Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Apr 14.
Published in final edited form as: J Adolesc. 2024 Mar 15;96(5):1048–1064. doi: 10.1002/jad.12315

Emotion regulation as a potential moderator of the association between HIV stigma and nonadherence to antiretroviral therapy among youth living with HIV

John Mark Wiginton 1, K Rivet Amico 2, Lisa Hightow-Weidman 3, Patrick Sullivan 4, Keith J Horvath 5
PMCID: PMC13076064  NIHMSID: NIHMS2155377  PMID: 38488698

Abstract

Introduction:

Human immunodeficiency virus (HIV)-related stigma affects adherence to antiretroviral therapy (ART) for youth living with HIV. Emotion regulation strategies such as cognitive reappraisal (reinterpreting adversity to mitigate emotional impact) and expressive suppression (inhibiting emotion-expressive behavior activated by adversity) may moderate the HIV stigma-ART adherence relationship in this group.

Methods:

Using baseline data from 208 youth living with HIV aged 15–24 years enrolled in an mHealth ART-adherence intervention, we performed modified Poisson regressions with robust variance between HIV stigma (internalized, anticipated, enacted) and ART nonadherence. We tested for multiplicative interaction via product terms between HIV stigma and emotion regulation scores, and additive interaction via relative excess risk due to interaction and attributable proportion using dichotomous HIV stigma and emotion regulation variables.

Results:

Mean age was 21 years; ≥50% of participants were cisgender male, non-Hispanic Black, and gay-identifying; 18% reported ART nonadherence. Confounder-adjusted regressions showed positive associations between each HIV stigma variable and ART nonadherence. Internalized HIV stigma and cognitive reappraisal negatively, multiplicatively interacted (as internalized HIV stigma increased, ART nonadherence increased for those with low cognitive reappraisal). High internalized HIV stigma positively, additively interacted with low cognitive reappraisal and low expressive suppression (when high internalized HIV stigma and low levels of either emotion regulation strategy were present, ART nonadherence increased dramatically).

Conclusion:

Cognitive reappraisal and expressive suppression may protect against internalized HIV stigma’s harmful association with ART nonadherence. These modifiable emotion regulation strategies may be targeted to potentially buffer the effects of internalized HIV stigma and support ART adherence for youth living with HIV.

Keywords: ART adherence, emotion regulation, HIV stigma, youth living with HIV

1 |. INTRODUCTION

Human immunodeficiency virus (HIV) continues to disproportionately impact young people in the United States, particularly minority youth aged 13–24 years (Allan-Blitz et al., 2021). In 2019, 21% of new HIV infections were among this age group (CDC, 2021a); moreover, 20% of youth living with HIV received no HIV care, 41% were not retained in care, and 37% were not virally suppressed (CDC, 2021b). Those aged 18–24 years (data for those <18 years unavailable) had the highest level of 30-day antiretroviral therapy (ART) nonadherence (62%) across age groups (CDC, 2020). ART adherence remains the cornerstone of living long and well with HIV and contributes to HIV prevention efforts. Supporting youth living with HIV achieve and maintain optimal ART adherence is critical to their health and development and aligns with goals of Ending the HIV epidemic in the United States (HHS, 2020).

Stigma related to positive HIV status remains among the most consequential factors affecting ART adherence for youth living with HIV (CDC, 2020; Robinson et al., 2023). Stigma refers to the process by which society designates and views certain attributes (e.g., positive HIV status) and possessors of those attributes (e.g., people living with HIV) as negative and undesirable, sanctioning a certain degree of mistreatment toward those individuals as a result (Goffman, 1963). The HIV Stigma Framework articulates how stigma related to HIV status in particular operates to impact health outcomes, including HIV outcomes, through internalized (i.e., the adoption of society’s negative views toward those with HIV and turning those views inward, toward oneself), anticipated (i.e., expectation of mistreatment due to positive status), and enacted mechanisms (i.e., overt mistreatment, such as discrimination or violence, due to positive status) (Earnshaw & Chaudoir, 2009; Earnshaw et al., 2013). Indeed, research has shown internalized, anticipated, and enacted HIV stigma to be negatively associated with ART adherence for youth living with HIV (Amico et al., 2021; Gillette et al., 2023; Kerrigan & Barrington, 2018; Mugo et al., 2023; Mutwa et al., 2013; Sibinga et al., 2022).

One of the primary mechanisms through which HIV stigma operates to affect ART adherence is related to mental health and emotional wellbeing. Qualitative research has documented the various distressing emotions that arise in the face of HIV stigma and how those emotions affect HIV care and treatment, including ART adherence (Robinson et al., 2023). Likewise, quantitative findings have linked HIV stigma to multiple mental health concerns, like depression and anxiety, which also affect ART adherence (Felker-Kantor et al., 2019; Hatzenbuehler et al., 2011; Hernandez et al., 2018; Logie & Gadalla, 2009; Meyers-Pantele et al., 2022; Sayles et al., 2009).

HIV stigma’s connections with ART adherence, mental health, and emotional wellbeing have motivated the development of interventions that foster resilience, support coping, and address mental health among youth living with HIV (Crowley & Rohwer, 2021; Laurenzi et al., 2022; Okonji et al., 2020). However, the regulation of emotions has been inadequately measured and evaluated in these efforts. Emotion regulation refers to the processes by which individuals influence which emotions they have, when they have these emotions, and how they experience and express these emotions (Gross et al., 1998). Ideally, individuals learn to rely on themselves (as opposed to caregivers) to regulate their emotions during childhood and adolescence, and observational learning is critical in the adoption and utilization of specific emotion regulation strategies (Morris et al., 2007). There are several types of emotion regulation strategies, including those involving cognitive change (i.e., choosing a meaning to attach to a situation or experience), and those involving response modulation (i.e., attempting to influence emotion response tendencies once they have already been elicited), among others (Gross, 1998, 2002). Two of the most commonly investigated strategies include cognitive reappraisal, which is a cognitive change strategy focused on reinterpreting the meaning or self-relevance of an emotion-eliciting situation, and expressive suppression, which is a response modulation strategy focused on inhibiting emotion-expressive behavior (Gross, 2002, 2015). Cognitive reappraisal tends to positively impact physical and mental wellbeing, and expressive suppression tends to do the opposite (Dryman & Heimberg, 2018; Koechlin et al., 2018; Mathur et al., 2022).

In addition to social and biological changes, adolescence and the transition to adulthood involve cognitive and psychological changes, including acquisition and cultivation of emotion regulation strategies (Gruhn & Compas, 2020; Silvers, 2022). For youth living with HIV, learning and utilizing healthy, adaptive emotion regulation strategies may optimize management of both HIV care and the effects of HIV stigma. DeSteno et al.’s (2013) affective science and health framework suggests that emotion regulation strategies can affect health directly as well as indirectly through various intermediary constructs such as coping effectiveness, decision-making, social support, memory, and emotional wellbeing (DeSteno et al., 2013). For youth living with HIV, ineffective or maladaptive regulation of distressing emotions in response to HIV stigma could underlie or contribute to difficulties adhering to ART. However, emotion regulation’s role in the HIV stigma-ART adherence relationship has been minimally examined.

The objectives of this study were to assess the extent to which cognitive reappraisal and expressive suppression interact with internalized, anticipated, and enacted HIV stigma to modify their effects on ART nonadherence among youth living with HIV. We hypothesized that cognitive reappraisal would negatively interact with each form of HIV stigma (i.e., risk for nonadherence associated with HIV stigma is attenuated in the presence of cognitive reappraisal), and that expressive suppression would positively interact with each form of HIV stigma (i.e., risk for nonadherence associated with HIV stigma is increased in the presence of expressive suppression). Findings may lead to new areas of inquiry for research and intervention development for youth living with HIV struggling to adhere to ART.

2 |. MATERIALS AND METHODS

2.1 |. Data source, participants, and procedures

Data were drawn from a baseline assessment of youth living with HIV enrolled in a randomized controlled trial of a web-based intervention called “YouTHrive,” which aimed to improve ART adherence and HIV treatment outcomes among youth living with HIV in six urban areas across the United States (Atlanta, Chicago, Houston, New York, Philadelphia, and Tampa). Detailed methods have been described elsewhere (Horvath et al., 2019). Briefly, individuals who met the following criteria were eligible to participate: aged 15–24 years at enrollment; living with HIV; residing in one of the aforementioned six urban areas with availability to meet in-person for baseline and follow-up visits (in-person clause was pre-COVID-19 only); had documentation of currently prescribed ART; English-speaking; expected to have continuous internet access and SMS messaging for the intervention period; had an email address to use during the study period (or were willing to create one); not a member of an iTech Youth Advisory Board; and not enrolled in another ART adherence intervention research study. Before the onset of the COVID-19 pandemic, there was one additional eligibility criterion (which ultimately applied to roughly one third of participants who enrolled before the pandemic): through medical chart verification or self-report, participants had to have a detectable viral load test result in the past 12 months while on ART for at least 3 months; at least one missed HIV care appointment in the past 12 months; no HIV care visit in the past 6 months; or less than 90% ART adherence in the previous 4 weeks.

Eligible participants were recruited from HIV clinics or through community outreach (e.g., targeted social media advertisements) and completed an online baseline survey on HIV treatment and related outcomes (e.g., ART regimen, self-reported adherence), mental health (e.g., emotion regulation), HIV stigma, sociodemographic characteristics, and other domains via a computer-assisted survey instrument. Participants received $50 for completing the survey.

2.2 |. Measures

2.2.1 |. ART adherence

ART adherence was assessed with the following visual analog scale item: “Click on the line at the point showing how much of your HIV antiretroviral medications you have taken in the past 4 weeks (0%–100%)” (Amico et al., 2006; Giordano et al., 2004; Oyugi et al., 2004; Walsh et al., 2002). Response options were in 10% increments. We dichotomized at 80%, with 80% or higher indicative of adherence and below 80% indicative of nonadherence. We selected this benchmark given recent evidence that a threshold of 80% is comparable to higher thresholds in leading to HIV viral suppression (Bezabhe et al., 2016; Byrd et al., 2019; O’Halloran Leach et al., 2021).

2.2.2 |. HIV stigma

Items developed by Earnshaw and colleagues were used to assess HIV-related stigma (Earnshaw & Chaudoir, 2009; Earnshaw et al., 2013). In response to the same prompt (How do you feel about being HIV positive?), internalized HIV stigma was assessed with six items (e.g., Having HIV makes me feel like I am a bad person.) on a 5-point Likert scale, ranging from strongly disagree (1) to strongly agree (5). Likewise, following the same prompt (How likely is it that people will treat you in the following ways in the future because of your HIV status?), anticipated HIV stigma was assessed with nine items (e.g., Family members will avoid me.) on a 5-point Likert scale, ranging from very unlikely (1) to very likely (5). Similarly, in response to the same prompt (How often have people treated you this way in the past because of your HIV status?), enacted stigma was assessed with nine items (e.g., Community/social workers have denied me services.) on a 5-point Likert scale, ranging from never (1) to very often (5). Internal consistency was excellent for internalized (α = .92), anticipated (α = .94), and enacted HIV stigma (α = .95) in our sample.

As ordinal variables, each scale was summed and averaged for each participant (range = 1–5), with higher scores indicative of greater internalized and anticipated stigma, and more frequently encountered enacted stigma. As dichotomous variables, for internalized and anticipated HIV stigma, a cutoff score of 4 was selected a priori (i.e., a score of 4–5 was coded 1, for high; a score below 4 was coded 0, for low). This cutoff separated those whose average score indicated agreement with, that is, endorsement of, internalized or anticipated HIV stigma (≥4), from those whose average score indicated neutrality or disagreement (score < 4). For enacted HIV stigma, a cutoff score of 2 was selected a priori (i.e., a score above 2 was coded 1, for often-enacted HIV stigma; a score of 2 or less was coded 0, for never or infrequent enacted HIV stigma). This cutoff separated those whose average score indicated often experiencing enacted stigma to some degree (>2; i.e., somewhat often, often, very often) from those whose average score did not indicate this (≤2, i.e., never or not often).

2.2.3 |. Emotion regulation

Emotion regulation was assessed with the 10-item Emotion Regulation Questionnaire (Gross & John, 2003), which is comprised of cognitive reappraisal and expressive suppression subscales. Cognitive reappraisal was assessed with six items (e.g., When I want to feel less negative emotion [such as sadness or anger], I change what I’m thinking about.) and expressive suppression with four items (e.g., I keep emotions to myself.) on a 7-point Likert scale, ranging from strongly disagree (1) to strongly agree (7). Internal consistency was adequate for cognitive reappraisal (α = .84) and expressive suppression (α = .75) in our sample. As ordinal variables, each subscale was summed and averaged for each participant (range = 1–7), with higher scores indicative of greater cognitive reappraisal or expressive suppression. As dichotomous variables, a cutoff score of 5 was selected a priori (i.e., a score of 5–7 was coded 1, for high; a score below 5 was coded 0, for low). This cutoff separated those whose average score indicated agreement with, that is, engagement in, a given emotion regulation strategy (≥5), from those whose average score indicated neutrality or disagreement/nonengagement (<5). This scale has been previously utilized in young adult and adolescent populations (e.g., Moore et al., 2008; Mouatsou & Koutra, 2021; Srivastava et al., 2009; Verzeletti et al., 2016; Wang et al., 2020).

2.2.4 |. Sociodemographic characteristics

Sociodemographic variables included age in years, gender identity, race/ethnicity, sexual identity, education status, employment status, relationship status, insurance status, and housing security (see Table 1 for more details).

TABLE 1.

Characteristics of youth living with HIV enrolled in an ART-adherence intervention in six US urban areas.

Total (N = 201) Adherent (n = 164, 81.6%) Nonadherent (n = 37, 18.4%)
Age (continuous)
 Mean (SD), median (IQR) 21.2 (2.3), 22 (20–23) 21.0 (2.3), 21.5 (19–23) 21.7 (1.9), 22 (21–23)
Z test statistic (p-value) - - −1.44 (.150)
Age group, n (%)
 15–17 15 (7.5) 14 (8.5) 1 (2.7)
 18–20 57 (28.4) 49 (29.9) 8 (21.6)
 21–24 129 (64.2) 101 (61.6) 28 (75.7)
χ2 test statistic (p-value) - - 3.04 (.219)
Gender identity, n (%)
 Cisgender man 137 (68.2) 112 (68.3) 25 (67.6)
 Cisgender woman 48 (23.9) 39 (23.8) 9 (24.3)
 Gender-diverse 15 (7.5) 12 (7.3) 3 (8.1)
  Transfeminine or transwoman 4 (2.0) 4 (2.5) 0 (0.0)
  Genderqueer 7 (3.5) 4 (2.5) 3 (8.1)
  Multiply-identifieda 4 (2.0) 4 (2.5) 0 (0.0)
 Missing/unknown 1 (0.5) 1 (0.6) 0 (0.0)
χ2 test statistic (p-value) - - 0.03 (.985)
Race/ethnicity, n (%)
 Non-Hispanic Black 121 (60.2) 98 (59.8) 23 (62.2)
 Non-Hispanic other 27 (13.4) 24 (14.6) 3 (8.1)
  White 9 (4.5) 9 (5.5) 0 (0.0)
  American Indian, Alaska Native 1 (0.5) 1 (0.6) 0 (0.0)
  Asian, Asian American 3 (1.5) 3 (1.8) 0 (0.0)
  Multiracial 11 (5.5) 9 (5.5) 2 (5.4)
  Other, unspecified 3 (1.5) 2 (1.2) 1 (2.7)
 Hispanic 46 (22.9) 35 (21.3) 11 (29.7)
  Black 7 (3.5) 7 (4.3) 0 (0.0)
  White 23 (11.4) 20 (12.2) 3 (8.1)
  American Indian, Alaska Native 6 (3.0) 4 (2.4) 2 (5.4)
  Native Hawaiian, Other Pacific Islander 1 (0.5) 0 (0.0) 1 (2.7)
  Multiracial 4 (2.0) 3 (1.8) 1 (2.7)
  Other, unspecified 5 (2.5) 1 (0.6) 4 (10.8)
 Ethnicity unknown/missing
  Black 2 (1.0) 2 (1.2) 0 (0.0)
  Asian, Asian American 1 (0.5) 1 (0.6) 0 (0.0)
  Multiracial 1 (0.5) 1 (0.6) 0 (0.0)
 Race/ethnicity missing/unknown 3 (1.5) 3 (1.8) 0 (0.0)
χ2 test statistic (p-value) - - 1.81 (.405)b
Sexual identity, n (%)
 Gay 100 (49.8) 79 (48.2) 21 (56.8)
 Bisexual 31 (15.4) 25 (15.2) 6 (16.2)
 Straight 53 (26.4) 45 (27.4) 8 (21.6)
 Other, multiply-identifiedc 14 (7.0) 12 (7.3) 2 (5.4)
 Missing/unknown 3 (1.5) 3 (1.8) 0 (0.0)
χ2 test statistic (p-value) - - 0.99 (.804)
Education, n (%)
 In school 107 (53.2) 91 (55.5) 16 (43.2)
 Not in school 92 (45.8) 71 (43.3) 21 (56.8)
 Missing/unknown 2 (1.0) 2 (1.2) 0 (0.0)
χ2 test statistic (p-value) - - 2.03 (.155)
Employment status, n (%)
 Employed 115 (57.2) 92 (56.1) 23 (62.2)
 Unemployed 82 (40.8) 70 (42.7) 12 (32.4)
 Missing/unknown 4 (2.0) 2 (1.2) 2 (5.4)
χ2 test statistic (p-value) - - 0.94 (.331)
Relationship status, n (%)
 Single 139 (69.2) 116 (70.7) 23 (62.2)
 Partnered 59 (29.4) 46 (28.0) 13 (35.1)
 Missing/unknown 3 (1.5) 2 (1.2) 1 (2.7)
χ2 test statistic (p-value) - - 0.84 (.36)
Insurance status, n (%)
 Insured 149 (74.1) 124 (75.6) 25 (67.6)
 Uninsured 37 (18.4) 29 (17.7) 8 (21.6)
 Missing/unknown 15 (7.5) 11 (6.7) 4 (10.8)
χ2 test statistic (p-value) - - 0.48 (.49)
Housing security, (%)
 Stably housed 149 (74.1) 128 (78.0) 21 (56.8)
 Unstable or disrupted housing 45 (22.4) 34 (20.7) 11 (29.7)
 Missing/unknown 7 (3.5) 2 (1.2) 5 (13.5)
χ2 test statistic (p-value) - - 2.69 (.101)
Open in a new tab

Abbreviations: ART, antiretroviral treatment; HIV, human immunodeficiency virus; IQR, interquartile range; SD, standard deviation; US, United States.

a

With two participants who identified as male and genderqueer and two who identified as genderqueer and transwoman.

b

Comparing non-Hispanic Black, non-Hispanic other, and Hispanic.

c

With six participants who identified as gay and bisexual, three who identified as bisexual and straight, three who identified as pansexual, one who identified as gynosexual, and one who identified as nonconforming.

2.3 |. Analysis

Descriptive statistics for variables of interest were calculated, after which normality of continuous variables (age, emotion regulation scores, HIV stigma scores) was assessed via Shapiro–Wilk tests. Differences in ART adherence by sociodemographic characteristics, emotion regulation variables, and HIV stigma variables were assessed with χ2 tests (for categorical variables), Wilcoxon rank sum tests (for nonnormally distributed continuous variables), and t-tests (for normally distributed continuous variables). Separate modified Poisson regressions with robust variance estimators were performed to determine associations between each HIV stigma variable and ART adherence. Sociodemographic variables that were associated (p < .20) with both a given HIV stigma variable and ART adherence were considered potential confounders and included in multivariable models.

Next, interaction between HIV stigma and emotion regulation was tested on both the multiplicative and additive scales (VanderWeele & Knol, 2014). Assessing interaction on both scales provides a fuller, more thorough assessment of the relationships between variables of interest, as interaction may emerge on one scale but not the other. Moreover, though multiplicative interaction is more easily calculated and visualized (hence its being more commonly assessed), additive interaction holds more public health relevance, as it can reveal which subgroups would benefit most from intervention (VanderWeele & Knol, 2014).

To test for multiplicative interaction, two-way product terms with each continuous HIV stigma (internalized, anticipated, enacted) and each emotion regulation variable (cognitive reappraisal, expressive suppression) were added to the previous multivariable modified Poisson regression models (six models total); each continuous term was centered to avoid collinearity issues. Significant product terms (p < .05) were decomposed using marginal effects models, fixing both HIV stigma and emotion regulation variables at their mean and mean ± 1 standard deviation (SD) values. To test for additive interaction, dichotomous HIV stigma (high/low internalized and anticipated HIV stigma; often experiencing enacted HIV stigma vs. never/not often) and emotion regulation variables (high/low cognitive reappraisal and expressive suppression) were used with Stata’s Interaction Contrast package. Three dummy variables were created to calculate the joint effects of each pair of HIV stigma-emotion regulation variables (six pairs total): presence of HIV stigma variable, absence of emotion regulation variable (coded “1”), absence of HIV stigma variable, presence of emotion regulation variable (coded “2”), and presence of both (coded “3”), with the absence of both serving as the reference (coded “0”). The relative excess risk due to interaction (RERI) in relation to the level of risk at no exposure and the attributable proportion (AP) of risk due to interaction among those with both exposures were calculated to quantify additive interaction. All analyses were performed in Stata v. 15 (StataCorp, College Station, TX).

3 |. RESULTS

3.1 |. Sample characteristics

Out of N = 208 youth living with HIV who were enrolled and began the baseline survey, 2 did not complete it, and another 5 did not provide outcome data; these 7 were excluded, leaving 201 for analysis. Mean age was 21.2 years. Two thirds of participants were cisgender men, roughly 1 in 4 were cisgender women, and 1 in 13 were gender-diverse (including transwomen, genderqueer persons, and others). Six in 10 were non-Hispanic Black, and roughly half identified as gay. Approximately 30% were partnered, and just over half were currently in school and employed. Around one in five were uninsured and had recently experienced unstable or disrupted housing. Nearly one in five participants reported ART nonadherence in the past 4 weeks (Table 1).

3.2 |. Emotion regulation strategies and HIV stigma

Overall, median cognitive reappraisal and expressive suppression scores were 5.2 (interquartile range [IQR] = 4.2–6.2) and 4.5 (IQR = 3.3–5.5), respectively, with 58.2% (n = 117) and 37.8% (n = 76) reporting high cognitive reappraisal and high expressive suppression, respectively; 24.9% (n = 50) reported both. Cognitive reappraisal (p = .181) and expressive suppression (p = .481) scores, as well as the proportion of individuals reporting high cognitive reappraisal (p = .078) and high expressive suppression (p = .757), did not differ between ART-nonadherent and ART-adherent participants. Cognitive reappraisal and expressive suppression were weakly correlated (r = .13).

Overall median internalized HIV stigma score was 2.3 (IQR = 1.2–3.3), which was significantly higher among ART-nonadherent relative to ART-adherent participants (2.8 vs. 2.2, p = .012). Overall, 13.4% (n = 27) reported high internalized HIV stigma, which was also significantly higher among ART-nonadherent relative to ART-adherent participants (24.3% vs. 11.0%, p = .031). Overall median anticipated HIV stigma score was 1.6 (IQR = 1.0–2.6), which did not differ between ART-nonadherent and ART-adherent participants (p = .064). Overall, 4.5% of participants reported high anticipated HIV stigma, which was significantly higher among ART-nonadherent relative to ART-adherent participants (13.5% vs. 2.4%, p = .003). Overall median enacted HIV stigma score was 1.0 (IQR = 1.0–1.3), which was significantly higher among ART-nonadherent relative to ART-adherent participants (1.2 vs. 1.0, p = .001). Overall, 11.9% of participants reported often experiencing enacted HIV stigma, which was also significantly higher among ART-nonadherent relative to ART-adherent participants (27.0% vs. 8.5%, p = .001; Table 2).

TABLE 2.

Emotion regulation and HIV stigma among youth living with HIV enrolled in an ART-adherence intervention in six US urban areas.

Total (N = 201) Adherent (n = 164, 81.6%) Nonadherent (n = 37, 18.4%)
Cognitive reappraisal score (continuous)
 Mean (SD), median (IQR) 5.2 (1.3), 5.2 (4.2–6.2) 5.2 (1.3), 5.3 (4.2–6.2) 4.9 (1.4), 4.7 (4.0–6.0)
Z test statistic (p-value) - - 1.34 (.181)
Cognitive reappraisal (dichotomous), n (%)
 High (≥5) 117 (58.2) 100 (61.0) 17 (45.9)
 Low (<5) 82 (40.8) 62 (37.8) 20 (54.1)
 Missing/unknown 2 (1.0) 2 (1.2) 0 (0.0)
χ2 test statistic (p-value) - - 3.10 (.078)
Expressive suppression score (continuous)
 Mean (SD), median (IQR) 4.3 (1.5), 4.5 (3.3–5.5) 4.3 (1.5), 4.3 (3.0–5.5) 4.5 (1.4), 4.6 (3.5–5.3)
t-Test statistic (p-value) - - −0.71 (.481)
Expressive suppression (dichotomous), n (%)
 High (≥5) 76 (37.8) 63 (38.4) 13 (35.1)
 Low (<5) 122 (60.7) 99 (60.4) 23 (62.2)
 Missing/unknown 3 (1.5) 2 (1.2) 1 (2.7)
χ2 test statistic (p-value) - - 0.10 (.757)
Internalized HIV stigma score (continuous)
 Mean (SD), median (IQR) 2.4 (1.2), 2.3 (1.2–3.3) 2.3 (1.2), 2.2 (1.0–3.0) 2.8 (1.2), 2.8 (1.8–3.8)
Z test statistic - - −2.51 (0.012)
Internalized HIV stigma (dichotomous), n (%)
 High (≥4) 27 (13.4) 18 (11.0) 9 (24.3)
 Low (<4) 174 (86.6) 146 (89.0) 28 (75.7)
χ2 test statistic (p-value) - - 4.63 (.031)
Anticipated HIV stigma score (continuous)
 Mean (SD), median (IQR) 1.9 (1.0), 1.6 (1.0–2.5) 1.8 (0.9), 1.5 (1.0–2.4) 2.3 (1.3), 2.0 (1.0–3.1)
Z test statistic - - −1.85 (0.064)
Anticipated HIV stigma (dichotomous), n (%)
 High (≥4) 9 (4.5) 4 (2.4) 5 (13.5)
 Low (<4) 191 (95.0) 160 (97.6) 31 (83.8)
 Missing/unknown 1 (0.5) 0 (0.0) 1 (2.7)
χ2 test statistic (p-value) - - 9.01 (.003)
Enacted HIV stigma score (continuous)
 Mean (SD), median (IQR) 1.4 (0.8), 1.0 (1.0–1.3) 1.3 (0.6), 1.0 (1.0–1.2) 1.9 (1.2), 1.2 (1.0–2.6)
Z test statistic (p-value) - - −3.30 (.001)
Enacted HIV stigma (dichotomous), n (%)
 Never/not often experienced 174 (86.6) 149 (90.9) 25 (67.6)
 Often experienced 24 (11.9) 14 (8.5) 10 (27.0)
 Missing/unknown 3 (1.5) 1 (0.6) 2 (5.4)
χ2 test statistic (p-value) - - 10.80 (.001)
Open in a new tab

Abbreviations: ART, antiretroviral treatment; HIV, human immunodeficiency virus; IQR, interquartile range; SD, standard deviation; US, United States.

Before proceeding with the moderation analysis, we confirmed that internalized HIV stigma (adjusted prevalence ratio [aPR] = 1.41, 95% confidence interval [CI] = 1.14, 1.75; p = .002), anticipated HIV stigma (aPR = 1.44, 95% CI = 1.11, 1.86; p = .005), and enacted HIV stigma (aPR = 1.70, 95% CI = 1.41, 2.06; p < .001) were associated with ART nonadherence, controlling for current school enrollment.

3.3 |. Interaction on the multiplicative scale

Interaction analyses using two-way product terms between continuous HIV stigma and emotion regulation variables revealed a significant interaction between internalized HIV stigma and cognitive reappraisal in both unadjusted (prevalence ratio [PR] = 0.85, 95% CI = 0.76, 0.95) and adjusted models (aPR = 0.87, 95% CI = 0.77, 0.97), indicating that the association between internalized HIV stigma and ART nonadherence depends on the level of cognitive reappraisal (Table 3). Specifically, when internalized HIV stigma is low (i.e., mean – 1 SD), ART nonadherence varies minimally by level of cognitive reappraisal (i.e., mean or mean ± 1 SD); however, as internalized HIV stigma increases (i.e., from mean – 1 SD to the mean, and from the mean to mean + 1 SD), the probability of ART nonadherence increases substantially for those with average cognitive reappraisal and even more so for those with low cognitive reappraisal (Figure 1). No other product terms were significant (Table 3).

TABLE 3.

Multiplicative interaction between continuous HIV stigma and emotion regulation scores on ART adherence among youth living with HIV.

ART nonadherence
PR (95% CI) aPR (95% CI)
Moderation by cognitive reappraisal
 Internalized stigma
  Cognitive reappraisal × internalized stigma 0.85 (0.76, 0.95)*** 0.87 (0.77, 0.97)**
  Internalized stigma 1.22 (0.98, 1.53)* 1.29 (1.02, 1.63)**
  Cognitive reappraisal 0.95 (0.74, 1.22) 0.94 (0.73, 1.21)
 Anticipated stigma
  Cognitive reappraisal × anticipated stigma 0.90 (0.78, 1.04) 0.89 (0.77, 1.04)
  Anticipated stigma 1.34 (1.02, 1.76)** 1.40 (1.06, 1.86)**
  Cognitive reappraisal 0.93 (0.74, 1.16) 0.91 (0.72, 1.14)
 Enacted stigma
  Cognitive reappraisal × enacted stigma 0.92 (0.79, 1.07) 0.90 (0.76, 1.08)
  Enacted stigma 1.59 (1.32, 1.92)**** 1.70 (1.37, 2.10)****
  Cognitive reappraisal 0.92 (0.73, 1.15) 0.89 (0.71, 1.13)
Moderation by expressive suppression
 Internalized stigma
  Expressive suppression × internalized stigma 0.91 (0.78, 1.06) 0.93 (0.80, 1.08)
  Internalized stigma 1.38 (1.10, 1.73)*** 1.45 (1.17, 1.79)***
  Expressive suppression 1.01 (0.81, 1.26) 1.02 (0.82, 1.28)
 Anticipated stigma
  Expressive suppression × anticipated stigma 0.99 (0.83, 1.18) 0.98 (0.81, 1.17)
  Anticipated stigma 1.37 (1.00, 1.87)** 1.43 (1.05, 1.96)**
  Expressive suppression 1.05 (0.87, 1.27) 1.07 (0.88, 1.29)
 Enacted stigma
  Expressive suppression × enacted stigma 0.94 (0.80, 1.10) 0.93 (0.78, 1.10)
  Enacted stigma 1.71 (1.28, 2.28)**** 1.84 (1.38, 2.45)****
  Expressive suppression 1.03 (0.85, 1.25) 1.05 (0.86, 1.28)
Open in a new tab

Note: Significant interaction terms are bolded. Adjusted results are controlled for being currently in school.

Abbreviations: ART, antiretroviral therapy; CI, confidence interval; HIV, human immunodeficiency virus; PR, prevalence ratio.

*

p < .10;

**

p < .05;

***

p < .01;

****

p < .001.

FIGURE 1.

FIGURE 1

Open in a new tab

Interaction of internalized HIV stigma and cognitive reappraisal on ART nonadherence among youth living with HIV. ART, antiretroviral therapy; HIV, human immunodeficiency virus; SD, standard deviation.

3.4 |. Interaction on the additive scale

We also found evidence of additive interaction. In the multivariable modified Poisson regression models, the joint effects of all (6/6) two-way combinations of HIV stigma and emotional regulation variables were significantly associated with ART nonadherence compared to the absence of both variables. Calculation of synergism parameters (RERI, AP) to understand the nature of these joint effects found two to have significantly greater-than-additive interaction.

A positive interaction was observed between high internalized HIV stigma and low cognitive reappraisal (RERI = 3.49, 95% CI = 1.11, 5.87; AP = 0.83, 95% CI = 0.52, 1.13; Table 4), indicating that 83% of ART nonadherence among those reporting both high internalized HIV stigma and low cognitive reappraisal could have been attributable to the interaction between these variables. The predicted probability of ART nonadherence increased fourfold from 0.15 in the absence of high internalized HIV stigma and low cognitive reappraisal to 0.64 in the presence of both (while remaining relatively low [0.08–0.18] in the presence of either; Figure 2). In other words, in the presence of high internalized HIV stigma, low cognitive reappraisal emerged as a potential risk factor for ART nonadherence, meaning that the inverse (high cognitive reappraisal) emerged as a potential protective factor against ART nonadherence.

TABLE 4.

Main and joint effects of HIV stigma/emotion regulation terms and additive interactions on ART nonadherence among youth living with HIV.

PR (95% CI) RERI AP
High internalized HIV stigma Low cognitive reappraisal
− − 1
+ − 0.53 (0.08, 3.74)
− + 1.21 (0.61, 2.37)
+ + 4.23 (2.33, 7.69) **** 3.49 (1.11, 5.87) *** 0.83 (0.52, 1.13) ****
High anticipated HIV stigma Low cognitive reappraisal
− − 1
+ − 4.36 (1.68, 11.33)***
− + 1.84 (0.98, 3.47)*
+ + 7.22 (2.71, 19.28) **** 2.02 (−5.31, 9.34) 0.28 (−0.54, 1.10)
Enacted HIV stigma Low cognitive reappraisal
− − 1
+ − 2.26 (0.85, 6.01)
− + 1.45 (0.71, 2.97)
+ + 5.27 (2.59, 10.75) **** 2.56 (−0.97, 6.10) 0.49 (<−0.01, 0.97)*
High internalized HIV stigma Low expressive suppression
− − 1
+ − 0.84 (0.42, 1.71)
− + 1.08 (0.33, 3.49)
+ + 3.84 (1.86, 7.89) **** 2.91 (0.53, 5.30) ** 0.76 (0.40, 1.12) ****
High anticipated HIV stigma Low expressive suppression
− − 1
+ − 1.11 (0.56, 2.22)
− + 3.42 (1.16, 10.09)**
+ + 6.58 (3.40, 12.72) **** 3.04 (−1.17, 7.25) 0.46 (−0.07, 1.00)*
Enacted HIV stigma Low expressive suppression
− − 1
+ − 1.27 (0.56, 2.90)
− + 3.52 (1.38, 8.97)***
+ + 3.65 (1.29, 10.31) ** −0.15 (−3.95, 3.65) −0.04 (−1.10, 1.02)
Open in a new tab

Note: “−” denotes SI could not be calculated. Significant and marginally significant interaction effects are bolded; all results are adjusted for currently being in school

Abbreviations: AP, attributable proportion; ART, antiretroviral therapy; CI, confidence interval; HIV, human immunodeficiency virus; PR, prevalence ratio; RERI, relative excess risk due to interaction; SI, synergy index.

*

p < .10;

**

p < .05;

***

p < .01;

****

p < .001.

FIGURE 2.

FIGURE 2

Open in a new tab

ART nonadherence by HIV stigma/emotion regulation in youth living with HIV. ART, antiretroviral therapy; HIV, human immunodeficiency virus.

A positive interaction was also observed between high internalized HIV stigma and low expressive suppression (RERI = 2.91, 95% CI = 0.53, 5.30; AP = 0.76, 95% CI = 0.40, 1.12; Table 4), suggesting that 76% of ART nonadherence among those reporting both high internalized HIV stigma and low expressive suppression could have been attributable to the interaction between these variables. The probability of ART nonadherence increased fourfold from 0.18 in the absence of high internalized HIV stigma and low expressive suppression to 0.68 in the presence of both (while remaining relatively low [0.15–0.19] in the presence of either; Figure 2). In other words, in the presence of high internalized HIV stigma, low expressive suppression emerged as a potential risk factor for ART nonadherence, meaning that the inverse (high expressive suppression) emerged as a potential protective factor against ART nonadherence.

No other significant interactions on the additive scale were observed. However, a positive interaction approaching statistical significance was found between enacted HIV stigma and low cognitive reappraisal (AP = 0.49, 95% CI = < −0.01, 0.97; p =.0507; Table 4).

3.5 |. Sensitivity analysis

Enrollment in school was the only covariate statistically indicated as a potential confounder of the examined associations and therefore was the only covariate included in our multivariable models. We therefore performed a sensitivity analysis in which we included all remaining covariates to assess whether statistical significance remained. The multiplicative interaction between internalized HIV stigma and cognitive reappraisal remained significant (aPR = 0.83, 95% CI = 0.70, 1.00; p = .048), as did the additive interaction between high internalized HIV stigma and low cognitive reappraisal (RERI = 4.66, 95% CI = 0.36, 8.95; p = .0337; AP = 0.81, 95% CI = 0.47, 1.15; p < .001). The additive interaction between high internalized HIV stigma and low expressive suppression was mixed, with a marginally significant RERI (RERI = 4.42, 95% CI = −0.24, 9.09; p = .0632) and a significant AP (AP = 0.81, 95% CI = 0.50, 1.13; p <.001).

4 |. DISCUSSION

We aimed to determine the extent to which two emotion regulation strategies—cognitive reappraisal and expressive suppression—interacted with internalized, anticipated, and enacted HIV stigma on ART nonadherence in a sample of youth living with HIV. We found that cognitive reappraisal multiplicatively and additively interacted with internalized HIV stigma, and as hypothesized, the nature of the interactions was indicative of a potential protective effect against HIV stigma’s association with ART nonadherence. Expressive suppression additively interacted with internalized HIV stigma, and, unexpectedly, likewise seemed to confer protection against ART nonadherence. Emotion regulation may play an important role in the HIV stigma-ART adherence relationship and warrants consideration in ART adherence interventions for youth living with HIV.

Although no prior study (to our knowledge) has examined how internalized HIV stigma and cognitive reappraisal interact on ART adherence, previous research has shown positive reappraisal, which is conceptually similar to cognitive reappraisal, to be positively associated with ART adherence (Finkelstein-Fox et al., 2020). Our findings extend this literature by showing that internalized HIV stigma’s association with ART adherence actually depends on the extent to which one utilizes cognitive reappraisal as an emotion regulation strategy. Specifically, at low levels of cognitive reappraisal, internalized HIV stigma’s adverse effect on ART adherence was pronounced. At high levels of cognitive reappraisal, however, this relationship was muted, suggesting a protective effect of cognitive reappraisal. Prior research has demonstrated a buffering effect of cognitive reappraisal on the association between intimate partner violence and substance use among sexual and gender minority youth (Scheer & Mereish, 2021) and on the association between HIV symptomology and depressive and anxiety symptoms (Finkelstein-Fox et al., 2020). Harnessing cognitive reappraisal’s mitigative power to support youth living with HIV may be warranted in future intervention development.

These findings were reinforced by results from additive interaction, which revealed exacerbated risk for ART nonadherence in the presence of both low cognitive reappraisal and high internalized HIV stigma, their interaction possibly accounting for the majority of observed instances of ART nonadherence. Increasing one’s cognitive reappraisal to high levels may have potential to improve ART adherence among youth living with HIV with high internalized HIV stigma. Cognitive reappraisal that has been successfully taught to participants in intervention trials has led to reductions in stress, negative affect, and body image disturbance (Denny & Ochsner, 2014; Klimek et al., 2020). In a trial with people living with HIV participating in an intervention based in part on cognitive reappraisal principles, ART adherence increased from 80.3% at baseline to 97.5% at follow-up (Molassiotis et al., 2003). Randomized trials testing cognitive reappraisal interventions and ART adherence among youth living with HIV are indicated, with cognitive reappraisal as a standalone treatment or embedded in a larger cognitive behavior treatment program.

Although no causal claims can be made due to the cross-sectional nature of the data, and though the emotion regulation measure was not specific to HIV stigma, a scenario in which the emotional impact of internalized HIV stigma is mitigated by cognitive reappraisal (thereby supporting ART adherence) can be reasonably postulated. For example, an individual plagued with thoughts such as “Having HIV makes me feel like I am a bad person” could use cognitive reappraisal to think “HIV is a virus—it is unrelated to who I am as a person.” An individual with the thought “I think less of myself because I have HIV” could use cognitive reappraisal to change this to “HIV is unrelated to my self-worth. I am worthy of good things.” In so doing, as cognitive reappraisal is an antecedent-focused emotion regulation strategy, the rise of distressing emotions that may complicate ART adherence may be stymied.

There was no evidence of multiplicative interaction between cognitive reappraisal and enacted HIV stigma. However, one measure of additive interaction approached statistical significance, suggesting high cognitive reappraisal could play a role in helping youth living with HIV manage the effects of enacted stigma to remain ART-adherent. This is an area for future research.

There was no evidence of multiplicative interaction between expressive suppression and any form of HIV stigma. However, we did observe additive interaction between high expressive suppression and high internalized HIV stigma, suggesting high expressive suppression may protect against ART nonadherence in the presence of high internalized HIV stigma. Individuals with high internalized HIV stigma may use expressive suppression to inhibit emotionally expressive behaviors that could interfere with taking ART. Going through the steps required to take ART—for example, setting and hearing a reminder or alarm, walking to the area (such as a cabinet) where ART is stored, opening the cabinet door and taking out the bottle of ART, and so on until one swallows the pill—could trigger or aggravate internalized HIV stigma, leading to an emotional response that impedes taking ART. Expressive suppression may therefore be used to inhibit this response so that an individual can successfully take and adhere to ART.

Although other studies have likewise found expressive suppression to be associated with positive outcomes, such as reducing death anxiety among people living with HIV (Chukwuorji et al., 2020), these findings contrast with the majority of research (which has not been HIV-focused) linking expressive suppression to negative physical (cardiovascular complications, memory disruptions, exacerbation of minor ailments, acceleration of cancer progression) and mental health outcomes (e.g., symptoms of anxiety, depression, eating disorders, general distress) (Dryman & Heimberg, 2018; Koechlin et al., 2018; Mathur et al., 2022). In light of this body of literature, expressive suppression’s conceptualization as a maladaptive emotion regulation strategy is understandable (Aldao et al., 2010; Gross, 1998, 2002; Hatzenbuehler, 2009; Hatzenbuehler et al., 2009). Findings like ours are indeed in the minority and cannot be taken as conclusive evidence that expressive suppression is adaptive or that it should be incorporated into interventions for youth living with HIV. However, it cannot be ignored that our behavioral outcome of adherence—and the context of internalized HIV stigma in which it is being considered here—does sharply differ from the primarily nonbehavioral outcomes (discussed above) previously examined in relation to expressive suppression. Taken together, in this specific scenario, suppressing behavior rooted in distressing emotions to enact a lifesaving behavior may in fact be reasonable and adaptive. Future research is warranted to investigate expressive suppression’s role in buffering the effects of internalized HIV stigma to support ART adherence (and perhaps other HIV-related outcomes) and to document any potential unintended negative effects of expressive suppression on other health domains.

We found no interaction between anticipated HIV stigma and either emotion regulation strategy. Anticipated HIV stigma may have been too minimally endorsed in our sample to detect an interaction, or perhaps the emotions that accompany anticipated stigma operate on regulatory pathways that differ from those likely to be targeted by cognitive reappraisal and expressive suppression, at least in the context of HIV stigma and ART adherence.

Our findings should be considered in light of several limitations. Our sample of youth living with HIV was comprised of individuals participating in an mHealth ART-adherence intervention trial recruited from HIV clinics and other locations in six urban areas across the Southern, Midwest, and Northeast US. Moreover, most participants were cisgender men, non-Hispanic Black, and gay-identifying. Our findings are therefore unlikely to be generalizable to all youth living with HIV, such as those residing in other US regions or nonurban areas, or those of differing demographic profiles. Second, the elimination of an eligibility criterion (i.e., recent detectable viral load while on ART, recent missed HIV care appointment, recent lack of HIV care, or recent ART nonadherence) upon the onset of the COVID-19 pandemic may have affected sample composition. The third of the sample for whom this criterion did apply would have necessarily experienced recent HIV care continuum challenges, whereas the two thirds of the sample for whom this criterion did not apply may not have. Retaining this criterion would have likely led to a different sample from the present one and potentially different findings. Third, the original study was not designed to investigate the questions addressed here, and the cross-sectional nature of the baseline data prevent the establishment of causality.

Fourth, out of many possible emotion regulation strategies, we only assessed two (cognitive reappraisal, expressive suppression), and our measure of each was brief and relatively nonspecific. Future research that thoroughly assesses a wider variety of emotion regulation strategies (e.g., acceptance, problem-solving; rumination, avoidance) may be informative in understanding in more detail the relationships examined here. Moreover, qualitative inquiry to understand the use of these strategies in HIV-specific contexts would be helpful. Relatedly, our participants may have experienced other (unassessed) stigmas that intersect with HIV stigma. Understanding how emotion regulation strategies interact with other stigmas on ART nonadherence may likewise prove fruitful and further support adherence intervention efforts. Fifth, we used a self-report measure of ART adherence; future replication studies may consider using objective measures instead. Finally, several minoritized populations (e.g., sexual, gender, racial/ethnic) were represented in our sample, but the sizes of these subgroups were small. A larger sample would facilitate further probing to understand the extent to which additional moderation by sociodemographic characteristics is present. A larger sample would have also addressed the loss of statistical power prompted by our use of interaction methods, which could have allowed us to detect additional significant relationships (see Horvath et al., 2019, for discussion on statistical power for the RCT from which these baseline data were drawn).

Despite these limitations, our study is notable for contributing to extant literature on HIV care continuum challenges among racially/ethnically diverse youth living with HIV, a highly vulnerable yet resilient population requiring targeted focus and intervention. A second strength of our study is the focus on emotion regulation strategies, an under-researched topic in this population, and how they differentially interact with commonly experienced HIV stigma to affect ART adherence. Third, our study applied multiple novel analytic methods to yield a more thorough, nuanced understanding of how HIV stigma and emotion regulation uniquely operate to shape ART adherence. Finally, our findings provide concrete future research directions and intervention targets that show promise in addressing HIV care continuum challenges among youth living with HIV.

5 |. CONCLUSION

The experience of going through adolescence includes learning to cope with stigma for many individuals, as youth from all walks of life may encounter stigma of some sort during this period, whether that be due to race or ethnicity, sexuality, gender identity or expression, body size, a health condition such as HIV, or some other attribute. Understanding ways to support youth cope with such stigma is therefore paramount to fostering their healthy growth and development and warrants investigation across diverse populations of youth with differential stigma experiences.

For youth living with HIV, stigma related to positive HIV status poses a formidable obstacle to successful engagement with the HIV care continuum and living well with HIV, not only marginalizing this population but also threatening broader HIV prevention efforts. In a show of resilience, many youth living with HIV have cultivated means of tackling entrenched HIV stigma that they experience, such as regulating their emotions. Emotion regulation strategies like cognitive reappraisal are teachable and effective at yielding positive outcomes and may be particularly useful for youth living with HIV struggling to adhere to ART due to or in the context of HIV stigma, especially internalized HIV stigma. Though the individual-level strategy of adaptive emotion regulation will admittedly not address broader structural dynamics that underlie and perpetuate HIV stigma, it shows promise in supporting ART adherence and thereby HIV prevention for youth living with HIV, bringing us closer to ending the HIV epidemic in the United States.

ACKNOWLEDGMENTS

This work was supported by the National Institutes of Health Adolescent Medicine Trials Network for HIV/AIDS Interventions (ATN 138; MPI: Horvath and Amico) as part of and the UNC/Emory Center for Innovative Technology (iTech; principal investigators: Dr. Hightow-Weidman/Sullivan, 1U19HD089881). In addition, J. M. W. received support from T32DA023356. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Funding information

National Institute on Drug Abuse; Adolescent Medicine Trials Network for HIV/AIDS Interventions

Footnotes

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

ETHICS STATEMENT

This study is registered as a clinical trial (Clinical Trials # NCT03149757) and was approved by the institutional review board at the University of North Carolina–Chapel Hill; parental consent was waived for participants aged 15–17 years.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the senior author upon reasonable request. Deidentified data from this study are not available in a public archive but may be requested by emailing K. J. H. Analytic code used to conduct the analyses in this study are not available in a public archive but may be requested by emailing J. M. W.

REFERENCES

  1. Aldao A, Nolen-Hoeksema S, & Schweizer S (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review, 30(2), 217–237. 10.1016/j.cpr.2009.11.004 [DOI] [PubMed] [Google Scholar]
  2. Allan-Blitz LT, Mena LA, & Mayer KH (2021). The ongoing HIV epidemic in American youth: Challenges and opportunities. mHealth, 7, 33. 10.21037/mhealth-20-42 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Amico KR, Crawford J, Ubong I, Lindsey JC, Gaur AH, Horvath K, Goolsby R, Mueller Johnson M, Dallas R, Heckman B, Filipowicz T, Polier M, Rupp BM, & Hudgens M (2021). Correlates of high HIV viral load and antiretroviral therapy adherence among viremic youth in the United States enrolled in an adherence improvement intervention. AIDS Patient Care and STDs, 35(5), 145–157. 10.1089/apc.2021.0005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Amico KR, Fisher WA, Cornman DH, Shuper PA, Redding CG, Konkle-Parker DJ, Barta W, & Fisher JD (2006). Visual analog scale of ART adherence. Journal of Acquired Immune Deficiency Syndromes (JAIDS), 42(4), 455–459. 10.1097/01.qai.0000225020.73760.c2 [DOI] [PubMed] [Google Scholar]
  5. Bezabhe WM, Chalmers L, Bereznicki LR, & Peterson GM (2016). Adherence to antiretroviral therapy and virologic failure. Medicine (United States), 95(15), e3361. 10.1097/MD.0000000000003361 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Byrd KK, Hou JG, Hazen R, Kirkham H, Suzuki S, Clay PG, Bush T, Camp NM, Weidle PJ, Delpino A, & Patient-Centered HIV Care Model Team. (2019). Antiretroviral adherence level necessary for HIV viral suppression using real-world data. JAIDS Journal of Acquired Immune Deficiency Syndromes, 82(3), 245–251. 10.1097/QAI.0000000000002142 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. CDC. (2020). HIV Surveillance Special Report 32: Behavioral and clinical characteristics of persons with diagnosed HIV infection – Medical Monitoring Project, United States 2021 Cycle (June 2021–May 2022). [Google Scholar]
  8. CDC. (2021a). HIV Surveillance Report: Diagnoses of HIV Infection in the United States and dependent areas, 2020 (updated) (Vol. 33). Centers for Disease Control and Prevention. [Google Scholar]
  9. CDC. (2021b). HIV Surveillance Report 2021: Monitoring selected national HIV prevention and care objectives by using HIV surveillance data – United States and 6 dependent areas (2019). Centers for Disease Control and Prevention. [Google Scholar]
  10. Chukwuorji JC, Uzuegbu CN, Chukwu CV, Ifeagwazi CM, & Ugwu C (2020). Social support serves emotion regulation function in death anxiety among people living with HIV/AIDS. South African Journal of Psychology, 50(3), 395–410. 10.1177/0081246319894700 [DOI] [Google Scholar]
  11. Crowley T, & Rohwer A (2021). Self-management interventions for adolescents living with HIV: A systematic review. BMC Infectious Diseases, 21(1), 431. 10.1186/s12879-021-06072-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Denny BT, & Ochsner KN (2014). Behavioral effects of longitudinal training in cognitive reappraisal. Emotion (Washington, D.C.), 14(2), 425–433. 10.1037/a0035276 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. DeSteno D, Gross JJ, & Kubzansky L (2013). Affective science and health: The importance of emotion and emotion regulation. Health Psychology, 32(5), 474–486. 10.1037/a0030259 [DOI] [PubMed] [Google Scholar]
  14. Dryman MT, & Heimberg RG (2018). Emotion regulation in social anxiety and depression: A systematic review of expressive suppression and cognitive reappraisal. Clinical Psychology Review, 65, 17–42. 10.1016/j.cpr.2018.07.004 [DOI] [PubMed] [Google Scholar]
  15. Earnshaw VA, & Chaudoir SR (2009). From conceptualizing to measuring HIV stigma: A review of HIV stigma mechanism measures. AIDS and Behavior, 13(6), 1160–1177. 10.1007/s10461-009-9593-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Earnshaw VA, Smith LR, Chaudoir SR, Amico KR, & Copenhaver MM (2013). HIV stigma mechanisms and well-being among PLWH: A test of the HIV stigma framework. AIDS and Behavior, 17(5), 1785–1795. 10.1007/s10461-013-0437-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Felker-Kantor EA, Wallace ME, Madkour AS, Duncan DT, Andrinopoulos K, & Theall K (2019). HIV stigma, mental health, and alcohol use disorders among people living with HIV/AIDS in New Orleans. Journal of Urban Health, 96(6), 878–888. 10.1007/s11524-019-00390-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Finkelstein-Fox L, Park CL, & Kalichman SC (2020). Health benefits of positive reappraisal coping among people living with HIV/AIDS: A systematic review. Health Psychology Review, 14(3), 394–426. 10.1080/17437199.2019.1641424 [DOI] [PubMed] [Google Scholar]
  19. Gillette E, Naanyu V, Nyandiko W, Chory A, Scanlon M, Aluoch J, Koros H, Ashimosi C, Beigon W, Munyoro D, Lidweye J, Nyagaya J, DeLong A, Kantor R, & Vreeman R (2023). HIV-related stigma shapes research participation for youth living with HIV in Kenya. Journal of the International Association of Providers of AIDS Care (JIAPAC), 22, 232595822311707. 10.1177/23259582231170732 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Giordano TP, Guzman D, Clark R, Charlebois ED, & Bangsberg DR (2004). Measuring adherence to antiretroviral therapy in a diverse population using a visual analogue scale. HIV Clinical Trials, 5(2), 74–79. 10.1310/jfxh-g3x2-eym6-d6ug [DOI] [PubMed] [Google Scholar]
  21. Goffman E (1963). Stigma: Notes on the management of spoiled identity. Simon & Schuster Inc. [Google Scholar]
  22. Gross JJ (1998). Antecedent- and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology. Journal of Personality and Social Psychology, 74(1), 224–237. [DOI] [PubMed] [Google Scholar]
  23. Gross JJ (2002). Emotion regulation: Affective, cognitive, and social consequences. Psychophysiology, 39(3), 281–291. 10.1017/S0048577201393198 [DOI] [PubMed] [Google Scholar]
  24. Gross JJ (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry, 26(1), 1–26. [Google Scholar]
  25. Gross JJ, Feldman Barrett L, John O, Lane R, Larsen R, & Pennebaker J (1998). The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2(5), 271–299. [Google Scholar]
  26. Gross JJ, & John OP (2003). Emotion Regulation Questionnaire. APA PsycTests [Database]. [Google Scholar]
  27. Gruhn MA, & Compas BE (2020). Effects of maltreatment on coping and emotion regulation in childhood and adolescence: A meta-analytic review. Child Abuse and Neglect, 103, 104446. 10.1016/j.chiabu.2020.104446 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Hatzenbuehler ML (2009). How does sexual minority stigma “get under the skin”? A psychological mediation framework. Psychological Bulletin, 135(5), 707–730. 10.1037/a0016441 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Hatzenbuehler ML, Nolen-Hoeksema S, & Dovidio J (2009). How does stigma “get under the skin”?: The mediating role of emotion regulation. Psychological Science, 20(10), 1282–1289. 10.1111/j.1467-9280.2009.02441.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Hatzenbuehler ML, O’Cleirigh C, Mayer KH, Mimiaga MJ, & Safren SA (2011). Prospective associations between HIV-related stigma, transmission risk behaviors, and adverse mental health outcomes in men who have sex with men. Annals of Behavioral Medicine, 42(2), 227–234. 10.1007/s12160-011-9275-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Hernandez D, Kalichman SC, Katner HP, Burnham K, Kalichman MO, & Hill M (2018). Psychosocial complications of HIV/AIDS-metabolic disorder comorbidities among patients in a rural area of southeastern United States. Journal of Behavioral Medicine, 41(4), 441–449. 10.1007/s10865-018-9912-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Horvath KJ, MacLehose RF, Martinka A, DeWitt J, Hightow-Weidman L, Sullivan P, & Amico KR (2019). Connecting youth and young adults to optimize antiretroviral therapy adherence (YouTHrive): Protocol for a randomized controlled trial. JMIR Research Protocols, 8(7), e11502. 10.2196/11502 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Kerrigan D, & Barrington C (2018). Social aspects of HIV structural dynamics of HIV risk, resilience and response. Springer. http://www.springer.com/series/11922 [Google Scholar]
  34. Klimek P, Wilhelm S, Safren SA, & Blashill AJ (2020). Cognitive behavioral therapy for body image and self-care (CBT-BISC) among sexual minority men living with HIV: Skills-based treatment mediators. Cognitive Therapy and Research, 44(1), 208–215. 10.1007/s10608-019-10035-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Koechlin H, Coakley R, Schechter N, Werner C, & Kossowsky J (2018). The role of emotion regulation in chronic pain: A systematic literature review. Journal of Psychosomatic Research, 107, 38–45. 10.1016/j.jpsychores.2018.02.002 [DOI] [PubMed] [Google Scholar]
  36. Laurenzi CA, Melendez-Torres GJ, Page DT, Vogel LS, Kara T, Sam-Agudu NA, Willis N, Ameyan W, Toska E, Ross DA, & Skeen S (2022). How do psychosocial interventions for adolescents and young people living with hiv improve adherence and viral load? A realist review. Journal of Adolescent Health, 71(3), 254–269. 10.1016/j.jadohealth.2022.03.020 [DOI] [PubMed] [Google Scholar]
  37. Logie C, & Gadalla TM (2009). Meta-analysis of health and demographic correlates of stigma towards people living with HIV. AIDS Care, 21(6), 742–753. 10.1080/09540120802511877 [DOI] [PubMed] [Google Scholar]
  38. Mathur A, Li JC, Lipitz SR, & Graham-Engeland JE (2022). Emotion regulation as a pathway connecting early life adversity and inflammation in adulthood: A conceptual framework. Adversity and Resilience Science, 3(1), 1–19. 10.1007/s42844-022-00051-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Meyers-Pantele SA, Lammert S, Rendina HJ, Shalhav O, Talan AJ, Smith LR, Pitpitan EV, & Horvath KJ (2022). Examining HIV stigma, depression, stress, and recent stimulant use in a sample of sexual minority men living with HIV: An application of the stigma and substance use process model. AIDS and Behavior, 26, 138–148. 10.1007/s10461-021-03517-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Molassiotis A, Lopez-nahas V, Chung WY, & Lam SW (2003). A pilot study of the effects of a behavioural intervention on treatment adherence in HIV-infected patients. AIDS Care, 15(1), 125–135. 10.1080/0954012021000039833 [DOI] [PubMed] [Google Scholar]
  41. Moore SA, Zoellner LA, & Mollenholt N (2008). Are expressive suppression and cognitive reappraisal associated with stress-related symptoms. Behaviour Research and Therapy, 46(9), 993–1000. 10.1016/j.brat.2008.05.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Morris AS, Silk JS, Steinberg L, Myers SS, & Robinson LR (2007). The Role of the family context in the development of emotion regulation. Social Development, 16(2), 361–388. 10.1111/j.1467-9507.2007.00389.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Mouatsou C, & Koutra K (2021). Emotion regulation in relation with resilience in emerging adults: The mediating role of self-esteem. Current Psychology, 42(1), 734–747. 10.1007/s12144-021-01427-x [DOI] [Google Scholar]
  44. Mugo C, Kohler P, Kumar M, Badia J, Kibugi J, Wamalwa DC, Kapogiannis B, Agot K, & John-Stewart GC (2023). Effect of HIV stigma on depressive symptoms, treatment adherence, and viral suppression among youth with HIV. AIDS, 37(5), 813–821. 10.1097/QAD.0000000000003473 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Mutwa PR, Van Nuil JI, Asiimwe-Kateera B, Kestelyn E, Vyankandondera J, Pool R, Ruhirimbura J, Kanakuze C, Reiss P, Geelen S, Wijgert J, & Boer KR (2013). Living situation affects adherence to combination antiretroviral therapy in HIV-infected adolescents in Rwanda: A qualitative study. PLoS One, 8(4), e60073. 10.1371/journal.pone.0060073 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Office of Infectious Disease and HIV/AIDS Policy, U. S. D. of H. & H. S. (HHS). (2020). Ending the HIV epidemic: Plan for America: Overview. Accessed October 25, 2023. https://www.hiv.gov/federal-response/ending-the-hiv-epidemic/overview
  47. O’Halloran Leach E, Lu H, Caballero J, Thomas JE, Spencer EC, & Cook RL (2021). Defining the optimal cut-point of self-reported ART adherence to achieve viral suppression in the era of contemporary HIV therapy: A cross-sectional study. AIDS Research and Therapy, 18(1), 36. 10.1186/s12981-021-00358-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Okonji EF, Mukumbang FC, Orth Z, Vickerman-Delport SA, & Van Wyk B (2020). Psychosocial support interventions for improved adherence and retention in ART care for young people living with HIV (10–24 years): A scoping review. BMC Public Health, 20(1), 1841. 10.1186/s12889-020-09717-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Oyugi JH, Byakika-Tusiime J, Pharm B, Charlebois ED, Kityo C, Mugerwa R, Mugyenyi P, & Bangsberg DR (2004). Multiple validated measures of adherence indicate high levels of adherence to generic HIV Antiretroviral therapy in a resource-limited setting. Journal of Acquired Immune Deficiency Syndromes (JAIDS), 36(5), 1100–1102. http://journals.lww.com/jaids [DOI] [PubMed] [Google Scholar]
  50. Robinson A, Cooney A, Fassbender C, & McGovern DP (2023). Examining the relationship between HIV-related stigma and the health and wellbeing of children and adolescents living with HIV: A systematic review. AIDS and Behavior, 27, 3133–3149. 10.1007/s10461-023-04034-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Sayles JN, Wong MD, Kinsler JJ, Martins D, & Cunningham WE (2009). The association of stigma with self-reported access to medical care and antiretroviral therapy adherence in persons living with HIV/AIDS. Journal of General Internal Medicine, 24(10), 1101–1108. 10.1007/s11606-009-1068-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Scheer JR, & Mereish EH (2021). Intimate partner violence and illicit substance use among sexual and gender minority youth: The protective role of cognitive reappraisal. Journal of Interpersonal Violence, 36(21–22), 9956–9976. 10.1177/0886260519881001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Sibinga E, Webb L, Perin J, Tepper V, Kerrigan D, Grieb S, Denison J, & Ellen J (2022). Mindfulness instruction for medication adherence among adolescents and young adults living with HIV: A randomized controlled trial. AIDS Care, 34(12), 1619–1627. 10.1080/09540121.2022.2105796 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Silvers JA (2022). Adolescence as a pivotal period for emotion regulation development for consideration at current opinion in psychology. Current Opinion in Psychology, 44, 258–263. 10.1016/j.copsyc.2021.09.023 [DOI] [PubMed] [Google Scholar]
  55. Srivastava S, Tamir M, McGonigal KM, John OP, & Gross JJ (2009). The social costs of emotional suppression: A prospective study of the transition to college. Journal of Personality and Social Psychology, 96(4), 883–897. 10.1037/a0014755 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. VanderWeele TJ, & Knol MJ (2014). A tutorial on interaction. Epidemiologic Methods, 3(1), 33–72. 10.1515/em-2013-0005 [DOI] [Google Scholar]
  57. Verzeletti C, Zammuner VL, Galli C, & Agnoli S (2016). Emotion regulation strategies and psychosocial well-being in adolescence. Cogent Psychology, 3(1), 1199294. 10.1080/23311908.2016.1199294 [DOI] [Google Scholar]
  58. Walsh JC, Mandalia S, & Gazzard BG (2002). Responses to a 1 month self-report on adherence to antiretroviral therapy are consistent with electronic data and virological treatment outcome. AIDS, 16(2), 269–277. http://journals.lww.com/aidsonline [DOI] [PubMed] [Google Scholar]
  59. Wang D, Yuan B, Han H, & Wang C (2020). Validity and reliability of emotion regulation questionnaire (ERQ) in Chinese rural-to-urban migrant adolescents and young adults. Current Psychology, 41(4), 2346–2353. 10.1007/s12144-020-00754-9 [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available from the senior author upon reasonable request. Deidentified data from this study are not available in a public archive but may be requested by emailing K. J. H. Analytic code used to conduct the analyses in this study are not available in a public archive but may be requested by emailing J. M. W.

RESOURCES