Journal of Substance Abuse Treatment 28 (2005) 121 – 133
Article
Outcomes for women with co-occurring disorders and trauma: Program and person-level effects Joseph P. Morrissey, (Ph.D.)a,b,*, Alan R. Ellis, (MSW)b, Margaret Gatz, (Ph.D.)c, Hortensia Amaro, (Ph.D.)d, Beth Glover Reed, (Ph.D.)e, Andrea Savage, (Ph.D.)f, Norma Finkelstein, (Ph.D.)g, Ruta Mazelis, (B.S.)h, Vivian Brown, (Ph.D.)i, Elizabeth W. Jackson, (Ph.D.)b, and Steven Banks, (Ph.D.) j a
Department of Health Policy and Administration, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA b Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA c Department of Psychology, University of Southern California, Los Angeles, CA 90089, USA d Bouve´ College of Health Sciences, Northeastern University, Boston, MA 02115, USA e Social Work and Women’s Studies, University of Michigan, Ann Arbor, MI 48109, USA f Doctoral Program in Social Welfare, Graduate Center, City University of New York; and Hunter College School of Social Work, New York, NY 10021, USA g Institute for Health and Recovery, Cambridge, MA 02139, USA h The Cutting Edge, Carrollton, OH 44615, USA i PROTOTYPES Centers for Innovation in Health, Mental Health, and Social Services, Culver City, CA 90230, USA j Policy Research Associates, Inc., Delmar, NY 12054, USA Received 11 March 2004; received in revised form 8 July 2004; accepted 19 August 2004
Abstract Six-month outcomes are evaluated from a 9-site quasi-experimental study of women with mental health and substance use disorders who have experienced physical or sexual abuse who enrolled in either comprehensive, integrated, trauma-informed, and consumer/ survivor/recovering person-involved services (N = 1023) or usual care (N = 983). Mental health, post-traumatic stress symptoms, and substance use outcomes are assessed with multilevel regression models, controlling for program and personal characteristics. Person-level variables predict outcomes independent of intervention condition and, to a small extent, moderate intervention and program effects. In sites where the intervention condition provided more integrated counseling than the comparison condition, there are increased effects on mental health and substance use outcomes; these effects are partially mediated by person-level variables. These results encourage further research to identify the longer-term effects of integrated counseling for women with co-occurring disorders and trauma histories. D 2005 Elsevier Inc. All rights reserved. Keywords: Women; Co-occurring disorders; Trauma; Intervention outcomes; Multi-level models
1. Introduction
* Corresponding author. Cecil G. Sheps, Center for Health Services Research, University of North Carolina at Chapel Hill, CB 7590, 725 Airport Road, Chapel Hill, NC 27599-7590, USA. Tel.: +1 919 966 5829; fax: +1 919 966 1384. E-mail address:
[email protected] (J.P. Morrissey). 0740-5472/05/$ – see front matter D 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.jsat.2004.08.012
Recent research indicates that 55% to 99% of women with co-occurring mental health and substance use disorders also have histories of trauma (Jennings, 1997; Miller, 1994; Najavits, Weiss, & Liese, 1996). These women, with a range of multiple and complex needs, often are not well served by the existing array of discrete and fragmented services found
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in most American communities (Grella, 1996, 2003; Harris, 1994; Young & Grella, 1998). The Substance Abuse and Mental Health Services Administration sponsored the Women, Co-Occurring Disorders, and Violence Study (WCDVS), a multi-site program developed to demonstrate more effective service interventions for these women. A total of 2,729 women enrolled in the WCDVS at nine sites in a nonrandom, quasi-experimental comparison group study for women with histories of mental health and substance use disorders who have experienced interpersonal violence (McHugo et al., 2005). In the intervention condition women received a trauma-specific manualized intervention in addition to existing treatment-as-usual services. In the comparison condition women received treatment-as-usual services only. The primary goals of the WCDVS were to generate empirical knowledge on developing integrated service approaches and to evaluate the effectiveness of these approaches for women who have traditionally been bhigh-endQ users of services (Becker et al., in press; Domino, Morrissey, Nadlicki-Patterson, & Chung, 2005). Here, we are concerned with whether women benefited from these services and whether individual characteristics interact with the intervention and other programlevel variables. In an earlier meta-analysis of WCDVS results at 6 months, Cocozza et al. (2005) in this issue report small positive and significant overall effects on drug use problem severity ( p = 0.02) and post-traumatic stress symptoms ( p = 0.02); there was no effect on alcohol use problem severity, and the effect on mental health status was only marginally significant ( p = 0.06). However, these results were not uniform across the nine participating sites. The five sites which as a group had positive effects on mental health status ( p = 0.01), alcohol use problem severity ( p = 0.0001), and drug use problem severity ( p = 0.0001) were those in which womenTs reports of receiving integrated counseling were greater in the intervention condition than in the usual care condition; the other four sites either had no effects or negative effects. Post-traumatic stress symptom effects were basically the same in these two groups of sites. These earlier analyses controlled only for baseline differences in scores on the outcome variables. They did not take into account the extent to which outcomes vary by person-level characteristics of the women at different sites who participated in the study. The report by McHugo et al. (2005) in this issue shows that there are a number of statistically significant differences between intervention and comparison subjects at baseline. Consequently, itTs unclear whether the reported results are truly intervention or integrated counseling effects as opposed to effects of selection bias that can be more parsimoniously explained at the person level. This problem is one of the limitations of the quasi-experimental, non-randomized groups design used in the WCDVS, i.e., personal characteristics of study participants may be related to the outcomes and women with these characteristics might not be equally distributed in the
intervention and comparison conditions across sites. In other words, covariates need to be identified and statistically controlled for in the analyses so we can avoid the error of saying that the effects are due to the WCDVS interventions when they may be due to these person-level covariates. Recent studies in many types of settings continue to confirm strong associations between substance use, cooccurring mental disorders, and trauma symptoms or experiences, as well as a host of other life problems, especially among women (Back, Sonne, Killeen, Dansky, & Brady, 2003; Duncan, Saunders, Kilpatrick, Hanson, & Resnick, 1996; El-Bassel et al., 2003; Gearon & Bellack, 1999; Ouimette, Kimerling, Shaw, & Moos, 2000; Palacios, Urmann, Newell, & Hamilton, 1999). However, much less is known about what is related to the outcomes of services for women dealing simultaneously with mental health, substance use, and trauma problems. The limited but growing literature on outcomes in these areas suggests that both personal characteristics of clients (Acharyya & Zhang, 2003; Carscaddon, 1990; Comfort, Sockloff, Loverro, & Kaltenback, 2003; Haller, Miles, & Dawson, 2003; Harvey, Rawson, & Obert, 1994; McLellan et al., 1994) and characteristics of treatment programs (D’Aunno & Vaughn, 1995; Friedmann, Alexander, & D’Aunno, 1999; Magura, Nwakeze, & Demsky, 1998; McCaughrin & Howard, 1996) influence treatment outcomes. The evidence for person-level effects is illustrated in a substance abuse study by Comfort et al. (2003) identifying several risk and protective factors for women in residential and outpatient treatment including social support, daily stressors, life satisfaction, partner abuse, substance abuse by self and significant others, psychiatric history, chronic medical conditions, childbirth history, childcare responsibilities, and treatment engagement. The relevance of program-level effects is illustrated in the work of Friedmann and colleagues (Friedmann et al., 1999; Friedmann, Lemon, Stein, & D’Aunno, 2003) who find that organizational variables such as ownership and managed care involvement affect access to and receipt of substance abuse treatment services (also see DTAunno & Vaughn, 1995; McCaughrin & Howard, 1996). However, all of these studies are based on provider reports of client experiences. Absent data on individual client outcomes, it is difficult to draw any clear conclusions from these studies about the role and relative importance of program-level and person-level variables as predictors of service outcomes, especially as regards women with co-occurring disorders who have experienced physical or sexual abuse. This gap exists in the broader substance abuse treatment literature as well, where there is a great need for further research on multilevel models of the individual and joint effects of person and program variables as determinants of client outcomes. Here, we respond to this need by extending the metaanalyses reported by Cocozza et al. (2005). Analyses focus on the relative contributions of integrated counseling— the program-level element found in that report to be
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important—and a variety of person-level variables in accounting for womenTs mental health status, substance use, and post-traumatic stress symptom outcomes in the WCDVS, one of the largest and geographically diverse comparison group studies yet undertaken in this area. Specifically, we address four research questions that seek to determine for each of the four outcomes whether the program-level effects reported by Cocozza and colleagues (2005) hold up when person-level covariates are examined and whether the findings are clinically meaningful: 1. Independent of intervention condition, do person-level characteristics account for variation in womenTs service outcomes at 6 months? 2. Is the intervention effect at 6 months mediated or moderated by person-level variables? 3. Is the program-level integrated counseling contrast at 6 months mediated or moderated by person-level variables? 4. Are the results clinically meaningful?
2. Materials and methods A detailed description of the research methods employed in the WCDVS is available elsewhere in this issue (McHugo et al., 2005). Here, we focus on the analysis strategies used to identify person-level variables that might account for or moderate the 6-month intervention effects reported by Cocozza et al. (2005). 2.1. Sample Of 2,729 subjects who completed baseline interviews, 2,101 (77%) also completed an interview approximately 6 months after baseline. Of the latter number, 95 (4.5%) are excluded from the current analysis because the 6-month interview did not occur within 12 weeks of the target date, leaving 2,006 women in the current analysis sample. Logistic regression (McHugo et al., 2005) detected only a few small differences, indicating that the likelihood of being interviewed within this 12-week window was greater with increasing age (OR = 1.017, p b 0.05), a larger number of lifetime mental hospitalizations (OR = 1.047, p b 0.05), and a lack of current stressors other than interpersonal abuse1 (OR = 1.073, p b 0.05). Across sites, the proportion of women who completed the 6-month interview within 1 Current Exposure to Other Stressors is an index of current exposure to traumatic events other than interpersonal abuse. The composite measure was created from women’s responses to the revised LSC-R (McHugo, Caspi, Kammerer, Mazelis, Jackson, Russell, Clark, Liebschutz, & Kimerling, in press). Four other composite measures referenced in this paper were developed from the same instrument and are also described by McHugo and colleagues: Current Exposure to Interpersonal Abuse, Frequency of Childhood Abuse, Lifetime Exposure to Stressful Events, and Lifetime Frequency of Interpersonal Abuse.
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12 weeks of the target date varied from 60% to 94%; m2(8) = 98.9, p b 0.0001. However, this proportion does not vary by intervention vs. comparison condition (72% vs. 75% respectively, m2 = 2.2, p = 0.137) or by high vs. low integrated counseling contrast (72% vs. 75% respectively, m2 = 1.5, p = 0.225). The mean age of women in the analysis sample was 36. They came from a diverse mix of racial and ethnic backgrounds (17% Hispanic, 49% White non-Hispanic, 26% Black non-Hispanic, 7% other non-Hispanic). About half (50%) had a high school degree (25% of these had a GED) and about a third (38%) were married or partnered (29% never married). The large majority (70%) experienced homelessness at some time in their lives and half (50%) reported a current serious illness or physical disability. As a group, these women reported long-term mental health, substance use, and trauma experiences as indicated by first mental health problem by age 12 (50%), regular use of alcohol to intoxication for at least 5 years (50%), regular use of drugs for at least 10 years (50%), and physical abuse in adulthood (85%). They were enrolled in the study through local projects in California (two sites), Colorado, Florida, Massachusetts (three sites), New York City, and Washington, DC. Table 1 describes the analysis sample using the covariates included in the present analysis. Overall, the women in the intervention condition (N = 1023) and comparison condition (N = 983) were very similar with respect to most of these variables. The only differences significant at p b 0.05 are that the intervention condition had a higher proportion of women currently receiving court-ordered substance abuse or mental health treatment (38.7% vs. 29.6%, p b 0.0001) and a lower proportion of women who received medication (here, predominantly methadone) for substance abuse treatment in the 3 months prior to baseline (15.5% vs. 20.7%, p b 0.01). Data collection procedures were approved by an Institutional Review Board at each site and at the two main components of the Coordinating Center (Policy Research Associates, Inc. and the University of North Carolina at Chapel Hill). All subjects provided written informed consent to participate in the research. 2.2. Outcome measures The effectiveness of the interventions in the WCDVS was assessed in three domains with four measures, as follow: Drug use problem severity and alcohol use problem severity were both assessed using the Addiction Severity Index (ASI; McLellan, Luborsky, Woody, & O’Brien, 1980). The Drug Composite Score (ASI-D) and Alcohol Composite Score (ASI-A)2 were calculated to measure problem severity during the prior 30 days. Higher scores on 2
The ASI-A score was modified slightly in consultation with its author, but is scored on the original scale. For details, see McHugo et al. (2005).
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Table 1 Person-level characteristics of WCDVS sample at baseline Variable Demographic and general Age Current court-ordered mental health or substance abuse treatment Homeless, ever Number of barriers to receiving services Serious physical illness or disability Substance abuse (SA) Alcohol use problem severity (ASI-A) baseline score Drug use problem severity (ASI-D) baseline score Cigarettes smoked per day Received SA medication (e.g., methadone) in past 3 months Years used alcohol to intoxication Years used drugs Mental health (MH) Age at first MH admissiona Age when first MH problem began Mental health status (GSI) baseline score Number of voluntary MH admissions Received MH medication in past 3 months Received MH treatment 2 times or for N6 months, ever Received MH treatment, ever Receiving MH treatment currently Trauma Admitted to hospital or emergency room in past 3 months: physical, medical, or injury reason Admitted to hospital or emergency room in past 3 months: violence, abuse, or trauma reason Current exposure to interpersonal abuse Current exposure to other stressful events Emotional abuse or neglect in childhood Frequency of childhood abuse Lifetime exposure to stressful events Lifetime frequency of interpersonal abuse Physical abuse in adulthood Physical abuse in childhood Post-traumatic stress symptom (PSS) baseline score Sexual abuse in adulthood Sexual abuse in childhood Stalked or threatened with death or harm, ever
% or M (SD) 36.28 (8.72) 34.3% 70.4% 0.77 (1.28) 49.6% 0.20 (0.30) 0.16 (0.15) 12.30 (10.66) 18.1%
Scale (Foa, Cashman, Jaycox, & Perry, 1997). The 17-item PSS was developed to assess the severity of Posttraumatic Stress Disorder (PTSD) symptoms. Respondents were asked to indicate how often in the past month (on a scale of 0 [not at all or only once] to 3 [5 or more times or almost always]) theyTve experienced a list of problems sometimes experienced after a traumatic event. Higher scores on the PSS indicate more severe PTSD symptoms (mild = 1–10, moderate = 11–20, moderate to severe = 21–35, severe = 36–51; Foa, 1995, p. 46). At baseline, the average PSS score was 23.7 (Table 1) indicating a moderate-to-severe level of symptom severity. 2.3. Analyses
8.34 (9.10) 11.75 (8.71) 0.88 (1.04) 13.83 (9.06) 1.35 (0.77) 1.21 (3.68) 57.2% 80.8% 89.0% 66.5% 36.9% 3.5% 1.09 (1.47) 3.03 (1.96) 72.7% 3.64 (2.98) 16.22 (4.50) 15.61 (7.27) 85.4% 60.5% 23.71 (11.87) 60.2% 61.9% 71.7%
a
To include subjects reporting no admissions, the following categories are used: 0 = never, 1 = ages 26+, 2 = age 16–25, 3 = age 1–15.
either index signify greater substance use problem severity. At baseline, average scores were 0.20 on ASI-D and 0.16 on ASI-A (Table 1) indicating a moderate level of severity. Mental health status was assessed using the global severity index (GSI) of the Brief Symptom Inventory (Derogatis, 1993). The Brief Symptom Inventory is a 53-item self-report scale that measures nine symptom dimensions. The respondent is asked how much a problem has distressed her in the past 7 days (ranging from 0–4, not at all to extremely). The GSI is a mean severity measure with higher scores indicating more severe symptoms. At baseline, the average GSI raw score was 1.35 (Table 1; T-score = 69) indicating a moderately elevated level of symptom severity. Trauma symptomatology was assessed by the symptom severity scale (PSS) of the Post-traumatic Stress Diagnostic
2.3.1. Overview An intent-to-treat approach was followed throughout the analyses with the data for participants retained in the condition in which they were enrolled regardless of their subsequent participation in treatment or other service use. Hierarchical linear modeling (HLM) was used to predict 6-month outcomes using person-level variables, intervention condition, and level of integrated counseling contrast.3 All HLM models employed three levels (time at level 1, person at level 2, and site at level 3). Discrete measures were used for Time (0 = baseline, 1 = 6 months), Intervention (0 = no, 1 = yes), and High Contrast (0 = no, 1 = yes). The final models had the following characteristics:
! The level 1 model was a function of Time plus an error term; ! The level 2 model was a function of Covariates, Intervention, and Covariate Intervention interaction terms, with an error term (random effect) for intercept but not for slope; and ! The level 3 model was a function of High Contrast, with an error term (random effect) for intercept but not for slope; where the Covariates were person-level characteristics of the women and High Contrast referred to a high level on the integrated counseling program contrast (see section 2.3.3 below) identified as significant by Cocozza et al. (2005). The steps in the hierarchical analysis included (1) screening potential covariates based on their correlations with each outcome measure at baseline, (2) applying model selection procedures to identify the appropriate set of person-level covariates for each outcome measure, 3
We first established that HLM (Raudenbush & Bryk, 2002) reproduced the meta-analysis results presented by Cocozza et al. (2005). The results of HLM models unadjusted for person-level variables were consistent with those of the meta-analysis in terms of intervention effects and program contrasts. (The results of these analyses may be obtained by contacting the primary author.) As HLM provides a more efficient way of evaluating multiple person-level covariates than meta-analysis, it is the method used in this paper.
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resulting in four models, and (3) for each of these four outcome models, adding a program contrast term for integrated counseling. 2.3.2. Screening of covariates and selection of person-level models Covariates whose correlation with a given outcome measure was at least .10 in absolute value were entered into the stepwise model selection process to identify the best multilevel model for that outcome measure, with the goal of balancing predictive power with parsimony.4 Correlations that met or exceeded this threshold are displayed in Table 2. Several potential covariates did not meet this selection threshold: years of education, current homelessness, monthly income, race/ethnicity, relationship status (divorced or widowed, married, separated, significant other), received substance abuse treatment ever, received substance abuse treatment 2 or more times in the past, and number of total mental hospital admissions. The model selection steps subsequent to covariate screening included: (1) Each potential covariate was entered into a separate multilevel model (i.e., one model per covariate) including all possible interactions with Intervention and Time, iteratively deleting the term with the highest p-value until all remaining terms had p b 0.15. (2) All terms surviving step 1 were combined into one multilevel model, iteratively deleting the term with the highest p-value until all remaining terms had p b 0.05. (3) Any terms excluded in step 1 were re-entered one at a time and any significant at p b 0.05 retained. When an interaction term met the significance criterion for a given step, the corresponding lower-order interactions and main effects were automatically retained. Completion of step 3 of the model selection procedure resulted in a final person-level model for each of the four outcome variables. 2.3.3. Program contrast A program contrast is a hypothesis formulated in advance to explain between-site differences in outcomes (Banks, McHugo, Williams, Drake, & Shinn, 2002). Cocozza et al. (2005) found that a program contrast based on inte4
Given the sample size, a correlation of .10 corresponds to a p-value less than .0001. This selection criterion ensured that all variables considered in subsequent analyses had at least a small association with one or more outcome variables. Since the models incorporated both the baseline and 6-month measurements as part of the dependent variable, the baseline value of a modelTs dependent variable was not used as a covariate. Post-traumatic stress symptoms (PSS) and mental health symptoms (GSI) were highly correlated (r = .77), so when one of the two was a dependent variable, the other was not considered as a covariate. For the substance use (ASI) outcomes, if both PSS and GSI were correlated with the outcome variable above the threshold level at baseline, the covariate with the higher correlation was selected.
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grated counseling was significant in explaining variations in the 6-month outcomes across the nine sites. Integrated counseling was based on a womanTs self-report at 3 months postbaseline of the number (range = 0–3) of foci (mental health, trauma, and substance abuse) addressed in her individual and group counseling services. When averaged across women within condition and site, this measure is used as an indicator of the extensiveness of integrated counseling at the programlevel. The 3-month time point is clearly antecedent and timewise independent of the assessment of outcomes at 6 months, and it also occurs when most of the women were still participating in services thereby minimizing recall biases. Five of the nine sites scored high on this contrast indicating that women in the intervention condition at these sites were significantly more likely to report receiving services that addressed all three foci (mental health, substance abuse, and trauma) compared to women receiving services at the matched comparison condition at those sites. The other four sites scored low on this contrast, meaning that women in intervention and comparison conditions did not differ in their reports of receiving integrated counseling. From each of the four final person-level models, a new model was created by adding a program contrast term (the interaction of High Contrast On Integrated Counseling with Time and Intervention)5 plus all lower-order terms that could be constructed using the three variables in the program contrast effect. In each of the four resulting program contrast models, any person-level variable with a significant three-way interaction (Covariate Intervention Time) was tested for a possible four-way interaction (Covariate Intervention Time High Contrast).6 The four-way interaction term was retained if significant at p b 0.05. It might be argued that the personal experience of and response to services are more important than program-level characteristics, and that since each individual received a unique combination of services, any effects attributed to the program-level measure of integrated counseling described above might be better explained by a person-level measure of the amount of integration that each subject experienced. As a check on this alternative specification, a person-level measure of integrated counseling was added to the HLM models along with the original program contrast variable. The person-level measure was operationalized as a 0–3 variable reflecting the maximum level of integration (i.e., maximum number of issues addressed out of three possible—mental health, substance abuse, and trauma) the subject reported experiencing in individual or group counseling in any setting. With this variable added to the models the program contrast effects were reduced somewhat, but
5 Although the phrase bprogram contrast effectQ could mean the main effect of program contrast condition, in order to simplify language it is used throughout this paper to refer to the specified 3-way interaction. 6 Generic SAS code for the final models and model specification in vector notation are available from the primary author.
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Table 2 Results of person-level covariate screening: Pearson correlationsa of potential person-level covariates with outcome variables Variable Demographic and general Age Current court-ordered mental health or substance abuse treatment Homeless, ever Number of barriers to receiving services Serious physical illness or disability Substance abuse (SA) Alcohol use problem severity (ASI-A) baseline score Drug use problem severity (ASI-D) baseline score Cigarettes smoked per day Received SA medication (e.g., methadone) in past 3 months Years used alcohol to intoxication Years used drugs Mental health (MH) Age at first MH admissionb Age when first MH problem began Mental health status (GSI) baseline scorec Number of voluntary MH admissions Received MH medication in past 3 months Received MH treatment 2 times or for N6 months, ever Received MH treatment, ever Receiving MH treatment currently Trauma Admitted to hospital or emergency room in past 3 months: physical, medical, or injury reason Admitted to hospital or emergency room in past 3 months: violence, abuse, or trauma reason Current exposure to interpersonal abuse Current exposure to other stressful events Emotional abuse or neglect in childhood Frequency of childhood abuse Lifetime exposure to stressful events Lifetime frequency of interpersonal abuse Physical abuse in adulthood Physical abuse in childhood Post-traumatic stress symptom (PSS) baseline scorec Sexual abuse in adulthood Sexual abuse in childhood Stalked or threatened with death or harm, ever
Alcohol use problem severity (ASI-A)
Drug use problem severity (ASI-D) 0.15 0.10
Mental health status (GSI)
0.12
0.10
0.14 0.17
0.10 0.15 0.15
0.10
0.26 0.26 0.12 0.10
Post-traumatic stress symptoms (PSS)
0.13 0.17 0.12
0.35
0.12 0.11 0.17
0.11 0.19 0.16 0.14
0.16 0.17
0.12 0.26 0.18 0.15 0.21
0.11 0.24 0.18 0.14 0.20
0.13
0.11
0.11
0.15
0.20 0.22
0.12 0.11
0.13
0.16
0.25 0.25 0.24 0.29 0.33 0.39 0.19
0.28 0.27 0.24 0.31 0.37 0.42 0.10 0.20
0.20 0.19 0.18
0.21 0.21 0.20
0.12
a Only correlations with absolute value greater than or equal to .10 are shown. Since the models incorporate both the baseline and 6-month measurements as part of the dependent variable, the baseline value of a modelTs dependent variable can not be used as a covariate in that model; therefore, correlations between the baseline and 6-month values of each dependent variable are omitted. b To include subjects reporting no admissions, the following categories are used: 0 = never, 1 = ages 26+, 2 = age 16–25, 3 = age 1–15. c PSS (post-traumatic stress symptoms) and GSI (mental health status) are highly correlated (r = .77), so when one of the two is a dependent variable, the other is not considered as a covariate. This correlation is therefore omitted from the table. For the ASI outcomes, if both PSS and GSI are correlated with the outcome variable above the threshold level at baseline, the covariate with the higher correlation is selected.
they remained significant and in the same direction. Any reduction in magnitude did not exceed 11.5%. No interaction was found between the person-level measure and the program contrast. These results indicate that, net of person-level effects, something meaningful does appear to be occurring on the program level, which supports the specification of integrated counseling as a program-level variable in these analyses. The results reported here are based upon final models and are presented as three distinct categories of person-level
effects, with each category corresponding to a research question—(1) those unrelated to the intervention or the program contrast; (2) those related to the intervention; and (3) those related to the program contrast effects—followed by (4) an evaluation of clinical significance. The order of the first three research questions implies a progression from lower-order to higher-order interactions. Consistent with standard practice, lower-order terms were not interpreted when there was a higher-order interaction involving the same covariate(s). To aid interpretation, the sign of each
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reported effect size and parameter estimate was adjusted such that a positive effect indicates improvement.
3. Results 3.1. Person-level characteristics and 6-month outcomes With regard to the first research question, we found several person-level characteristics (Table 3) of the women who participated in the study that are related to their 6-month outcomes ( p b 0.05), regardless of intervention condition and program contrast condition (i.e., Covariate Time interactions where no higher-order interaction is present). For drug use problem severity, women with the following characteristics at baseline show more improvement at 6 months: higher number of years using drugs, courtordered treatment, current exposure to interpersonal abuse, and current exposure to other stressful events ( p b 0.0001 to p b 0.05). Less improvement on drug use problem severity is shown by those who are older at time of enrollment, those who have a higher mental health symptom score at baseline, and those who are currently receiving mental health treatment at baseline ( p b 0.001 to p b 0.005). Only one variable is associated with alcohol use problem severity—those who have a high number of years using alcohol to intoxication show more improvement at the 6-month outcome assessment ( p b 0.0001). For mental health status, women who have more improvement at 6 months are those who, at baseline, have
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a high lifetime frequency of interpersonal abuse; those who have current exposure to other stressful events (i.e., not interpersonal abuse); and those with a higher baseline score on drug use problem severity (ASI-D; p b 0.0001 to p b 0.01). Women with less improvement are those who were younger at first psychiatric hospitalization, those who experienced physical abuse in childhood, and those with a current serious physical illness or disability ( p b 0.05). Women with more improvement on post-traumatic stress symptoms are those who have greater lifetime exposure to stressful events, current exposure to interpersonal abuse, current exposure to other stressful events, and higher baseline scores on alcohol use problem severity (ASI-A; p b 0.001 to p b 0.05). Less improvement in post-traumatic stress symptoms is associated with the presence of a serious illness or physical disability ( p b 0.05). 3.2. Person-level characteristics and intervention effects at 6 months With regard to the second research question, we found three person-level characteristics that moderate the 6-month intervention effect regardless of program contrast condition (i.e., significant interaction of Covariate Intervention Time where no higher-order interaction is present). For drug use problem severity (ASI-D), women with a high baseline score on alcohol use problem severity (ASI-A) have a more positive intervention effect than do others. Controlling for other person-level covariates in the model, an increase of 1 SD in ASI-A baseline severity is
Table 3 Effect of person-level characteristics on 6-month outcomes independent of treatment condition and level of integrated counseling contrast Outcome variable
Predictor
Drug use problem severity (ASI-D)
Age Current court-ordered mental health (MH) or substance abuse treatment Years used drugs Mental heath status (GSI) baseline score Currently receiving MH treatment Current exposure to interpersonal abuse Current exposure to other stressful events years used alcohol to intoxication serious physical illness or disability drug use problem severity (ASI-D) baseline score age at first MH admissionb Current Exposure to Other Stressful Events Lifetime Frequency of Interpersonal Abuse physical abuse in childhood serious physical illness or disability alcohol use problem severity (ASI-A) baseline score Current Exposure to Interpersonal Abuse Current Exposure to Other Stressful Events Lifetime Exposure to Stressful Events
Alcohol use problem severity (ASI-A) Mental health status (GSI)
Post-traumatic stress symptoms (PSS)
a
Parameter estimatea .002783**** .024050** .003350**** .015390*** .028060*** .005380* .009000**** .008130**** .064090* .266800** .032720* .035330**** .012450**** .096580** 1.043800* 2.534200** .541800** .341400* .237400***
Unstandardized regression coefficients; signs are adjusted so that a positive parameter estimate indicates improvement. To include subjects reporting no admissions, the following categories are used: 0 = never, 1 = ages 26+, 2 = age 16–25, 3 = age 1–15. * p b 0.05. ** p b 0.01. *** p b 0.001. **** p b .0001.
b
SE .000422 .007277 .000408 .004605 .007282 .002551 .001934 .000661 .030830 .103400 .015170 .008145 .002869 .037390 .543700 .899800 .207200 .160300 .068870
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associated with an additional intervention gain of 0.15 SD units on the ASI-D 6-month score ( p b 0.01).7 Similarly, having been stalked or threatened is associated with an additional intervention gain of .17 SD units on mental health status ( p b 0.05), and physical abuse in adulthood is associated with an increased intervention gain of .24 SD units on post-traumatic stress symptoms ( p b 0.05). In combination, these results suggest that intervention effects are moderated by several person-level variables. 3.3. Person-level characteristics and interactions with program contrast effects With regard to the third research question, we found one person-level characteristic that moderates the 6-month program contrast effect (i.e., Covariate Intervention Time High Contrast interaction). For alcohol use problem severity (ASI-A), women with a high baseline score on drug use problem severity (ASI-D) have a more positive intervention effect than others, with this difference being more pronounced in the high-integrated-counseling-contrast sites ( p b 0.05). Fig. 1 shows the interaction of the person-level covariate—dichotomized for the purpose of illustration— and the program contrast condition. There is an increase of .35 SD (.575–.225) on the ASI-A for the high-contrast sites and only .13 SD (.130–.000) for the low-contrast sites, so the effect is 2.7 times as large at the high contrast sites. For the other three outcomes, no person-level covariate moderates the 6-month program contrast effect. After controlling for person-level variables, location in a site with a high contrast on integrated counseling is associated with an added intervention benefit of .38 SD ( p b 0.001) and .17 SD ( p b 0.05) respectively for drug use problem severity and mental health status. For post-traumatic stress symptoms the added benefit of .08 SD is not statistically significant. These adjusted effects are somewhat attenuated relative to the effects found by Cocozza et al. (2005), but they still match in significance, direction, and overall pattern. These HLM results indicate that the effect of the integrated counseling contrast is partially mediated by person-level covariates but, after controlling for these covariates, the integrated counseling contrast remains statistically significant. 3.4. Clinical significance A large sample enables the detection of small differences, so it is important to ask whether the effects reported here are large enough that a consumer or therapist would view them as meaningful. The purpose of this section is to 7 In this analysis the SD of a dependent variable is estimated by the square root of its total estimated variance from an unconditional model (i.e., a model with random intercepts and no fixed predictors). The estimated effect sizes reported below are determined by dividing a parameter estimate by this estimated SD.
anchor the results in (1) an understanding of the overall changes from baseline to 6 months and (2) an evaluation of clinical significance. With respect to clinical significance, overall improvement is noted below, but the main focus is on the high-contrast integrated counseling effect. This is the strongest predictor among the intervention elements tested in Cocozza et al. (2005), and it is consistent across three of the four outcomes. As noted earlier, at baseline the sample means on ASI-D, ASI-A, GSI, and PSS were 0.20, 0.16, 1.35, and 23.7. Table 4 presents descriptive statistics for baseline to 6-month improvement on each of the four outcome variables, first for the sample as a whole and then by integrated counseling and intervention conditions. For the sample as a whole, the means for substance use severity indicate that on average there was improvement. For mental health and post-traumatic stress symptoms, the baseline means indicate moderately elevated GSI scores (T-score = 69) and moderate-to-severe PSS scores. At 6 months, mental health symptoms on average are reduced but still remain in the elevated range (T-score = 66), while post-traumatic stress symptoms have decreased further into the moderate range (11–20). The HLM results reported above indicate that larger effect sizes occur in sites where women in the intervention condition reported a higher level of integrated counseling relative to their counterparts in the comparison condition. Consistent with this finding, examination of the unadjusted means in Table 4 reveals that in the low-contrast sites (on average) the intervention condition had less improvement than the comparison condition on every outcome except post-traumatic stress symptoms, while in the high-contrast sites the intervention condition had more improvement than the comparison condition on all four outcomes. The added intervention effects for the high-contrast sites relative to low-contrast sites, as estimated from the HLM models, have the following clinical equivalents: For drug use problem severity, it is equivalent to a reduction from 20 days to 14 days of amphetamine, barbiturate, and polydrug use. For alcohol use problem severity, this effect (assuming a mean ASI-Drug score at baseline) is equivalent to a reduction from 28 days of use and 1 day of intoxication to 20 days of use and 1 day of intoxication. For mental health status, it is equivalent to a reduction from 20 symptoms to 18 symptoms. Another way of evaluating the clinical significance of this effect is to examine the percentages of women who improved at high-contrast and low-contrast sites. At the highcontrast sites, according to ASI-Drug scores, 50% (169/341) of the intervention women who were using drugs at baseline reported not using at follow-up. In the comparison condition, 34% (131/382) of those who used drugs at baseline were not using at follow-up. The analogous percentages for ASI-Alcohol are 54% (134/246) for intervention and 37% (111/303) for comparison. On mental health status, among women in the high-contrast sites with severe
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0.7
Intervention Effect Size
0.6
0.575
0.5
0.4 low contrast high contrast 0.3 0.225
0.2 0.131
0.1
0
0
ASI-Drug low
ASI-Drug high (+1 SD)
Drug Use Problem Severity (ASI-D) Baseline Score
Fig. 1. Effect of drug use problem severity (ASI-D) baseline score on 6-month intervention effect size for alcohol use problem severity (ASI-A), by level of integrated counseling contrast. The effect size controls for other covariates in the model and is relative to the reference group for that outcome measure (low program contrast condition combined with a low covariate value). The difference between blowQ and bhighQ covariate values is 1 SD. Effect size is the estimated effect divided by the square root of the total estimated variance of the outcome variable from an unconditional model (i.e., a model with random intercepts and no fixed predictors).
improvement. However, for women reporting baseline substance use, a much greater percentage of women in the intervention (as opposed to the comparison) condition improved to symptom-free/behavior-free status. The results were less dramatic for mental health outcomes, but a clear pattern emerged suggesting that women with the most extreme scores were more likely to improve if treated in the intervention condition.
baseline scores (T-score N = 75), 59% (47/80) in the intervention condition and 49% (49/99) in the comparison condition improved to moderately severe or better (T-score b 75). (For post-traumatic symptoms no significant program contrast effect was found.) Although intervention women improved more on average than their comparison counterparts, the average changes were small, and many symptoms remained even after
Table 4 Unadjusted statistics on baseline-to-6-month improvement,a overall and by integrated counseling and intervention conditions Group
Variable
N
Overall
ASI-D ASI-A GSI PSS ASI-D ASI-A GSI PSS ASI-D ASI-A GSI PSS ASI-D ASI-A GSI PSS ASI-D ASI-A GSI PSS
1997 2002 2004 1906 447 448 449 430 542 547 545 516 533 534 534 506 475 473 476 454
Low-contrast comparison
Low-contrast intervention
High-contrast comparison
High-contrast intervention
a
Positive numbers indicate improvement.
Min. 0.45 0.96 2.66 42.00 0.39 0.56 2.66 35.00 0.38 0.96 2.15 42.00 0.45 0.70 2.26 33.00 0.27 0.63 1.47 31.00
Max.
Mdn.
Mean
SD
0.63 1.0 3.13 48.0 0.5 1.0 2.32 36.0 0.63 1.0 3.13 48.0 0.54 1.0 2.34 46.0 0.62 1.0 2.79 43.0
0.05 0.0 0.2 4.0 0.09 0.0 0.26 4.0 0.04 0.0 0.19 4.0 0.02 0.0 0.12 2.0 0.06 0.0 0.21 4.0
0.09 0.11 0.23 4.03 0.12 0.14 0.26 4.45 0.09 0.1 0.24 4.81 0.06 0.09 0.15 2.75 0.11 0.14 0.26 4.18
0.16 0.28 0.67 11.56 0.16 0.28 0.65 11.42 0.16 0.26 0.73 12.74 0.14 0.27 0.66 10.99 0.16 0.3 0.63 10.79
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4. Discussion The WCDVS did not have a uniform intervention across sites nor were women randomly assigned to intervention and control conditions, as noted earlier. Under these circumstances, the true effects of the intervention could easily be masked by sample variability at the program level, the person level, or both. In the current analysis, program and person contrasts are used as statistical tools to identify sources of variability between and within study sites and to adjust for them in assessing outcomes. Overall, the results reported here provide evidence that WCDVS interventions led to improvements in womenTs substance use behaviors as well as reductions in their mental health symptoms, in sites where the intervention condition received a higher level of integrated counseling than did the comparison condition. It is noteworthy that although trauma-informed services were an important aspect of the intervention, the effect of the intervention on posttraumatic stress symptoms was not statistically significant in unadjusted HLM models. One possible explanation is that in the short run, substance use behaviors may be more responsive to these interventions, while mental health and trauma symptom outcomes may require more time or more intervention. The 12-month WCDVS follow-up data will provide an opportunity to further examine evidence for these delayed effects. With the exception of non-significant improvements in trauma symptoms, the HLM findings confirm the overall pattern of the meta-analysis results reported by Cocozza et al. (2005).8 In sites where women in the intervention condition reported a higher level of integration relative to their counterparts in the comparison condition, the intervention effects for drug use problem severity and mental health status are larger relative to sites where there was not a large difference in level of integration. For alcohol use problem severity there is also a larger intervention effect in sites with a high contrast on integrated counseling, but the magnitude of this difference depends on baseline level of drug use problem severity. The covariate-adjusted effect sizes for HLM are smaller than those for meta-analysis but still statistically significant, indicating that the personlevel covariates tested only partially mediate the effect of intervention/comparison differences in the extent to which counseling integrates mental health, substance abuse, and trauma issues.
8
This apparent inconsistency between the HLM and meta-analysis results likely is mostly due to the fact that HLM takes into account the dependence among observations within each site, which can result in increased standard errors and larger p-values for fixed effects. Between the two methods the actual difference in p-values for the intervention effect on posttraumatic stress symptoms is small: .02 for meta-analysis and .053 for HLM (unadjusted). For the there outcomes with significant program contrast effects, the p-values (ASI-D, ASI-A, and GSI) for meta-analysis are b 0.0001, b 0.0001, 0.009 and those for HLM (unadjusted) are b 0.0001, 0.0002, 0.02 respectively.
Where HLM goes beyond meta-analysis and adds to our understanding of the impact of the WCDVS is with regard to person-level covariates. From the HLM results presented here it is clear that person-level variables do not explain away the combined effects of the intervention and the integrated counseling contrast. To the contrary, it is remarkable how narrow the scope of person-level variables is in mediating or moderating those effects. Of the 45 potential person-level covariates considered for each of the four outcome measures, only four are found to have a statistically significant relationship either with the intervention condition or with the integrated counseling contrast. High alcohol use (ASI-A) baseline severity, having been stalked or threatened, and having experienced physical abuse in adulthood are associated with additional intervention gains on the drug, mental health, and post-traumatic stress symptom outcomes respectively. High drug use (ASI-D) baseline severity is associated with an additional intervention benefit on the alcohol outcome, with this difference being more pronounced in the high-integrated-counseling-contrast sites. There is a suggestion in these findings that women with more severe problems at baseline benefit more from the intervention. However, a large number of statistical tests were performed, and this interpretation of these four effects is not supported by a cluster of other severity variables with similar effects. Also, such an interpretation would run counter to current literature in the behavioral health field (see, e.g., Acharyya & Zhang, 2003; Haller et al., 2003; McLellan et al., 1994) indicating that baseline severity predicts poorer outcomes. For these reasons, it is prudent to conclude that unless these interactions are confirmed in the 12-month results, they may in fact be sample artifacts or spurious relationships. We should explain that, although a large number of tests were conducted in the analyses reported here, they follow upon the significant intervention and integrated counseling contrast findings reported by Cocozza and colleagues (2005). Our testing strategy derives from the clinical trials principle that once a predicted relationship is supported by the data, the next task is to assess whether any particular subset of individuals is adversely affected by the intervention. So we tested a comprehensive list of covariates to see whether the high contrast effects for integrated counseling were conditional on one or another personal characteristic of the women enrolled. Our conclusion is that the high integrated counseling contrast effects reported here appear to be fairly robust in that, save for the four covariates mentioned, these effects hold up across a wide array of demographic, clinical, and experiential characteristics of the women who participated in the study. It is encouraging from a service delivery perspective that women who have co-occurring disorders and have been abused physically or sexually respond positively to counseling that integrates mental health, substance abuse, and trauma, even though they come from diverse social backgrounds and life circumstances. What we cannot infer from
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these data, however, is whether women who were not interviewed at 6 months would respond in the same way. As reported in a companion article (McHugo et al., 2005), these women were younger, were less likely to have dseparatedT marital status, had fewer psychiatric hospitalizations, and had more recent stressors other than interpersonal abuse. All of this commentary is not to ignore that a number of person-level variables are related to one or more of the four outcomes considered in this study and do not interact with the intervention and program contrast effects (see Table 3). Because of the large number of covariates tested, these effects should be interpreted with caution, with added weight given to variables that are highly significant or affect more than one outcome in the same direction. These effects may highlight areas where the interventions could be adjusted or provided for a longer time period in order to achieve wider success with women who have these attributes. For example, controlling for other characteristics, women with a serious physical illness or disability had poorer mental health and trauma outcomes regardless of intervention and integrated counseling conditions, suggesting that it may be important for services to take physical health and disability issues into account. That said, these person-level relationships do not detract from the overall promising 6-month results reported here about the effectiveness of trauma-informed interventions in improving womenTs substance use problems as well as their mental health and post-traumatic stress symptoms. One potential limitation of a study with non-randomized groups is that, before or after attrition, there may be differences between the intervention and comparison condition with respect to characteristics (e.g., high baseline severity) that are related to the outcomes. If this were the case, the outcome differences observed between groups could not be clearly attributed to the intervention. As reported above, baseline differences between conditions were minimal on variables correlated with the outcome measures. There was a small amount of differential attrition involved in the WCDVS (reported above; also see McHugo et al., 2005); however, the four variables involved either were uncorrelated with the outcome measures (based on the |r| z .10 threshold employed here for the screening of potential covariates) or were found not to moderate the intervention and program contrast effects. So itTs likely that the findings reported here can not be explained away by baseline differences or differential attrition. Other limitations of this study should also be noted. The results are based entirely on self-reports that were not corroborated by agency service records or other independent data. Also, the quasi-experimental design of the WCDVS may have attenuated the true effects of the intervention, in that some of the comparison women reported receiving integrated counseling from service agencies in the comparison condition. A more direct measure of the actual amount and extent of integrated counseling received by study partici-
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pants, perhaps in a design with multiple study arms comparing varying dosage levels, would yield more definitive conclusions about the effectiveness of integrated counseling in producing the changes observed in this study. In addition, varying service approaches were implemented in different sites (see McHugo et al., 2005) and we are unable to determine whether the effects are greater for one approach or another. Also, the small number of sites (N = 9) prevented us from exploring the effects of other program-level characteristics that might be important such as setting (residential vs. outpatient), location (urban vs. rural), and whether services are provided by single vs. multiple agencies. On the person level, the covariate screening and model selection procedures used (which were designed to keep model complexity manageable) may have caused the omission of important interactions between person-level covariates, or groups of covariates that have a noticeable effect only when considered together. There may be important covariates that were not measured; for example, we were unable to control for service duration or date of service completion, and some women continued to receive services at the time of the 6-month follow-up. Each of these is an important consideration for the design of future research. Another important issue is whether integrated counseling can be provided more effectively by an individual therapist or by an inter-agency program. The findings of the WCDVS leave open this question, which is important from the provider perspective as well as that of the policy maker and should be part of a future research agenda in this area. Studies based upon carefully controlled and randomized designs offer the most promise for establishing which specific aspects of integrated, traumainformed interventions contribute to overall effectiveness. Using a large sample sometimes means that weak relationships or small improvements are identified as being statistically significant. The statistically significant improvements found in this paper are small, but this does not mean that they are insignificant clinically. Not only did intervention women in the high-integrated-counseling-contrast sites improve more than the comparison women, but more of them improved in clinically significant terms. The results were not uniform across outcomes and were notably better for the substance use outcomes. Although women did not achieve a complete amelioration of symptoms, even small improvements could be very meaningful for women who suffer from so many symptoms and problems. Moreover, these changes represent more improvement than that offered by care-as-usual. These findings indicate that attention to mental health and trauma issues is important in substance abuse services for women with co-occurring mental health disorders and trauma histories, and that interventions involving integrated counseling should be explored further in an effort to improve upon these services and outcomes. These are interim findings reflecting short-term outcomes at 6 months from a 12-month follow-up study. We
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will have the opportunity in a subsequent paper to consider whether the effects reported here at 6 months are enhanced, sustained, or diminished at 12-month follow-up. The current findings, however, are encouraging. They suggest that providing integrated, trauma-informed services can help women who have long standing problems improve their lives by reducing their mental health and trauma-related symptoms and their use of substances. Further research will be necessary to confirm the actual trajectory and to demonstrate the magnitude and sustainability of longer-term outcomes. Such research can provide the evidence base necessary to help communities throughout the U.S. to meet the needs of many thousands of women who today are not well served by traditional mental health and substance abuse services.
Acknowledgments This study was funded under Guidance for Applicants (GFA) No. TI 00-003 entitled Cooperative Agreement to Study Women with Alcohol, Drug Abuse and Mental Health (ADM) Disorders who have Histories of Violence: Phase II from the Department of Health and Human Services, Public Health Service, Substance Abuse and Mental Health Services AdministrationTs three centers: Center for Substance Abuse Treatment, Center for Mental Health Services and Center for Substance Abuse Prevention (March 2000). The assistance of project staff at the following participating sites (listed in alphabetical order by state) is gratefully acknowledged: Los Angeles, California: PROTOTYPES Systems Change Center, Vivian Brown, Principal Investigator, Stockton, California: Allies: An Integrated System of Care, Jennie Heckman, Principal Investigator, Thornton, Colorado: Arapahoe House–New Directions for Families, Nancy VanDeMark, Principal Investigator, Washington, DC: District of Columbia Trauma Collaboration Study, Roger Fallot, Principal Investigator, Avon Park, Florida: Triad WomenTs Project, Margo Fleisher-Bond, Co- Principal Investigator, Colleen Clark, Co- Principal Investigator, Boston, Massachusetts: Boston Consortium of Services for Families in Recovery, Hortensia Amaro, Principal Investigator, Cambridge, Massachusetts: Women Embracing Life and Living (WELL) Project, Norma Finkelstein, Principal Investigator, Greenfield, Massachusetts: Franklin County WomenTs Research Project, Rene Andersen, Principal Investigator, New York, New York: Portal Project, Sharon Cadiz, Principal Investigator. The Coordinating Center is operated by Policy Research Associates (PRA), located in Delmar, New York, in coordination with the National Center on Family Homelessness of Newton, Massachusetts and the Cecil G. Sheps Center for Health Services Research at the University of North Carolina (UNC) in Chapel Hill, North Carolina. The interpretations and conclusions contained in this publication do not necessarily represent the position of the
WCDVS Coordinating Center, participating study sites, participating Consumer/Survivor/Recovering persons, or the Substance Abuse and Mental Health Services Administration and its three centers (Center for Substance Abuse Treatment, Center for Mental Health Services, Center for Substance Abuse Prevention).
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