self-stigma and quality of life among people with mental illness who receive compulsory community...

A R T I C L E

SELF-STIGMA AND QUALITY OFLIFE AMONG PEOPLE WITHMENTAL ILLNESS WHO RECEIVECOMPULSORY COMMUNITYTREATMENT SERVICESJames LivingstonForensic Psychiatric Services Commission, British Columbia, Canada

The present study was designed to examine the relationship betweenself-stigma and quality of life over a one year time period for 71 people withmental illness who were receiving compulsory community mental healthtreatment. It was hypothesized that, over time, self-stigma would have thedirect effect of eroding quality of life among people with mental illness whowere receiving compulsory community treatment; however, this relationshipwas not confirmed by the data. Although the cross-sectional analysesrevealed a moderate, negative relationship between self-stigma and qualityof life, the longitudinal analyses indicated that self-stigma was not asignificant predictor of quality of life. Among the variables measured in thecurrent study, psychiatric symptom severity was the strongest predictor ofquality of life. C© 2012 Wiley Periodicals, Inc.

INTRODUCTION

The harmful effects of stigma on the lives of people with mental illness are thoroughlydocumented in the research literature. Self-stigma has been linked to hopelessness, poorself-esteem, decreased empowerment, reduced treatment adherence, and increased symp-tom severity (Livingston & Boyd, 2010). Though there is debate about what constitutesthe stigma construct (Link & Phelan, 2001; Manzo, 2004; Parker & Aggleton, 2003; Prior,Wood, Lewis, & Pill, 2003; Weiss, Ramakrishna, & Somma, 2006), self-stigma has beendefined in relation to mental illness as a subjective process that is “characterized by

Correspondence to: Dr. James Livingston, 70 Colony Farm Road, Port Coquitlam, British Columbia, Canada,V3C5X9. E-mail: [email protected]

JOURNAL OF COMMUNITY PSYCHOLOGY, Vol. 40, No. 6, 699–714 (2012)Published online in Wiley Online Library (wileyonlinelibrary.com/journal/jcop).C© 2012 Wiley Periodicals, Inc. DOI: 10.1002/jcop.21476

700 � Journal of Community Psychology, August 2012

negative feelings (about self), maladaptive behaviour, identity transformation, or stereo-type endorsement resulting from an individual’s experiences, perceptions, or anticipa-tion of negative social reactions on the basis of their mental illness” (Livingston & Boyd,2010, p. 2151). Although self-stigma is influenced by powerful macro-socio-cultural factors(Herek, 2007; Scambler, 2006; Yang et al., 2007), it manifests and is experienced at theindividual level. Unlike social and structural levels of stigma (Corrigan, Kerr, & Knudsen,2005; Herek, Gillis, & Cogan, 2009), self-stigma must be studied from, and anchoredby, the vantage point of people who live with the labels, statuses, or conditions deemedsocially undesirable.

The negative effects of stigma may be most acutely felt by people with mental illnesswho are ordered to receive compulsory community treatment. Research suggests thatcompulsory community treatment may increase the likelihood that people with mentalillness are exposed to situations perceived to be stigmatizing, which contributes to feelingsof powerlessness and oppression (Livingston & Rossiter, 2011). Consistent with the notionthat people who have mental illness should be treated in the least restrictive setting, com-pulsory community treatment provides another strategy for those who are not in need oftraditional involuntary hospitalization, but still require treatment, supervision, and sup-port. The two types of compulsory community treatment existing within British Columbia(BC), Canada are extended leave and conditional discharge. An extended leave is a legaloption under the civil Mental Health Act of BC, enabling a psychiatric hospital to transitiona civilly committed individual into the community and to evaluate their ability to functionin the community. A conditional discharge is similar to an extended leave; however, it isordered through the Criminal Code of Canada for individuals with mental illness who areadjudicated “Not Criminally Responsible on account of Mental Disorder” (NCRMD) or“Unfit to Stand Trial.” Under both forms of compulsory community treatment, the personwith mental illness remains under the control and supervision of a mental health profes-sional (e.g., psychiatrist) and is legally required to comply with a prescribed treatmentplan and other conditions (e.g., abstain from alcohol or drugs). Failure to comply withcompulsory community treatment conditions will result in the person being involuntarilydetained and indeterminately rehospitalized, which may be a factor that hampers socialreintegration.

Although self-stigma is referenced widely as a substantial obstacle in the mental healthrecovery process, the exact nature of its influence on health and social outcomes remainsunclear. The degree to which self-stigma causes or exacerbates poorer outcomes amongpeople with mental illness has important implications for mental health services and pol-icy. For example, to what degree should mental health programs and interventions aimedat improving the quality of life of people with mental illness concentrate on perceptionsand experiences of self-stigma, as opposed to other clinical or psychosocial factors? Sim-ilarly, should governments expect to achieve widespread improvements to quality of lifeby prioritizing efforts aimed at reducing self-stigma? And, lastly, should quality of life beemployed as an outcome measure to assess the effectiveness of self-stigma interventions?Such questions can be addressed through empirical investigations of how, and to whatextent, self-stigma adversely impacts variables related to mental health rehabilitation andrecovery.

One important variable to consider is quality of life—a construct that encompassesseveral key life domains for people with mental illness, including subjective well-being,life satisfaction, functioning in daily life, and external resources (Katschnig, 2000). Thepotential for self-stigma to negatively influence quality of life is consistent with mod-ified labeling theory, which suggests that people who anticipate and perceive mental

Journal of Community Psychology DOI: 10.1002/jcop

Self-Stigma and Quality of Life � 701

illness-related stigma may, as a result of maladaptive coping strategies, experience negativeconsequences across several life domains (Link, Struening, Cullen, Shrout, & Dohren-wend, 1989). Similarly, a literature review on the social and clinical determinants ofquality of life has also indicated that “although the scientific evidence so far is not over-whelming, stigma experiences in a broader sense might be a target for intervention withrelevance for quality of life” (Hansson, 2006, p. 50). Moreover, several authors have sug-gested that stigma may negatively influence quality of life for people with mental illnessby perpetuating exclusionary processes and decreasing opportunities for participationin important domains of conventional life, such as employment, education, and socialactivities (Corrigan et al., 2005; Finzen & Hoffman-Richter, 1997; Katschnig, 2000; Wahl,1999). A recent meta-analysis examining the variables associated with self-stigma founda moderate, negative relationship between self-stigma and quality of life (r = −.47) forpeople with mental illness across several cross-sectional studies (Livingston & Boyd, 2010);however, the longitudinal nature of this relationship has rarely been studied.

In one longitudinal study, the experiences of individuals who received communitymental health services either voluntarily (n = 108) or involuntarily (n = 86) were com-pared on a number of variables, including perceived coercion, self-stigma, and qual-ity of life (Link, Castille, & Stuber, 2008; Phelan et al., 2010). One of the main find-ings was that regardless of whether the participants received voluntary or involuntarytreatment services, higher perceptions of coercion were associated with increased self-stigma and reduced quality of life. The authors concluded by suggesting that address-ing the root causes of perceived coercion may be an effective strategy for reducingperceptions of stigma and improving quality of life (Link et al., 2008). Although thisstudy contributes additional insight into the association between perceptions of coercionand self-stigma for people with mental illness, it does not shed light on the relation-ship between self-stigma and quality of life because these two variables were analyzedindependently.

Four other longitudinal studies have considered the association between self-stigmaand quality of life among people with mental illness who were not receiving compulsorytreatment. A study conducted by Lysaker, Davis, Warman, Strasburger, and Beattie (2007)examined the relationship between self-stigma, psychiatric symptoms, and quality of lifeamong 35 individuals with severe mental illness over a 6-month period. They foundsignificant cross-sectional correlations between self-stigma and quality of life, but did notdetect a significant relationship between self-stigma at baseline and quality of life at 6-month follow-up. Although the study offers preliminary findings about the relationshipbetween these two variables, it did have some methodological limitations including a smallsample size and a measure of quality of life that did not attend to life domains beyondsocial functioning.

In another study with a larger sample size (n = 188), Marcussen, Ritter, and Munetz(2010) found a nonsignificant association between baseline self-stigma and change inquality of life for people with mental illness over a 6-month period. This finding providessome confirmation of the results from the aforementioned study (Lysaker et al., 2007);however, the researchers speculate that the effect of stigma on quality of life might havebeen more pronounced if the study period was extended beyond 6 months. The findingsof two other longitudinal studies by Markowitz (1998, 2001), which used a large sample(n ∼ 600) and extended follow-up period (18 months), found a small (β = −.07 to −.21)but significant (P < .05) negative relationship between self-stigma and life satisfaction(a domain of quality of life). Although the methodological strengths of the Markowitzstudies addressed several limitations of the other studies described above, the author



acknowledged that examination of the longitudinal relationship between self-stigma andquality of life may have been limited by the fact that self-stigma was assessed at follow-upbut not at baseline.

The dearth of longitudinal research in this area, and the limitations of the existingstudies, has constrained the conclusions and inferences that can be drawn about theassociation between self-stigma and quality of life. Additional longitudinal research—in different contexts and with diverse samples—is needed to precisely disentangle therelationship and temporal order between these two variables. This article reports onlongitudinal data from a mixed-methods study examining the stigma experiences amongpeople with mental illness receiving compulsory community treatment. Cross-sectionalfindings and qualitative data have been published elsewhere (Livingston, Rossiter, &Verdun-Jones, 2011; Livingston & Rossiter, 2011). The data presented here investigatethe longitudinal relationship between self-stigma and quality of life among the studyparticipants. Consistent with modified labeling theory, it was hypothesized that self-stigmaat baseline (T1) would predict subsequent quality of life (T2), and that change in self-stigma would predict change in quality of life during the 1-year study period. This studyrepresents the only longitudinal research to date that has evaluated the degree to whichbaseline self-stigma contributes to quality of life 1 year later in a sample of individuals withmental illness. Moreover, no published studies to date have described the relationshipbetween self-stigma and quality of life among people with mental illness who receivecompulsory community treatment services. The findings of the current study contributeto both of these areas of research.

METHOD

Participants

A non-probabilistic sampling approach was used to recruit study participants from severalcommunity mental health centers primarily situated in the Metro Vancouver area. At thetime of recruitment, each participant was receiving compulsory community treatmentservices within either the civil or the forensic mental health systems of BC. Inclusioncriteria for entry into the study were as follows: (a) certified under the BC Mental HealthAct (civil client) or adjudicated NCRMD under the Criminal Code of Canada (forensicclient); (b) receiving compulsory community treatment for at least 30 days; (c) 18 to 65years of age; (d) capable of communicating in English; (e) diagnosed by their treatingpsychiatrist with either schizophrenia, other psychotic disorder, or bipolar disorder; and(f) deemed suitable to participate by their primary mental health service provider (i.e.,clinically stable, not aggressive or hostile, sufficient cognitive capacity).

During the 33-month recruitment period, 288 individuals were identified as satisfyingthe study’s inclusion criteria. Of these, 91 (32%) individuals agreed to participate, 125(43%) explicitly refused to participate, and 72 (25%) agreed to participate but wereunable to because of logistical reasons (e.g., failure to attend multiple appointments).The relatively high rate of research refusals and missed appointments was expected,given that treatment noncompliance, low illness insight, and poor service engagementare prevalent issues for compulsory treatment populations. Of the 91 participants whoenrolled in the study, 73 (80%) completed the 1-year follow-up interview. The reasons forattrition were that participants could not be reached or scheduled for another interview(n = 12), they explicitly refused to be interviewed (n = 3), they were deceased at follow-up



(n = 2), or their poor mental state did not permit an interview (n = 1). Two participantswere removed from the dataset on account of missing data.

Therefore, the analysis is based on the remaining 71 participants, which provides anobserved power of .77 for multiple regression analysis with a .05 alpha level and medium(f 2 = .15) effect size (Soper, 2010). A comparison of the baseline data for individualswho did (n = 71) and did not (n = 20) contribute to the final dataset indicated thetwo groups did not significantly differ with respect to client type, χ2(1) = .47, P > .05;age, t(89) = .88, P > .05; gender, χ2(1) = .05, P > .05; ethnicity, χ2(1) = .002, P >

.05; relationship status, χ2(1) = .88, P > .05; employment status, χ2(1) = 2.65, P > .05;education level, χ2(1) = 2.41, P > .05; history of homelessness, χ2(1) = .47, P > .05;years with mental illness, t(89) = .09, P > .05; primary psychiatric diagnosis, χ2(3) = .84,P > .05; or presence of substance use diagnosis, χ2(1) = .03, P > .05. An overview of theparticipants’ characteristics is provided in Table 1.

Materials and Procedure

The study used a prospective, longitudinal design, with a 1-year time interval between base-line and follow-up periods. The primary data collection method was in-person, semistruc-tured interviews using standardized measures to assess self-stigma, quality of life, andpsychiatric symptoms. Each standardized measure was administered in an interview for-mat by reading the questions aloud to the participants and visually displaying the questionson a laptop computer. All interviews were conducted by the principal investigator or adoctoral student, both of whom were not blinded to the study hypotheses. Interviews wereperformed between April 2006 and December 2009, and were held in private within amental health setting, such as a community mental health clinic or group home. Par-ticipants were paid $20CDN for the baseline interview and $30CDN for the follow-upinterview. The research protocol for the present study was approved by the Simon FraserUniversity Research Ethics Board and written informed research consent was obtainedfrom each participant.

Quality of life. Quality of life was measured using the Wisconsin Quality of Life Index(WQL; Becker, Diamond, & Sainfort, 1993). The WQL is a self-report, comprehen-sive, multidimensional measure of quality of life for persons with severe mental illness.The WQL comprises open-ended and closed-ended items addressing eight different do-mains, including life satisfaction, occupational activities, psychological well-being, physicalhealth, social relationships, finances, activities of daily living, and psychiatric symptoms.The WQL total (unweighted) score comprises 48 items demonstrating good internalconsistency at T1 (Cronbach α = .82).

Psychiatric symptoms. Psychiatric symptom severity was measured using the Behaviorand Symptom Identification Scale-24 (BASIS24; (Eisen, Gerena, Ranganathan, Esch, &Idiculla, 2006). The BASIS24 is a self-report measure for assessing the symptom severityand functional difficulties of people with mental illness. The BASIS24 comprises 24 itemsassessing six areas of difficulty and distress, including depressive symptoms, interpersonalrelationships, psychotic symptoms, alcohol/drug use, emotional lability, and self-harm.The BASIS24 total score demonstrated good internal consistency at T1 (Cronbach α =.81).



Table 1. Participants’ Sociodemographic and Clinical Characteristics

Variables M SD n %

Age (years) 39.39 12.13 71Years with mental illness 12.72 10.88 71Gender

Male 55 77.5Female 16 22.5

EthnicityWhite 44 62.0Aboriginal 9 12.7Asian/South Asian 8 11.2Black 2 2.8Other 8 11.3

Education levelDid not complete high school/GED 30 42.3Completed high school/GED 41 57.7

Relationship statusMarried 43 60.6Unmarried 28 39.4

Employment statusEmployed 15 21.1Unemployed 56 78.9

On income assistanceYes 64 90.1No 7 9.9

Primary psychiatric diagnosisSchizophrenia 44 62.0Schizoaffective disorder 15 21.1Other psychotic disorder 8 11.3Bipolar disorder 4 5.6

Substance use diagnosisYes 38 53.5No 33 46.5

Client typeForensic mental health 42 59.2Civil mental health 29 40.8

Psychiatric symptoms (BASIS24 at T1)Depressive symptoms 0.77 0.60 71Relationships 1.11 0.75 71Self-harm 0.08 0.33 71Emotional lability 0.68 0.72 71Psychotic symptoms 0.58 0.78 71Substance use 0.63 0.75 71Total 0.72 0.44 71

Note. M = mean; SD = standard deviation; BASIS24 = Behavior and Symptom Identification Scale-24.

Self-stigma. Self-stigma was measured using the Internalized Stigma of Mental Illness(ISMI) scale (Ritsher, Otilingam, & Grajales, 2003). The ISMI is a self-report question-naire designed to measure the internalized, subjective experiences of stigma for peopleliving with mental illness. The ISMI poses a series of statements for which participants areasked to rate their level of agreement using a 4-point anchored Likert scale, ranging from1 (strongly disagree) to 4 (strongly agree). The ISMI comprises 29 items and five subscales:alienation, stereotype endorsement, discrimination experience, social withdrawal, and



stigma resistance. The ISMI total score demonstrated excellent internal consistency at T1(Cronbach α = .89).

Analytic Strategy

Change in self-stigma and quality of life from T1 to T2 were assessed with paired t tests.Preliminary examination of the relationship between self-stigma and quality of life waspreformed using several bivariate correlation analyses. A multiple hierarchical linearregression analysis was then performed to further assess the relationship between self-stigma at baseline (T1) and quality of life at follow-up (T2). To control for the effects of T1quality of life, it was forced into the regression model first in addition to other potentialconfounding variables. Sociodemographic and clinical variables that were significantlyassociated with both the predictor variable (T1 self-stigma) and the outcome variable(T2 quality of life) were considered potential confounders, and were entered into theregression models as covariates. Self-stigma at T1 was forced into the second step of theregression model. A second multiple hierarchical linear regression analysis was performedto assess the extent to which change in self-stigma predicted change in quality of life aftercontrolling for T1 quality of life, T1 self stigma, and T1 psychiatric symptoms. A thirdand final multiple linear hierarchical regression analysis was performed to examine thedegree to which T1 self-stigma moderated the direction and/or strength of the relationbetween T1 psychiatric symptoms and T2 quality of life. First, the predictor (T1 psychiatricsymptoms), moderator (T1 self-stigma), control (T1 quality of life), and outcome (T2quality of life) variables were mean-centered (Cohen, Cohen, West, & Aiken, 2003).Then, an interaction term was created by multiplying the centered predictor by thecentered moderator variable. T2 quality of life was added as the dependent variable andthe predictor, control, and moderator variables were forced into the first step of theregression model. Next, the interaction variable was forced into the second step of themodel. All analyses were performed using SPSS version 14.

RESULTS

Self-Stigma

The average scores on the ISMI subscales are presented in Table 2. The proportion ofparticipants scoring above the mid-point (2.5) on the ISMI subscales and total score—indicating high levels—at T1 were as follows: alienation 28% (n = 20), stereotypeendorsement 6% (n = 4), discrimination experience 35% (n = 25), social withdrawal23% (n = 16), stigma resistance 9% (n = 6), and total self stigma 9% (n = 6). Paired ttests revealed that the change in ISMI subscale and total average scores from T1 to T2did not reach significance. Therefore, self-stigma remained stable at a group level fromT1 to T2.

Quality of Life

The average scores on the WQL are also presented in Table 2. Paired t tests indicatedthat the change in WQL subscale and total scores over the 1-year study period did notreach significance, with the exception of activities of daily living, which demonstrated asignificant decline from T1 to T2, t(70) = 2.06, P < .05.



Self-Stigma and Quality of Life

Table 3 displays the bivariate correlations of quality of life (T1 and T2) with T1 self-stigma and T1 psychiatric symptoms. T1 self-stigma was significantly related to severaldomains of quality of life at baseline, including T1 life satisfaction (r = −.35, P < .01), T1psychological well-being (r = −.37, P < .01), T1 social relationships (r = −.26, P < .05),and T1 overall quality of life (r = −.35, P < .01). Therefore, at baseline, a higher level ofself-stigma was associated with a lower level of quality of life. This is similar to the patternand strength of the relationship between T1 psychiatric symptoms and T1 quality of life.

Regarding the association between T1 self-stigma (total) and T2 quality of life (total),the finding was consistent with hypothesized negative direction of the relationship (r =−.17), but it was not statistically significant (P > .05). T1 self-stigma was significantlyrelated with T2 social relationships (r = −.24, P < .05); however, partial correlationanalysis revealed that the association was no longer significant after controlling for T1social relationship (Partial r = −.10, P > .05). T1 social relationships was not significantlyassociated with T2 self-stigma (total; r = −.18, P > .05), but a partial correlation analysisindicated that it was significantly associated with T2 stigma resistance (partial r = −.28,p <

.05) after controlling for T1 stigma resistance. Therefore, those who reported higher levelsof satisfaction with social relationships at baseline demonstrated greater ability to resiststigma at 1-year follow-up. Baseline psychiatric symptoms was significantly correlated withseveral domains of quality of life at 1-year follow-up, including T2 life satisfaction (r =−.32, P < .01), T2 psychological well-being (r = −.32, P < .01), T2 psychiatric symptoms(r = −.66, P < .001), T2 social relationships (r = −.26, P < .05), T2 activities of dailyliving (r = −.35, P < .01), and T2 overall quality of life (r = .49, P < .001). Change inquality of life from T1 to T2 was significantly and negatively correlated with both change

Table 2. Comparison of Self-Stigma (ISMI) and Quality of Life (WQL) Total and Subscales at Baseline (T1)and 12-Month Follow-Up (T2) (n = 71)

T1 T2 Paired t tests

Variables M SD M SD t df P

Self-stigma (ISMI)Alienation 2.16 0.55 2.09 0.55 1.05 70 .30Stereotype endorsement 1.92 0.37 1.87 0.45 1.14 70 .26Discrimination experience 2.28 0.51 2.25 0.45 0.52 70 .61Social withdrawal 2.12 0.48 2.08 0.49 0.68 70 .50Stigma resistance 2.07 0.38 2.06 0.32 0.14 70 .89Total average 2.10 0.35 2.06 0.35 1.11 70 .27

Quality of life (WQL)Life satisfaction 1.36 1.07 1.31 1.09 0.43 70 .67Occupational activities 1.21 1.38 1.00 1.34 1.09 70 .28Psychological well-being 1.47 1.61 1.68 1.76 − 0.93 70 .36Physical health 0.40 1.46 0.17 1.76 1.26 70 .21Social relationships 1.47 1.05 1.56 1.12 − 0.98 70 .33Finances 0.48 1.28 0.53 1.38 − 0.28 70 .78Activities of daily living 2.43 0.71 2.22 0.83 2.06 70 < .05Psychiatric symptoms 2.38 0.66 2.29 0.78 0.97 70 .34Total average (unweighted) 1.39 0.70 1.34 0.71 0.74 70 .46

Note. ISMI = Internalized Stigma of Mental Illness scale; WQL = Wisconsin Quality of Life Index; m = mean; SD =standard deviation; df = degree of freedom.



in self-stigma (r = −.25, P < .05) and change in psychiatric symptoms (r = −.44, P <

.001) during the study period.To confirm these findings, a hierarchical linear regression analysis was performed

to examine the extent to which T1 self-stigma predicted T2 quality of life. Bivariatecorrelation analyses indicated that T1 self-stigma was not significantly related (P > .05)to the following baseline variables: client type (r = .14), age (r = −.01), gender (r =−.04), ethnicity (r = .001), relationship status (r = .14), employment status (r = −.02),income assistance status (r = .15), education level (r = .02), years with mental illness (r =.07), primary psychiatric diagnosis (r = −.07), or presence of substance use diagnosis(r = .04). These variables were, therefore, not included in the regression model. Fourvariables were statistically associated with T1 self-stigma (P < .05), including T1 historyof homelessness (r = .25), T1 psychiatric symptoms (r = .26), T1 service satisfaction (r =−.31), and change in self-stigma (r = −.43). Of these, only T1 psychiatric symptoms wasalso significantly associated with T2 quality of life (r = −.49,p < .001) and was thereforeforced into the model as a control variable. As is presented in Table 4, the baseline modelindicates that T1 quality of life and T1 psychiatric symptoms accounted for 44% of thevariance in T2 quality of life.

After controlling for the effects of these two variables, the analysis revealed that T1self-stigma was not a significant predictor of T2 quality of life (β = .17, standard error[SE] = .20, P > .05) for participants in the current study.

Table 3. Bivariate Correlations of Baseline Self-Stigma (ISMI Total) and Symptoms (BASIS24 Total) WithQuality of Life (WQL Total and Subscales) at Baseline (T1) and 12-Month Follow-Up (T2)

T1 T1Self-stigma Symptoms

(ISMI) (BASIS24)

T1 Quality of LifeLife satisfaction − 0.35** − 0.31**

Psychological well-being − 0.37** − 0.33**

Occupational activities − 0.06 − 0.04Physical health − 0.17 − 0.07Symptoms − 0.23 − 0.47***

Social relationships − 0.26* − 0.41***

Activities of daily living − 0.12 − 0.36**

Finances − 0.12 − 0.20Total − 0.35** − 0.41***

Adjusted total (w/o symptoms) − 0.34** − 0.37**

T2 Quality of LifeLife satisfaction − 0.20 − 0.32**

Psychological well-being − 0.11 − 0.32**

Occupational activities 0.13 − 0.16Physical health − 0.18 − 0.19Symptoms − 0.23 − 0.66***

Social relationships − 0.24* − 0.26*

Activities of daily living − 0.02 − 0.35**

Finances 0.03 − 0.17Total − 0.17 − 0.49***

Adjusted total (w/o symptoms) − 0.15 − 0.43***

Note. ISMI = Internalized Stigma of Mental Illness scale; BASIS24= Behavior and Symptom Identification Scale-24.*P < .05, two tailed. **P < .01, two tailed. ***P < .001, two tailed.



Table 4. Multivariate Hierarchical Regression Analysis Predicting Quality of Life (WQL Total) at 12-MonthFollow-Up (T2)

Unstandardized Standardized Collinearitycoefficients coefficients statistics

B SE Beta t Sig. Tolerance VIF

Model 1 (N = 71)T1 Quality of life .49 .10 .49 4.91 .000 .84 1.20T1 Psychiatric symptom severity − .48 .16 − .30 − 2.99 .004 .84 1.20R .66R2 .44Significance level .000

Model 2T1 Quality of life .52 .11 .51 4.95 .000 .77 1.30T1 Psychiatric symptom severity − .50 .16 − .31 − 3.07 .003 .82 1.22T1 Self-stigma .17 .20 .09 .88 .383 .86 1.16R .67R2 .45R2 change .01Sig. .000

Note. SE = standard error; Sig. = ; VIF =Model 1 contains control variables. Model 2 Contains control variables in addition to baseline (T1) self-stigma (ISMI)as the predictor variable.

Following a similar procedure, a second hierarchical linear regression analysis wasperformed with change in quality of life as the outcome variable and change in self-stigmaas the predictor variable. As summarized in Table 5, the three control variables (T1 qualityof life, T1 self-stigma, and T1 psychiatric symptoms) accounted for 29% of the variancein the change in quality of life.

After controlling for the effects of these three variables, the analysis revealed thatchange in self-stigma was not a significant predictor of change in quality of life (β = −.41,SE = .24, P > .05). T1 psychiatric symptoms remained a significant predictor of changein quality of life (β = −.45, SE = .16, P < .01).

The final analysis examined the moderator effect of T1 self-stigma on the relationshipbetween T1 psychiatric symptoms and T2 quality of life. The regression analysis revealedthat T1 quality of life (β = .53, SE = .11, P < .001) and T1 psychiatric symptoms (β = −.49,SE = .16, P < .01) were significant predictors of T2 quality of life. However, T1 self-stigma(β = .14, SE = .20, P > .05) and the interaction variable (β = −.54, SE = .59, P > .05)were not significant. As well, the addition of the interaction variable did not result in asignificant change or improvement in r2, F(1,66) = .85, P > .05. The analysis was repeatedwith T1 depressive symptoms (a domain of the BASIS24) as the predictor variable, ratherthan T1 psychiatric symptoms, which produced similar non-significant results with respectto change in r2, F(1,66) = .01, P > .05.

DISCUSSION

It was hypothesized that, over time, self-stigma would have the direct effect of erodingquality of life among people with mental illness who were receiving compulsory commu-nity treatment; however, this relationship was not confirmed by the data. Although the



Table 5. Multivariate Hierarchical Regression Analysis With Predicting Change in Quality of Life (WQL)From Baseline to 12-Month Follow-Up

Unstandardized Standardized Collinearitycoefficients coefficients statistics

B SE Beta t Sig. Tolerance VIF

Model 1 (N = 71)T1 Quality of life − .48 .11 − .54 − 4.59 .000 .77 1.30T1 Self-stigma .17 .20 .10 .88 .383 .86 1.16T1 Psychiatric symptom severity − .50 .16 − .35 − 3.07 .003 .82 1.22R .54R2 .29Sig. .000

Model 2T1 Quality of life − .49 .10 − .55 − 4.73 .000 .77 1.30T1 Self-stigma − .001 .22 .00 − .003 .998 .68 1.46T1 Psychiatric symptom severity − .45 .16 − .32 − 2.80 .007 .80 1.25Change in self-stigma − .41 .24 − .20 − 1.75 .085 .78 1.28R .57R2 .32R2 change .03Sig. .000

Note. SE = standard error; Sig. = ; VIF =Model 1 contains the control variables. Model 2 contains the control variables in addition to change in self-stigma(ISMI) from baseline to 12 month follow-up as the predictor variable.

cross-sectional analyses revealed a moderate, negative relationship between self-stigmaand quality of life, the longitudinal analyses indicated that self-stigma did not predictquality of life among the current study participants. In fact, after controlling for the ef-fects of potential confounding variables, baseline self-stigma accounted for less than onepercent of the variance in quality of life 1 year later.

This finding is consistent with other studies that have, using different methods, foundsignificant cross-sectional correlations between self-stigma and quality of life, but smallor nonsignificant associations over time (Lysaker et al., 2007; Marcussen et al., 2010).To date, only the Markowitz studies (1998, 2001) have, with a larger sample and ex-tended follow-up period, detected a significant negative association between self-stigmaand quality of life over time. The current study does not suggest that self-stigma hasno deleterious effects for people with mental illness. Rather, the findings indicated thatself-stigma was not an important predictor of subjective quality of life 1 year later. Thestudy did detect a significant, negative relationship between self-stigma at baseline andsubsequent social relationships (a domain of quality of life; r = −.24), but the rela-tionship was no longer significant once baseline social relationships were taken intoaccount.

This finding is in line with some studies, but not others. For instance, Perlick andcolleagues (2001) found that among a sample of people with bipolar disorder (n = 264),baseline stigma was negatively associated with social and leisure functioning 7 monthslater. In contrast, Mueller and colleagues (2006) found that among people with mentalillness (n = 165), perceived stigma did not predict social network size or social support 1year later. Their findings, however, did indicate that social support was a strong predictorof perceived stigma among people with recent onset of mental illness. In another study,



Sibitz and colleagues (2011) used structural equation modeling with cross-sectional dataand found that social network and stigma indirectly contributed to depression, which,in turn, resulted in poorer quality of life among people with schizophrenia. Amongparticipants of the current study, however, baseline levels of self-stigma did not moderatethe relationship between psychiatric (and depressive) symptoms and subsequent qualityof life. With such contradictory results, the nature of the relationships between self-stigma,psychiatric symptoms, social relationships, and quality of life remain unclear, and requirefurther investigation.

The critics of labeling theory have argued that psychiatric symptoms have moretroubling effects for people with mental illness compared with the effects of labelling andstigma (Gove, 1970), which, in relation to quality of life among the study participants,was confirmed by the present study. Among the variables measured in the current study,psychiatric symptom severity was the strongest predictor of quality of life, even uponremoval of the psychiatric symptoms subscale from the WQL. Participants with moresevere psychiatric symptoms at baseline were more likely to report lower levels of qualityof life at 1-year follow-up. Indeed, for the participants who live with severe and persistentmental illness, psychiatric symptoms have the potential to impair all areas of life, includingfinances, employment, relationships, well-being, outlook, and life satisfaction. There hasbeen some suggestion in the literature that for people with mental illness, the effects ofstigma are at least as equally pernicious as the effects of the illness itself; however, thepresent study indicated that for the study participants, the deleterious effects of psychiatricsymptoms on quality of life surpassed the direct effects of self-stigma.

The recovery model offers an alternative way of viewing these findings. Unlike adeterministic, linear pathway between self-stigma and negative outcomes, the recoverymodel emphasizes the role of self-empowerment and self-determination in determiningoutcomes (Andresen, Caputi, & Oades, 2010; Liberman & Kopelowicz, 2005). Recoveryhas been defined as “a way of living a satisfying, hopeful, and contributing life even withthe limitations caused by illness” (Anthony, 1993, para. 10). Accordingly, an individual’smembership within a stigmatized group does not automatically mean they will be self-stigmatized or suffer from a poor quality of life (Rusch, Angermeyer, & Corrigan, 2005).Although stigma is often identified as a barrier to recovery and wellness (Ho, Chiu, Lo, &Yiu, 2010; Link, Struening, Neese-Todd, Asmussen, & Phelan, 2001), people with mentalillness are not passive recipients of its negative effects (Link & Phelan, 2001). Stigmais something many people with mental illness manage or resist (Corrigan et al., 2010;Michalak et al., 2011; Sibitz, Unger, Woppmann, Zidek, & Amering, 2009), and it mayeven lead to positive outcomes (e.g., empowerment; Rusch et al., 2005).

Consistent with the recovery model, a sense of hope emerges from the findingsof the present study. Despite participants’ routine experiences with objective indicatorsof social oppression (e.g., involuntary treatment) and disadvantage (e.g., homelessness,unemployment), relatively few (9%) reported severe levels of self-stigma. As has beenreported elsewhere, the present sample did not have substantially higher levels of self-stigma at baseline compared with other samples of individuals with severe mental illnesswho are not receiving compulsory treatment (Livingston et al., 2011). Although T1 self-stigma was significantly correlated with T1 quality of life, it did not predict quality oflife at 1-year follow-up. Together, these results may paint a more hopeful and optimisticpicture for individuals who are subjected to official labelling processes (e.g., criminaljustice processing, compulsory treatment). During the 1-year study period, quality of lifeand self-stigma remained stable.



These findings align with those of other published studies that measured similaroutcomes. For instance, one study found that compulsory community treatment was notassociated with decreased quality of life or elevated levels of self-stigma (Link et al., 2008;Phelan et al., 2010). A potential area of opportunity is assisting individuals with mentalillness to acquire the ability to overtly resist stigma (Thoits, 2011), which, according to theISMI stigma resistance subscale, fewer than 10% of participants in the current study werehighly equipped to do. Several promising interventions, based on cognitive behaviourtherapy and psycho-educational principles, have been developed to help individuals withmental illness to develop the necessary skills needed to manage and overcome self-stigma(Knight, Wykes, & Hayward, 2006; MacInnes & Lewis, 2008).

The present study’s results should be considered within the context of several method-ological limitations. First, participants were recruited using a non-probabilistic samplingtechnique, with approximately two-thirds of potential participants who met the inclusioncriteria not recruited. Consequently, self-selection bias may undermine the validity ofthe findings. Systematic error cannot be ruled out since the decision to participate, ornot to participate, in the research may have been associated with factors (e.g., level ofstigma, severity of symptoms) relevant to the study. The possibility that individuals whoare highly self-stigmatized may have been unwilling to participate in a research inter-view presents a threat to this study’s internal validity. Second, the results are based onthe subjective, self-reported experiences of people who received compulsory communitytreatment services in the forensic and civil mental health systems of BC, Canada. In lightof this, generalizations based on these findings to mental health populations within otherjurisdictions should be made with caution. Similarly, the sample was comprised mostly ofpeople diagnosed with schizophrenia or schizoaffective disorder. Therefore, the resultsmay not be generalizable to all people who receive compulsory community treatment.Third, the sample size was modest in relation to the number of comparisons made, whichcould have increased the risk of spurious findings. While the sample size was adequatefor detecting medium-sized effects using multiple hierarchical regression analysis, it wasinsufficient for detecting small effects. The sensitivity of the longitudinal analysis wouldhave been improved by a larger sample size and increased statistical power. Lastly, al-though the two-wave design of the present study is an improvement over a cross-sectionaldesign, it is inadequate for providing details about the shape or structure of change overtime (Willett, Singer, & Martin, 1998). The 1-year study period may also have been toobrief to observe significant naturalistic changes in self-stigma and quality of life amongthe study participants. It is recommended that future studies collect multiple waves ofdata over longer periods of time to reveal additional information about the relationshipbetween self-stigma and quality of life.

Despite these limitations, this study offers insight that might inspire pause and re-flection among researchers and clinicians regarding the presumed relationship betweenself-stigma and quality of life. These findings, in conjunction with those of other studies,may have implications for the manner in which mental health interventions are designedand evaluated. Interventions seeking to reduce self-stigma should not necessarily ex-pect to find significant improvements in quality of life, even for compulsory communitytreatment populations. Additional longitudinal research with other populations of indi-viduals with mental illness and with extended follow-up periods is needed before firmconclusions can be reached regarding the relationship between self-stigma and quality oflife.



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