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Abstract

Objectives

There is a high prevalence of internalized stigma among people with HIV (PWH) and it is possible that factors associated with stigma differ by gender. Therefore, we evaluated whether gender is an effect modifier of the association between covariates and internalized stigma among 694 PWH.

Methods

Linear regression with interaction terms between covariates and gender was used to evaluate significant associations and test for interactions.

Results

We found a 10-year increase in age was associated with lower stigma among women (β (95% CI): −0.20 (−0.30, −0.10)) but not among men (β = 0). Generalized anxiety disorder (GAD) was associated with higher stigma (GAD & GAD-squared β (95% CI): 0.12 (0.08, 0.187), −0.004 (−0.006, −0.001)) and an increased time since HIV diagnosis was associated with lower stigma (β (95% CI): −0.20 (−0.30, −0.10)).

Conclusions

Gender-specific interventions should be developed to account for the differences in the association between age and stigma across genders.

Plain Lanugage Summary

Characteristics Associated with Self-Reported Stigma Among People with HIV in Washington DC and Whether These Characteristics Differ by Gender

We sought to evaluate factors associated with internalized stigma among people with HIV (PWH) and determine whether the relationships between these factors and stigma differ by a person’s gender identity. Therefore, we used survey data from 694 PWH enrolled in the DC Cohort, an ongoing research study in Washington, DC. We found that a 10-year increase in age was associated with lower stigma, but only among female participants. Anxiety was also associated with higher self-reported stigma and longer time since the person was diagnosed with HIV was associated with lower self-reported stigma. Gender-specific interventions should be developed to account for the differences in the association between age and stigma across gender identities.

Keywords

HIV/AIDS internalized stigma patient-reported outcomes (PROs)mental health age gender identity

Introduction

Receiving an HIV or AIDS diagnosis can be stressful, often leading to increased health challenges and decreased quality of life.¹ One of these stressors is stigma, which has long been associated with HIV.² Stigma occurs when an aspect of an individual is discredited or devalued.³ Experiencing stigma can impact psychosocial outcomes of people with HIV (PWH) in terms of life satisfaction and health-related consequences and is negatively associated with psychological and physical well-being.^1,4–9

There are three main types of stigma an individual can experience: external or public stigma, internal or self-stigma, and stigma by association. External stigma occurs when public perception or a large percentage of society apply negative attitudes or beliefs to a group of people. This type of stigma can lead to feelings of exclusion from societal groups.¹⁰ Stigma by association, also known as affiliate stigma, occurs when an individual experiences the detrimental effects of stigma against a loved one, leading to feelings of shame and isolation.¹⁰ Internalized stigma occurs when individuals internalize stigmatizing beliefs and apply these negative attitudes toward themselves.¹⁰ Prior studies have found that a majority of PWH report internalized stigma.^2,11 This is concerning, given that decreases in internalized stigma have been associated with viral suppression, ART adherence, more engagement in care, depression, and other mental health conditions.^7,12,13 Therefore, it is important to gain a better understanding of factors that are associated with experiencing internalized stigma in order to better inform interventions for reducing internalized stigma among PWH.

Multiple previous studies have evaluated factors related to internalized stigma among PWH. For instance, one study found that time since HIV diagnosis, lower family acceptance, not attending support groups, and knowing fewer PWH were associated with increased internalized stigma among PWH.² In contrast, another study on PWH in Kenya found that people who self-disclosed their HIV status were more likely to report internalized stigma.¹⁴ Race, age, housing status, and mental health are also associated with general HIV-related stigma and interventions aimed at reducing barriers to care and increasing engagement in care have been associated with a reduction in overall stigma among PWH.^15,16

Factors associated with internalized stigma may also have complex interactions with one another. For example, one study in Canada found that Black women, Asian men, and Latin-American men reported the highest levels of HIV-related stigma and therefore concluded gender was a modifier of the relationship between race/ethnicity and stigma.¹⁷

This effect modification by gender is not surprising given that the development of social support, defined as the nonprofessional social resources a person perceives to be available to them, differs across genders.^18,19 Among men, social support has been found to increase well-being and lower the likelihood of engaging in HIV risk behaviors, but these associations have not been found in women.^20,21 As increased social support is associated with lower levels of stigma, differences in social support by gender may contribute to why women have also reported higher levels of stigma internalization compared to men, as well as higher rates of enacted stigma in their daily lives.^5,22,23

Given these prior findings in the literature, it is possible that gender serves as an effect modifier for the relationship between many other individual-level factors and internalized stigma. Specifically, it is likely that the association between these factors and internalized stigma among PWH will be stronger among men. However, no studies have been published examining whether gender serves as an effect modifier for the association between important factors such as age, HIV transmission factor, time since HIV diagnosis, mental health, and other HIV-related clinical factors and internalized stigma. Understanding how stigma manifests across genders among PWH can better inform stigma-related interventions. Therefore, we conducted an exploratory cross-sectional analysis to determine whether mental health, race/ethnicity, age, HIV-related factors, and time since HIV diagnosis are related to internalized stigma among PWH in Washington, DC, and to determine whether gender is an effect modifier for these associations. We hypothesized that the magnitude of association between internalized stigma and each of these potential covariates will be stronger among men than other genders.

Materials and Methods

Data Collection

All participants were enrolled in the DC Cohort, an ongoing longitudinal cohort of consenting HIV patients in DC. The DC Cohort received approval from the George Washington University Institutional Review Board (IRB) (#071029). External participating sites with their own IRBs also obtained additional approval. Written informed consent was provided by all participants during a routine clinical visit or while receiving care from one participating site where consent for data use for research purposes is part of clinical care and explained annually in the explanation of benefits. Enrollment in the cohort began in 2011 and is ongoing as of 2024. The cohort contains data on risk factors, diagnoses, lab results, treatments, and procedures from the participant's HIV care site. All information is imported from electronic health records and stored in a secure database.²⁴ As of September 2022, there were over 12,000 participants in the DC Cohort.

Within the DC Cohort, we conducted a sub-study on patient-reported outcomes (PROs) using self-reported surveys from a subset of DC Cohort participants. Previously enrolled DC Cohort participants were recruited during visits with their HIV care provider or through telephone calls from Research Assistants at their HIV care provider clinic. Participants provided self-consent through an embedded form in the electronic survey. This waiver of written documentation was approved by the George Washington IRB. All PROs participants are people living with HIV receiving care at one of the DC Cohort sites and are at least 18 years old or adolescents seeking care independently. The questionnaire consisted of various PROs measures, including mental health and internalized stigma. At the time of analysis, there were 14 participating sites in the DC Cohort. Of these sites, there were seven community-based sites and seven hospital-based sites.

Information on demographics, HIV viral load (copies/mL), CD4 count (cells/µL), and HIV transmission risk factors (men who have sex with men, intravenous drug use, heterosexual sex, and other/unknown) was collected from the DC Cohort database. Measures of internalized stigma, mental health, and ART adherence were generated from the self-reported PROs survey, and all surveys completed from May 1, 2021, to September 1, 2022, were included in the analysis. Responses from the PROs survey were then linked to the participant's DC Cohort data, and surveys that could not be linked were excluded from the analysis.

Measures

Demographic measures, including race/ethnicity, age, and time since HIV diagnosis were taken from data available in the electronic health record. As we did not have self-reported gender identity, we defined gender based on available information in the electronic health record. Participants with female, male, transgender male-to-female, and transgender female-to-male in their electronic health record are further referred to here as women, men, transgender women, and transgender men.

To measure internalized stigma, we used a four-item instrument that asked participants to respond to the following statements regarding HIV: “Having HIV makes me feel like I am a bad person,” “Having HIV is disgusting to me,” “I feel ashamed of having HIV,” and “I think less of myself because I have HIV.” This four-item instrument has been used previously in the literature and has been shown to have high reliability with a Cronbach's alpha of 0.91.²⁵ It was originally adopted from a six-item scale developed by Earnshaw et al.²⁶ For each statement, participants were asked to respond using a Likert scale, and each response was given a score based on that scale (higher score = more agreement to the statement). The scores for each item were then averaged for each participant, resulting in that participant's stigma score. This stigma score could range from 1 to 5, with higher scores referring to higher levels of internalized stigma.

Generalized anxiety disorder (GAD) symptoms were measured using a seven-item anxiety scale (GAD-7) in which participants responded to how often they felt various symptoms of anxiety.²⁷ The scale has been previously validated and found to be highly reliable, with a Cronbach's alpha of 0.92.²⁷ The seven-item scores were then summed to calculate the overall GAD score for each participant. The GAD score could range from 0 to 21; higher scores are referred to as higher levels of GAD. Scores less than or equal to 4 were categorized as no GAD, scores greater than 4 but less than or equal to 9 were considered mild GAD symptoms, scores greater than 9 but less than or equal to 14 were considered moderate GAD symptoms, and scores greater than 14 were considered severe GAD symptoms.²⁷

Similarly, depressive symptoms were measured using an eight-item Patient Health Questionnaire (PHQ-8) in which participants responded to how often they felt various depressive symptoms.²⁸ This scale has previously been shown to be highly reliable, with a Cronbach's alpha of 0.89.²⁸ The responses to each item were scored and summed. Depression scores could range from 0 to 24, with higher scores corresponding to a higher frequency of feeling depressive symptoms. Participants with depression scores of 10 or higher were considered to have depressive symptoms.²⁸

Finally, participants were also asked how many doses of their HIV medications they had missed in the past 14 days. Individuals who said they had not missed any doses were considered adherent to their ARV medications for the 2 weeks prior.

Descriptive Statistics

We examined basic demographics for each participant, as well as various HIV-related factors, such as HIV viral suppression (copies/mL), CD4 counts (cells/µL), and ART adherence. Specifically, we examined age, race/ethnicity (Non-Hispanic Black, Hispanic, Non-Hispanic White, and other/unknown), gender (woman, man, transgender woman, transgender man), type of site where the participant took the survey (hospital vs community), and HIV transmission risk factor (men who have sex with men, intravenous drug use, heterosexual sex, and other/unknown). GAD symptoms and depressive symptoms scale results were presented both continuously and also categorized using standard clinical cutpoints as described above. We measured the participants’ mean stigma score and examined the distribution of responses to each of the four stigma items. Cronbach's alpha was calculated to examine the reliability between the four items.

Comparison of PROs Participants to Non-Participants

Research Associates were asked to record the race/ethnicity and sex of people approached for a PROs survey but refused participation. To evaluate potential bias, we compared the characteristics of PROs participants to those who were approached but refused to participate. Specifically, we compared the gender, race/ethnicity, and site type of participants to non-participants using chi-square tests.

Linear Regression Models

Using unadjusted linear regressions, we examined crude associations between stigma score and different covariates. To allow for more flexibility in the model, we modeled depressive and GAD symptoms on a continuous scale and evaluated potential multicollinearity between the two variables. We also tested for non-linear associations by including a quadratic term for GAD score, depression score, age, and time since HIV diagnosis. Of these, only GAD score showed a significant non-linear relationship.

Finally, we evaluated potential interactions between gender and each significant covariate from the unadjusted models. To reduce Type 1 statistical error, only interactions between gender and significant covariates were evaluated. The final multivariable linear regression model included significant covariates and interaction terms. A reduced model with no interaction terms was compared to the full model with significant interaction terms for goodness of fit (AIC, BIC, and R²). All statistical tests were conducted at a 0.05 significance level, and SAS 9.4 [SAS, Cary, NC, USA] was used for all analyses.

Results

Demographics

In total, 800 individuals completed a PROs survey as of September 1, 2022, of which 724 could be linked to a DC Cohort study ID. Of these 724 individuals, 694 completed all four stigma items and therefore were included in the final dataset. The median age was 56 (IQR: 46, 63) years, and 80.3% were non-Hispanic Black. Most participants were men (n = 490; 70.6%) while 27.5% were women (n = 191), 1.9% were transgender women (n = 13), and there were no transgender men. Thirty-nine percent (39.3%) of participants had mild, moderate, or severe GAD symptoms, and 21.2% had depressive symptoms, based on our PROs scales outlined above. The GAD scale in our sample had a Cronbach's alpha of 0.93 and the depression score had a Cronbach's alpha of 0.89, representing high internal consistency in our sample. The most common HIV transmission risk was men who have sex with men (44.0%) (Table 1).

Table 1.

Overview of Participant Demographics, Stratified by Gender. Note That Distributions Could not be Shown Among Transgender Women due to Small Cell Size.

Characteristic	Total participants	Men	Women
Characteristic	(N = 694)	(N = 490)	(N = 191)
Age (Median (IQR))	56 (46, 63)	57 (48, 64)	55 (45, 62)
Missing	1	0	1
Gender identity (n (%))
Man	490 (70.6)	490 (100.0)	0 (0.0)
Woman	191 (27.5)	0 (0.0)	191 (100.0)
Transgender woman	13 (1.9)	0 (0.0)	0 (0.0)
Race/ethnicity (n (%))
Non-Hispanic Black	517 (80.3)	340 (69.8)	167 (93.8)
Hispanic	27 (4.2)	20 (4.1)	6 (3.4)
Non-Hispanic White	88 (13.7)	83 (17.0)	4 (2.3)
Other	12 (1.9)	11 (2.3)	1 (0.6)
Missing	50	3	13
Sites (n (%))
Hospital sites	317 (45.7)	306 (62.5)	69 (36.1)
Community sites	377 (54.3)	184 (37.5)	122 (63.9)
GAD symptoms (n (%))
None (Score ≤ 4)	421 (60.7)	297 (60.6)	118 (61.8)
Mild (4 < Score ≤ 9)	164 (23.6)	117 (23.9)	41 (21.5)
Moderate (9 < Score ≤ 14)	61 (8.8)	39 (8.0)	22 (11.5)
Severe (Score > 14)	48 (6.9)	37 (7.6)	10 (5.2)
GAD score (Median (IQR))	3 (0, 7)	3 (0, 7)	3 (0, 7)
Depressive symptoms (n (%))
Has depressive symptoms (Score < 10)	147 (21.2)	103 (21.0)	41 (21.5)
No depressive symptoms (Score ≥ 10)	546 (78.8)	387 (79.0)	150 (78.5)
Depression score (Median (IQR))	4 (1, 8)	4 (1, 8)	4 (1, 9)
Missing	1 (0.1)	0	1
HIV risk (n (%))
Men who have sex with men	305 (44.0)	298 (60.9)	0 (0.0)
Intravenous drug use	41 (5.9)	29 (5.9)	12 (6.3)
Heterosexual sex	211 (30.4)	85 (17.4)	126 (66.0)
Other/Unknown	136 (19.6)	77 (15.7)	53 (27.7)
Missing	1	1	0
Viral suppression (n (%)) ^a	635 (91.9)	457 (93.5)	167 (88.4)
Missing	3	1	2
CD4 counts (n (%)) ^a
≥ 500 cells/µL	485 (70.1)	330 (67.6)	143 (74.9)
201–499 cells/µL	173 (25.0)	134 (27.5)	38 (19.9)
≤ 200 cells/µL	34 (4.9)	24 (4.9)	10 (5.2)
Missing	2	2	0
Self-reported adherence to ART (n (%))	450 (66.6)	317 (66.0)	124 (67.4)
Missing	18	10	1
Years since HIV diagnosis (Median (IQR))	19 (13, 26)	19.5 (12.5, 26)	17 (13, 25)
Missing	3	2	1
Stigma score (Median (IQR))	1.8 (1,3)	1.8 (1, 3)	1.5 (1, 3)

GAD = generalized anxiety disorder; ^aParticipants were considered virally suppressed if the viral load test taken on the date closest to completion of the PROs survey had a result of less than 200 copies/mL.

PRO = patient-reported outcomes.

In addition to the 694 participants, there were 142 DC Cohort enrollees who were approached but refused to participate. Participants differed in race/ethnicity, site of recruitment, and gender from those who refused. Specifically, 30.6% of patients approached at community sites refused to participate, while only 0.5% of patients approached at a hospital site refused to participate. None of the refusals were non-Hispanic White, while 16.8% of Black patients and 10.0% of Hispanic patients who were approached chose not to participate. Only 51.3% of refusals were men, while 72.5% of the PROs participants were men. An overview of the comparison between participants and refusals can be found in Supplemental Table 2.

Evaluation of Internalized Stigma

The frequency of responses to each HIV item can be found in Table 2. The item “I feel ashamed of having HIV” was the most commonly agreed to item (199 (28.7%) agreed). Based on our sample data, both the raw and standardized Cronbach alpha were 0.90 for the entire four-item scale, representing high internal consistency. An overview of item correlations can be found in Supplemental Table 1. The mean stigma score, which can range from 1 to 5, was 2.1 (± 1.1), and the median was 1.8 (1, 3). An overview of the distribution of the stigma score is shown in Figure 1.

Figure 1.

Histogram showing the distribution of stigma scores among participants, calculated by taking the average of each individual’s responses to each of the four items in our scale (1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = strongly agree). Higher stigma scores refer to higher levels of internalized stigma.

Table 2.

Proportion and Percent (%) of Participant Responses to Each Stigma Item.

Item	Strongly disagreeN (%)	DisagreeN (%)	NeitherN (%)	AgreeN (%)	Strongly agreeN (%)
“Having HIV makes me feel like I am a bad person.”	397 (57.2)	129 (18.6)	84 (12.1)	60 (8.7)	24 (3.5)
“Having HIV is disgusting to me.”	376 (54.2)	114 (16.4)	101 (14.6)	70 (10.1)	33 (4.8)
“I feel ashamed of having HIV.”	304 (43.8)	92 (13.3)	99 (14.3)	123 (17.7)	76 (11.0)
“I think less of myself because I have HIV.”	368 (53.0)	112 (16.1)	77 (11.1)	95 (13.7)	42 (6.1)

Crude Associations

We examined the crude associations between various factors and the continuous measure of stigma score using simple linear regression. A comprehensive list of these factors can be found in Table 3. A 10-year increase in age and time since HIV diagnosis were inversely related to a higher mean stigma score (Age (95% CI): −0.20 (−0.30, −0.10); time since HIV diagnosis (95% CI): −0.30 (−0.40, −0.20). Furthermore, GAD and depression score were directly related to a higher mean stigma score and GAD score had a significant squared term, meaning this association is significantly non-linear. No other covariates were significantly associated with stigma score in unadjusted analyses. All parameter estimates can be found in Table 3.

Table 3.

Associations Between Participant Characteristics and Stigma Score, Calculated Through Simple Linear Regression.^a

Characteristic	Crude parameter estimate (95% CI)	Adjusted parameter estimate (95% CI)^b
Gender
Woman	REF	REF
Man	−0.01 (−0.20, 0.18)	−1.17 (−2.02, −0.31)
Transgender woman	−0.11 (−0.76, 0.53)	0.24 (−2.62, 3.10)
Race/ethnicity		N/A
Non-Hispanic White	REF
Non-Hispanic Black	−0.19 (−0.44, 0.07)
Hispanic	−0.01 (−0.51, 0.48)
Other	0.10 (−0.59, 0.79)
Age (10 year Increase)	−0.20 (−0.30, −0.10)	−0.20 (−0.30, −0.10)
Time since HIV diagnosis (10 year Increase)	−0.30 (−0.40, −0.20)	−0.20 (−0.30, −0.10)
ART adherence		N/A
Not adherent	REF
Adherent	−0.15 (−0.33, 0.03)
Depression score (1 unit increase)	0.07 (0.06, 0.09)	0.02 (−0.01, 0.04)
Generalized anxiety disorder score (1 unit increase)
Score	0.16 (0.12, 0.20)	0.12 (0.08, 0.17)
Score-squared	−0.005 (−0.007, −0.002)	−0.004 (−0.006, −0.001)
HIV risk		N/A
Men who have sex with men	REF
Heterosexual sex	−0.02 (−0.22, 0.18)
Intravenous drug use	−0.06 (−0.44, 0.31)
Other/unknown	0.08 (−0.15, 0.32)
Viral labs (cells/mL)		N/A
Not virally suppressed	REF
Virally suppressed	−0.14 (−0.45, 0.17)
CD4 labs (cells/µL)		N/A
Mild	REF
Moderate	−0.10 (−0.29, 0.10)
Severe	0.05 (−0.34, 0.45)
Interaction terms	N/A
Age (10 year Increase)*Woman		REF
Age (10 year Increase)*Man		0.20 (0.10, 0.40)
Age (10 year Increase)*Transgender Woman		−0.10 (−0.70, 0.50)

^aHigher stigma scores refer to higher levels of internalized stigma.

^bAdjusted model included: gender, age, time since HIV diagnosis, depression score, GAD score, and the interaction terms between gender & age.

GAD = generalized anxiety disorder.

For each characteristic in Table 3, an additional linear regression model was run by adding two cross-product terms for the three gender categories. The interaction term between age & man versus woman was significant in the unadjusted model (P = 0.033). While age was associated with a lower stigma score among all gender identities, the magnitude of this relationship differed across gender identities. Among women, an older age was associated with a lower stigma score, but the relationship was weaker among men (Figure 2). The relationship between age and stigma among transgender women could not be determined due to small sample size (n = 13). No other interactions between gender and significant covariates were found.

Figure 2.

Crude fitted linear regression slopes showing the relationship between age and stigma score among different gender identities. Higher stigma scores refer to higher levels of internalized stigma. The relationship between age and stigma could not be evaluated among transgender women due to small sample size (n = 13).

Multivariable Linear Regression Model

Our final model consisted of the following covariates: (1) age, (2) depression score, (3) gender, (4) years since HIV diagnosis, and (5) GAD score (with the quadratic term). The model fit statistics suggested the model including the interaction term between age and gender was a better fit (Full Model R² = 0.204, AIC = 45.19, BIC = 47.48; Reduced Model R² = 0.194, AIC = 49.91, BIC = 52.10). Therefore, the interaction term between age and gender was retained in the final adjusted model. In the model, the relationship between stigma and depression score was no longer significant after controlling for other covariates (0.02 (95% CI: −0.01, 0.04)). The inverse relationship between years since HIV diagnosis and stigma score remained significant. Gender identity and age were significantly associated with level of stigma score. However, the interaction term for men and age in this adjusted analysis showed no association between age and internalized stigma among men after adjusting for other covariates. Among women, a 10-year increase in age was associated with, on average, a −0.20 (95% CI: −0.30, −0.10) lower stigma score (Table 3). The relationship between age and stigma could not be evaluated among transgender women due to small sample size (n = 13).

Discussion

We aimed to characterize internalized stigma among PWH in Washington, DC, and evaluate whether gender modifies the relationship between stigma and significant covariates. We found a moderately low level of internalized stigma among participants in our analysis, aligning with findings from previous studies.^25,29 Even with the moderately low overall stigma score, almost 30% of participants agreed with the item “I feel ashamed of having HIV.” This suggests shame may be a prevalent and important component of internalized stigma among our participants. Interventions that focus on reducing shame, such as acceptance and commitment therapy or identity reconstruction, should be prioritized to reduce the experience of stigma among PWH in urban regions. These interventions involve resisting social norms to reconstruct one's self-identity and examining the internal verbal processes that lead to internalized stigma.^30,31

We sought to evaluate whether gender was an effect modifier of the relationship between different covariates and internalized stigma and found that gender modifies the association between age and stigma. Specifically, increased age was associated with lower stigma among women, but not among men. These findings were in contrast to our original hypothesis that the association between individual-level factors and internalized stigma would be stronger among men, suggesting that effect modification by gender may differ across factors being evaluated. No other significant covariate interactions with gender were found. In prior studies, different relationships between gender, age, race, and stigma have been reported. Women have historically reported higher levels of stigma internalization compared to men, as well as higher rates of enacted stigma in their daily lives.^5,22 One study found gender was a modifier of the relationship between race/ethnicity and stigma.^17,32 These findings show the complex role gender may be playing in the experience of stigma and how methods of reducing internalized stigma may need to be gender-specific.

There are several reasons gender may be playing a modifying role in the association between age and stigma. As mentioned previously, the impacts of social support on HIV-related outcomes differ between men and women.^20,21 The impact of social support on stigma has also been found to be modified by age.³³ Therefore, the relationship between age, gender, and stigma found here could be related to how social support impacts stigma overall. A previous study among PWH in South Africa found specific aspects of social capital related to empowerment, trust, and group membership were important in reducing internalized stigma.³⁴ This shows social capital can be a significant contributor to internalized stigma. A prior exploration of the development of social capital as people age found significant differences by gender in that women gain more social capital through occupational contacts as they age, while men's occupational contacts remain consistent or even decline.³⁵ Another study by Eriksson and Ng similarly found that the association between several aspects of social capital had a stronger impact on self-rated health among women then among men.³⁶ It is also well-established that there are significant gender differences in the creation of social capital and, ultimately social support.¹⁸ Each of these findings combined showed the complicated relationship between gender, age, and social capital that may be ultimately impacting the relationship with internalized stigma found in our study. In addition to the relationship between age, gender, and internalized stigma, we also found that a shorter time since HIV diagnosis and higher GAD score were associated with increased internalized stigma. Depression score was associated with increased stigma in the unadjusted model but was no longer significant in the adjusted model. This could suggest that the association between depression score and stigma was due to the correlation between depression and anxiety, or that the association is representative of the impact of general mental health on internalized stigma. Previous studies have also found a link between stigma and mental health, especially for depressive symptoms^9,37–42. However, our analysis modeled GAD score using a quadratic term, which may have been advantageous in elucidating the true nature of the relationship between GAD score and internalized stigma. Future studies should evaluate whether GAD alone, or a broader definition of mental health conditions may be associated with internalized stigma among PWH. A better understanding of the specific mental health conditions that may be associated with internalized stigma can help inform how mental health treatment could have an indirect impact on reducing internalized stigma.

As mentioned previously, we found increased time since diagnosis was associated with lower internalized stigma. Studies have previously found that newly diagnosed PWH demonstrate increased levels of anxiety and depression. These mental health outcomes are made worse by internalized stigma, which may explain the relationship we found here.⁴³ Furthermore, this measure of time since diagnosis may serve as a proxy for coping strategies and community support. As time passes since an individual's initial diagnosis, that individual may have more opportunity to find community and develop healthy coping mechanisms. This sense of community and increased coping may ultimately lower the level of internalized stigma for PWH.⁴⁴ If years since HIV diagnosis is a proxy for community and coping strategies, our results suggest that earlier introductions to community and coping resources may reduce stigma in newly diagnosed individuals.

This study had several limitations. First, we only had 13 participants who identified as transgender. Due to this small sample size, there is a high degree of uncertainty for estimates among participants in this group and the interaction between transgender woman gender identity and each covariate could not be accurately evaluated. Furthermore, we used all available data at the time of analysis and did not complete any pre-analysis sample size calculations. Therefore, there may be limitations with analytic power. Then, the cross-sectional nature of our survey was a limitation. Participants filled out the PROs survey questions at one time point and there is no way to discern the temporality of relationships in our model. Additionally, participants were a consenting subset of overall DC Cohort participants who filled out the PROs survey during a care provider visit. PWH who have more support or coping strategies may be more engaged in care and may have been more inclined to consent and participate in the PROs subset study. Then, the demographics of the PROs participants differed from those that refused to participate. Given these differences, it is possible that those who refused also had a different experience of stigma than those who consented, potentially introducing selection bias and limiting the generalizability of our findings.

Furthermore, GAD and depression score, as well as time since HIV diagnosis and age, were correlated with each other. However, upon evaluation of multicollinearity using the variance inflation factor and condition indices, we found that collinearity diagnostics did not suggest these variables were contributing substantially to multicollinearity in our model. Despite these findings, the correlations between these variables may have introducing instability to our model. Finally, while we focused on the interaction between gender and each significant covariate, our statistical model does not capture the intersectionality between each social identity of an individual participant and is an oversimplification of the diversity of individual experiences that may lead to internalized stigma.⁴⁵ Future studies should evaluate the intersectionality between gender identity, stigma, and each social identity to fully understand the impact of gender on internalized stigma among PWH.

Conclusion

We examined internalized stigma among DC Cohort participants to determine factors associated with stigma and evaluate whether gender is an effect modifier of the relationship between covariates and stigma. Overall, we found that our average stigma score was moderately low, and more participants agreed with the statement “I feel ashamed of having HIV” than any other item. Older age was associated with lower stigma scores among our study participants, but this trend was modified by gender. An increase in the time since HIV diagnosis and GAD score was also associated with the level of internalized stigma in the adjusted models. Future research should focus on determining the causal relationships between these factors and internalized stigma and examining the intersectionality between participant characteristics, gender identity, and stigma. Younger PWH, especially women, newly diagnosed PWH, and PWH who have GAD symptoms, should be targeted for interventions aimed at reducing internalized stigma among PWH.

Supplemental Material

sj-docx-1-jia-10.1177_23259582251370561 - Supplemental material for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender

Supplemental material, sj-docx-1-jia-10.1177_23259582251370561 for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender by Lauren F. O’Connor, Jenna B. Resnik, Morgan Byrne and Patricia E. Houston, Sam Simmens, Amanda D. Castel, Sohail Rana, Anne K. Monroe, in Journal of the International Association of Providers of AIDS Care (JIAPAC)

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Supplemental material, sj-tiff-2-jia-10.1177_23259582251370561 for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender by Lauren F. O’Connor, Jenna B. Resnik, Morgan Byrne and Patricia E. Houston, Sam Simmens, Amanda D. Castel, Sohail Rana, Anne K. Monroe, in Journal of the International Association of Providers of AIDS Care (JIAPAC)

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sj-tiff-3-jia-10.1177_23259582251370561 - Supplemental material for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender

Supplemental material, sj-tiff-3-jia-10.1177_23259582251370561 for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender by Lauren F. O’Connor, Jenna B. Resnik, Morgan Byrne and Patricia E. Houston, Sam Simmens, Amanda D. Castel, Sohail Rana, Anne K. Monroe, in Journal of the International Association of Providers of AIDS Care (JIAPAC)

Supplemental Material

sj-tiff-4-jia-10.1177_23259582251370561 - Supplemental material for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender

Supplemental material, sj-tiff-4-jia-10.1177_23259582251370561 for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender by Lauren F. O’Connor, Jenna B. Resnik, Morgan Byrne and Patricia E. Houston, Sam Simmens, Amanda D. Castel, Sohail Rana, Anne K. Monroe, in Journal of the International Association of Providers of AIDS Care (JIAPAC)

Footnotes

Acknowledgements

Data in this manuscript were collected by the DC Cohort Study Group with investigators and research staff located at: Children's National Hospital Pediatric clinic (Natella Rakhmanina); the Senior Deputy Director of the DC Department of Health HAHSTA (Clover Barnes); Family and Medical Counseling Service (Rita Aidoo); Georgetown University (Princy Kumar); The George Washington University Biostatistics Center (Tsedenia Bezabeh, Vinay Bhandaru, Asare Buahin, Nisha Grover, Lisa Mele, Susan Reamer, Alla Sapozhnikova, Greg Strylewicz, and Marinella Temprosa); The George Washington University Department of Epidemiology (Shannon Barth, Morgan Byrne, Amanda Castel, Alan Greenberg, Shannon Hammerlund, Paige Kulie, Anne Monroe, Lauren O'Connor, James Peterson, and Mark Storey) and Department of Biostatistics and Bioinformatics; The George Washington University Medical Faculty Associates (Jose Lucar); Howard University Adult Infectious Disease Clinic (Jhansi L. Gajjala) and Pediatric Clinic (Sohail Rana); Kaiser Permanente Mid-Atlantic States (Michael Horberg); La Clinica Del Pueblo (Ricardo Fernandez); MetroHealth (Duane Taylor); Washington Health Institute, formerly Providence Hospital (Jose Bordon); Unity Health Care (Gebeyehu Teferi); Veterans Affairs Medical Center (Debra Benator and Rachel Denyer); Washington Hospital Center (Adam Klein); and Whitman-Walker Institute (Stephen Abbott). Thank you to all of our DC Cohort participants.

ORCID iDs

Lauren F. O’Connor

Jenna B. Resnik

Morgan Byrne

Sam Simmens

Amanda D. Castel

Anne K. Monroe

Ethics Approval and Informed Consent

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of George Washington University (IRB#: 071029). Informed consent was obtained from all participants involved in the study.

Author Contributions

LFO contributed to the conceptualization, design, analysis, statistical software, interpretation of results, and draft of the manuscript. JBR contributed to the interpretation of results and draft of the manuscript. MB contributed to the analysis, statistical software, interpretation of results, and draft of the manuscript. PEH contributed to the data acquisition, conceptualization, interpretation of results, and draft of the manuscript. SS contributed to the design, analysis, statistical software, interpretation of results, and draft of the manuscript. ADC contributed to the data acquisition, conceptualization, design, interpretation of results, and draft of the manuscript. SR contributed to the conceptualization, interpretation of results, and draft of the manuscript. AKM contributed to the data acquisition, conceptualization, design, analysis, interpretation of results, and draft of the manuscript. All authors read and approved the final manuscript.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this publication was supported by the National Institute Of Allergy And Infectious Diseases of the National Institutes of Health under Award Number R24AI152598. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The Milken Institute School of Public Health Research Innovation Award provided funding support for the Patient Reported Outcomes Survey.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability

Per DC Cohort protocols, data are available upon request and approval of the DC Cohort Executive Committee. Interested parties should email the Principal Investigator at acastel@gwu.edu.

Supplemental Material

Supplemental material for this article is available online.

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Supplementary Material

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A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington,DC: Evaluating Modification by Gender

Abstract

Objectives

Methods

Results

Conclusions

Plain Lanugage Summary

Keywords

Introduction

Materials and Methods

Data Collection

Measures

Descriptive Statistics

Comparison of PROs Participants to Non-Participants

Linear Regression Models

Results

Demographics

Evaluation of Internalized Stigma

Crude Associations

Multivariable Linear Regression Model

Discussion

Conclusion

Supplemental Material

sj-docx-1-jia-10.1177_23259582251370561 - Supplemental material for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender

Supplemental Material

sj-tiff-2-jia-10.1177_23259582251370561 - Supplemental material for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender

Supplemental Material

sj-tiff-3-jia-10.1177_23259582251370561 - Supplemental material for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender

Supplemental Material

sj-tiff-4-jia-10.1177_23259582251370561 - Supplemental material for A Cross-Sectional Study of Risk Factors for Internalized Stigma among People with HIV in Washington, DC: Evaluating Modification by Gender

Footnotes

Acknowledgements

ORCID iDs

Ethics Approval and Informed Consent

Author Contributions

Funding

Declaration of Conflicting Interests

Data Availability

Supplemental Material

References

Supplementary Material