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Substance Use Disorder Prevalence among Female State Prison Inmates

Steven L. Proctor, M.A.

Department of Psychology, Louisiana State University, Baton Rouge, LA, USA

Background: Substance use disorders (SUDs) are prevalent among female inmates. As the female state prison population continues to increase, describing the specific clinical and demographic characteristics of female prisoners remains of paramount importance to better define women’s needs in the state prison system. Objectives: To determine the prevalence and patterns of current DSM-IV SUDs and explore whether particular demographic characteristics are more strongly associated with specific SUD categories. Methods: Data were derived from routine clinical assessments of 801 female inmates incarcerated in the Minnesota Department of Corrections state prison system. The Substance Use Disorder Diagnostic Schedule-IV (Hoffmann NG, Harrison PA. SUDDS-IV: Substance Use Disorder Diagnostic Schedule-IV. Smithfield, RI: Evince Clinical Assessments, 1995) was administered to all inmates as a computer-prompted interview on admission to the prison. Results: Of the inmates, 70.0% were dependent on at least one substance, and 7.9% met criteria for substance abuse. Alcohol dependence (30.2%) and cocaine dependence (30.1%) were the two most prevalent SUDs. The remaining substance dependence diagnoses that predominated were as follows: stimulant dependence, 24.1%; marijuana dependence, 15.6%; and heroin dependence, 9.6%. Over half (56.9%) were dependent on a substance other than alcohol. Prevalence of cocaine dependence [odds ratio (OR) ¼ 2.83, 95% confidence interval (CI) ¼ 1.92–4.16] was significantly higher among African Americans, whereas prevalence of stimulant dependence (OR ¼ 9.24, 95% CI ¼ 5.40–15.80) was significantly higher among Caucasians. Prevalence of alcohol (OR ¼ 2.12, 95% CI ¼ 1.38–3.25) and heroin (OR ¼ 2.67, 95% CI ¼ 1.50–4.77) dependence was significantly higher among Native Americans. Conclusions and Scientific Significance: SUDs in general, and illicit drug use disorders in particular, are prevalent among female inmates entering a state

prison system. Membership to a particular ethnic group may identify a set of inmates at elevated risk for the presence of substance-specific dependence diagnoses.

Keywords: prevalence, substance use disorders, inmates, state prison, women

INTRODUCTION

Overcrowding has become a principal concern for state prison systems in the United States. Although men consti- tute over four-fifths of the total correctional population, there has been a dramatic increase in the number of women entering the state prison system over the past two decades (1). In fact, between 1990 and 2009, the total number of women incarcerated in prison has increased by over 100%. Current estimates of the percentage of women within the total adult correctional population have also increased since 1990 (18 vs. 14%, respectively) (1). High-incarceration rates contribute to incarceration costs and have the potential to place a disproportionate strain on correctional officers.

Not only has the total number of women incarcerated in the state prison system experienced a substantial increase over the past two decades, but trends in the number of felony convictions of women are also a cause for concern. The number of women convicted of a felony has grown at 2.5 times the rate of increase than that of male offen- ders (2). Specifically, the considerable growth in the rates of women convicted of felonies was accounted for by aggravated assault and drug-related charges related to drug trafficking and drug possession (2). Thus, given increases related to both the number and severity of offenses committed by women, the need to accurately identify relevant gender-specific issues unique to women and define women’s clinical needs within the context of a state prison setting is of paramount importance.

One such variable is the high prevalence of substance use and substance use disorders (SUDs) among incarcer- ated women (3–7). A systematic review of the vast SUD prevalence literature among female inmates on reception into prison found that estimates of SUD prevalence ranged

Address correspondence to Steven L. Proctor, Department of Psychology, Louisiana State University, 236 Audubon Hall, Baton Rouge, LA 70803, USA. E-mail: [email protected]

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from 10.0% to 23.9% for alcohol abuse and dependence and from 30.3% to 60.4% for drug abuse and dependence (8). Although the heterogeneity between the various stu- dies in terms of SUD prevalence rates for women prison inmates is quite large, such rates are still much higher than those found among the general adult population (9).

Extant research has amassed to support the contention that substance use in general and illicit drug use in parti- cular are common among female offenders and appear related to criminal behavior (2,10,11). In fact, findings from a meta-analysis of the vast criminal recidivism litera- ture found problematic alcohol or drug use to be a signifi- cant risk factor for future criminal behavior (11). Although many predictor variables of criminal recidivism among offenders have been shown to have gender-neutral effects, problematic substance use appears to be more strongly related to criminal behavior for women compared with men (12). Further, nearly one-third of the female state prison population is comprised of inmates convicted of drug-related offenses (13) and approximately half of women offenders incarcerated in state prisons were under the influence of drugs or alcohol at the time of the offense for which they had been incarcerated (2). Specifically, illicit drug use at the time of the offense was reported more often than alcohol use among female inmates, a finding different from that found among male inmates in state prisons. Female arrests for drug-related offenses have also experienced notable increases (14). A survey of state prison inmates found that more women reported being under the influence of drugs at the time they committed the offense for which they were currently incarcerated than men (15). Thus, illicit drug use and drug use disorders appear to be unique gender-specific variables among incar- cerated individuals.

Another noteworthy consideration is that, historically, the research literature dealing with the prevalence of SUDs among inmates has offered limited insight into the prevalence rates specific to women through their exclusive focus on male inmates (16–18). Additionally, research in this area is limited due to various methodological limita- tions, including the tendency to consider all nonalcohol SUDs as a single drug use disorder category, and/or the failure to definitively distinguish between diagnoses of dependence versus abuse (8,19–23). Given substance- dependent individuals tend to experience poorer prognosis and treatment outcomes relative to individuals with a sub- stance abuse diagnosis (24–26), the need to clearly differ- entiate between diagnoses of dependence versus abuse remains an important goal if authorities aspire to meet the unique SUD treatment needs of incarcerated women.

In sum, as the total female state prison population and trends in felony convictions of women regarding the num- ber and severity of offenses continue to increase, describ- ing the characteristics of the changing population of female state prison inmates is a critical first step in better defining women’s needs in the state prison system. Further, extant research has documented that SUDs in general, and drug use disorders in particular, are highly prevalent among female state prison inmates, and illicit drug use among

women appears related to offending. Therefore, illicit drug use disorders and drug use appear to be unique gender-specific variables among incarcerated individuals. Although a body of knowledge regarding SUD prevalence among female inmates is accumulating, to date there remains limited published research examining specific drug use disorder prevalence among female state prison inmates, as well as research addressing the issue of a pragmatic way of identifying those inmates in need of additional addictions services.

Thus, this study sought to fill the apparent gaps in the research literature regarding SUD prevalence among female inmates through the use of the Substance Use Disorder Diagnostic Schedule-IV (SUDDS-IV), a struc- tured diagnostic assessment interview compatible with DSM-IV (27) criteria, which provides substance abuse and dependence diagnoses for a variety of specific sub- stances, to estimate prevalence of alcohol and individual drug use disorders among female inmates incarcerated in a state prison setting. Prevalence and patterns of SUDs were explored in three ways: (1) providing general estimates of the prevalence of the various SUD categories as assessed by the SUDDS-IV, (2) exploring the apparent patterns of multiple SUD diagnoses, and (3) testing whether particular demographic characteristics were more strongly associated with the various SUD categories.

METHOD

Participants Data for this study were derived from routine clinical assessments of 801 female inmates between the ages of 18 and 58 years (M ¼ 32.8, SD ¼ 8.26) recently incarcerated in the Minnesota Department of Corrections state prison sys- tem from 2000 to 2003. Ethnic composition of the total sample was predominately Caucasian (57.7%), while African Americans (21.5%) and Native Americans (13.2%) constituted the largest racial-minority groups. The balance of the cases was distributed among Hispanics, Asians, and those inmates who reported “other or multi- racial” ethnicity. Over three-fourths had never been married (56.1%) or were divorced (23.0%) and only 12.4% of the inmates were currently married at the time of incarceration. Educational attainment tended to be low in that 34.3% had not completed high school and only 17.8% had received any vocational or formal education beyond high school. In terms of employment status, slightly more than half (54.3%) of the inmates were unemployed. The remainder of the total sample reported that they were employed either full-time (32.1%) or part-time (13.6%) prior to incarceration. Nearly one-fifth (18.5%) of the inmates reported that they worked as a service worker (e.g., waitress) with laborer/temporary worker (15.2%) or domestic worker (e.g., housekeeper; 13.1%) being the next largest job designations. Personal income also tended to be rather low in that 63.2% reported earning a range of less than $10,000 in the year prior to incarceration and only 5.4% reported earning more than $30,000. Slightly less than half (45.1%) of the inmates reported that they had children living with them in their

SUBSTANCE USE DISORDERS AMONG FEMALE PRISONERS 279

homes at the time of incarceration. Given an aim of this study was to examine the associations between ethnicity and substance dependence for the various substances cov- ered by the SUDDS-IV, demographic characteristics are presented separately in Table 1 for all ethnic groups of sufficient size for making statistical comparisons.

Measures The SUDDS-IV is a diagnostic assessment interview designed to provide detailed and thorough coverage of lifetime and current DSM-IV SUDs. The SUD inquiry of the SUDDS-IV is comprised of 48 items, which are used to assess the 7 DSM-IV dependence and 4 abuse criteria, with multiple items for most of the individual criteria. For instance, in regard to the DSM-IV dependence criterion 7 (i.e., medical or psychological contraindications to sub- stance use), the SUDDS-IV includes four items: Have you ever continued to use alcohol or drugs when you knew you had a physical illness that might be made worse by alcohol or drug use?; Have you ever had any medical problems that you or anyone else thought were related to your alcohol or drug use?; [Females only] Have you ever used alcohol or drugs more than you believed you should when you knew you were pregnant?; and Have you ever had so much to drink that the next day you could not

remember what you had said or done? All positive responses to the individual general questions are then followed up with clarifications as to whether the positive response refers to alcohol and/or the other specified sub- stances covered by the SUDDS-IV. Based on the algo- rithms used for this study, a positive response to any one of these four individual items for a given substance would assign this particular dependence criterion as being posi- tive for that substance.

The SUDDS-IV has been used to assess SUDs among numerous correctional populations (28–30) and has evi- denced adequate construct validity (29). Internal consis- tency reliability estimates for the items comprising the various substance-specific categories yielded Cronbach’s alphas ranging from over .90 for the dependence scales to above .85 for the abuse scales (29). The SUDDS-IV con- siders the 12 months prior to incarceration for the time frame utilized in arriving at current SUD diagnoses. This time frame takes into account that being in a restrictive environment precludes assigning a formal diagnosis after incarceration.

Procedure All inmates were assessed for SUD indications by certified addictions counselors to identify potential treatment needs

TABLE 1. Demographic characteristics by ethnic group.

Ethnic group

Caucasian African American Native American N ¼ 462 N ¼ 172 N ¼ 106

Variable % (n) % (n) % (n)

Age (years) 18–24 18.0 (83) 14.0 (24) 25.5 (27) 25–34 36.1 (167) 41.3 (71) 41.5 (44) 35–44 35.5 (164) 40.7 (70) 25.5 (27) 45þ 10.4 (48) 4.1 (7) 7.5 (8)

Marital status Never married 48.3 (223) 72.1 (124) 63.2 (67) Married 13.2 (61) 9.9 (17) 11.3 (12) Divorced 28.8 (133) 13.4 (23) 16.0 (17) Separated 7.6 (35) 3.5 (6) 7.5 (8) Widowed 2.2 (10) 1.2 (2) 1.9 (2)

Education Some high school or less 24.0 (111) 53.5 (92) 39.6 (42) High school graduate/GED 53.2 (246) 37.2 (64) 46.2 (49) Vocational/technical 13.2 (61) 6.4 (11) 8.5 (9) Associate degree 4.3 (20) 2.9 (5) 3.8 (4) Bachelor’s degree or more 5.1 (24) 0.0 1.9 (2)

Employment status Unemployed 48.0 (222) 59.8 (103) 73.6 (78) Full-time 36.1 (167) 29.1 (50) 17.9 (19) Part-time 15.8 (73) 11.0 (19) 8.5 (9)

Personal income $10,000 or less 57.1 (264) 67.4 (116) 80.2 (85) $10,001–20,000 22.3 (103) 20.3 (35) 15.1 (16) $20,001–30,000 13.4 (62) 8.7 (15) 1.9 (2) $30,001–40,000 2.8 (13) 2.3 (4) 0.0 $40,001þ 4.3 (20) 1.2 (2) 2.8 (3)

Note: Percentages may not total 100% due to rounding.

280 S. L. PROCTOR

on entering the Minnesota Department of Corrections sys- tem. Interviews typically were conducted for 35–45 min depending on the range of positive responses endorsed by the inmates. Data were derived from the SUDDS-IV, adapted for correctional applications. It was used as a computer-prompted interview whereby the clinical staff asked the questions as they appeared on the screen and recorded the inmates’ responses on laptop computers. The computer program exported a de-identified, tab-delimited text file that was imported into Statistical Package for the Social Sciences (SPSS, Version 16.0) for Windows (SPSS Inc., Chicago, IL) to facilitate the generation of quarterly and annual statistical summaries for the Minnesota Department of Corrections.

Data Analyses Data obtained from the SUDDS-IV were entered into SPSS and analyzed to assess the aims of this study. Algorithms were used to implement decision rules within the specific SUD categories to group cases into diagnostic classification groups. For each substance, the positive responses for items within each of the seven dependence and four abuse criteria are considered by the algorithms used in determining a diagnosis for this study. In accor- dance with the DSM-IV criteria, a positive finding on one or more abuse criteria would qualify for an abuse diagnosis unless there are three or more positive dependence criteria. In this case, a diagnosis of dependence would be assigned as the DSM-IV requires that a diagnosis of dependence supersedes the diagnosis of abuse. Chi-square analyses were conducted to explore the associations between ethni- city and substance dependence for the various substances covered by the SUDDS-IV. In terms of ethnic groups, only three groups (Caucasian, African American, and Native American) were of sufficient size for making statistical comparisons of diagnostic prevalence rates. A cross tabu- lation involving these three categories was utilized to ascertain whether particular ethnic groups were more strongly associated with the various substance-dependence diagnoses. In addition, separate binary logistic regression models were fitted to the data to test the hypothesis regard- ing the relationship between the likelihood that an inmate would be positive for the various substance dependence categories assessed by the SUDDS-IV and ethnicity after adjustment for other covariates, including age, marital status, educational level, and employment status – all are relevant variables identified in the literature as risk factors for the development of SUDs (31–33). A hierarchical method of data entry was utilized with relevant demo- graphic variables entered at block 1 and ethnic group entered at block 2. Goodness-of-fit statistics were exam- ined to assess the fit of each respective logistic model against actual outcome (i.e., whether inmates received a particular substance dependence diagnosis). One inferen- tial test (i.e., Hosmer–Lemeshow) and two additional descriptive measures of goodness of fit (i.e., R2 indices defined by Cox and Snell and Nagelkerke) were utilized to determine whether the various models fit to the data well.

RESULTS

Over two-thirds (70.0%) of the inmates met DSM-IV diagnostic criteria for substance dependence for at least one substance, and an additional 7.9% met criteria for substance abuse. The prevalence rates for the individual SUD categories are presented in Table 2. Regarding the substance dependence diagnoses, alcohol dependence (30.2%) and cocaine dependence (30.1%) were the two most prevalent SUDs with almost one-third meeting diag- nostic criteria for each of these disorders. Stimulant depen- dence (24.1%) was the next most common SUD, followed by marijuana dependence (15.6%) and heroin dependence (9.6%). The remaining substance dependence diagnoses related to the other substances assessed by the SUDDS-IV (e.g., sedatives, hallucinogens) accounted for less than 1.0% of the substance-dependent cases.

In particular, non-alcohol SUDs were prevalent among the total sample as over half (56.9%) were dependent on a substance other than alcohol. However, some overlap was noted between alcohol and illicit drug dependence. Of those inmates who met DSM-IV criteria for alcohol depen- dence, 64.1% were also dependent on another substance, and of those dependent on drugs, 30.1% were also depen- dent on alcohol. Dependence on multiple substances was also common among the total sample. In fact, of those inmates who met criteria for substance dependence for at least one substance, 44.0% were dependent on two or more substances.

Next, the prevalence rates for the individual substance- dependence categories were examined by ethnic groups to determine whether some demographic characteristics were more strongly associated with individual substance- dependence categories than others (Table 3). Of particular interest was the significant association found between ethnicity and cocaine dependence, X2(2, N ¼ 740) ¼

TABLE 2. Prevalence rates for select substance use disorders.

Diagnostic category Prevalence (%)

Alcohol Dependence 30.2 Abuse 10.2

Cocaine Dependence 30.1 Abuse 5.4

Marijuana Dependence 15.6 Abuse 7.5

Stimulant Dependence 24.1 Abuse 2.1

Heroin Dependence 9.6 Abuse 0.9

Note: Substance use disorder prevalence rates specific to sedatives and hallucinogens are not included due to low use rates (<1.0% of cases).

SUBSTANCE USE DISORDERS AMONG FEMALE PRISONERS 281

47.903, p < .001, V ¼ .254. As can be seen in Table 3, prevalence of cocaine dependence was markedly elevated for the African American inmates. Over half (50.6%) of the African Americans met DSM-IV criteria for cocaine dependence, whereas only 22.3% of the Caucasians and 29.2% of the Native Americans met criteria for cocaine dependence. Several additional significant associations were noted between ethnicity and dependence on other substances, including alcohol [X2(2, N ¼ 740) ¼ 17.640, p < .001, V ¼ .154], stimulants [X2(2, N ¼ 740) ¼ 94.182, p < .001, V ¼ .357], and heroin [X2(2, N ¼ 740) ¼ 14.320, p < .01, V ¼ .139]. Specifically, nearly half (46.2%) of the Native Americans met DSM-IV criteria for alcohol depen- dence, compared with only 27.7 and 23.8% of the Caucasian and African American inmates, respectively. Significantly more Caucasian inmates met criteria for sti- mulant dependence (36.8%) than the other two ethnic groups, and heroin dependence (19.8%) was most common among Native Americans.

Hierarchical binary logistic regressions were conducted to further assess the impact of ethnicity on the presence of specific substance dependence diagnoses after controlling for age, marital status, educational level, and employment status (see Table 4). Results revealed that inmates of African American ethnicity were much more likely to receive a cocaine-dependence diagnosis [odds ratio (OR) ¼ 2.83, 95% confidence interval (CI) ¼ 1.92–4.16] compared with those of Caucasian or Native American ethnicity even after adjustment for the other relevant demographic predictor variables, model X2(5) ¼ 81.179, p < .001, R2 ¼ .10 (Cox and Snell), R2 ¼ .15 (Nagelkerke). Further, the Hosmer–Lemeshow goodness-of-fit test was insignificant, X2(8) ¼ 6.840, p > .05, suggesting that the model was fit to the data well. Inmates of Caucasian ethnicity were much more likely to receive a stimulant dependence diagnosis (OR ¼ 9.24, 95% CI ¼ 5.40– 15.80) compared with those of African American or Native American ethnicity, model X2(5) ¼ 112.614, p < .001, R2 ¼ .14 (Cox and Snell), R2 ¼ .21 (Nagelkerke). The Hosmer–Lemeshow test was also insignificant for this model, X2(8) ¼ 4.007, p > .05. Inmates of Native American ethnicity were more likely to receive an alcohol dependence diagnosis (OR ¼ 2.12, 95% CI ¼ 1.38–3.25) compared with those of African American or Caucasian ethnicity, model X2(5) ¼ 24.824, p < .001, R2 ¼ .03 (Cox

and Snell), R2 ¼ .05 (Nagelkerke). The Hosmer– Lemeshow test was insignificant for this model as well, X2(8) ¼ 7.000, p > .05. Inmates of Native American ethnicity were also more likely to receive a heroin dependence diagnosis (OR ¼ 2.67, 95% CI ¼ 1.50–4.77) compared with those of African American and Caucasian ethnicity, model X2(5) ¼ 28.652, p < 0.001, R2 ¼ .04 (Cox and Snell), R2 ¼ .08 (Nagelkerke). The Hosmer–Lemeshow test was insignificant, X2(8) ¼ 7.775, p > .05. Finally, inmates of Native American ethnicity were not significantly more likely to receive a marijuana dependence diagnosis (OR ¼ 1.22, 95% CI ¼ 0.70–2.11) compared with those of African American and Caucasian ethnicity, model X2(5) ¼ 45.203, p < .001, R2 ¼ .06 (Cox and Snell), R2 ¼ .10 (Nagelkerke). The Hosmer–Lemeshow test approached sig- nificance, X2(8) ¼ 14.958, p ¼ .06, and if one considers the respective Wald statistic for this predictor (X2 ¼ 0.49), it appears that Native American ethnicity (β ¼ 0.20) pro- vided relatively little individual contribution to marijuana dependence outcome after adjustment for the other rele- vant demographic predictor variables.

DISCUSSION

The objectives of this study were to identify and describe the prevalence and patterns of SUDs among female inmates entering a state prison system. Several of the findings warrant further discussion. First, an important aspect of the results was the high prevalence of SUDs, with over three-fourths of the total sample meeting DSM- IV criteria for substance dependence (70.0%) or substance abuse (7.9%) for one or more substances. Specifically, alcohol and cocaine dependence were among the most prevalent substance dependence diagnoses, followed by stimulant, marijuana, and heroin dependence. Although the observed SUD prevalence rates appear high, similar findings have been found among female inmates entering a state prison system where the reported rate for any SUD was found to be 60.4%, as well as among a female arrestee population where 84.8% of women were found to be dependent on at least one substance (34,35).

Despite the relatively high estimates of SUD prevalence noted in this study, substance dependence was clearly more prevalent than substance abuse. This finding may be due to the fact that abuse, as defined by the DSM-IV, is

TABLE 3. Substance dependence prevalence by ethnicity.

Ethnic group

Dependence category Caucasian (n ¼ 462) (%) African American (n ¼ 172) (%) Native American (n ¼ 106) (%) Alcohol** 27.7 23.8 46.2 Marijuana 13.6 15.1 20.8 Cocaine** 22.3 50.6 29.2 Stimulant** 36.8 0.0 17.0 Heroin* 8.0 8.1 19.8

Notes: Only those ethnic groups of sufficient size for making statistical comparisons of diagnostic prevalence rates were included. *p < .01; **p < .001.

282 S. L. PROCTOR

consistently less prevalent than dependence in both incar- cerated samples and the general adult population, or it may be a function of the potential bias resulting from dependent women being more likely to be incarcerated than those women who exhibit substance use behaviors characteristic of abuse (8,15). Given the magnitude of the difference in prevalence between dependent and abuse cases (i.e., abso- lute difference of ,60%) in this study, the bias argument seems the more plausible explanation for the observed findings, which suggests the need for more intensive clinical services for incarcerated women.

Dependence on multiple substances was also common among this female state prison sample as nearly half of those inmates who met DSM-IV criteria for substance dependence for at least one substance were also dependent on two or more substances. From a clinical perspective, when substance dependence indications are detected from any one of the DSM-IV SUD classes, the odds would suggest that in approximately one in every two cases, multiple substance dependence diagnoses will be found among those female inmates entering a state prison system. Such findings may inform clinical decision-making and the need for clinical staff or addictions treatment profes- sionals to explore the full extent of substance dependence categories whenever any positive indications are reported by women. Therefore, positive dependence indications from any one group of substances should result in a care- ful, comprehensive examination of all categories of dependence.

Also noteworthy was the finding that over half (56.9%) of the total sample was dependent on a substance other than alcohol. Moreover, of those inmates dependent on alcohol, a majority were also dependent on another sub- stance. Thus, while alcohol dependence was among the most prevalent dependence diagnoses, dependence on

illicit drugs collectively was almost twice as prevalent. The results replicate the well-documented finding that illicit drug use and drug use disorders are prevalent among female state prison inmates (5,7,36). Such findings suggest that the clinical profiles of female inmates, in terms of SUDs, are unique and independent from those of men.

Given that the facilities and SUD treatment programs offered to female inmates are based primarily on models derived from those designed for male inmates, a call for gender-specific approaches is warranted in order to accom- modate the changing needs of incarcerated women. For instance, the present findings suggest that many women entering the state prison system may require addictions treatment services specifically tailored to illicit drug issues. This finding builds on the extant gender-responsive treat- ment literature for inmates, which has demonstrated that women clearly exhibit disparate pathways to crime, addic- tion, and recovery from those of men (37). Thus, women- focused therapeutic community treatment programs should incorporate techniques relevant to the unique beha- viors and cognitions specific to illicit drug use into existing conceptual frameworks (e.g., relational theory) when treat- ing substance-dependent state prison inmates (38).

The data clearly indicate that ethnicity was significantly associated with specific substance dependence prevalence. For instance, cocaine dependence appeared particularly prevalent among African Americans, whereas stimulant dependence was most common among Caucasians. For Native Americans, the prevalence of both alcohol and heroin dependence was significantly higher than the rates for these disorders among the other ethnic groups. In fact, findings from logistic regressions revealed that African Americans were 2.83 times more likely to receive a cocaine dependence diagnosis and Native Americans were significantly more likely to receive dependence

TABLE 4. Predictors of specific substance dependence diagnoses.

95% CI

Predictor variable1 β (SE) Wald’s X2 p OR Lower Upper

Cocaine dependence African American 1.04 (.20) 28.09 <.000 2.83 1.92 4.16 Constant �1.60 (.37)

Alcohol dependence Native American 0.75 (.22) 11.68 .001 2.12 1.38 3.25 Constant �.53 (.36)

Heroin dependence Native American 0.98 (.30) 11.11 .001 2.67 1.50 4.77 Constant �3.30 (.59)

Marijuana dependence Native American 0.20 (.28) 0.49 0.486 1.22 0.70 2.11 Constant 1.04 (.47)

Stimulant dependence Caucasian 2.22 (.27) 65.97 <.000 9.24 5.40 15.80 Constant �1.82 (.42)

Notes: Only those ethnic groups of sufficient size for logistic regressions were included. OR, odds ratio; CI, confidence interval. 1For all models, age, marital status, education level, and employment status were entered as covariates at block 1 with each ethnic group predictor variable for the respective substance dependence diagnosis entered at block 2.

SUBSTANCE USE DISORDERS AMONG FEMALE PRISONERS 283

diagnoses relating to alcohol (OR ¼ 2.12, 95% CI ¼ 1.38– 3.25) and heroin (OR ¼ 2.67, 95% CI ¼ 1.50–4.77) than the other two ethnic groups of interest even after adjust- ment for the relevant covariates included in the models. Of particular interest was the finding that inmates of Caucasian ethnicity were nearly 10 times more likely to be dependent on stimulants (OR ¼ 9.24, 95% CI ¼ 5.40– 15.80) than inmates of African American or Native American ethnicity. These findings demonstrate that mem- bership to a particular ethnic group may identify a set of inmates at elevated risk for the presence of substance- specific dependence diagnoses. However, it is important to note that in terms of the magnitude of the various associations, only the effect size estimates between the substance dependence diagnoses related to cocaine and stimulants revealed moderate associations with ethnicity (i.e., V > .200). Thus, in terms of the ethnic-minority groups, African American women may be more likely to report indications of cocaine dependence, and Native American women may be more likely to report indications of alcohol and heroin dependence based on demographic characteristics alone. These findings are important from a clinical perspective given certain substance dependence categories appear particularly prevalent among different ethnic groups. Such findings may inform the program structure of addictions treatment services for state prison systems, particularly urban prisons or prisons that serve predominately ethnic-minority female populations.

This study also documents the feasibility and practical- ity of using a brief diagnostic assessment interview to identify SUDs and related problems on a routine basis for state prison systems. At the clinical level, the findings provide support for the clinical utility of the SUDDS-IV and suggest that a relatively brief structured interview has the ability to standardize diagnostic assessments by incor- porating both empirically supported elements and a strong theoretical basis to symptoms described in the DSM-IV. Routine clinical administration of the SUDDS-IV may be of value in organizing assessments, designing treatment plans, and/or making appropriate treatment program place- ment decisions within a state prison context. Thus, prac- tical identification of SUDs with relevant information supporting the diagnoses appears possible with minimal time commitment.

The findings from this study should be considered in light of several limitations, which suggest the need for further work in this area. First, the total sample was com- prised exclusively of female inmates, which warrants cau- tion in the interpretation of the findings for male inmates or populations not comprised of incarcerated individuals. Second, the demographic composition of the Minnesota Department of Corrections female state prison population is not entirely representative of other state prison systems. In particular, the ethnic composition of the current sample appeared to over-represent inmates of Caucasian ethnicity, and the level of educational attainment for the current sample was slightly higher than that of nationally repre- sentative state prison samples of female inmates (2,39). Thus, one would need to be cautious in extrapolating the

findings for urban state prison settings with predominantly racial-minority populations or those prisons comprised of inmates with lower levels of education. Finally, as with other clinical interview data, the SUDDS-IV relies largely on self-report. Future research would benefit from a multi- method, multi-informant approach.

Consistent with previous research, the current findings confirm and extend knowledge regarding the prevalence and patterns of SUDs among female inmates entering a state prison system. The finding that nearly 10 times as many women met criteria for dependence than for abuse, coupled with the presence of multiple dependence diag- noses, suggests that female state prison admissions may represent a difficult to treat population requiring intensive and extensive services. If authorities aspire to meet the unique SUD treatment needs of women in the state prison system in an effort to reduce recidivism and ultimately alleviate prison overcrowding, identification and assess- ment of the prevalence and patterns of SUDs is the first step in developing effective treatment strategies. Pragmatic identification of SUDs among female inmates in need of further assessment and treatment appears possible with minimal time commitment. Consideration of various demographic risk factors is also a requisite for these efforts.

ACKNOWLEDGMENT

The author wishes to acknowledge Norman G. Hoffmann, Ph.D., for his assistance in providing feedback on drafts of this manuscript.

Declaration of Interest The author reports no conflicts of interest. The author alone is responsible for the content and writing of this article.

REFERENCES

1. Glaze LE. Correctional Populations in the United States, 2009. Office of Justice Programs, Bureau of Justice Statistics (NCJ Publication No. 23168). Washington, DC: US Department of Justice, 2010.

2. Greenfeld LA, Snell TL. Women Offenders. Office of Justice Programs, Bureau of Justice Statistics (NCJ Publication No. 175688). Washington, DC: US Department of Justice, 1999.

3. Daniel AE, Robins AJ, Reid JC, Wilfley DE. Lifetime and six-month prevalence of psychiatric disorders among sentence female offenders. Bull Am Acad Psychiatry Law 1988; 16:333–342.

4. Denton B. Psychiatric morbidity and substance dependence among women prisoners: An Australian study. Psychiatr Psychol Law 1995; 2:173–177.

5. Jordan BK, Schlenger W, Fairbank JA, Caddell JM. Prevalence of psychiatric disorders among incarcerated women: Convicted felons entering prison. Arch Gen Psychiatry 1996; 53:513–519.

6. Meyers-Chandler S, Kassebaum G. Drug-alcohol dependence of women prisoners in Hawaii. Affilia 1994; 9:157–170.

7. Parsons S, Walker L, Grubin D. Prevalence of mental disorder in female remand prisons. J Forens Psychiatry Psychol 2001; 12:194–202.

284 S. L. PROCTOR

8. Fazel S, Bains P, Doll H. Substance abuse and dependence in prisoners: A systematic review. Addiction 2006; 101:181–191.

9. Substance Abuse and Mental Health Services Administration. Results from the 2008 National Survey on Drug Use and Health: National Findings. Office of Applied Studies (NSDUH Series H-36, HHS Publication No. SMA 09-4434). Rockville, MD: SAMHSA, 2009.

10. Maden A, Swinton M, Gunn J. Women in prison and use of illicit drugs before arrest. BMJ 1990; 301:1133.

11. Bonta J, Law M, Hanson K. The prediction of criminal and violent recidivism among mentally disordered offenders: A meta-analysis. Psychol Bull 1998; 123:123–142.

12. Uggen C, Kruttschnitt C. Crime in the breaking: Gender differ- ences in desistance. Law Soc Rev 1998; 32:339–366.

13. Sabol WJ, West HC, Cooper M. Prisoners in 2008. Office of Justice Programs, Bureau of Justice Statistics (NCJ Publication No. 228417). Washington, DC: US Department of Justice, 2009

14. Harrison PM, Beck AJ. Prisoners in 2002. Office of Justice Programs, Bureau of Justice Statistics (NCJ Publication No. 200248). Washington, DC: US Department of Justice, 2003

15. Nunes-Dinis MC, Weisner C. Gender differences in the relation- ship of alcohol and drug use to criminal behavior in a sample of arrestees. Am J Drug Alcohol Abuse 1997; 23:129–141.

16. Bushnell JA, Bakker LW. Substance use disorders among men in prison: A New Zealand study. Aust NZ J Psychiatry 1997; 31:577–581.

17. Kouri EM, Pope HG, Powell KF, Olivia PS, Campbell C. Drug use history and criminal behavior among 133 incarcerated men. Am J Drug Alcohol Abuse 1997; 23:413–419.

18. Peters RH, Greenbaum PE, Edens JF, Carter CR, Oritz MM. Prevalence of DSM-IV substance abuse and dependence dis- orders among prison inmates. Am J Drug Alcohol Abuse 1998; 24:573–587.

19. Alexander MJ, Haugland G, Lin SP, Bertollo DN, McCorry FA. Mental health screening in addiction, corrections and social service settings: Validating the MMS. Int J Ment Health Addict 2008; 6: 105–119.

20. Draine J, Blank A, Kottsieper P, Solomon P. Contrasting jail diversion and in-jail services for mental illness and substance abuse: Do they serve the same clients? Behav Sci Law 2005; 23:171–181.

21. Smith H, Sawyer DA, Way BB. Central New York Psychiatric Center: An approach to the treatment of co-occurring disorders in the New York State correctional mental health system. Behav Sci Law 2002; 20:523–534.

22. Sullivan CJ, McKendrick K, Sacks S, Banks S. Modified ther- apeutic community treatment for offenders with MICA disor- ders: Substance use outcomes. Am J Drug Alcohol Abuse 2007; 33:823–832.

23. Young DS. Co-occurring disorders among jail inmates: Bridging the treatment gap. J Soc Work Pract Addict 2003; 3:63–85.

24. Hasin D, Van Rossem R, McCloud S, Endicott J. Alcohol dependence and abuse diagnoses: Validity in community sam- ple heavy drinkers. Alcohol Clin Exp Res 1997; 21:213–219.

25. Schuckit MA, Danko GP, Smith TL, Bierut LJ, Bucholz KK, Edenberg HJ, Hesselbrock V, Kramer J, Nurnberger JI Jr, Trim R, Allen R, Kreikebaum S, Hinga B. The prognostic implica- tions of DSM-IV abuse criteria in drinking adolescents. Drug Alcohol Depend 2008; 97:94–104.

26. Schuckit MA, Smith TL, Danko GP, Bucholz KK, Reich T, Bierut L. Five-year clinical course associated with DSM-IV alcohol abuse or dependence in a large group of men and women. Am J Psychiatry 2001; 158:1084–1090.

27. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (4th ed.). Washington, DC: American Psychiatric Association, 1994.

28. Hoffmann NG, DeHart SS, Campbell TC. Dependence: Whether a disorder or a disease; it is not a “concept”. J Dual Diagn 2002; 8:45–56.

29. Hoffmann NG, Hoffmann TD. Construct validity for alcohol dependence as indicated by the SUDDS-IV. Subst Use Misuse 2003; 38:293–306.

30. Jones GY, Hoffmann NG. Alcohol dependence: International policy implications for prison populations. Subst Abuse Treat Prev Policy 2006; 1:33.

31. Kalaydjian A, Swendsen J, Chiu WT, Dierker L, Degenhardt L, Glantz M, Merikangas KR, Sampson N, Kessler R. Sociodemographic predictors of transitions across stages of alcohol use, disorders, and remission in the National Comorbidity Survey Replication. Compr Psychiatry 2009; 50:299–306.

32. Swendsen J, Anthony JC, Conway KP, Degenhardt L, Dierker L, Glantz M, He J, Kalaydjian A, Kessler RC, Sampson N, Merikangas KR. Improving targets for the prevention of drug use disorders: Sociodemographic predictors of transitions across drug use stages in the National Comorbidity Survey Replication. Prev Med 2008; 47:629–634.

33. Swendsen J, Conway KP, Degenhardt L, Dierker L, Glantz M, Jin R, Merikangas KR, Sampson N, Kessler RC. Socio- demographic risk factors for alcohol and drug dependence: The 10-year follow-up of the National Comorbidity Survey. Addiction 2009; 104:1346–1355.

34. Lo CC, Stephens RC. Drugs and prisoners: Treatment needs on entering prison. Am J Drug Alcohol Abuse 2000; 26:229–245.

35. Heffernan EB, Finn J, Saunders JB, Byrne G. Substance-use disorders and psychological distress among police arrestees. Med J Aust 2003; 179:408–411.

36. Sacks JY. Women with co-occurring substance use and mental disorders (COD) in the criminal justice system: A research review. Behav Sci Law 2004; 22:449–466.

37. Messina N, Burdon W, Prendergast M. Assessing the needs of women in institutional therapeutic communities. J Offender Rehabil 2003; 37:89–106.

38. Calhoun S, Messina N, Cartier J, Torres S. Implementing gender-responsive treatment for women in prison: Client and staff perspectives. Fed Probat 2010; 74:27–33.

39. Snell TL, Morton DC. Women in Prison. Office of Justice Programs, Bureau of Justice Statistics (NCJ Publication No. 145321). Washington, DC: US Department of Justice, 1994.

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