Abstract: Using a Mix-Methods Approach to Understand the Health Care Experiences of a Diverse Sample of Individuals Who Experience Homelessness (Society for Social Work and Research 25th Annual Conference - Social Work Science for Social Change)

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367P Using a Mix-Methods Approach to Understand the Health Care Experiences of a Diverse Sample of Individuals Who Experience Homelessness

Schedule:
Tuesday, January 19, 2021
* noted as presenting author
Micaela Mercado, PhD, MSW, Research Associate, Arizona State University, Southwest Interdisciplinary Research Center, Phoenix, AZ
Seol Ki, PhD, Doctoral candidate, Arizona State University
Wendy Wolfersteig, PhD, Director, Arizona State University, Phoenix, AZ
Background:

Individuals who experience homelessness face significant health inequities across a range of health conditions (Gordon et al., 2019). Health care experiences is one indicator that is used to asses health disparities in the homeless population; however, this has been mainly limited to homeless adults (Omerov et al., 2020). Research is needed to advance this work across demography and the lifespan (Jones, 2016). Using a purposive sampling method, this mixed methods study aimed to understand the health care experiences of a diverse sample of individuals experiencing homelessness.

Methods:

A sub-sample (n=76) of survey and focus group data from the Maricopa County Community Health Needs Assessment was used for this study. Participants who were homeless included adolescents, young adults, women with children, veterans, and older adults from diverse racial and ethnic backgrounds. Participants who consented to the study and completed a survey and focus group received a $45 gift card and a meal. Participants answered survey questions about their physical and mental health well-being (e.g., “How would you rate your physical health?”), access to health care (e.g., “Do you have enough money to pay for health care expenses?”), community assets and barriers to health care, and quality of life. Participants in the focus groups were asked about their access to health care, barriers to health care, and community care services. Focus groups were audio recorded and transcribed verbatim. Guided by grounded theory (Strauss & Corbin, 1998), open coding and axial coding were conducted to inform theoretical connections between codes. Controlling for other variables, logistic regression analyses examined associations between demographic variables and health care experiences.

Findings:

Participants were female (41%), between 18 and 64 years old (83%), White (35%), Hispanic (16%), Black (28%), and completed high school or some college (81%). Four themes emerged from the qualitative analyses. First, participants discussed their health care experiences and the community context (i.e., discrimination). Second, participants discussed immediate healthcare needs such as access to hygienic facilities and oral health. Unmet health care needs including access to health care (i.e., providers’ attitudes, LGBTQ health services) emerged as a third theme from the analyses. The final theme participants discussed was improvements in health care they experienced. The results from the logistic regression analyses indicated that race, and age were significantly associated with health care experiences. Compared to White participants, minorities (OR=2.64) had higher odds of perceiving barriers to access health care. Older adults (OR=2.68) had increased odds of rating their physical and mental health status higher compared to adults younger than 45 years, adjusting for other variables in the model.

Conclusions and Implications:

In this study, we identified complex and varied health care experiences across a diverse group of individuals experiencing homelessness. Findings suggest there are distinctive indicators of health care experiences such as barriers to health care and health care status that vary by age and race. Such findings may contribute to prospective research that is needed to accurately represent the diverse characteristics of the homeless population for advancing health care disparities research.