Social Networks and Usage of Employment and Education Support Services Among Youth Experiencing Homelessness

Background: Youth experiencing homelessness (YEH) face significant obstacles to educational achievement and employment. Typically, YEH-serving organizations such as drop-in centers and shelters offer educational and employment support services to facilitate these opportunities. However, there remains a need to understand which youth are most likely to use these services. The present study examined individual and social network factors as predictors of service usage at three drop-in centers in Los Angeles County. We utilized diffusion of innovations and social capital theories to hypothesize that centrality, network exposure, and ties to supportive adult staff members would be positively associated with earlier service usage.

Methods: Data come from a larger social network study evaluating the use of peer leaders to reduce HIV risk behaviors and promote HIV testing among YEH. Participants were 253 YEH (Mean age=21.9, SD=2.2) at three drop-in centers who completed surveys at baseline, 1-month, and 3-month follow-ups. Sociometric network data at each drop-in was collected by asking youth to name up to 10 other study participants they interacted with. Social network variables were then calculated in UCINET: In-degree (number of incoming ties) out-degree (number of outgoing ties), betweenness centrality (number of times a youth lied on the shortest path connecting two other youth), network exposure (outgoing ties to service users). Relationships with a supportive adult staff member (yes=1, no=0) were also assessed. Individual characteristics included: age, birth sex, race/ethnicity, LGBQ identity, educational attainment, housing status, drop-in, and length of time frequenting the drop-in. Self-reported usage of education and employment services were two separate binary variables (yes=1, no=0). Cross-sectional and lagged logistic regression models were used to determine whether individual and social network characteristics were associated with service usage at each wave (controlling for service usage at the prior wave).

Results: In total, 29.4%, 31.1%, and 38.6% of participants used education services at each wave. At wave 1, college education (OR=0.32), and two drop-ins (OR=0.31, OR=0.24) were associated with lower odds of service usage; housing status (OR=2.12) and in-degree (OR=1.80) were associated with higher odds of service usage. At wave 2, prior service use (4.63) and longer drop-in center usage (OR=1.67) were associated with service usage. At wave 3, prior service usage (OR=6.15), LGBQ identity (OR=6.03), and shelter/transitional living (OR=6.42) were associated with service usage. In total, 32.1%, 32.8%, and 36.0% of participants reported using employment services at each wave. At wave 1, two drop-in centers were associated with lower service usage (OR=0.35, OR=0.19). At wave 2, previous service use (OR=3.39) and LGBQ identity (OR=2.83) were associated with service usage. No predictor variables were associated with service usage at wave 3.

Conclusions: Central (popular) youth were more likely to use education support services, but not employment services. This partially supports diffusion of innovations theory, suggesting that drop-in center programs may want to consider looking to these youth as peer leaders, or focus their efforts on youth who are less central in a given network.The specific drop-in center settings are also important determinants for usage of these types of services.