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. Author manuscript; available in PMC: 2016 Oct 17.
Published in final edited form as: Stigma Health. 2016 Feb 25;1(3):146–155. doi: 10.1037/sah0000027

Assessing Stigma among African Americans Living with HIV

Deepa Rao 1, Yamile Molina 2, Nina Lambert 3, Susan E Cohn 4
PMCID: PMC5067075  NIHMSID: NIHMS761481  PMID: 27761520

Abstract

Purpose

In the present study, we validated a culturally adapted stigma scale designed to assess stigma among African Americans living with HIV.

Methods

We collected data on the scale using an audio computer assisted self-interview (ACASI) format. We validated the scale with a sample of 62 African American participants living with HIV.

Results

Findings demonstrated that stigma can be measured succinctly and effectively in a 14-item scale with two subscales measuring enacted and internalized stigma.

Discussion

We identified many advantages to using the scale, which demonstrated good psychometric properties when used with an audio computer assisted self-interview format and with an African American sample. We recommend this scale’s use in both clinical practice and research study of HIV-stigma reduction interventions with African American populations.

Keywords: Stigma, HIV, Measurement, Validation, African American

Introduction

African-Americans have the greatest HIV burden of all groups in the United States, wherein they represent 12% of the US population but accounted for 46% of new HIV infections in 2013 and had the highest proportion of deaths among people living with HIV (CDC, 2015). Further, despite a greater decline in deaths, African Americans living with HIV had 1.5 times the risk of death relative to White counterparts (CDC, 2015). Researchers have explained the particularly poor outcomes for African Americans living with HIV in terms of delays in accessing care and difficulties in accessing and adhering to medication regimens (Cohen et al., 2007; Kahn et al., 2002; Siegel, Karus, & Schrimshaw, 2000). Studies have shown that African Americans living with HIV do not remain in care, access treatment later, and adhere to medications less well than other people living with HIV (Kahn, et al., 2002; Kempf et al., 2010; Palacio, Kahn, Richards, & Morin, 2002).

One potential reason for racial/ethnic disparities in adherence and engagement to care may be racial/ethnic differences in stigma among people living with HIV, which have been shown to be higher for African Americans (Rao, Kekwaletswe, Hosek, Martinez, et al. 2007). Indeed, researchers, especially in work with African American populations, have often cited stigma as a reason for not seeking care (Arnold, Rebchook, & Kegeles; 2014; Remien et al., 2015; Seekins, Scibelli, Juday, Stryker, & Das, 2010; Smith, Fisher, Cunningham, & Amico, 2012). These findings suggest that stigma may be an important underlying psychosocial factor contributing to healthcare and health outcome disparities among people living with HIV and African Americans in particular. Nonetheless, there are few HIV stigma reduction interventions targeting African Americans and addressing their unique needs (Rao et al., 2012; Stangl, Lloyd, Brady, Holland, & Baral, 2013). A lack of intervention may be in part due to few stigma measures developed specifically for African Americans living with HIV. Some studies have used stigma measures with African Americans living with HIV (Vyavaharkar, Moneyham, Corwin, Saunders, et al., 2010) without specific development for this population. This paper describes the development and validation of a stigma measurement tool revised specifically for African Americans living with HIV.

The Construct of Stigma

Stigma has been tied to people living at the margins of society who often struggle with multiple stigmatizing conditions, such as being poor, African American, and female. This is sometimes called intersectionality or intersectional stigma (Bowleg, 2012; Berger, 2006; Earnshaw, Smith, Cunningham, & Copenhaver, 2015). For example, African American women from low income communities who abuse substances and live with HIV may deal with separate stigmas associated with poverty, substance abuse, and race (racism). Taken together, these stigmas may have a compounding effect on the women’s health (Reidpath & Chan, 2005). Further, researchers have put forward a set of terms that are helpful in describing stigma’s impact. Public stigma refers to stigmas held by members of the public, such as healthcare professionals, clergy, or employers, about people with devalued characteristics that result in stereotypes, prejudice and discrimination. Once public stigmas are enacted (i.e., personally experienced), they can be internalized by the stigmatized individual. Internalized stigmas have a profound impact on mental health, medication adherence, health care service utilization, and ultimately, health outcomes for people living with HIV (Rao, Kekwaletswe, Hosek, et al., 2007; Lee, Kochman, Sikkema, 2002). Earnshaw and colleagues (2009, 2013) have demonstrated that enacted stigmas are associated with physical well-being and internalized stigmas are associated with affective and behavioral well-being. Corrigan (2006) provides a conceptual framework that ties enacted or perceived stigmas (i.e. awareness of stigmas existence in the public sphere), and an agreement with these stigmas, to the internalization of stigma. Other aspects of stigma also profoundly impact people living with HIV, such as anticipated or vicarious stigma. However, it is internalized stigma that leads to poor adherence, poor engagement in care, and ultimately, poor health outcomes (Rao, Feldman, Fredericksen, Crane, Simoni, Kitahata, Crane, 2011), and thus, internalized stigma was one of two aspects of stigma that was a focus of our measure.

A growing body of literature has addressed the importance of studying stigma among African Americans living with HIV, who appear to experience particularly high amounts of enacted (88% of sample, Radcliffe, Doty, Hawkins, Gaskins, Beidas, & Rudy, 2010; Rao et al., 2008), and subsequently, internalized stigma (e.g., >60% of sample, Foster & Gaskins, 2009). Enacted stigma becomes an important concept to measure for African Americans, given our previous studies of stigma in which African Americans living with HIV were more attuned to concepts around discrimination than their white counterparts (Rao, Pryor, Gaddist, Mayer, 2008). In addition, African Americans and Whites living with HIV differ in item endorsement on stigma measures (Rao, Pryor, Gaddist, Mayer, 2008). Thus, we felt it fundamental to adapt and test a measure of HIV-related stigma specifically for African Americans. Scales that measure stigma among people living with HIV in the U.S. have been developed with participants from multiple racial/ethnic backgrounds, but not specifically validated with African Americans living with HIV. For example, the HIV Stigma Scale (HSS) was developed in a sample with a low percentage of African American participants (21%; Berger, Ferrans, Lashley, 2001).

In terms of measurement development, targeted efforts for adaptation and psychometric validation may thus be particularly important for stigma instruments used with African Americans living with HIV, who express distinct concerns and types of stigmatizing experiences (Lekas, Siegel, & Schrimshaw, 2006). Second, the majority of instruments to date have either targeted only one dimension of stigma (e.g., Internalized AIDS-related Stigma Scale; Kalichman et al., 2009) or have been relatively long in nature (40 item HSS, Berger et al., 2001; 28-item Multidimensional Measure of Internalized HIV Stigma, Sayles et al., 2008). Due to specificity to one stigma dimension and/or great patient burden, such instruments may not be feasible to employ in practice-based settings or to evaluate the translation of interventions into community settings.

In order to assess stigma experienced by people living with HIV, investigators and clinicians need short measures that have good psychometric properties, are free of measurement bias, and have been modified to fit the needs and concerns of their target populations. Our team developed the Stigma Scale for Chronic Illness (SSCI), which was originally intended for use as a ‘generic’ scale to assess stigma experienced and internalized by people with a variety of conditions and marginalized statuses (e.g., epilepsy, HIV, minority race, minority sexual orientation, poverty). We developed both a 24-item and an 8-item version with good psychometric properties that were validated using novel psychometric techniques for use with people with neurological disorders (Molina, Choi, Cella, & Rao, 2011; Rao et al., 2009). In order to determine the appropriateness of using the SSCI with African Americans living with HIV, in this previous study, we conducted cognitive interviews to elicit feedback on its relevance and applicability with this population (Willis, 1999). Our African American participants living with HIV suggested that racism, sexism, and other ‘isms’ outside of HIV be queried in separate measures. In addition, several participants mentioned that they had not disclosed to others about their HIV status, and thus, items about disclosure concerns seemed better assessed in a separate scale. Examples of other problematic items included “Because of my illness, strangers tended to stare at me,” “I felt embarrassed about my speech,” “It was hard for me to stay neat and clean.”. With respect to these problematic items, participants sometimes misunderstood the item wording or felt that the items were generally irrelevant to their experience (Rao, Andrasik, Acharya, & Simoni, 2013). After considering the cognitive interview and item level responses, we concluded that 12 items were problematic and the remaining 14-items of the SSCI would be most appropriate for use with African Americans living with HIV.

The Present Study

The present study describes the psychometric properties of the 14-item SSCI used with a population of African Americans living with HIV. Given the need for literacy sensitive measures for people living with HIV (Kalichman et al., 2005; NIMH, 2007; Osborn, Paasche-Orlow, Davis, & Wolf, 2007; Pluhar et al., 2007; Sentell & Halpin, 2006; Wolf et al., 2006), we converted administration of the measure from a paper and pencil form to an Audio Computer Assisted Self Interview (ACASI). We also conducted factor analyses, investigated reliability and concurrent validity of the instrument in relation to the widely used HSS, and examined scores across socio-demographic and clinical characteristics of the participants. Our goal was to provide preliminary evidence concerning details of a brief, culturally adapted stigma scale with good psychometric properties, assessing both enacted and internalized stigma.

Methods

Participants

Participants were African American men and women living with HIV over the age of 18 years. All participants were currently seeking treatment at an HIV clinic within a university-based hospital in an urban Midwestern U.S. setting.

Procedures

Participants were recruited by a nurse research coordinator with the HIV clinic. The nurse coordinator informed potential qualifying participants about the study, and interested participants scheduled a meeting to review study procedures, provide consent, and complete study measures. After participants provided consent, the nurse coordinator demonstrated how to use the computer to complete study assessments. The ACASI assessments were completed such that the participant wore headphones (for privacy) and heard the computer read each item and response choices out loud. The participants would then enter their responses using a touch screen tablet computer. The participants answered a few ‘test’ multiple choice questions (e.g. “choose your favorite food”), and the nurse remained in the room as participants completed the test questions, in case participants had questions or difficulties with the computerized assessment. When the participants felt confident in using the ACASI modality, the nurse left the room and sat just outside in case the participant had questions or concerns.

Measures

Socio-demographic and Clinical Variables

We asked participants to provide standard information on their socio-demographic background (e.g., age, marital status) and self-reported clinical characteristics (e.g., year of diagnosis, CD4+ T cell count). We did not have access to medical record in this study. Further, due to small frequencies in categories, we collapsed groups across education (high school versus college) and living arrangement (alone versus with others).

HIV Stigma Scale (HSS)

We examined associations between total scores on the HIV Stigma Scale (Berger et al., 2001) and the 14-item SSCI to investigate concurrent validity. The HSS has been widely used to measure stigma that affects people living with HIV, but is considered a lengthy scale with 40 items and 4 subscales (Bunn, Solomon, Miller, & Forehand, 2007; Jeyaseelan et al., 2011). The HIV Stigma Scale uses a 4-point Likert scale (1 = Strongly Disagree to 4 = Strongly Agree).

Stigma Scale for Chronic Illness (SSCI)

As previously mentioned, this scale’s items have been validated in 24-item and 8-item versions for with people living with various neurological disorders (Molina, et al., 2011; Rao, et al., 2009). The original scale contained two factors, with items measuring both internalized and enacted stigma. We conducted cognitive interviews to modify the scale to be more appropriate for people living with HIV (Rao, et al., 2013). The result of these interviews was a 14-item scale, measuring internalized and enacted stigma, with a 5-point Likert response format (1 = Never to 5 = Always). The items are listed in Table 2. All items used “lately” as the recall period and each item had five response options ranging from “never” to “always.” The items referred to ‘my illness’ instead of HIV infection.

Table 2.

Factor loadings from exploratory factor analysis, n = 62

Item1 Enacted (SE) Internalized (SE) M SD
1. Because of my illness, some people have seemed uncomfortable with me. 0.77 (0.10) 0.2 (0.12) 2.11 1.28
2. Because of my illness, people were unkind to me. 0.98 (0.05) −0.01 (0.07) 1.61 1.16
3. Because of my illness, some people have avoided me. 0.82 (0.16) 0.08 (0.19) 1.81 1.23
4. Because of my illness, I was treated unfairly by others. 0.84 (0.08) 0.16 (0.10) 1.77 1.18
5. Because of my illness, people tended to ignore my good points. 0.84 (0.10) 0.01 (0.10) 1.69 1.24
6. Because of my illness, I worried that I was a burden to others. 0.56 (0.16) 0.36 (0.16) 2.29 1.48
7. Some people acted as though this was my fault. 1.00 (0.17) −.30 (0.20) 2.55 1.52
8. Because of my illness, I felt emotionally distant from other people. 0.15 (0.18) 0.75 (0.16) 2.44 1.42
9. Because of my illness, I felt left out of things. 0.19 (0.18) 0.76 (0.15) 2.24 1.35
10. I felt embarrassed about my illness. −0.001 (0.01) 0.90 (0.04) 3.05 1.62
11. Because of my illness, I felt different. from others. 0.19 (0.16) 0.72 (0.14) 2.92 1.55
12. I avoided making new friends. 0.34 (0.19) 0.49 (0.18) 2.39 1.62
13. I was careful who I told about my illness. 0.06 (0.24) 0.42 (0.20) 4.44 1.2
14. I worried that people would tell others about my illness. −0.34 (0.23) 0.92 (0.18) 3.69 1.51
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Notes.

1

Enacted stigma items are highlighted in grey, as demonstrated by higher loadings on the enacted stigma factor.

Data Analysis

To assess the psychometric properties of our instrument, we conducted Exploratory Factor Analysis (EFA) using Mplus software (Mplus, Muthén & Muthén). EFAs employ polychoric correlation coefficients, which are considered robust with ordinal item responses. We used weighted least squares with adjustment for means and variance estimation for categorical variables (WLSMV) with geomin rotation. WLSMV provides a robust estimation for ordinal data in terms of unbiased parameter estimates and adequate Type I error control (Lei, 2009). Geomin rotation is advantageous for multiple factors, especially when little is known regarding actual loadings (Asparouhov & Muthén, 2008). We assessed the number of factors through scree plots, initial eigenvalues from EFA, and parallel analysis. Parallel analysis is a recommended technique for identifying the optimal number of factors to rotate (Thompson & Daniel, 1996). According to Izquierdo, Olea, and Abad (2014), most studies they reviewed eliminate items with loadings lower than 0.3 and consider loadings between 0.3 and 0.5 to be low. Thus, for individual items, we reviewed factor loadings and assigned items to subscales with loadings of 0.30 or greater. We calculated internal consistency and reliability with Cronbach’s alpha and item-total correlations. Concurrent validity was assessed with calculation of a Pearson correlation coefficient between total scores on the HSS and the SSCI. Lastly, through Analysis of Variance (ANOVA), we examined mean differences in stigma scores across categorical socio-demographic characteristics. Through Pearson’s correlation coefficients, we examined strengths of relationships between SSCI and HSS scores on the continuous variables of age, years of living with HIV, and CD4+ T cell count variables. For ANOVA calculations with the gender variable, we dropped the single transgender individual’s data from the analysis because one case would not provide enough power to draw valid conclusions about the result.

Results

Sample Characteristics

In this clinical sample of 62 participants, ages ranged from 23- to 68-yearsold. Sixty-one percent of the participants were male, and the average number of years living with HIV was 13. We provided full descriptive information on socio-demographic and clinical variables of our 62 participants in Table 1.

Table 1.

Socio-demographic and clinical characteristics of participants, n = 62.

Variable Frequency
(%)
Gender
Male 38 (61)
Female 23 (37)
Transgender 1 (2)
Living arrangement
Alone 22 (36)
With others 40 (64)
Education1
High School 24 (39)
College 38 (61)
AIDS diagnosis
Yes 23 (37)
No 39 (63)
Route of transmission
Male-female sexual contact 27 (44)
Male-male sexual contact 24 (39)
Injection drug use/blood exposure 11 (17)
Average (SD) Range
Age 42.9 (10.6) 23–68
Years living with HIV 13.1 (8.11) 0–31
CD4+ T-cell count2 413.49 (297.97) 0–1000
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Notes.

1

High School = Some high school/high school diploma, College = Some college/college/advanced degree.

2

CD4+ T-cell counts are based on self-report.

Exploratory Factor Analysis

Eigenvalues (8.9, 1.4, 1.2) along with scree plots and parallel analysis suggested a 2-factor solution best fit the data instead of a 1- or 3-factor solution. Table 2 provides factor loadings and descriptive information for the 14 items. Item loadings were generally in line with previous findings on the SSCI in other clinical samples in which we have assigned items to subscales at 0.3 or higher (Molina et al., 2011; Rao et al., 2009). Item 6 had a modest factor loading (0.56) on the ‘enacted stigma’ subscale. Items 12 and 13 had low factor loadings on the ‘internalized stigma’ subscale. These items were still within our criteria for subscale assignments. Item 6 may have conceptually fit under the ‘internalized stigma’ subscale. In addition, although item 14 had a high factor loading, items 12, 13, and 14 may have been better characterized as disclosure concerns. We decided to assign the items to the respective subscales, maintaining a data driven manner of forming subscales rather assigning items to subscales in a theory driven, or mixed, manner.

Reliability

Our overall scale exhibited good internal consistency reliability (Cronbach’s alpha = 0.93) and item-total correlations were equal or greater than 0.42. Cronbach’s alphas for the SSCI-Enacted and SSCI-Internalized Stigma scales were 0.93 and 0.84 respectively. Item-total correlations for both sub-scales were generally equal to or greater than 0.53.

Concurrent validity

We calculated sum scores for the overall SSCI, SSCI-Enacted Stigma, and SSCI-Internalized Stigma scales to assess concurrent validity with HSS scores. Our scale demonstrated excellent concurrent validity; as predicted, there were strong positive relationships between the HSS and the SSCI overall (r = .76, df = 62, p <.0001), SSCI-Enacted (r = .69, df = 62, p <.0001), and SSCI-Internalized summary scores (r = .71, df = 62, p <.0001). Sub-scales were positively correlated (r = .69, df = 62, p < .0001); however, participants reported a greater frequency of internalized than enacted stigma(t(61) = −9.63, p < .0001; Table 2).

Stigma, Socio-demographic, and Clinical Variables

ANOVAs revealed no statistically significant differences in total SSCI or HSS scores across categorical variables. However, for the continuous variables, age was significantly associated with overall SSCI scores, such that younger individuals living with HIV reported higher rates of stigma (r = −.31, df = 61, p = .02).

Discussion

The results demonstrate that internalized and enacted stigma can be measured together in one scale with good psychometric properties to succinctly assess internalized and enacted HIV-related stigma among African Americans living with HIV. First, our analyses showed that the 14-item version of the SSCI was closely associated with the HSS but measured stigma in a more succinct manner. Second, the SSCI scale measured enacted stigma and internalized stigma, concepts focal to Earnshaw and colleagues (2013) framework of HIV-related stigma. Unlike other measures of HIV-related stigma, the SSCI was adapted specifically for African Americans living with HIV. Thus, as enacted and internalized stigma are important contributors to poor health outcomes for this population, this culturally adapted measure may help researchers better understand the magnitude with which stigma impacts morbidity and mortality, particularly among African American populations.

This study provides the first validation information for the SSCI revised and used with African Americans living with HIV. In previous studies, the scale was validated using Confirmatory Factor Analysis and Item Response Theory methodology with people living with various neurological disorders (e.g., epilepsy, multiple sclerosis, Parkinson’s disease) (Molina, et al., 2011; Rao et al., 2009). Another study used 4 items of the scale in a Structural Equation Model with data from people living with HIV, thereby providing positive information on the SSCI items’ performance as a single stigma construct (Rao, et al., 2011). With the addition of the present study, we have evidence that this revised 14-item version of the stigma scale may be used to precisely measure stigma among African Americans living with HIV, given several types of analyses used across different samples. In addition, its validation with two distinct population groups demonstrates that it can be used to compare and contrast stigmas across populations with neurological disorders and HIV infection.

This study aimed to provide psychometric data on an HIV stigma scale that was specifically targeted to measure stigma among African Americans living with HIV in a culturally appropriate manner. A few other measures of stigma have been developed for use in the United States. Some of these scales are lengthy, including the 40-item HSS (Berger et al., 2001) and the 28-item Multidimensional Measure of Internalized HIV Stigma (Sayles et al., 2008). One other measure developed using data collected from a United States-based population is quite brief: the 6-item Internalized AIDS-Related Stigma Scale (Kalichman et al., 2009).

In order for the instrument to be completed in private and in a literacy-friendly manner, we administered it using an Audio Computer Assisted Self Interview (ACASI) version of the scale. The ACASI version allowed for participants to hear response choices using headphones, without the need for another person to record answers on paper. Such privacy may enhance the quality of the responses, and social desirability may have less of an influence on responding patterns than do traditional interviewer modes of administration; future studies can further investigate these claims.

Our preliminary findings suggest few socio-demographic correlates of HIV stigma among this population of African Americans living with HIV. If further research with larger sample sizes supports these findings, this measure may be used to measure stigma reduction across gender, educational levels, and clinical variables among African Americans living with HIV. Our results are in line with recent findings from a meta-analysis examining socio-demographic correlates of HIV-related stigma (Logie & Gadalla, 2009) and also with an increasing interest in characterizing enacted and perceived stigma in young people living with HIV (Fielden, Chapman, & Cadell, 2011; Rao, Kekwaletswe, Hosek, Martinez, & Rodriguez, 2007; Swendeman, Rotheram-Borus, Comulada, Weiss, & Ramos, 2006).

Our study had some limitations. First, it should be noted that the SSCI scale does not measure all aspects of stigma, but only internalized and enacted stigma. In addition, our conceptualization that enacted stigma, and an individual’s agreement with these stigmas, contributes to internalized stigma impacted our interpretation of results. Third, our sample was powered to assess the strength of association between the HSS and the SSCI. Thus, the sample was relatively small for factor analyses. As such, results should be interpreted with caution and the validity of the subscale structure should be strengthened in studies with a larger sample size. We assigned items to subscales in a purely data driven manner, whereas other researchers may proceed in a theory driven or mixed manner. This choice in design may be interpreted as a limitation. Furthermore, the participants were prompted to consider ‘lately’ and ‘my illness’ when completing items of the SSCI. It is possible that our participants could have recalled illnesses other than HIV or varying time frames in responding to items. Thus, these results should be interpreted with caution. Finally, these data were collected cross-sectionally, thus interpretations regarding causality cannot be made.

We have shown the 14-item SSCI to have some statistical validity and reliability among African Americans living with HIV. Next steps for stigma researchers will be to use the measure in intervention studies so as to better understand changes in stigma over time, as well as changes after African Americans’ participation in stigma reduction or other health promotion interventions. Such studies would not only demonstrate the strength of the SSCI, but would also help develop an evidence base for interventions aimed at reducing internalized stigma in this population. For clinicians and those in social service practice, this tool can help to better understand the severity of stigmas experienced, and the impact of interventions delivered to African Americans with HIV. Whether used in research or clinical work, the adapted SSCI can help to monitor and evaluate secondary prevention strategies for, African Americans living with HIV.

Acknowledgments

This study was funded by the U.S. National Institutes of Health grant number K23 MH 084551 (PI: Rao).

Contributor Information

Deepa Rao, Department of Global Health, University of Washington, Seattle Washington

Yamile Molina, Health Services Department, University of Washington, Seattle, Washington

Nina Lambert, Division of Infectious Diseases, Department of Medicine, Northwestern University, Chicago, Illinois

Susan E. Cohn, Division of Infectious Diseases, Department of Medicine, Northwestern University, Chicago, Illinois

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