Direct and Modifying Influences of Selected Risk Factors on Pre-Adoption Functioning and Post-Adoption Adjustment

Background and Purpose: Adoption disruption is closely associated with higher levels of externalizing behaviors (Rosenthal & Groze, 1991). Researchers have identified several pre-adoption risk factors that adversely influence adoption outcome, such as prenatal drug exposure, gender, experience of sexual abuse and number of placements (Gibbs, Barth & Houts, 2005; Hauggard & Hazan, 2003). Prenatal drug exposure is especially value-laden and adoption research has tended to focus on illicit drugs to the exclusion of alcohol and tobacco. This research provided the opportunity to fill that gap by examining the influence of alcohol, tobacco, and other drug (ATOD) exposure on children's pre-adoption functioning (PAF) and post-adoption adjustment (PAA). Moreover, research has focused on the individual influences of risk factors, although they do not occur in isolation and individually are rarely directly responsible for any specific outcome (Seifer, Sameroff & Baldwin, 1992). A cumulative risk approach was used in recognition of this inter-relatedness. This study then examined whether the above identified risk factors, individually and cumulatively, predict outcome and modify the relationship between PAF and PAA.

Methods: Data were collected from a longitudinal survey of adoptive parents from Florida's child welfare system. The sample (n=636) was limited to respondents who answered “yes” or “no” to a prenatal ATOD-exposure item. Structural Equation Modeling was chosen because it allowed for analysis of robust latent variables, better utilizing the data. Those developed for this study were the measure of pre-adoption functioning (Chronbach's alpha =.83) and the ATOD risk index (Chronbach's alpha =.76). Post-adoption functioning was measured with the Child Behavior Checklist school-age version externalizing scale.

Results: Alcohol and tobacco were the most commonly used drugs by birth mothers (alcohol 79%, tobacco 54%). Prenatal ATOD exposure directly effected pre-adoption functioning (÷2[8] = 7.52, p =.48), but did not significantly influence post-adoption adjustment (÷2[2] = 12.09, p =.002). Moreover, the association between PAF and PAA was so well-fitting that with one exception, the addition of risk factors, individually and cumulatively, did not improve model fit. The behavioral, educational, and emotional indicators of PAF predicted behavioral outcome (PAA) (÷2[2] =.70, p =.70) better than any single risk factor or combination thereof, except for the cumulative moderation model that included all four risk factors.

Conclusions and Implications: This study bridges adoption, child development, and addiction research and attempts to illuminate the role played by individual and cumulative risk factors in predicting and modifying child adoption outcomes. Practitioner attempts to find suitable adoptive families for at-risk children are complicated by popular, albeit largely unfounded, biases, especially about prenatal ATOD exposure. This study adds to the body of knowledge that recognizes that the presence of individual risk factors is not sufficient in itself to predict negative outcomes. Increased awareness of this, along with appreciation for the cumulative interaction of these influences, may help practitioners and policy-makers develop more effective interventions and policies. Increased practitioner and public education is needed to reduce the stigma associated with adoption of children exposed to risk, and to trumpet the positive adoption outcomes that occur everyday.