Centering Communities of Color in the Modernization of a Public Health Survey System: Lessons from Oregon

Context: Public health survey systems are tools for informing public health programming and policy at the national, state, and local levels. Among the challenges states face with these kinds of surveys include concerns about the representativeness of communities of color and lack of community engagement in survey design, analysis, and interpretation of results or dissemination, which raises questions about their integrity and relevance. Approach: Using a data equity framework (rooted in antiracism and intersectionality), the purpose of this project was to describe a formative participatory assessment approach to address challenges in Oregon Behavioral Risk Factor Surveillance System (BRFSS) and Student Health Survey (SHS) data system by centering community partnership and leadership in (1) understanding and interpreting data; (2) identifying strengths, gaps, and limitations of data and methodologies; (3) facilitating community-led data collection on community-identified gaps in the data; and (4) developing recommendations. Results: Project team members’ concerns, observations, and critiques are organized into six themes. Throughout this engagement process, community partners, including members of the project teams, shared a common concern: that these surveys reproduced the assumptions, norms, and methodologies of the dominant (White, individual centered) scientific approach and, in so doing, created further harm by excluding community knowledges and misrepresenting communities of color. Conclusions: Meaningful community leadership is needed for public health survey systems to provide more actionable pathways toward improving population health outcomes. A data equity approach means centering communities of color throughout survey cycles, which can strengthen the scientific integrity and relevance of these data to inform community health efforts

Engaging Antiracist and Decolonial Praxis to Advance Equity in Oregon Public Health Surveillance Practices.

Public health surveillance and data systems in the US remain an unnamed facet of structural racism. What gets measured, which data get collected and analyzed, and how and by whom are not matters of happenstance. Rather, surveillance and data systems are productions and reproductions of political priority, epistemic privilege, and racialized state power. This has consequences for how communities of color are represented or misrepresented, viewed, and valued and for what is prioritized and viewed as legitimate cause for action. Surveillance and data systems accordingly must be understood as both an instrument of structural racism and an opportunity to dismantle it. Here, we outline a critique of standard surveillance systems and practice, drawing from the social epidemiology, critical theory, and decolonial theory literatures to illuminate matters of power germane to epistemic and procedural justice in the surveillance of communities of color. We then summarize how community partners, academics, and state health department data scientists collaborated to reimagine survey practices in Oregon, engaging public health critical race praxis and decolonial theory to reorient toward antiracist surveillance systems. We close with a brief discussion of implications for practice and areas for continued consideration and reflection

Are ecstasy users biased toward endorsing somatic mental health symptoms? Results from a general community sample

Rationale: Whether the reported poorer mental health of ecstasy users is due to a bias in endorsement of somatic symptoms has been postulated, but rarely examined. Objectives: The purpose of this study is to investigate whether levels of ecstasy use were associated with differential probabilities of endorsing somatic mental health symptoms. Methods: Current ecstasy users aged 24-30 years (n∈=∈316) were identified from a population-based Australian study. Measures included frequency of ecstasy, meth/amphetamine, and cannabis use and the Goldberg anxiety/depression symptom scales. Results: Multiple indicator, multiple cause models demonstrated no bias towards endorsing somatic symptoms with higher ecstasy use, both with and without adjustment for gender, cannabis, and meth/amphetamine use. Conclusions: Other studies using alternate measures of mental health should adopt this approach to determine if there is a bias in the endorsement of somatic symptoms among ecstasy users.</p