The Hidden Majority: Dual-Factor Mental Health Profiles Among Help-Avoidant University Students.

Unmet social needs such as food and housing insecurity are well-known contributors to poor child physical and mental health. In 2016, the American Academy of Pediatrics recommended social risk screening as a routine part of pediatric care. In the decade since, data collected from clinical screeners asking families about unmet needs are increasingly used for patient risk stratification and referral. Many hospital systems have developed robust screening protocols which, when implemented successfully, connect at-risk families with tailored resources and supports. Emerging evidence suggests that these programs may also have health benefits for children and caregivers. However, in practice, implementing screeners is often challenging. Providers report time constraints, workflow disruptions, and concerns about unintentional harm to patient relationships. In addition, evidence from adult clinical practice suggests that non-English-speaking patients are less likely to be screened than their peers and that screening rates differ by patient race and ethnicity. These barriers limit the reach of screening. One proposed solution is to utilize area-level measures – composite indices that summarize neighborhood conditions for small geographic units such as census tracts or block groups – to identify at-risk individuals based on residential address. These indices typically combine data on income, employment, education, housing, and related factors into a single score that can be linked to a patient’s electronic health record. While originally designed to measure neighborhood disadvantage and structural inequities, area-level measures are increasingly gaining attention in clinical spaces as potential proxies for individual risk. In theory, area-level risk indices could be used either as primary screeners (i.e., as the main indicator of social risk exposure) or as pre-screens (i.e., to determine which families should receive a primary screener). In this way, area-level measures might (1) circumvent the need for individual-level screening, (2) reduce the number of screens conducted in busy clinic settings, or (3) allow health systems to implement screening only at clinics located in high-need areas.