Parent Prevention Communication Profiles and Adolescent Substance Use: A Latent Profile Analysis and Growth Curve Model

References

• Ackard, D. M., Neumak-Sztainer, D., Story, M., & Perry, C. (2006). Parent–child connectedness and behavioral and emotional health among adolescents. American Journal of Preventive Medicine, 30, 59–66. doi:10.1016/j.amepre.2005.09.013
   PubMed Web of Science ®Google Scholar
• Baan, R., Straif, K., Grosse, Y., Secretan, B., El Ghissassi, F., Bouvard, V., … Cogliano, V. (2007). WHO International Agency for Research on Cancer Monograph Working Group. Carcinogenicity of alcoholic beverages. Lancet Oncology, 8, 292–293. doi:10.1016/S1470-2045(07)70099-2
   PubMed Web of Science ®Google Scholar
• Baxter, L. A., Bylund, C. L., Imes, R. S., & Scheive, D. M. (2005). Family communication environments and rule-based social control of adolescents’ healthy lifestyle choices. Journal of Family Communication, 5, 209–227. doi:10.1207/s15327698jfc0503_3
   Google Scholar
• Boyd, D. R., & Bee, H. L. (2012). The developing child. New York, NY: Pearson.
   Google Scholar
• Cabin, R. J., & Mitchell, R. J. (2000). To Bonferroni or not to Bonferroni: When and how are the questions. Bulletin of the Ecological Society of America, 81, 246–248.
   Google Scholar
• Cavazos-Rehg, P. A., Housten, A. J., Krauss, M. J., Sowles, S. J., Spitznagel, E. L., Chaloupka, F. J., … Bierut, L. J. (2016). Selected state policies and associations with alcohol use behaviors and risky driving behaviors among youth: Findings from Monitoring the Future study. Alcoholism: Clinical and Experimental Research, 40, 1030–1036. doi:10.1111/acer.13041
   PubMed Web of Science ®Google Scholar
• Chen, P., & Jacobson, K. C. (2012). Developmental trajectories of substance use from early adolescence to young adulthood: Gender and racial/ethnic differences. Journal of Adolescent Health, 50, 154–163. doi:10.1016/j.jadohealth.2011.05.013
   PubMed Web of Science ®Google Scholar
• Colby, M., Hecht, M. L., Miller-Day, M., Krieger, J., Syvertsen, A., Graham, J., & Pettigrew, J. (2013). Adapting school-based substance use prevention curriculum through cultural grounding: A review and exemplar of adaptation processes for rural schools. American Journal of Community Psychology, 51, 190–205. doi:10.1007/s10464-012-9524-8
   PubMed Web of Science ®Google Scholar
• Collins, L. M., Murphy, S. A., & Bierman, K. L. (2004). A conceptual framework for adaptive preventive interventions. Prevention Science, 5(3), 185–196. doi:10.1023/B:PREV.0000037641.26017.00
   PubMed Web of Science ®Google Scholar
• Connella, A. M., & Frye, A. A. (2006). Growth mixture modelling in developmental psychology: Overview and demonstration of heterogeneity in developmental trajectories of adolescent antisocial behaviour. Infant and Child Development, 15, 609–621. doi:10.1002/icd.481
   Web of Science ®Google Scholar
• Dollinger, S. J., & Malmquist, D. (2009). Reliability and validity of single-item self-reports: With special relevance to college students’ alcohol use, religiosity, study, and social life. The Journal of General Psychology, 136, 231–242. doi:10.3200/GENP.136.3.231-242
   PubMed Web of Science ®Google Scholar
• Ebersole, D. S., Miller-Day, M., & Raup-Krieger, J. (2014). Do actions speak louder than words? Adolescent interpretations of parental substance use. Journal of Family Communication, 14, 328–351. doi:10.1080/15267431.2014.945699
   PubMedGoogle Scholar
• Enders, C. K., & Bandalos, D. L. (2001). The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 8, 430–457. doi:10.1207/S15328007SEM0803_5
   Web of Science ®Google Scholar
• Ennett, S. T., Bauman, K. E., Foshee, V. A., Pembertonm, M., & Hicks, K. (2001). Parent–child communication about adolescent tobacco and alcohol use: What do parents say and does it affect youth behavior? Journal of Marriage and the Family, 63, 48–62. doi:10.1111/j.1741-3737.2001.00048.x
   Web of Science ®Google Scholar
• Fitzpatrick, M. A., & Ritchie, L. D. (1994). Communication schemata within the family. Human Communication Research, 20, 275–301. doi:10.1111/j.1468-2958.1994.tb00324.x
   Web of Science ®Google Scholar
• Graham, J. W., Cumsille, P. E., & Elek-Fisk, E. (2003). Methods of handling missing data. In J. A. Schinka & W. F. Velicer (Eds.), Research methods in psychology (pp. 87–114). New York, NY: John Wiley & Sons.
   Google Scholar
• Graham, J. W., Hofer, S. M., & MacKinnon, D. P. (1996). Maximizing the usefulness of data obtained with planned missing value patterns: An application of maximum likelihood procedures. Multivariate Behavioral Research, 31, 197–218. doi:10.1207/s15327906mbr3102_3
   PubMed Web of Science ®Google Scholar
• Graham, J. W., Pettigrew, J., Miller-Day, M., Krieger, J. L., Zhou, J., & Hecht, M. L. (2014). Random assignment of schools to groups in the Drug Resistance Strategies Rural Project: Some new methodological twists. Prevention Science, 15, 516–525. doi:10.1007/s11121-013-0403-9
   PubMed Web of Science ®Google Scholar
• Hansen, W. B., & Graham, J. W. (1991). Preventing alcohol, marijuana, and cigarette use among adolescents: Peer pressure resistance training versus establishing conservative norms. Preventive Medicine, 20, 414–430. doi:10.1016/0091-7435(91)90039-7
   PubMed Web of Science ®Google Scholar
• Harrison, L., & Hughes, A. (1997). The validity of self-reported drug use: Improving the accuracy of survey estimates (NIH Publication No. 97-4147, NIDA Research Monograph 167). Rockville, MD: National Institute on Drug Abuse.
   Google Scholar
• Hawkins, J. D., Graham, J. W., Maguin, E., Abbott, R., Hill, K. G., & Catalano, R. F. (1997). Exploring the effects of age of alcohol use initiation and psychosocial risk factors on subsequent alcohol misuse. Journal of Studies on Alcohol, 58, 280–290. doi:10.15288/jsa.1997.58.280
   PubMed Web of Science ®Google Scholar
• Jander, A., Crutzen, R., Mercken, L., & De Vries, H. (2015). Web-based interventions to decrease alcohol use in adolescents: A Delphi study about increasing effectiveness and reducing drop-out. BMC Public Health, 15, 340–353. doi:10.1186/s12889-015-1639-z
   PubMed Web of Science ®Google Scholar
• Johnston, L. (2010). Monitoring the future: National results on adolescent drug use: Overview of key findings. Darby, PA: Diane.
   Google Scholar
• Kam, J. A. (2011). Identifying changes in youth’s subgroup membership over time based on their targeted communication about substance use with parents and friends. Human Communication Research, 37, 324–349. doi:10.1111/j.1468-2958.2011.01408.x
   Web of Science ®Google Scholar
• Kam, J. A., Castro, F. G., & Wang, N. (2014). Parent–child communication’s attenuating effects on Mexican early adolescents’ perceived discrimination, depressive symptoms, and substance use. Human Communication Research, 41, 204–225. doi:10.1111/hcre.12043
   Web of Science ®Google Scholar
• Kam, J. A., Matsunaga, M., Hecht, M. L., & Ndiaye, K. (2009). Extending the theory of planned behavior to predict alcohol, tobacco, and marijuana use among youth of Mexican heritage. Prevention Science, 10, 41–53. doi:10.1007/s11121-008-0110-0
   PubMed Web of Science ®Google Scholar
• Kam, J. A., & Middleton, A. V. (2013). The associations between parents’ references to their own past substance use and youth’s substance-use beliefs and behaviors: A comparison of Latino and European American youth. Human Communication Research, 39, 208–229. doi:10.1111/hcre.12001
   Web of Science ®Google Scholar
• Kam, J. A., Potocki, B., & Hecht, M. L. (2014). Encouraging Mexican-heritage youth to intervene when friends drink: The role of targeted parent-child communication against alcohol. Communication Research, 14, 544–664. doi:10.1177/0093650212446621
   Web of Science ®Google Scholar
• Kam, J. A., & Yang, S. (2013). Explicating how parent–child communication increases Latino and European American early adolescents’ intentions to intervene in a friend’s substance use. Prevention Science, 15, 536–546. doi:10.1007/s11121-013-0404-8
   Web of Science ®Google Scholar
• Kirby, T., & Barry, A. E. (2012). Alcohol as a gateway drug: A study of US 12th graders. Journal of School Health, 82, 371–379. doi:10.1111/j.1746-1561.2012.00712.x
   PubMed Web of Science ®Google Scholar
• Koerner, A. F., & Fitzpatrick, M. A. (2002). Toward a theory of family communication. Communication Theory, 12, 70–91. doi:10.1111/j.1468-2885.2002.tb00260.x
   Web of Science ®Google Scholar
• Komro, K. A., Perry, C. L., Veblen-Mortenson, S., Farbakhsh, K., Toomey, T. L., Stigler, M. H., … Williams, C. L. (2008). Outcomes from a randomized controlled trial of a multi-component alcohol use preventive intervention for urban youth: Project Northland Chicago. Addiction, 103, 606–618. doi:10.1111/j.1360-0443.2007.02110.x
   PubMed Web of Science ®Google Scholar
• Kumpfer, K. L., Alvarado, R., & Whiteside, H. O. (2003). Family-based interventions for substance use and misuse prevention. Substance Use & Misuse, 38, 1759–1787. doi:10.1081/JA-120024240
   PubMed Web of Science ®Google Scholar
• Lustria, M. L. A., Noar, S. M., Cortese, J., Van Stee, S. K., Glueckauf, R. L., & Lee, J. (2013). A meta-analysis of web-delivered tailored health behavior change interventions. Journal of Health Communication, 18, 1039–1069. doi:10.1080/10810730.2013.768727
   PubMed Web of Science ®Google Scholar
• Maisto, S. A., McKay, J. R., & Connors, G. J. (1990). Self-report issues in substance abuse: State of the art and future directions. Behavioral Assessment, 12, 117–134.
   Google Scholar
• Matsunaga, M., Hecht, M. L., Elek, E., & Ndiaye, K. (2010). Ethnic identity development and acculturation: A longitudinal analysis of Mexican-heritage youth in the southwest United States. Journal of Cross-Cultural Psychology, 41, 410–427. doi:10.1177/0022022109359689
   PubMed Web of Science ®Google Scholar
• McLachlan, G. J., & Peel, D. (2000). Finite mixture models. New York, NY: Wiley.
   Google Scholar
• Miech, R. A., Johnston, L. D., O’Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2015). Monitoring the Future national survey results on drug use, 1975–2014. Darby, PA: Diane.
   Google Scholar
• Miller, M., Alberts, J. K., Hecht, M. L., Trost, M., & Krizek, R. L. (2000). Adolescent relationships and drug use. Mahwah, NJ: Lawrence Erlbaum Associates.
   Google Scholar
• Miller-Day, M. (2002). Parent-adolescent communication about alcohol, tobacco, and other drug use. Journal of Adolescent Research, 17, 604–616. doi:10.1177/074355802237466
   Web of Science ®Google Scholar
• Miller-Day, M. (2008). Talking to youth about drugs: What do late adolescents say about parental strategies? Family Relations, 57, 1–12. doi:10.1111/j.1741-3729.2007.00478.x
   Web of Science ®Google Scholar
• Miller-Day, M., & Dodd, A. H. (2004). Toward a descriptive model of parent–offspring communication about alcohol and other drugs. Journal of Social and Personal Relationships, 21, 69–91. doi:10.1177/0265407504039846
   Web of Science ®Google Scholar
• Miller-Day, M., & Hecht, M. L. (2013). Narrative means to preventative ends: A narrative engagement framework for designing prevention interventions. Health Communication, 28, 657–670. doi:10.1080/10410236.2012.762861
   PubMed Web of Science ®Google Scholar
• Miller-Day, M., & Kam, J. A. (2010). More than just openness: Developing and validating a measure of targeted parent–child communication about alcohol. Health Communication, 25, 293–302. doi:10.1080/10410231003698952
   PubMed Web of Science ®Google Scholar
• Muthén, L. K., & Muthén, B. O. (2007). Mplus users’ guide. Los Angeles, CA: Muthén & Muthén.
   Google Scholar
• Napper, L. E., Froidevaux, N. M., & LaBrie, J. W. (2016). Being blunt about marijuana: Parent communication about marijuana with their emerging adult children. Prevention Science, 17, 882–891. doi:10.1007/s11121-016-0681-0
   PubMed Web of Science ®Google Scholar
• Napper, L. E., Hummer, J. F., Lac, A., & LaBrie, J. W. (2014). What are other parents saying? Perceived parental communication norms and the relationship between alcohol-specific parental communication and college student drinking. Psychology of Addictive Behaviors, 28(1), 31–41. doi:10.1037/a0034496
   PubMed Web of Science ®Google Scholar
• National Center for Statistics and Analysis. (2016, May). Young drivers: 2014 data ( Traffic Safety Facts. Report No. DOT HS 812 278). Washington, DC: National Highway Traffic Safety Administration.
   Google Scholar
• National Institute on Drug Abuse. (2016). Monitoring the Future 2015: Teen drug use. Retrieved from www.drugabuse.gov
   Google Scholar
• Newman, D. A. (2003). Longitudinal modeling with randomly and systematically missing data: A simulation of ad hoc, maximum likelihood, and multiple imputation techniques. Organizational Research Methods, 6, 328–362. doi:10.1177/1094428103254673
   Web of Science ®Google Scholar
• Newton-Howes, G., & Boden, J. M. (2015). Relation between age of first drinking and mental health and alcohol and drug disorders in adulthood: Evidence from a 35-year cohort study. Addiction, 111, 637–644. doi:10.1111/add.13230
   Web of Science ®Google Scholar
• Noar, S. M., Harrington, N. G., & Aldrich, R. S. (2009). The role of message tailoring in the development of persuasive health communication messages. Annals of the International Communication Association, 33, 73–133. doi:10.1080/23808985.2009.11679085
   Google Scholar
• Nylund, K. L., Asparouhov, T., & Muthen, B. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling. A Monte Carlo simulation study. Structural Equation Modeling, 14, 535–569. doi:10.1080/10705510701575396
   Web of Science ®Google Scholar
• Oetting, E. R., & Donnermeyer, J. F. (1998). Primary socialization theory: The etiology of drug use and deviance. Substance Use & Misuse, 33, 995–1026. doi:10.3109/10826089809056252
   PubMed Web of Science ®Google Scholar
• Preacher, K. J., Wichman, A. L., MacCallum, R. C., & Briggs, N. E. (2008). Latent growth curve modeling. Los Angeles, CA: Sage.
   Google Scholar
• Reimuller, A., Hussong, A., & Ennett, S. T. (2011). The influence of alcohol-specific communication on adolescent alcohol use and alcohol-related consequences. Prevention Science, 12, 389–400. doi:10.1007/s11121-011-0227-4
   PubMed Web of Science ®Google Scholar
• Rice, W. R. (1989). Analyzing tables of statistical tests. Evolution, 43, 223–225. doi:10.2307/2409177
   PubMed Web of Science ®Google Scholar
• Schrodt, P., Witt, P. L., & Messersmith, A. S. (2008). A meta-analytic review of family communication patterns and their associations with information processing, behavioral, and psychosocial outcomes. Communication Monographs, 75, 248–269. doi:10.1080/03637750802256318
   Web of Science ®Google Scholar
• Schwartz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464. doi:10.1214/aos/1176344136
   Web of Science ®Google Scholar
• Shield, K. D., Parry, C., & Rehm, J. (2013). Focus on: Chronic diseases and conditions related to alcohol use. Alcohol Research: Current Reviews, 35, 155–173.
   PubMed Web of Science ®Google Scholar
• Spoth, R., Trudeau, L., Guyll, M., Shin, C., & Redmond, C. (2009). Universal intervention effects on substance use among young adults mediated by delayed adolescent substance initiation. Journal of Consulting and Clinical Psychology, 77, 620–632. doi:10.1037/a0016029
   PubMed Web of Science ®Google Scholar
• Stephenson, M. T., Quick, B. L., Atkinson, J., & Tschida, D. A. (2005). Authoritative parenting and drug-prevention practices: Implications for antidrug ads for parents. Health Communication, 17, 301–321. doi:10.1207/s15327027hc1703_6
   PubMed Web of Science ®Google Scholar
• Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality. (2013). Drug abuse warning network: Detailed tables: National estimates, drug-related emergency department visits for 2006–2011. Rockville, MD: Substance Abuse and Mental Health Services Administration.
   Google Scholar
• Tofighi, D., & Enders, C. K. (2007). Identifying the correct number of classes in a growth mixture model. In G. R. Hancock (Ed.), Mixture models in latent variable research (pp. 317–341). Greenwich, CT: Information Age.
   Google Scholar
• Turrisi, R., Wiersma, K. A., & Hughes, K. K. (2000). Binge-drinking-related consequences in college students: Role of drinking beliefs and mother–teen communications. Psychology of Addictive Behaviors, 14, 342–355. doi:10.1037/0893-164X.14.4.342
   PubMed Web of Science ®Google Scholar
• Vermeulen-Smit, E., Verdurmen, J. E. E., & Engels, R. C. M. E. (2015). The effectiveness of family interventions in preventing adolescent illicit drug use: A systematic review and meta-analysis of randomized controlled trials. Clinical Child and Family Psychology Review, 18, 218–239. doi:10.1007/s10567-015-0185-7
   PubMed Web of Science ®Google Scholar
• Vermunt, J. K., & Magidson, J. (2002). Latent class cluster analysis. In J. A. Hagenaars, & A. L. McCutcheon (Eds.), Applied latent class analysis (pp. 89–106). New York, NY: Cambridge University Press.
   Google Scholar
• Williams, L. R., Ayers, S., Baldwin, A., & Marsiglia, F. F. (2016). Delaying youth substance-use initiation: A cluster randomized controlled trial of complementary youth and parenting interventions. Journal of the Society for Social Work and Research, 7, 177–200. doi:10.1086/685298
   Web of Science ®Google Scholar
• Yang, C. (2006). Evaluating latent class analysis models in qualitative phenotype identification. Computational Statistics & Data Analysis, 50, 1090–1104. doi:10.1016/j.csda.2004.11.004
   Web of Science ®Google Scholar