The rise in hate crimes against Black U.S. American1 youth since the 2016 presidential election (Federal Bureau of Investigation, 2018) provides a stark indicator that anti-Blackness continues to be deeply woven into the U.S. societal fabric. Indeed, an accumulating body of research (see Benner et al., 2018) provides evidence that persistent racial discrimination targeting Black adolescents contributes to increased psychological symptoms (e.g., anxiety, depressive, trauma symptoms; Greene, Way, & Pahl, 2006; Priest et al., 2013), increased substance use (e.g., Gibbons, Gerrard, Cleveland, Wills, & Brody, 2004), decreased academic achievement (e.g., Chavous, Rivas-Drake, Smalls, Griffin, & Cogburn, 2008; English, Lambert, & Ialongo, 2016; Neblett Jr., Philip, Cogburn, & Sellers, 2006),
and increased physiological problems among these youth (e.g., inflammation, high blood pressure; Brody, Yu, Miller, & Chen, 2015; Clark & Gochett, 2006). Despite this evidence, researchers have suggested that their studies may underestimate the association between racial discrimination and negative biopsychosocial outcomes among Black adolescents (e.g., Berkel et al., 2009; English, Lambert, & Ialongo, 2014; Pachter, Bernstein, Szalacha, & García Coll, 2010) because they assessed a limited set of a larger group of qualitatively-indicated (e.g., Rosenbloom & Way, 2004) and theoretically-relevant (e.g., Sue, Capodilupo, & Holder, 2008) contemporary experiences of racial discrimination. In the present study, we sought to address this by examining the frequency and psychological effects of a broad set of daily racial discrimination experiences among Black adolescents including those experienced individually, vicariously, online, offline and through teasing.
Theoretical models of racial discrimination effects
The present study draws upon the theoretical models put forth by García Coll et al. (1996), Quintana and McKown (2008), and Sue et al. (2007). We extend García Coll and colleagues’ integrative model for the study of developmental competencies in minority children to incorporate both traditional, or offline, contexts as well as those online. This model centers the social position of adolescents of color, and for the present study, we are particularly concerned with race and its associated indicators of social position. These include skin color, hair texture, language and/or accent. García Coll and colleagues argue that aspects of social position alter developmental trajectories for adolescents of color through pervasive social stratification mechanisms such as discrimination and oppression. Further, they note that discrimination experiences may be subtle or overt.
Following this model, we account for the fact that racial discrimination is experienced regularly by Black adolescents in a myriad of forms, like peer harassment and teasing (Keltner, Capps, Kring, Young, & Heerey, 2001). In addition to these more overt forms, there are subtle, nuanced slights and insults based on phenotypic traits and/or racial group identification referred to as daily racial hassles (Pierce, 1970) or everyday racism (Essed, 1991). Evidence indicates these forms of racial discrimination can be experienced by Black adolescents as individual racial microaggressions—automatic, and potentially unintentional, expressions of subtle verbal, behavioral, and environmental exploitations of racial power against Black individuals in the U.S. (Sue et al., 2007; Sue et al., 2008). García Coll et al. (1996) framed these multiple forms of racial discrimination experiences as significant barriers to the healthy development of racial/ethnic minority youth. They suggested that these discrimination experiences can create inhibiting environments that influence child characteristics (e.g., health status, temperament) and ultimately affect cognitive, social, and emotional development for racial/ethnic minority youth.
Along with the García Coll and colleagues model, we draw upon Quintana and McKown’s (2008) integrated model of the influences of race and racism on the developing child. This model stresses the importance of vicarious racial discrimination experiences in addition to those experienced individually through teasing, harassment, and other forms of discrimination. Much of the research on racial discrimination has focused on individual experiences, but the researchers note that adolescents do not necessarily need to be personally involved for the discriminatory experience to influence their psychological adjustment (Quintana & McKown, 2008). Although not experienced directly, Quintana and McKown note that vicarious exposure to racial discrimination may be traumatic and equally impactful on developmental outcomes. Additionally, Tynes, Giang, Williams, and Thompson (2008) applied Quintana and McKown’s model to online experiences of racial discrimination, identifying that individual and vicarious racial discrimination can occur online in a myriad of expressions such as witnessing the use of racial epithets in social media.
To date, the literature on individual racial discrimination, and the comparatively limited literature on vicarious racial discrimination, have tended to focus on more overt forms of the stressor. Indeed, the literature on racial microaggessions is often published separately or, if included in racial discrimination studies, is measured separately (see Tynes, Markoe & Rose, 2013). The application of the microaggressions framework to online racial discrimination experiences is particularly complex, as early research suggests that once messages are written, voiced or shown graphically in digital formats, experiences may no longer be considered subtle (Tynes, Del Toro, & Lozada, 2013). For this reason, and following the above models, the present study assesses racial microaggessions in traditional or offline settings, but not in online settings.
We believe that examining microaggressions is critical because, despite evidence for key mechanisms, moderators, and outcomes associated with the racial discrimination for Black adolescents (see Benner et al., 2018; Priest et al., 2013), the microaggressions framework has recently come under criticism for lacking empirical support (e.g., Lilienfeld, 2017). In particular, critics have asserted that, contrary to theory, there is little evidence that subtypes of microaggressions actually occur on a regular basis for Black U.S. Americans. The present study aims to address this gap in the literature and examine the daily frequency of underlying subtypes of microaggressions identified in theoretical and qualitative research with Black U.S. Americans (Sue et al., 2008). Taken together, the aforementioned theoretical models frame our focus on vicarious and individual general discrimination offline (including microaggressions), individual and vicarious experiences online, and individual and vicarious teasing.
Developmentally-specific content of racial discrimination experiences
Recent reviews of racial discrimination assessment among adolescents of color have suggested that there is a need for more developmentally-appropriate (e.g., Benner et al., 2018) and contemporaneously-relevant (e.g., Seaton, Gee, Neblett, & Spanierman, 2018) approaches to racial discrimination measurement among Black youth. Indeed, recent research suggests that two types of racial discrimination experiences are particularly relevant, yet understudied, for Black adolescents: racial teasing and vicarious experiences of racial discrimination.
Research indicates that teasing, or the intentional provocation of a target individual around a topic important to them with some level of playfulness, is particularly relevant during childhood given it encompasses several forms of developmentally-normative social interactions during this period (e.g., play fighting; Keltner et al., 2001). Additionally, developmental theory on ethnic/racial identity indicates that, because adolescence is a key period for the development of ethnic/racial identity and bias perception, racial teasing may be particularly impactful for Black individuals during adolescence (Umaña-Taylor et al., 2014). This is critical as evidence indicates teasing is an exceedingly common way in which adolescents address race/ethnicity with their peers (Douglass, 2013) and that teasing experiences earlier in life predict negative psychosocial outcomes later in life (e.g., Ledley et al., 2006; McCabe, Miller, Laugesen, Antony, & Young, 2010). In fact, although adolescents often characterize racial/ethnic teasing as innocuous, daily teasing experiences are both frequent and lead to short-term increases in anxiety symptoms among adolescents of color (Douglass, Mirpuri, English, & Yip, 2016). This evidence notwithstanding, few studies have specifically focused on teasing as a form of discrimination outside of integrating one or two teasing items (e.g., Harrell, 1997; Tynes et al., 2008). Furthermore, no studies, to our knowledge, have focused on multiple forms of daily teasing experiences that target Black adolescents specifically associated with their race (e.g., targeting skin-tone, hair texture).
Vicarious racial discrimination, or “the secondhand exposure to the racial discrimination and/or prejudice directed at another individual” (p.235; Heard-Garris, Cale, Camaj, Hamati, & Dominguez, 2018) is the least-studied form of racial discrimination among youth (Priest et al., 2013). This is an important consideration because researchers posit that vicarious discrimination directed at peers, family members, and other racial group members may be the most frequent type of discrimination for children and adolescents because, as a function of their social and cognitive development, they have more difficulty recognizing individual discrimination (e.g., Brown & Bigler, 2005; Taylor, Wright, Moghaddam, & Lalonde, 1990). This is relevant to online settings as messages in social media settings are often directed at general groups or other individuals (Tynes et al., 2008). Moreover, a growing body of literature indicates that vicarious racial discrimination contributes to negative psychosocial outcomes among Black adolescents (Heard-Garris et al., 2018; Medina, Lewis, & Pati, 2010). However, there is currently little evidence documenting the daily frequency and impact of several different teasing and vicarious forms of racial discrimination among Black adolescents.
Online forms of racial discrimination
An emerging literature indicates that the Internet is a critical context for racial experiences among Black adolescents (Keum & Miller, 2018; Tynes et al., 2015). Studies have found that the vast majority of Black adolescents use the Internet daily and spend more time online and on social media than their peers from different races/ethnicities (Rideout, Lauricella, & Wartella, 2011). In particular, a Pew Research Center study found that 34% of Black youth report going online “almost constantly,” a substantially higher rate than their White peers (Lenhart & Page, 2015). Critically, evidence indicates that racial discrimination is common in online contexts since they are settings for quasi-anonymous self-expression where discrimination can occur with relative social impunity (Tynes, Reynolds, & Greenfield, 2004). Studies using the Online Victimization Scale (OVS; Tynes, Rose, & Williams, 2010) show associations between online racial discrimination and negative psychosocial outcomes for Black adolescents (e.g., Tynes et al., 2008; Tynes et al., 2010). However, to our understanding, no studies have examined the frequency and impact of daily online racial discrimination using intensive daily longitudinal survey methods. Given the amount of time Black adolescents spend online daily, quotidian measurement of online racial discrimination is necessary to accurately assess its frequency and impact for these youth.
Addressing retrospective and acquiescence biases
Two primary sources of bias potentially affect the validity of current racial discrimination self-report measurement with Black adolescents: retrospective bias and acquiescence bias. Regarding retrospective bias, although the majority of racial discrimination studies have focused on long-term (e.g., one year) and non-specific (e.g., how often in ‘daily life’) timeframes of racial discrimination experiences, more recent evidence suggests that daily racial discrimination assessment may provide more valid frequency estimates (Seaton & Iida, 2019). Indeed, studies that utilize large timeframes for measurement (e.g., one year and a lifetime; e.g., English et al., 2014; Seaton, Caldwell, Sellers, & Jackson, 2008) reduce the chance of accurate and representative recall, which causes retrospective bias (Stone & Shiffman, 2002), especially when assessing highly nuanced stressors like microaggressions (Sue et al., 2008; Wong, Eccles, & Sameroff, 2003). This is particularly relevant given adolescents, as a function of pubertal onset, are in the process of major cognitive developments such as memory refinement, an essential mechanism for measurement through self-report (Bradburn, Rips, & Shevell, 1987).
Studies that use ecological momentary assessment (EMA), the repeated sampling of participants’ experiences over short time periods, help to eliminate many of the retrospective biases inherent in self-report questionnaires, yielding data that are more reliable and accurate (Ong & Burrow, 2017; Stone & Shiffman, 2002). EMA racial discrimination research may, therefore, provide a clearer picture of the frequency of racial discrimination. For example, a study using daily measurement found that Black adolescents experienced racial discrimination an average of 2.44 days over a two-week period (Seaton & Iida, 2019)—a substantially higher estimate than past studies with larger measurement frames (e.g., English et al., 2014). Additionally, a recent meta-analysis found that measures with shorter time frames showed larger effects across psychosocial outcomes, suggesting that EMA studies could be essential to assessing short-term changes in psychosocial outcomes (Benner et al., 2018). In addition to the timeframe, survey methodologists find that multiple specific questions about several social settings within an EMA paradigm aids in participant recall, comprehension, and classification (Schaeffer & Presser, 2003; Tourangeau, 2000). As such, utilizing EMA to assess the impact of a comprehensive set of discrimination experiences (i.e., online, offline, vicarious, and teasing experiences) may be beneficial to examining both frequency and impact of racial discrimination experiences. Moreover, since EMA surveys are administered every day, and the theoretical literature indicates that racial discrimination occurs daily (e.g., Sue et al., 2008), EMA provides a strong opportunity to test the assumptions of those models (Lilienfeld, 2017; Ong & Burrow, 2017).
In addition to retrospective bias, current self-report measures of racial discrimination risk acquiescence bias, or the tendency for respondents to consistently endorse in a single direction on survey scales (Schaeffer & Presser, 2003). Because, to our knowledge, all items in the extant measures of racial discrimination for Black adolescents ask only about negative experiences without counterbalancing with items that vary in their wording, they may encourage automatic and consistent response patterns across items. As a result, these instruments may lead to either the over- or under-estimation of racial discrimination frequency.
Racial discrimination and depressive symptoms
Over 25 years of racial discrimination research with Black adolescents provides robust evidence for a strong link between racial discrimination experiences and depressive symptoms among these youth (see Benner et al., 2018). However, relatively few of these studies have assessed this link longitudinally (see for exceptions: Brody et al., 2006; English et al., 2014) and even fewer have examined associations between racial discrimination and short-term changes in depressive symptoms (Lilienfeld, 2017). This is critical given that understanding the immediate impact of racial discrimination among Black adolescents provides guidance for clinicians, school staff, policy makers, and researchers on how to intervene in the most effective and time-sensitive way (Ong & Burrow, 2017). Thus, it is important to know the types of discrimination that are both the most frequent and most impactful for short-term psychological symptoms among Black adolescents.
The present research
With the present study we sought to examine racial discrimination in multiple forms and contexts to gain an understanding of the multidimensional presentation and impact of daily racial discrimination among Black adolescents in the U.S. In particular, we focused on assessing racial teasing and more general racial discrimination messages (i.e., with a serious tone), racial discrimination in online and offline settings, and through individual and vicarious experiences. Thus, we specified subscales that included individual general experiences, vicarious general experiences, individual teasing, vicarious teasing, individual online experiences, and vicarious online experiences. We then examined their frequencies and tested their associations with changes in depressive symptoms across a two-week period. Additionally, specifically with individual general experiences, we tested tenets of microaggressions theory by examining whether groups of items were interrelated around types of racial microaggressions among Black U.S. Americans highlighted in past studies (Sue et al., 2007; Sue et al., 2008).
In light of past research that suggests the internet is a common social context in which overt racial discrimination is frequently expressed (Keum & Miller, 2018; Tynes et al., 2015), we expected online racial discrimination to be more common among participants than offline discrimination. In addition, given research suggests that young people are more likely to perceive vicarious than individual discrimination because of developmental considerations (e.g., Brown & Bigler, 2005; Taylor et al., 1990), we expected vicarious forms of racial discrimination would be the most frequent. Additionally, we anticipated that all forms of racial discrimination would be positively associated with short-term increases in depressive symptoms. Finally, we engaged in exploratory analyses to examine associations between subscales and key demographic variables (e.g., age) and tested whether racial discrimination subscales were differentially associated with changes in depressive symptoms by comparing the magnitudes of their effect sizes.
Participants were 101 students between the ages of 13 and 17 years old. Eighty-eight percent of participants identified as African American or Black, 1% identified as African, 1% identified as Afro-Latino, 2% identified as biracial/multiracial, and 8% identified as “other” and reported or wrote in an answer (e.g., “mixed with black, white, and indian”). To incorporate the diversity of ways in which participants identified, we use the term ‘Black’ to refer to their race throughout the manuscript. Table 1 presents additional demographic information on the sample.
Table 1. Demographic and psychological variables for participants (N = 101).
|African American or black||89 (88%)|
|Latino or hispanic (Afro-Latino)||1 (1%)|
|Neighborhood Racial Composition|
|Black or African American||96 (96%)|
|White or caucasian||3 (3%)|
|Latino or hispanic||1 (1%)|
|Depressive symptoms (Baseline)||1.82 (0.48)|
|Depressive symptoms (Follow-Up)||1.75 (0.37)|
Note. There is a small amount of missing data for each variable as a result of participant omission.
We collaborated with three different educational programs located in predominantly Black U.S. American neighborhoods in southeast and northeast Washington D.C. to recruit a non-random sample of participants. The racial composition of these schools and neighborhoods reflect those of the majority of Black adolescents in the U.S. who attend predominantly Black schools and live in predominantly Black neighborhoods as a function of high and growing racial segregation in the U.S. (Reardon & Owens, 2014). In total, we had four cohorts of participants from these three educational programs. The first cohort was from a middle school during December 2014 (n = 20); two cohorts came from the same high school: one in May 2015 (n = 54) and another in July 2015 (n = 17); and the final cohort consisted of high school students from a variety of Washington D.C. public schools enrolled in a pre-college academic enrichment summer program during July 2015 (n = 10). Across the four cohorts, we invited six classrooms of students to participate in the study. Of the approximately 120–140 students in these classrooms, 101 students assented and their legal guardians consented for them to be in the study. Summer participants indicated their grade based on the previous school year. For the high school with two cohorts, we cross-checked names and consent forms to ensure that there were no duplicate participants.
The primary purpose of the overall study was to examine a wide array of racial discrimination items for Black youth to establish the most frequent and salient experiences of racial discrimination to inform measure development for EMA studies. As such, our priorities were to collect data on as many racial discrimination items as possible within the restrictions of a daily administration paradigm. This informed our decisions described below to use a random administration design and to measure racial discrimination daily, while measuring depressive symptoms at baseline and follow-up. In particular, given the restrictions of an EMA design, including limits on the number of daily items that can be administered, we decided to utilize the EMA just for the racial discrimination items, administering a random sample of these items to each participant for each administration (Silvia, Kwapil, Walsh, & Myin-Germeys, 2014).
We administered the quantitative research protocols on an Internet-based Qualtrics platform across 15 days for each cohort. The baseline questionnaire occurred on the first day of the study period and included self-report measures of psychosocial outcomes including depressive symptoms. The EMA assessment portion started the day after and occurred for 14 days. Across days, participants received email and text-message reminders to log on to the study server and complete the daily survey. Each day, for each study participant, Qualtrics randomly administered 15 items. We decided on 15 daily items since past EMA research showed that a comparable number of items lead to an acceptable amount of daily participant burden (Douglass et al., 2016). Of these 15 items, 12 were discrimination items and 3 were positively-valenced items meant to counterbalance the item phrasing and protect against acquiescence bias. We designed the positively-valenced items using a comprehensive mixed-methods item development process described in English (2017) to be the opposite of racial discrimination. Thus, we asked about experiencing, witnessing, and interpreting interracial interactions in which racial power was neither exerted nor exploited. In line with a simple matrix design within an EMA framework (Silvia et al., 2014), we used simple randomization for a block of 88 discrimination items and a block of 13 positive items, separately. Thus, on a given day for a given participant, each discrimination item had a 3/22 (12 daily items/88 total items) chance of being administered.
The research team provided a cash incentive for participation based on the number of surveys completed: $30 for 16 surveys (1 baseline, 14 daily surveys, 1 follow-up), $25 for 10–15 surveys, and $15 for less than 10 surveys. Every participant had the opportunity to engage in a debriefing discussion with one of the research team members, each of whom is trained in clinical assessment, racial stress, and treatment of emotional distress. The George Washington University Institutional Review Board (protocol number: 051445, title: Youth Development Study) approved this study protocol.
To assess across individual general, vicarious general, individual online, vicarious online, individual teasing, and vicarious teasing experiences we utilized items from extant measures and also developed original items. We drew the online items from the individual and vicarious subscales of the Online Victimization Scale (Tynes et al., 2010). We drew items for the other subscales from the Perceptions of Racism in Children and Youth (Pachter et al., 2010), Adolescent Discrimination Index (Fisher, Wallace, & Fenton, 2000), Racism and Life Experiences Scale (Harrell, 1997), Schedule of Racist Events (Landrine & Klonoff, 1996), Everyday Discrimination Scale (Clark, Coleman, & Novak, 2004), and Perceived Racism Scale-Child Version (Nyborg & Curry, 2003). The supplemental appendix specifies the items we used from each subscale. These scales predominantly provided items that fit with subtypes of individual general microaggressions. Since teasing and vicarious racial discrimination experiences were the least commonly assessed experiences in the aforementioned measures, we engaged in a comprehensive mixed-methods item development process described in ( English, 2017). We also developed positively-valenced items during the mixed-methods item development process that described experiencing or witnessing positive racial encounters between two people of different races/ethnicities in which racial power was not exerted (e.g., “…did you have a positive discussion about race/ethnicity with a peer of a different racial/ethnic background?”; “…did you see a positive discussion about race/ethnicity on social media [e.g., Facebook, Twitter, Instagram, comments section]?”). The response scale for all items ranged from 0 (Did not happen) to 1 (Happened Once) up to 4 (Happened Four or More Times). We conducted confirmatory factor analysis and alpha statistics to examine reliability among the subscales. This process is described in the Data Analysis section. Although researchers have called into question whether racial discrimination experiences should be tested as effect-indicator models (i.e., with latent variables within CFAs; Lilienfeld, 2017), we deem it appropriate since we expect that each item is an indicator of a broader set of discrimination experiences that are driven by factors such as the social environment, which are acknowledged, but unmeasured here. Items for each subscale, factor loadings, and alphas for scales are presented in Table 2, Table 3, Table 4.