Running head: COMPARING OUTCOMES FOR ALCOHOL AND DRUG CLIENTS

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1 Running head: COMPARING OUTCOMES FOR ALCOHOL AND DRUG CLIENTS Comparing outcomes for alcohol and drug abuse clients: A 6-month follow-up of clients who completed a residential treatment program. J Subst Use 15(3): , 2010 Janice Hambley, Ph.D., C.Psych., Simone Arbour, Ph.D. Lakshmi Sivagnanasundaram, B.A.. Bellwood Health Services, Toronto, Canada

2 Comparing Outcomes for Alcohol and Drug Abuse Clients: A 6-Month Follow-up of Clients who Completed a Residential Treatment Program Abstract Objective: The present study examined the impact of an inpatient addiction treatment program and whether client-related treatment outcomes were moderated by addiction type 1) alcohol only, 2) cocaine only or with alcohol, 3) cocaine with other substances 4) prescription drugs, and/or cannabis. Method: Clients completed self-reports of their substance use and quality of life during their first week in treatment and at 6-months post-discharge. Pre-treatment motivation and post-treatment aftercare attendance were also assessed. Results: Overall, a positive impact of the addiction treatment program was noted as clients reported a significant reduction in substance use and improvement in quality of life. Results also demonstrated that drug of choice impacted recovery status such that compared to cocaine poly substance clients, alcohol clients obtained significantly higher scores on quality of life measures at both pre- and 6-months posttreatment. However, cocaine poly substance clients were also significantly younger than alcohol only clients and were less likely to be married or employed. Conclusions: In general, substance use clients responded well to treatment. Some variability was noted among substance use groups namely that cocaine poly-drug users obtained lowest levels of post-treatment reduction in substance use. The implications of such findings are discussed. Keywords: alcohol, drug, treatment outcome 2

3 It has been a priority for clinicians in the addiction field to understand why certain clients respond to treatment while others do not. In general, clients have shown considerable variability in treatment success, confirming that the effects of addiction treatment are not the same for all people. Previous studies examining the efficacy of addiction treatment have revealed that at 1- year follow-up, as much as two thirds of clients have relapsed and are struggling with their substance use (Moos, Moos & Andrassy, 1999). Moreover, while some individuals are able to maintain abstinence and positive behavioral changes after completing addiction treatment for the first time, others require longer retention or multiple treatment episodes to experience the same benefits (Hser, Joshi, Anglin & Fletcher, 1999; Simpson & Sells, 1990). Such evidence suggests that there are particular factors that may moderate and predict recovery success. The variability in addiction treatment outcomes has led treatment providers on an ongoing pursuit to identify specific factors that predict successful recovery. At present, substantial evidence has shown that there are certain client characteristics that are associated with post-treatment progress. For example, several studies have shown that clients with high treatment motivation and engagement, 12-step participation, and social support were more likely to have favourable treatment outcomes (Comfort, Sockloff, Loverro & Kaltenbach, 2002; Laudet, Morgen & White, 2006; McLellan et al. 1994; Moos & King 1997; Simpson, Joe, Rowan-Szal & Grenner, 1997; Staines et al. 2003;). In addition, it has also been found that clients with greater severity of substance use, mental health problems, and multiple treatment admissions were more inclined to have poor treatment outcomes (Hser et al., 1999; McLellan et al. 1994; Simpson, Joe, & Broome, 2002). Despite the ample studies that have focused on addiction treatment outcomes, there are only a few that have specifically assessed the impact of primary substance use group on recovery status and these studies yielded mixed results. For example, Brower, Blow, Hill & Mudd (1994) compared outcomes for inpatients treated for alcohol only, cocaine only, or both substances, and found that similar improvements were observed in all three groups. Similarly, Patkar et al. (2004) compared clients pre-treatment characteristics and outcomes for alcohol only, cocaine only, and multi-substance dependence, and found that despite pretreatment differences overall, outcomes were more comparable than different across the three groups. However, other research has shown that at one year followup, alcohol only clients were more likely to be abstinent than clients dependent on cocaine or other drugs (Miller, Millman, & Keskinen, 1990). In addition, it was found that clients concurrently dependent on cocaine and alcohol had poorer treatment outcomes compared to those who were dependent on either substance alone (Shmitz, Bordnick, Kearney, Fuller, & Breckenridge, 1997). Neither of these studies, however, have controlled the inpatient treatment program, or examined a marijuana or prescription drug group. Furthermore, other key outcome measures such as clients life-functioning, satisfaction and motivation for treatment were not all considered. The purpose of the present study is to examine whether individual characteristics moderate treatment outcomes for clients participating in the same inpatient program. Specifically, the authors examined whether addiction group 1) alcohol only, 2) cocaine only, 3) cocaine with other substances, and 4) prescription drugs and/or cannabis impacted clients post-treatment quality of life, life satisfaction, aftercare attendance, and substance use. The impact of other individual characteristics such as motivation for treatment, and client satisfaction were also examined. The findings are of clinical utility in terms of outlining potential variability in clients response to treatment and subsequent treatment outcome. METHOD Participants Participants consisted of male and female clients above the age of 18 who were admitted for intensive inpatient addiction treatment from July 2004 to August Clients were diagnosed with chemical dependence using the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition (DSM-IV) (American Psychiatric Association, 1994). All clients receiving substance abuse treatment were eligible to participate as long as they were willing to complete a 3

4 baseline survey while in treatment and were willing to be contacted by phone at 6-months postdischarge. A total of 695 potential participants were approached during their orientation week of treatment and 512 (73.6%) clients agreed to participate. Of those participants, 67 (13.1%) did not successfully complete their treatment program as some decided to leave Bellwood against medical advice while others were therapeutically discharged by staff due to relapse or inappropriate behaviour. Relapse is detected using random urine screens. Clients who completed treatment were those who remained at Bellwood for the recommendation length of time which could vary from client to client. Of the remaining 445 clients who completed treatment, 367 (64%) were successfully contacted at 6-months follow-up 86% of alcohol clients, 78% of marijuana/prescription drug clients, and 66.7% of cocaine clients. Some differences were noted among clients who were and were not contacted at follow-up. Specifically, those who were employed were more likely to be followed-up [χ 2 (1, N=491) = 4.9, p<.05]. It was also found that clients who were followed-up were more likely to be alcohol clients compared to cocaine clients who were less likely to be followedup [χ 2 (2, N=512) = 22.7, p<.001]. A comparison among clients who did or did not complete follow-up also revealed a significant difference in age [F (1, 511) = 31.13, p<.001] such that clients with follow-up data were significantly older (M = 42.11, SD = 9.87) than clients who could not be contacted at 6-months post treatment (M = 35.32, SD = 11.68). Chi square analyses revealed no significant differences between successful and failed follow-up attempts related to gender, marital status, or whether or not the client resided in the province of Ontario, where the treatment facility is located.. The final sample of 367 participants with baseline and follow-up data consisted of both alcohol (n=219) and drug clients (n=148). Participants were mostly male (64.3%). Ages ranged from years, with an average age of Just under half of the participants (44.2%) were married or living common-law while 30.2% were single and had never been married. Approximately 25.5% were widowed, separated or divorced. The majority of clients (84.8%) had completed at least a high school education. Most participants were employed or in school, either on a full-time (61.5%) or a part-time (3.4%) basis. For most of the clients (63.1%) this was their first attempt at substance use treatment. On average, clients spent 37.7 (SD=15.2) days in residential treatment -- drug use clients spent an average of 47.7 (SD=13.3) days in treatment while alcohol use clients spent an average of 31.0 (SD=12.4) days in treatment. The majority of clients (59.7%) were admitted for alcohol addiction followed by cocaine addiction (25.1%) and marijuana and/or prescription drug addiction (15.3%). Based on their DSM IV (APA, 1994) diagnosis and pattern of substance use, clients were categorized into one of the following substance use groups based on their primary drug of concern: 1) alcohol only clients (n=219); 2) marijuana/prescription drug clients (n=56); 3) cocaine only clients (n=37); 4) cocaine poly drug clients (n=55). Alcohol only clients were those identified with alcohol dependence without drug dependence. Clients in the marijuana/prescription drug group were those diagnosed with cannabis and/or prescription drug dependence. These marijuana and prescription drug clients consisted of 20 clients with marijuana as their primary substance of choice, 12 clients with both marijuana and prescription drugs as their primary substances of choice and 24 clients with prescription drugs as their primary substance of choice. The marijuana and prescription drug use clients were grouped together because the past three studies conducted at Bellwood revealed that no significant outcome difference between these groups of clients on substance use and quality of life outcome at 3-months, 6-months one-year and five year follow-up (Hambley & Ahmad, 2005). These clients may or may not also have an alcohol dependency. Cocaine only clients were diagnosed with cocaine dependence and may or may not also have an alcohol dependency. Cocaine poly drug users were clients assessed as having a cocaine dependency in addition to a dependency on any other drug(s). Cocaine poly drug users may or may not also have a comorbid alcohol dependency. Inpatient Treatment Program All clients in the sample completed treatment at Bellwood Health Services, an abstinence based addiction treatment facility, in Toronto, Canada. The addiction treatment modality used at 4

5 Bellwood is that of the Caring Community. Treatment is delivered using a holistic continuum of care that is characterized by an assessment phase, intensive inpatient treatment and aftercare. The inpatient addiction treatment program addresses an individual s physical, psychological, social, and spiritual well-being. Relying heavily on group therapy, psychosocial, behavioural, spiritual, and physical health education, clients apply the information and skills learned during treatment in order to maintain long-term positive behaviour change and continued abstinence from addictive substances and behaviours. Although clients receive specific sessions related to alcohol and drug use, the treatment programs offered by Bellwood are for the most part, integrated. Initial treatment programs range in length from approximately 21 to 80 days and aftercare is included for at least one year (preferably five years) post-discharge for the majority of clients. Materials Predictor Variables Demographics: The age, education, marital status and gender of the participants were all assessed via self-report questionnaires collected during the clients assessment for treatment. Assessment of a comorbid emotional or psychiatric problem such as depression, anxiety, or personality disorder was completed by the resident physician using DSM-IV criteria (American Psychiatric Association, 1994). Substance Use History and Pattern of Use: Participants reported their substance use history by indicating the number of years in which alcohol and/or drugs have been a problem. The age of onset of problematic substance use was then be calculated by subtracting the number of years of problematic use from the participants age. Participants reported their patterns of substance use by indicating the quantity and frequency of alcohol consumption in the six months prior to entering treatment and again at 6-months follow-up. Quantity-frequency methods, where clients retrospectively report average or usual consumption, have been deemed a relatively sensitive and objective method of establishing consumption patterns and appropriate for tracking changes in such behaviour (Kadden & Litt, 2004; Sobell, Sobell, Connors, & Agrawal, 2003). This assessment of substance use was adapted from the Alcohol Timeline Followback (TLFB) method developed by Sobell and Sobell (1992). However, because a follow-up phone call was used, the TLFB calendar format was not used to enhance recall. Instead, clients were assisted with ease of substance use recall by trying to estimate the number of days in which alcohol was consumed in an average month and then to multiply that number by six. Clients were then asked to report the average number of drinks they consumed on a drinking day. Clients also indicated how many days in the last 6 months (out of 180) that they used various drugs (including cocaine, cannabis, hallucinogens, heroin, opioids/narcotics, amphetamines, etc.). Percent reduction in substance use was calculated by first determining each client s relative change in substance use at 6-months follow-up compared to baseline levels (i.e. 6-month post-treatment self-report of total drinks and or drug use was subtracted from baseline total). Once this difference in alcohol and/or drug use is calculated, it is then divided into its baseline value in order to determine the percent reduction in alcohol and/or drug use. For example, an alcohol client who consumed 6 drinks a day for 170 days at 6-months pre-treatment would have a baseline level of 1020 (6x170). At six-months post-treatment, the same client reduced his alcohol consumption to 2 drinks a day for 5 days yielding a follow-up level of 10 (2x5). Therefore, at follow-up, the percent reduction in alcohol consumption for this client would be ( )/1020 = 0.99 or 99%. Similarly, for a drug client who used drugs for 100 days in the 6-months before entering treatment, and 12 days at 6-month post-treatment, the percent reduction in drug-using days at follow-up would be (100 12)/100 = 0.88 or 88%. Treatment Entry Motivation: Motivation for entering treatment was assessed using the Treatment Entry Questionnaire (TEQ; Addiction Research Foundation, 1997)). The TEQ yields three scores: 1) internal positive motivation, represented by a client s personal, intrinsic motivation for entering treatment and the desire to get better; 2) internal negative motivation, or feelings of shame or guilt that motivate treatment entry and; 3) external coercion motivation, represented by external pressures or coercions that prompt an individual to seek treatment. 5

6 Participants rate their levels of treatment entry motivation by indicating their extent of agreement with twelve items using a seven-point Likert scale ranging from 1 strongly disagree to 7 strongly agree. Scores on each of the three subscale items are added such that higher scores are associated with higher levels of each type of motivation (Crobach s alpha =.78,.80, and.83 for the internal positive, internal negative and external coercion subscales, respectively). Satisfaction with Initial Residential Treatment: Client satisfaction with treatment was measured using the Client Satisfaction Questionnaire-8 (CSQ-8) developed by Attkisson and Greenfield (2004). The CSQ-8 is widely used in research designed to gauge client satisfaction with medical health treatment. Clients rate their satisfaction on a scale from 1 to 4 for eight separate items. Anchors represented by the 4 ratings differ from statement to statement and include for example: 4 Excellent, 3 Good, 2 Fair, 1 Poor for the statement, How would you rate the quality of the service you have received. In another example, ratings associated with the statement, If you were to seek help again, would you come back to our program? consisted of: 4 Yes, definitely, 3 Yes, I think so, 2 No, I don t think so, 1 No, definitely not. Scores obtained from the CSQ-8 can range from 8-32, with higher scores indicating higher levels of satisfaction with treatment services (Cronbach s alpha =.83). Addiction Treatment Outcomes Quality of Life was measured using the Behaviour and Symptom Identification Scale (BASIS-32; Eisen, Dill and Grob, 1994) and the Bellwood Well-being Scale. The BASIS-32 assesses self-reported difficulty in symptoms and functioning in five major areas: relation to self/others; daily living/role functioning skills; depression/anxiety; impulsive/addictive behaviour (including substance abuse), and psychosis. Clients indicate the degree of difficulty they have experienced with a variety of life areas by rating 32 items on a scale ranging from 0 no difficulty to 4 extreme difficulty. Higher scores on the BASIS-32 indicate a greater perception of difficulty with the various life areas and therefore a lower level of quality of life (Cronbach s alpha =.95). Aftercare Attendance: Participants responded to a series of closed-ended questions designed to assess attendance at three types of aftercare: individual counseling, 12-step program or Bellwood aftercare. Clients indicated their frequency of attendance for each of the three types of aftercare as either: two times per week or more, once per week, one to two times per month, sporadic attendance (e.g. attended sometimes), never, or not applicable. High involvement in aftercare was defined as the frequency of attendance recommended by the treatment program s recovery counsellors. For 12-step and Bellwood s aftercare program, high involvement was operationalized as a minimum of weekly attendance. For individual counseling, high involvement was operationalized as a minimum of monthly attendance. Low involvement was therefore operationalized as attendance frequencies that were less than recommended or not at all. Procedure Clients receiving inpatient addiction treatment at Bellwood Health Services were approached about the study during their first week of treatment. In order to participate, clients gave their informed consent and agreed to complete three phases of data collection baseline, inpatient treatment discharge, and 6-months follow-up. At baseline, self-report measures were administered during orientation week and consisted of demographic questions, substance use history, quantity and frequency of substance use before entering treatment, as well as the BASIS- 32 and the Treatment Entry Questionnaire. One day prior to inpatient treatment discharge, clients completed the Client Satisfaction Questionnaire. At 6-months follow-up, clients were contacted by telephone in order to complete the same battery of questionnaires and in addition, they were questioned about their aftercare participation. Clients were asked at baseline to provide names and telephone numbers of two people they knew well in order to corroborate their reports at follow up. An attempt was made to contact at least one collateral at follow up. If neither were available, recovery counsellors at Bellwood were asked if they were in touch with the clients and could comment on the client s recovery status. Collateral reports were obtained for 68.1% (n=250) of clients. Of those contacted, there was an 89.6% concurrence rate. Given the number of variables used in the study and the pre treatment, post treatment design, there were some missing data. Missing data was uncommon for the self-administered 6

7 questionnaires because research assistants could ensure forms were thoroughly completed both in-person during baseline data collection and over the phone for follow-up data collection. However missing data was possible when collecting information from client assessments (e.g. psychiatric comorbidity, employment status, etc.). To determine whether data were missing for systematic reasons, an analysis was run to determine whether any of the variables were missing more than 5% of their values. When this was found to be the case for any one variable, an examination of participant files were conducted to determine whether missing information could be found elsewhere in the assessment. This method proved to be effective, especially for missing psychiatric comorbidity data, as a thorough review of participants assessment forms yielded such information. As a result, none of the variables contained more than 5% missing data and therefore missing data was not deemed to be problematic. RESULTS Demographic Differences Between Substance Use Groups An examination of the client characteristics of the alcohol and three drug groups (marijuana/prescription, cocaine only and cocaine poly drug users) revealed a number of significant differences (see Table 1 for summary of client and demographic characteristics). In particular, it was found that cocaine only clients were more likely to be male. Alcohol clients were significantly more likely to be married, while cocaine poly drug users were least likely to be married. In addition, clients in all three-drug groups were significantly younger than the clients in the alcohol group and the cocaine poly drug users were also significantly younger than the marijuana/prescription drug users. In terms of client characteristics, there were no significant differences obtained between the four groups on measures of employment status, employer involvement, or whether clients lived with someone who used substances. It should be noted that alcohol clients were more likely to be a student or employed even though the overall association between employment status and substance use group was not significant. Treatment Differences Between Substance Use Groups Treatment characteristics of the alcohol and three drug groups uncovered two significant differences (see Table 2 for summary of treatment characteristics). Results revealed that marijuana/prescription drug clients were more likely to have a concurrent psychiatric disorder such as depression or anxiety compared to clients in the other substance use groups. Comparisons also revealed that alcohol clients were more likely to complete treatment while cocaine poly drug users were more likely to discharge prematurely. In addition, a oneway analysis of variance revealed that age of onset of problematic substance use differed significantly among the primary substance use groups F(3, 364) = p<.001. Tukey s HSD post hoc analyses revealed that all pairwise comparisons between primary substance use groups differed significantly except for the marijuana/prescription drug and cocaine only clients. Overall, it was noted that cocaine poly substance users developed their substance use problem at the youngest age in their teens (M = 18.7, SD = 8.00) whereas alcohol clients developed their substance use problem in much later on in life (M = 33.0, SD = 11.7). As for the treatment variables, no significant differences were found between the groups on measures treatment entry motivation, treatment satisfaction, aftercare involvement or whether clients had completed previous treatment. Substance Use To examine the impact of the treatment program on substance use, percent reductions in alcohol and drug consumption were calculated (as described above). On average, participants reduced their alcohol consumption by 81.9%( SD=45.4) and their drug consumption by 87.6%( SD=26.1). Table 3 summarizes the average percent reduction of alcohol and drug use for each substance use group. On average, marijuana/prescription drug clients had the greatest percent reduction in both alcohol and drug use. Recovery status based on substance use improvement was determined by examining quantity and frequency of 6-month, follow-up alcohol and drug use as well as the client s overall percent reduction in substance use. Clients were categorized as being in either high or low 7

8 recovery: high recovery clients were abstinent or obtained at least a 95 per cent reduction in substance use; low recovery clients were those who had a 94 per cent reduction in substance use or less, or those who had more than one lapse per month on average. In order to explore any variability in substance use recovery status among the alcohol and drug clients, a chi square analysis was conducted to determine the proportion of clients in high and low recovery among the four groups of clients. Results revealed a significant association between recovery status and primary substance problem group [χ 2 (3, N = 367) = 11.2, p<.05]. The percent of clients in high and low recovery from each substance use group is shown in Figure 1. While the majority of all clients were in high recovery (72.5%), the proportion of clients in high recovery was greatest for the marijuana/prescription drug group (80.4%) and lowest for cocaine poly substance users (56.4%). Approximately 75.8% of alcohol clients and 64.9% of cocaine only clients were in high recovery at 6-months follow-up. To account for significant demographic differences noted between the primary substance problem groups at admission, a series of separate chi square analyses were conducted to examine the potential association between, marital status, gender, and psychiatric comorbidity and recovery status, regardless of primary substance problem group. Results revealed no significant associations between high or low recovery and gender [χ 2 (1, N = 367) =.34, ns], marital status [χ 2 (1, N = 364) =.09, ns], or psychiatric comorbidity [χ 2 (1, N = 366) =.69, ns]. A significant difference in age was however noted between clients in high and low recovery [F (1, 366) = 6.71, p<.05]. Results from the oneway analysis of variance revealed that clients in high recovery (M = 43.45, SD = 11.55) were significantly older than clients in low recovery (M = 39.94, SD = 11.76). Aftercare At follow-up, the majority of clients (76.3%) indicated they regularly attended at least one form of aftercare. A chi square analysis was performed to examine the relationship between any form of regular aftercare attendance and substance use recovery status. Results are summarized graphically in Figure 2 and revealed a significant association between recovery status and regular aftercare attendance [χ 2 (2, N = 367) = 13.93, p=.001]. Of the clients who regularly attended two or more forms of aftercare, 81.7% were in high recovery compared to 70.1% of those who regularly attended one form of aftercare. Only 59.8% of clients who did not regularly attend any form of aftercare were in high recovery at 6-months follow-up. Quality of Life A one-way repeated measures analysis of covariance was conducted to examine the primary substance problem groups baseline and 6-months follow-up BASIS-32 scores while controlling for age, gender, psychiatric comorbidity and marital status.. Tests of between-subjects effects revealed a significant main effect for primary substance problem group when controlling for the demographic variables [F (1, 356) = 8.91, p<.001]. Once this trend was detected, a more parsimonious repeated measures analysis of variance was conducted using only the primary substance problem group variable to examine pre and post treatment quality of life scores for the four groups and to examine their post hoc comparisons. Comparisons were again made among the various substance use groups and their data is depicted graphically in Figure 3. In addition to obtaining a significant main effect for time [Wilks Lambda =.85, F(1, 361)=61.51, p<.001, multivariate partial eta squared =.15], results of the BASIS-32 analysis reveal a significant main effect for substance use group [F(3, 361) = 13.99, p <.001]. Post hoc analyses reveal that mean scores on the BASIS-32 differed significantly between alcohol clients and all three-drug use groups at pre- and post-treatment time intervals. Alcohol clients had the lowest level of perceived difficulty with life domains at both data collection points. No significant interaction between substance use group and time interval was obtained at follow-up, the alcohol clients reported better perceived quality of life, but these clients also came into treatment with lower levels of perceived difficulty with life domains. 8

9 Correlates of Treatment Outcome A series of bivariate correlations were conducted between quality of life measures and percent reduction in substance use (See Table 4 for correlations). It was found that participants percent reduction in both alcohol and drug use was significantly associated with quality of life such that those who experienced greater levels of reduction in substance use also experienced higher levels of quality of life at 6-months follow-up. It is also of interest to note that satisfaction with treatment was significantly related to positive internal motivation for treatment such that higher levels of satisfaction with treatment were associated with higher levels of internal positive motivation for treatment. DISCUSSION The purpose of the present study was to examine the overall impact of an inpatient addiction treatment program and to determine whether any individual variables moderated quality of life and substance use outcomes. In general, results revealed that participants responded well to the inpatient treatment program. On average, significant improvements in substance use and quality of life at 6-months post-treatment were obtained. These results are worth highlighting as previous research has demonstrated that abstinence at 6-months post-treatment was predictive of abstinence at five years post-treatment (Weisner, Ray, Mertens, Satre & Moore, 2003). Furthermore, it has also been established that the first 6-months post-treatment is a critical time period since 60 to 80 per cent of relapses occur within this period (McLellan et al., 1993). Therefore these results are a good indication of how addiction treatment clients may fare in the long-term. While overall, clients alcohol and drug use was significantly reduced, some variability was noted among the different substance dependent groups. In particular, it was found that alcohol and marijuana/prescription drug clients achieved better substance use outcomes compared to cocaine use clients. It was also found that cocaine poly substance users obtained the lowest levels of post-treatment reduction in drug use. These results are consistent with previous findings that demonstrate that alcohol patients have higher abstinence rates compared to those dependent on both cocaine and alcohol (Miller, et al., 1990). Such findings are not surprising given that poly-substance abusers demonstrate increased impulsivity (McCormick, Dowd, Quirk, & Zegarra, 1998), and present with more psychiatric problems than do patients with only alcohol dependence (Cunningham, Corrigan, Malow, & Smason, 1993; Patkaar, et al., 2004). Similarly, it has been found that clients who use multiple substances have displayed a wider range and more complex set of problems than those who use only one substance (Heil, Badger, and Higgins, 2001). Although all clients obtained significant increases in quality of life at 6-months post treatment, it was found that alcohol clients had significantly higher levels of quality of life in general compared to drug use clients. These results are consistent with the hypothesis investigated by Garg et al. (1999). In particular, Garg et al. (1999) proposed that clients with multi-drug dependence would have more emotional impairment and thus a lower level of quality of life than would clients with only alcohol dependence. However, in their investigation of alcohol and drug dependent patients attending inpatient, outpatient and partial hospitalization, Garg et al. (1999) did not find any significant differences between alcohol dependent clients and drug and alcohol dependent clients on measures of quality of life as expected. Unlike these findings, results from the present study did however yield significant differences in quality of life between alcohol dependent clients and poly drug dependent clients. Therefore, findings from the present study are not consistent with Garg s et al. (1999) results, but instead, support their initial hypothesis and may reflect the possibility that multi-drug dependent clients have more emotional impairment than clients with only alcohol dependence. Related to this theory is our finding that compared to the other groups of clients, cocaine poly drug users developed their substance use problem at a significantly younger age. The implications of this early onset of substance abuse may explain the lower level of quality of life for these cocaine clients. For example, as is the case with most addicts, the social and emotional development process is cut short because most addicts self medicate in order to avoid dealing 9

10 with feelings, relationships and emotions. The substance use serves as an isolating and maladaptive coping mechanism. This may prevent the individual from growing emotionally and socially and developing meaningful relationships and adequate problem solving strategies. As a result, cocaine clients may perceive more difficulty with life functioning. Quality of life was also strongly related to post-treatment substance use. As one might expect, decreases in both alcohol and drug use are significantly associated with improved quality of life at 6-months post-treatment. Future research should continue to employ such measures as a means of evaluating treatment outcome. This finding is consistent with previous research revealing that clients social adjustment at follow-up is primarily and negatively predicted by the severity of family, psychiatric and employment problems at admission (McLellan et al., 1994). In the present sample, cocaine poly drug users obtained the lowest levels of post treatment quality of life and percent reduction in substance use. In addition, it was also found that cocaine poly substance clients were less likely to be married or employed and were significantly younger than alcohol and marijuana/prescription drug clients. Cocaine poly substance clients were also more likely to discharge prematurely and fail to complete inpatient addiction treatment. These findings suggest that the type of substance dependence may impact outcome variables because of inherent demographic and treatment differences between the alcohol, marijuana/prescription drug, and cocaine clients. These differences have important implications for treatment providers. For example, compared to alcohol clients, drug clients may not have the same level of social support that is afforded by important work and personal relationships while in initial treatment and within the first few months of recovery. Given that the presence of social supports is so vital in the recovery process, (Laudet et al, 2006) it is especially important for these younger substance use clients to establish positive and meaningful support networks while in initial treatment in order to complete treatment and to improve their chances of recovery success. Therefore treatment providers should attempt to improve treatment retention of cocaine and poly drug use clients by understanding some of the issues that influence whether or not these clients engage in the continuum of care. It is also important that treatment providers ensure that aftercare supports are tailored to the unique needs of these clients. Other noteworthy findings of the present study revealed that aftercare attendance was significantly related to substance use. In particular, it was found that regular attendance at two or more aftercare programs was associated with the largest proportion of clients in high recovery. These findings are not surprising, as previous research has consistently demonstrated the importance of attending post-treatment aftercare to improve relapse prevention (Gossop et al., 2003 & Ritsher, McKellar, Finney, Otilingam & Moos, 2002). By engaging in a form of organized support, it appears that clients in aftercare are not resuming the maladaptive coping patterns sustained by their chemical dependence and instead are preventing a return to active addiction by turning to others in times of need. These findings reinforce the importance of continuing care and emphasize that rehabilitation does not end when the client leaves the safe and controlled environment of inpatient treatment. Moreover, it is during this time of transition that recovering addicts are beginning to practice and refine the skills learned in treatment and therefore require ongoing support. Results from the present study confirm that continuing care is important for successful recovery namely that more support is better. Limitations Results from the present study may be limited in that all data was obtained through selfreport questionnaires. Although it is reasonable to question the accuracy of such measures, collateral reports were used to increase the reliability of self-reported substance use. Past research has found that in general, self-reported substance use can be a good indicator of treatment outcome (Miller & Hoffmann, 1995). The results from the present study support this assertion as over 89 per cent of collaterals that were contacted confirmed clients reports of substance use. Future research should continue to use collaterals as a means of verifying the accuracy of self-reported treatment outcomes. From a methodological standpoint, there are also certain limitations inherent to conducting research in an applied setting. The practical constraints and well being of the clients take precedence over scientific methodology. In particular, the use of random assignment into 10

11 treatment and control groups is not ethical and was not possible for the present study. Therefore, causal inferences about the specific effects of treatment cannot be made conclusively. Instead, it is only possible to outline the associations among the individual, treatment and outcome variables and the practical utility of the various trends detected in the data. Also, the likelihood of correctly detecting true effects in the analyses is hampered by the unequal sample sizes among the various primary substance use groups. While there may be certain methodological limitations associated with conducting research in the applied setting, there are noticeable benefits from a practitioner s point of view. For example, when conducting 6-month follow-up calls, research assistants were able to reconnect clients with their recovery counselors if it was found that clients were experiencing difficulties. Clients were also able to share any comments to the research assistants about the treatment program. This feedback is valuable to help the treatment facility improve programming to best meet the needs of their current and future clients. It is also rewarding for staff to learn of client successes as well. Research results can therefore be presented to staff as a means of quality assurance and evidence-based practice. Nonetheless, despite certain constraints, much can be gained from future research that aims to understand how and why certain individuals respond well to addiction treatment while others may not. 11

12 References Addiction Research Foundation (1997). Treatment Entry Questionnaire. Toronto, ON: Author American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4 th ed.). Washington, DC: APA Attkisson, C. C., & Greenfield, T. K. (2004). The USCF Client Satisfaction Scales: I. The Client Satisfaction Questionnaire-8. The use of psychological testing for treatment planning and outcomes assessment: Volume 3: Instruments for adults (3 rd ed.) Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers. Brower, K. J., Blow, F. C., Hill, E. M., & Mudd, S. A. (1994). Treatment outcome of alcoholics with and without cocaine disorders. Alcoholism: Clinical and Experimental Research, 18, Carlson, M. J., & Gabriel, R. M. (2001). Patient satisfaction, use of services, and one-year outcomes in publicly funded substance abuse treatment. Psychiatric Services, 52, Comfort, M., Sockloff, A., Loverro, J., & Kaltenbach, K. (2003). Multiple predictors of substanceabusing women s treatment and life outcomes: A prospective longitudinal study. Addictive Behaviors, 28, Cunningham, S. C., Corrigan, S. A., Malow, R. M., & Smason, I. H. (1993). Psychopathology in inpatients dependent on cocaine or alcohol and cocaine. Psychology of Addictive Behaviors, 7, Doerfler, L. A., Addis, M. E., & Moran, P. W. (2002). Evaluating mental health outcomes in an inpatient setting: convergent and divergent validity of the OQ-45 and BASIS-32. Journal of Behavioral Health Services & Research, 29, Eisen, S. V., Dill, D. L., Grob, M. C. (1994). Reliability and validity of a brief patient-report instrument for psychiatric outcome evaluation. Hospital and Community Psychiatry, 45, Garg, N., Yates, W. R., Jones, R., Zhou, M. and Williams, S. (1999). Effects of gender, treatment site and psychiatric comorbidity on quality of life outcome in substance dependence. American Journal on Addictions, 8, Gossop, M., Harris, J., Best, D., Man, L., Manning, V., Marshal, J., & Strang, J. (2003). Is attendance at alcoholics anonymous meetings after inpatient treatment related to improved outcomes? A 6-month follow-up study. Alcohol and Alcoholism, 38, Hambley, J. & Ahmad, S. (2005, November). Predictors of Alcohol and Drug Treatment Outcomes: A 6-month Follow-Up of Clients Attending a Residential Treatment Program. Paper presented at the Issues of Substance Conference of the Canadian Centre on Substance Abuse. Markham, ON. Heil, S. H., Badger, G. J., and Higgins, S. T. (2001). Alcohol dependence among cocainedependent outpatients: demographics, drug use, treatment outcome and other characteristics. Journal of Studies on Alcohol, 62(1),

13 Hser, Y. I., Joshi, V., Anglin, M. D., & Fletcher, B. W. (1999). Predicting post-treatment cocaine abstinence: What works for first-time admissions and treatment repeaters. American Journal of Public Health, 89(5), Kadden, R. M., & Litt, M. D. (2004). Searching treatment outcome measures for use across trials. Journal of Studies on Alcohol, 65(1), Laudet, A. B., Morgen, K., and White, W. L. (2006). The role of social supports, spirituality, religiousness, life meaning and affiliation with 12-step fellowships in quality of life satisfaction among individuals in recovery from alcohol and drug problems. Alcohol Treatment Quarterly, 24(1-2), Marlowe, D. B., Merikle, E. P., Kirby, K. C., Festinger, D. S., & McLellan, A. T. (2001). Multidimensional assessment of perceived treatment-entry pressures among substance abusers. Psychology of Addictive Behaviors, 15, McCormick, R. A., Dowd, E. T., Quirk, S. & Zegarra, J. H. (1998). The relationship of NEO-PI performance to coping styles, patterns of use, and triggers for use among substance abusers. Addictive Behaviors, 23, McLellan, A. T., Grissom, G. R., Brill, P., Durell, J., Metzger, D. S., & O Brien, C. P. (1993). Private substance abuse treatments: are some programs more effective than others? Journal of Substance Abuse Treatment, 10, McLellan, A. T., Alterman, A. I., Metzger, D. S., Grissom, G. R., Woody, G. E., Luborsky, L. & O Brien, C. P. (1994). Similarity of outcome predictors across opiate, cocaine, and alcohol treatments: Role of treatment services. Journal of Consulting and Clinical Psychology, 62, Miller, N.S., & Flaherty, J. A. (2000). Effectiveness of coerced addiction treatment (alternative consequences). A review of the clinical research. Journal of Substance Abuse Treatment, 18, Miller, N. S. & Hoffmann (1995). Addiction treatment outcomes. Alcoholism Treatment Quarterly, 12, Miller, N. S., Millman, R. B., & Keskinen, S. (1990). Outcome at six and twelve months post inpatient treatment for cocaine and alcohol dependence. Advances in Alcohol Substance Abuse, 9(3-4), Moos, R. H., Moos, B. S., & Andrassy, J. M. (1999). Outcomes of four treatment approaches in community residential programs for patients with substance use disorders. Psychiatric Services, 50, Moos R. H., & King, M. J. (1997). Participation in community residential treatment and substance abuse patients' outcomes at discharge. Journal of Substance Abuse Treatment 14, Patkar, A. A., Thornton, C. C., Mannelli, C. C., Hill, K. P., Gottheil, E., Vergare, M. J., & Weinstein, S. P. (2004). Comparison of Pretreatment Characteristics and Treatment Outcomes for Alcohol-, Cocaine-, and Multisubstance-Dependent Patients. Journal of Addictive Diseases, 23,

14 Ritsher, J. B., McKellar, J. D., Finney, J. W., Otilingam, P. G. & Moos, R. H. (2002). Psychiatric comorbidity, continuing care and mutual help as predictors of five-year remission from substance use disorders. Journal of Studies on Alcohol, 63, Schmitz, J. M., Bordnick, P. S., Kearney, M. L., Fuller, S. M. and Breckenridge, J. K. (1997). Treatment outcome of cocaine-alcohol dependent patients. Drug and Alcohol Dependence, 47(1), Sederer, L. I., Dickey, B., & Eisen, S. V. (1997). Assessing outcomes in clinical practice. Psychiatric Quarterly, 68, Simpson, D. D., Joe, G. W., & Broome, K. M. (2002). A national 5-year follow-up of treatment outcomes for cocaine dependence. Archives of General Psychiatry, 59, Simpson, D. D., & Sells, S. B. (eds.). Opioid Addiction and Treatment: A 12-Year Follow-Up. Malabar, FL: Krieger Publishing Company, Sobell, L. C., Sobell, M. B., Connors, G. J., & Agrawal, S. (2003). Assessing drinking outcomes in alcohol treatment efficacy studies: selecting a yardstick of success. Alcoholism: Clinical and Experimental Research, 27(10), Staines, G., Magura, S., Rosenblum, A., Fong, C., Kosanke, N., Foote, J., & Deluca, A. (2003). Predictors of drinking outcomes among alcoholics. The American Journal of Drug and Alcohol Abuse, 29, Weisner, C., Ray, G. T., Mertens, J. R., Satre, D. D., & Moore, C. (2003). Short-term alcohol and drug treatment outcomes predict long-term outcome. Drug and Alcohol Dependence, 71(3),

15 Table 1 Client and Demographic Characteristics of Alcohol and Drug Clients Comparing Outcomes for Alcohol and Drug Clients Substance Use Group Alcohol M or % (SD) Marijuana/ Prescription M or % (SD) Cocaine Only M or % (SD) Cocaine Poly-Drug M or % (SD) Male a 65.5 Comparisons χ 2 3df = 9.344, p<.05 Married or Common Law Employed or Student Age Living Situation living with someone who uses 56.0 b c χ 2 3df = , p< Not Significant 47.0 d (10.4) 39.1 (12.0) 36.4 e (8.3) 32.3 (8.7) F (3, 363) = p< Not Significant Note: a = significant greater proportion of males in the cocaine only group b = significant greater proportion are married or common law in the alcohol group c = significant lower proportion are married or common law in the cocaine poly-drug group d = significant greater proportion are older in the alcohol group e = significant greater proportion are younger in the cocaine only group than the alcohol and marijuana/prescription group 15

16 Table 2 Client and Treatment Characteristics of Alcohol and Drug Clients Substance Use Group TEQ Internal Positive Motivation TEQ Internal Negative Motivation TEQ External Coercion Motivation Treatment Satisfaction (CSQ) Completed Treatment High Aftercare Involvement Previous Treatment Alcohol M or % (SD) 26.2 (3.1) 12.3 (5.6) 10.7 (6.9) 28.0 (3.3) Marijuana/ Prescription M or % (SD) 26.2 (2.9) 11.6 (5.5) 10.1 (6.1) 28.0 (3.7) Cocaine Only M or % (SD) 25.4 (3.8) 12.5 (4.9) 11.8 (6.1) 28.8 (2.9) Cocaine Poly- Drug M or % (SD) 26.2 (2.8) 13.3 (5.5) 10.4 (6.6) 28.3 (2.7) Comparison Not Significant Not Significant Not Significant Not Significant 95.4 a b χ 2 3df = 50.00, p< Not Significant a 29.6 Not Significant Psychiatric Comorbidity Age of Onset of Problem d (years) c (11.7) (11.4) (9.3) (8.0) χ 2 3df = 10.11, p<.05 F(3, 364) = p<.001 Note: a = significant greater proportion completed treatment in the alcohol group b = significant lower proportion completed treatment in the cocaine poly-drug group c = significant greater proportion have a concurrent psychiatric disorder in the marijuana/prescription drug d = significant differences noted among all post hoc pairwise comparisons except between marijuana/prescription drug and cocaine only clients 16

17 Table 3 Average Percent Reduction of Substance Use Client Group Alcohol Use Drug Use % Reduction % Reduction M (SD) M (SD) Alcohol Only (134.0) n/a Marijuana/ (48.7) (14.6) Prescription Drug Cocaine Only (132.9) (25.0) Cocaine Poly (56.2) (32.3) Drug 17

18 Table 4 Correlations Between Baseline and Follow-up Variables Variable % reduction alcohol --.26** ** 2. % reduction drugs * ** 3. Treatment satisfaction --.16* TEQ internal positive ** TEQ internal negative --.43** TEQ external coercion Baseline BASIS-32 total --.41** 8. Follow-up BASIS-32 total -- * p <.05 **p <.01

19 Figure 1 Recovery Status by Substance Use Group percent of clients High Recovery (n=266) Low Recovery (n=101) 0 alcohol only (n=219) marijuana/ prescription drug (n=56) cocaine and alcohol (n=37) cocaine poly drug (n=55) Substance Use Group Note: There is a significant association between recovery status and substance use group [χ 2 (3, N = 367) = 11.2, p<.05]. 19

20 Figure 2 Recovery Status by Aftercare Support Usage percent of clients High Recovery (n=266) Low Recovery (n=101) 0 none (n=87) one (n=89) two or more (n=125) Number of Regular Aftercare Supports Used Note: There is a significant association between recovery status and regular aftercare attendance [χ 2 (2, N = 367) = 13.93, p=.001]. 20

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