SEARCHing for Solutions: Applying a Novel Person-Centered Analysis to the Problem of Dropping Out of Preventive Parent Education

Abstract

Behavioral parent training is an effective intervention for many child behavior problems; however, low parent attendance and premature termination of intervention have been chronic barriers to successful implementation. Socioeconomic factors, demographic characteristics, social support, stressful life events, and parental depression have all been identified in prior research as risk factors for premature termination. The present study tested whether these risk factors were valid predictors in a targeted prevention sample using a novel methodology, a binary segmentation procedure (SEARCH), to identify meaningful subgroups within the sample. The SEARCH procedure, a person-centered approach to analysis, resulted in five mutually exclusive groups. These groups were classified based on social support and stressful life events, and group membership significantly predicted attendance at parent training. Other frequently studied predictors, such as income, were not significant predictors within this sample. The groups which were characterized by higher social support and fewer life events typically attended more sessions; however, the relationship between these risk factors was not linear and would not have been detected by many other methods of analysis. These findings both contribute to the overall literature on parent training preventions, and suggest that binary segmentation procedures, such as SEARCH, may have widespread utility in prevention research because such procedures allow for the detection of non-linear interactions between risk factors.

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Fig. 1

Notes

  1. 1.

    Some of the variables identified as risk factors could also be conceptualized as protective factors. For the present study, we treat all the identified variables as risk factors, or variables that increase the likelihood of a negative outcome (in this case, low attendance at parent training). In contrast, protective factors reduce the likelihood of the negative outcome. Protective factors typically act as moderators to reduce the effects of risk factors (Arthur et al. 2002).

  2. 2.

    Number of sessions attended (the dependent variable) was modeled as a continuous, rather than count, variable because MicrOsiris does not distinguish between count and continuous variables for the purposes of SEARCH (N. Van Eck, personal communication, August 29, 2014). Because SEARCH is not testing a linear model, the typical assumptions of normality are not required, and using a zero-bounded or zero-inflated dependent variable is no longer problematic.

  3. 3.

    Although social support and life events are uncorrelated with attendance, these two predictors emerged as the only remaining variables in a backward stepwise regression. In other words, after the effects of the other predictors are controlled for, social support and life events are correlated with attendance.

  4. 4.

    To address a separate question of how the predictors relate to willingness to attend any sessions at all, we created a categorical variable (0 = never attended; 1 = attended at least once), as recommended in Sonquist et al. (1974), and consistent with procedures used by Lochman et al. (2006). Then, we ran the SEARCH procedure, using Kendall’s tau-b as the splitting criterion. This analysis produces a different type of dependent variable, and the question asked becomes “did parents attend at all,” rather than the question we were asking (degree of dosage). For this analysis, the first split was on social support, the second on depression, then income, and finally again on social support. Although these results do not match the results of our primary analyses, this is because this analysis is addressing a different question.

References

  1. Anderson, C. M., Robins, C. S., Greeno, C. G., Cahalane, H., Copeland, V. C., & Andrews, R. M. (2006). Why lower income mothers do not engage with the formal mental health care system: Perceived barriers to care. Qualitative Health Research, 16, 926–943.

    Article  PubMed  Google Scholar 

  2. Arthur, M. W., Hawkins, J. D., Pollard, J. A., Catalano, R. F., & Baglioni, A. J. (2002). Measuring risk and protective factors for use, delinquency, and other adolescent problem behaviors the communities that care youth survey. Evaluation Review, 26, 575–601.

    PubMed  Google Scholar 

  3. Baydar, N., Reid, M. J., & Webster-Stratton, C. (2003). The role of mental health factors and program engagement in the effectiveness of a preventive parenting program for Head Start mothers. Child Development, 74, 1433–1453.

    Article  PubMed  Google Scholar 

  4. Beck, A. T., Steer, R. A., & Carbin, M. G. (1988). Psychometric properties of the Beck depression inventory: Twenty-five years of evaluation. Clinical Psychology Review, 8, 77–100.

    Article  Google Scholar 

  5. Brannan, A. M., Heflinger, C. A., & Foster, E. M. (2003). The role of caregiver strain and other family variables in determining children’s use of mental health services. Journal of Emotional and Behavioral Disorders, 11, 78–92.

    Article  Google Scholar 

  6. Cahalan, D. (1970). Problem drinkers. San Francisco: Jossey-Bass.

    Google Scholar 

  7. Chronis, A. M., Lahey, B. B., Pelham, W. E., Jr., Williams, S. H., Baumann, B. L., Kipp, H., & Rathouz, P. J. (2007). Maternal depression and early positive parenting predict future conduct problems in young children with attention-deficit/hyperactivity disorder. Developmental Psychology, 43, 70–82.

    Article  PubMed  Google Scholar 

  8. Dodge, K. A., Bates, J. E., & Pettit, G. J. (1990). Mechanisms in the cycle of violence. Science, 250, 1678–1683.

    CAS  Article  PubMed  Google Scholar 

  9. Farrington, D. P., & Tarling, R. (1985). Prediction in criminology. New York: State University of New York Press.

    Google Scholar 

  10. Hollingshead, A. B. (1975). Four factor index of social status. Unpublished manuscript. New Haven: Yale University.

    Google Scholar 

  11. Kazdin, A. E., & Whitley, M. K. (2003). Treatment of parental stress to enhance therapeutic change among children referred for aggressive and antisocial behavior. Journal of Consulting and Clinical Psychology, 71, 504–515.

    Article  PubMed  Google Scholar 

  12. Kazdin, A. E., Mazurick, J. L., & Siegel, T. C. (1994). Treatment outcome among children with externalizing disorder who terminate prematurely versus those who complete psychotherapy. Journal of the American Academy of Child and Adolescent Psychiatry, 33, 549–557.

    CAS  Article  PubMed  Google Scholar 

  13. Kazdin, A. E., Holland, L., & Crowley, M. (1997). Family experience of barriers to treatment and premature termination from child therapy. Journal of Consulting and Clinical Psychology, 65, 453–463.

    CAS  Article  PubMed  Google Scholar 

  14. Kumpfer, K. L., & Tala, K. (2009). Guide to implementing family skills training programmes for drug abuse prevention. New York: United Nations Office on Drugs and Crime.

    Google Scholar 

  15. Lochman, J. E., & The Conduct Problems Prevention Research Group. (1995). Screening of child behavior problems for prevention programs at school entry. Journal of Consulting and Clinical Psychology, 63, 549–559.

    CAS  Article  PubMed  Google Scholar 

  16. Lochman, J. E., Boxmeyer, C., Powell, N., Roth, D. L., & Windle, M. (2006). Masked intervention effects: Analytic methods for addressing low dosage of intervention. New Directions for Evaluation, 2006, 19–32.

  17. Lochman, J. E., Wells, K. C., & Lenhart, L. A. (2008). Coping power: Child Group Facilitator’s Guide. New York: Oxford University Press.

    Google Scholar 

  18. Lochman, J. E., Baden, R. E., Boxmeyer, C. L., Powell, N. P., Qu, L., Salekin, K. L., & Windle, M. (2013). Does a booster intervention augment the preventive effects of an abbreviated version of the Coping Power Program for aggressive children? Journal of Abnormal Child Psychology, 42, 1–15.

    Google Scholar 

  19. Lubke, G., & Neale, M. (2008). Distinguishing between latent classes and continuous factors with categorical outcomes: Class invariance of parameters of factor mixture models. Multivariate Behavioral Research, 43, 592–620.

    PubMed Central  Article  PubMed  Google Scholar 

  20. McKay, M., Pennington, J., Lynn, C., & McCadam, K. (2001). Understanding urban child mental health service use: Two studies of child, family, and environmental correlates. The Journal of Behavioral Health Services and Research, 28, 475–483.

    CAS  Article  PubMed  Google Scholar 

  21. Mendez, J. L., Carpenter, J. L., LaForett, D. R., & Cohen, J. S. (2009). Parental engagement and barriers to participation in a community-based preventive intervention. American Journal of Community Psychology, 44, 1–14.

    Article  PubMed  Google Scholar 

  22. Minney, J. A., & Lochman, J. E. (2010). Racial and ethnic differences in caregiver strain in targeted prevention. Kansas Conference in Clinical Child and Adolescent Psychology: Translating Research into Practice. Lawrence, Kansas.

  23. Morgan, J. N. (2005). History and potential of binary segmentation for exploratory data analysis. Journal of Data Science, 3, 123–136.

    Google Scholar 

  24. Nix, R., Bierman, K., McMahon, R., & Conduct Problems Prevention Research Group. (2009). How attendance and quality of participation affect treatment response in parent management training. Journal of Consulting and Clinical Psychology, 77, 429–438.

    PubMed Central  Article  PubMed  Google Scholar 

  25. Nock, M. K., & Kazdin, A. E. (2005). Randomized controlled trial of a brief intervention for increasing participation in parent management training. Journal of Consulting and Clinical Psychology, 73, 872–879.

    Article  PubMed  Google Scholar 

  26. Ross, J., & Bang, S. (1966). Predicting the adoption of family planning. Studies in Family Planning, 1, 8–12.

    Article  Google Scholar 

  27. Sarason, I. G., Sarason, B. R., Shearin, E. N., & Pierce, G. R. (1987). A brief measure of social support: Practical and theoretical implications. Journal of Social and Personal Relationships, 4, 497–510.

    Article  Google Scholar 

  28. Sonquist, J. A., & Morgan, J. N. (1964). The detection of interaction effects: A report on a computer program for the selection of optimal combinations of explanatory variables (No. 35). Survey Research Center, Institute for Social Research, University of Michigan.

  29. Sonquist, J. A., Baker, E. L., & Morgan, J. N. (1974). Searching for structure. Ann Arbor: Institute for Social Research.

    Google Scholar 

  30. Spoth, R., Goldberg, C., & Redmond, C. (1999). Engaging families in longitudinal preventive intervention research: Discrete-time survival analysis of socioeconomic and social–emotional risk factors. Journal of Consulting and Clinical Psychology, 67, 157–163.

    CAS  Article  PubMed  Google Scholar 

  31. Staudt, M. (2007). Treatment engagement with caregivers of at-risk children: Gaps in research and conceptualization. Journal of Child and Family Studies, 16, 183–196.

    Article  Google Scholar 

  32. The Conduct Problems Prevention Research Group. (2002). Predictor variables associated with positive fast track outcomes at the end of third grade. Journal of Abnormal Child Psychology, 30, 37–52.

    PubMed Central  Article  Google Scholar 

  33. Van Eck, N., & Van Eck, S. (2011a). MicrOsiris (Version 13). Derry: Van Eck Computer Consulting.

    Google Scholar 

  34. Van Eck, N., & Van Eck, S. (2011b). MicrOsiris: Statistical and Data Management Software System User Manual. Derry: Van Eck Computer Consulting.

    Google Scholar 

  35. Weissberg, R. P., Kumpfer, K. L., & Seligman, M. E. P. (2003). Prevention that works for children and youth: An introduction. American Psychologist, 58, 425–432.

    Article  PubMed  Google Scholar 

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Acknowledgments

The authors would like to thank Neil Van Eck for his review of the methodology, David Pollio for his suggestions on this research, Michael Alec Owens and Mary Margaret Popova for their careful editing, and the University of Alabama ASPECT group for their helpful comments on an earlier draft of this paper.

Conflict of Interest

The authors declare that they have no conflict of interest.

Disclosure

Dr. Lochman is a developer of the Coping Power program, and has a publishing agreement with Oxford University Press. Ms. Minney and Dr. Guadagno have no financial relationships to disclose. This research was supported by a grant from the Centers for Disease Control and Prevention (R49 CCR418569).

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Correspondence to Jessica A. Minney.

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Minney, J.A., Lochman, J.E. & Guadagno, R.E. SEARCHing for Solutions: Applying a Novel Person-Centered Analysis to the Problem of Dropping Out of Preventive Parent Education. Prev Sci 16, 621–632 (2015). https://doi.org/10.1007/s11121-014-0526-7

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Keywords

  • Cluster-type analyses
  • Binary segmentation
  • Parent training preventions
  • Person-centered analysis