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. Author manuscript; available in PMC: 2015 Nov 1.
Published in final edited form as: Health Soc Care Community. 2014 Dec 3;23(6):642–653. doi: 10.1111/hsc.12178

Substance abuse and batterer programmes in California, USA: factors associated with treatment outcomes

Christine Timko 1, Helen Valenstein 2, Gregory L Stuart 3, Rudolf H Moos 1
PMCID: PMC4573371  NIHMSID: NIHMS667257  PMID: 25470658

Abstract

The association between substance abuse and intimate partner violence is quite robust. A promising area to improve treatment for the dual problems of substance abuse and violence perpetration is the identification of client characteristics and organisational and programme factors as predictors of health outcomes. Therefore, we examined associations of client, organisational and programme factors with outcomes in community health settings. Directors of 241 substance use disorder programmes (SUDPs) and 235 batterer intervention programmes (BIPs) reported outcomes of programme completion and substance use and violence perpetration rates at discharge; data collection and processing were completed in 2012. SUDPs having more female, non-white, younger, uneducated, unemployed and lower income clients reported lower completion rates. In SUDPs, private, for-profit programmes reported higher completion rates than public or private, non-profit programmes. SUDPs with lower proportions of their budgets from government sources, and higher proportions from client fees, reported better outcomes. Larger SUDPs had poorer programme completion and higher substance use rates. Completion rates in SUDPs were higher when clients could obtain substance- and violence-related help at one location, and programmes integrated violence-prevention contracting into care. In BIPs, few client, organisational and programme factors were associated with outcomes, but the significant factors associated with programme completion were consistent with those for SUDPs. Publicly owned and larger programmes, and SUDPs lacking staff to integrate violence-related treatment, may be at risk of poorer client outcomes, but could learn from programmes that perform well to yield better outcomes.

Keywords: batterer intervention, client factors, community health, intimate partner violence, organisational factors, programme factors, substance use disorder, treatment outcomes

Introduction

The association between substance abuse and intimate partner violence (IPV) is theoretically and empirically robust (Stuart et al. 2013). Batterers who received substance abuse treatment demonstrated reduced violence recidivism rates (Jones & Goldolf 2001), and individuals treated in substance use disorder programmes (SUDPs) evidenced significantly reduced violence recidivism (Stuart et al. 2009). In addition to better understanding client characteristics as predictors of health outcomes, a promising area to improve treatment for the dual problems of substance abuse and violence perpetration is the identification of organisational and programme factors that influence client outcomes. Studies of SUDPs have shown organisational factors to be associated with the adoption of treatment innovations and the cost and quality of treatment (Lemak & Alexander 2005, Bride et al. 2011). Accordingly, this study examined client, organisational and programme factors associated with end-of-treatment outcomes in SUDPs and batterer intervention programmes (BIPs). Outcomes examined were programme completion, and use of substances and perpetration of IPV at programme discharge.

The rate at which clients complete the programme, estimated at 42% in outpatient SUDPs nationally (Substance Abuse & Mental Health Services Administration, Office of Applied Studies 2010), and 50%–75% in BIPs (Daly & Pelowski 2000, Rooney & Hanson 2001, Dalton 2007, Stalans & Seng 2007), is an important performance indicator because it is associated with better client outcomes in both systems of care. Specifically, clients who complete SUD treatment are more likely to achieve abstinence (Magill & Ray 2009, Soyka & Schmidt 2009), and those who complete batterer interventions may be more likely to refrain from additional violence perpetration (Babcock et al. 2004, Coulter & VandeWeerd 2009, Olver et al. 2011). The outcomes of substance use and IPV perpetration are also important because the goal of most SUDPs is abstinence (Office of National Drug Control Policy 2002, Finney et al. 2003), and the goal of BIPs is to prevent IPV to increase victim safety (Bennett & Williams 2001, Eckhardt et al. 2006).

This study focused on a sample of SUDPs and BIPs in California, USA. The study’s design was guided by a modified version of Moos’ (1997) conceptual framework for informing policy through evaluations of treatment programmes (Figure 1). This model is broadly consistent with the model of organisational change in addictions treatment outlined by Simpson (2004). It highlights the role of organisational factors and aggregate client characteristics in shaping the use of specific linkage practices within and across programmes and how these factors influence treatment outcomes. Specifically, the model suggests that characteristics of the organisation and the types of clients served shape linkages (D’Aunno 2006, Oser et al. 2009), and that stronger linkages are associated with more positive client outcomes (Fletcher et al. 2009, Flynn et al. 2012). However, critical data have been lacking from SUDPs and BIPs on associations of these domains with client outcomes.

Figure 1.

Figure 1

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Determinants and outcomes of SUDP and BIP linkages. SUDP, substance use disorder programme; BIP, batterer intervention programme; SES, socioeconomic status.

Client characteristics

Client characteristics are indicative of personal needs and resources and include factors such as gender, race and ethnicity, socioeconomic status and court mandates to treatment. In SUDPs, clients who were male, black, older and more educated were more likely to complete treatment (Stack et al. 2000, Brecht et al. 2005, Zanis et al. 2009, Darke et al. 2012), and clients who were older were more likely to be abstinent post-treatment (Heinrich & Fournier 2004). In BIPs, clients who were married, more educated, employed and with higher incomes were more likely to complete treatment; however, clients with prior criminal histories, court mandates to treatment, or mental health concerns were less likely to complete treatment (Daly & Pelowski 2000, Stalans & Seng 2007, Catlett et al. 2010).

Organisational factors

Organisational factors that may influence client outcomes include the programme’s years of operation, setting in a rural or urban area, ownership, size, staffing and financing. Historically, SUD treatment outcome research has overlooked organisational factors in favour of client characteristics (Grella et al. 2007). Older programmes may be more experienced in effective practices to ensure treatment retention (Campbell et al. 2009). However, older programme age was associated with shorter treatment durations (Friedmann et al. 2006). SUDPs located in urban areas had lower treatment completion rates than SUDPs in rural areas (Rootman et al. 2005), and those with public ownership were less successful at retaining clients and reducing clients’ substance use than SUD-Ps with private ownership (Heinrich & Fournier 2004, Campbell et al. 2009). Possibly, larger programmes have more resources to offer clients, such as specialised staff and services, which may facilitate treatment retention (Campbell et al. 2009), but this has not been examined in SUDPs or BIPs.

Linkages: in-programme and cross-programme practices

Recommended practices for addressing the co-occur ring problems of SUD and IPV perpetration urge SUD-Ps and BIPs to assess and monitor the cross problem, to help clients with both problems in a co-ordinated way and to collaborate with each other in providing comprehensive services (Bennett 2008, Macy & Goodbourn 2012). SUDPs may or may not offer services for addressing IPV perpetration, and BIPs may or may not offer services for addressing clients’ alcohol and drug problems. In general, healthcare consumers prefer ‘one stop shopping’ for co-occurring needs – that is, obtaining care for different health problems in a single location, co-ordinated during a single visit (Weisner et al. 2001) – and this should extend to individuals with both substance use- and violence-related problems. However, there has been little effort to collect data to examine associations between linkage practices and outcomes in SUDPs and BIPs.

Study aims

Our aims were to study a sample of SUDPs and BIPs to examine the associations of client, organisational and programme linkage factors with the end-of-treatment outcomes of programme completion, substance use and IPV perpetration. Improving our knowledge of the extent to which these factors are determinants of SUDP and BIP outcomes will help to guide policy makers’ recommendations. It will also help programme managers and providers understand these associations and adapt interventions to better reduce substance abuse and violence, thereby improving the quality of care in these settings.

Method

Sample

The initial sampling frame was all BIPs in the state, using a current listing by the California State Auditor. Although BIPs are not typically described as providing treatment for a diagnosed disorder, all would fall in the category of outpatient care. Within each of the state’s 58 counties, the same number of SUD outpatient treatment programmes as BIPs was randomly selected using Substance Abuse and Mental Health Services Administration (SAMHSA’s) Substance Abuse Treatment Facility Locator. Considering sampling with respect to county reduced the likelihood of extraneous factors (e.g. judicial practices; availability of health, social and other services) affecting results. We confirmed the accuracy of contact information, requested surveys from directors of 339 SUD-Ps and 339 BIPs, and used a sequence of follow-up procedures to target non-responders (Dillman et al. 2009). Surveys were checked for completion upon receipt, and any missing data were collected by calling respondents to obtain them. All procedures were approved by Stanford University’s Institutional Review Board. Data collection and processing were completed in December 2012.

Survey

Where possible, survey items were drawn from previously used measures: the Residential Substance Abuse and Psychiatric Programs Inventory (Timko 1995, 1996); and Bennett and Lawson’s (1994), and Collins and Spencer’s (1999) surveys of SUDPs and IPV-related programmes. An initial draft of the survey was pretested with six programme directors (three SUDP, three BIP) selected at random from the potential participant pool. Feedback from the pretest was used to finalise the survey.

The survey ascertained programme aggregate client characteristics, organisational factors and within-programme practices (assessment, treatment and monitoring of IPV in SUDPs and of SUDs in BIPs) and cross-programme practices (service centralisation, staff cross-training and treatment integration). It also assessed programme-level outcomes among clients leaving the programme in the past year: rates of programme completion (‘What percentage of the clients who left your programme in the past 12 months completed the programme [i.e. did not drop out or were terminated prematurely]?’), substance use (‘What percentage of the clients who left your programme in the past 12 months were using alcohol and/or drugs at discharge?’) and IPV perpetration (‘What percentage of the clients who left your programme in the past 12 months were perpetrating IPV or battering at discharge?’). Specific items are described in the Results section.

Evidence supports the validity of outcomes at the programme (client aggregate) level in that they are relatively stable (not sensitive to changes in the individual making the report or to turnover in the client or staff population) and have convergent and discriminate validity (Timko & Moos 1998a,b). More generally, research shows that SUDP directors, including those serving offenders, provide valid and reliable data on programme practices and their determinants and outcomes (Timko 1995, 1996, Henderson et al. 2008, Herbeck et al. 2008). In this study, the validity and reliability of the data were supported in that 40% of BIP, and 45% of SUDP, directors reviewed programme records themselves and/or with colleagues to provide outcome data, and the remainder checked their responses and stated that they were confident in their answers.

Data analysis

Analyses were conducted using SPSS Version 21. Variables with positively skewed distributions were log-transformed prior to analysis (staff–client ratio, annual operating budget).

We first examined interrelationships of aggregated client characteristics by conducting partial correlations that controlled for programme type (SUDP, BIP). We then examined associations, within SUDPs or BIPs, of client, organisational and programme factors with outcomes using correlations for continuous variables, t-tests for dichotomous variables and analyses of variance (ANOVAs) for categorical variables. For example, in the first section of Table 2, within each type of programme (SUDPs in the left-hand column, BIPs in the right-hand column), we present correlations between each aggregated client characteristic and the outcome of the percentage of clients completing the programme. In the next section (Organisational factors), we present a correlation between the number of years the programme had been in operation (the potential determinant) with the percentage of clients completing the programme (the outcome). Then, in the next row of Table 2, we present results of an ANOVA using the programme’s location as rural, suburban or urban (the potential determinant) to compare the mean percentage of clients who completed the programme.

Table 2.

Factors associated with programme completion

SUDPs
(N = 241)		 BIPs
(N = 235)
Client factors – percent of clients (r)
  Male 0.133* −0.040
  Hispanic −0.104 0.074
  White, non-Hispanic 0.165** −0.024
  Under age 40 −0.161* −0.114
  Married 0.017 0.028
  College graduate 0.257*** 0.114
  Employed 0.146* 0.073
  Homeless −0.059 0.064
  In poverty −0.258*** −0.063
  Mandated to programme −0.046 0.066
  Dually diagnosed 0.051 −0.057
  Alcohol use disorder 0.008 0.021
  Drug use disorder −0.108 −0.101
  Former arrestees
    For substance-related reasons −0.063 −0.067
    For IPV −0.041 0.027
Organisational factors
  Years of operation (r) −0.051 0.039
  Location (M, SD)
    Rural 59.3 (21.3) 66.4 (28.2)
    Suburban 62.6 (23.7) 70.2 (23.2)
    Urban 59.0 (23.6) 67.1 (26.3)
    F 0.27 0.35
  Ownership (M, SD)
    Public 51.8a (20.6) 66.3 (26.6)
    Private, not for profit 56.6b (23.3) 65.0 (26.5)
    Private, for profit 72.3ab (19.5) 71.1 (25.9)
    F 12.8*** 1.4
  Number of: (r)
    Clients −0.165** −0.109
    Paid staff −0.173** −0.127*
    Paid staff in direct service −0.138* −0.092
    Paid staff with prof. degree −0.042 −0.046
  Staff–client ratio (r) 0.066 0.023
  Annual operating budget (r) −0.161* 0.052
  Per cent of budget from: (r)
    Government sources −0.306*** −0.126*
    Private sources 0.024 −0.130*
    Client fees 0.317*** 0.189**
Programme factors: in-programme practices (M, SD)
  Cross problem is assessed among potential clients
    No 61.1 (22.6) 51.0 (29.9)
    Yes 59.2 (23.3) 69.0 (25.2)
    t 0.58 −2.64*
  When client has cross problem, makes a contract to refrain during treatment
    No 55.8 (24.1) 66.8 (26.4)
    Yes 64.0 (21.2) 67.4 (25.8)
    t −2.41* −0.16
  Has at least one service for cross problem
    No 58.5 (23.5) 66.9 (27.3)
    Yes 60.4 (22.9) 68.3 (25.0)
    t −0.58 −0.41
Programme factors:
  Cross-programme practices (M, SD)
  To get help for both problems, potential clients go to only one location
    No 57.8 (22.9) 68.8 (26.1)
    Yes 63.3 (23.2) 67.2 (25.3)
    t −1.65* 0.45
Staff is trained in cross problem
    No 57.2 (22.8) 65.8 (26.8)
    Yes 64.3 (23.2) 68.4 (25.6)
    t −2.20* −0.66
Programme integrates cross problem into care
    Not at all/slightly/moderately 57.8 (22.5) 66.4 (25.9)
    Strongly/very strongly 71.2 (22.2) 68.9 (25.9)
    t −3.20** −0.71
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SUDP, substance use disorder programme; BIP, batterer intervention programme; IPV, intimate partner violence; (r) indicates that a correlation was computed between the factor and the outcome (programme completion); (M, SD) indicates that a -test (for dichotomous factors) or an analysis of variance (for categorical factors) was conducted. Means that share a superscript are significantly different at P < 0.05.

*

P < 0.05,

**

P < 0.01,

***

P < 0.001.

When the association between an organisational or programme factor and the outcome was significant, we conducted an additional analysis. This new analysis examined if the association was still significant when controlling for aggregated client characteristics significantly associated with the outcome. It consisted of a partial correlation when the independent variable was continuous, and an analysis of covariance when the independent variable was categorical.

Results

We obtained completed surveys from 241 SUDPs and 235 BIPs (response rates of 71% and 69% respectively). SUDPs’ average length of treatment obtained by clients was about 6 months (mean = 191.5 days, SD = 165.3). The majority (75% or more) of SUDPs offered the SUD-related services of individual counselling, group counselling, continuing care or case management. In BIPs, the average length of treatment obtained was 1 year (mean = 365.4 days, SD = 22.2). The majority of BIPs offered counselling for IPV perpetration in groups for men only (98.3%) and for women only (74.4%), and group or individual anger management counselling (60.7%).

Client characteristics

Table 1 shows intercorrelations of programmes’ client characteristics. Generally, as expected, clients who were Hispanic or non-white, younger and of lower socioeconomic status were more likely to be involved with the criminal justice system. These results lend further support to the validity and reliability of the survey data.

Table 1.

Partial correlations among client characteristics, controlling for programme type (SUDP or BIP)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1. Male
2. Hispanic 0.04
3. White −0.03 −0.64
4. <40 −0.11 0.08 −0.15
5. Married 0.15 0.04 −0.03 −0.03
6. College 0.01 −0.22 0.26 −0.33 0.11
7. Employed 0.13 0.04 0.16 −0.21 0.22 0.44
8. Homeless −0.04 −0.05 −0.07 0.14 −0.13 −0.14 −0.36
9. Poverty 0.04 0.25 −0.36 0.40 −0.10 −0.67 −0.52 0.24
10. Mandated 0.32 0.15 −0.13 0.14 0.16 −0.27 −0.08 −0.04 0.34
11. Dual diagnosis −0.12 −0.18 0.10 0.02 0.02 0.12 0.03 0.17 −0.11 −0.12
12. AUD −0.06 0.03 0.03 −0.20 −0.02 0.16 0.24 −0.05 −0.23 −0.21 0.07
13. DUD −0.08 0.04 −0.03 −0.10 −0.08 −0.04 −0.06 0.08 −0.04 −0.03 −0.16 0.19
14. Substance 0.24 0.12 −0.12 0.18 0.03 −0.37 −0.33 0.12 0.45 0.61 −0.04 −0.20 0.01
15. IPV 0.05 0.05 −0.03 0.11 0.05 −0.02 −0.15 0.19 0.11 0.01 −0.04 −0.13 −0.06 0.06
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SUDP, substance use disorder programme; BIP, batterer intervention programme; AUD, alcohol use disorder; DUD, drug use disorder; Substance, arrested for substance-related reasons; IPV, arrested for IPV perpetration. Correlations in bold are significant at P < 0.05.

Programme completion

In SUDPs, the average rate of programme completion was 59.8% (SD = 23.1%) (not tabled). Aggregate client characteristics were associated with higher programme completion rates in SUDPs: male, white, older age, college graduate, employed and having an income above the poverty level (Table 2). The organisational factor of private, for-profit ownership was associated with higher rates of clients completing the programme. In addition, larger programmes – indi cated by greater numbers of clients and staff members – had lower rates of programme completion. Programmes with larger operating budgets, and those obtaining a larger percentage of funds from government sources, had lower completion rates, whereas those depending more on client fees had higher completion rates. In addition, the in-pro gramme practice of clients with battering histories contracting to not engage in violence during SUD treatment was associated with programme completion, as were cross-programme practices. Specifically, when clients could obtain help for both substance abuse and violence problems at one location, staff members were trained in the cross problem, and when the programme integrated the cross problem into its care practices, clients were more likely to complete the programme.

When significant client characteristics were controlled, factors still significantly associated with programme completion were the organisational factors of private, for-profit ownership (F(8, 232) = 8.88, P < 0.001) and having fewer paid staff and fewer paid staff in direct service (r = −0.215, P = 0.04, and r = −0.262, P < 0.001, respectively), and the linkage practices of client contracting (F(7, 233) = 2.87, P = 0.04) and of obtaining help at one location (F(7, 233) = 6.51, P = 0.01).

BIPs had an average completion rate of 67.8% (SD = 25.8%) (not tabled). Compared to SUDPs, fewer factors were associated with programme completion in BIPs, but significant factors were consistent between programme types (Table 2). Having more paid staff members was associated with a lower completion rate, as was having a higher proportion of the budget from government sources, and a lower proportion from client fees. In addition, depending more on private funding sources was associated with lower completion rates. In BIPs, assessing substance abuse among potential clients was associated with a higher rate of programme completion.

Substance use

In SUDPs, the average rate at which clients were using alcohol or drugs at discharge was 23.2% (SD = 21.3%) (not tabled). Substance use at discharge was associated with a client population that was Hispanic, with stable housing and mandated to treatment (Table 3). Programmes with more clients, and a lower staff–client ratio, had a higher rate of clients using substances at discharge. In addition, substance use was more likely when funding came from government sources, and less frequent when funding came from client fees. Finally, clients’ substance use at discharge was more likely in programmes in which staff members were not trained in IPV. When significant client characteristics were controlled, programmes with more clients (r = 0.306, P < 0.001), a lower staff–client ratio (r = −0.186, P = 0.04), more funding from government sources (r = 0.229, P = 0.03) and less funding from client fees (r = −0.251, P = 0.01) had a higher rate of client substance use at discharge.

Table 3.

Factors associated with substance use at discharge

SUDPs
(N = 241)		 BIPs
(N = 235)
Client factors – per cent of clients (r)
  Male 0.040 −0.004
  Hispanic 0.126* −0.079
  White, non-Hispanic −0.082 0.125
  Under age 40 0.020 0.258*
  Married 0.072 −0.044
  College graduate −0.082 −0.046
  Employed 0.056 −0.110
  Homeless −0.165* 0.139
  In poverty 0.062 0.068
  Mandated to programme 0.144* 0.096
  Dually diagnosed 0.079 0.021
  Has alcohol use disorder 0.012 0.189*
  Has drug use disorder 0.105 0.180
  Former arrestees
    For substance-related reasons 0.100 0.257**
    For IPV −0.158 0.060
Organisational factors
  Years of operation (r) 0.026 −0.147
  Location (M, SD)
    Rural 27.2 (22.1) 40.2a (36.1)
    Suburban 21.6 (21.8) 39.7b (32.8)
    Urban 22.4 (20.5) 22.9ab (25.2)
    F 1.02 4.46**
  Ownership (M, SD)
    Public 28.3 (21.2) 10.5 (13.1)
    Private, not for profit 24.1 (21.6) 28.0 (28.2)
    Private, for profit 18.6 (19.6) 33.3 (32.1)
    F 2.14 1.28
  Number of: (r)
    Clients 0.275*** 0.103
    Paid staff 0.021 −0.023
    Paid staff in direct service 0.041 0.000
    Paid staff with prof. degree −0.075 0.080
  Staff–client ratio −0.260*** −0.126
  Annual operating budget (r) 0.109 0.087
  Per cent of budget from: (r)
    Government sources 0.234** 0.008
    Private sources −0.067 −0.174*
    Client fees −0.242*** 0.114
Programme factors: in-programme practices
  Cross problem is assessed among potential clients (M, SD)
    No 25.3 (21.0) 33.8 (34.2)
Yes 22.3 (21.3) 29.7 (29.9)
    t 0.91 0.37
  When client has cross problem, makes a contract to refrain during treatment
    No 23.7 (19.2) 30.2 (31.1)
    Yes 22.7 (22.0) 25.2 (26.1)
    t 0.75 0.44
Has at least one service for cross problem
    No 22.9 (20.6) 30.7 (31.4)
    Yes 23.4 (21.6) 28.4 (27.3)
    t −0.15 0.37
Programme factors: cross-programme practices
  To get help for both problems, potential clients go to only one location
    No 25.3 (22.9) 29.3 (30.5)
    Yes 21.2 (18.5) 29.4 (29.5)
    t 1.20 −0.03
  Staff is trained in cross problem
    No 25.4 (23.1) 36.0 (32.7)
    Yes 20.3 (17.9) 28.2 (29.0)
    t 1.73* 1.18
Programme integrates cross problem into care
  Not at all/slightly/moderately 24.5 (21.4) 28.6 (30.8)
  Strong/very strongly 17.9 (20.3) 31.0 (29.8)
  t 0.16 −0.41
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SUDP, substance use disorder programme; BIP, batterer intervention programme; IPV, intimate partner violence; (r) indicates that a correlation was computed between the factor and the outcome (substance use at discharge); (M, SD) indicates that a t-test (for dichotomous factors) or an analysis of variance (for categorical factors) was conducted. Means that share a superscript are significantly different at P < 0.05.

*

P < 0.05,

**

P < 0.01,

***

P < 0.001.

In BIPs, an average of 30.0% (SD = 30.1%) of clients was using substances at discharge (not tabled). This outcome was more likely when clients were younger, had an alcohol use disorder and had been arrested for substance-related reasons (Table 3). Clients’ substance use at discharge was less likely in programmes located in urban settings and when the programme’s budget was more dependent on private sources (Table 3), even with significant client characteristics controlled (for location, F(5, 229) = 3.63, P = 0.03; for budgets from private sources, r = 0.299; P = 0.02).

IPV perpetration

In SUDPs, the rate of IPV perpetration at programme discharge was 2.6% (SD = 5.2%) (not tabled). IPV perpetration occurring at discharge was associated with the aggregate client characteristics of being male, Hispanic, non-white, poor, free of co-occurring mental health problems and having been arrested for substance-related reasons (Table 4). It was also associated with more funding from government sources, and less from client fees. Programmes having at least one service for IPV and staff trained in IPV had clients who were less likely to be perpetrating IPV at discharge.

Table 4.

Factors associated with IPV perpetration at discharge

SUDPs
(N = 241)		 BIPs
(N = 235)
Client factors – per cent of clients: (r)
  Male 0.167* −0.015
  Hispanic 0.185* −0.025
  White, non-Hispanic −0.246** −0.017
  Under age 40 0.091 0.117
  Married 0.050 −0.119
  College graduate −0.153 −0.021
  Employed −0.136 −0.067
  Homeless −0.045 0.191*
  In poverty 0.201* 0.066
  Mandated to programme 0.155 0.095
  Dually diagnosed −0.189* 0.003
  Has alcohol use disorder −0.026 0.093
  Has drug use disorder 0.049 0.032
  Former arrestees
    For substance-related reasons 0.177* 0.079
    For IPV 0.031 −0.032
Organisational factors
  Years of operation (r) 0.068 −0.089
  Location (M, SD)
    Rural 1.9 (3.1) 10.6 (19.2)
    Suburban 2.2 (4.0) 8.3 (13.7)
    Urban 3.0 (6.2) 8.1 (14.6)
    F 0.51 0.31
  Ownership (M, SD)
    Public 2.6 (5.5) 4.3 (4.9)
    Private, not for profit 2.8 (4.5) 7.6 (11.9)
    Private, for profit 2.0 (6.4) 10.1 (18.6)
    F 0.254 0.181
  Number of: (r)
    Clients 0.134 0.122
    Paid staff −0.024 0.133*
    Paid staff in direct service −0.050 0.124
    Paid staff with prof. degree −0.132 0.156*
  Staff–client ratio −0.123 −0.026
  Annual operating budget (r) −0.105 0.082
  Per cent of budget from: (r)
    Government sources 0.217* 0.034
    Private sources −0.053 −0.053
    Client fees −0.180* −0.011
Programme factors: in-programme practices
  Cross problem is assessed among potential clients (M, SD)
    No 3.1 (6.8) 8.8 (15.5)
    Yes 2.4 (4.6) 7.2 (10.9)
    t 0.60 0.32
  When client has cross problem, makes a contract to refrain during treatment
    No 2.8 (5.2) 10.6 (19.8)
    Yes 2.2 (3.0) 7.3 (13.1)
    t 0.56 0.25
  Has at least one service for cross problem
    No 3.1 (5.8) 9.7 (17.5)
    Yes 1.2 (2.7) 6.8 (9.7)
    t 2.33* 1.33
Programme factors: cross-programme practices
  To get help for both problems, potential clients go to only one location
    No 3.4 (5.7) 9.7 (17.0)
    Yes 2.0 (4.9) 7.8 (13.7)
    t 1.34 0.74
  Staff is trained in cross problem
    No 3.5 (5.4) 10.1 (17.2)
    Yes 1.3 (2.3) 8.4 (14.7)
    t 2.67** 0.63
Programme integrates cross problem into care
    Not at all/slightly/moderately 4.8 (7.1) 7.6 (12.7)
    Strongly/very strongly 2.0 (4.4) 9.8 (17.8)
    t 1.93 1.25
Open in a new tab

SUDP, substance use disorder programme; BIP, batterer intervention programme; IPV, intimate partner violence; (r) indicates that a correlation was computed between the factor and the outcome (IPV perpetration at discharge); (M, SD) indicates that a t-test (for dichotomous factors) or an analysis of variance (for categorical variables) was conducted.

*

P < 0.05,

**

P < 0.01.

In BIPs, IPV perpetration occurring at discharge (mean = 8.7%, SD = 15.2%; not tabled) was associated with only three factors: having more homeless clients, paid staff and paid staff with professional degrees (Table 4). However, in both SUDPs and BIPs, organisational and programme factors were not associated with IPV rates after significant client characteristics were controlled.

Discussion

This study of SUDPs and BIPs found that smaller, private-for-profit programmes had better client outcomes. In addition, a different client profile was associated with each outcome, suggesting that risk factors for one outcome, such as programme dropout, may not generalise to those for other outcomes, such as continued substance use or IPV perpetration. Relatively few client, organisational and programme factors were associated with outcomes in BIPs, suggesting that more research is needed to fully identify the determinants of outcomes in these justice system programmes.

Client characteristics

As in previous studies (Stack et al. 2000, Heinrich & Fournier 2004, Brecht et al. 2005, Zanis et al. 2009, Darke et al. 2012), we found that SUDPs having more clients of particular sociodemographic characteristics – female, non-white, younger, less educated, unemployed, lower income – had poorer programme completion rates. There is a trend towards greater substance use severity among women (Campbell et al. 2009) who face unique barriers that may hinder completion of treatment, such as lack of childcare, fear of losing child custody and trauma history (Greenfield et al. 2007). Patients admitted for SUD treatment are also increasingly diverse in terms of race and ethnicity, and those who are more socioeconomically disad-vantaged may be more difficult to retain in treatment (Brecht et al. 2005). As Beyko and Wong (2005) cautioned, it is important to avoid creating an attrition profile for clients; this could undermine their chances of being accepted into treatment and for success in treatment. However, awareness of client factors associated with programme dropout may alert staff to the need for more effective efforts to retain them.

In SUDPs, different client characteristics were associated with the outcomes of substance use and IPV perpetration at discharge than with programme completion. Thus, attrition profiles may not carryover to profiles for other important outcomes. Client characteristics of being non-Hispanic, homeless and not mandated to the programme were associated with lower rates of client substance use at discharge; and, having more female, non-Hispanic and dually diagnosed clients, but fewer non-white, poor and previously arrested clients, were associated with lower rates of IPV perpetration. Studies have linked acculturation stress, which we did not assess, to substance use among Hispanic samples (Buchanan & Smokowski 2009). In addition, culturally appropriate programmes for Hispanic IPV perpetrators have been developed (Welland & Ribner 2010), based in part on the rapid growth of this population and recognition of IPV’s negative consequences within Hispanic communities (Klevens et al. 2007). Within BIPs, men of colour tended to also have other characteristics associated with poorer treatment outcomes, such as younger age, less education and unemployment (Gondolf 1996).

Although there is a strong association between homelessness and substance use (Tsai et al. 2014), a minority of homeless individuals may use substances while receiving help resources such as shelter (Bannon et al. 2012). Similar to our finding, Howard and McCaughrin (1996) found that SUDPs with higher proportions of clients mandated to treatment had a greater rate of clients failing to comply with their treatment plan; however, others reported that mandated and non-mandated clients had comparable therapeutic gains (Kelly et al. 2005). The extent to which SUD treatment is beneficial for mandated clients has yet to be determined. The association of dual diagnosis status with IPV perpetration also remains unclear; although there is a limited literature on dual diagnoses in victims of IPV (Cohen et al. 2013), we could not identify studies of dual diagnosis as a predictor of IPV perpetration.

In BIPs, only having younger clients with alcohol use disorders and arrest histories was associated with more substance use at discharge. And, having more homeless clients was associated with more IPV perpetration at discharge. Although it is well known that homelessness increases among women fleeing abusive homes (Pavao et al. 2007), there has been little examination of homelessness as a predictor of IPV perpetration (Frye et al. 2007).

Organisational factors

In SUDPs, private, for-profit programmes had higher client completion rates than did public or private, not-for-profit programmes. Consistently, in both SUDPs and BIPs, those with lower percentages of budgets from government sources, and higher percentages from client fees, had higher completion rates. In SUDPs, less reliance on government sources, and more on client fees, was also associated with less substance use at discharge. Public programmes may be challenged by having more resource constraints (Campbell et al. 2009).

In addition, the advantage of private-for-profit programmes for client retention may reflect client populations with less severe problems, more ability to pay for longer treatment and fewer barriers to treatment (e.g. lack of transportation or childcare). That is, private, for-profit programmes may be more likely to restrict access to or duration of treatment for clients unable to pay (Nahra et al. 2009), thus limiting indigent clients obtaining and completing care (Friedmann et al. 2003). Accordingly, we found that SUDP directors reported lower completion rates when programmes had more clients living in poverty. For-profit SUDPs, in addition to relying more on clients who can pay treatment fees, may also have clients with less severe disorders who require fewer costly ancillary services and co-ordination of care (Nahra et al. 2009). Generally, SUDPs that offer greater access to care, such as to client populations that are more racially and ethnically diverse, may have poorer client outcomes (Nahra et al. 2009), which fits with our findings that programmes with more white clients had better outcomes in terms of programme completion and less IPV perpetration at discharge.

We found that in SUDPs, larger programmes, indicated by having more paid staff and more paid staff in direct service, had lower rates of programme completion. In addition, SUDPs with more clients had higher substance use rates among clients at discharge. Similarly, in BIPs, those with more paid staff had lower programme completion rates. Poorer client engagement has been implicated as a link between larger programme size and poorer client outcomes (Broome et al. 2007). In programmes of larger size, the chances of clients failing to receive appropriate attention increases. Accordingly, in SUDPs, higher staff–client ratios, which are indicative of higher quality care (Stanton & Rutherford 2004), were associated with lower substance use rates at discharge.

In- and cross-programme practices

In BIPs, assessment of substance use among potential clients was associated with higher completion rates, possibly because clients with alcohol or drug problems were not admitted. Programme completion rates were higher in SUDPs when clients could obtain help for both substance abuse and violence problems at one location (Weisner et al. 2001), and when clients contracted to not engage in IPV perpetration. Providing such services targeted at IPV may be challenging in SUDPs because it requires resources such as qualified staff members (Campbell et al. 2009).

Despite findings that efforts to integrate violence-related services into SUD care improves outcomes, in practice, substance abuse and IPV perpetration have often been viewed as separate problems with different interventions (Bennett 2008). Parallel treatment, in which help is obtained for both substance abuse and violence at the same time but in separate programmes, reduces substance abuse and domestic violence (Bennett 2008). The disadvantage of parallel substance abuse and batterer programmes is that time and financial commitments may become a burden, engender resistance in clients and their family members, and increase perceived hardship in an already-difficult situation (Bennett 2008). In addition, without explicit integration of treatment, clients may have difficulty managing the cognitive and affective components of battering intervention treatment during early abstinence because individuals in early abstinence often experience memory loss, emotional dysregula-tion and poor impulse control (Fox et al. 2007, 2008).

Research also suggests that integrated substance abuse and family relationship treatment reduces both substance abuse and family violence for some couples (Brannen & Rubin 1996, O’Farrell et al. 1999, 2004). Importantly, such integrated treatment should include components to protect victims’ safety (McCollum & Stith 2008, Johnson 2009). For some couples, improvements in relationship functioning and substance use outcomes jointly account for reductions in IPV perpetration associated with SUD treatment (Murphy & Ting 2010).

Limitations

Limitations are that we studied programmes in only one state using a cross-sectional design with programme-level outcomes. Thus, although we examined associations of client characteristics with programme outcomes, we cannot be certain that clients with the identified characteristics achieve those outcomes. To augment programme-level findings, investigations are needed of organisational influences on individual differences among substance abuse and batterer programme clients. We did not independently audit each programme; thus, the accuracy of data presented is based on programme directors’ reports, which may slightly differ in some cases from those of other staff members such as clinicians (McGovern et al. 2006).

In terms of strengths, we achieved high response rates for this type of survey in samples of SUDPs and BIPs, and, guided by a conceptual model, collected a substantial amount of useful information from both types of programmes to understand determinants of outcomes.

Conclusions

Publicly owned and larger programmes, and SUDPs that do not utilise staff to integrate IPV-related needs, may be at risk of poorer client outcomes because they are more accessible to clients with fewer resources. However, there are many large, publicly owned programmes that achieve positive client outcomes. Poorly performing programmes may be able to take lessons from those performing well. A programme might designate a change team, involving clients, to better understand client needs, gather ideas for improvement from other, well-performing programmes, and test improvements to address client outcomes in rapid cycles (McCarty & Chandler 2009). Poorly performing programmes on client outcomes could partner with well-performing programmes to implement more comprehensive services for clients. Because the consequences of substance abuse and violence can be quite severe, including permanent injury or death to victims, the community of researchers, providers and policy makers needs to continue to design better programmes and systems to achieve better health outcomes.

What is known about this topic

  • Associations of substance abuse and intimate partner violence are robust.

  • Understanding client, programme and organisational characteristics of community programmes as predictors of health outcomes may improve treatment for dual problems.

  • Improved public health requires better understanding violence in substance abuse treatment, and substance abuse in violence programmes, to optimally integrate care.

What this paper adds

  • Small, private-for-profit programmes had better client outcomes: more programme completion, and less substance use and violence perpetration.

  • Different client profiles were associated with each outcome; risk factors for one outcome may not generalise to others.

  • Outcomes were better when the programme trained staff in violence prevention and integrated substance abuse and violence-related services.

Acknowledgements

This work was supported by the Robert Wood Johnson Foundation and the Department of Veterans Affairs (VA) Office of Research and Development (Health Services Research and Development Service, RCS 00-001). The views expressed here are of the authors. We thank Ruth Cronkite for her earlier contributions to this project.

References

  1. Babcock JC, Green CE, Robie C. Does batterers’ treatment work? Clinical Psychology Review. 2004;23(8):1023–1053. doi: 10.1016/j.cpr.2002.07.001. [DOI] [PubMed] [Google Scholar]
  2. Bannon WM, Jr, Beharie N, Olshtain-Mann O, et al. Youth substance use in a context of family homelessness. Children and Youth Services Review. 2012;34(1):1–7. doi: 10.1016/j.childyouth.2010.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bennett LW. Substance abuse by men in partner abuse intervention programs: current issues and promising trends. Violence and Victims. 2008;23(2):236–248. doi: 10.1891/0886-6708.23.2.236. [DOI] [PubMed] [Google Scholar]
  4. Bennett LW, Lawson M. Barriers to cooperation between domestic violence and substance abuse programs. Families in Society. 1994;75:277–286. [Google Scholar]
  5. Bennett LW, Williams OJ. Batterer treatment programs. In: Renzetti CM, Edleson JL, Bergen RK, editors. Sourcebook on Violence Against Women. Thousand Oaks, California: Sage Publications; 2001. pp. 261–277. [Google Scholar]
  6. Beyko MJ, Wong SCP. Predictors of treatment attrition as indicators for program improvement not offender shortcomings: a study of sex offender treatment attrition. Sexual Abuse: A Journal of Research and Treatment. 2005;17(4):375–389. doi: 10.1177/107906320501700403. [DOI] [PubMed] [Google Scholar]
  7. Brannen SJ, Rubin A. Comparing the effectiveness of gender-specific and couples groups in a court-mandated spouse abuse treatment program. Research on Social Work Practice. 1996;6(4):405–424. [Google Scholar]
  8. Brecht ML, Greenwell L, Anglin MD. Metham-phetamine treatment: trends and predictors of retention and completion in a large state treatment system (1992–2002) Journal of Substance Abuse Treatment. 2005;29(4):295–306. doi: 10.1016/j.jsat.2005.08.012. [DOI] [PubMed] [Google Scholar]
  9. Bride BE, Abraham AJ, Roman PM. Organisational factors associated with the use of contingency management in publicly funded substance abuse treatment centres. Journal of Substance Abuse Treatment. 2011;40(1):87–94. doi: 10.1016/j.jsat.2010.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Broome KM, Flynn PM, Knight DK, Simpson DD. Program structure, staff perceptions, and client engagement in treatment. Journal of Substance Abuse Treatment. 2007;33(2):149–158. doi: 10.1016/j.jsat.2006.12.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Buchanan RL, Smokowski PR. Pathways from acculturation stress to substance use among Latino adolescents. Substance Use and Misuse. 2009;44(5):740–762. doi: 10.1080/10826080802544216. [DOI] [PubMed] [Google Scholar]
  12. Campbell CI, Alexander JA, Lemak CH. Organisational determinants of outpatient substance abuse treatment duration in women. Journal of Substance Abuse Treatment. 2009;37(1):64–72. doi: 10.1016/j.jsat.2008.09.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Catlett BS, Toews ML, Walilko V. Men’s gendered constructions of intimate partner violence as predictors of court-mandated batterer treatment drop out. American Journal of Community Psychology. 2010;45(1–2):107–123. doi: 10.1007/s10464-009-9292-2. [DOI] [PubMed] [Google Scholar]
  14. Cohen LR, Field C, Campbell AN, Hien DA. Intimate partner violence outcomes in women with PTSD and substance use. Addictive Behaviors. 2013;38(7):2325–2332. doi: 10.1016/j.addbeh.2013.03.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Collins JJ, Spencer DL. Linkage of Domestic Violence and Substance Abuse Services. North Carolina: Research Triangle Institute, Research Triangle Park; 1999. [Google Scholar]
  16. Coulter M, VandeWeerd C. Reducing domestic violence and other criminal recidivism. Violence and Victims. 2009;24(2):139–152. doi: 10.1891/0886-6708.24.2.139. [DOI] [PubMed] [Google Scholar]
  17. Dalton B. What’s going on out there? A survey of batterer intervention programs. Journal of Aggression, Maltreatment, and Trauma. 2007;15(1):59–74. [Google Scholar]
  18. Daly JE, Pelowski S. Predictors of dropout among men who batter. Violence and Victims. 2000;15(2):137–160. [PubMed] [Google Scholar]
  19. Darke S, Campbell G, Popple G. Retention, early dropout and treatment completion among therapeutic community admissions. Drug and Alcohol Review. 2012;31(1):64–71. doi: 10.1111/j.1465-3362.2011.00298.x. [DOI] [PubMed] [Google Scholar]
  20. D’Aunno T. The role of organisation and management in substance abuse treatment: review and roadmap. Journal of Substance Abuse Treatment. 2006;31(3):221–233. doi: 10.1016/j.jsat.2006.06.016. [DOI] [PubMed] [Google Scholar]
  21. Dillman DA, Smyth JD, Christian LM. Internet, Mail, and Mixed-Mode Surveys: The Tailored Design Method. Hoboken, New Jersey: John Wiley & Sons Inc; 2009. [Google Scholar]
  22. Eckhardt CI, Murphy C, Black D, Suhr L. Intervention programs for perpetrators of intimate partner violence. Public Health Reports. 2006;121(4):369–381. doi: 10.1177/003335490612100405. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Finney JW, Moyer A, Swearingen CE. Outcome variables and their assessment in alcohol treatment studies. Alcoholism: Clinical and Experimental Research. 2003;27(10):1671–1679. doi: 10.1097/01.ALC.0000091236.14003.E1. [DOI] [PubMed] [Google Scholar]
  24. Fletcher BW, Lehman WEK, Wexler HK, Melnick G, Taxman FS, Young DW. Measuring collaboration and integration activities in criminal justice and substance abuse treatment agencies. Drug and Alcohol Dependence. 2009;103S:S54–S64. doi: 10.1016/j.drugalcdep.2009.01.001. [DOI] [PubMed] [Google Scholar]
  25. Flynn PM, Knight DK, Godley MD, Knudsen HK. Introduction to the special issue on organisational dynamics within substance abuse treatment. Journal of Substance Abuse Treatment. 2012;42(2):109–115. doi: 10.1016/j.jsat.2011.10.029. [DOI] [PubMed] [Google Scholar]
  26. Fox HC, Alexrod P, Paliwal P, Sleeper J, Sinha R. Difficulties in emotional regulation and impulse control during cocaine abstinence. Drug and Alcohol Dependence. 2007;89(2–3):298–301. doi: 10.1016/j.drugalcdep.2006.12.026. [DOI] [PubMed] [Google Scholar]
  27. Fox HC, Hong KA, Sinha R. Difficulties in emotion regulation and impulse control in recently abstinent alcoholics compared with social drinkers. Addictive Behaviors. 2008;33(2):388–394. doi: 10.1016/j.addbeh.2007.10.002. [DOI] [PubMed] [Google Scholar]
  28. Friedmann PD, Lemon S, Stein MD, D’Aunno TA. Accessibility of addiction treatment. Health Services Research. 2003;38(3):887–903. doi: 10.1111/1475-6773.00151. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Friedmann PD, Alexander JA, Yey Y, Nahra T, Soliman S, Pollack HA. Duration of nonmethadone outpatient treatment. Substance Abuse. 2006;27(3):47–53. doi: 10.1300/J465v27n03_07. [DOI] [PubMed] [Google Scholar]
  30. Frye V, Latka MH, Wu Y, et al. Intimate partner violence perpetration against main female partners among HIV-positive male injection drug users. Journal of Acquired Immune deficiency Syndromes. 2007;46(Suppl 2):S101–S109. doi: 10.1097/QAI.0b013e31815767e6. [DOI] [PubMed] [Google Scholar]
  31. Gondolf EW. Characteristics of Batterers in a Multi-Site Evaluation of Batterer Intervention Systems. Minnesota: Minnesota Center Against Violence and Abuse, Minneapolis; 1996. [Google Scholar]
  32. Greenfield SF, Brooks AJ, Gordon SM, et al. Substance abuse treatment entry, retention, and outcome in women. Drug and Alcohol Dependence. 2007;86(1):1–21. doi: 10.1016/j.drugalcdep.2006.05.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Grella CE, Greenwell L, Prendergast M, et al. Organisational characteristics of drug abuse treatment programs for offenders. Journal of Substance Abuse Treatment. 2007;32(3):291–300. doi: 10.1016/j.jsat.2007.01.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Heinrich C, Fournier E. Dimensions of publicness and performance in substance abuse treatment organisations. Journal of Policy Analysis and Management. 2004;23(1):49–70. doi: 10.1002/pam.10178. [DOI] [PubMed] [Google Scholar]
  35. Henderson CE, Taxman FS, Young DW. A Rasch model analysis of evidence-based treatment practices used in the criminal justice system. Drug and Alcohol Dependence. 2008;93(1–2):163–175. doi: 10.1016/j.drugalcdep.2007.09.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Herbeck DM, Hser Y, Teruya C. Empirically supported substance abuse treatment approaches. Addictive Behaviors. 2008;33(5):669–712. doi: 10.1016/j.addbeh.2007.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Howard DL, McCaughrin WC. The treatment effectiveness of outpatient substance misuse treatment organisations between court-mandated and voluntary clients. Substance Use and Misuse. 1996;31(7):895–926. doi: 10.3109/10826089609063962. [DOI] [PubMed] [Google Scholar]
  38. Johnson MP. Differentiating among types of domestic violence. In: Peters HE, Dush CMK, editors. Marriage and Family: Perspectives and Complexities. New York: Columbia University Press; 2009. pp. 281–297. [Google Scholar]
  39. Jones AS, Goldolf EW. Time varying risk factors for reassault among batterer program participants. Journal of Family Violence. 2001;16(4):345–359. [Google Scholar]
  40. Kelly JF, Finney JW, Moos RH. Substance use disorder patients who are mandated to treatment: characteristics, treatment process, and 1- and 5-year outcomes. Journal of Substance Abuse Treatment. 2005;28(3):213–223. doi: 10.1016/j.jsat.2004.10.014. [DOI] [PubMed] [Google Scholar]
  41. Klevens J, Shelley G, Clavel-Arcas C, et al. Latinos’ perspectives and experiences with intimate partner violence. Violence Against Women. 2007;13(2):141–158. doi: 10.1177/1077801206296980. [DOI] [PubMed] [Google Scholar]
  42. Lemak CH, Alexander JA. Factors that influence staffing of outpatient substance abuse treatment programs. Psychiatric Services. 2005;56(8):934–939. doi: 10.1176/appi.ps.56.8.934. [DOI] [PubMed] [Google Scholar]
  43. Macy RJ, Goodbourn M. Promoting successful collaborations between domestic violence and substance abuse treatment service sectors. Trauma, Violence, and Abuse. 2012;13(4):234–251. doi: 10.1177/1524838012455874. [DOI] [PubMed] [Google Scholar]
  44. Magill M, Ray LA. Cognitive-behavioural treatment with adult alcohol and illicit drug users. Journal of Studies on Alcohol and Drugs. 2009;70(4):516–527. doi: 10.15288/jsad.2009.70.516. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. McCarty D, Chandler RK. Understanding the importance of organisational and system variables on addiction treatment services within criminal justice settings. Drug and Alcohol Dependence. 2009;103S(1):S91–S93. doi: 10.1016/j.drugalcdep.2009.03.001. [DOI] [PubMed] [Google Scholar]
  46. McCollum EE, Stith SM. Couples treatment for interpersonal violence. Violence and Victims. 2008;23(2):187–201. doi: 10.1891/0886-6708.23.2.187. [DOI] [PubMed] [Google Scholar]
  47. McGovern MP, Xie H, Segal SR, Siembab L, Drake RE. Addiction treatment services and co-occurring disorders. Journal of Substance Abuse Treatment. 2006;31(3):267–275. doi: 10.1016/j.jsat.2006.05.003. [DOI] [PubMed] [Google Scholar]
  48. Moos RH. Evaluating Treatment Environments. New Jersey: Transaction Publishers, New Brunswick; 1997. [Google Scholar]
  49. Murphy CM, Ting L. The effects of treatment for substance use problems on intimate partner violence. Aggression and Violent Behaviour. 2010;15(5):325–333. [Google Scholar]
  50. Nahra TA, Alexander J, Pollack H. Influence of ownership on access in outpatient substance abuse treatment. Journal of Substance Abuse Treatment. 2009;36(4):355–365. doi: 10.1016/j.jsat.2008.06.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. O’Farrell TJ, Van Hutton V, Murphy CM. Domestic violence before and after alcoholism treatment. Journal of Studies on Alcohol. 1999;60(3):317–321. doi: 10.15288/jsa.1999.60.317. [DOI] [PubMed] [Google Scholar]
  52. O’Farrell TJ, Murphy CM, Stephan SH, Fal-Stewart W, Murphy M. Partner violence before and after couples-based alcoholism treatment for male alcoholic patients. Journal of Consulting and Clinical Psychology. 2004;72(2):202–217. doi: 10.1037/0022-006X.72.2.202. [DOI] [PubMed] [Google Scholar]
  53. Office of National Drug Control Policy. Contemporary Drug Abuse Treatment: A Review of the Evidence Base. Washington, District of Columbia: Executive Office of the President; 2002. [Google Scholar]
  54. Olver ME, Stockdale KC, Wormith JS. A meta-analysis of predictors of offender treatment attrition and its relationship to recidivism. Journal of Consulting and Clinical Psychology. 2011;79(1):6–21. doi: 10.1037/a0022200. [DOI] [PubMed] [Google Scholar]
  55. Oser CB, Knudsen HK, Staton-Tindall M, Taxman FE, Leukefield C. The adoption of wraparound services among women-specific and nonwomen-specific substance abuse treatment programs serving criminal offenders. Drug and Alcohol Dependence. 2009;103S:S82–S90. doi: 10.1016/j.drugalcdep.2008.12.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Pavao J, Alvarez J, Baumrind N, Induni M, Kimerling R. Intimate partner violence and housing instability. American Journal of Preventative Medicine. 2007;32(2):143–146. doi: 10.1016/j.amepre.2006.10.008. [DOI] [PubMed] [Google Scholar]
  57. Rooney J, Hanson RK. Predicting attrition from treatment programs for abusive men. Journal of Family Violence. 2001;16(2):131–149. [Google Scholar]
  58. Rootman DB, Mann RE, Ferris LE, Chalin C, Adlaf E, Shuggi R. Predictors of completion status in a remedial program for male convicted drinking drivers. Journal of Studies on Alcohol and Drugs. 2005;66(3):423–427. doi: 10.15288/jsa.2005.66.423. [DOI] [PubMed] [Google Scholar]
  59. Simpson DD. A conceptual framework for drug treatment process and outcomes. Journal of Substance Abuse Treatment. 2004;27(2):99–121. doi: 10.1016/j.jsat.2004.06.001. [DOI] [PubMed] [Google Scholar]
  60. Soyka M, Schmidt P. Outpatient alcoholism treatment - 24-month outcome and predictors of outcome. Substance Abuse Treatment, Prevention, and Policy. 2009;4:4–15. doi: 10.1186/1747-597X-4-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Stack K, Cortina J, Samples C, Zapata M, Arcand LF. Race, age, and back pain as factors in completion of residential substance abuse treatment by veterans. Psychiatric Services. 2000;51(9):1157–1161. doi: 10.1176/appi.ps.51.9.1157. [DOI] [PubMed] [Google Scholar]
  62. Stalans LJ, Seng M. Identifying subgroups at high risk of dropping out of domestic batterer treatment. International Journal of Offender Therapy and Comparative Criminology. 2007;51(2):151–169. doi: 10.1177/0306624X06290204. [DOI] [PubMed] [Google Scholar]
  63. Stanton MW, Rutherford MK. Hospital Nurse Staffing and Quality of Care. Rockville, Maryland: Agency for Healthcare Research and Quality; 2004. [Google Scholar]
  64. Stuart GL, O’Farrell TJ, Temple JR. Review of the association between treatment for substance misuse and reductions in intimate partner violence. Substance Use and Misuse. 2009;44(9/10):1298–1317. doi: 10.1080/10826080902961385. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Stuart GL, Shorey RC, Moore TM, et al. Randomized clinical trial examining the incremental efficacy of a 90-minute motivational alcohol intervention as an adjunct to standard batterer intervention for men. Addiction. 2013;108(8):1376–1384. doi: 10.1111/add.12142. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Substance Abuse and Mental Health Services Administration, Office of Applied Studies. National Admissions to Substance Abuse Treatment Services. Rockville, Maryland: Substance Abuse and Mental Health Services Administration; 2010. Treatment Episode Data Set (TEDS) pp. 1998–2008. [Google Scholar]
  67. Timko C. Policies and services in residential substance abuse programs. Journal of Substance Abuse. 1995;7(1):43–59. doi: 10.1016/0899-3289(95)90305-4. [DOI] [PubMed] [Google Scholar]
  68. Timko C. Physical characteristics of residential psychiatric programs. American Journal of Community Psychology. 1996;24(1):173–192. doi: 10.1007/BF02511886. [DOI] [PubMed] [Google Scholar]
  69. Timko C, Moos RH. Determinants of the treatment climate in psychiatric and substance abuse programs. Journal of Nervous and Mental Disease. 1998a;186(2):96–103. doi: 10.1097/00005053-199802000-00005. [DOI] [PubMed] [Google Scholar]
  70. Timko C, Moos RH. Outcomes of the treatment climate in psychiatric and substance abuse programs. Journal of Clinical Psychology. 1998b;54(8):1137–1150. doi: 10.1002/(sici)1097-4679(199812)54:8<1137::aid-jclp12>3.0.co;2-0. [DOI] [PubMed] [Google Scholar]
  71. Tsai J, Kasprow WJ, Rosenheck RA. Alcohol and drug use disorders among homeless veterans. Addictive Behaviors. 2014;39(2):455–460. doi: 10.1016/j.addbeh.2013.02.002. [DOI] [PubMed] [Google Scholar]
  72. Weisner C, Mertens J, Parthasarathy S, Moore C. Integrating primary medical care with addiction treatment. Journal of the American Medical Association. 2001;286(14):1715–1723. doi: 10.1001/jama.286.14.1715. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Welland C, Ribner N. Culturally specific treatment for partner-abusive Latino men: a qualitative study to identify and implement program components. Violence and Victims. 2010;25(6):799–813. doi: 10.1891/0886-6708.25.6.799. [DOI] [PubMed] [Google Scholar]
  74. Zanis DA, Coviello DM, Lloyd JJ, Nazar BL. Predictors of drug treatment completion among parole violators. Journal of Psychoactive Drugs. 2009;41(2):173–180. doi: 10.1080/02791072.2009.10399910. [DOI] [PubMed] [Google Scholar]

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