Maintenance of HIV risk reduction among injection opioid users: a 12 month posttreatment follow-up

Drug and Alcohol Dependence 47 (1997) 11 – 18

Maintenance of HIV risk reduction among injection opioid users: a 12 month posttreatment follow-up L.M. Camacho *, N.G. Bartholomew, G.W. Joe, D.D. Simpson Institute of Beha6ioral Research, Texas Christian Uni6ersity, TCU Box 298740, Fort Worth, TX 76129, USA Received 20 September 1996; accepted 13 April 1997

Abstract Study objectives were to examine HIV risk behaviors 12 months following methadone maintenance (MM) treatment termination, and to assess the effects of treatment tenure, cocaine use, and gender on posttreatment HIV risk. Injection and sex risk behaviors were measured at treatment entry and 12 months after leaving treatment among 435 injection opioid users. Multi-way contingency tables for treatment tenure and HIV risk at treatment intake and at 12 month follow-up were analyzed using the GSK weighted least-squares estimation procedure. The effects of treatment tenure, gender, and cocaine use on risk behavior at follow-up, while controlling for intake risk and background variables were tested using a series of multiple logistic regression analyses. Results showed that injection and sex risk behaviors were significantly lower at 12 month follow-up than at treatment entry. Additionally, increased tenure was related to risk reductions, while cocaine use was related to increased risk-taking. Gender was generally unrelated to risk changes. These findings support broader use of MM in helping reduce HIV risks among injection drug users and highlight the need to explore ways to encourage treatment compliance in order to reduce risky practices. © 1997 Elsevier Science Ireland Ltd. Keywords: HIV; Injection opioid user; Methadone maintenance treatment

1. Introduction Rates of HIV infection and AIDS among injection drug users (IDUs) continue to increase. Currently, about 37% of reported AIDS cases are linked in some way to injection drug use (Centers for Disease Control and Prevention, 1995). In addition, sex with an IDU appears to be a primary mode of heterosexual and neonatal transmission, with perhaps 65% of cases among women linked to personal injection and/or sex with an IDU and at least 55% of neonatal cases linked to having an IDU parent. Recent studies indicate that methadone maintenance (MM) treatment is helpful in reducing HIV risk-taking behaviors among injection

* Corresponding author.

opioid users (Ball et al., 1988; Camacho et al., 1996; Caplehorn and Ross, 1995; Gottheil et al., 1993; Longshore et al., 1993). These findings support broader use of MM for this high-risk group of drug users. Although more research is still needed to help determine what specific aspects of MM treatment are the most useful in helping stem the spread of HIV among IDUs, increasing treatment tenure (entering and staying with a program) seems to have a positive impact on lowering HIV risks. Williams et al. (1992) found lower seroconversion rates (2 vs. 19%) among IDUs who remained continuously in MM treatment during a 39 month study period, when compared to those who left treatment. Subjects in continuous treatment reported less needle sharing, as well as fewer needle-sharing and sex partners. Similarly, an 18 month follow-up study found a 22% seroconversion rate for out-of-treatment

0376-8716/97/$17.00 © 1997 Elsevier Science Ireland Ltd. All rights reserved. PII S 0 3 7 6 - 8 7 1 6 ( 9 7 ) 0 0 0 5 6 - 2

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subjects, compared to a 3.5% rate for those who remained in MM (Metzger et al., 1993). Additional studies are needed, however, to help determine if reduced risk-taking continues after clients leave MM and explore relationships between treatment tenure and longterm risk reduction after treatment. Recent studies also have examined how factors such as cocaine use and gender are associated with risk for contracting HIV (Booth et al., 1995; Camacho et al., 1996; Joe and Simpson, 1995). For example, Joe and Simpson (1995) found that cocaine users compared to nonusers and women compared to men entering MM programs engaged in more HIV-risky sex and injection practices. In the same study population, Camacho et al. (1996) found that MM treatment helped lower risk-taking behaviors during treatment, but cocaine users and women showed lower rates of change than nonusers and men. Because cocaine use is common among opioid users admitted to MM treatment programs (Condelli et al., 1991; Joe et al., 1994; Kolar et al., 1990), it is important to understand if cocaine users continue to engage in higher risk behaviors after leaving treatment. Similarly, because women involved in the drug culture face higher HIV risks, either by their own injection practices or by having an IDU sex partner (Brown and Weissman, 1993; Cohen, 1991; Dwyer et al., 1994), knowing whether or not risk-reduction efforts are maintained after treatment can help treatment providers tailor better programs for women. The present study was designed to broaden the during-treatment HIV risk reduction findings by Camacho et al. (1996) with the same treatment population and with comparable HIV risk indicators. One purpose was to examine the maintenance of lower risk behavior rates 12 months following discharge from MM treatment, and the second was to assess the effects of treatment tenure, cocaine use, and gender on posttreatment HIV-risky behaviors. To accomplish this, changes in risk behaviors such as drug injection frequency, use of ‘dirty works,’ number of sex partners, and frequency of unprotected sex were examined at treatment intake and at 12 month follow-up. In addition, treatment tenure, (B90 days, 90 – 360 days, and \ 360 days) cocaine use, and gender were examined to evaluate their relationship to treatment outcomes. It was hypothesized that overall reductions in risk behaviors observed during treatment would be maintained 12 months after leaving treatment, but that cocaine users and women would continue to show evidence of more injection and sex-related risks. However, it was predicted also that treatment retention would have an impact on how well risk-reduction changes were maintained at follow-up, with clients who stayed in treatment longer showing stronger persistence of change.

2. Method

2.1. Sample Study participants were opioid addicts admitted to three public methadone treatment programs in Texas as part of a federally-funded treatment evaluation project (Simpson et al., 1997). All clients received no-fee treatment services as an incentive to participate in the research, and written informed consent was obtained after treatment and data collection procedures were explained. A total of 711 clients participated in the 12 month posttreatment follow-up phase of the project. These were clients who had been admitted between April 1990 and August 1993, dates that allowed the opportunity to be in treatment for at least a full year. Of the 711 clients, 643 (90%) were located by trained interviewers. Interviews were completed for 435 clients (61% of 711 sample); of the other located clients, 134 (19%) were in prison and unavailable for interview, 21 (3%) were deceased, 36 (5%) had moved out of state, 14 (2%) refused to be interviewed, and 3 (1%) were medically incapacitated. The high percentage of clients found to be incarcerated at follow-up was associated with a large expansion of prison facilities in Texas during this study and a simultaneous increase in the rate of parole revocations. This subsample of prisoners has been included in our other evaluations of follow-up outcomes (Hiller et al., 1997), but were excluded from this study to avoid confounding effects from truncated treatment retention due to imprisonment and the absence of posttreatment performance indicators. In terms of sociodemographics, 69% of the 435 follow-up interviewees were males and mean age was 37 years (S.D.= 7.4); 43% were Mexican American, 36% Caucasian, and 17% African American (Table 1). Almost half (48%) were married or living as married and 61% had graduated from high school or received a GED. Only 57% worked (full- or part-time or odd jobs) within the 6 months before treatment intake, while 31% had been arrested once or more often during that time; 47% were legally involved (primarily parole) but less than 5% had been officially referred to treatment by legal authorities. All clients were daily opioid users. After opioids, cocaine (used intravenously) was the most common illicit drug of choice and was used by almost 3/4 of the sample in the 6 months prior to treatment—27% used it daily, 16% weekly, and 25% less-than-weekly. Additionally, 13% reported crack/ freebase use. Concerns about potential sampling bias between the interviewed (n= 435) and noninterviewed (n=276) clients were addressed by comparing the two groups on demographics, treatment history, legal involvement, and pretreatment drug use. Contingency table analyses showed the two were not different on these measures,

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Table 1 Description of sample Tenure Group

Gender Male (%) Female (%) Age (years) 18–30 (%) 31–35 (%) 36–40 (%) \40 (%) Mean (S.D.) Race-ethnicity African American (%) Mexican American (%) White (%) Other (%) High school graduate Yes (%) Employment Any Employment (%) Marital status Married (includes common law) (%) Alcohol use Never (%) Less than weekly (%) At least weekly (%) Cocaine use Never (%) Less than weekly (%) At least weekly (%) Speedball use Never (%) Less than weekly (%) At least weekly (%) Methadone dose Mean (S.D.) Range Counseling sessions Mean (S.D.) Range

B90 days (n=136)

90 – 360 days (n = 163)

\360 days (n = 136)

Total (n =435)

69 31

72 28

64 36

69 31

18 28 28 26 36 (7.5)

23 20 28 29 36 (7.4)

16 29 34 21 37 (7.5)

20 25 30 26 37 (7.4)

21 43 31 5

17 45 34 4

12 41 42 5

17 43 36 4

40

40

45

42

50

60

59

57

46

47

51

48

21 27 53

18 30 52

24 33 43

21 30 49

42 27 31

45 29 26

49 30 21

45 29 26

38 23 39

46 20 34

51 25 24

45 23 33

39 (12.0) 10–65

42 (12.2) 0 – 80

43 (11.1) 20 – 90

41 (11.9) 0 – 90

2 (2.2) 0–12

12 (8.1) 0 – 37

50 (28.9) 2 – 147

21 (26.2) 0 – 147

with the exception that the interviewed clients were more likely to be married than the noninterviewed clients (49 vs. 36%; x 2(2,711) =11.44, P B .01). We also investigated and found that the two samples differed in terms of discharge reasons (x 2(2, n =711) = 7.90, PB .02). Because 10% of each group was terminated for reasons of noncompliance, the significance was due to differences for leaving program against medical advice (AMA) and for other reasons (released, transferred, incarcerated, hospitalized, deceased, other); 58% of the noninterviewed left AMA versus 47% of the interviewed sample; correspondingly, 32% of the noninterviewed sample left for other reasons (mainly transfers) versus 42% of the interviewed sample. Of primary importance is that noncompliance discharge rates were the same for both groups, implying that the noninterviewed were not less compliant with program rules.

2.2. Treatment procedure The average methadone dose was about 40 mg throughout treatment, but ranged up to 90 mg per day for some individuals. This average level is low compared to currently recommended therapeutic standards (Cooper, 1992), but it is representative of national trends as reported in a study that indicated 2/3 of methadone programs in the US provided doses of 50 mg or less (D’Aunno and Vaughn, 1992). Clients were encouraged to attend multiple counseling sessions per month, although program policy based on state guidelines required only one session per month. On average, the cumulative number of counseling sessions attended per client during treatment was 21, but this varied by treatment tenure; those in treatment under 90 days

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averaged two sessions, those completing between 90– 360 days averaged 12 sessions, and those staying over 360 days averaged 50 sessions. At the time of the follow-up interview 40% of the clients were in a drug treatment program. (For a more detailed description of treatment procedures see Simpson et al., in press,c).

2.3. Follow-up procedure Clients were located and interviewed by trained follow-up workers approximately 12 months after they left treatment in the DATAR project. The follow-up interview was similar in structure and content to the interview completed by clients at treatment intake (see Simpson, 1992). It included information on demographic factors, family functioning, peer relations, criminal behaviors, drug use, treatment, and HIV/ AIDS risk behavior. The interviews took approximately 80 min to complete and respondents were paid $20 for the interview and an additional $5 for a urine specimen.

2.4. HIV risk measures Items measuring HIV-risky behavior were included in both the intake and follow-up interviews; all measures assessed risk behavior in the 6 months prior to each interview. Three items measured injection-related risk in terms of: (1) self-reported injection frequency; (2) use of ‘dirty works’ (needles, cooker, or cotton used by others and not cleaned with bleach); (3) times shared ‘dirty works’ with strangers (i.e. persons they did not know well). Response categories for these measures ranged from ‘0’ to ‘8’, where 0, never; 1, 1 –3 times; 2, 1 time/month; 3, 2 – 3 times/month; 4, 1 time/week; 5, 2–6 times/week; 6, 1 time/day; 7, 2–3 times/day; 8, 4 or more times/day. Four items measured sex-related risks in terms of: (1) number of sex partners, (2) the frequency of unprotected sex, and unprotected sex with (3) an IDU, and (4) while high on drugs. The latter three measures were scored using the ‘0’ to ‘8’ scale described above.

2.5. Data analyses Due to the skewed distributions for these data, ease of interpretation, and clear reporting considerations, measures were recoded such that (in most cases) any risk was scored as ‘1’ and the absence of risk was left at ‘0’. The exceptions included the injection frequency measure which was not recoded, and the number of sex partners measure, where a value of ‘0’ was assigned if there was only one or no sex partners and a value of ‘1’ to indicate multiple partners. Multi-way contingency tables (except injection frequency) for

treatment tenure and HIV risk at intake and at 12 month follow-up were analyzed using the repeated measurement option in SAS for performing categorical data modeling (PROC CATMOD; SAS Institute Inc., 1989). This uses the GSK weighted least-squares estimation procedure (Grizzle et al., 1969) to test the linear model that the independent variable (treatment tenure) predict the repeated-measures dependent variable (time)—that is, the same HIV risk measured at intake and at follow-up. The analysis allows each source of variance to be tested for significance, similar to analysis of variance procedures. However, the significance of each source of variation is evaluated in terms of a statistic distributed as x 2 rather than Fisher’s F-statistic. The GSK analysis is not possible when all of the sample falls into one category, as with injection frequency (everyone injected at intake), and thus repeated-measures analysis of variance (ANOVA) was applied for this measure. For the GSK and ANOVA procedures, three tenure groups were created based on empirical, statistical and logical considerations. Prior studies have shown that at least 3 months of treatment is needed to produce positive long-term outcomes, and for MM clients it may require up to a year (Hubbard et al., 1989; Simpson, 1981; Simpson and Sells, 1982; Simpson et al., in press,b). These tenure categories are therefore important to research from logical perspectives. Additionally, in this study, 1/3 of the sample stayed under 3 months and approximately another 1/3 left after 1 year, further justifying this breakdown. Specifically, the groups consisted of clients who stayed in treatment under 90 days (n=136), 90–360 days (n= 163), and the third group stayed over 360 days (n= 136). Overall comparisons across the three tenure groups showed that the groups were similar in terms of sociodemographic and drug use characteristics. Finally, in order to test the simultaneous effects of treatment tenure, gender, and cocaine use on risk behavior at follow-up while controlling for intake risk, and additional background variables, and treatment status (whether client is in treatment at the time of follow-up), a series of multiple logistic regression analyses were performed for each risk measure. Although methadone dose is an important variable that can influence treatment retention (see Simpson and Joe, 1993), it was not included in the present logistic regression analyses because dose level was low in the three programs, and it was neither significantly different for the three tenure groups, nor was it significantly related to HIV risk-taking behavior. Potential moderating effects of discharge status were also of concern, but because 73% of those discharged for noncompliance reasons stayed over 90 days, it was not an actual factor.

L.M. Camacho et al. / Drug and Alcohol Dependence 47 (1997) 11–18

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Table 2 Six month HIV risk behavior at intake and follow-up by treatment tenure (n = 435)

Injected (%)a Used dirty works (%) Shared w/strangers (%) Sex partners \1 (%) Unprotected sex (%) w/IDU While high

Time

B90 days

90 – 360 days

\360 days

Time×tenure

Intake

Follow-up

x2

I

FU

I

FU

I

FU

x2

100 61 19 33 87 43 76

72 23 4 25 79 30 39

100.6*** 150.8*** 42.5*** 10.4*** 8.4** 21.4*** 126.0***

100 62 19 36 85 46 73

78 26 7 29 81 32 43

100 58 16 36 91 41 80

74 28 4 31 81 32 49

100 65 21 26 82 42 74

63 13 2 13 75 25 25

3.8* 13.4*** 2.4 2.4 2.7 1.7 6.0*

These analyses statistically control for whether client is in treatment at follow-up. Based on ANOVA results for injection frequency; F is reported. * PB0.05, ** PB0.01, *** PB0.001. a

3. Results

3.1. Trend analyses ANOVA results showed that mean injection frequency dropped significantly from 7.3 (S.D. =1.0) at intake to 3.6 (S.D.= 3.1) at follow-up (F(1,431)= 100.6, PB0.001). The interaction between time and treatment tenure was also significant (F(2,431) = 3.8, PB 0.02), indicating that the largest decline in injection frequency was associated with the highest treatment tenure group (Table 2 portrays the interaction pattern in terms of percent injectors across groups). From the GSK repeated-measures analysis, other injection-related risk measures also showed significant reductions from intake to follow-up. Table 2 shows that users of ‘dirty works’ dropped from 61% at intake to 23% at follow-up (x 2(1,435) =150.8, P B 0.001), and sharing injection equipment with strangers changed from 19 to 4% (x 2(1,435)= 37.1, P B 0.001). Sex risk measures also were significantly lower at follow-up. For example, 33% had multiple sex partners at intake and 25% at followup, while unprotected sex declined from 87 to 79% (x 2(1,435)= 8.4, PB 0.01). Also shown in Table 2 are the interaction tests between time and treatment tenure. Interactions were significant for use of ‘dirty works’ (x 2(2,435) = 13.4, PB 0.001) and frequency of unprotected sex while high (x 2(2,435)= 6.0, P B0.05). Results for both these measures indicated that the rate of risk reduction change was greater the longer the client had been in treatment. For example, use of ‘dirty works’ for clients staying less than 90 days declined from 62% at intake to 26% at follow-up, while this risk for those staying over 360 days dropped from 65 to 13%. Although a similar pattern was observed for most of the other measures, they failed to reach significant levels. Interactions of time with gender and with cocaine use also were tested, but these were not significant.

In order to test whether the lowered levels of HIV risk-taking were due to a reduction in drug use or changes in injection practices, further analyses were performed based only on clients who had continued to inject drugs at follow-up (n= 313). Repeated-measures ANOVA results showed that frequency of injections dropped significantly from a mean of 7.3 (S.D.=0.9) at intake to 5.0 (S.D.= 2.4) at follow-up (F(1,312) = 268.7, PB 0.001). GSK repeated-measures analyses showed that use of ‘dirty works’ dropped from 62% at intake to 31% at follow-up (x 2(1,313)= 104.2, PB 0.001), and sharing with strangers went down from 19% at intake to 5% at follow-up (x 2(1,313)= 32.0, PB 0.001). The percentage of clients who had multiple sex partners changed from 33% at intake to 28% at followup, but was not significant (x 2(1,313)= 3.3, PB.07), and for unprotected sex the decline was from 87 to 81% (x 2(1,313)= 6.3, PB 0.01). Unprotected sex with an IDU dropped from 44% at intake to 38% at follow-up, but this change was not significant (x 2(1,313)=3.3, PB 0.07), and having unprotected sex while high was 75% at intake and 49% at follow-up (x 2(1,313)=47.5, PB 0.001). Thus, HIV risk reductions were evident beyond those accounted for by subjects who were not injecting at the time of follow-up.

3.2. Logistic regression analyses Table 3 shows results of the set of multiple logistic regression analyses for each HIV-risk measure tested using HIV risk at intake, gender, race-ethnicity (African-American, Caucasian, Hispanic), age, education (high-school graduate), any pretreatment cocaine use, treatment tenure (number of days), and treatment status at follow-up as predictors of risk behaviors 12 months after treatment discharge. Results generally showed that increased tenure was related to less HIV risk at follow-up, while pretreatment cocaine use was related to increased risk levels at follow-up. Specifically, longer treatment tenure was significantly related to

0.90 −0.72 −0.95 0.43 0.04 −0.15 −0.01 −0.51 1.71

8.7** 6.5** 3.2 1.8 0.1 0.3 5.6* 3.0 39.6***

x2 2.53 −0.91 −0.29 −0.18 0.48 −0.37 −0.00 −0.34 3.33

b 17.3*** 2.0 0.1 0.1 2.6 0.3 1.6 0.3 9.8**

x2

Times shared with strangers

1.30 −0.01 −0.35 −0.13 −0.03 −0.14 −0.01 −0.19 0.80

b 27.9*** 0.0 0.7 0.2 0.1 0.3 5.0* 0.5 10.8***

x2

No. of sex partners

Outcomes are for the last 6 months and each measure was scored ‘0’ versus ‘1 or more’. * PB0.05, ** PB0.01, *** PB0.001.

Risk at intake Male Black Hispanic Age HS graduate Tenure In treatment Cocaine Use

b

Dirty works

Table 3 Logistic regression analysis predicting HIV risk taking at follow-up (n =435)

1.96 0.38 0.15 0.16 −0.43 −0.23 −0.00 0.34 0.28

b 37.1*** 1.8 0.2 0.2 9.6** 0.6 3.5 1.3 1.0

x2

Unprotected sex

1.71 −0.46 −0.01 0.21 −0.01 −0.21 −0.01 −0.68 1.23

b

44.6*** 3.2 0.0 0.5 0.0 0.6 4.1* 6.2** 25.4***

x2

Unprotected sex with IDU

0.37 −0.12 0.11 0.01 −0.25 −0.02 −0.01 −0.45 1.02

b

2.0 0.3 0.1 0.0 5.4* 0.0 5.0* 3.6 23.1***

x2

Unprotected sex while high

16 L.M. Camacho et al. / Drug and Alcohol Dependence 47 (1997) 11–18

L.M. Camacho et al. / Drug and Alcohol Dependence 47 (1997) 11–18

lower use of ‘dirty works’ (b = −0.01, P B 0.05) and to lower sex risks in terms of multiple sex partners, unprotected sex with IDU, or sex while high (b = −0.01, P B 0.05 for all). With the exception of the unprotected sex measure, cocaine use was consistently associated with increased risk-taking behaviors (b = 0.80 – 3.3, PB 0.01). Gender differences were generally not evident; only on ‘dirty works’ were males less risky than females at follow-up (b= −0.72, P B 0.01).

4. Discussion The results from this study extend our previous findings on during-treatment HIV risk reductions. Specifically, risk behaviors measured by injection frequency, sharing and use of ‘dirty’ injection equipment, number of sex partners, frequency of unprotected sex, and incidences of unprotected sex with an IDU and while high, were significantly lower 12 months after leaving treatment than they were at the time of treatment entry. Thus, reductions in both HIV injection and sex risk behaviors observed during treatment (Camacho et al., 1996) were also evident 12 months after leaving treatment. Similar to prior findings (Camacho et al., 1996, Longshore et al., 1993), even IDUs who continued to inject at follow-up appeared to reduce their HIV risk— implying that risk reduction cannot be explained solely by reductions in drug use. Although this subgroup was still using, their overall reductions in risk levels may suggest that more deliberate health protection behaviors came into play as a result of exposure to the HIV prevention messages that are becoming a normal part of MM and other drug treatment programs (see Bartholomew and Simpson, 1994; Boatler et al., 1994). Clients in the present study had the opportunity to be exposed to a variety of HIV education and prevention approaches during treatment, including health education classes, having HIV issues raised in individual counseling sessions (part of a state requirement), pamphlets and displays in waiting areas, and the availability of on-site HIV testing and counseling services. Studies which focus on treatment process and how it relates to risk reduction are now needed (Simpson et al., 1995; Simpson et al., in press,a). The second purpose of the study was to assess the effects of treatment tenure, cocaine use, and gender on posttreatment HIV-risky behavior, factors which prior studies have shown to be consistently associated with HIV risk taking (e.g. Booth et al., 1995; Williams et al., 1992). Our results showed longer treatment tenure was associated with lower incidence of injection frequency, less ‘dirty works’, fewer sex partners, less unprotected sex with IDUs, and less sex while high. The results also showed that pretreatment cocaine use was positively

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associated with almost all risk-taking measures at follow-up, and women were more likely to use ‘dirty works’ than men. Overall, increased tenure was related to risk reductions at follow-up, while cocaine use was related to increased risks, and gender was generally unrelated to risk changes. These treatment tenure results are consistent with recent findings in the same treatment population which showed that longer retention was associated with better outcomes in terms of illicit drug use, alcohol use, and criminal involvement (Simpson et al., in press,c). One limitation of this study involves the lack of after treatment data for the noninterviewed sample, which was primarily composed of clients who were in prison at the time of follow-up. Concerns about the representativeness of the interviewed sample were addressed by comparing statistically the interviewed and noninterviewed samples on data collected at intake and reasons for termination from treatment; sampling bias was not evident. A second limitation is the lack of random assignment to the treatment duration categories in order to test more conclusively its effects. Another limitation is that HIV test results were not available; however, it should be noted that HIV incidence among IDUs in Texas is relatively low (compared to other states), thus limiting the feasibility of seroconversion studies. Finally, availability of interim measures, such as risk at discharge, would have allowed us to test if there was deterioration of positive outcomes over time, and more importantly, if a lower degree of deterioration was associated with longer tenure. Although this might be an interesting proposition for future research, this information is typically unavailable in outpatient programs in the drug treatment world. The present study adds support to the importance of offering methadone maintenance as part of treatment efforts for reducing HIV risks among IDUs (Ball et al., 1988; Metzger et al., 1993; Williams et al., 1992), and it underscores the need for more research on how consistently during-treatment changes in HIV risky behavior are maintained over time. Additionally, there is a need to continue exploring ways to encourage treatment compliance among MM clients—entering and staying with a treatment program appears to reduce risky practices. The finding that cocaine use increases the likelihood of HIV-risky behavior emphasizes the importance of finding effective treatments for IDUs who are addicted to both opiates and cocaine (Condelli et al., 1991; Kolar et al., 1990; Magura et al., 1991). Finally, the availability of targeted interventions for both women and men that strengthen the development of life skills, relationship and communication skills, self-esteem, and self-efficacy may help attract and keep clients in treatment (Amaro and Hardy-Fanta, 1995; Bartholomew et al., 1994; Reed, 1987). Further development and testing of new interventions for cocaine

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users as well as separate interventions for women and men in MM treatment appear warranted.

Acknowledgements This work was supported by the National Institute on Drug Abuse (Grant No. DA06162). The interpretations and conclusions, however, do not necessarily represent the position of NIDA or the Department of Health and Human Services.

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