Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2018 Dec 1.
Published in final edited form as: Int J Offender Ther Comp Criminol. 2016 Feb 26;61(16):1819–1832. doi: 10.1177/0306624X16634702

Hazardously-Drinking Jailed Women: Post-Release Perceived Needs and Risk of Reincarceration

Yael Chatav Schonbrun 1,2, Jennifer E Johnson 3,2, Bradley J Anderson 1, Celeste Caviness 1, Michael D Stein 1,2
PMCID: PMC5517360  NIHMSID: NIHMS879004  PMID: 26920551

Abstract

Women who drink hazardously face a high risk for re-arrest and reincarceration when they return to their communities after a jail stay. This study is the first to examine the associations between women’s own reports of basic needs one month after jail release, and reincarceration (defined as spending at least one night in jail) during the next 5 months among unsentenced, female pretrial jail detainees who drink hazardously. Perceived needs for housing (AOR=3.63; p<.01), substance treatment services (AOR=2.65; p<.01), assistance/benefits (AOR=2.37; p<.05), and mental health counseling (AOR=2.07; p<.05) at one month after jail release were associated with reincarceration during the next 5 months for the 165 hazardously drinking jailed women in this study. These findings demonstrate that self-reported needs during the high-risk period immediately following jail release are associated with heightened odds of reincarceration among hazardously drinking jailed women.

Keywords: Jail, Alcohol, Women, Needs, Reincarceration

A 2009 World Health Organization Declaration and the United Nations Office on Drugs and Crime (UNODC) asserts that the unique needs of women and their health care are frequently overlooked in criminal justice policy. The neglect of women’s needs is notable given the more than one million women in the United States under the supervision of the criminal justice system, and more than 1,000,000 women that are admitted to U.S. jails each year (Minton & Golinelli, 2014). Although women constitute a smaller total percentage of inmates compared to men (Minton & Golinelli, 2014), the increase in female arrest rates has exceeded that of male arrest rates since the 1980’s and continues to surpass it by 1.5% (Guerino, Harrison, & Sabol, 2011).

The vast majority of women who are arrested spend time in jail (Sabol & Minton, 2008) rather than prison (Guerino et al., 2011). Unlike most prisoners, pretrial jail detainees are unsentenced and are incarcerated for shorter periods of time (often days). Therefore, jail often serves a “catch and release” function for many individuals at the highest risk for substance use, mental health, housing, employment, and other problems. Women in particular may encounter these risks. For example, compared to incarcerated men, incarcerated women are more likely to have substance use disorders, mental health disorders, to be incarcerated for alcohol and drug related offenses (Guerino et al., 2011), and to have been victims of physical and sexual assault (Messina, Burdon, Hagopian, & Prendergast, 2006). Compared to men who are currently incarcerated, currently incarcerated women also report more problems with housing, employment, income, and educational attainment (Langan & Pelissier, 2001; Messina et al., 2006; Pelissier, Camp, Gaes, Saylor, & Rhodes, 2003).

Such problems, of course, do not occur in a vacuum, but are intertwined with the complex set of circumstances that women encounter in their daily lives. Primary among these is difficulty meeting basic needs, such as housing, employment or medical and mental health treatment, which facilitate productive and prosocial lives (e.g., Luther, Reichert, Holloway, Roth, & Aalsma, 2011). Indeed, it is difficult to imagine how a woman with a history of hazardous drinking who is leaving jail might manage to maintain sobriety in the face of unstable housing, challenges finding employment, and difficulty in getting to treatments she may need to address substance and/or mental health problems. In order to effectively develop services for this population to be delivered during this high-risk period, then, it is critical to develop a clear understanding of the needs that women experience during the early weeks after release from jail and return to the community that may contribute to reincarceration. Despite an existing literature on female offenders’ basic needs, previous inquiries, particularly quantitative studies, have neglected to gather such data from the women themselves. Generating a more comprehensive picture of incarcerated women’s needs that is informed by the women themselves has the potential to more effectively guide policy and intervention development.

With high rates of both substance and mental health problems (e.g., Binswanger et al., 2010; Lynch et al., 2014), the need for re-entry programs for jailed women is substantial. Prior research suggests that unmet re-entry needs may complicate re-integration, possibly increasing risk for reincarceration. In a number of qualitative studies, women describe how the inability to meet one’s own basic substance use and mental health treatment needs interferes with successful community reintegration. (e.g., Luther et al., 2011; Pogorzelski, Wolff, Pan, & Blitz, 2005; van Olphen, Eliason, Freudenberg, & Barnes, 2009). Qualitative work with prison and aftercare providers similarly underscores the need for substance use and mental health aftercare resources for women, including continuous contact with providers during the community re-integration process (Johnson, Schonbrun, Peabody, et al., 2014). In a mixed methods study exploring treatment needs among 54 women with co-occurring substance use and depressive disorder following return to the community from prison, women identified a need for pre-release planning and post-release treatment to address mental health problems (Johnson et al., 2013). Using data gathered from offender case files, one study (Makarios, Steiner, & Travis, 2010) found that for women, greater number of treatment referrals, suggesting higher levels of need, was associated with higher likelihood of felony re-arrest. However, Makarios and colleagues’ study focused on prison not jail, did not include a measure of women’s own perceptions of their needs and the association between needs and reincarceration.

Finding stable housing is yet another challenge to life after jail, with one study reporting that 25% of women were uncertain about where they were going to live after their jail discharge (McLean, Robarge, & Sherman, 2006). In a qualitative study (Pogorzelski et al., 2005), 17 women recently discharged from jail described their challenges of re-entry as including the ability to secure housing. In fact, the most prevalent concerns reported were finding a means to earn an income and locate safe housing. In our earlier mixed methods study evaluating treatment needs in a prison sample, women similarly reported that lack of housing represented a challenge during the period of re-entry into the community after prison (Johnson et al., 2013). A greater number of residence changes has also associated with greater risk for re-arrest among women releasing from prison (Makarios et al., 2014). Therefore, evidence from both jail and prison studies highlight the importance of stable housing after incarceration.

Previous research also documents that difficulty in securing employment is associated with higher risk for reincarceration. Several qualitative studies conducted with prison samples highlight how women perceive challenges to finding and maintaining adequate legal employment as barriers to successful community re-integration (e.g., Harm & Phillips, 2001; Johnson et al., 2013; Johnson et al., 2014). Makarios, Steiner, and Travis (2010) found that offenders who were stably employed were less likely to recidivate than those who were unemployed, and offenders who experienced changes in employment were less likely to recidivate than those who were unemployed in the year after prison release for both men and women. Van der Knaap, Alberda, Oosterveld, and Born (2011) reported that education, work, and training were correlated with general reincarceration for men but not for women. Jurik (1983) found that the magnitude of the association between employment and reincarceration was smaller for women than for men and Martin and colleagues (Martin, Cloninger, & Guze, 1978) found a week correlation between employment and reincarceration. Thus, while qualitative findings generally point to the clear link between employment and reincarceration, quantitative findings are less clear. However, quantitative studies, to date, have focused on external markers of employment needs, rather than self-identified needs for employment. Data that directly capture jailed women’s perceptions of employment need and their likelihood of reincarceration would help to clarify the importance of employment needs in risk for reincarceration.

Lack of access to resources to meet various other needs ranging from medical services, prescriptions, insurance coverage, legal aid, transportation assistance, abuse services, HIV/STD services, and child care assistance, may also contribute to the revolving door of arrest and reincarceration. For example, low rates of insurance coverage, potentially impeding mental and/or medical service use, are experienced by women being released from incarceration periods (Watch, 2003), and could complicate successful reentry for this population. Women in one qualitative study described that involuntary disruptions in prescriptions were common (Sered & Norton-Hawk, 2013). Consideration of these types of basic needs, and women’s own perceptions of such needs during the critical period of community re-entry are an additional important area for continued investigation.

Studies evaluating how women view their own needs (i.e., their self-reported needs) shortly after release, and how their need perceptions are associated with reincarceration are largely limited to qualitative research. In contrast, research quantitatively linking unmet needs to reincarceration has predominantly been gathered using offender records or otherwise neglects the assessment of women’s own need perceptions. A reliance on external markers of needs limits the knowledge about what needs women, themselves, endorse during the challenging period of community re-entry, with potential implications of neglecting or minimizing the needs that jailed women most forcefully identify. Further, both qualitative and quantitative research largely neglect a focus on jailed populations, despite the higher prevalence of women being placed into jail versus prison, and the high rates of turnover (i.e., catch and release cycles) common in the jail system. Quantitative data explicitly capturing women’s self-reported needs may therefore provide greater insight into the role of basic needs and women’s insights into their own basic needs in the context of risk for reincarceration. In addition, in the research that has queried offenders directly about their needs perceptions (van der Knaap, Alberda, Oosterveld, & Born, 2012), timing of needs assessment has not been clarified; needs assessment conducted following release from jail may elucidate the needs that are most salient during the high-risk period directly following discharge from jail. In addressing these limitations, development of policies and interventions that are designed to aid incarcerated women who drink hazardously as they return to the community can more effectively be conducted.

Using data from a sample of hazardously drinking, unsentenced, jailed women, we examined women’s self-reported needs in the month after jail discharge and their effects on spending at least one additional night incarcerated (i.e., reincarceration)—in the following 5 months. We predicted that perceived needs, particularly in the domains of substance and mental health treatment, housing, and employment, would be associated with greater risk of reincarceration compared to those who endorsed no needs in these same domains.

Methods

Study Design

Data for this secondary analysis were drawn from a study evaluating a brief alcohol and HIV intervention for pretrial jailed women who reported hazardous drinking patterns (Stein, Caviness, Anderson, Hebert, & Clarke, 2010). Participants were recruited from 2004–2007 during the first three days of their incarceration. Nearly all jailed, unsentenced women detained in the women’s facility at the Rhode Island Department of Corrections during this period were approached by BS or BA level research assistant, who were on-site five days a week, and screened for eligibility. Participation was voluntary, and confidentiality was assured through a Federal Certificate of Confidentiality. Assessments were conducted in private rooms. Eligibility criteria included the following: (1) English speaking, (2) ability to provide contact information, (3) endorsement of risky heterosexual behavior (non-universal condom use in the last 90 days), (4) reports of hazardous alcohol consumption (i.e., consumption of 4 or more drinks at a time on 3 or more occasions in the prior 3 months, or a total score of 8 or greater on the Alcohol Use Disorders Identification Test (AUDIT; Saunders, Aasland, Babor, & de la Fuente, 1993).

Participants in this study completed the baseline assessment and were then randomized to one of two treatment conditions: assessment only and or an intervention consisting of 2 brief sessions of Motivational Interviewing (MI) for reducing alcohol use (one delivered during jail and the other a month after community re-entry). These sessions used the standard MI strategies for setting goals regarding making a change in alcohol use behavior and exploring strategies to deal with internal or external obstacles to achieving those goals. These techniques included exploring participants’ values, pros and cons of alcohol use, thoughts about cutting back/quitting, feedback on cost of alcohol and negative consequences, thoughts about usefulness of alcohol treatment, state of readiness to make changes, and generation of a change plan (see Stein et al., 2010). The present study utilized data collected at the 1-month follow-up assessment (which contained questions about perceived needs) and data collected through jail records throughout the 5-month follow-up period (which contained data on reincarceration).

Participants

A total of 1,415 women were screened throughout the recruitment period. A large number (n=1,133) were ineligible. Furthermore, 37 women who were initially screened refused to be fully assessed for eligibility (meaning that we do not know whether or not they would have been eligible), leaving the final study sample size of 245 women. Overall, 17% of women who were screened were eligible and enrolled, 3% refused eligibility assessments, and 80% were ineligible. Ineligibility resulted from the approximately 15% (n= 212) of women who had no HIV risk (i.e., did not endorse risky heterosexual behavior), the 33% (n= 467) who had no alcohol risk, the 24% (n= 340) who had no HIV or alcohol risk, and the 10% who were ruled out for various other reasons (e.g., were not English speaking) leaving a total of 245 women jailed at a correctional facility in the Northeast enrolled in the parent study. The one-month follow-up (when post-release needs were assessed) included the 67% (165/245) of the women who completed the one-month follow-up and were successfully followed for the 5-month follow-up period; it is this sample that was used in the current study’s analysis.

Measures

Needs Measure

Participants were presented at the 1-month assessment with a list of basic needs and were asked to indicate whether she had experienced each in the month since jail release. Individuals who did not endorse a given need were classified as having no need. Those who endorsed a need for a service were classified as having a perceived need in this domain. Services included in these analyses included: medical services, mental health counseling, substance treatment services, medication prescriptions, income or health care benefits assistance, job assistance, housing, legal aid, transportation assistance, domestic violence services, HIV/STD services, and child care assistance. Each need was coded 1 if endorsed and 0 otherwise.

Reincarceration

Reincarceration events (defined as spending at least one night in the Adult Correctional Institute) were assessed through daily checks of the intake report at the Adult Correction Institute throughout the follow-up period.

Substance Use

The Timeline Followback (TLFB; Sobell, Brown, Leo, & Sobell, 1996; Sobell, Sobell, Litten, & Allen, 1992; Stein et al., 2010) was used to assess alcohol binge episodes. Binge episodes during the follow-up period were defined as 4 or more drinks for women on a drinking day (Alcoholism, 2005).

Demographic Characteristics

Demographic characteristics assessed included age (participants were asked “How old are you?”), and race/ethnicity (participants were offered a selection of White/Black/Asian/American Indian/Other, and Hispanic/Non Hispanic).

Social Support

Four items assessing tangible support from the Medical Outcomes Study Social Support Survey (Sherbourne & Stewart, 1991) were used to gather information about social support. Response options on support items (e.g., “someone to help with daily chores if you were sick”) ranged from none of the time (0) to all of the time (4).

Statistical Analysis

We present descriptive statistics to summarize sample characteristics and the distribution of perceived needs in this cohort. T-tests and χ2-tests were used to compare persons lost to follow-up at 1-month to the analyzed sample. We used logistic regression to estimate the adjusted association between perceived needs (coded 1 if need, 0 otherwise) 1-month post release with subsequent reincarceration. We estimated separate models for each of the 12 needs. Control variables in all logistic regression models included age, race/ethnicity, frequency of binge drinking at baseline, social support, and intervention assignment.

Additionally, we estimated parallel models estimating the effect of cumulative number of perceived needs at 1-month with 5-month reincarceration. This model adjusted for the covariates listed above.

Results

Participant Characteristics

Women averaged 34.9 (± 8.6) years of age; 112 (67.9%) were non-Latino Caucasian, 39 (23.6%) were African-American, 12 (7.3%) were Latino, and 2 (1.2%) were of other racial or ethnic origins; race/ethnicity was dichotomized to contrast non-Latino Caucasians to all ethnic minorities in subsequent analyses. Prior to baseline, participants binge drank on an average of 43.4% (± 34.7) of the assessed TLFB days. Eighty (48.5%) and 85 (51.5%) persons were randomized to the control and active intervention arms, respectively.

The mean age of participants who completed the 1-month assessment was significantly (t = −2.06, p = .041) higher (34.9, ± 8.61) than for those who were lost to follow-up (32.4, ± 8.61). But these two groups did not differ significantly with respect to race/ethnicity (χ2 = 3.12, p = .077), educational attainment (t = 1.69, p = .093), frequency of heavy alcohol use (t = −0.44, p = .659), mean social support (t = −1.18, p = .240), or treatment assignment (χ2 = 0.02, p = .898).

Sixty-three (38.2%) participants were reincarcerated (i.e., spent one night or more in jail or prison) 1 or more times during follow-up. Intervention arms did not differ significantly with respect to reincarceration; 32 (40.0%) controls and 31 (36.5%) persons randomized to intervention were re-incarcerated during follow-up (χ2 = 0.22, p = .641). We also examined the association of intervention assignment with each perceived need; none of the associations were statistically significant.

Distribution of Perceived Needs

In Table 1, we examined how self-reports of having a need (versus having no need) were associated with subsequent reincarceration. We ordered the need categories in descending order based on frequency of perceived needs. Mental health counseling (57.3%) and medical services (54.9%) were the most frequently endorsed perceived needs. Almost half (49.7%) said they needed treatment for substance abuse, 45.7% said they needed assistance benefits, and 45.4% said they needed prescriptions. Transportation assistance was endorsed as a need by 36.2% of the participants. Job assistance, housing, and legal services were all perceived as a need by approximately 30% of the participants. HIV/STD services (11.0%), domestic violence services (9.8%), and childcare assistance (4.3%) were the least frequently cited needs. Only 10 (6.1%) participants did not endorse any perceived needs.

Table 1.

Perceived needs and their adjusted association with reincarceration

Need Valid na Perceived Need (Yes) Adj. OR
(95%CI)b 		(p =)
Mental Health Counseling 164 94 (57.3%) 2.07 (1.04; 4.13) .038
Medical Services 164 90 (54.9%) 0.92 (0.46; 1.82) .808
Substance treatment Services 165 82 (49.7%) 2.65 (1.35; 5.22) .005
Assistance/Benefits 162 74 (45.7%) 2.37 (1.21; 4.64) .011
Prescriptions 163 74 (45.4%) 0.95 (0.49; 1.83) .882
Transportation Assistance 163 59 (36.2%) 1.45 (0.74; 2.85) .279
Job Assistance 163 50 (30.7%) 2.23 (1.09; 4.57) .028
Housing 164 50 (30.5%) 3.63 (1.75; 7.51) .001
Legal Aid 163 48 (29.5%) 0.52 (0.25; 1.12) .094
HIV/STD Services 163 18 (11.0%) 1.92 (0.68; 5.39) .216
Abuse Services 163 16 (9.8%) 0.81 (0.27; 2.45) .704
Child Care Assistance 163 7 (4.3%) 0.30 (0.03; 2.72) .283
Open in a new tab
a

Valid n refers to the number of participants who responded to the specific item.

b

Separate regression models were estimated for each of the 12 needs. Each model included the need being evaluated. Control variables in each model included were adjusted for age, race/ethnicity (non-Latino Caucasian versus minority), educational attainment, percent days binge alcohol use, social support, and treatment condition. None of the control variables were associated significantly with reincarceration in any of the models; all p-values > .10.

Perceived Need and Likelihood of Reincarceration

Table 1 also provides the adjusted association between each area of perceived need and the likelihood of reincarceration. Control variables included age, race/ethnicity, educational attainment, frequency of binge drinking, social support, and intervention group assignment. None of the control variables (age, race/ethnicity, frequency of binge drinking, and intervention group assignment) were associated significantly (all p-values > .10) with reincarceration in any of the estimated logistic regression models; coefficients for these variables are not presented in the table.

The expected likelihood of reincarceration was associated positively and significantly with a perceived need for mental health counseling (AOR = 2.07, 95%CI 1.04; 4.13, p = .038), substance abuse treatment (AOR = 2.65, 95%CI 1.35; 5.22, p = .005), a perceived need for assistance benefits (AOR = 2.37, 95%CI 1.21; 4.64, p = .011), a need for job assistance (AOR = 2.23, 95%CI 1.09; 4.57, p = .028), and a perceived need for housing (AOR = 3.63, 95%CI 1.75; 7.51, p = .001). None of the other areas of potential need evaluated in Table 1 were associated significantly with the likelihood of reincarceration during follow-up.

Examining the effect of cumulative needs, with each additional perceived need at 1-month, the expected odds of reincarceration increased by a factor of 1.31 (95%CI 1.11; 1.54; p = .001).

Discussion

This study examines the associations between one-month, post-release perceived needs and reincarceration during the next 5 months among jailed women with a history of hazardous alcohol use. Women who endorsed a need for mental health counseling, substance treatment services, income assistance and health benefits, job assistance, and housing were significantly more likely to spend at least one night in jail or prison over the next 5 months, compared to women who did not endorse these needs. Further, there was a cumulative effect of needs such that a greater number of perceived needs was associated with increased risk for reincarceration. It should be noted that needs and short-term (i.e., 5-month) reincarceration were evaluated, and that long-term reincarceration may differ from results found in this brief window of observation. Nevertheless, the emergent pattern of findings points to an impact of self-reported needs on likelihood of reincarceration.

With regard to frequency of needs endorsed, women most often endorsed treatment needs, including medical, mental health, and substance abuse needs, with more than half of all women perceiving need for each of these services, as might be expected in our sample of women with a history of hazardous alcohol use. These findings reflect previous qualitative research reflecting how common such needs are (e.g. Johnson et al., 2013; Pogorzelski et al., 2005). Not only were perceived treatment needs common, but both mental health and substance treatment needs were also associated with subsequent reincarceration in our sample. It is clear that hazardously drinking women perceive their own needs for treatment, and that this needs perception links to poorer outcomes. These associations are consistent with prior research (Lynch et al., 2014; McPhail, Falvo, & Burker, 2012; Nowotny, Belknap, Lynch, & DeHart, 2014; Scott & Dennis, 2012) and suggest that women who are unable to access relevant treatment services early after release are less likely than those without such needs to successfully remain in their communities. It may also be that women who identify a need for treatment may be more likely to partake and respond to treatment, though this question needs to be explored in future investigations.

Petersilia (2005) points out that offenders face other serious obstacles after release, particularly in the domains of employment and income. Employment is associated with having access to a secure income, as well as insurance benefits, making these concerns of special consequence, particularly for women with the immediate treatment needs discussed above. While data on income and job security among incarcerated populations are limited, earlier survey data demonstrate that approximately 60% of inmates earned less than $1,000 per month prior to their arrest (James, 2004). In a California-based study, results indicated that jailed populations are also, in large part, uninsured, with 90% of individuals entering jail reporting that they have no health insurance (Wang et al., 2008). Women in our sample were likely to report a perceived need for employment, income and health benefits assistance, and these needs were associated with heightened odds of reincarceration, suggesting that experience of these needs places individuals at higher risk for reincarceration. It would be valuable to investigate the impact of the recent Affordable Care Act in increasing access to health insurance for incarcerated populations (Gates, Artiga, & Rudowitz, 2014), and examine how changes in access might influence risk for reincarceration. More generally, future investigations should evaluate the whether vocational interventions might mitigate risk for reincarceration.

Our findings also support previous research documenting a link between housing needs and short-term risk for reincarceration. While some prior research (van der Knapp et al., 2012) documents that reincarceration is associated with housing needs for men but not for women, our examination suggests that, in a shorter window of follow-up, hazardously drinking women with unmet housing needs have greater risk for reincarceration than heavy drinking women with no housing needs. In contrast to van der Knap and colleagues’ study, our study involved a shorter 5-month follow-up window (versus 2 years) and participants from jail (versus prison) suggesting that the association between unmet housing need and reincarceration is significant even in the immediate period following an incarceration period. This finding also plausibly fits with prior qualitative research (e.g., McLean et al., 2006; Pogorzelski et al., 2005; Johnson et al., 2013) suggesting that women rank housing among their most important needs following an incarceration period.

While the present study affords a valuable examination into the perceived needs of hazardously drinking jailed women during the tumultuous period of community reintegration, there are a number of limitations that should be noted. First, the study sample was limited to women incarcerated at a single jail in the Northeast, and who described patterns of hazardous drinking. While we note that the hazardous drinking eligibility criteria limits generalizability, it may also be worth pointing out that about two-thirds of women in jail or state prison have alcohol and/or drug use disorders (Binswanger et al., 2010; Guerino et al., 2011; James & Glaze, 2006; Jordan, Schlenger, Fairbank, & Caddell, 1996; Lynch et al., 2014; Teplin, Abram, & McClelland, 1996) and that present findings may be pertinent to many incarcerated women. Also, because the needs assessment occurred 1 month following jail release, some women from the original intervention trial sample who were lost to follow-up may have been reincarcerated before this needs assessment was conducted. So, while the assessment of perceived post-release needs during the post-release period is a strength of the study, this design may have excluded some of the highest-risk women. Third, we were unable to verify whether women who did not show up on the correctional facility census were actually in the community. Fourth, substantial variation likely exists in how individuals prioritize their needs and we did not ask participant to name their “greatest” need or needs. Future studies may also benefit from comparing met versus unmet needs. Perception of need also varies significantly over time (Wiersma, van den Brink, Wolters, McCabe, Bullenkamp, et al., 2009), suggesting that timing of needs assessments may be particularly important. Assessing needs shortly after jail discharge (rather than during jail detention) may therefore more accurately reflect women’s actual needs and challenges as they return to the community, but we were unable to evaluate how needs identified at the 1-month follow-up changed over the course of the 5-month follow-up period. Future research providing multiple assessments of needs for a longer follow-up period would provide greater insight into the nature of perceived needs and associated outcomes over time.

Women living in the community after release from jail who identify their own needs for mental health counseling, substance treatment services, income assistance and benefits, job assistance, and housing are more likely to return to jail or prison than women without these needs. Policies that support, as well as interventions that facilitate access, to these treatment services during the initial re-entry period may be particularly critical to avoiding reincarceration in the next half-year. Indeed, previous research evaluating treatments for female offenders suggests that treatment services do reduce risk for reincarceration (e.g., Hall, Prendergast, Wellisch, Patten, & Cao, 2004; Sacks, McKendrick, & Hamilton, 2012; Witkiewitz et al., 2014). As targeting these basic needs was identified as being critical for the women, themselves, a focus on these specific basic needs may have the potential to be particularly influential in implementation, particularly because women who perceive a need for treatment services may be most willing to take part and more likely to benefit from treatment; continued research is needed to support this possibility. For example, the linkage of women completing brief jail stays to community-based twelve-step programs represents one potential method to facilitate substance treatment during the chaotic period of community re-entry (Johnson, Schonbrun, & Stein, 2014). Evaluation of novel methods to connect women, in an ongoing manner, to a wide range of needed services, is worthy of testing as a means to change the trajectories of lives filled with new hopes and old challenges.

Acknowledgments

This work was supported by the NIH grants AA 014495 and AA 17815.

References

  1. Alcoholism NI oAAa. Helping Patients Who Drink Too Much: A Clinician’s Guide. 2005 Retrieved from Rockville MD: [Google Scholar]
  2. Binswanger IA, Merrill JO, Krueger PM, White MC, Booth RE, Elmore JG. Gender differences in chronic medical, psychiatric, and substance-dependence disorders among jail inmates. American Journal of Public Health. 2010;100(3):476–482. doi: 10.2105/AJPH.2008.149591. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Gates A, Artiga S, Rudowitz R. Health coverage and care for the adult criminal justice-involved population. 2014 Retrieved from http://kff.org/uninsured/issue-brief/health-coverage-and-care-for-the-adult-criminal-justice-involved-population/
  4. Guerino P, Harrison PM, Sabol WJ. Prisoners in 2010 2011 [Google Scholar]
  5. Hall EA, Prendergast ML, Wellisch J, Patten M, Cao Y. Treating drug-abusing women prisoners: An outcomes evaluation of the forever free program. The Prison Journal. 2004;84(1):81–105. doi: 10.1177/0032885503262456. [DOI] [Google Scholar]
  6. James D. Profile of jail inmates, 2002. Washington, DC: Bureau of Justice Statistics; 2004. Retrieved from http://www.bjs.gov/content/pub/pdf/pji02.pdf. [Google Scholar]
  7. James D, Glaze LE. (Bureau of Justice Statistics Special Report).Mental health problems of prison and jail inmates. 2006 (NCJ 213600) [Google Scholar]
  8. Johnson JE, Schonbrun YC, Nargiso JE, Kuo CC, Shefner RT, Williams CA, Zlotnick C. ‘I know if I drink I won’t feel anything’: Substance use relapse among depressed women leaving prison. International Journal of Prisoner Health. 2013;9(4):169–186. doi: 10.1108/IJPH-02-2013-0009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Johnson JE, Schonbrun YC, Peabody ME, Shefner RT, Fernandes KM, Rosen RK, Zlotnick C. Provider experiences with prison care and aftercare for women with co-occurring mental health and substance use disorders: Treatment, resource, and systems integration challenges. The Journal of Behavioral Health Services & Research. 2014 doi: 10.1007/s11414-014-9397-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Johnson JE, Schonbrun YC, Stein MD. Pilot test of 12-step linkage for alcohol-abusing women in leaving jail. Substance Abuse. 2014;35(1):7–11. doi: 10.1080/08897077.2013.794760. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Jordan BK, Schlenger WE, Fairbank JA, Caddell JM. Prevalence of psychiatric disorders among incarcerated women: Convicted felons entering prison. Archives of General Psychiatry. 1996;53(6):513–519. doi: 10.1001/archpsyc.1996.01830060057008. [DOI] [PubMed] [Google Scholar]
  12. Jurik NC. The economics of female recidivism: A study of TARP women ex-offenders. Criminology: An Interdisciplinary Journal. 1983;21(4):603–622. doi: 10.1111/j.1745-9125.1983.tb00282.x. [DOI] [Google Scholar]
  13. Langan NP, Pelissier BMM. Gender differences among prisoners in drug treatment. Journal of Substance Abuse. 2001;13(3):291–301. doi: 10.1016/S0899-3289(01)00083-9. [DOI] [PubMed] [Google Scholar]
  14. Luther JB, Reichert ES, Holloway ED, Roth AM, Aalsma MC. An exploration of community reentry needs and services for prisoners: A focus on care to limit return to high-risk behavior. AIDS Patient Care and STDs. 2011;25(8):475–481. doi: 10.1089/apc.2010.0372. [DOI] [PubMed] [Google Scholar]
  15. Lynch SM, DeHart DD, Belknap JE, Green BL, Dass-Brailsford P, Johnson KA, Whalley E. A multisite study of the prevalence of serious mental illness, PTSD, and substance use disorders of women in jail. Psychiatric Services. 2014;65(5):670–674. doi: 10.1176/appi.ps.201300172. [DOI] [PubMed] [Google Scholar]
  16. Makarios M, Steiner B, Travis LF., III Examining the predictors of recidivism among men and women released from prison in Ohio. Criminal Justice and Behavior. 2010;37(12):1377–1391. doi: 10.1177/0093854810382876. [DOI] [Google Scholar]
  17. Martin RL, Cloninger RC, Guze SB. Female criminality and the prediction of recidivism: A prospective six-year follow-up. Archives of General Psychiatry. 1978;35(2):207–214. doi: 10.1001/archpsyc.1978.01770260085010. [DOI] [PubMed] [Google Scholar]
  18. McPhail ME, Falvo DR, Burker EJ. Psychiatric disorders in incarcerated women: Treatment and rehabilitation needs for successful community reentry. Journal of Applied Rehabilitation Counseling. 2012;43(1):19–26. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=2012-08496-003&site=ehost-live. [Google Scholar]
  19. Messina N, Burdon W, Hagopian G, Prendergast M. Predictors of prison-based treatment outcomes: A comparison of men and women participants. The American Journal of Drug and Alcohol Abuse. 2006;32(1):7–28. doi: 10.1080/00952990500328463. [DOI] [PubMed] [Google Scholar]
  20. Minton TD, Golinelli D. Jail inmates at midyear 2013. US Department of Justice; 2014. [Google Scholar]
  21. Nowotny KM, Belknap J, Lynch S, DeHart D. Risk profile and treatment needs of women in jail with co-occurring serious mental illness and substance use disorders. Women & Health. 2014;54(8):781–795. doi: 10.1080/03630242.2014.932892. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Pelissier BMM, Camp SD, Gaes GG, Saylor WG, Rhodes W. Gender differences in outcomes from prison-based residential treatment. Journal of Substance Abuse Treatment. 2003;24(2):149–160. doi: 10.1016/S0740-5472(02)00353-7. [DOI] [PubMed] [Google Scholar]
  23. Petersilia J. Hard Time Ex-Offenders Returning Home After Prision. (cover story) Corrections Today. 2005;67(2):66–155. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=sih&AN=16730181&site=ehost-live. [Google Scholar]
  24. Pogorzelski W, Wolff N, Pan KY, Blitz CL. Behavioral Health Problems, Ex-Offender Reentry Policies, and the ‘Second Chance Act’. American Journal of Public Health. 2005;95(10):1718–1724. doi: 10.2105/AJPH.2005.065805. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Sabol WJ, Minton TD. Jail Inmates at Midyear 2007 2008 [Google Scholar]
  26. Sacks JY, McKendrick K, Hamilton Z. A randomized clinical trial of a therapeutic community treatment for female inmates: Outcomes at 6 and 12 months after prison release. Journal of Addictive Diseases. 2012;31(3):258–269. doi: 10.1080/10550887.2012.694601. [DOI] [PubMed] [Google Scholar]
  27. Saunders JB, Aasland OG, Babor TF, de la Fuente JR. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption: II. Addiction. 1993;88(6):791–804. doi: 10.1111/j.1360-0443.1993.tb02093.x. Retrieved from. http://search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=1993-43780-001&site=ehost-live. [DOI] [PubMed] [Google Scholar]
  28. Scott CK, Dennis ML. The first 90 days following release from jail: Findings from the Recovery Management Checkups for Women Offenders (RMCWO) experiment. Drug and Alcohol Dependence. 2012;125(1–2):110–118. doi: 10.1016/j.drugalcdep.2012.03.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Sered S, Norton-Hawk M. Criminalized women and the health care system: The case for continuity of services. Journal of Correctional Health Care. 2013;19(3):164–177. doi: 10.1177/1078345813486323. [DOI] [PubMed] [Google Scholar]
  30. Sherbourne C, Stewart A. The MOS social support survey. Social Science and Medicine. 1991;32(6):705–714. doi: 10.1016/0277-9536(91)90150-b. [DOI] [PubMed] [Google Scholar]
  31. Sobell LC, Brown J, Leo GI, Sobell MB. The reliability of the alcohol Timeline Followback when administered by telephone and by computer. Drug and Alcohol Dependence. 1996;42(1):49–54. doi: 10.1016/0376-8716(96)01263-x. [DOI] [PubMed] [Google Scholar]
  32. Sobell LC, Sobell MB, Litten RZ, Allen JP. Measuring alcohol consumption: Psychosocial and biochemical methods. Totowa, NJ US: Humana Press; 1992. Timeline follow-back: A technique for assessing self-reported alcohol consumption; pp. 41–72. [Google Scholar]
  33. Stein MD, Caviness CM, Anderson BJ, Hebert M, Clarke JG. A brief alcohol intervention for hazardously drinking incarcerated women. Addiction. 2010;105:466–475. doi: 10.1111/j.1360-0443.2009.02813.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Teplin LA, Abram KM, McClelland GM. Prevalence of psychiatric disorders among incarcerated women: Pretrial jail detainees. Archives of General Psychiatry. 1996;53(6):505–512. doi: 10.1001/archpsyc.1996.01830060047007. [DOI] [PubMed] [Google Scholar]
  35. van der Knaap LM, Alberda DL, Oosterveld P, Born MP. The predictive validity of criminogenic needs for male and female offenders: Comparing the relative impact of needs in predicting recidivism. Law and Human Behavior. 2012;36(5):413–422. doi: 10.1037/h0093932. [DOI] [PubMed] [Google Scholar]
  36. van Olphen J, Eliason MJ, Freudenberg N, Barnes M. Nowhere to go: How stigma limits the options of female drug users after release from jail. Substance Abuse Treatment, Prevention, and Policy, 4. 2009 doi: 10.1186/1747-597X-4-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Wang E, White M, Jamison R, Goldenson J, Estes M, Tulsky J. Discharge planning and continuity of health care: findings from the San Francisco County Jail. American Journal of Public Health. 2008;98(12):2182–2184. doi: 10.2105/AJPH.2007.119669. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Watch HR. Ill-equipped: U.S. prisons and offenders wth mental illness. Washington, DC: 2003. [Google Scholar]
  39. Witkiewitz K, Warner K, Sully B, Barricks A, Stauffer C, Thompson BL, Luoma JB. Randomized trial comparing mindfulness-based relapse prevention with relapse prevention for women offenders at a residential addiction treatment center. Substance Use & Misuse. 2014;49(5):536–546. doi: 10.3109/10826084.2013.856922. [DOI] [PubMed] [Google Scholar]

RESOURCES