DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 1
Differential Effectiveness of Substance Abuse Treatment
For Drug Traffickers...
DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 2
KAPLAN UNIVERSITY
Abstract
Differential Effectiveness of Substance Abuse Tre...
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traffickers are receiving treatment designed for substance users, and treatm...
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Table of Contents
List of Tables...............................................
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Acknowledgments
The author wishes to express sincere appreciation to the Res...
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The United States (US) war on drugs has been in effect since 1971 (Vulliami,...
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method to “scale back the harsh and racially disparate mandatory sentences f...
DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 8
prevention, and aftercare in various multimodality designs, of which a recen...
DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 9
with drug related crimes apart from substance abuse may not be receiving the...
DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 10
In 1977, the U.S. imprisoned 11,212 women; by 2004, that number had balloon...
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attention on providing appropriate treatment to the offender population of ...
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narcissistic values that are inherent in this culture. The author also give...
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“Identifying the Proper Drug-Abuse Treatment for Offenders”, Simpson (2008)...
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drug related charges have no evidence of drug use? Is the drug dealing popu...
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follow-up, six month follow up, and 12 month follow up. A discharge assessm...
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sociodemographic data, but given its national scope, these sociodemographic...
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10. Relationship Issues
11. Irresponsible Parenting
12. Continued Aftercare...
DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 18
placed in a separate Windows folder on each computer, segregated from any o...
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of these variables were reviewed, and it was determined that, of the 77, 64...
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In five of the 12 outcome categories, one or more outcome measures differed...
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In the category of Relationship Issues, two out of eight variables were sig...
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The results of this study will likely not be surprising to substance abuse ...
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denial and to misrepresent their substance use. As such, there is an elemen...
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abuse treatment, but with poorer outcomes. Creating a different modality of...
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determine if the differences found remain over time. Third, although drug t...
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References
American Psychiatric Association. (2000). Diagnostic and statist...
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http://search.ebscohost.com.lib.kaplan.edu/login.aspx/direct=true&db=nfh&AN...
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Vulliamy, E. (2011, July 23). Nixon's war on drugs began 40 years ago, and ...
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APPENDIX A
Tables
Table 1
Sociodemographic Characteristics of the Sample
Me...
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Never Married
Divorced/Separated
52.3%
30.0%
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Table 2
90 Day Treatment Outcomes for Drug/Alcohol Users vs. Drug Trafficke...
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% Any Illegal Activity 07 (26) 20 (40) 2.79
Total # of Arrests .06 (.31) 0....
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Homicidal Suicidal Thought Scale .06 (.27) .10 (.33) 0.35
Psychiatric Issue...
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% Peers Weekly Intoxication 14 (35) 29 (46) 9.09*
Days Housemates Used Alco...
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Masters thesis differential effectiveness of substance abuse treatment by j fuller

  1. 1. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 1 Differential Effectiveness of Substance Abuse Treatment For Drug Traffickers vs. Substance Users By Joyce Julianne Fuller A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Psychology Kaplan University 2013
  2. 2. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 2 KAPLAN UNIVERSITY Abstract Differential Effectiveness of Substance Abuse Treatment For Drug Traffickers vs. Substance Users By Joyce Julianne Fuller Study considered the differential effectiveness of standard substance abuse treatment for persons with actual histories of drug use vs. those who have been arrested for drug trafficking, possession, dealing, delivery, manufacture, or sale. Dataset contained 1,348 subjects who had completed drug and alcohol treatment. Mean age was 33; 2/3 of subjects were male, 1/3 female; ethnic mix was well rounded. The researcher identified 77 outcome variables within 12 outcome categories. Of the 77, 64 trended as predicted, suggesting poorer outcomes for drug traffickers vs. substance users. A Chi Square was computed on trend data and was highly statistically significant. A MANOVA was then computed, considering each of the 64 outcome variables, with two covariates: 1) number of days during the three months post treatment that the individual was in a controlled environment; and 2) severity of alcohol and drug abuse at time of treatment commencement. The overall MANOVA was highly statistically significant, indicating that drug trafficking has a pure effect on poorer treatment outcomes. ANOVAs were computer to contrast drug traffickers vs. substance users on each of the 64 individual outcome variables, using a Bonferroni corrected alpha level. In five of 12 outcome categories, one or more outcome measures differed significantly between traffickers and users. The five categories with significantly different outcomes were Continued Alcohol/Drug Use, Reinstitutionalization, Environmental Issues, High Risk Sexual Behaviors, and Relationship Issues. Why drug
  3. 3. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 3 traffickers are receiving treatment designed for substance users, and treatment alternatives for drug traffickers along with costs and policy implications are considered. Keywords: substance use, drug trafficking, treatment, outcomes, substance abuse
  4. 4. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 4 Table of Contents List of Tables...............................................................................................................................4 Introduction.................................................................................................................................6 Literature Review ..................................................................................................................6 Hypotheses/Research Questions ...........................................................................................13 Method......................................................................................................................................14 Participants..........................................................................................................................14 Procedures...........................................................................................................................14 Results ......................................................................................................................................18 Discussion.................................................................................................................................21 Findings ..............................................................................................................................22 Limitations ..........................................................................................................................25 References.................................................................................................................................26 Appendix A: Tables...................................................................................................................29
  5. 5. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 5 Acknowledgments The author wishes to express sincere appreciation to the Research Associates and Data Analysis Teams of Chestnut Health Systems and the addiction recovery programs that provided the data for this study. Without their support, this thesis would not have been possible. The author also thanks her Thesis Adviser, Dr. Edward Cumella PhD, and her Thesis Committee members, Dr. John Burke and Dr. Alyssa Gilston. Thank you for all your help in completing this research!
  6. 6. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 6 The United States (US) war on drugs has been in effect since 1971 (Vulliami, 2011). Since its inception, Americans have seen stronger and more punitive sentencing laws which have filled the jails and prisons with offenders incarcerated for drug-related charges and fueled the prison industry and prison building boom across the nation (Bewley-Taylor, Hallam, & Allen, 2009; Mauer, 2010; Muftić & Bouffard, 2008). Many authors have documented growing disappointment in the lack of changes these greater sentences have had on recidivism rates for the population of drug offenders (Bewley-Taylor, Hallam, & Allen, 2009; Mauer, 2010; Muftić & Bouffard, 2008). As greater focus has been placed on sentencing laws, less attention has focused on the needs for specific forms of treatment in relation to a person’s frequency and severity of substance abuse. This paper therefore explores the effectiveness of mandated substance abuse treatment in relation to the frequency and severity of substance use. Muftić and Bouffard (2008) speak of alternative options to prison overcrowding using intermediate sanctions. Intermediate sanctions are strategies imposed by Probation and Parole (P&P) departments to intervene in offenders’ destructive patterns of behavior. Intermediate sanctions utilize methods such as drug court, substance abuse treatment programs, electronic monitoring, and other interventions prior to offenders being sentenced to incarceration. These sanctions attempt to control the overcrowding of an overburdened criminal justice system, as well as reduce recidivism rates. In an article titled, “Beyond the Fair Sentencing Act”, Mauer (2010) addresses issues within the Fair Sentencing Act and mandatory sentencing provisions that have eventuated in the incarceration of the majority of ethnic minority offenders. The Fair Sentencing Act, enacted by Congress and signed into law by President Barack Obama in 2010, was initiated as an attempt to create fairer sentencing laws for cocaine and crack cocaine users. Mauer describes the Act as a
  7. 7. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 7 method to “scale back the harsh and racially disparate mandatory sentences for federal crack cocaine offenses” (Mauer, 2010, p. 1). Mauer (2010) identifies that the problem lies within the sentencing and advocates for more drug treatment within communities as well as fairer sentencing laws. However, both Muftić and Bouffard (2008) and Mauer (2010) fail to note that many of those sentenced for drug sales or trafficking may not be in need of drug treatment at all, as they do not necessarily use substances themselves. Studies of substance abuse treatment outcomes among incarcerated drug felons often fail to differentiate the portion of the population that does not meet the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) (American Psychiatric Association, 2000) criteria for addiction. This potentially important failure to differentiate recipients of treatment is a notable factor in a recent Department of Justice report regarding the lack of effective tracking of grant programs aimed at reducing recidivism from drug related crimes using re-entry programs (Anonymous, 2010). Williams’ (2008) article, titled “Whose Responsibility is Substance Abuse Treatment?” provides evidence that admissions to drug treatment programs have increased by 35% between 1995 and 2005. During this same time period, federal spending for drug treatment increased by 15%. Yet there has been insufficient accountability regarding how these dollars have been spent, partly related to the use of substance abuse treatment for criminals who do not meet criteria for a substance abuse or dependence disorder. Programs have been initiated throughout the US to provide substance abuse education and treatment within the criminal justice system. These programs include modalities of treatment such as outpatient drug treatment, using peer discussion groups, counselor led groups, vocational therapy, and cognitive therapy. Programs also include 12-step meetings, relapse
  8. 8. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 8 prevention, and aftercare in various multimodality designs, of which a recent focus is on transition classes and re-entry programs (Center for Substance Abuse Treatment [CSAT], 2005). There is literature to support a measure of success with these substance abuse programs in assisting drug users; however, almost no data reports how successful these modalities of treatment have been for those offenders who have never or only rarely used illegal drugs. One recent study of a small sample (N=30) of women mandated into drug treatment suggests that 60% did not have a DSM-IV-TR drug abuse or dependence diagnosis; some of these women were satisfied with drug treatment at time of discharge, but many were not (Shaw, 2012). Yet no post-discharge follow-up data were available on this sample. Meanwhile, the incarcerated offender population continues to face major challenges as there is no specific curriculum or identified modality to address criminal thinking behaviors (Simpson, 2008; Williams, 2008). In short, there appears to be no specific criteria or specialized treatment components designed to meet the needs of those incarcerated individuals who are: 1) sentenced as drug traffickers, 2) identified as non-users, or 3) mandated to receive substance abuse treatment for a range of drug-related crimes apart from drug use itself. US and state agencies, such as the Department of Corrections (DOC), place offenders in drug treatment simply due to the presence of any drug related charge. Many of these individuals return to prison perhaps because their underlying needs have not been addressed through their participation in treatment designed only for those who abuse drugs. Furthermore, empirical research suggests that punitive prison sentences, programs aimed at shocking youthful offenders with the harsh reality of the jail/prison environments, such as Scared Straight, and military and disciplinary styled behavior modification programs, often called boot camps, may result in increased rather than decreased recidivism rates (Serin, Caleb, & Hanby, 2012). Thus, those
  9. 9. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 9 with drug related crimes apart from substance abuse may not be receiving the assistance they need through other programs they are encountering while in the criminal justice system. In discussion of methods in separate areas within the same system regarding corrections and re- entry, Serin et al. (2012, p. 56) state, “In reality, little is known regarding their relative and combined contributions to offender success and crime desistance. Moreover, an overarching conceptual model that integrates these literatures is presently and noticeably absent.” This is also true of available and accurate reports of currently used assessment methods, in regard to success rates of those who engage in drug sales as a form of employment. Placing individuals who do not use drugs in substance abuse treatment due to their drug related charge of drug trafficking, sales, manufacturing, delivery, or possession may be unethical, costly, and ineffective (Shaw, 2012). In an article titled “Downsizing Prisons: Should Non-violent Inmates be Incarcerated”, Katel (2011) discusses the high costs associated with placing inmates in substance abuse treatment within the prison system. This cost includes many who may not need or benefit from such treatment, but would rather benefit from a different modality of treatment that better addresses their criminal thinking and behaviors. Johnson (2012), in his article titled “Prisoners facing long waits for drug rehab”, laments the lack of available treatment for those who truly need it, caused in part by the use of treatment for those who do not abuse substances. Although greater attention has been paid to the male offender population, the problem is not limited to males. Female offenders who have no evidence of actual drug use are also mandated into substance abuse treatment programs (Mares, 2011). The Women’s Prison Association reports:
  10. 10. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 10 In 1977, the U.S. imprisoned 11,212 women; by 2004, that number had ballooned to 96,125, a 757% increase. In 1977, the United States imprisoned 10 women per 100,000 female residents; in 2004, the rate had grown to 64 per 100,000 (Jacobs & From, 2006, para. 1). Authors Greene & Pranis (2011) shed light on the growing numbers of women engaging in drug trafficking in an article entitled “HARD HIT: The Growth in the Imprisonment of Women”, suggesting that “Women were described as responding to the same social and economic dynamics that drove increased levels of violence among men, making gender a ‘less salient factor’” (Greene & Pranis, 2011, p. 21). Andrea Mares (2011) uses the term femicide to describe the mass killing of women occurring among Latin American women. In her article titled “The Rise of Femicide and Women in Drug Trafficking”, the author contends that the 400 percent increase in women incarcerated in Mexico since 2007 is directly linked to organized crime, specifically related to women’s increased participation in drug trafficking . Mares speaks to the accessibility of financial gain and lavish lifestyles women are afforded to provide for their children and families, stating, “women are probably drawn to the excitement, mystery and power of drug trafficking. By way of narcotic smuggling, some women are able to attain opulent lifestyles”. It is suggested that this same dynamic, so evidence in Mexico and various other Latin American nations, is also impacting women’s increased involvement in drug trafficking in the US. In a study conducted on US women in New York State, Shaw (2012) reports similar economic factors as driving the increased number of women convicted of drug related crimes, but also reports other influences as well. Shaw summarizes that “many [women] appear to be placed in treatment environments meant for different populations”. Thus, whether male or female, it would seem prudent to focus
  11. 11. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 11 attention on providing appropriate treatment to the offender population of drug traffickers, and to free up scarce drug treatment resources for those who truly have an addiction in need of treatment (Mares, 2011; Shaw, 2012). Realizing that there is a potentially significant difference between the user and the dealer is not a new concept. Many authors have linked the differences to the criminogenic thinking and lifestyles of the latter group (Simpson, 2008; Williams, 2008). Simpson expresses that, “offenders engage in crime as a means to obtain money, sex, material possessions and status” (Simpson, 2008, p. 71). Simpson goes on to explain that the use of drugs for this offender population is “not the primary focus of their lives; rather, drugs are viewed as a means to support their criminal enterprise” (Simpson, 2008, p. 71). In fact, the drug dealer who does not use drugs may have a more serious issue than the typical drug user. Many dealer come from communities that condone their criminal behaviors (Simpson, 2008). Their behaviors are deeply rooted in a psychological, cultural, and spiritually flawed belief system. In some communities where quality education and access to jobs are limited, these offenders are seen as neighborhood role models who are able to provide food and shelter for their families. There are many works of fiction that depict the hero worship of the criminal lifestyle associated with drug trafficking, such as Drama City, Soul Circus, and Hard Revolution, all by George Pelecanos. Movies such as American Gangster, In Too Deep, and Scarface all portray the affluent and destructive lifestyles associated with drug sales and culture. Although often published and created to educate about the evils of this lifestyle, offenders often glorify and attempt to identify with and mimic the behaviors of the fictional characters. One such book of fiction is by Sister Souljah, titled The Coldest Winter Ever. The author gives a clear and accurate picture of this criminal lifestyle, the hero worship of the community, and the egotistic and
  12. 12. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 12 narcissistic values that are inherent in this culture. The author also gives a realistic view of the issues of women involved in the drug dealing culture and the consequences thereof, namely the problematic legacy to the children growing up in this environment, in which the criminal culture is inculcated. Once drug users stop using and engage in a recovery program, their lifestyle often improves (CSAT, 2005; Wexler, 1995). On the other hand, when drug dealers stop dealing, they may be faced with what they believe to be a lesser quality of life due to financial and community esteem losses (Williams, 2008). Much of society may believe that these individuals are lazy or unintelligent, when much to the contrary they are often intelligent and work diligently in their trade (Mares, 2011). For instance, US authorities have estimated the business of drug trafficking as profitable and lucrative, with “between USD [United States Dollar] 18 and USD 35 billion in drug earnings per year” (Mares, 2011). When a dealer can make thousands of dollars in one day and is then faced with the very real possibilities of earning minimum wage to meet his needs and those of his family, it is self-evidence that his value system may have to change to accept such a drastic change in lifestyle. Certain behavior modification modalities, such as Therapeutic Communities, have demonstrated success with the incarcerated population of drug dealers (Wexler, 2011). Providing drug education, accountability, character building, and stress coping techniques, the success of this modality has been primarily attributed to dimension of community accountability. However, many drug users have also been enrolled in programs of this type, and the research has not differentiated between the outcomes associated with users vs. dealers. Several authors have acknowledged the need for separation in treatment between drug users and dealers (Fitzgerald, 2009; Simpson, 2008; Snipes 2011). In the article titled,
  13. 13. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 13 “Identifying the Proper Drug-Abuse Treatment for Offenders”, Simpson (2008) states, “While drug abuse is considered one such criminogenic need, psychological interventions that focus solely on offenders' drug use and do not attempt to address their criminal behavior will likely show limited success in impacting recidivism”. Their criminal behaviors are often influenced by grandiosity, narcissism, power and control issues, spirituality issues, co-dependency, and underlying anger (Simpson, 2008), some of which are not addressed routinely within chemical dependency treatment programs. In an online article, titled “Drug Dealing as an Addiction”, Snipes (2011) expresses that specialized treatment for drug dealers is just as vital as for drug users. For example, Snipes (2011) notes that, “Long-winded groups on pharmacology and deficit based instruction are only going to irritate this [drug dealing] patient”. Snipes notes similarities between drug dealers and those with problem gambling in an effort to identify treatment needs and how counselors can address the needs of the non-using offender by focusing on career and employability skills. The need for separate treatment for drug traffickers vs. users is also discussed by Fitzgerald (2009). Fitzgerald (2009) emphasizes the need for harm reduction modalities among drug dealers because studies reflect a high level of habitual violence in this population, fueled in part by disputes in competition among rival drug dealers for customers and territorial power (Ward, Mann, & Gannon, 2006). Clearly, an emerging literature suggests that many professionals in the field of substance abuse and in the criminal justice system recognize that the need for education and treatment for the drug dealer is as important as it is for the drug user, and that the modalities of treatment for drug users are not necessarily helpful for drug dealers (Simpson, 2008). This recognition leads to a range of questions, such as: What percentage of criminals enrolled in drug treatment due to
  14. 14. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 14 drug related charges have no evidence of drug use? Is the drug dealing population large enough to justify the costs of exploring and developing separate treatments? What are the assessment tools necessary to reliably differentiate drug users from dealers? What are the treatment outcomes for drug users vs. dealers who complete current substance abuse treatment programs designed primarily for users? What is the recidivism rate of those with the same charges who did not attend drug treatment programming? In standard drug treatment programs, what types of rehabilitative efforts are being offered to those with sentences of drug trafficking, sales, manufacturing, delivery, possession, or distribution? What would specialized treatment for drug dealers include? What additional training would be necessary for addiction professionals to provide treatment for drug dealers? The present study isolates one of these research questions: What is the differential effectiveness of standard substance abuse treatment for persons with actual histories of drug use vs. those without these diagnoses who have been arrested for drug trafficking, possession, dealing, delivery, manufacture, or sale, but who may not evidence actual drug use? It is hypothesized that outcomes for the latter population will be significantly lower than for those with actual drug abuse or dependence diagnoses. Method Participants This study utilized data from inpatient substance abuse treatment programs that were grantees of the Offender Re-Entry Programs (ORP) funded by the Center for Substance Abuse Treatment (CSAT) through the Substance Abuse and Mental Health Administration (SAMHSA) and monitored through Chestnut Health Systems. The data were collected by the use of the Global Assessment of Individual Needs (GAIN), which was administered at intake; three month
  15. 15. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 15 follow-up, six month follow up, and 12 month follow up. A discharge assessment was also utilized at the completion of the four to six month outpatient treatment time for those clients who successfully completed the program. The GAIN assessment and follow-ups were provided for every client admitted to treatment facilities, whether they completed treatment or dropped out for any reason. The GAIN assessment and follow ups were given to patients by trained Re-Entry Care Coordinators, as part of a series of routine intake paperwork. Staff administered the assessments online, with data maintained in a database at Chestnut Health Systems. Comments of Care Coordinators and observations were entered at the end of each section of the assessment. The researcher was not present at the time of data collection. The data covers all clients admitted between January 1, 2010 through October 31, 2012. The research question of this thesis was not framed at the time of data collection; as such, there are not expected to be observer effects. The participants were anonymous in this study as there was no individually identifiable information available in the database and the subject code had been de-identified such that it does not link back in any way whatsoever to the client or client records. All results were presented in aggregate form to further protect subjects’ identities. Inclusion criteria specified adults aged 18 years and over who attended ORP community based substance abuse treatment programs during the target dates in 2010-2012, and who had completed the GAIN Assessment. Data are missing for several reasons that are unlikely to bias the representativeness of the sample. Most missing data were due to administrative recording errors and oversights, or for clients who did not meet the substance abuse diagnostic criteria. Some missing data were due to client refusal to complete paperwork. The dataset consisted of 1,323 individuals, age 18-60 who met inclusion criteria. The dataset included basic
  16. 16. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 16 sociodemographic data, but given its national scope, these sociodemographics were insufficient to identify any particular subjects. Research Design The GAIN includes many questions on substance abuse and dependence, including those needed to suggest a DSM-IV-TR diagnosis and additional questions about each drug and alcohol, amount used, frequency of use, physical, social, criminal, and economic consequences, and treatment history. Among these variables is an indicator of whether or not the individual self reports drugs trafficking, sale, or transport during the past year. This will serve as the independent variable to divide the subjects into “traffickers” vs. “users”. The dataset contains 150 traffickers and 1,173 abusers. All subjects in the GAIN database have been enrolled in an appropriate form of alcohol or drug treatment based on the severity of their substance use. Variables in the dataset include arrest data, ongoing drug and alcohol use, and measures that have been collapsed to create the following 12 outcome categories post-discharge: 1. Continued Alcohol/Drug Abuse 2. Reinstitutionalization 3. Illegal Activity 4. Environmental Issues 5. Employment Issues 6. Risky Sexual Behaviors 7. Suicidality/Homicidality 8. Psychiatric Issues 9. Financial Instability
  17. 17. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 17 10. Relationship Issues 11. Irresponsible Parenting 12. Continued Aftercare In the GAIN database, the researcher identified 77 individual outcome variables that could be used as measures of these 12 outcome categories; see Table 2. Each of these 77 variables measures outcome for the three month period following discharge from substance abuse treatment. Means of these variables were reviewed, and it was determined that, of the 77, 64 trended as predicted--i.e., suggesting poorer outcomes for drug traffickers vs. substance users. These 64 variables will therefore be entered into further analysis. A MANOVA will be computed, considering each of the 64 outcome variables in relation to drug trafficking vs. alcohol or drug abuse. A power analysis indicates that the MANOVA and individual ANOVAs will have sufficient power to detect even small effect sizes (Cohen, 1988). The alpha level for the ANOVA for each dependent variable will be adjusted using the Bonferroni method to correct for family-wise error in significance testing; p = .05/64 = .001. In the MANOVA, two variables will be controlled as covariates: 1) number of days during the three months post treatment that the individual was in a controlled environment (i.e., jail, prison, or treatment), since days in a controlled environment impacts access to drugs and alcohol and other behavioral indicators of potential treatment success; and 2) severity of alcohol and drug abuse at time of treatment commencement, since severity also affects treatment outcome. With these two factors controlled, the MANOVA will be able to detect the pure effect of drug trafficking on treatment outcome. During this study, only the thesis chair and the student researcher will have access to the data. The data are stored on the two computers owned by these individuals. The data have been
  18. 18. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 18 placed in a separate Windows folder on each computer, segregated from any other files that are not related to the data set. The two computers are locked by strong Windows passwords, known only to the computer owners. Following completion of the research, the data set and related files will be retained by the researcher for a minimum of seven years in case questions arise about the analyses. The data set and related files will be transferred to any future computer owned by the researcher until the seven years have expired. Throughout the study and subsequent seven years, the researcher will implement a weekly backup plan wherein the data set and related files are backed up using a secure online data backup system. The current system used is Qwest Personal Digital Vault. Details of this service’s security policy can be found at this link: https://digitalvault.qwest.com/help.aspx. Once the seven years are over, the researcher will destroy the electronic dataset using an economical method recommended by Department of Defense Data Destruction Standards. Results The final dataset contained 1,348 subjects who had completed drug and alcohol treatment. Table 1 presents their sociodemographic information. Their mean age was 33 years; 2/3 was male and 1/3 female. The dataset represents a well rounded ethnic mix, with 46% of subjects being White and the remainder members of other minority groups. However, Hispanics were over-represented in the dataset and Asian-Americans were under-represented. Most, 56%, had not completed high school, and only 10% had some form of college. Only 18% were married or in a committed relationship, with more than half never married. In the GAIN database, the researcher identified 77 individual outcome variables that could be used as measures of the 12 outcome categories. Each of these 77 variables measured outcome for the three month period following discharge from substance abuse treatment. Means
  19. 19. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 19 of these variables were reviewed, and it was determined that, of the 77, 64 trended as predicted-- i.e., suggesting poorer outcomes for drug traffickers vs. substance users. A 1 x 1 Chi Square was computed on these trend data and was highly statistically significant, indicating that, even without statistical controls, drug traffickers appeared to have poorer treatment outcomes than substance users; X2 = 33.78, df = 1, p < .001. A MANOVA was then computed, considering each of the 64 outcome variables that trended as predicted in relation to drug trafficking vs. substance use. In the MANOVA, two variables were controlled as covariates: 1) number of days during the three months post treatment that the individual was in a controlled environment (i.e., jail, prison, or treatment), since days in a controlled environment impacts access to drugs and alcohol and other behavioral indicators of potential treatment success; and 2) severity of alcohol and drug abuse at time of treatment commencement, since severity also affects treatment outcome. With these two factors controlled, the MANOVA was able to detect the pure effect of drug trafficking on treatment outcome. The overall MANOVA was highly statistically significant; Pillai’s Trace = 0.991, F(66,174) = 293.44, p < .001. This indicates that, overall, there is a highly significant outcomes difference between drug traffickers vs. substance users. ANOVAs were computer to contrast drug traffickers vs. substance users on each of the 64 individual outcome variables. The alpha level for the ANOVAs was adjusted using the Bonferroni method to correct for family-wise error in significance testing; p = .05/64 = .001. Table 2 presents means and standard deviations for the 64 drug and alcohol treatment outcome variables, organized by 12 major categories, along with the F statistic from each individual ANOVA.
  20. 20. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 20 In five of the 12 outcome categories, one or more outcome measures differed significantly between traffickers and users. The five categories with significantly different variables were: Continued Alcohol/Drug Use, Reinstitutionalization, Environmental Issues, High Risk Sexual Behaviors, and Relationship Issues. In the category of Continued Alcohol/Drug Use, eight of 11 outcome measures were significantly different between traffickers and users. This category is critical, since it measures the most essential target outcome of alcohol and drug treatment--abstinence. The fact that eight of 11 variables were statistically significantly different between traffickers and users, even with statistical controls and a stringent Bonferroni corrected alpha level, appears to suggest a clear difference in abstinence between the two groups. In the category of Reinstitutionalization, the one available measure, days in a controlled environment, was significantly different between traffickers and users. The mean days in a controlled environment in the past 90 days, 35 vs. 28, suggest that traffickers spent seven more days in a controlled environment than users. In the category of Environmental Issues, one out of three outcome measures was significantly different between groups. The significant variable was the Environmental Strengths Index, a composite of several measures of environmental stressors and supports. The difference indicated that, overall, traffickers had less environmental strength than users. In the category of High Risk Sexual Behaviors, one out of three measures was significantly different between groups. The variable that was significant was the Sexual Risk Scale, a composite of several measures of risky sexual practices. This indicated that, overall, traffickers were engaging in more high risk sexual behaviors than users.
  21. 21. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 21 In the category of Relationship Issues, two out of eight variables were significantly different between groups. Traffickers had more housemates who engaged in illegal activity and who were frequently intoxicated. Discussion The present study asked the following research question: What is the differential effectiveness of standard substance abuse treatment for persons with clear histories of drug use vs. those who have been arrested for drug trafficking, possession, dealing, delivery, manufacture, or sale? It was hypothesized that outcomes for the latter population would be significantly lower than for those with drug abuse or dependence diagnoses. Results suggested that 64 of 77 outcome measures trended as hypothesized; a Chi Square on the trend data indicated that this difference was highly statistically significant. MANOVA results also suggested that this difference was highly significant, even when days post-treatment in a controlled environment and substance use severity were controlled. Thus, the MANOVA suggested that there is a strong, pure effect of drug trafficking on poorer treatment outcome. As such, the hypothesis of this study appears to be well confirmed. The effect of drug trafficking on poorer treatment outcomes is evident across all 12 outcome categories; see Table 2. The effect is particularly strong in five of the 12 outcome categories where one or more outcome measures differed significantly between traffickers and users even with multiple statistical controls from two covariates and the remaining outcome variables. These five outcome categories are: Continued Alcohol/Drug Use, Reinstitutionalization, Environmental Issues, High Risk Sexual Behaviors, and Relationship Issues. With this in mind, the question arises as to why drug traffickers are routinely being enrolled in treatment programs designed for substance users. This question is explored below.
  22. 22. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 22 The results of this study will likely not be surprising to substance abuse counselors who work within the prison system. Psychosocial assessments, GAIN assessments, and a variety of other assessments have been created to identify, diagnose, and aid in treating substance users. When used with drug traffickers, these assessments may falsely flag the individuals as potentially having the diagnosis of substance abuse, because several criteria of the DSM-IV-TR substance abuse diagnosis are vague enough that they may apply to drug traffickers who do not use substances regularly. These criteria include: recurrent substance related legal problems; recurrent use resulting in failure to fulfill major role obligation at work, home, or school; and recurrent use in physically hazardous situations. These items, especially “recurrent substance related legal problems”, are readily endorsed by drug traffickers as they capture the circumstances of drug trafficking fairly well. The majority of treatment funding sources, state and federal, during incarceration and after incarceration, require that a person enrolled in treatment have a DSM-IV-TR substance abuse or dependence diagnosis. There is no DSM-IV-TR diagnosis for drug dealing. With funding being harder and harder to obtain, treatment providers often diagnose this population with substance abuse in an attempt to meet the requirements that those receiving treatment have a DSM-IV-TR substance use diagnosis. It is possible to justify the diagnosis of substance abuse in these persons, for several reasons. First, some of the drug traffickers do sometimes use substances. Second, the DSM-IV-TR criteria for substance abuse include these items: recurrent substance related legal problems; recurrent use resulting in failure to fulfill major role obligation at work, home, or school; and recurrent use in physically hazardous situations. These items, especially “recurrent substance related legal problems”, can apply to drug traffickers even if they do not use substances regularly. Third, persons involved with substances are known to be in
  23. 23. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 23 denial and to misrepresent their substance use. As such, there is an element of clinical judgment with a drug trafficker which may allow a counselor to make the substance abuse diagnosis without unequivocally clear evidence of substance abuse. If this is what is needed to obtain treatment for the person, it may seem like an attractive and even ethical option. This is particularly the case because there is no alternative for treatment of drug trafficking, and thus the drug trafficker will likely remain in the same unproductive cycle of repeated incarcerations. There is no current known assessment to identify, diagnose, and aid with treatment of drug traffickers. Drug trafficking is not even conceptualized by many as a disorder. Should this issue be identified as a mental disorder? Should it be identified as a behavioral disorder? What are the symptoms and how are they identified, measured, and diagnosed? How could treatment for this population be funded to reduce their recidivism? The results of this study suggest that there is a need for these questions to be answered. Drug dealers/traffickers are returning to society with inadequate treatment, despite the attempts of federal, state, and local programs, DOC Re-Entry programs, transitional programs, and post release treatment. The results of this study indicate that, after their completion of standard substance abuse treatment, there is little change in the people they socialize and live with, how they resolve disagreements, and their ability to condone risky sexual behavior as an inherent part of that culture. Thus, they would appear to remain at significant risk of recidivism. There are no easy answers or solutions. To address these issues would change the entire process of assessment and diagnosis in the penal system. However, it is suggested that just as there is federal and state funding for the users, there is a need to identify federal and state funding targeted to the specific population of drug traffickers. Let us keep in mind that these dollars are already being spent on these clients because they are being sent to standard substance
  24. 24. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 24 abuse treatment, but with poorer outcomes. Creating a different modality of treatment and segregating the populations could provide appropriate treatment for the appropriate clients. Furthermore, many substance users are in need of treatment that is obviously being directed to drug traffickers who do not benefit much from the current treatment methods. Pilot programs initiated within the criminal justice system should present minimal additional costs, as the clients’ treatment is already being paid for. The greatest issue lies with the DOC and other criminal justice agencies which now receive funding from federal and state sources that require a DSM-IV-TR diagnosis and evidence-based treatment. This issue would need to be addressed by a coalition of clinicians, policymakers, mental health and behavioral health professionals, and social scientists. For policy makers on both the federal and state levels to adjust methods of funding, it may be as simple as moving already existing funding in another direction. The researcher has been working with these clients for many years, using what may be inappropriate methods to address their needs. The problem will not resolve itself. If we as clinicians continue to utilize inappropriate treatment options with this population simply because we have no alternatives, this is an ethical dilemma. We must create these alternatives by addressing the issue openly and with good science. This present research is intended to draw attention to this issue to promote an open dialogue. This study entails several limitations. First, although the data are based on a reliable and valid instrument, the GAIN, GAIN data derive from client self-reporting. All self-reporting, especially when it involves persons with alcohol and drug abuse or criminality, is subject to some degree of distortion. Second, the outcome measures used were obtained at three months following end of treatment. Longer periods of time post treatment should be considered to
  25. 25. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 25 determine if the differences found remain over time. Third, although drug traffickers clearly are evidencing lower outcomes at three months post treatment, their status on these measures before treatment was not assessed. It is possible that drug traffickers have more risk factors and dysfunctional behaviors pre treatment, and that treatment is having an impact on these issues. Thus, pre treatment to post treatment change scores should be examined for a deeper understanding of the effects of standard substance abuse programs on drug traffickers.
  26. 26. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 26 References American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text revision). Washington, DC: Author. Anonymous. (2010). Audit: DOJ can't show prisoner re-entry grant effectiveness. Corrections Forum, 19(4), 9-10. Bewley-Taylor, D., Hallam, C., & Allen, R. (2009). The incarceration of drug offenders: An overview. The Beckley Foundation Drug Policy Programme, Report 16, 1-18. Retrieved from www.beckleyfoundation.org/pdf/BF_Report_16.pdf Center for Substance Abuse Treatment. (2005). Substance abuse treatment for adults in the criminal justice system. Rockville (MD): Substance Abuse and Mental Health Services Administration (US). (Treatment Improvement Protocol (TIP) Series, No. 44.) DHHS Publication No. (SMA)05-4056Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York, NY: Routledge. Fitzgerald, J. L. (2009, May). Mapping the experience of drug dealing risk environments: An ethnographic case study. International Journal of Drug Policy, 20(3), 261-269. Greene, J., & Pranis, K. (2004). Hard hit: The growth in the imprisonment of women, 1977 - 2004. New York, NY: Institute on Women and Criminal Justice. Retrieved from http://www.wpaonline.org/institute/hardhit/Part1GrowthTrends.pdf Jacobs, A., & From, S. (2006). The punitiveness report. Retrieved from http://www.wpaonline.org/institute/hardhit/foreword.htm Johnson, K. (2012, December 5). Prisoners facing long waits for drug rehab, GAO finds. USA Today. Retrieved from
  27. 27. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 27 http://search.ebscohost.com.lib.kaplan.edu/login.aspx/direct=true&db=nfh&AN=JOE308 533156612&site=ehost-live Katel, P. (2011). Downsizing prisons: Should non-violent inmates be incarcerated? CQ Researcher, 21(10), 217-240. Mares, A. (October, 2011 28). The rise of femicide and women in drug trafficking. Retrieved from http://www.coha.org/the-rise-of-femicide-and-women-in-drug-trafficking/ Mauer, M. (2010). Overview of the model drug dealer liability act: Beyond the fair sentencing act. The Nation. Retrieved from http://www.thenation.com/article/157009/beyond-fair- sentencing-act Muftic, L. R., & Bouffard, J. A. (2008). A comparison of recidivism rates for low-level drug and.or alcohol offenders receiving intermediate sanctions. Corrections Compendium, 33(4), 1-4 & 28-31. Serin, R. C., Lloyd, C. D., & Hanby, L. J. (2010). Enhancing offender re-entry: an integrated model for enhancing offender re-entry. European Journal of Probation, 2(2), 53-75. Retrieved from www.ejprob.ro/uploads_ro/712/Enhancing_Offender_re_entry.pdf Shaw, R. W. (2012). Women's entry pathways into and perceptions of mandated drug treatment: An exploratory profile. Unpublished Master’s Thesis, Kaplan University. Simpson, M. T. (2008). Identifying the proper drug-abuse treatment for offenders. Criminal Justice Periodicals, 70(6), 70-72. Snipes, D. (2011). Drug dealing as an addiction. Retrieved from http://www.allceus.com/2011/03/drug-dealing-as-an-addiction/ Souljah, S. (1999). The coldest winter ever. New York, NY: Simon & Schuster.
  28. 28. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 28 Vulliamy, E. (2011, July 23). Nixon's war on drugs began 40 years ago, and the battle is still raging. The Observer, 28. Retrieved from http://www.guardian.co.uk/society/2011/jul/24/war-on-drugs-40-yearsWard, T., Mann, R. E., & Gannon, T. A. (2006). The good lives model of offender rehabilitation: Clinical implications. Aggression and Violent Behavior, 12, 87-107. doi: 10.1016/j.avb.2006.03.004 Wexler, H. K. (1995). The success of therapeutic communities for substance abusers in American prisons. Journal of Psychoactive Drugs, 27(l), 57-66. Retrieved from http://amityfoundationpress.org/?p=66 Williams, M. L. (2008). Whose responsibility is substance abuse treatment? Corrections Today, 70(6), 82-84.
  29. 29. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 29 APPENDIX A Tables Table 1 Sociodemographic Characteristics of the Sample Measure All Subjects N 1,323 Age 32.5 (10.5) RANGE: 20-59 Ethnicity White African-American Asian-American Native-American Hispanic 45.6% 19.5% 0.7% 4.8% 29.3% Gender Male Female 67.7% 32.3% Education Less than high school High school completed/GED College Graduate school 34.1% 55.9% 9.4% 0.6% Relationship Status Married/In Committed Relationship 17.8%
  30. 30. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 30 Never Married Divorced/Separated 52.3% 30.0%
  31. 31. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 31 Table 2 90 Day Treatment Outcomes for Drug/Alcohol Users vs. Drug Traffickers Measure Users Mean (SD) Traffickers Mean (SD) F (df=2) N 1,173 150 Continued Alcohol/Drug Use Days Abstinent 57.03 (38.59) 39.60 (37.97) 373.29* Denial/Misrepresentation Scale .36 (.53) .69 (.59) 9.62* % Used Alcohol in Past 90 Days 23 (42) 35 (48) 17.10* % Using AOD most of day 20 (40) 37 (48) 17.01* Mental Denial & Misrepresentation Rating .20 (.52) .57 (.75) 3.76 Outcome in Recovery (0-1 scale) .57 (.50) .33 (.47) 45.20* Days Used AOD 6.39 (18.38) 18.90 (31.42) 6.75* Substance Abuse Index .08 (.32) .26 (.58) 6.96* Substance Dependence Scale (past month) .06 (.31) .19 (.56) 4.38 Substance Problem Scale (past month) .16 (.43) .36 (.68) 5.68 Substance Severity Measure (past month) 2.15 (.58) 2.42 (.97) 7.04* Reinstitutionalization Days in Controlled Environment 27.59 (37.64) 34.98 (37.89) 1407.71* Illegal Activity Times sold/distributed/made illegal drugs 0.18 (2.18) 1.87 (10.05) 0.97 Days in any activities you thought illegal 1.12 (7.84) 5.54 (18.73) 0.78
  32. 32. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 32 % Any Illegal Activity 07 (26) 20 (40) 2.79 Total # of Arrests .06 (.31) 0.88 (8.91) 1.27 Illegal Activity Scale 1.03 (.33) 1.10 (.47) 1.15 Days of Illegal Activity to get AOD .42 (4.38) 2.36 (12.30) 1.10 How many times arrested .08 (.39) .34 (2.34) 2.79 General Crime Scale .06 (.28) .20 (.49) 2.25 Environmental Issues Number of Days Homeless 5.08 (18.84) 7.92 (22.57) 0.11 Environmental Risk Scale 1.00 (.37) 1.22 (.49) 4.26 Environmental Strengths Index-Reversed 1.12 (.67) .93 (.75) 8.48* Employment Issues Days Worked .78 (.84) .50 (.75) 0.80 Employment Activity Scale .84 (.88) .57 (.83) 0.61 Vocational Risk Index 1.61 (.61) 1.72 (.52) 1.56 Risky Sexual Behaviors Number of Male Sex Partners .22 (.89) .25 (.65) 1.25 Any High Risk Sex .08 (.27) .19 (.40) 5.90 Sexual Risk Scale .43 (.50) .50 (.57) 19.25* Suicidality/Homicidality Thought About Committing Suicide .03 (.17) .03 (.16) 0.10 # Suicidal/Homicidal Attempts/Thoughts .06 (.24) .09 (.29) 0.31 Thought About Killing or Hurting Someone .04 (.20) .06 (.24) 0.80
  33. 33. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 33 Homicidal Suicidal Thought Scale .06 (.27) .10 (.33) 0.35 Psychiatric Issues Conduct Disorder Scale .20 (.78) .47 (1.21) 0.93 Days with Psychiatric Problems .56 (.83) .84 (.87) 0.23 Anxiety/Fear Symptom Scale .37 (.60) .57 (.71) 0.39 Emotional Problem Scale .57 (.65) .75 (.69) 0.64 General Mental Distress Scale .65 (.88) .91 (.95) 0.95 Internal Mental Distress Scale .28 (.56) .53 (.71) 0.38 High Mental Distress .27 (.44) .40 (.49) 0.57 Strength Self-Efficacy Index-Reversed .65 (.65) .61 (.66) 0.04 Days Cut, Burned or Hurt Self on Purpose .10 (1.71) .13 (.92) 0.95 Financial Instability Financial Instability Scale .13 (.15) .18 (.19) 2.20 Days with Money Problems (0-1) .14 (.31) .23 (.37) 0.47 Financial Instability Scale .37 (.64) .59 (.74) 2.06 Financial Problem Scale .24 (.54) .52 (.73) 2.46 Past Month School/Work .53 (.50) .40 (.49) 0.23 Work Full Time 22.90 (30.80) 14.54 (27.10) 1.82 Relationship Issues People Lived with Shout, Argue, Fight .29 (.80) .50 (1.05) 5.27 No Family Problems .88 (.33) .83 (.38) 2.33 Housemates Engaged in Illegal Activity 2.87 (4.65) 3.12 (5.16) 7.26*
  34. 34. DIFFERENTIAL EFFECTIVENESS OF SUD TREATMENT 34 % Peers Weekly Intoxication 14 (35) 29 (46) 9.09* Days Housemates Used Alcohol 2.67 (11.60) 10.89 (25.61) 4.48 Days Housemates Used Drugs 2.35 (11.84) 10.59 (25.00) 2.65 General Social Support Index-Reversed .30 (.59) .39 (.69) 0.47 Social Environmental Risk Index 9.70 (4.36) 11.72 (5.83) 2.26 Irresponsible Parenting Day had Children in Foster Care 2.48 (14.75) 3.88 (18.36) 0.94 Continued Aftercare Times in Support Recovery Meetings 1.22 (3.56) 1.06 (3.41) 4.94 General Continuing Care Adherence .62 (.74) .54 (.71) 1.00 Days Attended Groups 19.55 (31.14) 16.63 (27.14) 0.32 Treatment Resistance Index .59 (.64) .83 (.61) 0.18 % Weekly Self-Help 32 (47) 31 (46) 0.36 % Weekly Aftercare 27 (45) 15 (36) 1.59 Spiritual Social Support Index-Reversed .90 (.71) 1.23 (.73) 0.45

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