Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-22T18:07:21.611Z Has data issue: false hasContentIssue false
  • English
  • Français

Time-varying effects of families and peers on adolescent marijuana use: Person–environment interactions across development

Published online by Cambridge University Press:  15 July 2016

Marina Epstein ,
Karl G. Hill ,
Stephanie S. Roe ,
Jennifer A. Bailey ,
William G. Iacono ,
Matt McGue ,
Allison Kristman-Valente ,
Richard F. Catalano  and
Kevin P. Haggerty
Marina Epstein*
Affiliation:
University of Washington
Karl G. Hill
Affiliation:
University of Washington
Stephanie S. Roe
Affiliation:
University of Washington
Jennifer A. Bailey
Affiliation:
University of Washington
William G. Iacono
Affiliation:
University of Minnesota
Matt McGue
Affiliation:
University of Minnesota
Allison Kristman-Valente
Affiliation:
University of Washington
Richard F. Catalano
Affiliation:
University of Washington
Kevin P. Haggerty
Affiliation:
University of Washington
*
Address correspondence and reprint requests to: Marina Epstein, Social Development Research Group, School of Social Work, University of Washington, 9725 3rd Avenue NE, Suite 401, Seattle, WA 98115; E-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Studies have demonstrated that the effects of two well-known predictors of adolescent substance use, family monitoring and antisocial peers, are not static but change over the course of adolescence. Moreover, these effects may differ for different groups of youth. The current study uses time-varying effect modeling to examine the changes in the association between family monitoring and antisocial peers and marijuana use from ages 11 to 19, and to compare these associations by gender and levels of behavioral disinhibition. Data are drawn from the Raising Healthy Children study, a longitudinal panel of 1,040 youth. The strength of association between family monitoring and antisocial peers and marijuana use was mostly steady over adolescence, and was greater for girls than for boys. Differences in the strength of the association were also evident by levels of behavioral disinhibition: youth with lower levels of disinhibition were more susceptible to the influence of parents and peers. Stronger influence of family monitoring on girls and less disinhibited youth was most evident in middle adolescence, whereas the stronger effect of antisocial peers was significant during middle and late adolescence. Implications for the timing and targeting of marijuana preventive interventions are discussed.

Type
Regular Articles
Information
Development and Psychopathology , Volume 29 , Issue 3 , August 2017 , pp. 887 - 900
Copyright
Copyright © Cambridge University Press 2016 

Access options

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

Footnotes

Funding for this study was provided by grants from the National Institute on Drug Abuse (R01DA024411 and R01DA08093). The authors gratefully acknowledge the Raising Healthy Children study participants for their continued contribution to the longitudinal study. They also acknowledge the Social Development Research Group Survey Research Division for their hard work maintaining high panel retention and the Social Development Research Group editorial and administrative staff for their editorial and project support. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the funding agency. Richard F. Catalano is a board member of Channing Bete Company, distributor of Supporting School Success® and Guiding Good Choices®. Although the intervention effects are not studied in this paper, these programs were tested in the studies that produced the data sets used in this paper. An earlier version of this paper was presented in May 2015 at the annual meeting of the Society for Prevention Research held in Washington, DC.

References

Abadi, M. H., Shamblen, S. R., Thompson, K., Collins, D. A., & Johnson, K. (2011). Influence of risk and protective factors on substance use outcomes across developmental periods: A comparison of youth and young adults. Substance Use & Misuse, 46, 1604–1612.Google Scholar
Allen, M., Donohue, W. A., Griffin, A., Ryan, D., & Turner, M. M. M. (2003). Comparing the influence of parents and peers on the choice to use drugs. Criminal Justice and Behavior, 30, 163–186.Google Scholar
Arseneault, L., Cannon, M., Poulton, R., Murray, R., Caspi, A., & Moffitt, T. E. (2002). Cannabis use in adolescence and risk for adult psychosis: Longitudinal prospective study. British Medical Journal, 325, 1212–1213.CrossRefGoogle ScholarPubMed
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908. doi:10.1037/a0017376 Google Scholar
Bohnert, K. M., Anthony, J. C., & Breslau, N. (2012). Parental monitoring at age 11 and subsequent onset of cannabis use up to age 17: Results from a prospective study. Journal of Studies on Alcohol and Drugs, 73, 173–177.Google Scholar
Bröning, S., Kumpfer, K., Kruse, K., Sack, P.-M., Schaunig-Busch, I., Ruths, S., et al. (2012). Selective prevention programs for children from substance-affected families: A comprehensive systematic review. Substance Abuse Treatment, Prevention, and Policy, 7, 1–17.Google ScholarPubMed
Brown, E. C., Catalano, R. F., Fleming, C. B., Haggerty, K. P., & Abbott, R. D. (2005). Adolescent substance use outcomes in the Raising Healthy Children project: A two-part latent growth curve analysis. Journal of Consulting and Clinical Psychology, 73, 699–710. doi:10.1037/0022-006X.73.4.699 Google Scholar
Burt, S. A., & Neiderhiser, J. M. (2009). Aggressive versus nonaggressive antisocial behavior: Distinctive etiological moderation by age. Developmental Psychology, 45, 1164–1176.Google Scholar
Catalano, R. F., & Hawkins, J. D. (1996). The social development model: A theory of antisocial behavior. In Hawkins, J. D. (Ed.), Delinquency and crime: Current theories (pp. 149–197). New York: Cambridge University Press.Google Scholar
Catalano, R. F., Mazza, J. J., Harachi, T. W., Abbott, R. D., Haggerty, K. P., & Fleming, C. B. (2003). Raising healthy children through enhancing social development in elementary school: Results after 1.5 years. Journal of School Psychology, 41, 143–164. doi:10.1016/S0022-4405(03)00031-1 Google Scholar
Chen, P., & Jacobson, K. (2013). Impulsivity moderates promotive environmental influences on adolescent delinquency: A comparison across family, school, and neighborhood contexts. Journal of Abnormal Child Psychology, 41, 1133–1143. doi:10.1007/s10802-013-9754-8 Google Scholar
Chilcoat, H. D., & Anthony, J. C. (1996). Impact of parent monitoring on initiation of drug use through late childhood. Journal of the American Academy of Child & Adolescent Psychiatry, 35, 91–100. doi:10.1097/00004583-199601000-00017 Google Scholar
Choquet, M., Hassler, C., Morin, D., Falissard, B., & Chau, N. (2008). Perceived parenting styles and tobacco, alcohol and cannabis use among French adolescents: Gender and family structure differentials. Alcohol and Alcoholism, 43, 73–80. doi:10.1093/alcalc/agm060 Google Scholar
Cicchetti, D., & Rogosch, F. A. (2002). A developmental psychopathology perspective on adolescence. Journal of Consulting and Clinical Psychology, 70, 6–20. doi:10.1037/0022-006X.70.1.6 Google Scholar
Cicchetti, D., & Toth, S. L. (2009). The past achievements and future promises of developmental psychopathology: The coming of age of a discipline. Journal of Child Psychology and Psychiatry, 50, 16–25. doi:10.1111/j.1469-7610.2008.01979.x Google Scholar
Cleveland, M. J., Feinberg, M. E., Bontempo, D. E., & Greenberg, M. T. (2008). The role of risk and protective factors in substance use across adolescence. Journal of Adolescent Health, 43, 157–164.Google Scholar
Cleveland, M. J., Feinberg, M. E., & Jones, D. E. (2012). Predicting alcohol use across adolescence: Relative strength of individual, family, peer, and contextual risk and protective factors. Psychology of Addictive Behaviors, 26, 703–713.Google Scholar
Conrod, P. J., Stewart, S. H., Comeau, N., & Maclean, A. M. (2006). Efficacy of cognitive–behavioral interventions targeting personality risk factors for youth alcohol misuse. Journal of Clinical Child and Adolescent Psychology, 35, 550–563. doi:10.1207/s15374424jccp3504_6 Google Scholar
Copeland, J., Rooke, S., & Swift, W. (2013). Changes in cannabis use among young people: Impact on mental health. Current Opinion in Psychiatry, 26, 325–329.Google Scholar
Dever, B., Schulenberg, J., Dworkin, J., O'Malley, P., Kloska, D., & Bachman, J. (2012). Predicting risk-taking with and without substance use: The effects of parental monitoring, school bonding, and sports participation. Prevention Science, 13, 605–615. doi:10.1007/s11121-012-0288-z Google Scholar
DiClemente, R. J., Wingood, G. M., Crosby, R., Sionean, C., Cobb, B. K., Harrington, K., et al. (2001). Parental monitoring: Association with adolescents’ risk behaviors. Pediatrics, 107, 1363–1368. doi:10.1542/peds.107.6.1363 Google Scholar
Dishion, T. J., Nelson, S. E., & Kavanagh, K. (2003). The family check-up with high-risk young adolescents: Preventing early-onset substance use by parent monitoring. Behavior Therapy, 34, 553–571.Google Scholar
Dishion, T. J., & Owen, L. D. (2002). A longitudinal analysis of friendships and substance use: Bidirectional influence from adolescence to adulthood. Developmental Psychology, 38, 480–491.Google Scholar
Donohew, R. L., Hoyle, R. H., Clayton, R. R., Skinner, W. F., Colon, S. E., & Rice, R. E. (1999). Sensation seeking and drug use by adolescents and their friends: Models for marijuana and alcohol. Journal of Studies on Alcohol, 60, 622–631.Google Scholar
Duncan, L. E., & Keller, M. C. (2011). A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry. American Journal of Psychiatry, 168, 1041–1049.Google Scholar
Eaton, N., Krueger, R., Johnson, W., McGue, M., & Iacono, W. (2009). Parental monitoring, personality, and delinquency: Further support for a reconceptualization of monitoring. Journal of Research in Personality, 43, 49–59.Google Scholar
Ellickson, P. L., Tucker, J. S., Klein, D. J., & Saner, H. (2004). Antecedents and outcomes of marijuana use initiation during adolescence. Preventive Medicine, 39, 976–984.Google Scholar
Ellis, B. J., Boyce, W. T., Belsky, J., Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2011). Differential susceptibility to the environment: An evolutionary–neurodevelopmental theory. Development and Psychopathology, 23, 7–28. doi:10.1017/S0954579410000611 Google Scholar
Epstein, J. A., & Botvin, G. J. (2002). The moderating role of risk-taking tendency and refusal assertiveness on social influences in alcohol use among inner-city adolescents. Journal of Studies on Alcohol, 63, 456–459.Google Scholar
Evans-Polce, R. J., Vasilenko, S. A., & Lanza, S. T. (2015). Changes in gender and racial/ethnic disparities in rates of cigarette use, regular heavy episodic drinking, and marijuana use: Ages 14 to 32. Addictive Behaviors, 41, 218–222. doi:10.1016/j.addbeh.2014.10.029 Google Scholar
Fagan, A. A., Van Horn, M. L., Antaramian, S., & Hawkins, J. D. (2011). How do families matter? Age and gender differences in family influences on delinquency and drug use. Youth Violence & Juvenile Justice, 9, 150–170. doi:10.1177/1541204010377748 Google Scholar
Fergusson, D. M., Swain-Campbell, N. R., & Horwood, L. J. (2002). Deviant peer affiliations, crime and substance use: A fixed effects regression analysis. Journal of Abnormal Child Psychology, 30, 419–430. doi:10.1023/A:1015774125952 Google Scholar
Furman, W., & Buhrmester, D. (1992). Age and sex differences in perceptions of networks of personal relationships Child Development, 63, 103–115. doi:10.1111/j.1467-8624.1992.tb03599.x Google Scholar
Griffin, K. W., Botvin, G. J., Scheier, L. M., Diaz, T., & Miller, N. L. (2000). Parenting practices as predictors of substance use, delinquency, and aggression among urban minority youth: Moderating effects of family structure and gender. Psychology of Addictive Behaviors, 14, 174–184. doi:10.1037/0893-164X.14.2.174 Google Scholar
Hampson, S. E., Andrews, J. A., & Barckley, M. (2008). Childhood predictors of adolescent marijuana use: Early sensation-seeking, deviant peer affiliation, and social images. Addictive Behaviors, 33, 1140–1147.Google Scholar
Hawkins, J. D., & Weis, J. G. (1985). The social development model: An integrated approach to delinquency prevention. Journal of Primary Prevention, 6, 73–97. doi:10.1007/BF01325432 Google Scholar
Hayatbakhsh, M. R., Mamun, A. A., Najman, J. M., O'Callaghan, M. J., Bor, W., & Alati, R. (2008). Early childhood predictors of early substance use and substance use disorders: Prospective study. Australian and New Zealand Journal of Psychiatry, 42, 720–731.Google Scholar
Hill, K. G., Hawkins, J. D., Bailey, J. A., Catalano, R. F., Abbott, R. D., & Shapiro, V. B. (2010). Person–environment interaction in the prediction of alcohol abuse and alcohol dependence in adulthood. Drug and Alcohol Dependence, 110, 62–69.Google Scholar
Hoeve, M., Dubas, J. S., Eichelsheim, V. I., van der Laan, P. H., Smeenk, W., & Gerris, J. R. M. (2009). The relationship between parenting and delinquency: A meta-analysis. Journal of Abnormal Child Psychology, 37, 749–775.Google Scholar
Jang, S. J. (2002). The effects of family, school, peers, and attitudes on adolescents’ drug use: Do they vary with age? Justice Quarterly, 19, 97–126.Google Scholar
Johnston, L., O'Malley, P., Bachman, J., Schulenberg, J., & Miech, R. (2014). Monitoring the Future national survey results on drug use, 1975–2013: Vol. 1. Secondary school students. Ann Arbor, MI: University of Michigan, Institute for Social Research.Google Scholar
Kaynak, Ö., Meyers, K., Caldeira, K. M., Vincent, K. B., Winters, K. C., & Arria, A. M. (2013). Relationships among parental monitoring and sensation seeking on the development of substance use disorder among college students. Addictive Behaviors, 38, 1457–1463. doi:10.1016/j.addbeh.2012.08.003 Google Scholar
Kelly, A. B., Toumbourou, J. W., O'Flaherty, M., Patton, G. C., Homel, R., Connor, J. P., et al. (2011). Family relationship quality and early alcohol use: Evidence for gender-specific risk processes. Journal of Studies on Alcohol and Drugs, 72, 399–407.Google Scholar
Knyazev, G. G., Slobodskaya, H. R., Kharchenko, I. I., & Wilson, G. D. (2004). Personality and substance use in Russian youths: The predictive and moderating role of behavioural activation and gender. Personality and Individual Differences, 37, 827–843.Google Scholar
Kopstein, A. N., Crum, R. M., Celentano, D. D., & Martin, S. S. (2001). Sensation seeking needs among 8th and 11th graders: Characteristics associated with cigarette and marijuana use. Drug and Alcohol Dependence, 62, 195–203.CrossRefGoogle ScholarPubMed
Kosterman, R., Hawkins, J. D., Guo, J., Catalano, R. F., & Abbott, R. D. (2000). The dynamics of alcohol and marijuana initiation: Patterns and predictors of first use in adolescence. American Journal of Public Health, 90, 360–366.Google Scholar
Kretschmer, T., Dijkstra, J. K., Veenstra, R., Ormel, J., & Verhulst, F. C. (2013). Dopamine receptor D4 gene moderates the effect of positive and negative peer experiences on later delinquency: The Tracking Adolescents’ Individual Lives Survey study. Development and Psychopathology, 25, 1107–1117.Google Scholar
Lac, A., & Crano, W. D. (2009). Monitoring matters: Meta-analytic review reveals the reliable linkage of parental monitoring with adolescent marijuana use. Perspectives on Psychological Science, 4, 578–586.Google Scholar
Lanza, S. T., Vasilenko, S. A., Liu, X., Li, R., & Piper, M. E. (2014). Advancing the understanding of craving during smoking cessation attempts: A demonstration of the time-varying effect model. Nicotine & Tobacco Research, 16(Suppl. 2), S127–S134. doi:10.1093/ntr/ntt128 Google Scholar
Lee, S. S. (2011). Deviant peer affiliation and antisocial behavior: Interaction with monoamine oxidase A (MAOA) genotype. Journal of Abnormal Child Psychology, 39, 321–332.Google Scholar
Li, R., Tan, X., Huang, L., Wagner, A., & Yang, J. (2014). TVEM (time-varying effect model) SAS macro suite users’ guide. University Park, PA: Pennsylvania State University.Google Scholar
Macleod, J., Oakes, R., Copello, A., Crome, L., Egger, M., Hickman, M., et al. (2004). Psychological and social sequelae of cannabis and other illicit drug use by young people: A systematic review of longitudinal, general population studies. Lancet, 363, 1579–1588. doi:10.1016/s0140-6736(04)16200-4 Google Scholar
Martins, S. S., Storr, C. L., Alexandre, P. K., & Chilcoat, H. D. (2008). Adolescent ecstasy and other drug use in the National Survey of Parents and Youth: The role of sensation-seeking, parental monitoring and peer's drug use. Addictive Behaviors, 33, 919–933.Google Scholar
Masten, A. S. (2006). Developmental psychopathology: Pathways to the future. International Journal of Behavioral Development, 30, 47–54. doi:10.1177/0165025406059974 Google Scholar
McArdle, P., Wiegersma, A., Gilvarry, E., Kolte, B., McCarthy, S., Fitzgerald, M., et al. (2002). European adolescent substance use: The roles of family structure, function and gender. Addiction, 97, 329–336. doi:10.1046/j.1360-0443.2002.00066.x Google Scholar
Mears, D. P., Ploeger, M., & Warr, M. (1998). Explaining the gender gap in delinquency: Peer influence and moral evaluations of behavior. Journal of Research in Crime and Delinquency, 35, 251–266.Google Scholar
Meldrum, R. C., Miller, H. V., & Flexon, J. L. (2013). Susceptibility to peer influence, self-control, and delinquency. Sociological Inquiry, 83, 106–129. doi:10.1111/j.1475-682x.2012.00434.x Google Scholar
Moon, S. S., Blakey, J. M., Boyas, J., Horton, K., & Kim, Y. J. (2014). The influence of parental, peer, and school factors on marijuana use among Native American adolescents. Journal of Social Service Research, 40, 147–159. doi:10.1080/01488376.2013.865578 Google Scholar
Newcomb, M. D., & McGee, L. (1991). Influence of sensation seeking on general deviance and specific problem behaviors from adolescence to young adulthood. Journal of Personality and Social Psychology, 61, 614–628.Google Scholar
Parsai, M., Voisine, S., Marsiglia, F. F., Kulis, S., & Nieri, T. (2009). The protective and risk effects of parents and peers on substance use, attitudes, and behaviors of Mexican and Mexican American female and male adolescents. Youth & Society, 40, 353–376.Google Scholar
Reboussin, B. A., Hubbard, S., & Ialongo, N. S. (2007). Marijuana use patterns among African-American middle-school students: A longitudinal latent class regression analysis. Drug and Alcohol Dependence, 90, 12–24.Google Scholar
Rodgers-Farmer, A. Y. (2000). Parental monitoring and peer group association: Their influence on adolescent substance use. Journal of Social Service Research, 27, 1–18. doi:10.1300/J079v27n02_01 Google Scholar
Sargent, J. D., Tanski, S., Stoolmiller, M., & Hanewinkel, R. (2010). Using sensation seeking to target adolescents for substance use interventions. Addiction, 105, 506–514.Google Scholar
Schulenberg, J. (1999). On peer influences to get drunk: A panel study of young adolescents. Merrill–Palmer Quarterly, 45, 108–142.Google Scholar
Seydlitz, R. (1991). The effects of age and gender on parental control and delinquency. Youth & Society, 23, 175–201. doi:10.1177/0044118X91023002002 Google Scholar
Sher, K. J., & Trull, T. J. (1994). Personality and disinhibitory psychopathology: Alcoholism and antisocial personality disorder. Journal of Abnormal Psychology, 103, 92–102. doi:10.1037/0021-843X.103.1.92 Google Scholar
Shillington, A. M., Lehman, S., Clapp, J., Hovell, M. F., Sipan, C., & Blumberg, E. J. (2005). Parental monitoring: Can it continue to be protective among high-risk adolescents? Journal of Child & Adolescent Substance Abuse, 15, 1–15. doi:10.1300/J029v15n01_01 Google Scholar
Shiyko, M., Burkhalter, J., Li, R., & Park, B. J. (2014). Modeling nonlinear time-dependent treatment effects: An application of the generalized time-varying effect model (TVEM). Journal of Consulting and Clinical Psychology, 82, 760–772. doi:10.1037/a0035267 Google Scholar
Shiyko, M., Lanza, S., Tan, X., Li, R., & Shiffman, S. (2012). Using the time-varying effect model (TVEM) to examine dynamic associations between negative affect and self confidence on smoking urges: Differences between successful quitters and relapsers. Prevention Science, 13, 288–299. doi:10.1007/s11121-011-0264-z Google Scholar
Silins, E., Horwood, L. J., Patton, G. C., Fergusson, D. M., Olsson, C. A., Hutchinson, D. M., et al. (2014). Young adult sequelae of adolescent cannabis use: An integrative analysis. Lancet Psychiatry, 1, 286–293.Google Scholar
Simons-Morton, B., Haynie, D. L., Crump, A. D., Eitel, P., & Saylor, K. E. (2001). Peer and parent influences on smoking and drinking among early adolescents. Health Education & Behavior, 28, 95–107.Google Scholar
Slater, M. D. (2003). Sensation-seeking as a moderator of the effects of peer influences, consistency with personal aspirations, and perceived harm on marijuana and cigarette use among younger adolescents. Substance Use & Misuse, 38, 865–880.Google Scholar
Smetana, J. G., & Daddis, C. (2002). Domain-specific antecedents of parental psychological control and monitoring: The role of parenting beliefs and practices. Child Development, 73, 563–580.Google Scholar
Steinberg, L., Fletcher, A., & Darling, N. (1994). Parental monitoring and peer influences on adolescent substance use. Pediatrics, 93, 1060–1064.CrossRefGoogle ScholarPubMed
Stephenson, M. T., & Helme, D. W. (2006). Authoritative parenting and sensation seeking as predictors of adolescent cigarette and marijuana use. Journal of Drug Education, 36, 247–270.Google Scholar
Substance Abuse and Mental Health Services Administration. (2014). Results from the 2013 National Survey on Drug Use and Health: Summary of national findings (NSDUH Series H-48, HHS Publication SMA 14-4863) . Rockville, MD: Substance Abuse and Mental Health Services Administration.Google Scholar
Svensson, R. (2004). Gender differences in adolescent drug use: The impact of parental monitoring and peer deviance. Sage Family Studies Abstracts, 26, 300–329.Google Scholar
Tan, X., Shiyko, M. P., Li, R., Li, Y., & Dierker, L. (2012). A time-varying effect model for intensive longitudinal data. Psychological Methods, 17, 61–77. doi:10.1037/a0025814 [supplemental doi:10.1037/a0025814.supp]Google Scholar
Tang, Z., & Orwin, R. G. (2009). Marijuana initiation among American youth and its risks as dynamic processes: Prospective findings from a national longitudinal study. Substance Use & Misuse, 44, 195–211.Google Scholar
Teichman, M., Barnea, Z., & Ravav, G. (1989). Personality and substance use among adolescents: A longitudinal study. British Journal of Addiction, 84, 181–190.Google Scholar
Thomas, K. J., & McGloin, J. M. (2013). A dual-systems approach for understanding differential susceptibility to processes of peer influence. Criminology, 51, 435–474.Google Scholar
Tucker, C. J., McHale, S. M., & Crouter, A. C. (2003). Dimensions of mothers’ and fathers’ differential treatment of siblings: Links with adolescents’ sex-typed personal qualities. Family Relations, 52, 82–89.Google Scholar
Van Ryzin, M. J., Fosco, G. M., & Dishion, T. J. (2012). Family and peer predictors of substance use from early adolescence to early adulthood: An 11-year prospective analysis. Addictive Behaviors, 37, 1314–1324.Google Scholar
Varner, F., & Mandara, J. (2014). Differential parenting of African American adolescents as an explanation for gender disparities in achievement. Journal of Research on Adolescence, 24, 667–680.Google Scholar
Vasilenko, S. A., & Lanza, S. T. (2014). Predictors of multiple sexual partners from adolescence through young adulthood. Journal of Adolescent Health, 55, 491–497. doi:10.1016/j.jadohealth.2013.12.025 Google Scholar
Vasilenko, S. A., Piper, M. E., Lanza, S. T., Liu, X., Yang, J., & Li, R. (2014). Time-varying processes involved in smoking lapse in a randomized trial of smoking cessation therapies. Nicotine & Tobacco Research, 16(Suppl. 2), S135–S143. doi:10.1093/ntr/ntt185 Google Scholar
Vitulano, M. L., Fite, P. J., & Rathert, J. L. (2010). Delinquent peer influence on childhood delinquency: The moderating effect of impulsivity. Journal of Psychopathology and Behavioral Assessment, 32, 315–322.Google Scholar
Wiebe, S. A., Clark, C. A. C., De Jong, D. M., Chevalier, N., Espy, K. A., & Wakschlag, L. (2015). Prenatal tobacco exposure and self-regulation in early childhood: Implications for developmental psychopathology. Development and Psychopathology, 27, 397–409. doi:10.1017/S095457941500005X Google Scholar
Wright, A. G. C., Hallquist, M. N., Swartz, H. A., Frank, E., & Cyranowski, J. M. (2014). Treating co-occurring depression and anxiety: Modeling the dynamics of psychopathology and psychotherapy using the time-varying effect model. Journal of Consulting and Clinical Psychology, 82, 839–853. doi:10.1037/a0034430 Google Scholar
Yabiku, S. T., Marsiglia, F. F., Kulis, S., Parsai, M. B., Becerra, D., & Del-Colle, M. (2010). Parental monitoring and changes in substance use among Latino/a and non-Latino/a preadolescents in the Southwest. Substance Use & Misuse, 45, 2524–2550. doi:10.3109/10826081003728256 Google Scholar
Yanovitzky, I. (2005). Sensation seeking and adolescent drug use: The mediating role of association with deviant peers and pro-drug discussions. Health Communication, 17, 67–89. doi:10.1207/s15327027hc1701_5 Google Scholar