Abstract: (WITHDRAWN) Maternal Caregiver Typologies and Adverse Community Exposures in African American Adolescents Living in Urban Public Housing (Society for Social Work and Research 25th Annual Conference - Social Work Science for Social Change)

All live presentations are in Eastern time zone.

559P (WITHDRAWN) Maternal Caregiver Typologies and Adverse Community Exposures in African American Adolescents Living in Urban Public Housing

Schedule:
Tuesday, January 19, 2021
* noted as presenting author
Margaret Lombe, PhD, Associate Professor, Boston College, Chestnut Hill, MA
Von Nebbitt, PhD, Associate Professor, Washington University in Saint Louis, St. Louis, MO
Mansoo Yu, PhD, Associate Professor, University of Missouri-Columbia, Columbia, MO
Takashi Amano, MSW, Assistant Professor, Washington University in Saint Louis, St. Louis, MO
Chrisann Newransky, PhD, Assistant Professor, Adelphi University, Garden City, NY
Background and Purpose: The maternal caregiver plays an important role in the way that their adolescent children feel and think. An encouraging and supervising maternal caregiver may help youth living in tough neighborhoods survive day-to-day urban hassle. Due to American’s legacy of residential segregation, African American youth are disproportionately over-represented in poor racially segregated neighborhoods, like urban public housing neighborhoods. Consequently, these youth experience greater adverse community exposures (e.g., violence, deviant peer groups, and urban hassle) than their White and LatinX counterparts. An involved and informed maternal caregiver may help their adolescent child navigate tough environments. This study attempts to assess and explicate how, or whether, various classes of maternal caregivers are associated with adolescents’ adverse community exposures such as community hassle, deviant peer groups and violence. Two questions are advanced: 1) What are the latent classes of maternal caregiver types, if any, based upon youths’ self-reports on their mothers’ monitoring and encouraging behaviors? 2) To what extent are youth correctly classified into maternal caregiver classes based upon their self-reported child / parent relationship, adverse community and household exposures?

Methods: Using a sample of 375 African American youth (average age = 15.5; SD=2.2) recruited from public housing in three large US cities, this paper attempts to rectify the observed gap in knowledge by assessing how variations in maternal caregiver types are associated with their child’s perceived child / parent relationship, and their child's adverse community exposures. We use Latent Profile Analysis to identify various maternal caregiver classes. Then we used One-way ANOVA and a Multinominal Logistic Regression to assess means difference across classes and to assess whether or not youth could be correctly classified into maternal caregivers’ classes, respectively.

Results: The overall multinomial logistic regression model was significant, explaining 39% of the variance in the model (X2 = 157.37(24); R2 = .398; p < .000). The High-High group served as the reference group for this analysis. We identified three maternal caregiver classes, and correctly classified 87% of the youth into caregiver classes. Results also suggests that youth in higher types of maternal caregivers (i.e., highly supportive and highly monitored) were associated with higher parent / child relationship and lower community violence. Implications for practice are discussed.

Conclusion & Implications: These findings highlight the critical role maternal caregivers play in buffering against negative peer influences and reducing negative community exposures in their adolescent children in public housing. Within this dyad, maternal encouragement and monitoring serve as protective factors that enhance youth outcomes. Practitioners working with maternal caregivers in this environment may need to develop context-specific training and interventions to further enhance encouragement behaviors. Attention could be devoted to understanding barriers to maternal monitoring in resource-constrained environments.