Perceived racial discrimination among home health aides: Evidence from a national survey.

Lee, Doohee ; Muslin, Ivan ; Mcinerney, Marjorie 等

ABSTRACT

Home health aides are one of our essential human resources in the U.S. long-term care industry but understanding whether home health aides experience racial discrimination in the workplace and, if so, which personal/organizational factors are associated at the national level has been unnoticed. Using a nationally representative sample (n=3,377), we attempt to investigate the association between racial discrimination and personal and organizational factors. The study found the 13.5% prevalence rate of racial discrimination. The study findings from multiple regression analysis reveal that black home care aides are more likely than white aides to experience racial discrimination in the workplace, suggesting that racial disparity may be an additional barrier to our home health care industry. National chain affiliation and low income were also found to be associated with perceived racial discrimination.

INTRODUCTION

Reducing health disparity remains significant within the medical community. One of the main objectives of Healthy People 2020 is to reduce health disparity, including racial discrimination, in the U.S. (Healthy People 2020, 2011). Prior studies on human resource management (Akee & Yuksel, 2012; Hughes & Dodge, 1997) and health services (Burr, Hartman, & Matteson, 1999; Sanders-Phillips, Settles-Reaves, Walker, & Brownlow, 2009; Williams, Neighbors, & Jackson, 2003) well document evidence of various racial discrimination concerns but the current literature is unclear about racial discrimination in the level of home-care aides in the U.S.

U.S. home health services (e.g., assisting elderly and/or disabled to live independently in their homes) have been growing fast in recent years with the $77.8 billion spending in 2012. The 2010 Patient Protection and Affordable Care Act (PPACA) supports and encourages home health services to compensate for expensive nursing home services. Some studies also highlight benefits of utilizing home health services (Chae et al., 2001; Intrator & Berg, 1998; Landers, 2010; Marx, Burke, Gaines, Resnick, & Parrish, 2011). However, there is a concern about workplace performance and compensation for nearly 2 million home health aides: low income salary and unattractive employment benefits (Gleckman, 2010), the 40-75% employment turnover rate (Stonerock, 1997), and work-related injuries that may be linked to high turnover among aides (Jorgensen et al., 2009; Parsons, Dixon, Brandt, & Wade, 2004). As home health aides are projected to grow 48% from 2012 to 2022 (USDOL Bureau of Labor Statistics, 2014), it is necessary to investigate how home health aides experience in the workplace, with respect to perceived racial discrimination and the extent to which racial discrimination affects home health care organizations.

RACIAL DISCRIMINATION

Racial discrimination may be defined as unequal treatment of someone (an applicant or employee) based on a certain race or personal characteristics associated with race (The U.S. Equal Employment Opportunity Commission, 2014). Research has crossed discipline boundaries in areas as diverse as applied psychology and management, healthcare, and criminal justice to name a few. Though much of the research delving into racial discrimination in the workplace centers on empirics and metrics of violations in the employment life cycle: Elkins & Phillips (2000); Harris, Lievens, & Van Hoye (2004); Lawshe (1983); Maxwell & Arvey (1993); racial discrimination also exists as interpersonal interactions (Fox & Stallworth, 2005; Johnson & Lecci, 2003). Workplace discrimination as interpersonal interaction has been discussed in terms of racial bullying (Cortina, 2008; Fox & Stallworth, 2005). To understand discrimination as interpersonal interaction an understanding of racism is necessary.

Researchers have noted that racism has evolved from more overt to more covert or subtle manifestations (Dovidio & Gaertner, 1986; Pettigrew, 1998). Modern aversive racism combines egalitarian views and negative racial beliefs (Dovidio & Gaertner, 1986, 1991). Previous research has allowed for these innocuous, plausible explanations to justify potentially discriminatory actions (Dovidio & Gaertner, 1991). However, the underlying negative racial beliefs still remain. For example, individuals who scored high on the modern racism scale engaged in discriminatory decision making when they were given business or organizational justifications for the decisions (Brief, Dietz, Cohen, Pugh, & Vaslow, 2000). Similarly, individuals who are subtly prejudiced were more apt to be influenced by pressure to maintain a homogenous workplace (Petersen & Dietz, 2005). Another study found that while evaluators with greater negative racial attitudes did not rate potential applicants differently based on race, they did have significantly different confidence in their ratings as a result of race (Stewart & Perlow, 2001).

CONCEPTUAL FRAMEWORK

According to the theory of social stratification (e.g., ranking individuals in a hierarchy), inequality is the result of genuine social structure such as age, gender, race, and socioeconomic status (Lenski, 1966). Many studies (Carr, 2012; Muntaner, Ng, Vanroelen, Christ, & Eaton, 2013; Nazroo, 2003) have applied the social stratification theory to explain the disparity and address various race-related concerns in the medical community. The 2003 Institute of Medicine report (Smedley, Stith, & Nelson, 2003) highlights the importance of our social hierarchy along with racial disparity that may be associated with substandard quality of care in the medical community. In the present study, we specifically argue that racial discrimination, one dimension of our social structure or stratification, is the byproduct of certain organizational and personal characteristics among home health aides.

The association between personal characteristics and racial disparity is well suggested in the literature. Watson and associates (2002), whose survey examined 460 adult women, documented a direct linkage between socioeconomic status and perceived racial discrimination. Similarly another study of English-speaking American adults (n=1,659) (Ren, Amick, & Williams, 1999) concluded a correlation between self-perceived discrimination and socioeconomic status. In determining patient satisfaction with medical care (n=1,748), one study (LaVeist, Nickerson, & Bowie, 2000) reported that African American patients were more likely to report racial discrimination and mistrust. Perceived racial discrimination may be associated with depression and anxiety (Kessler, Mickelson, & Williams, 1999; Noh, Beiser, Kaspar, Hou, & Rummens, 1999). Numerous studies have also suggested a link between racial/ethnic discrimination and poor health outcomes (Williams et al., 2003), such as low birth weight in infants (Collins et al., 2000), increased risk of suicide (Burr et al., 1999; Walker, Salami, Carter, & Flowers, 2014), low-quality in surgical outcomes (Rangrass, Ghaferi, & Dimick, 2014).

Organizational characteristics may be linked to exposure to racial discrimination. Griffith and colleagues (2007) found the important role of racial disparity in a rural southern community organization. In line with institutional racism (e.g., systematic inequality grounded on race/ethnicity) (Rodriguez, 1987), substantial studies (Acevedo-Garcia, Rosenfeld, Hardy, McArdle, & Osypuk, 2013; Came, 2014; Lukachko, Hatzenbuehler, & Keyes, 2014) provide evidence of racial discrimination in the context of utilizing human resource management measures including recruitment, promotion, and evaluation within the organization.

Taken together, we postulate the following two hypotheses. First, the national prevalence rate of perceived racial discrimination among home health aides will be similar to that of other studies. Second, perceived racial discrimination will be negatively associated with organizational and personal factors.

This empirical analysis will advance the current literature body of home health care as home health aides are understudied in the literature (U.S. Department of Health & Human Services, 2004). Our findings also can be useful for many policymakers and practitioners who need to know more about workplace performance of home health aides in an effort to deliver and enhance quality of patient care in the long-term care settings. This study hence attempts to fill the research gap in the home health care industry. The main objective of this analysis is to identify personal and organizational factors in relation to perceived experience of racial discrimination among home care aides at the national level.

METHODOLOGY

Data

We analyzed secondary data for this study: the 2007 National Home Health Aide Survey (NHHAS). The NHHAS is the first and latest national probability survey of home health aides sponsored by the National Center for Health Statistics (NCHS) at the Centers for Disease Control and Prevention (CDC). The survey was conducted by phone using a computer-assisted telephone interviewing (CATI) system. This is a multistage probability sample survey. Home health aides were eligible to participate in the study if they were: (1) directly employed by the sampled agency, (2) provided assistance in activities of daily living (ADLs), including bathing, dressing, transferring, eating, and toileting. A total of 3,377 interviews of home health aides were done between September 2007 and April 2008. Of the 984 eligible agencies, 22 agencies refused to participate and 7 additional agencies were ineligible because the interviewers did not complete the survey. Of 955 agencies, 4,416 home health aide cases were sampled. Of 4,416, 137 were not eligible because of the following: (1) not employed on the sampling date, did not provide assistance with ADLs, were contract employees, were sampled in error, or were identified as ineligible during the aide interview. Of 4,279, 3,377 aides completed the survey. The overall weighted response rate was 40%. More detailed information about the sampling methods and study design is described elsewhere (Centers for Disease Control and Prevention, 2007).

Measures

In line with prior studies investigating the importance of perceived racial discrimination (Benkert, Peters, Clark, & Keves-Foster, 2006; Gonzales, Harding, Lambert, Fu, & Henderson, 2013; Hagelskamp & Hughes, 2014), we utilized a single dependent variable for the study: perceived experience of racial discrimination. Specifically, the survey asked, "In your current job have you ever been discriminated against because of race/ethnicity?" The response was categorical (1=yes, 0=no).

The following two set of variables were used as covariates in the study: organizational and personal factors. Three organizational factors are: (1) agency type (1=home health, 2=hospice, and 3=mixed), (2) ownership (1=for profit, 0=others), (3) chain-affiliation (1=chain, 0=nonchain). Personal factors included in the multivariate logistic regression analysis are: age, gender (male/female), race (whites, black, and others), education, and annual household income. Geographical areas (1=metropolitan, 2=micropolitan, 3=neither) were controlled in the regression model.

Analyses

All statistical analyses were performed using STATA 13.1 (StataCorp, 2013). We first calculated means, standard deviations, proportions and then cross-tabulated the status of racial discrimination with other aforesaid covariates to determine any statistical significance between the two comparison groups. We then conducted inferential statistics using multivariate regression analysis to estimate the association of organizational/personal characteristics with perceived discrimination. As our dependent variables are categorical (yes=1, no=0), we employed a multivariate logistic regression analysis. For logistic regression, we provided odds ratio (OR) and 95% confidence intervals (CI) of perceived racial discrimination in relation to assessed covariates. Given the NHHAS is a large national survey with the complex survey design and accurately estimating sampling variances is important (Henry, 1990; Lee & Forthofer, 2006), we used the STATA survey ('svy') estimators to correctly account for complex survey design. Using the 'vif' estimator available in STATA, we also checked for possible multicollinearity among the measured variables and there was no indication of severe multicollinearity in the analysis. We reported statistical significance at alpha level of less than 0.05.

RESULTS

Table 1 portrays sample characteristics. The majority of the sample were females (95.03%) and whites (53.3%) and the mean age was 45.63 (SD=12.07). Approximately 47% of the sample reported earning less than $30,000 per year. Most of the sample lived in metropolitan area (84.2%) and were employed in the home health agency setting (74.19%). The majority worked for the for-profit (63.28%) and non-chain affiliated organizations (70.05%). The overall prevalence rate of racial discrimination was 13.5%, and nearly 23% of black home health aides reported racial discrimination (p<.0005). Annual incomes between $20,000 and $40,000 were related to racial discrimination. Living in the metropolitan area was found to be associated with racial discrimination (90.93% vs. 82.75%, p= .039).

Table 2 displays the results of a multivariate logistic regression analysis for perceived racial discrimination in relation to organizational and personal factors. Non-chain home health agencies remained significant indicating a negative association with racial discrimination (OR=.48, p=.03). Consistent with the results of descriptive statistics shown in Table 1, ethnicity also remained significant in relation to racial discrimination, showing that black home health agents were more likely to report experiencing racial discrimination (OR=4.05, p<.001). Income is another personal factor found to predict the status of racial discrimination (OR = 1.12, p=.02). Finally, with respect to geographical areas, non-metro/micro was negatively associated with racial discrimination, suggesting that those home health aides living in metropolitan areas are more likely to report racial discrimination (OR = .22, p= .002).

DISCUSSION

The main objective of this research is twofold: (1) to estimate the perceived racial discrimination prevalence rate at the national level, and (2) to identify both personal and organizational characteristics in relation to their perceived racial discrimination among home health aides.

After adjusting geographical areas, we found the overall 13.5% perceived racial discrimination prevalence rate among home health aides. Nearly 23% of black home-care aides reported experiencing racial discrimination compared to that of 7.5% among their white counterparts. No published research explicitly documents the perceived racial discrimination prevalence rate among home care aides but our 23% rate is much lower than that of Krieger et al. (2006) whose study (n=1202 in the Greater Boston area) found 44% of their black workers reporting racial discrimination compared with 10% of the white employees.

Chain affiliation remained significant in multivariate regression in relation to perceived racial discrimination. It is unclear how and why national chain affiliation is linked to racial discrimination as no related study exists. One plausible explanation is that the status of chain affiliation was not statistically significant in a crosstab analysis (Table 1), in relation to exposure to racial discrimination but it remained significant when personal factors and geographic regions were controlled in the regression model. This suggests a certain role confounding factors play in estimating the status of perceived racial discrimination. Our finding of the association of low-income with exposure to perceived racial discrimination is in line with other studies suggesting socioeconomic disadvantage linked to ethnic inequalities in health (Hudson, Puterman, Bibbins-Domingo, Matthews, & Adler, 2013; Nancy Krieger, Rowley, Herman, & Avery, 1993). Our results also are echoed by the work of Bower et al. (2013), whose study findings suggested common racial discrimination among poor urban whites.

The present study makes one important contribution to the long-term care literature by revealing that racial discrimination exists in the home health care industry. To our knowledge, this is the first study to estimate the national racial discrimination prevalence rate and the potential link between perceived racial discrimination and organizational and personal characteristics in the context of the home health care industry.

The following study limitations must be noted. Our dependent variable is perceived experience of racial discrimination, which is subject to self-perception bias. Perceived discrimination may be altered, for example, depending on behaviors or beliefs of managers or employers. Also, our study lacks the ability to consider other related factors, such as nativity (native- vs. foreign-born), language, culture, and the type of care they provide in the workplace setting, that may play a role in determining perceived racial discrimination. Given the majority of the sample (95%) is women, the study findings may not be applicable to male home health aides. Our study is cross-sectional and cannot explain causation between perceived racial discrimination and personal and organizational factors. The 40% survey response rate is low and hence our study may not represent those who did not participate in the study. Finally, the 2006 survey data may not well represent the current practice in the context of the PPACA. Considered to be the most comprehensive health care reform legislation since 1965, the 2010 PPACA affects all stakeholders in the medical community including home health aides. Policymakers and future researchers hence may want to evaluate the impact of ObamaCare on home care aides including discriminatory policies.

POLICY IMPLICATIONS

In order to lessen the chance of racial discriminatory practices, home health care organizations might want to establish a diversity recruitment and retention plan, which is found to be well received in addressing related concerns of the nursing labor force (Gilchrist & Rector, 2007; Noone, 2008). This plan would not only establish goals for diversity recruiting, but also develop selection interview questions that could identify potential discrimination problems. Interview questions have long been used by human resource professionals to identify potential problem employees (i.e. use of stress interviews for police officers). Questions detailing discriminatory situations could be put to job applicants to detail responses.

Employees in home health care settings must learn to deal with clients and client family members as well as co-workers and managers who could potentially act in a racially discriminatory manner. In fact, the racial discrimination could be more blatant in a client's home than discrimination experienced in the workplace. Training may play an important role among health care professionals (Kirmayer, Rousseau, Guzder, & Jarvis, 2008; Sholomskas et al., 2005; Story et al., 2002) and would be a key to helping home health care employees deal with discriminatory behavior. In a recent national study of nursing and home aides (Sengupta, Ejaz, & Harris-Kojetin, 2012), the vast majority of certified nursing assistants found training to be very helpful but it was unclear whether racial discrimination was part of their training program. Behavioral training modules could be used that provide real-life situations experienced by the agency employees. Trainers could come from the agency managers or senior employees.

Reporting or grievance procedures should also be established to allow employees to deal with incidents they perceive to be racial discrimination. Timelines for reporting the incident, investigation and follow-up should be documented in policy and communicated to all managers and employees. Upper management must clearly state that discrimination of any type will not be tolerated. Penalties for violation of policy should also be specifically delineated.

Finally, considering the association between communication outcomes and perceived discrimination (Hausmann et al., 2011), communication of the policies dealing with recruitment, training and grievance reporting will be critical to minimizing discrimination in the workplace. Top management must communicate their commitment to ending discrimination while mid-level and lower level managers work to enforce the policies. Workers also need to communicate within the grievance procedure when they perceive when discrimination happens.

In conclusion, we found the 13.5% national prevalence rate of perceived racial discrimination among home health aides. Compared to whites (7.5%), black home care aides were prone to report racial discrimination (23.5%). Also, low-income aides, national chain affiliation, and residing in the metropolitan area were all found to predict exposure to racial discrimination in the home health industry. Our data provides empirical evidence that perceived racial disparity exists in the home health care industry.

REFERENCES

Acevedo-Garcia, D., Rosenfeld, L. E., Hardy, E., McArdle, N., & Osypuk, T. L. (2013). Future directions in research on institutional and interpersonal discrimination and children's health. American Journal of Public Health, 103(10), 1754-1763. doi: 10.2105/ajph.2012.300986

Akee, R., & Yuksel, M. (2012). Decreasing Effect of Skin Tone on Women's Full-Time Employment, The. Indus. & Lab. Rel. Rev., 65, 398.

Benkert, R., Peters, R. M., Clark, R., & Keves-Foster, K. (2006). Effects of perceived racism, cultural mistrust and trust in providers on satisfaction with care. Journal of the National Medical Association, 98(9), 1532-1540.

Bower, K. M., Thorpe, R. J., Jr., & LaVeist, T. A. (2013). Perceived racial discrimination and mental health in low-income, urban-dwelling whites. Int J Health Serv, 43(2), 267-280.

Brief, A. P., Dietz, J., Cohen, R. R., Pugh, S. D., & Vaslow, J. B. (2000). Just doing business: Modern racism and obedience to authority as explanations for employment discrimination. Organizational behavior and human decision processes, 81(1), 72-97.

Burr, J. A., Hartman, J. T., & Matteson, D. W. (1999). Black suicide in US metropolitan areas: An examination of the racial inequality and social integration-regulation hypotheses. Social Forces, 77(3), 1049-1080.

Came, H. (2014). Sites of institutional racism in public health policy making in New Zealand. Social Science and Medicine, 106, 214-220. doi: 10.1016/j.socscimed.2014.01.055

Carr, D. (2012). The social stratification of older adults' preparations for end-of-life health care. Journal of Health and Social Behavior, 53(3), 297-312.

Centers for Disease Control and Prevention. (2007). 2007 National Home Health Aide Survey. Retrieved from: http://www.cdc.gov/nchs/nhhas.htm#about_nhhas

Chae, Y. M., Heon Lee, J., Hee Ho, S., Ja Kim, H., Hong Jun, K., & Uk Won, J. (2001). Patient satisfaction with telemedicine in home health services for the elderly. International Journal of Medical Informatics, 61(2), 167-173.

Collins, J. W., Jr., David, R. J., Symons, R., Handler, A., Wall, S. N., & Dwyer, L. (2000). Low-income African-American mothers' perception of exposure to racial discrimination and infant birth weight. Epidemiology, 11(3), 337-339.

Cortina, L. M., & Berdahl, J. L. . (2008). Sexual harassment in organizations: A decade of research in review: Thousand Oaks, CA: Sage Publications.

Dovidio, J. F., & Gaertner, S. L. (1986). Prejudice, discrimination, and racism. New York: Academic Press.

Dovidio, J. F., & Gaertner, S. L. (1991). Changes in the expression and assessment of racial prejudice Opening Doors: Perspectives on Race Relations in Contemporary America (pp. 119-148). Tuscaloosa, AL: University of Alabama Press.

Elkins, T. J., & Phillips, J. S. (2000). Job context, selection decision outcome, and the perceived fairness of selection tests: biodata as an illustrative case. Journal of Applied Psychology, 85(3), 479.

Fox, S., & Stallworth, L. E. (2005). Racial/ethnic bullying: Exploring links between bullying and racism in the US workplace. Journal of Vocational Behavior, 66(3), 438-456.

Gilchrist, K. L., & Rector, C. (2007). Can you keep them? Strategies to attract and retain nursing students from diverse populations: best practices in nursing education. J Transcult Nurs, 18(3), 277-285. doi: 10.1177/1043659607301305

Gleckman, H. (2010). The faces of home care. Health Affairs, 29(1), 125-129.

Gonzales, K. L., Harding, A. K., Lambert, W. E., Fu, R., & Henderson, W. G. (2013). Perceived experiences of discrimination in health care: a barrier for cancer screening among American Indian women with type 2 diabetes. Womens Health Issues, 23(1), e61-67. doi: 10.1016/j.whi.2012.10.004

Griffith, D. M., Childs, E. L., Eng, E., & Jeffries, V. (2007). Racism in organizations: The case of a county public health department. Journal of community psychology, 35(3), 287-302.

Hagelskamp, C., & Hughes, D. L. (2014). Workplace Discrimination Predicting Racial/Ethnic Socialization Across African American, Latino, and Chinese Families. Cultur Divers Ethnic Minor Psychol. doi: 10.1037/a0035321

Harris, M. M., Lievens, F., & Van Hoye, G. (2004). "I think they discriminated against me": using prototype theory and organizational justice theory for understanding perceived discrimination in selection and promotion situations. International Journal of Selection and Assessment, 12(1-2), 54-65.

Hausmann, L. R., Hannon, M. J., Kresevic, D. M., Hanusa, B. H., Kwoh, C. K., & Ibrahim, S. A. (2011). Impact of perceived discrimination in health care on patient-provider communication. Medical Care, 49(7), 626.

Healthy People 2020. (2011). Healthy People 2020. Washington, DC: U.S. Department of Health and Human Services Retrieved from http://www.healthypeople.gov/2020/default.aspx.

Henry, G. (1990). Practical sampling: Sage Publications, Inc.

Hudson, D. L., Puterman, E., Bibbins-Domingo, K., Matthews, K. A., & Adler, N. E. (2013). Race, life course socioeconomic position, racial discrimination, depressive symptoms and self-rated health. Social Science & Medicine, 97, 7-14.

Hughes, D., & Dodge, M. A. (1997). African American women in the workplace: Relationships between job conditions, racial bias at work, and perceived job quality. American Journal of Community Psychology, 25(5), 581-599.

Intrator, O., & Berg, K. (1998). Benefits of home health care after inpatient rehabilitation for hip fracture: health service use by Medicare beneficiaries, 1987-1992. Archives of physical medicine and rehabilitation, 79(10), 1195-1199.

Johnson, J. D., & Lecci, L. (2003). Assessing anti-white attitudes and predicting perceived racism: The Johnson-Lecci scale. Personality and Social Psychology Bulletin, 29(3), 299-312.

Jorgensen, D., Parsons, M., Reid, M. G., Weidenbohm, K., Parsons, J., & Jacobs, S. (2009). The providers' profile of the disability support workforce in New Zealand. Health & Social Care in the Community, 17(4), 396-405. doi: 10.1111/j.1365-2524.2008.00839.x

Kessler, R. C., Mickelson, K. D., & Williams, D. R. (1999). The prevalence, distribution, and mental health correlates of perceived discrimination in the United States. J Health Soc Behav, 40(3), 208-230.

Kirmayer, L. J., Rousseau, C., Guzder, J., & Jarvis, G. E. (2008). Training clinicians in cultural psychiatry: a Canadian perspective. Academic Psychiatry, 32(4), 313-319.

Krieger, N., Rowley, D. L., Herman, A. A., & Avery, B. (1993). Racism, sexism, and social class: implications for studies of health, disease, and wellbeing. American journal of preventive medicine.

Krieger, N., Waterman, P. D., Hartman, C., Bates, L. M., Stoddard, A. M., Quinn, M. M., . . . Barbeau, E. M. (2006). Social hazards on the job: workplace abuse, sexual harassment, and racial discrimination--a study of Black, Latino, and White low-income women and men workers in the United States. Int J Health Serv, 36(1), 51-85.

Landers, S. H. (2010). Why health care is going home. New England Journal of Medicine, 363(18), 1690-1691.

LaVeist, T. A., Nickerson, K. J., & Bowie, J. V. (2000). Attitudes about racism, medical mistrust, and satisfaction with care among African American and white cardiac patients. Med Care Res Rev, 57 Suppl 1, 146-161.

Lawshe, C. (1983). A simplified approach to the evaluation of fairness in employee selection procedures. Personnel psychology, 36(3), 601-608.

Lee, E., & Forthofer, R. (2006). Analyzing complex survey data: Sage Publications, Inc.

Lenski, G. E. (1966). Power and privilege: A theory of social stratification: UNC Press Books.

Lukachko, A., Hatzenbuehler, M. L., & Keyes, K. M. (2014). Structural racism and myocardial infarction in the United States. Social Science and Medicine, 103, 42-50. doi: 10.1016/j.socscimed.2013.07.021

Marx, K. A., Burke, K. L., Gaines, J. M., Resnick, B., & Parrish, J. M. (2011). Satisfaction with Your New Home: Advantages and Disadvantages to Living in a CCRC. Seniors Housing & Care Journal, 19(1).

Maxwell, S. E., & Arvey, R. D. (1993). The search for predictors with high validity and low adverse impact: Compatible or incompatible goals? Journal of Applied Psychology, 78(3), 433.

Muntaner, C., Ng, E., Vanroelen, C., Christ, S., & Eaton, W. W. (2013). Social Stratification, Social Closure, and Social Class as Determinants of Mental Health Disparities Handbook of the Sociology of Mental Health (pp. 205-227): Springer.

Nazroo, J. Y. (2003). The structuring of ethnic inequalities in health: economic position, racial discrimination, and racism. American Journal of Public Health, 93(2), 277-284.

Noh, S., Beiser, M., Kaspar, V., Hou, F., & Rummens, J. (1999). Perceived racial discrimination, depression, and coping: a study of Southeast Asian refugees in Canada. J Health Soc Behav, 40(3), 193-207.

Noone, J. (2008). The diversity imperative: Strategies to address a diverse nursing workforce. Paper presented at the Nursing Forum.

Parsons, M., Dixon, R., Brandt, T., & Wade, D. (2004). Disability Support Services in New Zealand: The Workforce survey. Auckland, New Zealand: Ministry of Health, NZ.

Petersen, L. E., & Dietz, J. (2005). Prejudice and Enforcement of Workforce Homogeneity as Explanations for Employment Discrimination1. Journal of Applied Social Psychology, 35(1), 144-159.

Pettigrew, T. F. (1998). Intergroup contact theory. Annual review of psychology, 49(1), 65-85.

Rangrass, G., Ghaferi, A. A., & Dimick, J. B. (2014). Explaining racial disparities in outcomes after cardiac surgery: the role of hospital quality. JAMA Surg, 149(3), 223-227. doi: 10.1001/jamasurg.2013.4041

Ren, X. S., Amick, B. C., & Williams, D. R. (1999). Racial/ethnic disparities in health: the interplay between discrimination and socioeconomic status. Ethn Dis, 9(2), 151-165.

Rodriguez, A. (1987). Institutional racism in the organizational setting: An action research approach. Strategies for improving race relations: The Anglo-American experience, 128, 148.

Sanders-Phillips, K., Settles-Reaves, B., Walker, D., & Brownlow, J. (2009). Social inequality and racial discrimination: risk factors for health disparities in children of color. Pediatrics, 124(Supplement 3), S176-S186.

Sengupta, M., Ejaz, F. K., & Harris-Kojetin, L. D. (2012). Training of home health aides and nurse aides: findings from national data. Gerontol Geriatr Educ, 33(4), 383-401. doi: 10.1080/02701960.2012.702167

Sholomskas, D. E., Syracuse-Siewert, G., Rounsaville, B. J., Ball, S. A., Nuro, K. F., & Carroll, K. M. (2005). We don't train in vain: a dissemination trial of three strategies of training clinicians in cognitivebehavioral therapy. Journal of consulting and clinical psychology, 73(1), 106.

Smedley, B. D., Stith, A. Y., & Nelson, A. R. (2003). Institute of Medicine, Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care. Unequal treatment: confronting racial and ethnic disparities in health care: Washington, DC: National Academies Press.

StataCorp, L. (2013). Stata Statistical Software: Release 13. College Station, TX: StataCorp LP.

Stewart, L. D., & Perlow, R. (2001). Applicant race, job status, and racial attitude as predictors of employment discrimination. Journal of Business and Psychology, 16(2), 259-275.

Stonerock, C. (1997). Home health aides: home care's "endangered species". Home Care Provider, 2(1), 15-17.

Story, M. T., Neumark-Stzainer, D. R., Sherwood, N. E., Holt, K., Sofka, D., Trowbridge, F. L., & Barlow, S. E. (2002). Management of child and adolescent obesity: attitudes, barriers, skills, and training needs among health care professionals. Pediatrics, 110(Supplement 1), 210-214.

The U.S. Equal Employment Opportunity Commission. (2014). Race/Color Discriminiation. Retrieved September 14, 2014, from http://www.eeoc.gov/laws/types/race_color.cfm

U.S. Department of Health & Human Services. (2004). Nursing Aides, Home Health Aides, and Related Health Care Occupations--National and Local Workforce Shortages and Associated Data Needs. HRSA Retrieved from http://www.directcareclearinghouse.org/download/RNandHomeAides.pdf.

Walker, R. L., Salami, T. K., Carter, S. E., & Flowers, K. (2014). Perceived Racism and Suicide Ideation: Mediating Role of Depression but Moderating Role of Religiosity among African American Adults. Suicide Life Threat Behav. doi: 10.1111/sltb.12089

Watson, J. M., Scarinci, I. C., Klesges, R. C., Slawson, D., & Beech, B. M. (2002). Race, socioeconomic status, and perceived discrimination among healthy women. J Womens Health Gend Based Med, 11(5), 441-451. doi: 10.1089/15246090260137617

Williams, D. R., Neighbors, H. W., & Jackson, J. S. (2003). Racial/ethnic discrimination and health: findings from community studies. American Journal of Public Health, 93(2), 200-208.

DOOHEE LEE

IVAN MUSLIN

MARJORIE MCINERNEY

Marshall University

Table 1
Descriptive Statistics of the Sample (n=3,377)

                               Total %        Racial
                               (Adjusted)     Discrimination
                                              Yes       No      P-value
                                              (13.49%)  (85%)

Gender                                                           .40
 Female                        95.1           92.88     95.45
 Male                           4.97           7.12      4.55
Race                                                             .0005
 White                         53.3            7.5      91.72
 Black                         34.93          22.94     75.99
 Other                         11.77          12.54     81.31
Age (Mean, SD)                 45.63 (12.07)  47.87     45.36    .36
Education (Mean, SD)           11.20 (4.46)   11.19     11.21    .97
Household Income (Mean, SD)     3.37 (3.18)                     <.001
 Less than $10,000              5.42           3.25      5.86
 $10,000--Under $20,000       16.07          10.78     17.2
 $20,000--Under $30,000       25.38          27.42     25.44
 $30,000--Under $40,000       20.46          29.09     19.4
 $40,000--Under $50,000       10.79          10.1      11.11
 $50,000--Under $60,000        5.25           3.89      5.56
 $60,000--Under $70,000        3.97           3.43      4.12
 $70,000--Under $80,000        2.63           2.67      2.67
 $80,000 or above               4.78           9.6       4.19
Metropolitan Statistical Area                                    .039
 Metropolitan                  84.02          90.93     82.75
 Micropolitan                  10.4            7.44     10.97
 Neither                        5.58           1.63      6.29
Agency type                                                      .597
 Home health                   74.19          74.28     73.86
 Hospice                       12.44          12.36     12.62
 Mixed                         13.37          13.36     13.52
Ownership                                                        .156
 For profit                    63.28          60.45     63.19
 Others                        36.72          39.55     36.81
Chain-affiliation                                                .275
 Chain                         29.95          39.17     28.71
 Non-chain                     70.05          60.83     71.29

Table 2
Results of Multivariate Logistic Regression for Racial Discrimination

                                     N = 3,339
                         Odds Ratio (95% CI)     P-value

Ownership
 For profit              Ref.
 Others                   .62 (.31-1.22)          .17
Chain                    Ref.
Non-chain                 .48 (.24-.93)           .03
Agency type
 Home health              Ref.
 Hospice                  .77 (.45-1.31)          .34
 Mixed                   1.05 (.49-2.26)          .89
Male                     Ref.
Female                   1.12 (.36-3.48)          .84
Age                      1.02 (.99-1.04)          .12
White                    Ref.
Black                    4.05 (1.85-8.84)        <.001
Other                    2.14 (.86-5.30)          .09
Income                   1.12 (1.02-1.24)         .02
<12 years                Ref.
High school graduate     1.11 (.36-3.35)          .85
Some college             1.13 (.40-3.22)          .81
College graduate          .90 (.24-3.41)          .89
Neither                  Ref.
Micropolitan             3.82 (1.29-12.05)        .022
Metropolitan             4.47 (1.72-11.58)        .002