LABELING THEORY CAPSTONE PAPER
Jayden McGowan
ManagingtheConcealableStigmaofCriminalJusticeSystemInvolvementALongitudinalExaminationofAnticipatedStigmaSocialWithdrawalandPostReleaseAdjustment.pdf
Journal of Social Issues, Vol. 73, No. 2, 2017, pp. 322--340 doi: 10.1111/josi.12219
Managing the Concealable Stigma of Criminal Justice System Involvement: A Longitudinal Examination of Anticipated Stigma, Social Withdrawal, and Post–Release Adjustment
Kelly E. Moore∗ and June P. Tangney George Mason University
People with concealable stigmatized identities, such as a criminal record, often anticipate stigma from others. Anticipated stigma is thought to cause withdrawal from situations in which there is the potential for discrimination, which then negatively impacts behavior and functioning. This may have implications for offenders reentering the community, possibly hindering community integration and encouraging maladaptive behavior postrelease. Drawing upon a sample of 197 male jail inmates, we examine a theoretical model in which anticipated stigma during incarceration predicts behavioral outcomes 1 year after release from jail (i.e., recidivism, substance use disorder symptoms, mental health symptoms, community adjustment) through social withdrawal. Anticipated stigma during incarceration predicted social withdrawal three months postrelease, which then predicted more mental health problems 1 year postrelease. Stigma resistance and optimism buffered the effect of anticipated stigma on social withdrawal. Race moderated multiple paths in the model, suggesting that the relations between anticipated stigma, social withdrawal, and adjustment are more pronounced for White offenders.
∗Correspondence concerning this article should be addressed to Kelly E. Moore, Department of Psychiatry, Yale University School of Medicine, 389 Whitney Ave, New Haven, CT 06511. Tel: (203)-785-3225; [E-mail: [email protected]].
This research was supported by Grant #R01 DA14694 from the National Institute on Drug Abuse to June P. Tangney and Grant #5F31DA035037 from the National Institute on Drug Abuse to Kelly E. Moore. Many thanks to the members of the Human Emotions Research Lab for their assistance with this research, and the inmates who participated in this research.
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C© 2017 The Society for the Psychological Study of Social Issues
Managing the Concealable Stigma 323
Introduction
Upon release from incarceration, individuals face many challenges, such as securing housing, staying sober, finding a job, financially supporting them- selves/families, taking care of mental health needs, and finding transportation. In addition to these obstacles, offenders possess the concealable stigmatized iden- tity of having a criminal record and have to manage thoughts and expectations associated with this identity (Quinn, 2017). Will I be discriminated against be- cause of my record? Will others give me a fair chance in the community? Ex- pectations about obstacles can be as detrimental to functioning as the obstacles themselves.
People are inundated with stereotypes about stigmatized groups through- out the life-course and develop expectations about how stigmatized people are treated (Link, Mirotznick, & Cullen, 1991). Upon receiving a stigmatized label, these expectations become personally relevant (Link et al., 1991). Anticipated stigma, the expectation of being discriminated against because of one’s identity, is linked to psychological distress (Quinn & Chaudoir, 2009) and mediates the relations between a) internalized stigma and treatment avoidance in people with physical illness (Earnshaw & Quinn, 2012), and b) perceived stigma and poor community adjustment among offenders (Moore, Stuewig, & Tangney, 2016). Thus, anticipated stigma contributes to poor adjustment, however, the mecha- nisms through which this occurs are unclear. Most stigmatized people anticipate stigma to some degree, and negative expectancies do not always impede behavior. Drawing upon Modified Labeling Theory (Link, Cullen, Struening, Shrout, & Dohrenwend, 1989), anticipated stigma may be problematic when coped with in maladaptive ways.
One form of maladaptive coping worth considering is social withdrawal. So- cial withdrawal is a form of defensive behavioral or disengagement coping, which involves physically or mentally avoiding situations that may involve discrimina- tion (Ilic et al., 2014; Miller & Kaiser, 2001). Defensive behavioral strategies, including concealment and social withdrawal, are used to protect oneself from experiencing discrimination. Social withdrawal can be considered a more extreme form of concealment, as it involves avoidance of contact with others altogether in addition to avoidance of disclosure. Anticipated stigma may prompt defensive behavioral coping; the greater the threat of discrimination, the more likely people are to experience defensiveness, fear, and urges to escape/conceal their identity (Link, Struening, Neese-Todd, Asmussen, & Phelan, 2001) that are associated with withdrawal. Studies show perceived stigma (related to anticipated stigma) is associated with social withdrawal among people with mental illness (Kleim et al., 2008) and anticipation of coping via withdrawal among offenders (Winnick & Bodkin, 2008).
324 Moore and Tangney
At first glance, defensive behavioral coping strategies seem adaptive, in that less exposure to discrimination may limit distress. However, defensive behavioral coping is associated with physical illness and psychological distress (Kaiser & Miller, 2001; Major, Spencer, Schmader, Wolfe, & Crocker, 1998) and longitu- dinally predicts poor mental health (Roubinov & Luecken, 2013) among various stigmatized groups. Avoidance of stigma stressors, particularly within social re- lationships, can be maladaptive (Lattanner & Richman, 2017). Social withdrawal in particular can have multifaceted harmful effects on functioning, as it prevents adapting to stigma stressors (Ilic et al., 2014) and occurs hand in hand with alien- ation, feeling inferior to nonstigmatized others (Ritsher, Otilingam, & Grajales, 2003). Social withdrawal can lead to isolation, diminishing one’s social support, which itself has negative effects on mental health (Miller & Kaiser, 2001). In- deed, using social withdrawal to manage stigma is associated with poor mental health among people with mental illness (Ilic et al., 2014). In addition to negative effects on mental health, social withdrawal may inhibit community participation (Link et al., 1989) and cause failure to fulfill other responsibilities (i.e., paying bills, attending school) (Miller & Kaiser, 2001). For instance, perceived stigma and social withdrawal are associated with unemployment among people with mental illness (Link et al., 1991). Though research has not examined the mediating role of social withdrawal in the relation between anticipated stigma and outcomes, there is evidence that social withdrawal mediates the link between perceived stigma and poor mental health recovery (Chronister, Chou, & Liao, 2013) and poor social interactions (Perlick et al., 2001) among people with mental illness.
Among criminal offenders, coping with anticipated stigma via social with- drawal may not only impact mental health and community participation, but it may increase illicit behaviors. Unlike concealment, which may be adaptive in some so- cial situations for offenders, social withdrawal from nonstigmatized others may break prosocial connections offenders have with community values. Toward this end, Labeling Theory identifies social withdrawal as the reason people persist in criminal behavior, stating that offenders expect discrimination from and hence avoid community domains that provide opportunities to become law-abiding cit- izens, and instead surround themselves with stigmatized others (Lemert, 1951). Having a peer group of offenders is associated with illegal behavior (Bernburg, Krohn, & Rivera, 2006) and substance use (Malouf, Stuewig, & Tangney, 2012). Therefore, social withdrawal may mediate the relation between anticipated stigma and illegal behaviors/substance use in offenders.
Certain people may be less likely to cope with anticipated stigma via social withdrawal. Optimism is a worldview in which people generally expect positive outcomes and use adaptive, engagement coping (Carver, Scheier, & Segerstrom, 2010). Similarly, stigma resistance is a mindset/attitude that one can persevere through the negative effects of stigma (Thoits, 2011), and it is associated with adaptive coping (Sibbetz, Unger, Woppmann, Ridek, & Amering, 2011). People
Managing the Concealable Stigma 325
Anticipated Stigma
Mental Health
Symptoms
Social Withdrawal
Community Adjustment
Substance Use Disorder
Symptoms+
- +
+
Recidivism
+
Race
Attitudes toward Criminals
Stigma Resistance Optimism
Fig. 1. Hypothesized Model. This figure shows the hypothesized model including moderators.
who are highly optimistic, or who possess stigma resistance attitudes may believe they can overcome discrimination and thus not avoid situations potentially involv- ing discrimination. Further, race is an obvious stigma, which leaves people open to more discrimination and thus the opportunity to develop engagement (as opposed to avoidant) coping (Branscombe, Schmitt, & Harvey, 1999; Major, 2012). Man- aging racial stigma over one’s lifetime may also result in less emotional reactivity to other stigma-related threats, precluding avoidance. Nonminorities may conceal their identity and thus not develop such coping strategies. The relation between anticipated stigma and social withdrawal may be attenuated for racial minorities, and people high in optimism and stigma resistance attitudes. For the same reasons, the relation between social withdrawal and outcomes may also be attenuated for racial minorities. Finally, the relation between social withdrawal and illicit be- haviors may be stronger when offenders have positive attitudes about their group; offenders with more positive attitudes may associate more with criminal peers and hence engage in more criminal behavior.
Present Study
This study uses structural equation modeling to examine whether crimi- nal offenders’ anticipated stigma predicts behavioral outcomes through social withdrawal, and whether optimism, stigma resistance, race, and attitudes to- ward criminals moderate these relations (see Figure 1). This study extends re- search on offenders’ perceived stigma and anticipated use of withdrawal coping
326 Moore and Tangney
(Winnick & Bodkin, 2008) as well as research on the effect of offenders’ perceived and anticipated stigma on functioning (Moore, Stuewig, & Tangney, 2013; Moore et al., 2016). This study is one of few to utilize a multivariate longitudinal design and test moderators of these relations.
Method
Participants and Procedures
A university institutional review board approved this study. Participants were 197 male inmates recruited from an adult detention center in 2008–2010 as part of a randomized controlled trial (RCT) of a restorative justice intervention (see Folk et al., 2016). Only sentenced inmates who were likely to serve their sentence at the host jail (i.e., not transferred or deported), and who did not have serious mental health or medical problems were eligible. Inmates were informed participation was voluntary and that data were confidential. Anticipated stigma was assessed at Time 3 (prior to release from jail), social withdrawal was assessed at Time 4 (three months postrelease), and outcomes were assessed at Time 5 (1 year postrelease). Participants received $25 for Time 3, $50 for Time 4, and $100 for Time 5. A total of 203 participants completed the Time 3 assessment and were followed longitudinally. Of these, four passed away and two withdrew, leaving 197 eligible to be reinterviewed at Time 4. Of these, 13 were unable to be reached within the allotted period, four refused, and one was not available at the time of analysis, leaving 179 participants who completed Time 4. Of 197 participants who were eligible for Time 4, 194 were eligible for Time 5 (1 year postrelease), as three other participants withdrew between Time 4 and 5. Of these 194 participants, six could not be reached in the allotted time frame, one refused, and seven were not available for analysis, leaving 180 participants who completed Time 5.
Because some measures were added late, there were missing data; 79 of 203 (61% missing) participants completed anticipated stigma measures at Time 31; 107 of 203 (47% missing) completed social withdrawal measures at Time 4. A total of 52 people had data at all three timepoints. Full Information Maximum Likelihood (FIML), which uses all available data to estimate model parameters, was used to handle missing data.2 This sample (N = 197) includes all people who completed Time 5 (N = 180), participants who completed the anticipated stigma
1 Participants who completed the anticipated stigma measure (N = 79) were not significantly different from those who did not (N = 101) on all model measures and were descriptively similar to the sample analyzed in FIML. They were 32 years old on average (range = 18–65), and racially diverse (41.8% African American, 34.2% Caucasian, 5.1% Hispanic, 13.9% mixed race/other race, 5.1% Asian/Pacific Islander).
2 FIML is encouraged over listwise deletion, which deletes participants with incomplete data and thus creates a biased sample (Schafer & Graham, 2002). FIML is most useful when data are not
Managing the Concealable Stigma 327
measure but did not complete Time 5 (N = 12), and participants who completed the social withdrawal measure at Time 4 but did not complete Time 5 (N = 5). This sample was diverse (mean age = 33, SD = 10.89, range = 18–65; 45.7% African American, 37.1% Caucasian, 10.1% mixed/other; 3.6% Hispanic, 2.5% Asian/Pacific Islander, 1.0% Middle Eastern).
Measures and Data Preparation
Structural equation modeling via Mplus was used to analyze the data. Latent variables were created for all variables with the exception of single-item mod- erators (i.e., attitudes toward criminals)3 and dichotomous variables (i.e., race), which were analyzed as observed. Latent variables were identified using the marker variable method. Indicators that loaded significantly and above .40 were retained. Latent variable names are capitalized throughout. Descriptive statistics are displayed in Table 1. Bivariate correlations are presented in Table 2.
Anticipated stigma was assessed at Time 3 (prior to release) by adapting the 5-item Discrimination Experiences subscale of the Internalized Stigma of Mental Illness scale (ISMI; Ritsher et al., 2003), a reliable measure of various stigma constructs. One item, “People often patronize me, or treat me like a child because I have a mental illness” was not applicable and excluded. Items were reworded to capture expectations (e.g., “People discriminate against me . . . ” was changed to “I expect people to discriminate against me . . . ”). Responses range from 1 (strongly disagree) to 4 (strongly agree). A latent variable used these four items as indicators.
Social withdrawal from nonstigmatized others was assessed at Time 4 (3 months postrelease) by adapting ISMI (Ritsher et al., 2003) social withdrawal (i.e., “I avoid getting close to people who don’t have a criminal record to avoid rejection”) and alienation (“I feel inferior to others who don’t have a criminal record”) subscales. A Social Withdrawal latent variable was created using the six subscale items as three parceled indicators (Little, Cunningham, Shahar, & Widaman, 2002).4
missing for reasons relevant to the phenomenon being measured (Schafer & Graham, 2002; Wothke, 2000). The reason for missing data here (i.e., measures added late) is unrelated to the variables being analyzed.
3 When constructs are assessed with just one item, the latent variable has residual variance set to 0, and loading set to 1, which constitute the same assumptions as observed variables.
4 Parceling involves averaging multiple items, which simplifies structural equation models by decreasing the parameters estimated (Little et al., 2002). Parcels were created by creating a one- construct factor in Mplus with each of the six items as indicators; the three highest factor loadings were chosen as anchors for three parcels, and the remaining indicators assigned to parcels using the balanced approach described in Little et al. (2002).
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Managing the Concealable Stigma 329
Table 2. Bivariate Relationships
Anticipated Stigma Optimism ATC
Stigma Resistance
Social Withdrawal
IV & moderators (prior to release)a
Anticipated Stigma 1 −0.22+ −0.13 −0.07 0.16 Optimism −0.22+ 1 0.25** 0.17+ −0.11 Attitudes toward
Criminals (ATC) −0.13 0.25** 1 0.16 −0.24*
Stigma Resistance −0.07 0.17+ 0.16 1 −0.42** Mediator (3 months postrelease)
Social Withdrawal 0.16 −0.11 −0.24* −0.42** 1 DV’s (1 year postrelease)
Self-reported Arrests −0.23+ 0.04 0.05 0.07 −0.09 Self-reported Offenses −0.10 −0.13+ −0.10 0.08 −0.12 Alcohol 0.13 −0.17+ −0.09 −0.07 0.01 Marijuana 0.01 −0.16+ 0.03 −0.01 0.13 Hard drugs −0.11 −0.13 0.07 0.07 0.03 Cognitive Anxiety 0.21+ −0.33** −0.24* −0.12 0.32** Affective Anxiety 0.19 −0.38** −0.10 −0.13 0.25* Physiological Anxiety 0.17 −0.29** −0.09 −0.18+ 0.31** Cognitive Depression 0.16 −0.42** −0.31** −0.29** 0.31** Affective Depression 0.17 −0.35** −0.24* −0.22* 0.25* Physiological
Depression 0.03 −0.24** −0.06 −0.27* 0.35**
# Hours Employed −0.26* 0.20* −0.01 0.20* −0.10 Community
Functioning Index 0.04 −0.00 −0.08 0.04 0.02
Note. 79 participants completed anticipated stigma measure; N ranged from 54 to 178. a Stigma resistance was assessed at Time 4, 3 months postrelease. +p < .10, *p < .05, ***p < .001.
Latent outcomes replicated an independent sample of inmates (Moore et al., 2016). A Community Adjustment latent variable was created using employment and community functioning activities between Time 4 and 5 (i.e., span of 9 to 21 months). The number of days participants were employed at each job during this time was multiplied by the average hours worked per day, resulting in hours worked at each job. These values were added to obtain total hours employed; 48 of 180 participants who completed Time 5 were unemployed for the entire period, three due to incarceration. Each participant’s total hours employed was multiplied by a ratio of employability (days in time period/days in community) to obtain total hours employed while in the community. This prevented employment from being confounded with recidivism.
The community functioning index captured adaptive functioning in the ar- eas of (a) residential stability, (b) marital status, (c) valid driver’s license, (d)
330 Moore and Tangney
financial support of children, (e) educational and vocational upgrades, and (f) volunteerism between Time 4 and 5. Responses deemed most beneficial for de- sistance from crime were scored 1, and remaining responses were scored 0. Liv- ing in two or fewer places was scored 1 (79.3%) and living in more than two places or being homeless for the entire period was scored 0. Being legally mar- ried (6.2%); financially supported children and paying child support (40.1%); participating in vocational or educational upgrades (i.e., graduating high school, working on/completing vocational training or GED, taking/completing college classes; 23.9%); having a valid driver’s license (26.6%); and participating in non- required volunteer work during the time frame were scored 1 (18.5%). Participants incarcerated for the entire period from Time 4 to 5 (N = 3) were made missing on all items. Scores were averaged across the six indicators to create a total score (see Table 1).
A Recidivism latent variable was composed of self-reported arrests and unde- tected offenses that occurred between 3 and 12 months postrelease. Participants were asked whether they had been arrested for and committed without being arrested for 16 types of crime (i.e., theft, robbery, assault, murder, domestic vi- olence, weapons offenses, major driving offenses, prostitution, drug offenses, sex offenses, fraud, kidnapping, arson, resisting arrest, miscellaneous, other). The number of different types of arrests and offenses (i.e., versatility) was ana- lyzed rather than frequency because the latter is confounded with type of crime (see Table 1).
A Mental Health (MH) Symptoms latent variable was created as a higher order factor composed of Depression and Anxiety latent variables, which were composed of cognitive, affective, and physiological symptom subscales of the widely used, well-validated Personality Assessment Inventory (PAI; Morey, 2007). Responses ranged from 1 (false, not at all true) to 4 (very true). The PAI uses T-scores normed on a community sample of adults.
A Substance Use Disorder (SUD) Symptoms latent variable captured DSM-5 symptoms of abuse/dependence (with the exception of cravings) on cocaine, al- cohol, marijuana, and opiates using Simpson and Knight’s (1998) Texas Christian University: Correctional Residential Treatment Form (TCU-CRTF). Questions referred to substance use 3 months prior to the Time 5 interview; 30 partici- pants who were incarcerated for the entire 3 months did not receive the TCU- CRTF. Responses ranged from 0 (never) to 4 (7 or more times). Given similar- ities between cocaine and opiates (e.g., illegal, highly addictive) and low rate of use in this sample, they were combined into “hard drugs.” The TCU-CRTF is reliable with jail inmates (Stuewig, Tangney, Mashek, Forkner, & Dearing, 2009).
Managing the Concealable Stigma 331
Moderators
An Optimism latent variable was composed of the 4 items from the Values in Action inventory (e.g., “I can always find the positive in what seems negative to others”) administered at Time 3 (VIA; Peterson and Seligman, 2001). This scale has been shown to be reliable and valid with inmates (Heigel, Stuewig, & Tangney, 2010). A Stigma Resistance latent variable (with two τ -equivalent indicators) was composed of two adapted items from the ISMI stigma resistance subscale (Ritsher et al., 2003) administered at Time 4 (i.e., “I can have a good life, despite my criminal record” and “In general, I am able to live life the way I want to, despite my criminal record”). This subscale has adequate test–retest reliability (Ritsher et al., 2003). Race was coded as 0 (White; N = 80) and 1 (Black; N = 93). There were too few participants from other racial groups to analyze separately. Attitudes toward individuals with criminal records was assessed at Time 3 using a single item: “In general, my attitudes toward people with a criminal record are _______?” with responses ranging from 1 (very negative) to 7 (very positive). Because this sample was drawn from a RCT, treatment status (“0” = treatment as usual, “1” = restorative justice intervention) was controlled for.
Results
In the measurement model containing Anticipated Stigma, Social Withdrawal, and outcomes (i.e., Recidivism, SUD Symptoms, MH Symptoms, Community Ad- justment), all indicators loaded significantly above .40 (ranged from .41 to .95) with the exception of the community functioning index, which had a significant loading of .26. This was attributed to low variance; because it loaded significantly, it was retained. The measurement model fit well, χ 2(153) = 220.26, p < .001; RMSEA = .05, CI = 0.03–0.06; CFI = .94, SRMR = .08.5
Structural paths from Anticipated Stigma to Social Withdrawal and Social Withdrawal to outcomes were modeled (see Figure 2). Anticipated Stigma during incarceration predicted Social Withdrawal 3 months postrelease (β = .36, p = .03), which predicted MH Symptoms 1 year postrelease (β = .52, p < .001). The indirect path from Anticipated Stigma to MH Symptoms through Social Withdrawal was marginally significant (β = .19, p = .06) though when bootstrapped, the confi- dence interval included 0, which means the effect may not differ from 0. The paths
5 The measurement model initially produced a nonpositive definite error due to a linear dependency between SUD Symptoms and Recidivism (r = .87, p < .001), in part reflecting the fact that cocaine, opiate, and marijuana use disorder symptoms necessarily entail possession of illegal substances, contributing substantial duplicate variance to Recidivism. This was corrected by removing possession of drugs from Recidivism indicators; the resulting correlation between SUD Symptoms and Recidivism was .77 and the model ran with no errors.
332 Moore and Tangney
Anticipated Stigma
Social Withdrawal
Substance Use Disorder
Symptoms
-.13
.52***
.20
Recidivism
.36*
*p < .05, **p < .001, two-tailed tests χ2(157)= 224.60, p < .001, RMSEA=.05 (CI = .03-.06), CFI=.94 SRMR=.08 Social Withdrawal R2: 12.6%; Recidivism R2: 1.7%; Substance Use Disorder Symptoms R2: 3.9%; Mental Health Symptoms R2: 27.3%; Community Adjustment R2: 5.2% Indirect path from Anticipated Stigma to Mental Health Symptoms: (β = .19, p = .06).
Mental Health
Symptoms
Community Adjustment
-.23
Fig. 2. Structural Model (N = 197). This figure illustrates the structural paths. The legend provides Mplus fit indices.
from Social Withdrawal to Recidivism, SUD Symptoms, and Community Adjust- ment were nonsignificant, although two of three paths were in the hypothesized direction (see Figure 2). The structural model fit well, χ 2(157) = 224.60, p < .001; RMSEA = .05, CI = 0.03–0.06; CFI = .94, SRMR = .08. When controlling for treatment status, all paths remained the same.
The Latent Moderated Structural Equations method (see Klein & Moosbrugger, 2000; Maslowsky, Jager, & Hemken, 2015) was used to perform latent interactions. Two models are tested: Model 0 is the baseline model (i.e., main structural paths) plus the main effect of the moderator, and Model 1 con- tains everything in Model 0 plus the latent interaction. Log-likelihood ratio test (D = –2[(log-likelihood for Model 0) – (log-likelihood for Model 1)]) is used to compare Model 0 and Model 1. Significance is determined using the chi square table and degrees of freedom (df) difference between Model 0 and 1.
We examined whether Stigma Resistance and Optimism moderated the rela- tion between Anticipated Stigma and Social Withdrawal. In Model 0, there was a main effect of Stigma Resistance on Social Withdrawal (β = –.68, p < .001); in Model 1, Anticipated Stigma and Stigma Resistance interacted to predict So- cial Withdrawal (β = –.35, p = .01).6 Figure 3(a) shows that, as predicted, for those high in Stigma Resistance, Anticipated Stigma was unrelated to Social With- drawal, but for those low in Stigma Resistance, Anticipated Stigma was related to Social Withdrawal. Model 1 surpassed the cutoff for a significant df difference of 1 (D = –2[(–3084.71) – (–3079.95)], D = 9.52), indicating Model 0 represented a significant loss in fit compared to Model 1. Similarly, there was a main effect of Optimism on Social Withdrawal in Model 0 (β = –.26, p = .01), and a significant
6 A negative residual variance for Depression was fixed to 0. The confidence interval (CI) for Depression’s residual variance ranged from –0.19 to 0.13; because the CI includes 0, the negative residual variance can be attributed to random sampling variation and set to 0 (Dillon, Kumar, & Mulani, 1987).
Managing the Concealable Stigma 333
(c) (d)
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Fig. 3. (a) Stigma Resistance Moderation. This figure illustrates the interaction of Anticipated Stigma and Stigma Resistance predicting Social Withdrawal (N = 173). (b) Optimism Moderation. This figure illustrates the interaction of Anticipated Stigma and Optimism predicting Social Withdrawal (N = 173). (c) Race Moderation 1. This figure illustrates the interaction of Anticipated Stigma and Race predicting Social Withdrawal (N = 173). (d) Race Moderation 2. This figure illustrates the interaction of Social Withdrawal and Race predicting Community Adjustment (N = 173).
interaction between Anticipated Stigma and Optimism in predicting Social With- drawal (β = –.54, p = .01) in Model 1. Figure 3(b) shows that, as hypothesized, Anticipated Stigma was unrelated to Social Withdrawal for highly optimistic of- fenders, but related to Social Withdrawal for those low in Optimism. Model 0 represented a significant loss in fit compared to Model 1 (D = –2[(–3576.72) – (–3573.61)], D = 6.22).
Race was analyzed via the LMS method (Woods & Grimm, 2011; Muthén & Muthén, 1998–2015); the preferred multigroup method was not possible due to sample size limitations (N = 173; White = 80, Black = 93). Because Type 1 error can be inflated when analyzing categorical variables in the LMS method, results are interpreted with caution. We hypothesized the relation between Anticipated Stigma and Social Withdrawal would be attenuated for racial minorities.7 There
7 There were no significant differences between Black and White offenders’ mean levels of antic- ipated stigma (Black mean = 1.88, SD = 0.80; White mean = 1.95, SD = 0.69; t(58) = –.38, p = .70) or social withdrawal (Black mean = 2.11, SD = 0.52; White mean = 2.13, SD = 0.55; t(84) = –.19, p = .85).
334 Moore and Tangney
was no main effect of race on Social Withdrawal (β = .02, p = .89), but the interaction was significant (β = –.39, p = .04). Figure 3(c) shows that Anticipated Stigma was unrelated to Social Withdrawal for Black offenders but positively related for White offenders. Robustness checks were conducted; split bivariate correlations were consistent, showing anticipated stigma and social withdrawal were correlated for Whites (r = .45, p = .04) but not Blacks (r = –.18, p = .46) (Z = –4.15, p < .001). Also, Model 0 represented a significant loss in fit compared to Model 1 (D = –2[(–2308.306) – (–2306.189)], D = 4.23). We hypothesized the relations between Social Withdrawal and Recidivism, SUD Symptoms, MH Symp- toms, and Community Adjustment would also be attenuated for minorities. There were no interactions in the relation between Social Withdrawal and Recidivism (β = –.05, p = .68), SUD Symptoms (β = .05, p = .65), or MH Symptoms (β = –.03, p = .81), but there was an interaction for Community Adjustment (β = .38, p = .01). Figure 3(d) shows that for Whites, Social Withdrawal was negatively related to Community Adjustment, but not for Blacks. Split bivariate correlations were consistent; social withdrawal was negatively related to employment (r = –.42, p = .02) and community functioning (r = –.21, p = .25) for Whites but unrelated to employment (r = .11, p = .46; Z = –3.48, p < .001) and community functioning (r = .10, p = .53; Z = –4.15, p < .001) for Blacks. Model 1 was superior to Model 0 (D = –2[(–2307.667) – (–2304.141)], D = 7.05). Finally, we hypothesized attitudes toward criminals would attenuate the relation between Social Withdrawal and Recidivism and SUD Symptoms. There was no main effect (β = –.10, p = .35) or interaction (β = –.04, p = .76) for Recidivism and no main effect (β = .07, p = .56) or interaction (β = .08, p = .18) for SUD Symptoms.
Discussion
The more stigma offenders anticipated during incarceration, the more likely they were to withdraw from social interactions and feel isolated from people with- out a criminal record 3 months postrelease. Social withdrawal then predicted more mental health problems 1 year postrelease. This indirect effect was marginally significant (and nonsignificant when a more conservative bootstrapping test was conducted), thus replication is needed. Importantly, race moderated several paths, making it an important factor to consider when interpreting the results. Specif- ically, anticipated stigma only predicted social withdrawal for White offenders. Therefore, the indirect effect from anticipated stigma to MH symptoms would likely have been stronger if examining only White inmates, and would not have generalized to Blacks inmates.
This study also showed that social withdrawal at three months postrelease predicted poor adjustment in the community 1 year postrelease for White but not Black offenders. Compared to White offenders, Black offenders may be more likely to use active, engagement coping skills due to prior experience coping
Managing the Concealable Stigma 335
with racial stigma. Further, withdrawing socially may have more devastating behavioral consequences for Whites. Social withdrawal from the community is likely associated with shame and hopelessness about community adjustment for all races. However, Blacks are shown to have higher self-esteem compared to their nonstigmatized counterparts (Crocker & Major, 1989), so even if they avoid situations that involve the potential for stigma, this may not negatively affect their sense of self or ability to participate in the community. Alternatively, it may be that arrest and incarceration are more normative in Black offenders’ immediate communities, as they are incarcerated at higher rates than Whites. This may lead to perceived stigma from the community at large but lack of social withdrawal from the immediate community. These interactions are consistent with recent findings in an independent sample of inmates in which anticipated stigma predicted worse community adjustment for White but not Black offenders (Moore et al., 2016). Another alternative explanation is that Black offenders have less variance in community adjustment at 1 year postrelease compared to White offenders, attenuating the relation between Black offenders’ social withdrawal and community adjustment (i.e. floor effect). This is plausible, as research shows White offenders have an advantage over Black offenders in obtaining employment after release from prison (Pager, Western, & Sugie 2009); however, post hoc t- tests showed that Whites and Blacks had equal variance and means in Community Adjustment indicators. This lends more support to differential effects of social withdrawal on postrelease community adjustment for Blacks versus Whites.
Our findings are consistent with the limited empirical research showing that offenders’ perceived stigma is associated with anticipated use of withdrawal as a way to cope with stigma (Winnick & Bodkin, 2008), and extend this research by us- ing a longitudinal design and assessing actual use of social withdrawal to cope with stigma. Our findings also extend research on offenders’ experience with and man- agement of the stigma associated with having a criminal record. Most research on offender stigma emphasizes the impact of stigma on recidivism, not mental health or community adjustment, and thus, it was unclear whether anticipated stigma had the same consequences for offenders as it does in other stigmatized groups. Our findings suggest Modified Labeling Theory (MLT; Link et al., 1989), which identifies avoidant coping as a mechanism through which stigma damages mental health and community participation, is supported in offenders. Offenders who expect unfair treatment avoid situations involving the potential for discrimination, which over time may diminish social support and self-efficacy, increasing depres- sion and anxiety (Quinn & Earnshaw, 2013). Some offenders likely use adaptive coping (i.e., preparing for discrimination), which would bolster rather than impede functioning. Research on coping and interventions that address coping is needed.
Anticipated Stigma did not predict recidivism or substance use via so- cial withdrawal as hypothesized. If anything, results showed anticipated stigma and social withdrawal led to less recidivism. The only other study examining
336 Moore and Tangney
anticipated stigma and criminal behavior (Moore et al., 2013) found no relation between anticipated stigma and recidivism. It may be that anticipated stigma causes impairment in community adjustment, which in turn later, down the line, leads to recidivism via various mechanisms (i.e., driving on suspended license, probation violation, failure to pay child support). Anticipating stigma may leave ex-offenders on the fringes of the community, with ample opportunities to engage in criminal behavior, but longitudinal assessment beyond 1 year may be neces- sary to detect such distal effects. Alternatively, offenders may have withdrawn from both nonstigmatized and stigmatized others (i.e., criminal offenders), which would eliminate the mechanism of increased illicit behavior via antisocial peers. Unlike other stigmatized groups, social withdrawal could have both positive and negative effects on offenders’ functioning, thereby cancelling out effects on illicit behavior. This is an important direction for research. Finally, the relation between social withdrawal and recidivism and SUD symptoms generalized across offenders with varying attitudes toward their group, suggesting this construct may not be particularly influential in this population.
As hypothesized, the effect of anticipated stigma on social withdrawal was buffered by optimism and stigma resistance. These findings are consistent with re- search showing optimism is a protective factor and brings about active, engagement coping (Carver et al., 2010). People who are highly optimistic or possess stigma resistance attitudes may believe they can overcome stigma-related adversity, or re- frame negative predictions about discrimination. Both of these moderators appear to be important in buffering the negative effects of stigma on maladaptive coping, and are important beliefs to bolster in stigmatized people.
Limitations
This study has several limitations. Our sample was too small to analyze a multigroup test that could compare the entire model, including indirect effects for Black versus White inmates. There may be a significant indirect effect be- tween Anticipated Stigma and Community Adjustment via Social Withdrawal for White offenders. This is an important direction for future research. In addition, this sample was all male and from one jail. Therefore, generalizability to females and inmates in different correctional facilities (especially prisons) is unknown. A final limitation is that some relevant variables were not assessed here. The decision to conceal or disclose one’s stigmatized identity may cause distress (Newheiser & Baretto, 2014) and be a motivation for coping via social withdrawal (Quinn, 2017). Disclosing one’s stigmatized identity can have psychological ben- efits (Chaudoir & Quinn, 2010); however, this is unknown for offenders who face significant consequences on the job market and other areas after disclo- sure. It is also worth noting that alienation and social withdrawal subscales were drawn from a measure of internalized stigma; internalized stigma refers to the
Managing the Concealable Stigma 337
acceptance of stereotypes as personally descriptive (Corrigan, Watson, & Barr, 2006), whereas alienation and social withdrawal are considered behavioral con- sequences of internalized stigma here. Anticipated stigma may be more strongly linked to social withdrawal for those high in internalized stigma, making internal- ized stigma another important variable to examine in future research.
Clinical and Policy Implications
Oftentimes, offenders have difficulty accessing services in the community, and offenders with mental health issues are likely to repeatedly cycle through the criminal justice system (Skeem, Manchak, & Peterson, 2011). There is a critical need for policy that supports and facilitates offenders receiving mental health and other treatment after incarceration. In addition, anticipated stigma is a key point of intervention to prevent later mental health issues. Expectations about discrimination and ways of coping with these expectations are malleable and have been targeted with cognitive-behavioral interventions (Mittal, Sullivan, Cherkuri, Allee, & Corrigan, 2012; Lucksted et al., 2011). Interventions focused on behavioral control (i.e., Dialectical Behavior Therapy skills; Linehan, 1993) may be especially helpful in buffering the effects of anticipated stigma. Innovative interventions addressing anticipated stigma among this population are needed.
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KELLY E. MOORE is a postdoctoral fellow at Yale University School of Medicine. Her research interests include health and risk behaviors that contribute to crimi- nal justice system involvement, evidence-based treatments for offenders, and the psychological implications of being in a stigmatized group.
JUNE TANGNEY is a University Professor and Professor of Psychology at George Mason University. Her research interests include moral emotions and cognitions, strengths and virtues, and interventions with offenders.
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