The study goal was to explore the association between utilization of school-based health and wellness programming and youths' school-based developmental assets. We hypothesized that, after rigorously controlling for potential confounding student risk factors and demographic characteristics, use of school-based health and wellness services (HWS) would be positively related to school-based youth development assets.
Methods: The San Francisco Wellness Initiative, a partnership between The San Francisco Unified School District (SFUSD), The Department of Children Youth and their Families and the Department of Public Health, has been offering coordinated HWS to high schools since 2000. Services are intentionally designed to address a wide range of student needs using a public health model (i.e., offering a continuum of primary prevention to indicated intervention strategies).
The study is a secondary data analysis of the 2008-2009 SFUSD California Healthy Kids Survey (CHKS). The CHKS is the largest statewide survey of risk and protection factors among California school children. The response rate was 70%, which yielded a sample size of 9,673 students. The SFUSD population is primarily composed of Chinese (37%), Latino (21%), African-American (12%), and Caucasian (9%) students. Fifty-one percent of the student population is female, 20% are English Language Learners (ELL) and 43% receive free or reduced lunch (SFUSD, 2009).
Measures: The key dependent variable is a composite variable of youth school-based assets, reflecting caring relationships, meaningful participation, and high expectations (Austin & Kim, 2007). The primary independent variable is a dichotomous (0,1) variable, indicating whether a student reported using HWS. Control variables include dichotomous variables representing student sex and race/ethnicity, current grades, and a composite variable of health/mental health risk behaviors (alpha=.80).
Analytic Approach: Both propensity scoring method and multiple regression analyses were used to estimate the relationship between use of HWS and youth reported assets. Key controls were first used to predict use of HWS. Predicted probabilities of HWS use were then entered into regressions estimating the relationship between youth assets, use of HWS and key controls.
Results: Controlling for the underlying propensity to utilize services, students' use of HWS was positively associated with school based assets (β =.13, p ≤ .0000).
Conclusions: Given the inherent limitations of these data, including its cross-sectional nature and reliance only on observed potential confounders, these findings suggest that district and school level HWS may positively relate to youth assets and may be an important strategy to enhance student academic performance.