Advertisement

Journal of Youth and Adolescence

, Volume 45, Issue 10, pp 2164–2177 | Cite as

A Longitudinal Test of the Parent–Adolescent Family Functioning Discrepancy Hypothesis: A Trend toward Increased HIV Risk Behaviors Among Immigrant Hispanic Adolescents

  • David Córdova
  • Seth J. Schwartz
  • Jennifer B. Unger
  • Lourdes Baezconde-Garbanati
  • Juan A. Villamar
  • Daniel W. Soto
  • Sabrina E. Des Rosiers
  • Tae Kyoung Lee
  • Alan Meca
  • Miguel Ángel Cano
  • Elma I. Lorenzo-Blanco
  • Assaf Oshri
  • Christopher P. Salas-Wright
  • Brandy Piña-Watson
  • Andrea J. Romero
Empirical Research

Abstract

Parent-adolescent discrepancies in family functioning play an important role in HIV risk behaviors among adolescents, yet longitudinal research with recent immigrant Hispanic families remains limited. This study tested the effects of trajectories of parent–adolescent family functioning discrepancies on HIV risk behaviors among recent-immigrant Hispanic adolescents. Additionally, we examined whether and to what extent trajectories of parent-adolescent family functioning discrepancies vary as a function of gender. We assessed family functioning of 302 Hispanic adolescents (47 % female) and their parent (70 % female) at six time points over a three-year period and computed latent discrepancy scores between parent and adolescent reports at each timepoint. Additionally, adolescents completed measures of sexual risk behaviors and alcohol use. We conducted a confirmatory factor analysis to determine the feasibility of collapsing parent and adolescent reported family functioning indicators onto a single latent discrepancy variable, tested model invariance over time, and conducted growth mixture modeling (GMM). GMM yielded a three-class solution for discrepancies: High-Increasing, High-Stable, and Low-Stable. Relative to the Low-Stable class, parent–adolescent dyads in the High-Increasing and High-Stable classes were at greater risk for adolescents reporting sexual debut at time 6. Additionally, the High-Stable class was at greater risk, relative to the Low-Stable class, in terms of adolescent lifetime alcohol use at 30 months post-baseline. Multiple group GMM indicated that trajectories of parent-adolescent family functioning trajectories did not vary by gender. Implications for future research and practice are discussed.

Keywords

HIV Alcohol use Family functioning Discrepancies Adolescents 

Notes

Authors’ Contributions

DC conceived of the study, participated in its design and coordination, performed statistical analysis, participated in interpretation of the data, and wrote the first draft of the manuscript; SJ participated in conception and design of study, data collection, statistical analysis and interpretation of the data; JU participated in conception and design of study, data collection; LBG participated in conception and design of study, and data collection; JV participated in conception and design of study, and data collection; DS participated in conception and design of study, and data collection; SDR participated in conception and design of study, and data collection; TKL participated in statistical analysis and interpretation of the data; AM participated in statistical analysis and interpretation of the data; MAC participated in conception and design of study and interpretation of the data; ELB participated in conception and design of study, and interpretation of the data; AO participated in statistical analysis and interpretation of the data; CSW participated in conception and design of study, and interpretation of the data; BPW participated in conception and design of study, and interpretation of the data; AR participated in conception and design of study, and interpretation of the data. All authors read, revised and approved the final manuscript.

Conflicts of interest

The authors report no conflict of interests.

Funding

This study was funded by the National Institute on Drug Abuse, co-funded by the National Institute on Alcohol Abuse and Alcoholism (Grant DA026594; Seth J. Schwartz, PI; Jennifer B. Unger, Co-PI). Preparation of this manuscript was supported in part by grants from the National Institute of Mental Health (Grant R25 MH067127; Torsten B. Neilands) and National Institute on Minority Health and Health Disparities Loan Repayment Program (Grant L60 MD006269; PI, David Córdova).

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

References

  1. Acock, A. (2008). Latent growth curve modeling using Mplus. Corvallis, OR: Summer Institute on Research Methodology.Google Scholar
  2. Barnes, H. L., & Olson, D. H. (1985). Parent-adolescent communication and the circumplex model. Child Development, 56, 438–447. doi: 10.2307/1129732.CrossRefGoogle Scholar
  3. Cano, M. A., Schwartz, S. J., Castillo, L. G., Unger, J. B., Huang, S., Zamboanga, B. L., et al. (2016). Health risk behaviors and depressive symptoms among Hispanic adolescents: Examining acculturation discrepancies and family functioning. Journal of Family Psychology, 30, 254–265. doi: 10.1037/fam0000142.PubMedCrossRefGoogle Scholar
  4. Centers for Disease Control and Prevention. (2015). HIV Surveillance Report, 2013, 25. Retrieved from http://www.cdc.gov/hiv/library/reports/surveillance/.
  5. Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9, 233–255.CrossRefGoogle Scholar
  6. Córdova, D., Ciofu, A., & Cervantes, R. (2014a). Exploring culturally based intrafamilial stressors among Latino adolescents. Family Relations, 63, 693–706.PubMedPubMedCentralCrossRefGoogle Scholar
  7. Córdova, D., Heinze, J., Mistry, R., Hsieh, H.-F., Stoddard, S., Salas-Wright, C. P., et al. (2014b). Family functioning and parent support trajectories and substance use and misuse among minority urban adolescents: A latent class growth analysis. Substance Use and Misuse, 49, 1908–1919. doi: 10.3109/10826084.2014.935792.PubMedPubMedCentralCrossRefGoogle Scholar
  8. Córdova, D., Huang, S., Arzon, M., Freitas, D., Malcolm, S., & Prado, G. (2011). The role of attitudes, family, peer and school on alcohol use, rule breaking and aggressive behavior in Hispanic delinquent adolescents. The Open Family Studies Journal, 4(Suppl 1–M4), 38–45.PubMedPubMedCentralCrossRefGoogle Scholar
  9. Córdova, D., Huang, S., Lally, M., Estrada, Y., & Prado, G. (2014c). Do parent-adolescent discrepancies in family functioning increase the risk of Hispanic adolescent HIV risk behaviors? Family Process, 53, 348–363. doi: 10.1111/famp.12067.PubMedPubMedCentralCrossRefGoogle Scholar
  10. Córdova, D., Huang, S., Pantin, H., & Prado, G. (2012). Do the effects of a family intervention on alcohol and drug use vary by nativity status? Psychology of Addictive Behaviors, 26, 655–660. doi: 10.1037/a0026438.PubMedCrossRefGoogle Scholar
  11. De Los Reyes, A. (2011). Introduction to the special section: More than measurement error: Discovering meaning behind informant discrepancies in clinical assessments of children and adolescents. Journal of Clinical Child and Adolescent Psychology, 40, 1–9. doi: 10.1080/15374416.2011.533405.PubMedCrossRefGoogle Scholar
  12. De Los Reyes, A. (2013). Strategic objectives for improving understanding of informant discrepancies in developmental psychopathology research. Development and Psychopathology, 25, 669–682. doi: 10.1017/S0954579413000096.PubMedCrossRefGoogle Scholar
  13. De Los Reyes, A., Goodman, K. L., Kliewer, W., & Reid-Quiñones, K. (2010). The longitudinal consistency of mother-child reporting discrepancies of parental monitoring and their ability to predict child delinquent behaviors two years later. Journal of Youth and Adolescence, 39, 1417–1430. doi: 10.1007/s10964-009-9496-7.PubMedCrossRefGoogle Scholar
  14. De Los Reyes, A., & Kazdin, A. E. (2005). Informant discrepancies in the assessment of childhood psychopathology: A critical review, theoretical framework, and recommendations for further study. Psychological Bulletin, 131, 483–509. doi: 10.1037/0033-2909.131.4.483.PubMedCrossRefGoogle Scholar
  15. Ennis, S., Rios-Vargas, M., Albert, N. (2011). The Hispanic Population: 2010. 2010 Census Briefs. http://www.census.gov/prod/cen2010/briefs/c2010br-04.pdf.
  16. Farrelly, C., Córdova, D., Huang, S., Estrada, Y., & Prado, G. (2013). The role of acculturation and family functioning in predicting HIV risk behaviors among Hispanic delinquent youth. Journal of Immigrant and Minority Health, 15, 476–483. doi: 10.1007/s10903-012-9627-1.PubMedPubMedCentralCrossRefGoogle Scholar
  17. Geiser, C. (2013). Data analysis with Mplus. New York: The Guilford Press.Google Scholar
  18. Gorman-Smith, D., Tolan, P. H., Zelli, A., & Huesmann, L. R. (1996). The relation of family functioning to violence among inner-city minority youths. Journal of Family Psychology, 10, 115–129. doi: 10.1037/0893-3200.10.2.115.CrossRefGoogle Scholar
  19. Huang, S., Córdova, D., Estrada, Y., Brincks, A. M., Asfour, L. S., & Prado, G. (2014). An application of the complier average causal effect analysis to examine the effects of a family intervention in reducing illicit drug use among high-risk Hispanic adolescents. Family Process, 53, 336–347. doi: 10.1111/famp.12068.PubMedCrossRefGoogle Scholar
  20. Johnston, L. D., O’Malley, P. M., Miech, R. A., Bachman, J. G., & Schulenberg, J. G. (2015). Monitoring the future national results on adolescent drug use: Overview of key findings. Ann Arbor, MI: Institute for Social Research, The University of Michigan.Google Scholar
  21. Jung, T., & Wickrama, K. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2, 302–317. doi: 10.1111/j.1751-9004.2007.00054.x.CrossRefGoogle Scholar
  22. Kann, L., Kinchen, S., Shanklin, S. L., Flint, K. H., Kawkins, J., Harris, W. A, Zaza, S. (2014). Youth risk behavior surveillance–United States, 2013. Morbidity and Mortality Weekly Report. Surveillance Summaries, 63(SS04), 1–168. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/24918634.
  23. Kim, S. Y., Chen, Q., Wang, Y., Shen, Y., & Orozco-Lapray, D. (2013). Longitudinal linkages among parent–child acculturation discrepancy, parenting, parent–child sense of alienation, and adolescent adjustment in Chinese immigrant families. Developmental Psychology, 49, 900–912. doi: 10.1037/a0029169.PubMedCrossRefGoogle Scholar
  24. Leung, J. T., & Shek, D. T. (2014). Parent–adolescent discrepancies in perceived parenting characteristics and adolescent developmental outcomes in poor Chinese families. Journal of Child and Family Studies, 23, 200–213.PubMedCrossRefGoogle Scholar
  25. Li, W., Jaroszewski, L., & Godzik, A. (2001). Clustering of highly homologous sequences to reduce the size of large protein databases. Bioinformatics, 17, 282–283.PubMedCrossRefGoogle Scholar
  26. Little, T. D. (2013). Longitudinal structural equation modeling. New York: Guilford Press.Google Scholar
  27. Malcolm, S., Huang, S., Córdova, D., Freitas, D., Arzon, M., Jimenez, G. L., et al. (2012). Predicting condom use attitudes, norms, and control beliefs in Hispanic problem behavior youth: The effects of family functioning and parent-adolescent communication about sex on condom use. Health Education and Behavior, 40, 384–391. doi: 10.1177/1090198112440010.PubMedPubMedCentralCrossRefGoogle Scholar
  28. Marsiglia, F. F., Nagoshi, J. L., Parsai, M., & Castro, F. G. (2014). The effects of parental acculturation and parenting practices on the substance use of Mexican-heritage adolescents from Southwestern Mexican neighborhoods. Journal of Ethnicity in Substance Abuse, 13, 288–311.PubMedPubMedCentralCrossRefGoogle Scholar
  29. Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in tests of measurement invariance. The Journal of Applied Psychology, 93, 568–592. doi: 10.5465/AMBPP.2006.27182124.PubMedCrossRefGoogle Scholar
  30. Muthén, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345–368). Thousand Oaks, CA: SAGE Publications.Google Scholar
  31. Muthén, L. K. & Muthén, B. O. (1998–2012). Mplus User’s Guide (7th ed.). Los Angeles, CA: Muthén & Muthén. Retrieved from http://www.webcitation.org/6eJVvEGlw.
  32. Ohannessian, C. M. (2012). Discrepancies in adolescents’ and their mothers’ perceptions of the family and adolescent externalizing problems. Family Science, 3, 135–140. doi: 10.1080/19424620.2012.704596.PubMedPubMedCentralCrossRefGoogle Scholar
  33. Ohannessian, C. M., Lerner, R. M., Lerner, J. V., & Eye, A. Von. (2000). Adolescent-parent discrepancies in perceptions of family functioning and early adolescent self-competence. International Journal of Behavioral Development, 24, 362–372. doi: 10.1080/01650250050118358.CrossRefGoogle Scholar
  34. Ohannessian, C. M., Lerner, R. M., Lerner, J. V., & von Eye, A. (1995). Discrepancies in adolescents’ and parents’ perceptions of family functioning and adolescent emotional adjustment. Journal of Early Adolescence, 15, 490–516. doi: 10.1177/0272431695015004006.CrossRefGoogle Scholar
  35. Pantin, H. (1996). Ecodevelopmental measures of support and conflict for Hispanic youth and families. Miami, FL: University of Miami School of Medicine.Google Scholar
  36. Patterson, J. M. (2002). Integrating family resilience and family stress theory. Journal of Marriage and Family, 64, 349–360.CrossRefGoogle Scholar
  37. Pew Research Center. (2015). Modern immigration wave brings 59 million to U.S., driving population, growth and change through 2065: Views of immigrations impact on U.S. society mixed. Washington, DC. Retrieved from http://www.pewhispanic.org/2015/09/28/ modern-immigration-wave-brings-59-million-to-u-s-driving-population-growth-and-change-through-2065/.
  38. Prado, G., Córdova, D., Huang, S., Estrada, Y., Rosen, A., Bacio, G. A., et al. (2012). The efficacy of Familias Unidas on drug and alcohol outcomes for Hispanic delinquent youth: Main effects and interaction effects by parental stress and social support. Drug and Alcohol Dependence, 125(SUPPL.1), S18–S25. doi: 10.1016/jdrugalcdep.2012.06.011.PubMedPubMedCentralCrossRefGoogle Scholar
  39. Prado, G., Huang, S., Córdova, D., Malcolm, S., Estrada, Y., Cano, N., & Brown, C. H. (2013). Ecodevelopmental and intrapersonal moderators of a family based preventive intervention for Hispanic youth: A latent profile analysis. Prevention Science, 14, 290–299. doi: 10.1007/s11121-012-0326-x.PubMedPubMedCentralCrossRefGoogle Scholar
  40. Reynolds, E. K., MacPherson, L., Matusiewicz, A. K., Schreiber, W. M., & Lejuez, C. W. (2011). Discrepancy between mother and child reports of parental knowledge and the relation to risk behavior engagement. Clinical Child and Adolescent Psychology, 40, 67–79. doi: 10.1080/15374416.2011.533406.CrossRefGoogle Scholar
  41. Schwartz, S. J., Unger, J. B., Baezconde-Garbanati, L., Benet-Martínez, V., Meca, A., Zamboanga, B. L., et al. (2015). Longitudinal trajectories of bicultural identity integration in recently immigrated Hispanic adolescents: Links with mental health and family functioning. International Journal of Psychology, 50, 440–450. doi: 10.1002/ijop.12196.PubMedCrossRefGoogle Scholar
  42. Schwartz, S. J., Unger, J. B., Baezconde-Garbanati, L., Zamboanga, B. L., Córdova, D., Lorenzo-Blanco, E. I. et al. (In press.). Testing the parent-adolescent acculturation discrepancy hypothesis: A five-wave longitudinal study. Journal of Research on Adolescence. http://dx.doi.org/10.1111/jora.12214.
  43. Schwartz, S. J., Unger, J. B., Des Rosiers, S. E., Huang, S., Baezconde-Garbanati, L., & Lorenzo-Blanco, E. I. (2012). Substance use and sexual behavior among recent Hispanic immigrant adolescents: Effects of parent-adolescent differential acculturation and communication. Drug and Alcohol Dependence, 125(Suppl), S26–S34. doi: 10.1016/j.drugalcdep.2012.05.020.PubMedPubMedCentralCrossRefGoogle Scholar
  44. Schwartz, S. J., Unger, J. B., Des Rosiers, S. E., Lorenzo-Blanco, E. I., Zamboanga, B. L., Huang, S., et al. (2013). Domains of acculturation and their effects on substance use and sexual behavior in recent Hispanic immigrant adolescents. Prevention Science, 15, 385–396. doi: 10.1007/s11121-013-0419-1.CrossRefGoogle Scholar
  45. Smokowski, P. R., Rose, R., & Bacallao, M. L. (2008). Acculturation and Latino family processes: How cultural involvement, biculturalism, and acculturation gaps influence family dynamics*. Family Relations, 57, 295–308.CrossRefGoogle Scholar
  46. Smokowski, P. R., Rose, R. A., Evans, C. B. R., Cotter, K. L., Bower, M., & Bacallao, M. (2014). Familial influences on internalizing symptomatology in Latino adolescents: An ecological analysis of parent mental health and acculturation dynamics. Development and Psychopathology, 26, 1191–1207. doi: 10.1017/S0954579414000960.PubMedCrossRefGoogle Scholar
  47. Stuart, J., & Jose, P. E. (2012). The influence of discrepancies between adolescent and parent ratings of family dynamics on the well-being of adolescents. Journal of Family Psychology, 26, 858–868. doi: 10.1037/a0030056.PubMedCrossRefGoogle Scholar
  48. Szapocznik, J., & Coatsworth, J. D. (1999). An ecodevelopmental framework for organizing the influences on drug abuse: A developmental model of risk and protection. In M. D. Glantz & C. R. Hartel (Eds.), Drug abuse: Origins & interventions (pp. 331–366). Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  49. Tello, J., Cervantes, R. C., Córdova, D., & Santos, S. M. (2010). Joven noble: Evaluation of a culturally focused youth development program. Journal of Community Psychology, 38, 799–811. doi: 10.1002/jcop.20396.CrossRefGoogle Scholar
  50. Tolan, P. H., Gorman-Smith, D., Huesmann, L. R., & Zelli, A. (1997). Assessment of family relationship characteristics: A measure to explain risk for antisocial behavior and depression among urban youth. Psychological Assessment, 9, 212–223. doi: 10.1037/1040-3590.9.3.212.CrossRefGoogle Scholar
  51. Tolvanen, A. (2007). Latent growth mixture modeling: A simulation study. P. Koskela (Ed.). Finland: University of Jyväskylä. Retrieved from http://urn.fi/URN:ISBN:951-39-2971-8.
  52. Unger, J. B., Ritt-Olson, A., Wagner, K. D., Soto, D. W., & Baezconde-Garbanati, L. (2009). Parent-child acculturation patterns and substance use among Hispanic adolescents: A longitudinal analysis. Journal of Primary Prevention, 30, 293–313. doi: 10.1007/s10935-009-0178-8.PubMedPubMedCentralCrossRefGoogle Scholar
  53. U.S. Census Bureau. (2014). U.S. Census Quick Facts: United States. Retrieved from http://www.webcitation.org/6eJOgCRPv.
  54. Wang, C. P., Hendricks Brown, C., & Bandeen-Roche, K. (2005). Residual diagnostics for growth mixture models: Examining the impact of a preventive intervention on multiple trajectories of aggressive behavior. Journal of the American Statistical Association, 100(471), 1054–1076.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • David Córdova
    • 1
  • Seth J. Schwartz
    • 2
  • Jennifer B. Unger
    • 3
  • Lourdes Baezconde-Garbanati
    • 3
  • Juan A. Villamar
    • 4
  • Daniel W. Soto
    • 3
  • Sabrina E. Des Rosiers
    • 5
  • Tae Kyoung Lee
    • 2
  • Alan Meca
    • 2
  • Miguel Ángel Cano
    • 6
  • Elma I. Lorenzo-Blanco
    • 7
  • Assaf Oshri
    • 8
  • Christopher P. Salas-Wright
    • 9
  • Brandy Piña-Watson
    • 10
  • Andrea J. Romero
    • 11
  1. 1.University of MichiganAnn ArborUSA
  2. 2.University of Miami Miller School of MedicineMiamiUSA
  3. 3.University of Southern California Keck School of MedicineLos AngelesUSA
  4. 4.Northwestern University Feinberg School of MedicineChicagoUSA
  5. 5.Barry UniversityMiamiUSA
  6. 6.Florida International UniversityMiamiUSA
  7. 7.University of South CarolinaColumbiaUSA
  8. 8.University of GeorgiaAthensUSA
  9. 9.Boston UniversityBostonUSA
  10. 10.Texas Tech UniversityLubbockUSA
  11. 11.University of ArizonaTucsonUSA

Personalised recommendations