Social Worker Perceptions of Trauma-Informed Schools: Mixed-Method Analysis of School Practices, Policies, and Climate
Abstract
The School Community, Culture, and Climate (S3C) Special Interest Group is excited to announce that we will be hosting a webinar, featuring our 2024 recipient of the Outstanding Dissertation in the Field of School Climate Award, Dr. Kate Watson. Kate Watson, PhD is a graduate of the UCLA Luskin School of Public Affairs. She uses qualitative, quantitative, and mixed methods to explore trauma-informed approaches in child welfare, nonprofits, and schools. A passionate advocate for children and youth, Kate has served on the boards of Child Advocates of Silicon Valley and the Los Angeles Junior Chamber of Commerce, as chair of the LAJCC Foundation, and as a court-appointed special advocate (CASA) for multiple foster youth.
This dissertation examined trauma-informed schools from the perspective of school social workers, addressing the limited empirical research on whole-school trauma-informed approaches. Using survey data from 538 social workers, Studies 1 and 2 identified key practices, policies, and climate characteristics associated with schools perceived as trauma informed. Study 1 found that trauma training and resources for secondary traumatic stress predicted trauma-informed identification, while Study 2 showed that safer, strengths-based, equitable, and collaborative school climates were also key indicators. Study 3, based on interviews with 20 social workers, revealed that trauma-informed schools are understood as holistic, systemic environments that extend beyond training or clinical services. Collectively, the findings highlight the need for social workers to lead institutional change, address inequities, and support support sustainable trauma-informed practices in schools.
The video can be viewed here:
Francis Huang
Professor / SIG Program Chair
My research interests include school climate, school violence, and threat assessment. My methodological interests focus on the analysis of clustered data (multilevel modeling).