Abstract: Predictors of School and/or Work Connection Trajectories Among U.S. Young Adults Experiencing Low-Incomes (Society for Social Work and Research 30th Annual Conference Anniversary)

630P Predictors of School and/or Work Connection Trajectories Among U.S. Young Adults Experiencing Low-Incomes

Schedule:
Saturday, January 17, 2026
Marquis BR 6, ML 2 (Marriott Marquis Washington DC)
* noted as presenting author
Ashley N. Palmer, PhD., Assistant Professor, Texas Christian University, TX
Mary Collins, A.M., PhD, Professor, Social Welfare Policy, Boston University, Boston, MA
John Connolly, PhD, Manager, University of Texas at Arlington, Arlington, TX
Deidre Potter, Graduate Research Assistant, Texas Christian University, Fort Worth, TX
Background and Purpose: In the United States, nearly 12.6% of young people ages 16 to 24 are neither enrolled in school nor working. This disconnection, particularly over the long term, is known to have negative effects on well-being. An annual estimate reflects connection at a single time point although research had indicated that young adults have varied connections to school and/or work during the transition into adulthood. One approach to support young adults with low incomes is to provide education, training, and job-related services through career pathways programs. Currently, we know little about whether having access to career pathways programs is related to consistent connection to school and/or work over time, particularly when controlling for covariates. This study addresses the research question: When controlling for other factors, is having access to a career pathways program related to trajectories of connection to school and/or work among young adults experiencing low-income?

Methods: The study utilized longitudinal data from the Pathways for Advancing Careers and Education (PACE) evaluation to understand factors related to connection to school and/or work trajectories across a three-year period among young adults with low-incomes. First, we used an unconditional growth mixture model to estimate latent classes. Then, we held those classes fixed and regressed class membership on having access to a career pathways program, while controlling for factors at baseline (e.g., age group, assigned sex, use of public assistance programs, life challenges, educational attainment and working status, social support, depressive symptoms). Missing data was handling using listwise deletion. Our analysis included 3,767 young adults aged 18 to 34 at baseline.

Results: We selected a 7-class model based on fit statistics and practical usefulness; the connection to school and/or work could be broadly described as “consistent connection” (largest class), “variable connection” which groups two classes with dips in connection that were largely connected by the third year, “consistent disconnection,” “initial disconnection, later connection” and “initial connection, later disconnection” which captured patterns for the two smallest classes. We used the “consistent connection” class as the reference group. There were variations in the socio-demographic factors associated with being assigned to each class. For example, those who had a job at baseline were more likely to be in the “consistent connection” class. Being offered the opportunity to participate in career pathways programs that provided additional supports was significantly related to being assigned to trajectories of connection to school and/or work that were more variable than consistent.

Conclusions and Implications: The findings demonstrate a need for more nuanced understanding of how workforce development programs can support career pathway development among young adults. Covariates identify some of the nuance to guide intervention. Future research should consider how local economic contexts and state-level policies might influence connection to school and work for young adults who experience low-incomes.