Abstract: Community Safety Solutions for Safer Neighborhoods: A Case Study of the California Bay Area (Society for Social Work and Research 30th Annual Conference Anniversary)

Community Safety Solutions for Safer Neighborhoods: A Case Study of the California Bay Area

Schedule:
Friday, January 16, 2026
Marquis BR 12, ML 2 (Marriott Marquis Washington DC)
* noted as presenting author
Leyi (Joy) Zhou, PhD student, University of California, Berkeley, CA
Amy Lam, PhD, Chief Program Strategist, Korean Community Center of the East Bay, San Leandro, CA
Dana Kurlander, MS, Advocacy and Impact Manager, Korean Community Center of the East Bay, San Leandro, CA
Julian Chun-Chung Chow, PhD, Hutto-Patterson Charitable Foundation Professor, University of California, Berkeley, CA
Background and Purpose:

Since COVID-19, reports of community violence—such as robbery, hate crimes, discrimination, and abuse—have increased across the Bay Area in California. Socioeconomically marginalized groups, including immigrants, non-English speakers, and racial minorities such as Asian, Black, and Latine communities, along with adolescents and older adults, have been disproportionately affected. This study examines community residents’ exposure to violence since 2022, their personal sense of safety, and their preferences for solutions to violence. With the introduction of the Healthy Places Index (HPI), we were curious how factors of race, language and HPI might differ in terms of individuals’ selection of community-based solutions to prevent future violence.

Methods:

This study draws on survey data collected by Alameda County RICE (Refugee and Immigrant Collaborative for Empowerment). Led by the Korean Community Center of the East Bay, seven RICE agencies surveyed adults from diverse communities in 13 languages. Binomial logistic regression was used to assess how participant characteristics influenced solution selection. Dependent variables include 10 binary indicators representing the most frequently selected strategies across six domains: economic stability, neighborhood conditions, political engagement, law enforcement, education, and social support. Independent variables include the Healthy Places Index (HPI), age, gender, English proficiency, and race/ethnicity.

Results:

707 Alameda County residents aged 18+ participated in the study. Findings revealed that the Healthy Places Index (HPI), age, language proficiency, and race had differential effects on preferences for preventing community violence. Residents in lower-resourced neighborhoods—those ranked in the bottom 50% statewide (HPI 0–50%)—were more likely to select “More police” (OR = 1.72, p = .047) and “Fewer guns and drugs on the street” (OR = 1.90, p = .023), compared to those in higher-resourced areas (HPI 75–100%). Individuals aged 60–74 were more likely to support “More police” (OR = 1.92, p = .009) and less likely to support “More mental health services” (OR = 0.35, p < .001). Respondents don’t speak English were less likely to support community education solutions such as “Learn about your rights as an immigrant” (OR = 0.54, p = .010) and “Teach about discrimination and hate crimes” (OR = 0.29, p < .001). Compared to White respondents, Black and Tongan respondents were significantly less likely to support “Fewer guns and drugs on the street” (Black: OR = 0.20, p = .007; Tongan: OR = 0.25, p = .030).

Conclusions and Implications:

In addition to factors such as race, language, and age, this study highlights how neighborhood conditions—shaped by structural inequities and racism—influence the types of solutions communities seek. Residents experiencing the highest levels of violence and the fewest resources were more likely to support direct interventions, such as reducing the presence of guns and increasing police presence. These findings suggest that policymakers should consider proximity to violence as a key factor shaping residents’ preferred safety strategies and prioritize building stronger relationships with under-resourced communities. Future research should examine the interaction between the Healthy Places Index (HPI) and sociodemographic factors such as race and age.