Predictors of Positive Outcomes for Out-of-Treatment Opiate Injectors Recruited into Methadone Maintenance through Street Outreach

• Author: Karen Fortuin Corsi,Robert E. Booth,Carol F. Kwiatkowski
• Published date: 01 July 2002
• Date: 01 July 2002
• DOI: 10.1177/002204260203200316
• Subject Matter: Article

© 2002 BY THE JOURNAL OF DRUG ISSUES

JOURNAL OF DRUG ISSUES 0022-0426/02/03 999-1016

__________

Karen Fortuin Corsi, MPH is an Instructor at the University of Colorado Health Sciences Center,

Department of Psychiatry in the Division of Substance Dependence. She has been the Project Manager

for Project Safe since 1998. She is currently completing her doctorate at the Johns Hopkins University

Bloomberg School of Public Health. At the time of the preparation of the manuscript, Carol F.

Kwiatkowski, Ph.D. was an Assistant Professor at the University of Colorado Health Sciences Center,

Department of Psychiatry in the Division of Substance Dependence. She has authored numerous

papers on HIV prevention and intervention. Robert E. Booth, Ph.D. is a Professor of Psychiatry at the

University of Colorado Health Sciences Center. He has been conducting HIV-related research for 15

years and his work has appeared in numerous publications. He currently serves on the Office of AIDS

Research Advisory Council. Address correspondence to: Karen Fortuin Corsi, Project Safe, 1741 Vine

St., Denver, CO 80206; email: karen.fortuin@uchsc.edu

PREDICTORS OF POSITIVE OUTCOMES FOR OUT-OF-

TREATMENT OPIATE INJECTORS RECRUITED INTO

METHADONE MAINTENANCE THROUGH STREET

OUTREACH

KAREN FORTUIN CORSI, CAROL F. KWIATKOWSKI, ROBERT E. BOOTH

This study was conducted to assess behavior change in the areas of drug use,

productivity, criminal activity, and HIV risk among street-recruited injection drug

users who entered methadone maintenance treatment. In addition, the study

examined a number of variables that could account for these changes, including

demographics, intervention effects, and treatment-related measures. A total of 168

participants were interviewed at baseline, received outreach interventions, entered

methadone maintenance treatment, and were reinterviewed 5-9 months later.

Significant (p<.001 improvements were seen in the areas of drug use productivity>

criminality, and HIV risk behaviors. The only variables significantly associated with

behavior change were related to drug treatment. In particular, being in treatment at

the time of the follow-up assessment had the strongest relationship to positive

outcomes, including length of treatment. Having no prior treatment experience was

associated with fewer injections at follow-up. These findings emphasize the

importance of retaining clients, given the likelihood that positive change is likely to

be evidenced while they remain in treatment.

CORSI, KWIATKOWSKI, BOOTH

1000 JOURNAL OF DRUG ISSUES

INTRODUCTION

Drug use in general, and opiate addiction in particular, are significant problems

in the United States. In 2000, the Substance Abuse Mental Health Services

Administration (SAMHSA) reported that 14 million Americans were current illicit

drug users, representing approximately 6.3% of the population 12 years of age and

older. This figure includes 130,000 heroin users (SAMHSA, 2001). Since methadone

maintenance treatment was first tested on opiate-addicted IDUs by Dole and

Nyswander (1965) in the 1960s, its role as an effective therapeutic modality for

opiate addiction treatment has been repeatedly studied (Dole, Nyswander, & Warner,

1968; Ball & Ross, 1991; Ward, Hall, & Mattlick, 1999; Glass, 1993). Aspects of

methadone maintenance that have been examined include dose, length of time in

treatment and the number of treatment episodes. Studies have shown that a higher

methadone dose predicts better outcomes and retention in treatment (Rhoades,

Creson, Elk, Schmitz, & Grabowski, 1998; D’Ippoliti, Davoli, Perucci, & Pasqualini,

1998; Strain, Stitzer, Liebson, & Bigelow, 1993). Length of time in treatment has

been studied to determine what treatment duration predicts optimal outcomes for

drug users. Simpson (1981) and others have shown that greater time in treatment

(90 days or more) predicts better outcomes (Ball, Lange, Myers, & Friedman, 1988;

McLellan, Luborsky, & O’Brien, 1986; Gottheil, Sterling, & Weinstein, 1993; Sees

et al., 2000). It has also been found that prior treatment experience can have a

negative effect on treatment outcome and retention (McLellan et al., 1986),

indicating that first-time treatment clients have a higher success rate than repeat

clients. Further research is needed to clarify what factors may account for behavior

change among drug users in treatment.

Although not all IDUs who enter methadone treatment programs quit drug use

altogether, they are likely to reduce their drug use (Sorenson & Copeland, 2000;

Metzger, Navaline, & Woody, 1998; Booth, Crowley, & Zhang, 1996; Simpson,

1981; McLellan et al., 1986), as well as improve other areas of their lives, including

health, employment, personal relationships, and criminal behavior (Kidorf,

Hollander, King, & Brooner, 1998; Farrell et al., 1994; Murray, 1998; Ball, Corty,

Bond, Myers, & Tommasello, 1981; Rounsaville, Kosten, & Kleber, 1987; Strain,

Stizer, & Bigelow, 1991; Weiss, Griffin, & Mirin, 1989). By reducing drug use,

drug users also reduce their risk of contracting blood-borne diseases, including

HIV and hepatitis (Sorenson & Copeland, 2000; Metzger et al., 1998; Longshore,

Hsieh, Danila, & Anglin, 1993; Ball et al., 1988; Comacho, Bartholomew, &

Simpson, 1997). Getting opiate-addicted clients engaged in methadone programs

and retaining them is an important means of decreasing the spread of HIV and

other diseases, as well as reducing costs to society. Research has shown that

incentives, such as decreasing delays at intake and reduced or no-cost treatment

PREDICTORS OF POSITIVE OUTCOMES FOR OPIATE INJECTORS

1001SUMMER 2002

fees, can dramatically increase retention (Woody, O’Hare, Mintz, & O’Brien, 1975;

Dennis, Ingram, Burks, & Rachal, 1994; Maddux, Prihoda, & Desmond, 1994;

Kwiatkowski, Booth, & Lloyd, 2000).

HIV infection persists as a significant public health threat, in particular within

populations that engage in high-risk behaviors, including needle sharing and

unprotected sex. Moreover, injection drug use ranks as the second highest risk

factor for contracting HIV, after homosexual contact among males (Centers for

Disease Control and Prevention, 2000). Despite the success of prevention projects

that raise awareness through outreach and intervention to drug users (Booth &

Weibel, 1992; Watters, 1996), some marginalized groups continue to engage in

risky injection and sex practices. In the United States, through June 2000, injection

drug users (IDUs) accounted for 25% of all adult/adolescent AIDS cases. An

additional 6% of AIDS cases were found among men who had sex with men and

also injected drugs, and more than half of pediatric AIDS cases (57%) occurred

among mothers using drugs or having an IDU sex partner (Centers for Disease

Control and Prevention, 2000). Sharing drug injection paraphernalia, such as needles,

cotton, cooker, and rinse water, has been found to be a significant factor in the

transmission of HIV (Chitwood et al., 1995). IDUs who share paraphernalia are not

only at risk of contracting HIV, but also hepatitis, a debilitating liver disease that is

reaching epidemic proportions in this population due to its virulence and ease of

spread (Hagan et al., 2001). Since the HIV epidemic began, researchers and public

health authorities have called for prevention strategies targeting the IDU population

that include increasing safe injection practices and stopping or reducing injection

drug use (Schuster, 1988). Research has shown that methadone maintenance

treatment for opiate-addicted IDUs is effective in decreasing risks for contracting

HIV and in improving both quality of life and health (Sorenson & Copeland, 2000;

Metzger et al., 1993). Further, both researchers and treatment providers have

recommended methadone maintenance as a modality that reduces needle sharing

and other risk behaviors, in addition to promoting drug use cessation (Brickner et

al., 1989; Sorenson & Copeland, 2000).

In the current study, we hypothesized that out-of-treatment IDUs who were

induced to enter methadone maintenance treatment through a variety of incentives

would show improved behaviors in the areas of drug use, productivity, criminal

activity, and HIV risk behaviors. Several factors that might account for these

improvements were assessed in multiple analyses, including background

characteristics of users and treatment-related variables. By testing some of these

factors, treatment centers may be able to better tailor their programs to foster greater

success for clients who are less likely to benefit from treatment.

CORSI, KWIATKOWSKI, BOOTH

1002 JOURNAL OF DRUG ISSUES

METHODS

RECRUITMENT

Subjects included in the present study were part of a larger investigation designed

to test the effectiveness of outreach interventions, as well as free treatment, in

increasing treatment entry and retention among out-of-treatment IDUs. Participants

were recruited through street outreach in Denver, Colorado from 1996-2000 using

targeted sampling methods (Watters & Biernacki, 1989). Indicators of drug use

(e.g., drug-related arrests, treatment admissions, HIV/AIDS cases among IDUs)

were used to estimate the number of drug users residing within census tracts in the

city and surrounding areas. Recruitment quotas were developed for each census

tract representing the estimated distribution of drug users within each area. Outreach

workers familiar with the drug-using community recruited subjects, conducted an

initial street eligibility assessment, and scheduled and transported clients to

interviews. Outreach workers also conducted behavioral interventions, as described

below.

Eligibility criteria included: 1) injection drug use in the 30 days prior to the

baseline interview; 2) at least 18 years of age; and 3) not enrolled in substance

abuse treatment in the 30 days prior to the baseline interview. Eligibility was verified

through urinalysis and visual inspection for signs of recent venipuncture. Those

testing negative for opiates, cocaine and methamphetamines were not eligible to

participate in the study. Subjects were also ineligible if they were in treatment at

the time of eligibility screening, as verified by a methadone urinalysis test.

Participants had to be competent to provide informed consent. Eligible subjects

were compensated $20 and $25 for their baseline and follow-up interviews,

respectively, for their time as research participants. The current research focuses

on those participants who chose to enter treatment between baseline and the 6-

month follow-up. Study procedures were approved by the Institutional Review Board

of the University of Colorado Health Sciences Center and affiliated institutions.

PROCEDURES

Interviews were conducted by trained interviewers using a modified version of

the Risk Behavior Assessment (RBA). The RBA is a structured interview developed

by a grantee consortium of the National Institute on Drug Abuse (1991). It assesses

demographics, drug use, sexual behaviors, medical histories, and HIV risk behaviors.

Reliability and validity studies of the RBA support its adequacy as a research tool

with this population (Weatherby et al., 1994; Needle et al., 1995).

All participants were offered free HIV testing and counseling and were randomly

assigned to receive either a Risk Reduction (RR) or a Motivational Interviewing

PREDICTORS OF POSITIVE OUTCOMES FOR OPIATE INJECTORS

1003SUMMER 2002

(MI) intervention. The RR intervention focused on reducing the participant’s risk

for HIV and included assessing individual risk behaviors, offering viable alternatives

to high-risk behaviors, and reinforcing risk reduction efforts (Weibel, 1993). The

MI intervention focused on more sweeping lifestyle changes, particularly by

encouraging individuals to enter drug treatment (Miller & Rollnick, 1991).

Techniques such as providing feedback on drug use, discussing the perceived pros

and cons of drug use, and encouraging drug use cessation and/or treatment entry

were used to promote behavior change. Prevention materials, including bleach kits

and condoms, were also made available to participants. In addition, half of the

sample was randomly assigned to receive a coupon for 90 days of free substance

abuse treatment. In order to receive free treatment, subjects had to enter treatment

at the clinic associated with the University of Colorado Health Sciences Center

(Addiction Research and Treatment Services) within 2 months of their baseline

interview. The clinic provides outpatient drug-free treatment, methadone

maintenance, and methadone detox. Subjects who wished to enter treatment,

regardless of their intervention assignment or whether or not they received a coupon,

were assisted by outreach staff: they scheduled the intake appointment, provided

rapid intake (i.e., within 24-72 hours), transported the client to the clinic, and waived

the intake fee ($40). Transportation to subsequent appointments for all study

participants in treatment was provided via bus tokens. For the present study, only

participants who entered methadone maintenance treatment were included in the

analyses.

ANALYSIS

Seven outcome variables were assessed at baseline and again 5-9 months later

at the follow-up interview. They included two drug use variables (morphine

urinalysis results and self-reported frequency of heroin injections in the prior month),

two indicators of productivity (employment and legal income earned), one measure

of criminal behavior (illegal income) and two indicators of HIV risk behaviors

(using needles that had been previously used without bleaching [dirty needles], and

sharing other drug paraphernalia [cookers, cotton filters or rinse water]).

Variables tested for their association with each of the outcomes included

demographics (gender, ethnicity, age), treatment variables (whether they had ever

been in drug treatment before, days in treatment in the 6 months prior to the follow

up interview, in treatment in the 30 days before the follow-up interview, number of

treatment counselor contacts, maximum methadone dose), and three intervention

variables (type of intervention, number of intervention contacts, free treatment).

In addition, in multiple variable models, baseline levels of the respective outcome

variables were controlled for in each model. All data were self-reported except

CORSI, KWIATKOWSKI, BOOTH

1004 JOURNAL OF DRUG ISSUES

urinalysis results and the treatment variables, which were verified through the

treatment agency. Univariate tests were run using chi-square, correlations, and

one-way ANOVA. Significant variables (p<.10 were included in statistical models>

using multiple logistic regression and ANCOVA.

RESULTS

A total of 586 subjects were enrolled in the larger study. Of these, 218 (37%)

entered methadone maintenance drug treatment, constituting the basis for the present

study. We were able to obtain follow-up interviews approximately 5-9 months

after the baseline interview on 180 (83%) of this sample. Baseline and treatment

differences were minimal between those who were followed and those not followed,

as described below. Twelve subjects from this pool were dropped from further

analyses because they had been in jail for more than 15 days in the month prior to

their follow-up interview (the time period queried for most outcome variables).

The decision to eliminate these subjects was based on comparison analyses that

indicated that participants who were in jail for more than 15 of the prior 30 days at

follow-up were substantially different on the outcome variables than the rest of the

sample (e.g., none were employed). Attrition analyses were run to compare the

remaining 168 subjects with the 38 subjects who received a baseline interview and

entered treatment, but who did not return for their follow-up interview. Those who

were not reinterviewed differed from those who were on only one variable: their

maximum methadone dose was lower, on average, than those who were successfully

followed (58 mg vs. 71 mg; F(1,181)=5.7, p<.05 none of the other variables>

(including demographics, background variables, treatment and intervention related

variables) demonstrated statistically significant differences.

Descriptive variables for the 168 study participants who were interviewed at

follow-up are shown in Table 1. The sample was primarily male, White or Hispanic,

and averaged 39 years old. They injected drugs nearly 3 times a day on average and

had been injecting for over 18 years. A little over two thirds had been in drug

treatment previously, including methadone maintenance, outpatient, and residential

treatment.

Following the baseline interview, subjects were randomly assigned to an

intervention condition; 49.4% were assigned to the more intensive, treatment-

focused MI group. A total of 61.9% had received coupons for free treatment (random

assignment in the larger study was 50%, however, a larger percentage of those who

received free treatment coupons are represented in this subset of those who entered

treatment). Project interventionists conducted an average of 3.5 intervention sessions

with each participant between their baseline and follow-up interviews (sd=2.0).

While in treatment, participants also received an average of 1.2 counseling sessions

PREDICTORS OF POSITIVE OUTCOMES FOR OPIATE INJECTORS

1005SUMMER 2002

per month from the treatment clinic (sd=0.6). The average treatment stay was 100.4

days (sd=58.1), and 38.7% were still in drug treatment during the month prior to

their follow-up interview. The average maximum methadone dose while in treatment

was 71.0 mg (sd=28.7).

Pre/post change figures on the seven outcome variables are shown on Table 2.

At baseline, all but one participant had a positive morphine urinalysis result, and

the average number of heroin injections in the prior month for the sample was 70.

About one third reported being employed, and, overall, subjects reported making

nearly $800 a month in legal income. Nearly 60% also reported making illegal

income in the prior month. Approximately one third of participants reported using

a dirty needle, and over two thirds shared other drug paraphernalia. Changes from

baseline to follow-up on these outcome variables were substantial and significant

for all variables except legal income. That is, the percentage of positive morphine

tests declined, monthly heroin injections decreased, the percentage of participants

who were employed increased, the percentage who acquired illegal income

decreased, and the percentage engaging in HIV risk behaviors decreased.

In order to determine what accounted for the positive changes seen at follow-

up, models were developed for each of the six outcome variables demonstrating

significant change from baseline to follow-up. The first step in building the models

was to test the independent variables (demographics, treatment and intervention

TABLE 1

BASELINE DESCRIPTIVE VARIABLES FOR 168 PARTICIPANTS

CORSI, KWIATKOWSKI, BOOTH

1006 JOURNAL OF DRUG ISSUES

variables) in univariate analyses (chi-square, one-way ANOVA, and correlations).

Independent variables that were significant in univariate tests at p<.10 were entered>

into logistic regression models and ANCOVA in order to determine the most

significant variables contributing to each of the outcomes. For the dichotomous

outcome variables, baseline levels of the outcome variables were controlled for in

logistic regression models (note that these are reported in the text but omitted from

the table for clarity). Percentages, odds ratios (OR) and 95% confidence intervals

(CI) are reported for significant independent variables in the logistic regression

models. For the one continuous outcome variable, ANCOVA was run on the

difference between the number of heroin injections at baseline and the number at

follow-up. Results, shown in Table 3, are presented in terms of positive outcomes:

reduced drug use, increased productivity, decreased criminal behavior, and decreased

HIV risk behaviors.

DRUG USE

With regards to having a negative morphine urinalysis result at the follow-up

interview, variables that were significant in the univariate tests included being in

treatment in the month prior to the follow-up interview and receiving the RR

intervention. When these variables were entered simultaneously into a logistic

regression model, only the treatment variable was significant. Those who had a

negative UA result, 59.6% were in treatment in the prior month, compared to 30.5%

of those who had a positive result (OR=3.2).

The decrease, between baseline and follow-up, in the number of times that

participants injected heroin was associated with not having ever previously been in

TABLE 2

CHANGES IN OUTCOME VARIABLES BETWEEN BASELINE AND FOLLOW-UP INTERVIEWS

PREDICTORS OF POSITIVE OUTCOMES FOR OPIATE INJECTORS

1007SUMMER 2002

treatment, longer retention (in days) in treatment, having more contact with the

treatment counselor, having a higher maximum methadone dose and being in

treatment during the month prior to the follow-up interview. The two variables that

were significant in the final model were not having ever been in treatment before

and greater treatment retention. That is, those who had not ever been in treatment

prior to enrolling in this study showed greater reductions in heroin injections (60.4

times fewer at follow-up) than those who had been in treatment before (33.3 times

fewer at follow-up), F(1,144)=4.9, p<.05 and the more days spent in treatment>

greater the decrease in heroin injections, F(1,144)=10.5, p<.001.>

PRODUCTIVITY

Five variables, including baseline employment, were significantly associated

with being employed at the follow-up interview. Men were more likely to be

employed at follow-up, as were participants who received the RR intervention and

those who were in treatment in the month prior to the follow-up interview. Those

who were employed at follow-up also received fewer counseling contacts while in

TABLE 3

MULTIVARIATE MODELS OF ASSOCIATIONS WITH POSITIVE OUTCOMES

CORSI, KWIATKOWSKI, BOOTH

1008 JOURNAL OF DRUG ISSUES

treatment. When these variables were entered into a logistic regression, baseline

employment and counseling contacts were significant, and being in treatment in

the month prior to follow-up was marginally significant (p=.058). Findings showed

that 33.6% of those who were not employed at baseline were employed at follow-

up, compared to 69.1% of those who were employed at baseline and were also

employed at follow-up (OR=4.2). Those who were employed at follow-up received

an average of 1.1 counseling contacts while they were in treatment, while those

who were not employed received an average of 1.3 contacts (OR=2.3). Fifty-two

percent of those who were in treatment in the month prior to follow-up were

employed, compared to only 41% of those who were not in treatment (OR=2.0).

CRIMINAL BEHAVIOR

Reporting no illegal income in the month prior to the follow-up interview was

significantly related to three variables in univariate tests: no illegal income at

baseline, being in treatment during the month prior to follow-up and not having

previously been in treatment. When these variables were entered simultaneously

into the logistic regression model, only the former two remained significant

predictors. As would be expected, those reporting no illegal income at baseline

were more likely to report no illegal income at follow-up (95.7%) than those who

reported illegal income at baseline but not at follow-up (57.1%; OR=15.7). In

addition, participants who were in treatment in the month prior to their follow-up

interview were more likely not to report illegal income (84.6%) than those who

were not in treatment (66.0%; OR=2.7).

HIV RISK BEHAVIORS

In univariate tests, the only variable significantly associated with not using dirty

needles at follow-up was not using dirty needles at baseline. Those who did not use

dirty needles at baseline were less likely to use them at follow-up (98.1%) compared

to those who did use dirty needles at baseline (71.7%; OR= 20.9).

With regards to reduced sharing of drug paraphernalia, not sharing at follow-up

was associated with not sharing at baseline, more days in treatment, being in

treatment in the month prior to follow-up and having fewer intervention contacts.

Two separate logistic regression models were developed to assess and compare the

separate contributions of the highly correlated variables of being in treatment and

having more days in treatment. Sharing paraphernalia at baseline was significant in

both models (those who did not share at baseline were less likely to share at follow-

up [79.6%] than those who did share at baseline [55.5%; OR=1.1] in both models).

The number of intervention contacts was not significant in either model. Because

both models were equally strong, logistic regression results are presented for each.

PREDICTORS OF POSITIVE OUTCOMES FOR OPIATE INJECTORS

1009SUMMER 2002

Those who did not share paraphernalia at follow-up spent more days in treatment

(110.3 days) than those who did share (83.9; OR=1.0) and those who were in

treatment during the month prior to follow-up were more likely not to share

paraphernalia (80.0%) compared to those who were not in treatment at follow-up

(51.5%; OR=3.7).

DISCUSSION

This study was conducted with 168 opiate-addicted IDUs located for a follow-

up interview 5-9 months after receiving an initial assessment interview, HIV testing

and counseling and HIV prevention interventions. All research subjects also entered

methadone maintenance treatment during the time between baseline and follow

up. The results of this investigation showed significant improvements in this

population of drug injectors between baseline and follow-up on several important

social and behavioral measures. This included reduced drug use, increased

productivity (as measured by employment), decreased criminal behavior (as

measured by illegal income), and decreased HIV risk behaviors (as measured by

dirty needle use and sharing of drug paraphernalia). Two treatment-related variables

(time in treatment and being in treatment at the time of the follow-up assessment)

were strongly associated with positive outcomes.

One of the most consistent predictors of positive outcomes was being in treatment

in the month prior to follow up, which nearly tripled the likelihood that subjects

would have a negative morphine urinalysis, be employed, not make illegal income

and not share drug paraphernalia. While many studies have reported that greater

treatment retention predicts more positive outcomes, few studies have directly

compared retention in treatment to being in treatment at the time of the outcome

assessment. This study found that being in treatment during the 30 days prior to

follow-up was more strongly associated with positive behavior change than the

amount of time spent in treatment. This is an area of research that deserves more

attention, particularly since our research also found that time spent in treatment

was predictive of two positive outcomes: reporting fewer injections, and not sharing

drug paraphernalia. These outcomes are particularly important for HIV prevention,

suggesting that spending some time in treatment, although the duration is uncertain,

is effective in reducing HIV risk behaviors, as well as being in treatment at follow-

up.

Another variable that was associated with reduced injections was having no

prior treatment experience. In the present study, participants who had never been

in treatment reported significantly fewer injections at follow-up than those who

had previously been in drug treatment. Claus and colleagues (1999) found that

previous treatment clients were more likely to have more severe substance abuse

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1010 JOURNAL OF DRUG ISSUES

problems, co-morbid psychiatric problems, and greater problems in other life areas

than those with no prior treatment experience. This indicates that treatment programs

may need to use different approaches for clients who have been in treatment

previously, since they may be less likely to change their problem behavior. It also

suggests that strategies to entice treatment-naive IDUs into drug treatment may be

worthwhile, as such individuals typically have more positive outcomes. One such

strategy for recruiting injectors into drug treatment is the provision of free treatment.

In previous studies we reported that offering free treatment leads to better treatment

entry rates and longer retention in treatment (Booth et al., 1998a; Kwiatkowski et

al., 2000), and that for first-time treatment clients, free treatment is a particularly

strong motivator (Kwiatkowski et al., 2000). Although in the present study offering

free treatment did not have a direct effect on behavior change, the effectiveness of

free treatment for recruiting treatment-naive clients, combined with the finding

that such clients are likely to have more positive outcomes, suggests that this could

be an important strategy for intervening in the lives of drug users.

Prior research has demonstrated that methadone treatment is effective in

improving many life outcomes for drug users (Sorenson & Copeland, 2000).

However, most studies have been conducted with drug users already in treatment

and otherwise motivated or required to be there, such as self-referred or court-

ordered clients. This study, on the other hand, recruited IDUs who were not seeking

treatment at the time that they entered the study. Data reported elsewhere from this

same population of out-of-treatment drug users demonstrated that they had more

severe substance use issues than drug users recruited in more traditional ways, (i.e.

through treatment centers). Their increased chronic drug use was demonstrated in

that they injected more drugs, injected more frequently and were more likely to

have used dirty needles in the thirty days prior to admission than traditional treatment

clients. Furthermore, they had more social and productivity problems, in that they

were more likely to be homeless, unemployed and recipients of public assistance

than those who entered treatment through other referral sources (Kwiatkowski &

Booth, 2001). The present study demonstrates that street-recruited out-of-treatment

drug users, induced to enter treatment through a variety of incentives, can

significantly change their behaviors.

The following limitations should be considered when drawing conclusions from

this study. The recruitment of this population of opiate injectors used a targeted

sampling plan, an approach that is less rigorous than a random sample. However, it

is more feasible than random sampling, more experimentally rigorous than a

convenience sample, and has been shown to be an appropriate method for recruiting

hidden or hard-to-reach populations (Watters & Biernacki, 1989). Another limitation

is that all risk-related behaviors and background information collected were based

PREDICTORS OF POSITIVE OUTCOMES FOR OPIATE INJECTORS

1011SUMMER 2002

on self-report, which is subject to social desirability and inaccurate memory. Since

respondents were asked to comment on a relatively short period of time (in the last

30 days) recall problems may have been minimized. Furthermore, drug use was

confirmed by urinalysis and all treatment information was obtained and verified

from the treatment provider. Additionally, prior research has shown that self-report

generates sufficiently valid data for this type of research (Magura et al., 1987;

Booth et al., 1996).

Loss to follow-up and sample attrition is an issue with this typically transient

population. We were unable to follow 17% of the respondents for whom we had

baseline data. There were no baseline differences between those who were followed

and those who were not, and the only treatment difference that was significant was

in dosing, as described in the results section. Nonetheless, this limits the

generalizability of the findings to a population of opiate IDUs that can be successfully

located, in that those who were available for follow-up interviews may represent a

different cross-section of the population than those who were not available. Follow-

up eligibility was not an issue since all subjects who were able to be located were

eligible for a follow-up interview.

The relatively brief period from baseline to follow-up (6 months) should also be

considered in the interpretation of this research. Although this “at risk” period is

common in these types of investigations (Booth et al., 1998b), lengthier follow-up

periods may produce differing results. Another limitation is in the study design,

with only a single group lacking a comparison. However, the project was designed

to facilitate treatment entry and retention among out-of-treatment IDUs. Additional

efforts are currently underway comparing differences in those who entered vs. not

entered treatment for their substance abuse problem.

This study supports previous research on the effectiveness of methadone

maintenance treatment in contributing to decreased drug use and HIV risk behaviors

and improved life and social behaviors. In particular, the study isolated several

treatment-related factors that contributed to these positive changes. Being in

treatment at follow-up suggests that continued contact with the treatment agency

affects positive behavior change and decreases risk factors for blood-borne diseases,

underscoring the need to continue to facilitate treatment entry to affect myriad

improved outcomes. Treatment centers can find support from these findings to

design programs that induce treatment-naive IDUs to enter treatment and to remain

as long as possible. Keeping clients in treatment is critical, given the positive

outcomes, including decreased HIV risk behaviors.

CORSI, KWIATKOWSKI, BOOTH

1012 JOURNAL OF DRUG ISSUES

ACKNOWLEDGMENTS

The authors would like to thank the two anonymous reviewers whose comments

were extremely helpful in preparing the final draft of this article. The authors also

thank Karyn Smith for her editorial assistance. Support for this research was provided

by the National Institute on Drug Abuse grant DA09832.

REFERENCES

Ball, J., Corty E., Bond, H., Myers, C., & Tommasello, A.

1981 The reduction of intravenous heroin use, non-opiate abuse and crime during

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