PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Issues Ment Health Nurs. Author manuscript; available in PMC May 23, 2012.
Published in final edited form as:
PMCID: PMC3359372
NIHMSID: NIHMS365261
Correlates of Depressive Symptoms among Homeless Men on Parole
Adeline Nyamathi, ANP, Ph.D., FAAN, Barbara Leake, PhD, Cynthia R. Albarrán, RN, MS, CNS, Sheldon Zhang, PhD, Elizabeth Hall, PhD, David Farabee, PhD, Elizabeth Marlow, FNP, PhD., Mary Marfisee, MD, MPH, Farinaz Khalilifard, MFA, and Mark Faucette, RAS, CSAC
Adeline Nyamathi, University of California, Los Angeles, School of Nursing;
Correspondence should be addressed to: Adeline Nyamathi, ANP, Ph.D., FAAN, UCLA, School of Nursing, Room 2-250, Factor Building, Box 951720, Los Angeles, CA 90095-1702, (310) 825-8405, phone, anyamath/at/sonnet.ucla.edu
This study describes correlates of high levels of depressive symptoms among recently paroled men in Los Angeles who reside in a community substance abuse treatment program and report homelessness. Cross-sectional data were obtained from male residents who were released on parole within the last 30 days (N=157) to assess parental relationship, self-esteem, social support, coping behaviors, drug and alcohol use behaviors, depressive symptoms, and sociodemographic information. Results indicated that 40% of participants were classified as experiencing high levels of depressive symptoms (CES-D ≥ 10). Results of a logistic regression analysis showed that the following were predictors of depressive symptoms (p < .05): physical abuse in childhood, non-residential alcohol treatment, violent behaviors, low self-esteem, and disengagement coping. Being Mexican-American, Mexican, American Indian, or Asian) and not displaying cognitive problems was inversely related to depressive symptoms in the final model (B = −2.39, p < .05). Findings support proper use of both prison and community assessment services to at-risk individuals eligible for parole to increase self-esteem and coping.
Keywords: Depressive symptoms, parolees, self-esteem, coping behaviors
In the United States (US), there are over 2.3 million people incarcerated in jails and prisons combined (Bureau of Justice Statistics, 2010). In addition, more than 5 million individuals are under community supervision for either probation (84%) or parole (16%; Bureau of Justice Statistics, 2010). California hosts nearly 15% of the entire paroled population in the country; the rate of individuals on parole to California’s total state population is 323.2 per 100,000 (aCalifornia Department of Corrections and Rehabilitation [CDCR], 2009a; Bureau of Justice Statistics, 2010). Offenders who are granted parole face distinct reentry challenges as they may be unprepared to make independent decisions that will positively affect their well-being outside of an institutionalized setting (Taxman, 2004). Particularly for drug abusers who start the addiction recovery process in prison, re-entering society can be an experience akin to that of “immigrants [arriving] in a foreign land” (Gideon, 2009, p. 44), and is complicated by numerous contextual and psychological stressors (Sung & Richter, 2006).
There is a link between mental illness and parolee recidivism (Hiscoke, Langstrom, Ottosson, & Grann, 2003; Skeem & Louden, 2006). Among parolees with mental illness, recidivism rates are significantly higher during the first year of parole than for those without psychiatric disorder (Messina, Burdon, Hagopian, & Prendergast, 2004), and were as high as 34% in a sample of parolees attending outpatient psychiatric clinics (Solomon, Draine, & Marcus, 2002). In a large retrospective cohort study (N=79,211), inmates with bipolar disorder were more than 3 times as likely as those without psychiatric comorbidities to be reincarcerated on multiple occasions (>4 times) within a 6-year period (Baillargeon, Binswanger, Penn, Williams, & Murray, 2009). This is particularly important in light of the fact that more than half of all individuals paroled in California are returning to prison within two years after release (CDCR, 2009b). In addition, two-thirds of individuals in the general population with depressive symptoms remain undiagnosed (Ani et al., 2008), suggesting that an even greater burden of depressive symptomatology exists among parolees. Therefore, understanding the correlates of depressive symptoms in this population will assist mental health providers, professionals within the criminal justice system, and policymakers to encourage screening and provide needed care to assist parolees with psychiatric comorbidities to successfully reintegrate into society.
Depression is the leading cause of disability for individuals ages 15–44 in the U.S. (World Health Organization [WHO], 2008). In those over age 18, a total of 6.7% of the total U.S population have a major depressive disorder in a given year, translating into just over 14 million adults who are living with major depression in the U.S. (Kessler, Chiu, Demler, & Walters, 2005; US Census Bureau, 2002). As of 2001, no studies had directly measured the numbers of persons with serious mental illness on parole (Lurigio, 2001). In 2004, one of the first studies examining depression in parolees found a 25% prevalence rate among Maryland parolees (Visher, La Vigne, & Travis, 2004). Thus, there remains a paucity of research on mental illness, and on depression in particular, in individuals on parole supervision.
In contrast to the limited findings on parolees, there is a growing body of literature surrounding mental illness in inmates. A nationwide survey of healthcare in prisons revealed that 14.8% of federal inmates, 25.5% of state inmates, and 25% of county jail inmates had at least 1 mental health diagnosis; among those who remain undiagnosed, numbers may be even higher (Wilper et al., 2009). Other estimates place the prevalence of mental illness among inmates to be between 20.6% and 53.7% (Zlotnick, Clarke, Friedmann, Roberts, & Melnick, 2008). A meta-analysis of 62 prison surveys concluded that about 1 in 7 prisoners in Western countries have psychotic illness or major depression, showing a burden of disease that is between 2 – 4 times that of the general population of the US or Britain (Fazel & Danesh, 2002). This is especially significant considering that those who have been incarcerated appear to have different psychosocial functioning, and different psychopathological and service use profiles than those with mental illness who are not incarcerated (Dumais, Cote, & Lesage, 2010). This indicates that psychiatric treatment for those who are mentally ill and have a history of incarceration must be tailored to address their unique needs.
Parolees who are homeless have even greater problems with incarceration. In a national survey of inmates (N=6,953), 15.3% reported at least one episode of homelessness in the year prior to incarceration—a number that is 7–11 times that of the general US population reporting homelessness (Greenberg & Rosenheck, 2008). These authors further contend that inmates reporting homelessness were more likely to have past criminal justice involvement, report mental illness and substance abuse, and report less education and previous unemployment. In those who have been incarcerated and have a history of mental illness, substance abuse is extremely common (Cuomo, Sarchiapone, Di Giannantonio, Mancini, & Roy, 2008; Kerridge, 2009; Pelissier & O’Neil, 2000).
Inmates with a history of substance abuse constitute a unique subgroup within the prison population, burdened by increased judiciary and psychiatric issues when compared with those who do not have a history of substance abuse (Cuomo et al., 2008). Specifically, those with history of substance abuse had multiple incarcerations (78.8%), more juvenile convictions (60.2%), more violent behaviors during detention (28.8%), a history of one or more suicide attempts (20.8%), and higher scores for childhood trauma, psychoticism, neuroticism, impulsivity, hostility, and suicidal ideation (Cuomo et al., 2008). Depressive symptoms are correlated with a co-occurring substance abuse disorder among inmates (Kerridge, 2009). In regard to parolees, those with a dual diagnosis of a major psychiatric disorder (major depressive disorder, bipolar disorder, schizophrenia, or other psychotic disorder) and a substance use disorder have a much higher risk of parole revocation (Baillargeon et al., 2009).
Low levels of social support predict escalated depressive symptoms in patients with baseline depressive or anxiety disorders (van Beljouw, Verhaak, Cuijpers, van Marwijk, & Penninx, 2010) and also among injection drug users (IDUs; Risser, Cates, Rehman, & Risser, 2010). Little research has addressed the impact of social support and coping mechanisms for parolees with psychiatric comorbidities—and even less has focused on social support among parolees experiencing depressive symptoms. Recent research demonstrates that among male parolees, lack of social support has been associated with increased drug use, high-risk sexual practices and reincarceration (Seal, Eldridge, Kacanek, Binson, & MacGowan, 2007). In contrast, stable social support has been associated with increased health care access in HIV-positive formerly incarcerated men (Harzke, Ross, & Scott, 2006), and appears to buffer the relationship between polydrug use and depressive symptoms among HIV-positive drug users (Mizuno, Purcell, Dawson-Rose, & Parsons, 2003).
Lack of positive coping skills often leads to resumption of high-risk behaviors, including, IDU, and reincarceration (Haney, 2003; Marlow, 2007; Travis, Solomon, & Waul, 2001). Religious participation is cited in the literature as a positive way of coping for incarcerated individuals. Levitt and Loper (2009) revealed that 70.3% of inmates reported some participation in religious activities, and those who perceived high levels of support from religious participation reported lower levels of depression. Other measures of religiosity/spirituality showed significant improvements in depression (Boelens, Reeves, Replogle, & Koenig, 2009), better emotional health (Allen, Phillips, Roff, Cavanaugh, & Day, 2008), and improved psychological adjustment to prison (Clear & Sumter, 2002) among samples of inmates who reported prayer or other religious participation.
An individual’s well-being and psychosocial outcomes may be related to peer attachments, although few studies have examined mental health in relation with gang membership in formerly incarcerated individuals. Gang membership is an important factor of adolescent peer relationships among those who have increased deviant behavior and substance use (Gatti, Tremblay, Vitaro, & McDuff 2005; Swahn, Bossarte, West, & Topalli, 2010). Gang membership is also correlated with higher levels of depression, anxiety, and violent behavior (Harper, Davidson, & Hosek, 2008).
Adolescent self-concept is correlated to depressive symptoms in early adulthood (Park, 2003). Self-esteem is directly affected by parental attachment in children (Liable, Carlo, & Roesch, 2004), and adolescent self-esteem appears to play a limited role in the development of violent behavior (Boden, Fergusson, & Horwood, 2007). However, the relationship between self-esteem in adolescence and later mental health and substance abuse outcomes in adulthood is limited, demonstrating that that the psychosocial context that fosters self-esteem may more clearly predict adult mental health outcomes (Boden, Fergusson, & Horwood, 2008).
Adverse childhood experiences, including physical, psychological, and sexual abuse, also impact children’s mental health (Matsuura, Hashimoto, & Toichi, 2009). Children who have been maltreated show twice the amount of depressive symptoms than those who have not (Lansford et al., 2002). Parenting strategies and parental psychopathology also impact children’s mental health (Vostanis et al., 2006). A growing body of research indicates that parental factors impact children’s mental health and problem behavior, including parental alcoholism (Christoffersen & Soothill, 2003; Peiponen, Laukkanen, Korhonen, Hintikka, & Lehtonen, 2006; Rangarajan, 2008), parental substance abuse and violence (Hanson et al., 2006), and maternal depression (Peiponen et al., 2006).
Among adolescents entering the criminal justice system, mental illness plays a large role. For male youth, prevalence rates of mental illness in juvenile detention are as high as 60–70% (Golzari, Hunt, & Anoshiravani, 2006). As many as 45% of male youths in the juvenile detention system have experienced some form of abuse (Abrantes, Hoffman, & Anton, 2005). These effects carry through to adulthood. Childhood sexual abuse by a family member is associated with violent behaviors including homicide in adulthood (Brewer-Smyth & Burgess, 2008), poor adult psychological well-being (Roberts, O’Connor, Dunn, Golding, & the ALSPAC Study Team, 2004), and adult alcoholism and depression (Anda et al., 2002). Poor early parent-child relationships are correlated with adults’ increased psychological distress (Mallers, Charles, Neupert, & Almeida, 2010). Adult children of alcoholics also report more depressive symptoms than those whose parents were not alcoholics (Anda et al., 2002; Kelley et al., 2010). The apparent intergenerational cycle of adverse childhood experiences, mental illness, alcoholism, substance use and criminal justice involvement make understanding these issues of primary importance (Barreras, Drucker, & Rosenthal, 2005; Dube, Anda, Felitti, Edwards, & Croft, 2002, Wu, Schairer, Dellor, & Grella, 2010).
Depressed parolees are less likely to make use of effective coping strategies, hampering their re-integration into society. Understanding the correlates of depression among homeless parolees could improve planning for post-release services.
Parolees with depressive symptoms are less likely to make use of effective coping strategies, hampering their re-integration into society. Understanding the correlates of depressive symptoms among homeless parolees could improve planning for post-release services.
As part of a larger investigation, the purpose of this study is to determine the correlates of depressive symptoms for men ages 18–60 who have been released on parole within the last 30 days, who are participating in a residential substance abuse treatment program, and who report homelessness. Research questions include: 1) What is the profile of homeless men on parole at a community treatment center in Los Angeles, in relation to sociodemographics, substance abuse history, and psychological resources? and 2) What are the predictors of depressive symptoms among homeless men on parole in a model including sociodempgrahics, family/childhood history, physical health, lifetime symptoms/problems, serious drug use, substance treatment, and psychosocial measures?
Sample
The convenience sample of 157 recently-released parolees were administered baseline assessments. Participants were recruited from a 187-bed residential drug treatment facility in southern California. They were eligible if they met the following criteria: a) released from prison within the last 30 days; b) had a history of drug use prior to their last entry into the prison system; c) age 18–60; d) entered the participating drug treatment program; e) labeled as homeless on their pre-release prison form; and f) willing to provide informed consent. Almost all (93%) of the men who met study criteria participated in the study and were paid $20 for completion of the baseline assessment. Participants were excluded if they were monolingual speakers of languages other than English or Spanish; and were judged to be cognitively impaired by the research staff. The UCLA Human Subjects Protection Committee approved the study.
Instruments
Sociodemographic information was collected by a structured questionnaire that assessed 15 items relating to age, birthdate, race/ethnicity, education, marital status, number of parents in birth family, family SES, relationship status with parents, childhood abuse, country of birth, physical health, lifetime symptoms and problems not directly caused by alcohol or drug use, history of homelessness.
Parental and Family Relationships were assessed by a series of questions relating to: a) Relationship with Parents (one item measured on a 6-point Likert scale ranging from “Excellent Relationship” to “No Relationship”); b) Closeness of Family (measured on a 6-point Likert scale ranging from “Very Close” to “Don’t Know”); and c) Supportiveness of the Mother and/or the Father (measured on a 5-point Likert scale ranging from “Very Supportive” to “Not Around”).
Self-Esteem was measured using the revised Coopersmith (1967) 23-item Self-Esteem Inventory (SEI). The internal consistency of this scale with homeless males was .83 (Nyamathi et al., 1993; 1997); in the present study, it was .84. Additionally, parolees were asked how they had felt about themselves as teenagers on a 5-point Likert scale ranging from “liked yourself a great deal” to “disliked yourself a great deal.”
Social Support was measured by 18 items from the Medical Outcomes Study (MOS) Social Support Survey (Sherbourne & Stewart, 1991). These items contained 4 subscales: emotional support (8 items), tangible support (3 items), positive support (4 items) and affective support (3 items). Reliabilities for these subscales in this sample were .95. 86 .91 and .88, respectively.
Coping behaviors were measured by 12 items from Carver’s (1997) Brief Cope and represent six separate subscales, with two items for each subscale. The items are rated on a 4-point Likert scale from “not at all” to “a lot.” Internal consistencies for these subscales in this study were .61 for self-blame coping, .66 for denial coping, .74 for disengagement coping, .76 for instrumental support coping, .80 for planning coping and .84 for religious coping.
Perceived health status was measured on a 5-point scale from “excellent” to “poor”, and a dichotomous item (any vs none) inquired about past six-month hospitalization. Health status was dichotomized at fair or poor versus better health.
Drug and alcohol use behaviors six months prior to the recent incarceration were measured by a modified Texas Christian Univerisity (TCU) Drug History form (Simpson & Chatham, 1995). This questionnaire has been tested with men and women with a history of drug addiction and homelessness. The modified form recorded the frequency of use of alcohol, tobacco and 7 drugs and selected combinations of drugs used by injection and orally during a six-month period before the last incarceration and also elicited information about lifetime use. Favorable results regarding the reliability and validity of data collected in this format have been reported by Anglin et al. (1996).
Depressive Symptoms were assessed with the 10-item short form of the Center for Epidemiological Studies Depression (CES-D) scale (Radloff, 1977), which has been validated for use in homeless populations (Nyamathi et al., 2006; 2008). The 10-item self-report instrument is designed to measure depressive symptoms in the general population (Andresen, Malmgren, Carter, & Patrick, 1994) and measures the frequency of a symptom in the past week on a 4-point response scale from 0 Rarely or none of the time (Less than 1 day) to 3 All of the time (5–7 days). Scale scores range from 0 to 30, with higher scores indicating greater symptom severity. Scale scores were dichotomized at a cutoff value of 10 (8 and 10 are frequently-used figures to suggest depressive symptoms). The internal reliability of the scale in this sample was .80. As the CES-D scale is not a diagnostic screener for depression, we refer to participants experiencing high level of depressive symptomotology if they reported a score of 10 or higher on the CES-D.
Procedure
A collaborative relationship was established with the director of the drug treatment program, which led to the submission and subsequent funding of the study. Data were collected between February to September, 2010. Trained research staff screened potential study participants who resided at the drug treatment site for eligibility criteria in a private area of the facility. Human Subject approved flyers were posted at the site and presentations were made at the treatment facility by trained staff.
After informed consent for the study had been discussed, read and signed for parolees who met the eligibility criteria, staff administered a brief two-minute structured questionnaire asking about socio-demographic characteristics and hepatitis-related information, and a detailed locator guide that elicited information about hangout places, family/friends addresses, etc. If parolees were eligible and interested in participating in the study continued, the research staff read and discussed the final informed consent. Subsequent to this, the baseline questionnaire was administered by a tablet PC, which allowed parolees to respond to questions in privacy.
Statistical Analysis
Frequencies and percents or means and standard deviations described the study variables. Unadjusted relationships between depression and sociodemographic characteristics, family/childhood measures, lifetime symptoms and problems, substance use and treatment characteristics and psycho-social measures were assessed with chi-square and two-sample t tests, depending on the underlying distributions of the potential correlates. Variables that were associated with depression at the .15 level in these analyses were then used as predictors of depression in a stepwise backward logistic regression analysis; the retention level was .10. To determine whether effects were consistent across race/ethnicity, potential interactions between race/ethnicity and variables in the final set of predictors were examined; an interaction between ethnicity, specifically Whites, African-Americans and non-Mexican or Mexican-American Latinos, and cognitive problems was observed. Four design variables were constructed to represent their interaction and the regression model was rerun with the inclusion of three of these variables. The reference group was Whites, African-Americans and Latinos of non-Mexican heritage who did not report cognitive difficulties. Predictors in the final model were checked for multicollinearity and the Hosmer-Lemeshow test was used to assess goodness of fit. The p value for the Hosmer-Lemeshow test was .538.
Sociodemographic Characteristics
To assess the profile of homeless men on parole at a community treatment center, we determined the sociodemographic, characteristics, substance abuse history, and psychological resources of our sample. The all male sample reported a mean age of 41.9 years (SD: 10.1; range of 22–60; Table 1). Nearly half (47%) were African-American, just over one-quarter (26%) were Mexican American, and 15% were Caucasian. Slightly over one-third of the sample reported committing a serious violent crime in the past. A history of childhood sexual abuse was reported by 16% of the participants, while childhood physical abuse and verbal abuse was reported by 31% and 47%, respectively. Over 40% were in prison before the age of 21 and almost half reported belonging to a gang. Health status was very good or excellent for 44% of the sample; just over half (51%) reported a previous hospitalization for physical health. About 40% of the sample reported experiencing high level of depressive symptoms (CES-D ≥ 10).
Table 1
Table 1
Sample Characteristics
While data was not shown, the family SES ranged from middle class to poor for the overwhelming majority of parolees (93%); furthermore, the relationship with parents ranged from fair/average to no relationship for over half. Closeness of the family appeared better, with a range of “very close” to “at times very close” for about two-thirds of the sample. Feelings about self as a teenager ranged from “liked self a great deal” to “liked self moderately” for more than two-thirds of the sample (69%).
Substance Use
One of the eligibility criteria was that parolees had a history of substance use prior to their recent incarceration documented in their record. Among serious drugs ever used, the most prevalent were crack (91%), cocaine (65%), methamphetamine (49%) and hallucinogens (48%) (See Table 2). Approximately one-third reported prior residential treatment for alcohol use, and an additional 12% had participated in non-residential treatment for their alcohol use. Nearly one-quarter had also attended a non-residential program for drug use.
Table 2
Table 2
Substance Use, Substance Treatment and Psychosocial Resources
Psychological Resources
Self- esteem was rated slightly above the midpoint by the participants (X = 14.1; SD 4.9), while coping varied depending on the style of coping. More specifically, denial coping and disengagement coping were utilized less, while self-blame coping, planning, religious and instrumental support coping were utilized more frequently. In terms of support, participants reported moderate amounts of the four types of support examined.
Associations with Depressive Symptoms
In relation to assessing the predictors of depressive symptoms among our sample, we discovered that a number of sociodemographic variables were not associated with depression in this sample of men. These included age, education and having one or more children (Table 3). Race/ethnicity was significantly related to depression. In particular, Whites, African-Americans and Latinos with ethnic roots outside of Mexico were over-represented in the depressed group. A number of family/childhood variables were also associated with depression. These variables included low family SES, lack of family cohesion, poor relationship with parent(s) and abuse. Childhood abuse encompassed sexual, physical and verbal abuse. Moreover, poor self-esteem as a teenager was also related to current depression.
Table 3
Table 3
Associations of Selected Variables with Depression
Physical health, as measured by general self-assessment and history of hospitalization, was also related to depression. As shown in Table 3, violent behaviors, hallucinations, binge drinking, and serious learning problems and cognitive difficulties were all strongly associated with depression in the sample.
In terms of psychosocial measures and resources, high level of depressive symptoms was related to self-esteem, as well as to emotion social support (p = .007) and positive interaction (p = .03). All of the coping variables except religious coping were also related to depressive symptoms; these included active, denial, blame, disengagement and instrumental coping. No associations with depressive symptoms were discovered for affection or tangible social support.
Multivariate Results
Two lifetime problems were important in logistic regression analysis for depression (Table 4). The first was violent behavior that the men reported as difficult to control; this measure had an overall positive association with depression. The second was cognitive difficulty, which interacted with race/ethnicity. Compared to African-Americans, Whites and Latinos of non-Mexican heritage without cognitive problems, men of Mexican-American, Mexican, Asian and other ethnicities who also reported no cognitive difficulties were less likely to be depressed. There was also a trend for African-Americans, Whites, and Latinos of non-Mexican heritage who reported cognitive problems to be more likely to have experienced high depressive symptoms than those of the same ethnicities without these problems. Physical abuse was the only family/childhood measure that remained significant when other correlates of depression were controlled. While substance use variables were not important themselves in the regression model, having participated in a non-residential alcohol treatment program was a positive predictor of current depression. Two psycho-social variables were also in the model. Self-esteem was inversely related to depression, while disengagement coping had a direct relationship with depression.
Table 4
Table 4
Logistic Regression Results for Depression (N=157)
In 2002, Anda et al. described the childhood antecedents of depression and alcoholism in a large adult sample. They discovered an independent, graded association between the number of adverse childhood experiences (such as physical, sexual, or psychological abuse) reported and the risk of alcoholism and depression. In this study, we examined both childhood factors and current factors to provide a broader picture of the correlates of depression in homeless parolees.
Consistent with the literature, we revealed high level of depressive symptoms to be prevalent among homeless parolees. These participants suffered from depressive symptoms at a rate of 40%, roughly six times that of the general U.S. population (Kessler, Chiu, Demler, & Walters, 2005; US Census Bureau, 2002). Moreover, these parolees were also confronted by a host of socio-economic as well as physical adversities, such as poverty, serious illness (requiring hospitalization), fractured family relations, and abusive childhoods. As expected, substance abuse went hand in hand with depressive symptoms in this population. Serious drug use was pervasive and over half reported binge drinking.
Other factors strongly associated with depressive symptoms included violent behaviors, hallucinations, serious learning problems and cognitive difficulties. Many psychosocial factors measured in this group of homeless parolees were significantly related to their depressive symptoms - self-esteem, emotional support, positive interaction, and ineffective coping skills such as denial, blame, and disengagement. In this study, a lack of social support, along with a disengaged coping style, are associated with depressive symptoms in this study. Logistic regression analyses revealed predictors of depressive symptoms including childhood physical abuse, non-residential alcohol treatment, violent behaviors, low self-esteem and disengagement coping. However, being Mexican-American, Mexican, American, Indian, Asian and of another race ethnicity without cognitive problems was inversely related to depressive symptoms.
The high level of depressive symptoms among substance-abusing parolees is perhaps not surprising. Since the late 1950s, the deinstitutionalization movement in mental health services has shifted emphasis from state-funded mental institutions to community-based programs (Petersilia, 2003). However, the movement, while more humane in some aspects than institutionalization, has also left many people with mental illnesses, without adequate treatment or proper supervision for medications and other services. As a result, prisons are now increasingly used as the default venue to warehouse persons with mental illnesses as many state-funded mental institutions were closed (Petersilia, 2003).
All prison inmates, except for the few on death row and with life sentences, will eventually be paroled back into the community. The implications for correctional agencies are serious, as people with mental disorders are released into the community from a highly structured environment but expected to make independent decisions and adjust to a different life (Taxman, 2004). According to Petersilia (2003), the majority of parole agencies in the country are not prepared to deal with large number of clients with mental disorders. Unless parolees exhibit explicit psychiatric symptoms or their offenses were determined to have been caused by mental illness, mental health problems among parolees are either ignored or underserved (Lurigio, 2001).
Many parolees quickly revert back to old behaviors that lead to re-arrest, as their reentry process is complicated by numerous contextual and psychological stressors (Sung & Richter, 2006). This is particularly notable in California. With a prison population of 164,000 and another 108,000 parolees in the community, the state of California spends more on its correctional system than any other state in the nation (CDCR, 2009a). However, community reentry efforts in California have for decades seen little success. Roughly 40% of parolees are returned to prison within 12 months of release, and the rate of reincarceration increases to 70% within three years after release (Zhang, Roberts, & McCollister, 2009; Zhang, Roberts, & Callanan, 2006).
Unfortunately, as discussed earlier, little research has been done regarding mental illness on parole populations (Skeem & Louden, 2006) or the prison population in general (Petersilia, 2003: 37). Such lack of basic knowledge hinders clinical intervention in community corrections and other reentry efforts, because mental health problems, substance abuse, and criminal activities are well known to correlate strongly with one another (Forrester, Chiu, Dove, & Parrott, 2010; Sacks et al., 2009; Shinkfield, Graffam, & Meneilly, 2009).
To make matter worse, the use of illicit drugs, such as those identified in this study, is also known to correlate significantly with violent behaviors and homelessness (Cartier, Farabee, & Prendergast, 2006; Darke, Torok, Kaye, Ross, & McKetin, 2010; Felson & Staff, 2010). It is therefore important, from a policy-making perspective, to recognize the complexity and challenges confronting community reentry programs as parolees face multiple obstacles to recovery and reintegration. Proper assessment and identification of these clinical and social obstacles will enable health care and social service providers to explore and deploy effective interventions.
Limitations
There are several limitations in this study that warrant cautions when interpreting the findings. First, the study sample is relatively small and based on convenience sampling, which limits the generalizability of the findings. Second, participants were recruited from a residential drug treatment facility, which may have magnified the prevalence and severity of depression and other psychosocial adversities. Although in concordance with existing literature, the findings of the high rates of depressive symptoms and other comorbidities perhaps were unique to this population and may reflect at best an exaggeration of the challenges facing certain segments of the correctional population in California. In other words, one would expect to find high rates of depressive symptoms and other mental health problems among homeless and substance abusing parolees.
In addition, the findings are based upon self-report data and two of the subscales of coping had relatively low reliability (Cronbach’s alpha = .61 for self-blame coping and .66 for denial coping). However, the disengagement coping style, which was in the final model for depression, was more reliable at .74 and therefore can be interpreted with greater confidence. Although these results demonstrate the correlates of depressive symptoms among men on parole, cross-sectional data cannot determine the causes of depression in this sample. Finally, we do not claim that all of those with depressive symptoms might necessarily meet criteria for a DSM-IV diagnosis of depression, although certainly it is known that depression remains under-diagnosed in the general population (Ani et al., 2008).
Conclusion
Despite the limitations, findings in this study provide further evidence on two major challenges confronting correctional agencies across the nation in their reentry efforts: (a) proper assessment of mental health problems among prison inmates to be released into the community; and (b) provision of appropriate services. High level of depressive symptoms, as indicated in this study sample, may be common in the general parolee population. This leads to the question of how these ex-prison inmates, already facing insurmountable psychosocial and economic adversities, may cope with their mental health problems. Illicit drugs and alcohol are likely to become their obvious choice of “self-medication.” Thus, mental health implications are critical. The persistently high rates of recidivism in California suggest that extensive screening and treatment of parolees with mental illnesses should be an integral part of community reentry programs. This will ensure the mobilization of necessary health services to stabilize and treat a sizeable number of released inmates to decrease the risk of recidivism. It is also important for healthcare providers and other correctional service agencies to become aware of the widespread mental health challenges in the correctional population and devise interventions that target the underlying causes.
Understanding that fractured, dysfunctional families are an important component in the etiology of alcoholism, substance abuse, and depression could be critical to the diagnosis and treatment of depression in a homeless, parolee population. In addition, a better understanding of the factors that lead to high level of depressive symptoms can assist in primary prevention efforts. As children, the homeless parolees in this study often grew up in extremely dysfunctional family relationships. That, combined with cognitive problems, social isolation, and poor coping styles is correlated with the high level of depressive symptoms and substance abuse revealed in this sample. Clearly, our study findings support the need for a multifaceted system for primary prevention in childhood and intervention and provision of treatment for homeless parolees with comorbid psychiatric disorders.
Acknowledgments
This study was funded by the National Institute on Drug Abuse 1 R01 DA27213-01
Contributor Information
Adeline Nyamathi, University of California, Los Angeles, School of Nursing.
Barbara Leake, University of California, Los Angeles, School of Nursing.
Cynthia R. Albarrán, University of California, Los Angeles, School of Nursing.
Sheldon Zhang, San Diego State University, Department of Sociology.
Elizabeth Hall, University of California, Los Angeles, Integrated Substance Abuse Programs.
David Farabee, University of California, Los Angeles, Integrated Substance Abuse Programs.
Elizabeth Marlow, University of California, San Francisco, School of Nursing.
Mary Marfisee, University of California, Los Angeles, School of Nursing.
Farinaz Khalilifard, University of California, Los Angeles, School of Nursing.
Mark Faucette, Amity Foundation.
  • Abrantes AM, Hoffman NG, Anton R. Prevalence of co-occurring disorders among juveniles committed to detention centers. International Journal of Offender Therapy & Comparative Criminology. 2005;49(2):179–193. [PubMed]
  • Allen RS, Phillips LL, Roff LL, Cavanaugh R, Day L. Religiousness/spirituality and mental health among older male inmates. The Gerontologist. 2008;48(5):692–697. [PubMed]
  • Anda RF, Whitfield CK, Felitti VJ, Chapman D, Edwards VJ, Williamson DF. Adverse childhood experiences, alcoholic parents, and later risk of alcoholism and depression. Psychiatric Services. 2002;53(8):1001–1009. [PubMed]
  • Andresen EM, Malmgren JA, Carter WB, Patrick DL. Screening for depression in well older adults: Evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale) American Journal of Preventive Medicine. 1994;10:77–84. [PubMed]
  • Anglin MD, Longshore D, Turner S, McBride D, Inciardi J, Prendergast M. Studies of the functioning and effectiveness of treatment alternatives to street crime (TASC) programs. Los Angeles: UCLA Drug Abuse Research Center; 1996.
  • Ani C, Bazargan M, Hindman D, Bell D, Farooq MA, Rodriguez M. Depression symptomatology and diagnosis: Discordance between patients and physicians in primary care settings. BMC Family Practice. 2008;9:1–9. [PMC free article] [PubMed]
  • Baillargeon J, Binswanger IA, Penn JV, Williams BA, Murray OJ. Psychiatric disorders and repeat incarcerations: The revolving prison door. American Journal of Psychiatry. 2009;166:103–109. [PubMed]
  • Barreras RE, Drucker EM, Rosenthal D. The concentration of substance use, criminal justice involvement, and HIV/AIDS in the families of drug offenders. Journal of Urban Health. 2005;82(1):162–170. [PMC free article] [PubMed]
  • Boden JM, Fergusson DM, Horwood LJ. Self-esteem and violence: Testing links between adolescent self-esteem and later hostility and violent behavior. Social Psychiatry & Psychiatric Epidemiology. 2007;42:881–891. [PubMed]
  • Boden JM, Fergusson DM, Horwood LJ. Does adolescent self-esteem predict later life outcomes? A test of the causal role of self-esteem. Development & Psychopathology. 2008;20:319–339. [PubMed]
  • Boelens PA, Reeves RR, Replogle WH, Koenig HG. A randomized trial of the effect of prayer on depression and anxiety. International Journal of Psychiatry in Medicine. 2009;39(4):377–392. [PubMed]
  • Brewer-Smyth K, Burgess AW. Childhood sexual abuse by a family member, salivary cortisol, and homicidal behavior of female prison inmates. Nursing Research. 2008;57(3):166–174. [PubMed]
  • Bureau of Justice Statistics. Key facts at a glance: Correctional populations. 2010 [Website.] Retrieved on 1/20/11 from http://bjs.ojp.usdoj.gov/content/glance/tables/corr2tab.cfm.
  • California Department of Corrections & Rehabilitation (CDCR) California prisoners & parolees 2008: Summary statistics on adult felon prisoners and parolees, civil narcotic addicts and outpatients and other populations. 2009a Retrieved on January 20, 2011 from http://www.cdrc.ca.gov/Reports_Research/Offender_Information_Services_Branch/Annual/CalPris/CALPRISd2008.pdf.
  • CDCR. One and two year follow-up rates for all paroled felons released from prison for the first time in 2006 under the supervision of the California Department of Corrections and Rehabilitation. 2009b Retrieved on January 22, 2011 from www.cdcr.ca.gov/Reports_Research/Offender_Information_Services_Branch/Annual/RECID2/RECID2d2006.pdf-2010-06-01.
  • Cartier J, Farabee D, Prendergast ML. Methamphetamine use, self-reported violent crime, and recidivism among offenders in California who abuse substances. Journal of Interpersonal Violence. 2006;21(4):435–45. [PubMed]
  • Carver CS. You want to measure coping but your protocol’s too long: Consider the Brief COPE. International Journal of Behavioral Medicine. 1997;4:92–100. [PubMed]
  • Christoffersen MN, Soothill K. The long-term consequences of parental alcohol abuse: A cohort study of children in Denmark. Journal of Substance Abuse Treatment. 2003;25:107–116. [PubMed]
  • Clear TR, Sumter MT. Prisoners, prison, and religion: Religion and adjustment to prison. Journal of Offender Rehabilitation. 2002;35(3):125–156.
  • Coopersmith S. The antecedents of self-esteem. San Francisco: W.H. Freeman; 1967.
  • Cuomo C, Sarchiapone M, Di Giannantonio M, Mancini M, Roy A. Depression, impulsivity, personality traits, and childhood trauma of prisoners with substance abuse and addition. Journal of Drug &Alcohol Abuse. 2008;34:339–345. [PubMed]
  • Darke S, Torok M, Kaye S, Ross J, McKetin R. Comparative rates of violent crime among regular methamphetamine and opiod users: Offending and victimization. Addiction. 2010;105:916–919. [PubMed]
  • Dube SR, Anda RF, Felitti VJ, Edwards VJ, Croft JB. Adverse childhood experiences and personal alcohol abuse as an adult. Addictive Behaviors. 2002;27:713–725. [PubMed]
  • Dumais A, Cote G, Lesage A. Clinical and sociodemographic profiles of male inmates with severe mental illness: A comparison with voluntarily and involuntarily hospitalized patients. The Canadian Journal of Psychiatry. 2010;55(3):172–179. [PubMed]
  • Fazel S, Danesh J. Serious mental disorder in 23,000 prisoners: A systematic review of 62 surveys. The Lancet. 2002;359:545–550. [PubMed]
  • Felson RB, Staff J. The effects of alcohol intoxication on violent versus other offending. Criminal Justice &Behavior. 2010;37(12):1343–1360.
  • Forrester A, Chiu K, Dove S, Parrott J. Prison health-care wings: Psychiatry’s forgotten frontier? Criminal Behavior & Mental Health. 2010;20(1):51–61. [PubMed]
  • Gatti U, Tremblay RE, Vitaro F, McDuff P. Youth gangs, delinquency and drug use: A test of the selection, facilitation, and enhancement hypotheses. Journal of Child Psychology & Psychiatry. 2005;46(11):1178–1190. [PubMed]
  • Gideon L. What shall I do now? Released offenders’ expectations for supervision upon release. International Journal of Offender Therapy &Comparative Criminology. 2009;53:43–56. [PubMed]
  • Golzari M, Hunt SJ, Anoshiravani A. The health status of youth in juvenile detention facilities. Journal of Adolescent Health. 2006;38:776–782. [PubMed]
  • Greenberg GA, Rosenheck RA. Jail incarceration, homelessness, and mental health: A national study. Psychiatric Services. 2008;59(2):170–177. [PubMed]
  • Haney C. The psychological impact of incarceration: Implications for post prison adjustment. In: Travis J, Waul M, editors. Prisoners once removed. Washington D. C: United States Department of Health and Human Services; 2003. pp. 33–66.
  • Hanson RF, Self-Brown S, Fricker-Elhai A, Kilpatrick DG, Saunders BE, Resnick H. Relations among parental substance use, violence exposure and mental health: The national survey of adolescents. Addictive Behaviors. 2006;31:1988–2001. [PubMed]
  • Harper GW, Davidson J, Hosek DG. Influence of gang membership on negative affect, substance use, and antisocial behavior among homeless African American male youth. American Journal of Men’s Health. 2008;2:229–243. [PubMed]
  • Harzke AJ, Ross W, Scott DP. Predictors of post-release primary care utilization among HIV-positive prison inmates: A pilot study. AIDS Care. 2006;18(4):290–301. [PubMed]
  • Hiscoke UL, Langstrom N, Ottosson H, Grann M. Self-reported personality traits and disorders (DSM-IV) and risk of criminal recidivism: A prospective study. Journal of Personality Disorders. 2003;17(4):293–305. [PubMed]
  • Kelley ML, Braitman A, Henson JM, Schroeder V, Ladage J, Gumienny L. Relationship among depressive mood symptoms and parent and peer relations in collegiate children of alcoholics. American Journal of Orthopsychiatry. 2010;80(2):204–212. [PubMed]
  • Kessler RC, Chiu WT, Demler O, Walters EE. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the national comorbidity survey. Archives of General Psychiatry. 2005;62:617–627. [PMC free article] [PubMed]
  • Kerridge BT. Sociological, social psychological, and psychopathological correlates of substance use disorders in the US jail population. International Journal of Offender Therapy & Comparative Criminology. 2009;53(2):168–190. [PubMed]
  • Lansford JE, Dodge KA, Petit GS, Bates JE, Crozier J, Kaplow J. A 12-year prospective study of the long-term effects of early child physical maltreatment on psychological, behavioral, and academic problems in adolescence. Archives of Pediatric & Adolescent Medicine. 2002;156:824–830. [PMC free article] [PubMed]
  • Levitt L, Loper AB. The influence of religious participation on the adjustment of female inmates. Journal of American Orthopsychiatry. 2009;79(1):1–7. [PubMed]
  • Liable DJ, Carlo G, Roesch SC. Pathways to self-esteem in late adolescence: The role of parent and peer attachment, empathy, and social behaviours. Journal of Adolescence. 2004;27:703–716. [PubMed]
  • Lurigio AJ. Effective services for parolees with mental illnesses. Crime & Delinquency. 2001;47(3):446–461.
  • Mallers MH, Charles ST, Neupert SD, Almeida DM. Perceptions of childhood relationships with mother and father: Daily emotional and stressor experiences in adulthood. Developmental Psychology. 2010 doi: 10.1037/a0021020. advance online publication. [PMC free article] [PubMed] [Cross Ref]
  • Marlow E. The impact of health care access on the community reintegration of male parolees (unpublished dissertation results) San Francisco: University of California; 2007.
  • Matsuura N, Hashimoto T, Toichi M. Correlations among self-esteem, aggression, adverse childhood experiences and depression in inmates of a female juvenile correctional facility in Japan. Psychiatry and Clinical Neurosciences. 2009;63:478–485. [PubMed]
  • Messina N, Burdon W, Hagopian G, Prendergast M. One year return to custody rates among co-disordered offenders. Behavioral Sciences and the Law. 2004;22:503–518. [PubMed]
  • Mizuno Y, Purcell DW, Dawson-Rose C, Parsons JT. Correlates of depressive symptoms among HIV-positive injection drug users: The role of social support. AIDS Care. 2003;15(5):689–698. [PubMed]
  • Nyamathi A, Bennett C, Leake B, Lewis C, Flaskerud J. AIDS-related knowledge, perceptions, and behaviors among impoverished minority women. American Journal of Public Health. 1993;83:65–71. [PubMed]
  • Nyamathi A, Flaskerud J, Leake B. HIV-risk behaviors and mental health characteristics among homeless or drug-recovering women and their closest sources of social support. Nursing Research. 1997;46:133–7. [PubMed]
  • Nyamathi AM, Christiani A, Nahid P, Gregerson P, Leake B. A randomized controlled trial of two treatment programs for homeless adults with latent tuberculosis infection. International Journal of Tuberculosis & Lung Disease. 2006;7:775–82. [PubMed]
  • Nyamathi A, de Castro V, McNeese-Smith D, Nyamathi K, Shoptaw S, Marfisee M, Khallifard F, Cohen A. Alcohol use reduction program in methadone maintained individuals with HCV infection. Journal of Addictive Diseases. 2008;27(4):27–30. [PubMed]
  • Park J. Adolescent self-concept and health into adulthood. Statistics Canada, Supplement to Health Reports, 82-003. 2003:41–52. [PubMed]
  • Peiponen S, Laukkanen E, Korhonen V, Hintikka U, Lehtonen J. The association of parental alcohol abuse and depression with severe emotional and behavioral problems in adolescents: A clinical study. International Journal of Social Psychiatry. 2006;52(5):395–407. [PubMed]
  • Pelissier BM, O’Neil JA. Antisocial personality and depression among incarcerated drug treatment participants. Journal of Substance Abuse Treatment. 2000;11(4):379–393. [PubMed]
  • Petersilia J. When prisoners come home. New York, NY: Oxford University Press; 2003.
  • Radloff S. The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement. 1977;1:385–401.
  • Rangarajan S. Mediators and moderators of parental alcoholism effects on offspring self-esteem. Alcohol & Alcoholism. 2008;43(4):481–491. [PubMed]
  • Risser J, Cates A, Rehman H, Risser W. Gender differences in social support and depression among injection drug users in Houston, Texas. The American Journal of Drug & Alcohol Abuse. 2010;36:18–24. [PubMed]
  • Roberts R, O’Connor T, Dunn J, Golding J. The ALSPAC Study Team. The effects of child sexual abuse in later family life; mental health, parenting and adjustment offspring. Child Abuse & Neglect. 2004;28:525–545. [PubMed]
  • Sacks S, Cleland CM, Melnick G, Flynn PM, Knight K, Friedmann PD, Prendergast ML, Coen C. Violent offenses associated with co-occurring substance use and mental health problems: Evidence from CJDATS. Behavioral Sciences & Law. 2009;27(1):51–69. [PMC free article] [PubMed]
  • Seal DW, Eldridge GG, Kacanek D, Binson D, MacGowan RJ. A longitudinal, qualitative analysis of the context of substance use and sexual behavior among 18–29 year old men after their release from prison. Social Science & Medicine. 2007;65:2394–2406. [PubMed]
  • Sherbourne CD, Stewart AL. The MOS social support survey. Social Science & Medicine. 1991;32:705–714. [PubMed]
  • Shinkfield AJ, Graffam J, Meneilly S. Co-morbidity of conditions among prisoners. Journal of Offender Rehabilitation. 2009;48(4):350–365.
  • Simpson D, Chatham L. TCU/DATAR forms manual. Ft. Worth, TX: Institute of Behavioral Research, Texas Christian University; 1995.
  • Skeem JL, Louden JE. Toward evidence-based practice for probationers and parolees mandated to mental health treatment. Psychiatric Services. 2006;57(3):333–342. [PubMed]
  • Solomon P, Draine J, Marcus SC. Predicting incarceration of clients of a psychiatric probation and parole service. Psychiatric Services. 2002;53(1):50–56. [PubMed]
  • Sung HE, Richter L. Contextual barriers to successful reentry of recovering drug offenders. Journal of Substance Abuse Treatment. 2006;31:365–374. [PubMed]
  • Swahn MH, Bossarte RM, West B, Topalli V. Alcohol and drug use among gang members: Experiences of adolescents who attend school. Journal of School Health. 2010;80(7):353–360. [PubMed]
  • Taxman FS. The offender and reentry: Supporting active participation in reintegration. Federal Probation. 2004;68(2):31–35.
  • Travis J, Solomon A, Waul M. From prison to home: The dimensions and consequences of prisoner reentry. Washington, DC: The Urban Institute; 2001.
  • US Census Bureau. US summary: 2000. 2002 Retrieved from http://www.census.gov/prod/2002pubs/c2kprof00-us.pdf.
  • van Beljouw IM, Verhaak PF, Cuijpers P, van Marwijk HW, Penninx BW. The course of untreated anxiety and depression, and determinants of poor one-year outcome: A one-year cohort study. BMC Psychiatry. 2010;10:86. [PMC free article] [PubMed]
  • Visher C, La Vigne N, Travis J. Returning home: Understanding the challenges of prisoner reentry, Maryland pilot study, findings from Baltimore. Washington, DC: Urban Institute; 2004.
  • Vostanis P, Graves A, Meltzer H, Goodman R, Jenkins R, Brugha T. Relationship between parental psychopathology, parenting strategies and child mental health. Social Psychiatry and Psychiatric Epidemiology. 2006;41:509–514. [PubMed]
  • Wilper AP, Woolhandler S, Boyd W, Lasser KE, McCormick D, Bor DH, Himmelstein DU. The health and health care of US prisoners: Results of a nationwide survey. American Journal of Public Health. 2009;99(4):666–672. [PubMed]
  • World Health Organization (WHO) The global burden of disease: 2004 update, Table A2: Burden of disease in DALYs by cause, sex and income group in WHO regions, estimates for 2004. Geneva, Switzerland: 2008. Retrieved January 11, 2011 from http://ww.who.int/healthinfo/global_burden_disease/GBD_report_2004update_AnnexA.pdf.
  • Wu NS, Schairer LC, Dellor E, Grella C. Childhood trauma and health outcomes in adults with comorbid substance abuse and mental health disorders. Addictive Behaviors. 2010;35(1):68–71. [PMC free article] [PubMed]
  • Zhang SX, Roberts REL, Callanan VJ. Preventing parolees from returning to prison through community-based reintegration. Crime & Delinquency. 2006;52(4):551–571.
  • Zhang SX, Roberts REL, McCollister KE. Therapeutic community in a California prison: Treatment outcomes after five years. Crime & Delinquency. 2009 (first published on January 29, 2009; available at: http://cad.sagepub.com/content/early/2009/01/29/0011128708327035.full.pdf+html)
  • Zlotnick C, Clarke JG, Friedmann PD, Roberts MB, Melnick G. Gender differences in comorbid disorders among offenders in prison substance abuse treatment programs. Behavioral Sciences &the Law. 2008;26:403–412. [PMC free article] [PubMed]