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