Preview: Next Manuscript for PHL
As with our inaugural manuscript, our subsequent white paper will undergo peer-review. Read here. We are preparing a follow-up discussion on PHL research, practice, and training. The following themes will be explored. The manuscript is expected in fall 2022 or winter 2023. In part, it will critically assess accepted approaches and practices in research on race and ethnicity that we believe to be methodologically and ethically problematic.
Systemic Racism in Society Has Major Implications for Research - Clear evidence of widespread racism in the public health economy suggests an "exposure" which most major research studies should account for, as it likely confounds study findings that cannot be controlled for simply by controlling for race in data analysis. Race is an ill-defined construct apt to measurement error. In fact, any belief in the common occurrence of racism translates as a nesting effect in statistical theory and makes many common inferential statistical tests inappropriate.
Training - The noted lack of diversity in the public health workforce is only part of the challenge facing public health training. Outdated curricula, flourishing campus racism, faculty misconduct, student mistreatment, and lack of institutional accountability are among others. An African American author currently in a PhD public health program will share his personal experiences at a top US research public university and how deep-seated racism and non-inclusive teaching negatively impacted his mental health. The discussion will also include a PHL training model for communities and students.
Race is Inherently Marked by Measurement Error - Inferential statistics assume no measurement error in reliably interpreting test results (e.g., P-value, confidence intervals, etc.) Given how race is prone to error, there arise serious, perhaps fatal, flaws in study design and analysis. Race lacks uniform interpretability and precise meaning that have major implications for research. Race is commonly measured using different categories. Further, the methodological drawbacks of collapsing race and ethnicity variables is hardly addressed in the literature. Large populations do not ascribe to a race at all. The public health literature is rife with major statistical problems related to errors in data collection and analysis on race.
Public Health Datasets Lack Sufficient Structural Measures - Many national public health datasets lack sufficient coverage of structural or community level factors that impede rich data analysis for structural-level interventions. We will explore the Behavioral Risk Factor Surveillance System (BRFSS), among others.
Unethical Research on Race and Ethnicity - We will discuss the common occurrence of unethical research involving race and ethnicity. Longstanding publicly-funded research with highly biased research questions on race and criminality, that erroneously imply a biological basis for race, and that suffer from major sources of biases (e.g., no control group, time period bias, measurement error, other threats to internal and external validity) will be examined.
Encouraging Alignment à la PHL in Research - We will provide a framework for agents within the public health economy to better align speech, philosophy, practice, research and training for greater coherence and improved effectiveness.
