Cultural and Social Identity and the Role of Insurance Status in Mental Health Service Utilization: An Exploratory Data Analysis

Abstract

The research on disparities in mental health services regarding specific cultural identities is vast and continues to grow. Previous research findings regarding cultural and social identities associated with help-seeking behaviors and mental health, have indicated age, gender, income, racial identity, and health insurance coverage as factors to consider in regard to both access and utilization. Yet, the source, manner, and resulting impact of such disparities is unclear with some scholars focusing on access, others on utilization, and still others attending to quality of services. Additionally, some disparities are framed in terms of racial and ethnic differences, while some are focused on factors such as insurance status and general mental health. The present study was an exploratory data analysis focused on the role insurance may play in mitigating or propagating disparities, particularly the intersection of insurance status with both age and gender, diagnosis and self-identified need. A nationally representative dataset was utilized, and the following research questions were proposed in an effort to expand the research base regarding disparities in mental health: 1. Is insurance status (private insurance, government insurance, or uninsured) predictive of mental health service utilization (seen within the past 12 months for anxiety or depression)? 1a. Further, is insurance status predictive of mental health service utilization when controlling for cultural variables including sex, age, race/ethnicity, self-identified need, and income-to-need ratio? 2. Is insurance status (private insurance, government insurance, or uninsured) predictive of mental health service utilization among those diagnosed with depression or anxiety in their lifetime? 2a. Further, is insurance status predictive of mental health service utilization among those diagnosed with depression or anxiety in their lifetime when controlling for cultural variables including sex, age, race/ethnicity, self-identified need, and income-to-need ratio? Contingency analysis via Pearson chi-squared test with Rao-Scott second order correction was completed exploring service utilization by gender, race/ancestry, and insurance status, respectively. Four logistic regression models were fitted using an iteratively reweighted least-squares estimation method. Logistic regression was chosen in response to the dichotomous nature of service utilization as the outcome variable. Statistical analyses failed to support unique differences in predictive ability across insurance types beyond simply being insured when additional predictors are present. The data suggest insurance status may be associated with service utilization, particularly for those with a diagnosis of depression or anxiety sometime in their life, or those with a self-identified need for service. In addressing the research questions posed, these findings reflect modest support at best for the role insurance, cultural and social factors, self-identified need, and diagnosis play in service utilization. The data indicate a previous diagnosis of depression or anxiety potentially increases the likelihood one might seek services. A discussion of the findings, limitations, and future directions for research and practice is also presented.