., Grenard, J. L., Thush, C., Sussman, S., Wiers, R. W., & Stacy, A. W. (2007). Comparison of indirect assessments of association as predictors of marijuana use among at-risk adolescents. Experimental and Clinical Psychopharmacology, 15, 204–218. https://doi.org/10.1037/1064-1297.15.2.218.CrossRefPubMedPubMedCentral

Ames, S.L., Grenard, J.L., Stacy, A.W., Xiao, L., He, Q., Wong, S.W., … Bechara, A. (2013). Functional imaging of implicit marijuana associations during performance on an implicit association test (IAT). Behavioural Brain Research, 256, 494–502. doi:https://doi.org/10.1016/j.bbr.2013.09.013.

Ames, S. L., Xie, B., Shono, Y., & Stacy, A. W. (2017). Adolescents at risk for drug abuse: A 3-year dual-process analysis. Addiction, 112, 852–863. https://doi.org/10.1111/add.13742.CrossRefPubMedPubMedCentral

Atkins, A. L., Deaux, K. K., & Bieri, J. (1967). Latitude of acceptance and attitude change: Empirical evidence for a reformulation. Journal of Personality and Social Psychology, 6, 47–54. https://doi.org/10.1037/h0024527.CrossRefPubMed

Barrett, L. F., Tugade, M. M., & Engle, R. W. (2004). Individual differences in working memory capacity and dual-process theories of the mind. Psychological Bulletin, 130, 553–573. https://doi.org/10.1037/0033-2909.130.4.553.CrossRefPubMedPubMedCentral

Barry, A. E., King, J., Sears, C., Harville, C., Bondoc, I., & Joseph, K. (2016). Prioritizing alcohol prevention: Establishing alcohol as the gateway drug and linking age of first drink with illicit drug use. The Journal of School Health, 86, 31–38. https://doi.org/10.1111/josh.12351.CrossRefPubMed

Bava, S., & Tapert, S. F. (2010). Adolescent brain development and the risk for alcohol and other drug problems. Neuropsychology Review, 20, 398–413. https://doi.org/10.1007/s11065-010-9146-6.CrossRefPubMedPubMedCentral

Beleva, Y., Pike, J. R., Miller, S., Xie, B., Ames, S. L., & Stacy, A. W. (2019). Share of advertising voice at the point-of-sale and its influence on at-risk students’ use of alternative tobacco products. Nicotine & Tobacco Research, 21, 903–910. https://doi.org/10.1093/ntr/nty152.CrossRef

California Department of Education (2020). Alternative Schools & Programs of Choice. Sacramento, CA. Retrieved from: www.cde.ca.gov.

Chen, C. Y., Storr, C. L., & Anthony, J. C. (2009). Early-onset drug use and risk for drug dependence problems. Addictive Behaviors, 34, 319–322. https://doi.org/10.1016/j.addbeh.2008.10.021.CrossRefPubMed

de Velasco, J.R., & Gonzales, D. (2017). Accountability for alternative schools in California. Retrieved from Sacramento, CA:

de Velasco, J. R., Austin, G., Dixon, D., Johnson, J., McLaughlin, M., & Perez, L. (2008). Alternative education options: A descriptive study of California continuation high schools. San Diego: California Alternative Education Research Project, San Diego University.

Deas, D., Riggs, P., Langenbucher, J., Goldman, M., & Brown, S. (2000). Adolescents are not adults: Developmental considerations in alcohol users. Alcoholism: Clinical and Experimental Research, 24, 232–237. https://doi.org/10.1111/j.1530-0277.2000.tb04596.x.CrossRef

Deaux, K. K., & Bieri, J. (1967). Latitude of acceptance in judgments of masculinity-femininity1. Journal of Personality, 35, 109–117. https://doi.org/10.1111/j.1467-6494.1967.tb01418.x.CrossRefPubMed

Degenhardt, L., Dierker, L., Chiu, W.T., Medina-Mora, M.E., Neumark, Y., Sampson, N., … Kessler, R.C. (2010). Evaluating the drug use “gateway” theory using cross-national data: Consistency and associations of the order of initiation of drug use among participants in the WHO World Mental Health Surveys. Drug and Alcohol Dependence, 108(1–2), 84–97. doi:https://doi.org/10.1016/j.drugalcdep.2009.12.001.

Dillard, J. P., Shen, L., & Vail, R. G. (2007). Does perceived message effectiveness cause persuasion or vice versa? 17 consistent answers. Human Communication Research, 33, 467–488. https://doi.org/10.1111/j.1468-2958.2007.00308.x.CrossRef

Eisenberg, M. E., Toumbourou, J. W., Catalano, R. F., & Hemphill, S. A. (2014). Social norms in the development of adolescent substance use: A longitudinal analysis of the International Youth Development Study. Journal of Youth and Adolescence, 43, 1486–1497. https://doi.org/10.1007/s10964-014-0111-1.CrossRefPubMedPubMedCentral

Ennett, S. T., Foshee, V. A., Bauman, K. E., Hussong, A., Faris, R., Hipp, J. R., & Cai, L. (2010). A social contextual analysis of youth cigarette smoking development. Nicotine & Tobacco Research, 12, 950–962. https://doi.org/10.1093/ntr/ntq122.CrossRef

Fergusson, D. M., Boden, J. M., & Horwood, L. J. (2006). Cannabis use and other illicit drug use: Testing the cannabis gateway hypothesis. Addiction, 101, 556–569. https://doi.org/10.1111/j.1360-0443.2005.01322.x.CrossRefPubMed

Fishbein, M., & Ajzen, I. (1974). Attitudes towards objects as predictors of single and multiple behavioral criteria. Psychological Review, 81, 59–74. https://doi.org/10.1037/h0035872.CrossRef

Fritz, M. S., & Mackinnon, D. P. (2007). Required sample size to detect the mediated effect. Psychological Science, 18, 233–239. https://doi.org/10.1111/j.1467-9280.2007.01882.x.CrossRefPubMedPubMedCentral

Garnier, H. E., & Stein, J. A. (2002). An 18-year model of family and peer effects on adolescent drug use and delinquency. Journal of Youth and Adolescence, 31, 45–56. https://doi.org/10.1023/a:1014085016511.CrossRef

Gilreath, T. D., Chaix, B., King, G., Matthews, S., & Flisher, A. J. (2012). Multi-level influence of school norms on tobacco use in South Africa: An ecometric consideration of group differences. Cancer Causes & Control, 23, 27–36. https://doi.org/10.1007/s10552-012-9908-y.CrossRef

Graham, J. W., Flay, B. R., Johnson, C. A., Hansen, W. B., Grossman, L., & Sobel, J. L. (1984). Reliability of self-report measures of drug use in prevention research: Evaluation of the Project SMART questionnaire via the test-retest reliability matrix. Journal of Drug Education, 14, 175–193.CrossRef

Graham, J. W., Olchowski, A. E., & Gilreath, T. D. (2007). How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prevention Science, 8, 206–213. https://doi.org/10.1007/s11121-007-0070-9.CrossRefPubMed

Grant, B. F., & Dawson, D. A. (1997). Age at onset of alcohol use and its association with DSM-IV alcohol abuse and dependence: Results from the national longitudinal alcohol epidemiologic survey. Journal of Substance Abuse, 9, 103–110. https://doi.org/10.1016/s0899-3289(97)90009-2.CrossRefPubMed

Grenard, J. L., Ames, S. L., Wiers, R. W., Thush, C., Sussman, S., & Stacy, A. W. (2008). Working memory capacity moderates the predictive effects of drug-related associations on substance use. Psychology of Addictive Behaviors, 22, 426–432. https://doi.org/10.1037/0893-164X.22.3.426.CrossRefPubMedPubMedCentral

Grunbaum, J. A., Lowry, R., & Kann, L. (2001). Prevalence of health-related behaviors among alternative high school students as compared with students attending regular high schools. Journal of Adolescent Health, 29, 337–343. https://doi.org/10.1016/s1054-139x(01)00304-4.CrossRef

Hanson, K. L., Thayer, R. E., & Tapert, S. F. (2014). Adolescent marijuana users have elevated risk-taking on the balloon analog risk task. Journal of Psychopharmacology, 28, 1080–1087. https://doi.org/10.1177/0269881114550352.CrossRefPubMed

Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76, 408–420. https://doi.org/10.1080/03637750903310360.CrossRef

Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (second ed.). New York: Guilford Publications.

Hayes, A. F., & Scharkow, M. (2013). The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter? Psychological Science, 24, 1918–1927. https://doi.org/10.1177/0956797613480187.CrossRefPubMed

Hoffman, B. R., Sussman, S., Unger, J. B., & Valente, T. W. (2006). Peer influences on adolescent cigarette smoking: A theoretical review of the literature. Substance Use & Misuse, 41, 103–155. https://doi.org/10.1080/10826080500368892.CrossRef

Hovland, C. I., Harvey, O. J., & Sherif, M. (1957). Assimilation and contrast effects in reactions to communication and attitude change. The Journal of Abnormal and Social Psychology, 55, 244–252. https://doi.org/10.1037/h0048480.CrossRef

Janik, P., Kosticova, M., Pecenak, J. P., & Turcek, M. (2017). Categorization of psychoactive substances into “hard drugs” and “soft drugs”: A critical review of terminology used in current scientific literature. The American Journal of Drug and Alcohol Abuse, 43, 636–646. https://doi.org/10.1080/00952990.2017.1335736.CrossRefPubMed

Johnson, K., & Taliaferro, L. (2012a). Health behaviors and mental health of students attending alternative high schools: A review of the research literature. Journal for Specialists in Pediatric Nursing, 17, 79–97. https://doi.org/10.1111/j.1744-6155.2011.00311.x.CrossRefPubMed

Johnson, K. E., & Taliaferro, L. A. (2012b). Health behaviors and mental health of students attending alternative high schools: A review of the research literature. Journal for Specialists in Pediatric Nursing, 17, 79–97.CrossRef

Johnson, K. E., McMorris, B. J., & Kubik, M. Y. (2013). Comparison of health-risk behaviors among students attending alternative and traditional high schools in Minnesota. The Journal of School Nursing, 29, 343–352. https://doi.org/10.1177/1059840512469409.CrossRefPubMed

Johnston, L.D., O’Malley, P. M., Miech, R. A., Bachman, J. G., & Schulenberg, J. E. (2016). Monitoring the future national survey results on drug use, 1975–2015: Overview, key findings on adolescent drug use. Ann Arbor: Institute for Social Research, University of Michigan.

Johnston, L.D., Miech, R.A., O’Malley, P.M., Bachman, J.G., Schulenberg, J.E., & Patrick, M.E. (2019). Monitoring the future national survey results on drug use 1975–2018: Overview, key findings on adolescent drug use. Retrieved from Ann Arbor, Michigan.

Kandel, D. (1975). Stages in adolescent involvement in drug use. Science, 190, 912–914. https://doi.org/10.1126/science.1188374.CrossRefPubMed

Kandel, E. R., & Kandel, D. B. (2014). Shattuck lecture. A molecular basis for nicotine as a gateway drug. The New England Journal of Medicine, 371, 932–943. https://doi.org/10.1056/NEJMsa1405092.CrossRefPubMedPubMedCentral

Kann L, McManus T, Harris WA, et al. Youth Risk Behavior Surveillance — United States, 2015. MMWR Surveill Summ 2016;65(No. SS-6):1–174. https://doi.org/10.15585/mmwr.ss6506a1.

King, K. M., & Chassin, L. (2007). A prospective study of the effects of age of initiation of alcohol and drug use on young adult substance dependence. Journal of Studies on Alcohol and Drugs, 68, 256–265. https://doi.org/10.15288/jsad.2007.68.256.CrossRefPubMed

Kirby, T., & Barry, A. E. (2012). Alcohol as a gateway drug: A study of US 12th graders. The Journal of School Health, 82, 371–379. https://doi.org/10.1111/j.1746-1561.2012.00712.x.CrossRefPubMed

LAO. (2015). Next steps for improving state accountability for alternative schools. Retrieved from Sacramento, CA:

Mackinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39, 99. https://doi.org/10.1207/s15327906mbr3901_4.CrossRefPubMedPubMedCentral

McCuller, W. J., Sussman, S., Holiday, K., Craig, S., & Dent, C. W. (2002). Tracking procedures for locating high-risk youth. Evaluation & the Health Professions, 25, 345–362. https://doi.org/10.1177/0163278702025003006.CrossRef

McCusker, C. G. (2001). Cognitive biases and addiction: An evolution in theory and method. Addiction, 96, 47–56. https://doi.org/10.1080/09652140020016950.CrossRefPubMed

Miller, J. W., Naimi, T. S., Brewer, R. D., & Jones, S. E. (2007). Binge drinking and associated health risk behaviors among high school students. Pediatrics, 119, 76–85. https://doi.org/10.1542/peds.2006-1517.CrossRefPubMed

Murray, D. M., Varnell, S. P., & Blitstein, J. L. (2004). Design and analysis of group-randomized trials: A review of recent methodological developments. American Journal of Public Health, 94, 423–432. https://doi.org/10.2105/ajph.94.3.423.CrossRefPubMedPubMedCentral

Newcomb, M. D., & Bentler, P. M. (1988). The impact of family context, deviant attitudes, and emotional distress on adolescent drug use: Longitudinal latent-variable analyses of mothers and their children. Journal of Research in Personality, 22, 154–176. https://doi.org/10.1016/0092-6566(88)90012-8.CrossRef

Park, H. S., Levine, T. R., Kingsley Westerman, C. Y., Orfgen, T., & Foregger, S. (2007). The effects of argument quality and involvement type on attitude formation and attitude change: A test of dual-process and social judgment predictions. Human Communication Research, 33, 81–102. https://doi.org/10.1111/j.1468-2958.2007.00290.x.CrossRef

Pike, J. R., Shono, Y., Tan, N., Xie, B., & Stacy, A. W. (2019). Retail outlets prompt associative memories linked to the repeated use of nicotine and tobacco products among alternative high school students in California. Addictive Behaviors, 99, 106067. https://doi.org/10.1016/j.addbeh.2019.106067.CrossRefPubMedPubMedCentral

Reid, L. W., Elifson, K. W., & Sterk, C. E. (2007). Ecstasy and gateway drugs: Initiating the use of ecstasy and other drugs. Annals of Epidemiology, 17, 74–80. https://doi.org/10.1016/j.annepidem.2006.07.013.CrossRefPubMed

Rohrbach, L. A., Sussman, S., Dent, C. W., & Sun, P. (2005). Tobacco, alcohol, and other drug use among high-risk young people: A five-year longitudinal study from adolescence to emerging adulthood. Journal of Drug Issues, 35, 333–356. https://doi.org/10.1177/002204260503500206.CrossRef

Rooke, S. E., Hine, D. W., & Thorsteinsson, E. B. (2008). Implicit cognition and substance use: A meta-analysis. Addictive Behaviors, 33, 1314–1328. https://doi.org/10.1016/j.addbeh.2008.06.009.CrossRefPubMed

Saunders, J., & Saunders, E. (2001). Alternative school students’ perceptions of past [traditional] and current [alternative] school environments. The High School Journal, 85, 12–23.CrossRef

Schlomer, G. L., Bauman, S., & Card, N. A. (2010). Best practices for missing data management in counseling psychology. Journal of Counseling Psychology, 57, 1–10. https://doi.org/10.1037/a0018082.CrossRefPubMed

Sherif, M., & Hovland, C.I. (1961). Social judgment: Assimilation and contrast effects in communication and attitude change. Yale University Press. New Haven, CT.

Sherif, C.W., Sherif, M., & Nebergall, R.E. (1965). Attitude and attitude change: The social judgement-involvement process. Saunders Co.: Philadelphia & London.

Smith, S. W., Atkin, C. K., Martell, D., Allen, R., & Hembroff, L. (2006). A social judgment theory approach to conducting formative research in a social norms campaign. Communication Theory, 16, 141–152. https://doi.org/10.1111/j.1468-2885.2006.00009.x.CrossRef

Spijkerman, R., van den Eijnden, R. J., Vitale, S., & Engels, R. C. (2004). Explaining adolescents’ smoking and drinking behavior: The concept of smoker and drinker prototypes in relation to variables of the theory of planned behavior. Addictive Behaviors, 29, 1615–1622. https://doi.org/10.1016/j.addbeh.2004.02.030.CrossRefPubMed

Squeglia, L. M., Jacobus, J., & Tapert, S. F. (2009). The influence of substance use on adolescent brain development. Clinical EEG and Neuroscience, 40, 31–38. https://doi.org/10.1177/155005940904000110.CrossRefPubMedPubMedCentral

Stacy, A. W. (1997). Memory activation and expectancy as prospective predictors of alcohol and marijuana use. Journal of Abnormal Psychology, 106, 61–73.CrossRef

Stacy, A. W., & Wiers, R. W. (2010). Implicit cognition and addiction: A tool for explaining paradoxical behavior. Annual Review of Clinical Psychology, 6, 551–575. https://doi.org/10.1146/annurev.clinpsy.121208.131444.CrossRefPubMedPubMedCentral

Stacy, A. W., Flay, B. R., Sussman, S., Brown, S. K., Santi, S., & Best, J. A. (1990). Validity of alternative self-report indices of smoking among adolescents. Psychological Assessment, 2, 442–446. https://doi.org/10.1037/1040-3590.2.4.442.CrossRef

Sussman, S., & Ames, S. L. (2001). The social psychology of drug abuse. Buckingham, GB: Open University Press.

Sussman, S., Stacy, A.W., Dent, C.W., Simon, T.R., Galaif, E.R., Moss, M.A., … Johnson, C.A. (1995). Continuation high schools: Youth at risk for drug abuse. Journal of Drug Education, 25, 191–209. doi:https://doi.org/10.2190/HDQH-XD21-GJT0-9G8V.

Sussman, S., Dent, C. W., & Galaif, E. R. (1997). The correlates of substance abuse and dependence among adolescents at high risk for drug abuse. Journal of Substance Abuse, 9, 241–255. https://doi.org/10.1016/s0899-3289(97)90019-5.CrossRefPubMed

Sussman, S., Dent, C. W., & Stacy, A. W. (2002). Project towards no drug abuse: A review of the findings and future directions. American Journal of Health Behavior, 26, 354–365. https://doi.org/10.5993/ajhb.26.5.4.CrossRefPubMed

Sussman, S., Skara, S., & Ames, S. L. (2008). Substance abuse among adolescents. Substance Use & Misuse, 43, 1802–1828. https://doi.org/10.1080/10826080802297302.CrossRef

Sussman, S., Arpawong, T. E., Sun, P., Tsai, J., Rohrbach, L. A., & Spruijt-Metz, D. (2014). Prevalence and co-occurrence of addictive behaviors among former alternative high school youth. Journal of Behavioral Addictions, 3, 33–40. https://doi.org/10.1556/JBA.3.2014.005.CrossRefPubMedPubMedCentral

Volkow, N. D., Baler, R. D., Compton, W. M., & Weiss, S. R. (2014). Adverse health effects of marijuana use. The New England Journal of Medicine, 370, 2219–2227. https://doi.org/10.1056/NEJMra1402309.CrossRefPubMedPubMedCentral

Wiers, R. W., & Stacy, A. W. (2006). Implicit Cognition and Addiction: An Introduction. In R. W. Wiers & A. W. Stacy (Eds.), Handbook of implicit cognition and addiction (p. 1–8). Sage Publications, Inc. https://doi.org/10.4135/9781412976237.n1.

Zweig, J.M. (2003). Vulnerable youth: Identifying their need for alternative educational settings. The Urban Institute. Washington, D.C.

Title: Acceptance of Drug Use Mediates Future Hard Drug Use Among At-Risk Adolescent Marijuana, Tobacco, and Alcohol Users
Authors: Christopher Cappelli
Susan L. Ames
Bin Xie
James Russell Pike
Alan W. Stacy
Publication date: 01-07-2021
Publisher: Springer US
Published in: Prevention Science / Issue 5/2021
Print ISSN: 1389-4986
Electronic ISSN: 1573-6695
DOI: https://doi.org/10.1007/s11121-020-01165-9

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Acceptance of Drug Use Mediates Future Hard Drug Use Among At-Risk Adolescent Marijuana, Tobacco, and Alcohol Users

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 5/2021

Keepin’ It REAL—Mantente REAL in Mexico: a Cluster Randomized Controlled Trial of a Culturally Adapted Substance Use Prevention Curriculum for Early Adolescents

Boredom by Sensation-Seeking Interactions During Adolescence: Associations with Substance Use, Externalizing Behavior, and Internalizing Symptoms in a US National Sample

“Dying is Not a Fear”: Teen and Parent Perspectives on Messaging to Prevent Crystal Meth Use Among Teens in Rural North Idaho

Service Coordination to Address Maternal Mental Health, Partner Violence, and Substance Use: Findings from a National Survey of Home Visiting Programs

Social Validity of the Strengthening Families Program in Northeastern Brazil: the Voices of Parents, Adolescents, and Facilitators

A Rebuttal-Based Social Norms-Tailored Cannabis Intervention for At-Risk Adolescents