Discrimination and Depressive Symptoms Among Black American Men: Moderated-Mediation Effects of Ethnicity and Self-Esteem.

Discrimination is related to depression and poor self-esteem among Black men. Poorer self-esteem is also associated with depression. However, there is limited research identifying how self-esteem may mediate the associations between discrimination and depressive symptoms for disparate ethnic groups of Black men. The purpose of this study was to examine ethnic groups as a moderator of the mediating effects of self-esteem on the relationship between discrimination and depressive symptoms among a nationally representative sample of African American (n = 1201) and Afro-Caribbean American men (n = 545) in the National Survey of American Life. Due to cultural socialization differences, we hypothesized that self-esteem would mediate the associations between discrimination and depressive symptoms only for African American men, but not Afro-Caribbean American men. Moderated-mediation regression analyses indicated that the conditional indirect effects of discrimination on depressive symptoms through self-esteem were significant for African American men, but not for Afro-Caribbean men. Our results highlight important ethnic differences among Black men.

Using the People of Color Racial Identity Attitude Scale among Asian American college students: an exploratory factor analysis.

In this study, an exploratory factor analysis of the People of Color Racial Identity Attitude Scale (PRIAS; Helms, 1995b) among a sample of Asian American college students (N = 225) was conducted. The factorial structure that emerged revealed mixed results in terms of consistency with the People of Color (POC) theory (Helms, 1995a). The measure's construct validity for Asian Americans may be improved through further scale development and revision. Directions for future research on the PRIAS are discussed.

Implications for social policy of variability in racial groups.

Social policy and federal and state legislation require the use of single cut scores when tests of cognitive ability, knowledge, or skills (CAKS) are used to make high-stakes assessment decisions, such as whether students or employees may be promoted. Rationales offered for the requirement are that cut scores provide objective standards and are fairer than using subjective criteria, such as racial group membership. It is argued that failure to consider threats to statistical conclusion validity, such as differences in variability between groups, obscures the differential impact of using a common cut score as the basis for highstakes decisions. Analyses of 40 Black and White samples revealed that (a) Whites might be considerably advantaged and Blacks might be considerably disadvantaged by the same cut score and (b) depending on where the cut score is set, decisions based on ratios of numbers of Whites numbers of Blacks might be fairer than use of CAKS test cut scores. Implications for assessment practice and social policy are discussed.

Implementing fairness in racial-group assessment requires assessment of individuals.

Replies to comments by R. J. Griffore and D. A. Newman et al on the author's original article on test validity and cultural bias in racial-group assessment. Helms notes that, given that within-group variance exceeds between-groups variance, racial groups are probably simulating a psychological construct that is more strongly related to individuals' test scores than to their respective racial group's mean test scores. Therefore, models of individual differences, such as her Helms individual-differences (HID) model, that remove construct-irrelevant racial variance, are needed to make the testing process fair at the level of individual African American, Latino/Latina American, and Native American test takers. Her HID model is intended to focus attention on identifying the factors responsible for the racial-group-level differences and, thereby, assist test users to look beyond presumed physical appearance (e.g., racial-group designations) for explanations of individuals' cognitive abilities, knowledge, or skills test scores.

Fairness is not validity or cultural bias in racial-group assessment: a quantitative perspective.

When test scores that differ by racial groups are used for assessment purposes, resulting decisions regarding members of the lower scoring group are potentially unfair. Fairness is defined as the removal from test scores of systematic variance attributable to experiences of racial or cultural socialization, and it is differentiated from test-score validity and cultural bias. Two fairness models for identifying, quantifying, and removing from test scores construct-irrelevant variance attributable to racial or cultural psychological attributes are presented. ((c) 2006 APA, all rights reserved).

The meaning of race in psychology and how to change it: a methodological perspective.

The primary purpose of this article was to offer a methodological critique in support of arguments that racial categories should be replaced as explanatory constructs in psychological research and theory. To accomplish this goal, the authors (a) summarized arguments for why racial categories should be replaced; (b) used principles of the scientific method to show that racial categories lack conceptual meaning; (c) identified common errors in researchers' measurement, statistical analyses, and interpretation of racial categories as independent variables; and (d) used hierarchical regression analysis to illustrate a strategy for replacing racial categories in research designs with conceptual variables. Implications for changing the study of race in psychology are discussed.

An examination of the evidence in culturally adapted evidence-based or empirically supported interventions.

Measurement yields perhaps the most critical evidence influencing whether culturally adapted evidence- based practice (EBP) and empirically supported treatments (EST) are deemed more effective for African Americans, Latino/a Americans, Asian/Pacific Islander Americans, Native Americans, and related immigrant groups than standard treatments, as well as for determining the validity of results of surveys of health conditions in nondominant populations internationally. However, little attention has been given to measuring the effects of race and ethnic culture, as experiential constructs rather than sociodemographic categories, on diagnosis, the treatment process, and outcomes. Three meta-analyses of culturally adapted treatments and three studies cited in them were analyzed to determine the ways in which researchers incorporated measurement of racial and ethnic cultural dynamics as explicit factors in any phase of their interventions. The analysis revealed that researchers did not report adapting standard measures to address cultural influences, nor did they define symptoms from participants' cultural or racial experiences. The author concludes that although there are criteria for judging good research designs, which may or not be feasible for research on nondominant racial and ethnic groups, there are no paradigms for developing measures or for interpreting existing measures to incorporate ethnicity and racialized experiences. Some principles from cross-cultural assessment research (i.e., functional, conceptual, metric, and linguistic equivalence) are adapted to suggest how measures for investigating the effectiveness of culturally adapted interventions for nondominant ethnic and racialized groups might be developed and/or used more appropriately throughout the course of the intervention.

Recent reliability reporting practices in Psychological Assessment: recognizing the people behind the data.

Helms, Henze, Sass, and Mifsud (2006) defined good practices for internal consistency reporting, interpretation, and analysis consistent with an alpha-as-data perspective. Their viewpoint (a) expands on previous arguments that reliability coefficients are group-level summary statistics of samples' responses rather than stable properties of scales or measures and (b) encourages researchers to investigate characteristics of reliability data for their own samples and subgroups within their samples. In Study 1, we reviewed past and current reliability reporting practices in a sample of Psychological Assessment articles published across 3 decades (i.e., from the years 1989, 1996, and 2006). Results suggested that contemporary and past researchers' reliability reporting practices have not improved over time and generally were not consistent with good practices. In Study 2, we analyzed an archival data set to illustrate the real-life repercussions of researchers' ongoing misconstrual and misuse of reliability data. Our analyses suggested that researchers should conduct preliminary analyses of their data to determine whether their data fit the assumptions of their reliability analyses. Also, the results indicated that reliability coefficients varied across racial or ethnic and gender subgroups, and these variations had implications for whether the same depression measure should be used across groups. We concluded that the alpha-as-data perspective has implications for one's choice of psychological measures and interpretation of results, which subsequently affect conclusions and recommendations. We encourage researchers to recognize the people behind their data by adopting better practices in internal consistency reporting, analysis, and interpretation.