Project Title

Quantitative Evaluation of African American Men with Chronic Illnesses Using a Latent Profile Analysis

Academic department under which the project should be listed

RCHSS - Sociology & Criminal Justice

Research Mentor Name

Evelina Sterling

Abstract (300 words maximum)

Recent studies have demonstrated that African American communities have suffered a disproportionate number of COVID-19 cases and deaths. In 2020 alone, the virus reduced the life expectancy of African American men by over three years. African American men are particularly vulnerable to COVID-19 complications due to higher rates of hypertension, diabetes, obesity, and cardiovascular disease. Other factors such as distrust in medical systems and lack of health insurance further compound these disparities. To address these issues, self-management programs have been developed by applied researchers. However, these programs have not been as effective for African American men as they have been for other groups. The goal of culturally competent self-management programs is to provide healthcare professionals with adaptable tools to improve the day-to-day lives of those in need. Additionally, the COVID-19 pandemic has highlighted the need for a specific module in self-management programs that address viral hygiene. Therefore, understanding the profiles of participants to determine those who were at most risk during the COVID-19 pandemic is crucial for improving the effectiveness of self-management programs and reducing disparities. The purpose of the current project was to quantitatively evaluate the profiles of African American men with chronic conditions during the Covid-19 pandemic. In particular, this study developed profiles for participants using a latent profile analysis to determine if profiles emerged around participants attitudes, knowledge, and behaviors during the pandemic. Model comparisons showed that a 3-cluster model best fit the data. Interpretations of these clusters reveal and unique set of profiles our team named “Positive Consistency”, “Negative Consistency”, and “No Consistency” groups. Those in the “No Consistency” group were more likely to display dysfunctional cognitions, higher stress, and lower perceived health quality. However, those in the “Negative Consistency” group were more likely to display signs of objective reduced health quality. Implications are discussed.

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Quantitative Evaluation of African American Men with Chronic Illnesses Using a Latent Profile Analysis

Recent studies have demonstrated that African American communities have suffered a disproportionate number of COVID-19 cases and deaths. In 2020 alone, the virus reduced the life expectancy of African American men by over three years. African American men are particularly vulnerable to COVID-19 complications due to higher rates of hypertension, diabetes, obesity, and cardiovascular disease. Other factors such as distrust in medical systems and lack of health insurance further compound these disparities. To address these issues, self-management programs have been developed by applied researchers. However, these programs have not been as effective for African American men as they have been for other groups. The goal of culturally competent self-management programs is to provide healthcare professionals with adaptable tools to improve the day-to-day lives of those in need. Additionally, the COVID-19 pandemic has highlighted the need for a specific module in self-management programs that address viral hygiene. Therefore, understanding the profiles of participants to determine those who were at most risk during the COVID-19 pandemic is crucial for improving the effectiveness of self-management programs and reducing disparities. The purpose of the current project was to quantitatively evaluate the profiles of African American men with chronic conditions during the Covid-19 pandemic. In particular, this study developed profiles for participants using a latent profile analysis to determine if profiles emerged around participants attitudes, knowledge, and behaviors during the pandemic. Model comparisons showed that a 3-cluster model best fit the data. Interpretations of these clusters reveal and unique set of profiles our team named “Positive Consistency”, “Negative Consistency”, and “No Consistency” groups. Those in the “No Consistency” group were more likely to display dysfunctional cognitions, higher stress, and lower perceived health quality. However, those in the “Negative Consistency” group were more likely to display signs of objective reduced health quality. Implications are discussed.