TY - JOUR
AU - Joe,, Sean
AB - Abstract The prevalence of community-based violence (CBV) exposure among black American male emerging adults ages 18 to 25 with a history of involvement with the criminal justice system is a major public health concern. Although exposure (whether as victim or witness) to CBV is linked with negative outcomes, empirical research examining black men’s negative emotional responses to seeing videos of real-life incidents of CBV on social media is scant. To address these identified concerns and make recommendations for future research, the present study examines the relationship between seeing videos of CBV on social media and three types of negative emotional responses (that is, feeling sad, angry, and fearful) prior to incarceration among a sample of 101 black men detained in a midwestern jail. Social media use and seeing videos of CBV on social media were moderately high for study participants. Seeing a video involving police violence was significantly associated with an increase in the odds of feeling sad, angry, and fearful. Social media research is an emerging area that has the potential to advance our understanding of the impact of seeing social media videos of police violence on the well-being of black men and factors that mediate or moderate this relationship. Exposure to community-based violence (CBV) is a major public health concern for black male emerging adults with a history of involvement with the criminal justice system in the United States, given its prevalence and association with behavioral health problems (Dahlberg & Mercy, 2009; Motley & Banks, 2018; Motley, Sewell, & Chen, 2017; Office of the Surgeon General, 2001; Sheats et al., 2018). CBV is defined as direct (that is, victimization) or indirect (that is, witnessed event in person) exposure to the threat or use of interpersonal violence (for example, being chased, shootings, homicide, and other types of serious physical harm) committed in public areas (Fowler, Tompsett, Braciszewski, Jacques-Tiura, & Baltes, 2009; Rosenthal, 2000; Schwartz & Proctor, 2000; Wilson & Rosenthal, 2003). Data from the Bureau of Justice Statistics show that 2,336 per 100,000 black men are sentenced to prison or jail compared with 1,054 per 100,000 Hispanic men and 397 per 100,000 white men (Bronson & Carson, 2019; Zeng, 2019), and the majority of these men are between 18 to 29 years of age (Bronson & Carson, 2019; Child Trends Databank, 2016). Furthermore, between 62% and 98% of incarcerated men report exposure to at least one CBV event prior to incarceration (Breslau, 2009; Pettus-Davis, 2014; N. Wolff, Huening et al., 2014), compared with 22% to 47% of men in the general population (Briere & Elliott, 2003; Kilpatrick et al., 2013). The advent of social media has created online communities that put black men at risk for increased rates of exposure to CBV through videos (Acosta & Spencer, 2016; Peralta, 2016; Spangler, 2016). Social media has been defined as “Internet-based channels that allow users to opportunistically interact and selectively self-present, either in real-time or asynchronously, with both broad and narrow audiences who derive value from user-generated content and the perception of interaction with others” (Carr & Hayes, 2015, p. 50). Cell phones, iPads, and iPods are some of the devices used to record and upload videos of CBV onto various social media platforms like Facebook, Twitter, and Instagram. Gang activity, physical assaults, robberies, and fatal incidents involving police use of force against black men are just some of the violent incidents captured on video. Some of the videos are live, exposing viewers to the violence in real time, and have been viewed more than several million times (Acosta & Spencer, 2016; Peralta, 2016; Seetharaman, 2016; Spangler, 2016). Social media has become one of the most used platforms for communication among black emerging adults, with 70% reporting using Facebook, 76% YouTube, and 26% Twitter, in comparison with their white counterparts (67%, 71%, and 24%, respectively) (Bostic, 2014; Noble, 2015; Smith & Anderson, 2018). Emerging adulthood is a period of identity exploration and transition for black men (Arnett, 2016), and social media platforms provide online communities that enable these young adults to express themselves, socialize with their peers, and engage in identity exploration (R. Wolff, McDevitt, & Stark, 2011; Wright, 2017). An emerging field of scholars have conducted ethnographic, computational, and survey-based research focused on unpacking the role of social media in CBV, particularly for youths and emerging adults involved in gangs (Decker & Pyrooz, 2012; Moule, Pyrooz, & Decker, 2013; Patton, Eschman, & Butler, 2013; Patton et al., 2014). Studies using community samples of emerging adults involved in street crime show that 81% use social media and spend more hours on a weekly basis frequenting social media platforms than their non–crime involved peers (10.5 hours, compared with 3.8 hours) (Moule et al., 2013; Pyrooz, Decker, & Moule, 2015) and use social media to post threats, videos, and pictures of violent acts perpetrated by them or one of their fellow peers as a way to show or gain respect (Patton et al., 2013). In addition, research found that urban gang-involved black youths use social media to express their grief regarding the killing of their peers by police and plans for retaliation (Patton et al., 2016). Many black male emerging adults with a history of involvement with the criminal justice system have been exposed (whether as victim or witness) to police use of force and other forms of CBV (for example, being chased, shootings, homicide, and other types of serious physical harm) (Boxer, Schappell, Middlemass, & Mercado, 2011; Komarovskaya, Booker Loper, Warren, & Jackson, 2011; Kubiak, 2004; Meade, Steiner, & Klahm, 2015; Struckman-Johnson & Struckman-Johnson, 2000). Moreover, research has documented a positive relationship between exposure to CBV and mental and behavioral health problems (Bor, Venkataramani, Williams, & Tsai, 2018; Dahlberg & Mercy, 2009; DeVylder et al., 2018; DeVylder et al., 2017; Fowler, Ahmed, Tampsett, Jozefowitz-Simbeni, & Toro, 2008; Geller, Fagan, Tyler, & Link, 2014; Meade et al., 2015; Motley et al., 2017; Office of the Surgeon General, 2001; Rosenthal & Hutton, 2001; Scarpa et al., 2002; Scarpa, Haden, & Hurley, 2006; Voisin, Chen, Fullilove, & Jacobson, 2015). However, we have scant empirical research examining criminal justice–involved black male emerging adults’ negative emotional responses to seeing videos of real-life incidents of CBV on social media prior to incarceration. There is an important distinction between experiencing CBV in person (as a victim or witness) and watching a video of a real-life incident of CBV on social media. Exposure to CBV in person may have a direct influence on a black male individual because he is familiar with the community and connected to people and places in that environment. In contrast, the CBV captured on video and posted to social media can happen anywhere, and the influence from viewing this content may be more indirect. The relevance and significance of the violence captured on video to a black male emerging adult’s self-schema is an influential factor that can channel his negative influence (Kira et al., 2008). The indirect effect may be greatest when a black male individual personalizes the event and considers himself similar to the victim (Becker-Blease, Finkelhor, & Turner, 2008; Dixon, Rehling, & Shiwach, 1993), lives in an affected area (Pine, Costello, & Masten, 2005; Trautman et al., 2002), or was also a victim to similar violence (Moore et al., 2016). Therefore, it is reasonable to consider that viewing videos of real-life incidents of CBV on social media may evoke negative emotional responses for some black men (Adetiba & Almendrala, 2016; Kira et al., 2008; Maercker & Mehr, 2006; Moore et al., 2016). The present exploratory study examines the relationship between exposure to videos of real-life incidents of CBV on social media and three types of negative emotional responses (that is, feeling sad, angry, and fearful) prior to incarceration among a sample of black male emerging adults detained in a medium-size midwestern city jail, while controlling for sociodemographic factors, frequency of social media use, and previous witnessing of community violence (WCV) in person. Method Sample Participants in the current study were 102 male emerging adults who self-identified as black and were 18 to 25 years of age (M = 22.6) detained in a medium-size midwestern city jail. One respondent who identified as white was excluded from the sample, resulting in a sample size of 101. Participants were part of a larger study designed to assess the effects of the Fathers Make a Difference: A Reentry Mentoring Project. The project is funded by the Office of Juvenile Justice and Delinquency Prevention and provides participants with pre- and post-release case management, post-release workforce activities leading to employment, post-release mentoring services, and services to promote responsible fatherhood. Procedures The current study was granted ethical approval by a university-based institutional review board. Researchers visited the selected study site and met with staff to introduce the project and describe the procedures of recruitment and data collection. Researchers worked with staff to schedule individual information and informed consent sessions with prospective participants in a private meeting room. Researchers conducted informed consent procedures for men interested in participating in the study. Men who self-reported being a father, between the ages of 18 and 25, English speaking, and having an expected release date within the next 60 days were eligible to participate in the study. Individuals who were not a father, charged with a sex offense, and did not have an expected release date within the next 60 days were excluded from participating in the study. A total of 125 potential participants were screened, and 23 were excluded due not meeting the age requirement (n = 8) or not having an expected release date from jail within the next 60 days (n = 15). At least two research assistants were available to administer the surveys to individuals who met eligibility criteria and consented to participate in the study. To manage the range in reading levels of the participants, the research assistants read all questions aloud and marked the responses given by the participant for each survey item. Measures WCV in person in the six months prior to incarceration was assessed using Richters and Martinez’s (1990) Things I Have Seen and Heard measure that assesses the frequency of participants’ exposure (through seeing or hearing) to violence in their home and neighborhood. Things I Have Seen and Heard contains 12 items ranked on a four-point Likert scale ranging between 0 = never and 3 = many times to measure a respondent’s exposure to violence in the community, and this scale has demonstrated good test–retest reliability and validity in prior studies (Richters & Martinez, 1990; Richters & Martinez, 1993a, 1993b). Examples of survey items included “I have heard guns being shot,” “I have seen drug deals,” and “I have seen gangs in my neighborhood.” A total possible score ranged from 0 to 36, with a higher score indicating more frequent experiences of WCV. Cronbach’s alpha for this measure was .87. Frequency of social media use in the six months prior to incarceration was assessed by asking each participant how often they used five social media platforms—Facebook, Instagram, Twitter, YouTube, and WorldStarHipHop—using a seven-point Likert scale ranging between 0 = never use and 6 = several times a day. The score was summed (range = 0–30), with a higher score indicating more use of social media. Cronbach’s alpha for this measure was .70. The Exposure to Community-Based Violence through Social Media Survey was used to measure participants’ exposure to videos of real-life incidents of CBV on social media in the six months prior to their incarceration. This survey was developed specifically for this study and contains six items modified from the Richters and Martinez’s (1990) Things I Have Seen and Heard measure, which assesses exposure (through seeing or hearing) to CBV in the home and neighborhood. The Exposure to Community-Based Violence through Social Media Survey uses a four-point Likert scale ranging from 0 = never to 3 = many times to measure respondents’ exposure to videos of CBV on social media. Examples of survey items included “On social media, I have seen a video of someone getting shot by police in a community” and “On social media, I have seen a video of someone getting robbed in a community.” An exploratory factor analysis was conducted to examine the factor structure of the Exposure to Community-Based Violence through Social Media Survey. The initial assessment showed that the commonalities across items were high, with values all above .62. In a simulation study that considers both the sample size issue and related diagnostics when conducting factor analysis, MacCallum, Widaman, Zhang, and Hong (1999) suggested that, although a larger sample size remains preferred, with high communalities (.6 or higher), a relatively small sample size (in their study, N = 100) is adequate for factor analysis. Furthermore, a higher Kaiser–Meyer–Olkin value (in this study, .70) and a significant test of Bartlett’s test (χ2 = 218.22, p < .001) suggested the feasibility of using factor analysis. Following the recommendations made by Field (2009), we used varimax rotation with an eigenvalue greater than 1 to explore the factor structure. Results showed that two factors—police violence (two items) and civilian violence (three items)— were extracted. One item from the police violence factor was excluded due to a small loading. Police violence (eigenvalue = 2.70) explained 54% of the variance with a range of factor loading between .67 and .68 (α = .93). Civilian violence (eigenvalue = 1.06) explained 21% of the variance with a range of factor loading between .45 and .65 (α = .67). These results were supported by Stevens (2002), in that for a sample size of 100 the loading should be greater than .5. Each factor was summed, with higher scores indicating more frequent exposure to videos of CBV on social media. Negative emotional response to viewing videos of CBV on social media was assessed by asking participants three separate questions, each using a five-point Likert scale ranging from 0 = never to 4 = all the time. The first question asked participants, “How often do you feel sad after viewing the video?” the second question asked participants, “How often do you feel angry after viewing the video?” and the third question asked participants, “How often do you feel fearful after viewing the video?” After an examination of the distribution of the measures, results revealed that a small proportion of respondents (ranging from 5% to 9%) responded with “rarely” or “often” when compared with other response categories. Therefore, we collapsed each measure into three levels: low (never or rarely), medium (sometimes), and high (often or all the time). These three separate measures were used as the dependent variables in this study. Age, educational attainment, and individual income were used as sociodemographic variables in the current study. Age was self-reported and was measured continuously. Educational attainment was originally an ordinal measure whereby participants reported their highest degree (from 1 = no high school to 8 = master’s degree). We dichotomized the education variable into a binary measure, with 0 = no college experience (including some high school experience, high school degree, and GED) and 1 = college experience (including some college, college degree, and technical degree). Respondents also reported their income level based on three categories that included no income, less than $10,000, and $10,000 and above. Analysis Univariate analysis and bivariate analyses (independent t test and F test) were conducted to explore the association between the categorical sociodemographic factors (that is, education and income groups) and key continuous constructs in this study (that is, WCV in person, use of social media, and seeing videos of CBV on social media). Equal variance assumptions for the bivariate analyses were met. Ordinal logistic regressions analysis was used to examine the association between sociodemographic factors, WCV in person, use of social media, seeing videos of CBV on social media, and negative emotional response for the study sample. To isolate each negative emotional response measure, we performed three ordinal logistic regression models for each negative emotional outcome. The regression diagnostics results showed that multicollinearity was not an issue as the largest variance inflated factor was 1.40, and all three ordinal logistic regressions passed the parallel odds assumption as the Brant test for each model showed an insignificant result (Brant, 1990). Missing values were found among variables of income, WCV in person, and use of social media, with approximately 11% of respondents missing when these variables were considered together. We therefore used multiple imputation with chained equations to handle the nonresponsiveness among variables (White, Royston, & Wood, 2011). With suggestions made by Graham, Olchowski, and Gilreach (2007), we created 20 imputed data sets to address the uncertainty of missing values across imputed data sets; the results were combined using Rubin’s rule (Rubin, 1987). All analyses were performed using Stata 14.0. Results Univariate and Bivariate Analysis The participants in this study were 101 black male emerging adults (mean age = 22.7 years) detained in a medium-size midwestern city jail. Approximately 84% of participants had no college experience (including some high school experience 44%, high school degree 26%, and GED 14%), and 41.8% self-reported having no income (see Table 1). WCV in person, social media use, and seeing videos of CBV on social media were moderately high for study participants. In addition, the majority of participants self-reported experiencing moderate levels of sadness, high levels of anger, and low levels of fear after viewing videos of CBV on social media. Table 1 Sample Descriptive Statistics (N = 101) Variable . n (%) . M (SD) . Range . Age (years) 22.7 (1.97) 18–25 Education  No college experience 85 (84.2)  College experience 16 (15.8) Income groups  No income 41 (41.8)  Less than $10K 22 (22.5)  $10K or more 35 (35.7) WCV in person 15.8 (7.27) 0–36 Social media use 12.33 (5.02) 0–30 Seen video of CBV  Police violence 3.77 (2.24) 0–6  Civilian violence 2.24 (2.36) 0–9 Sadness after viewing video of CBV  Low 23 (22.8)  Medium 38 (37.6)  High 40 (36.9) Anger after viewing video of CBV  Low 27 (26.7)  Medium 36 (35.6)  High 38 (37.6) Fearful after viewing video of CBV  Low 55 (54.5)  Medium 18 (17.8)  High 28 (27.7) Variable . n (%) . M (SD) . Range . Age (years) 22.7 (1.97) 18–25 Education  No college experience 85 (84.2)  College experience 16 (15.8) Income groups  No income 41 (41.8)  Less than $10K 22 (22.5)  $10K or more 35 (35.7) WCV in person 15.8 (7.27) 0–36 Social media use 12.33 (5.02) 0–30 Seen video of CBV  Police violence 3.77 (2.24) 0–6  Civilian violence 2.24 (2.36) 0–9 Sadness after viewing video of CBV  Low 23 (22.8)  Medium 38 (37.6)  High 40 (36.9) Anger after viewing video of CBV  Low 27 (26.7)  Medium 36 (35.6)  High 38 (37.6) Fearful after viewing video of CBV  Low 55 (54.5)  Medium 18 (17.8)  High 28 (27.7) Notes: WCV = witnessed community violence; CBV = community-based violence. Open in new tab Table 1 Sample Descriptive Statistics (N = 101) Variable . n (%) . M (SD) . Range . Age (years) 22.7 (1.97) 18–25 Education  No college experience 85 (84.2)  College experience 16 (15.8) Income groups  No income 41 (41.8)  Less than $10K 22 (22.5)  $10K or more 35 (35.7) WCV in person 15.8 (7.27) 0–36 Social media use 12.33 (5.02) 0–30 Seen video of CBV  Police violence 3.77 (2.24) 0–6  Civilian violence 2.24 (2.36) 0–9 Sadness after viewing video of CBV  Low 23 (22.8)  Medium 38 (37.6)  High 40 (36.9) Anger after viewing video of CBV  Low 27 (26.7)  Medium 36 (35.6)  High 38 (37.6) Fearful after viewing video of CBV  Low 55 (54.5)  Medium 18 (17.8)  High 28 (27.7) Variable . n (%) . M (SD) . Range . Age (years) 22.7 (1.97) 18–25 Education  No college experience 85 (84.2)  College experience 16 (15.8) Income groups  No income 41 (41.8)  Less than $10K 22 (22.5)  $10K or more 35 (35.7) WCV in person 15.8 (7.27) 0–36 Social media use 12.33 (5.02) 0–30 Seen video of CBV  Police violence 3.77 (2.24) 0–6  Civilian violence 2.24 (2.36) 0–9 Sadness after viewing video of CBV  Low 23 (22.8)  Medium 38 (37.6)  High 40 (36.9) Anger after viewing video of CBV  Low 27 (26.7)  Medium 36 (35.6)  High 38 (37.6) Fearful after viewing video of CBV  Low 55 (54.5)  Medium 18 (17.8)  High 28 (27.7) Notes: WCV = witnessed community violence; CBV = community-based violence. Open in new tab The bivariate analysis showed that respondents who had college experience showed higher levels of WCV in person, use of social media, and seeing videos of CBV on social media. However, there was only marginal or no significant difference compared with their counterparts with no college experience. A sensitivity test was conducted whereby education was categorized into three levels (below high school [45.10%], high school [39.22%], and college [15.69%]). Both bivariate and multivariate analyses showed that the results remained unchanged and the effect of education was not significant. In addition, there was no significant difference in WCV in person, use of social media, and seeing videos of CBV on social media by income levels (see Table 2). Table 2 WCV in Person, Use of Social Media Web Sites, and Seeing Videos of Community Violence on Social Media by Education and Income Level . Education . . Income . . . . College . . . . . . . No College . Experience . . No Income . <$10,000 . ≥$10,000 . . Variable . M (SD) . M (SD) . t . M (SD) . M (SD) . M (SD) . F . WCV in person 15.16 (7.37) 19.00 (6.00) −1.95† 16.68 (7.84) 15.15 (8.13) 15.72 (6.15) .31 Use of social media 11.95 (4.83) 14.47 (5.69) −1.81† 11.95 (4.99) 12.90 (4.97) 12.31 (5.37) .24 Seen video of CBV  Police violence 3.66 (2.29) 4.38 (1.85) −1.18 3.65 (2.18) 3.86 (2.32) 3.89 (2.27) .11  Civilian violence 2.22 (2.31) 2.31 (2.77) 0.89 2.37 (2.31) 2.32 (2.93) 2.14 (2.18) .08 . Education . . Income . . . . College . . . . . . . No College . Experience . . No Income . <$10,000 . ≥$10,000 . . Variable . M (SD) . M (SD) . t . M (SD) . M (SD) . M (SD) . F . WCV in person 15.16 (7.37) 19.00 (6.00) −1.95† 16.68 (7.84) 15.15 (8.13) 15.72 (6.15) .31 Use of social media 11.95 (4.83) 14.47 (5.69) −1.81† 11.95 (4.99) 12.90 (4.97) 12.31 (5.37) .24 Seen video of CBV  Police violence 3.66 (2.29) 4.38 (1.85) −1.18 3.65 (2.18) 3.86 (2.32) 3.89 (2.27) .11  Civilian violence 2.22 (2.31) 2.31 (2.77) 0.89 2.37 (2.31) 2.32 (2.93) 2.14 (2.18) .08 Notes: WCV = witnessed community violence; CBV = community-based violence. †p < .10. Open in new tab Table 2 WCV in Person, Use of Social Media Web Sites, and Seeing Videos of Community Violence on Social Media by Education and Income Level . Education . . Income . . . . College . . . . . . . No College . Experience . . No Income . <$10,000 . ≥$10,000 . . Variable . M (SD) . M (SD) . t . M (SD) . M (SD) . M (SD) . F . WCV in person 15.16 (7.37) 19.00 (6.00) −1.95† 16.68 (7.84) 15.15 (8.13) 15.72 (6.15) .31 Use of social media 11.95 (4.83) 14.47 (5.69) −1.81† 11.95 (4.99) 12.90 (4.97) 12.31 (5.37) .24 Seen video of CBV  Police violence 3.66 (2.29) 4.38 (1.85) −1.18 3.65 (2.18) 3.86 (2.32) 3.89 (2.27) .11  Civilian violence 2.22 (2.31) 2.31 (2.77) 0.89 2.37 (2.31) 2.32 (2.93) 2.14 (2.18) .08 . Education . . Income . . . . College . . . . . . . No College . Experience . . No Income . <$10,000 . ≥$10,000 . . Variable . M (SD) . M (SD) . t . M (SD) . M (SD) . M (SD) . F . WCV in person 15.16 (7.37) 19.00 (6.00) −1.95† 16.68 (7.84) 15.15 (8.13) 15.72 (6.15) .31 Use of social media 11.95 (4.83) 14.47 (5.69) −1.81† 11.95 (4.99) 12.90 (4.97) 12.31 (5.37) .24 Seen video of CBV  Police violence 3.66 (2.29) 4.38 (1.85) −1.18 3.65 (2.18) 3.86 (2.32) 3.89 (2.27) .11  Civilian violence 2.22 (2.31) 2.31 (2.77) 0.89 2.37 (2.31) 2.32 (2.93) 2.14 (2.18) .08 Notes: WCV = witnessed community violence; CBV = community-based violence. †p < .10. Open in new tab Correlates of Negative Emotional Responses Table 3 shows the unique contribution of sociodemographic factors, WCV in person, social media use, and seeing a video of CBV on social media (that is, police and civilian violence) for predicting each type of negative emotional response (sadness, anger, and fear). Feeling sad after seeing a video of CBV on social media was included in model I as the outcome variable. Results showed that the odds of a participant with no college experience feeling sad after seeing a video of CBV on social media was 3.76 (95% confidence interval [CI]: 1.21, 11.67) times more likely than participants with college experience, while holding all other variables constant, and the effect was statistically significant. In addition, seeing a video of CBV on social media that involved police violence was significantly associated with an increase in the odds of feeling sad after seeing the video, with an odds ratio of 1.47 (95% CI: 1.18, 1.82). Table 3 Summary of Ordinal Logistic Regression Analysis for Variables Predicting Sadness, Anger, and Fear (N = 101) . Sadness Model I . Anger Model II . Fear Model III . Variable . OR . [95% CI] . OR . [95% CI] . OR . [95% CI] . Age 1.07 [0.87, 1.31] 1.11 [0.90, 1.35] 1.09 [0.87, 1.36] Education (ref = college experience)  No college experience 3.76* [1.21, 11.67] 1.44 [0.45, 4.56] 1.99 [0.55, 7.26] Income (ref = greater than $10K)  No income 1.48 [0.61, 3.61] 0.70 [0.29, 1.71] 0.81 [0.30, 2.17]  Less than $10K 2.08 [0.69, 6.26] 0.66 [0.23, 1.94] 1.18 [0.38, 3.68 WCV in person 0.97 [0.91, 1.03] 0.97 [0.91, 1.04] 0.89** [0.82, 0.97] Social media use 0.98 [0.92, 1.06] 1.03 [0.95, 1.11] 1.03 [0.94, 1.13] Seen video of CBV  Police violence 1.47*** [1.18, 1.82] 1.40*** [1.14, 1.72] 1.56*** [1.20, 2.02]  Civilian violence 1.01 [0.84, 1.21] 1.05 [0.87, 1.25] 1.08 [0.88, 1.33] Model pseudo R2 0.0956 0.0833 0.1319 . Sadness Model I . Anger Model II . Fear Model III . Variable . OR . [95% CI] . OR . [95% CI] . OR . [95% CI] . Age 1.07 [0.87, 1.31] 1.11 [0.90, 1.35] 1.09 [0.87, 1.36] Education (ref = college experience)  No college experience 3.76* [1.21, 11.67] 1.44 [0.45, 4.56] 1.99 [0.55, 7.26] Income (ref = greater than $10K)  No income 1.48 [0.61, 3.61] 0.70 [0.29, 1.71] 0.81 [0.30, 2.17]  Less than $10K 2.08 [0.69, 6.26] 0.66 [0.23, 1.94] 1.18 [0.38, 3.68 WCV in person 0.97 [0.91, 1.03] 0.97 [0.91, 1.04] 0.89** [0.82, 0.97] Social media use 0.98 [0.92, 1.06] 1.03 [0.95, 1.11] 1.03 [0.94, 1.13] Seen video of CBV  Police violence 1.47*** [1.18, 1.82] 1.40*** [1.14, 1.72] 1.56*** [1.20, 2.02]  Civilian violence 1.01 [0.84, 1.21] 1.05 [0.87, 1.25] 1.08 [0.88, 1.33] Model pseudo R2 0.0956 0.0833 0.1319 Notes: Results were based on 20 multiple imputation data sets. WCV= witnessed community violence; CBV = community-based violence. *p < .05. **p < .01. ***p < .001. Open in new tab Table 3 Summary of Ordinal Logistic Regression Analysis for Variables Predicting Sadness, Anger, and Fear (N = 101) . Sadness Model I . Anger Model II . Fear Model III . Variable . OR . [95% CI] . OR . [95% CI] . OR . [95% CI] . Age 1.07 [0.87, 1.31] 1.11 [0.90, 1.35] 1.09 [0.87, 1.36] Education (ref = college experience)  No college experience 3.76* [1.21, 11.67] 1.44 [0.45, 4.56] 1.99 [0.55, 7.26] Income (ref = greater than $10K)  No income 1.48 [0.61, 3.61] 0.70 [0.29, 1.71] 0.81 [0.30, 2.17]  Less than $10K 2.08 [0.69, 6.26] 0.66 [0.23, 1.94] 1.18 [0.38, 3.68 WCV in person 0.97 [0.91, 1.03] 0.97 [0.91, 1.04] 0.89** [0.82, 0.97] Social media use 0.98 [0.92, 1.06] 1.03 [0.95, 1.11] 1.03 [0.94, 1.13] Seen video of CBV  Police violence 1.47*** [1.18, 1.82] 1.40*** [1.14, 1.72] 1.56*** [1.20, 2.02]  Civilian violence 1.01 [0.84, 1.21] 1.05 [0.87, 1.25] 1.08 [0.88, 1.33] Model pseudo R2 0.0956 0.0833 0.1319 . Sadness Model I . Anger Model II . Fear Model III . Variable . OR . [95% CI] . OR . [95% CI] . OR . [95% CI] . Age 1.07 [0.87, 1.31] 1.11 [0.90, 1.35] 1.09 [0.87, 1.36] Education (ref = college experience)  No college experience 3.76* [1.21, 11.67] 1.44 [0.45, 4.56] 1.99 [0.55, 7.26] Income (ref = greater than $10K)  No income 1.48 [0.61, 3.61] 0.70 [0.29, 1.71] 0.81 [0.30, 2.17]  Less than $10K 2.08 [0.69, 6.26] 0.66 [0.23, 1.94] 1.18 [0.38, 3.68 WCV in person 0.97 [0.91, 1.03] 0.97 [0.91, 1.04] 0.89** [0.82, 0.97] Social media use 0.98 [0.92, 1.06] 1.03 [0.95, 1.11] 1.03 [0.94, 1.13] Seen video of CBV  Police violence 1.47*** [1.18, 1.82] 1.40*** [1.14, 1.72] 1.56*** [1.20, 2.02]  Civilian violence 1.01 [0.84, 1.21] 1.05 [0.87, 1.25] 1.08 [0.88, 1.33] Model pseudo R2 0.0956 0.0833 0.1319 Notes: Results were based on 20 multiple imputation data sets. WCV= witnessed community violence; CBV = community-based violence. *p < .05. **p < .01. ***p < .001. Open in new tab Feeling anger after seeing a video of CBV on social media was included in model II as the outcome variable. Results showed that seeing a video of CBV on social media that involved police violence was significantly associated with an increase in the odds of feeling anger after seeing the video, while controlling for all other predictors, with an odds ratio of 1.40 (95% CI: 1.14, 1.72). Feeling fearful after seeing a video of CBV on social media was included in model III as the outcome variable. Results revealed that WCV in person was significantly associated with a decrease in the odds of feeling fearful after seeing a video of CBV on social media, while controlling for all other predictors, with an odds ratio of 0.89 (95% CI: 0.82, 0.97). In contrast, seeing a video of CBV on social media that involved police violence was significantly associated with an increase in the odds of feeling anger after seeing the video, with an odds ratio of 1.56 (95% CI: 1.20, 2.02). However, age, income, and social media use were not significant predictors of negative emotional response in any of the ordinal logistic regression models. Discussion Social media platforms allow users to create profiles, share information, and build and maintain social and professional networks (Carr & Hayes, 2015; Cheung, Chiu, & Lee, 2011; Patton et al., 2013). However, a growing number of videos of real-life CBV are recorded and uploaded to various social media platforms, putting individuals at risk for experiencing negative emotional responses as a result of viewing such content. The current study extends previous social media and CBV research and provides novel findings regarding the relationship between seeing videos of real-life CBV on social media and negative emotional responses, six months prior to incarceration, among a sample of black male emerging adults involved with the criminal justice system. The majority of black young men in the current study were low-income and reported moderately high rates of seeing videos of CBV on social media. However, seeing a video on social media that involved police violence was the only type of CBV significantly associated with an increase in the odds of feeling sad, angry, or fearful. Findings from the current study suggest that the individuals perpetrating the CBV in videos seen on social media—versus the type of violence—is more emotionally impactful for black male emerging adults with a history of involvement with the criminal justice system. Police officers have an entrusted professional role to safeguard the well-being of the citizens they serve. Yet, only 44.2% of black emerging adults report that they trust the police compared with their white (71.5%) and Latino (59.6%) counterparts (Rogowski & Cohen, 2015). Exposure to police violence may be more impactful for individuals who perceive police as a threat to their personal safety. The negative emotional responses to videos of police violence on social media by black young men in the current study may be attributed to the prevalence of police violence toward black young men in the United States (Butler, 2017; Davis, 2017; Swaine & McCarthy, 2017). Research shows that per population size, black male emerging adults in United States are more likely than their white and Hispanic counterparts to experience direct exposure to police threat or use of force (Bureau of Justice Statistics, 2015) and be killed by police while unarmed (Centers for Disease Control and Prevention [CDC], 2017; Mapping Police Violence, 2017; ``Fatal Force,'' 2017; ``The Counted,'' 2018). Black young men in the current study may have also perceived the police violence in the videos as being excessive or unfair (Hyland, Langton, & Davis, 2015; Motley & Joe, 2018), outside of their control (Adetiba & Almendrala, 2016; Butler, 2017; Moore et al., 2016), and absent of any dire consequences for the perpetrators (Adetiba & Almendrala, 2016; Butler, 2017; Horace & Harris, 2018; Moore et al., 2016), which may have contributed to their negative emotional responses. However, the relationship between exposure to videos of CBV on social media and negative emotional responses warrants further investigation to confirm the assumption that the individuals perpetrating the CBV, versus the type of violence in videos seen on social media, is more emotionally impactful for black young men. In contrast, WCV in person was significantly associated with a decrease in the odds of feeling fearful after viewing a video of CBV on social media for black men in the current study. This finding lends support to prior research suggesting a desensitization effect to violence seen in the media (Fanti & Avraamides, 2011; Krahé et al., 2011; Mrug, Madan, Cook, & Wright, 2015). For example, Mrug et al. (2015) found a negative correlation between exposure to higher levels of real-life violence and emotional distress when viewing TV or movies depicting violence for a sample of emerging adults. However, the violence viewed on TV or in movies in the aforementioned study was fictional, whereas the videos viewed on social media in the current study were real-life events. Limitations Several limitations should be noted in this study. First, the cross-sectional design used in the study limited our ability to establish temporal precedence and make causal inferences about seeing videos of real-life CBV on social media and negative emotional responses (that is, sadness, anger, and fear). Second, reliance on self-reported accounts of black male WCV in person, use of social media, seeing videos of real-life CBV on social media, and negative emotional responses may have minimized findings due to biases inherent in self-reporting. Third, although results from exploratory factor analysis showed that this scale has good fit, our newly developed Exposure to Community-Based Violence through Social Media Survey has not been validated in previous studies and future studies need to examine the psychometric property for this measure. Fourth, the current study would have been strengthened by the use of negative emotional response variables that have demonstrated validity and reliability in prior research. Finally, the sample used in the current study is a convenience sample and may not be generalizable beyond black male emerging adults incarcerated in a midwestern city jail. Despite the limitations, the current study extends previous social media and CBV research and provides novel findings regarding the relationship between seeing videos of real-life CBV on social media and negative emotional responses prior to incarceration among a sample of black male emerging adults, carrying implications for future research, practice, and policy. Implications and Conclusion To our knowledge, this is the first study to quantify exposure to videos of real-life CBV by type (civilian violence and police violence) on social media. Coupled with disparate rates of police violence toward black men in the United States (CDC, 2017; ``Fatal Force,'' 2017; Mapping Police Violence, 2017; ``The Counted,'' 2018) and black men’s perceptions of police violence as being excessive and unfair (Motley & Joe, 2018; Hyland et al., 2015), many black men may come to view police officers as merely another threat to their physical safety and overall well-being (Butler, 2017). In addition to experiencing negative emotional responses, exposure to videos involving real-life incidents of police violence on social media may introduce or augment existing mental and behavioral problems for black men (Becker-Blease et al., 2008; Center for Substance Abuse Treatment, 2013; Dixon et al., 1993; Otto et al., 2007; Pfefferbaum et al., 2001). For example, a Brooklyn photographer reported experiencing nightmares, anxiety, depression, and fear of police after watching videos of police using excessive force on black citizens (Lartey, 2016). The photographer also spoke of instinctively locking his car door at the sight of a police cruiser. Given the dearth of empirical research examining this relatively new phenomenon, future studies should rely on more rigorous sampling techniques and research designs to investigate the short- and long-term effects of exposure to videos of police violence on social media on the mental, emotional, and behavioral outcomes of black male emerging adults and factors that mediate or moderate this relationship. In addition, further research examining the relationship between WCV in person and desensitization to seeing videos of real-life CBV on social media is essential. Social media research is an emerging area that has the potential to make substantial contributions to the field of science and advance practitioners and policymakers’ understanding of its impact on the well-being of black male emerging adults. Understanding this new phenomenon may inform policies focused on effective policing practices that are culturally relevant and ensure the safety of police and the community residents they serve, and alternative preventive and intervention strategies focused on reducing rates of exposure to videos of real-life CBV and attenuating associated negative outcomes. Robert O. Motley, Jr., MSW, and Yu-Chih Chen, MSW, are PhD candidates, George Warren Brown School of Social Work, Washington University in St. Louis. Carnayla Johnson, MSW, is clinical trial assistant, Hennepin Health Care Research Institute, Minneapolis. Sean Joe, PhD, is Benjamin E. Youngdahl professor of social development, George Warren Brown School of Social Work, Washington University in St. Louis. Address correspondence to Robert O. Motley, Jr., George Warren Brown School of Social Work, Washington University in St. Louis, 1 Brookings Drive, St. Louis, MO 63130; e-mail: motley.r@wustl.edu. This study was funded by the Office of Juvenile Justice and Delinquency Prevention (2014-IGBX-0005). Robert O. Motley, Jr., received predoctoral fellowship funding from the National Institute of Mental Health. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health. References Acosta , A. , & Spencer , J. ( 2016 ). Technology’s impact on exposing police brutality. Retrieved from https://amandaacostarws200.wordpress.com/2016/03/01/technologys-impact-on-exposing-police-brutality-final/ Adetiba , L. , & Almendrala , A. ( 2016 ). Watching videos of police brutality can traumatize you, especially if you’re black: “You never know if you’re going to be that next case”. Retrieved from https://www.huffingtonpost.com/entry/watching-police-brutality-videos_us_577ee9b3e4b0344d514eaa5d Arnett , J. J. ( 2016 ). 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Retrieved from https://www.bjs.gov/content/pub/pdf/ji17.pdf © 2020 National Association of Social Workers This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
TI - Exposure to Community-Based Violence on Social Media among Black Male Emerging Adults Involved with the Criminal Justice System
JO - Social Work Research
DO - 10.1093/swr/svaa002
DA - 2020-06-04
UR - https://www.deepdyve.com/lp/oxford-university-press/exposure-to-community-based-violence-on-social-media-among-black-male-3ke767miRd
SP - 87
VL - 44
IS - 2
DP - DeepDyve
ER -