16 High support, higher risks? Identifying and exploring how social risk factors influence the support needs of youth with developmental disabilities

Abstract Background The link between the social determinants of health and children's health outcomes is well-known, with certain factors serving as protective shields while others heighten risk, but their impact specifically on transitional-aged youth with developmental disabilities remains understudied. Furthermore, no studies have examined how these risk factors affect their access to health and social services, nor delineate the type of support these youth require. This is a critical area of study, as disruptions or inadequacies in the transition to adult care can adversely affect their long-term health outcomes and overall well-being. Objectives The study aimed to assess the association between specific social risk factors and the type and level of support needed for youth with developmental disabilities transitioning to adult care. Design/Methods This case-control study included participants aged 14-25 with developmental disabilities that were seen at a transitional-aged youth clinic in Toronto. Data was collected in 2022-2023 through intake surveys and chart reviews, focusing on their demographics, the clients’ support needs, and the services received. Participants were grouped into low, high, or crisis-level of support based on the amalgamation of the 1) hours spent 2) support format and 3) type of referrals they received. The association between social risk factors and the degree of support were then analyzed using multivariate logistical regression on Jamovi software. Results The study included 50 participants, with 30.6% requiring crisis-level interventions, 38.8% needing high-level support, and 30.6% categorized as low-level support. Hierarchical regression analysis found that family income significantly influenced support levels, with unstable income greatly increasing the odds of higher support needs (OR 49.16, p < 0.05). Owning a home was linked to lower odds of needing high support compared to subsidized housing (OR 8.96, p < 0.05). Factors like employment, ethnicity, English as a second language, and education showed varying but non-significant associations. Conclusion These findings underscore that socioeconomic variables like income and housing intersect to shape the level of support required for families of youth with developmental disabilities. Targeted interventions focusing on these areas could help reduce the need for crisis-level interventions as these youth transition to adult care.