Research Article: Perceived microaggressions in health care: A measurement study

Date Published: February 5, 2019

Publisher: Public Library of Science

Author(s): Daniel Cruz, Yubelky Rodriguez, Christina Mastropaolo, Nickolas Zaller.

http://doi.org/10.1371/journal.pone.0211620

Abstract

The current study examined the psychometric properties of the Microaggressions in Health Care Scale (MHCS), including factor structure, measurement invariance, and internal consistency reliability. We used a cross-sectional research design to study perceived racial microaggressions, discrimination, and mental health in 296 African American and Latino respondents. Participants completed measures that assess healthcare microaggressions and daily discrimination as well as the Depression, Anxiety and Stress Scale (DASS-21). Results revealed that the MHCS has promising psychometric properties. The confirmatory factory analysis (CFA) revealed that the MHCS is a unidimensional scale. Multi-group CFAs provided evidence of measurement invariance across racial / ethnic groups and gender. The internal consistency reliability of the scale was .88 for the overall sample. Microaggressions correlated with daily discrimination scores (r = .67), as well as mental health symptoms (r’s = .40 –.52). The MHCS is a brief, valid, and reliable measure that can be used to assess and monitor racial and cultural forces that shape patient-provider interactions. This study concludes with a discussion of the ongoing need for research on microaggressions in healthcare as well as implications for future research.

Partial Text

Racial minorities have been pervasively marginalized because of racism and oppression. This social problem has had measurable effects on the health and well-being of people of color and on society as a whole. Racial discrimination is still widespread and is a significant social determinant of minority population health. The health disparities literature suggests that racism is responsible, in part, for the increased morbidity and mortality rates observed among racial minority groups [1]. Furthermore, racial discrimination is understood to be a complicated construct in that it occurs in both obvious as well as subtle ways. For example, researchers have found that racism can occur explicitly through blatant discriminative encounters, as well as through microaggressions [2–3].

Study recruitment occurred via Amazon’s Mechanical Turk. Potential participants from Mechanical Turk reviewed the study description, and, if interested and eligible, they were directed to a Qualtrics survey. To qualify for the study, participants had to be over the age of 18 and identify as Black/African-American or Hispanic/Latino. After reviewing and agreeing to the informed consent form, participants were directed to the Qualtrics link, where they responded to a demographic questionnaire and completed all psychometric instruments. The study was reviewed and approved by the Institutional Review Board at Seton Hall University.

Participant demographic variable analysis revealed that the gender composition of the participants was relatively equal (51% male and 49% female; Table 1). The average age of participants was 35 ± 10.91 years (range: 18 to 71). The majority of participants were college educated (89%), worked full-time (72%), and earned between $21,000 to $60,000 per year (56%).

The primary goal of this study was to provide psychometric evidence for the Microaggressions in Health Care Scale with a sample of African-Americans and Latinos. The confirmatory factor analysis showed strong evidence in support of a single-factor solution for the instrument. Moreover, measurement invariance testing revealed good model fit across all multigroup comparisons and within increasingly constrained models for both gender and race/ethnicity.

Accurate assessment and identification of racial microaggressions, particularly within the healthcare environment, is critical for improving health outcomes in vulnerable populations.

 

Source:

http://doi.org/10.1371/journal.pone.0211620

 

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