Predictors of depression in African American men and their implications for community and individual focused interventions.

Depression;Men;African-American;National Survey of American Life;Community interventions;Individual-focused interventions

Michael A. Robinson

University:University of Louisville

Department:Social Work

关键词: Depression;    Men;    African-American;    National Survey of American Life;    Community interventions;    Individual-focused interventions;   

Others  :  https://ir.library.louisville.edu/cgi/viewcontent.cgi?article=2218&context=etd

美国|英语

来源: The Universite of Louisville's Institutional Repository

【 摘 要 】

Background: In any given year depression affects as many as 121 million people worldwide and 20 percent or 19 million people in the U.S. suffer from at least one episode of depression during their lifetime. In the U.S., depression has a substantial impact on the economy. It is estimated that $17 billion dollars in salary and/or equivalent compensation is lost due to missing work days, caused by major depression. Depression is considered a highly prevalent condition that can lead to significant functional impairments, such as absenteeism and work productivity and problems with activities of daily living. This study focuses on depression in African-American men, and addresses three research questions. What are the differences in the magnitude and severity of depression among African-American (AA) and non-Latino white (nLw) males and females? What variables in the Socio Determinants of Health model predict depression in African-American males? Given the research results, what types of intervention could prevent or lessen the impact of depression in African-American males? Methods: A multivariate analytical model was developed to answer research questions posed by this study. The general purpose of multiple regressions was to identify relationships between independent variables and the dependent variable, depression in African-American males. The study used a nationally representative sample from the National Survey of American Life dataset and used a revised Social Determinants of Health model as a conceptual framework to guide the analysis. Results: Several steps were taken to select which predictor variables were significant in building a multiple regression model to predict depression in African-American males. In the end, 23 predictor variables were identified and these variables explained approximately 18.1 percent of the variance in the depression score. The top five predictors are distress, being African American, everyday discrimination, and hopelessness and mastery. This informs the reader that these variables are the top five predictors of depression. Moreover, regression results showed that the amount of variance explained in the dependent variable, depression, by each of the three sections of the Social Determinants of Health model, were: socioeconomic & structural determinants (1.1%), the community context (5%), and the individual level factors (12%). The final chapter addresses the implications of these findings for policy and programmatic interventions.