British Journal of Addiction (1992) 87, 251-258
Changes in criminal activity after entering methadone maintenance JAMES BELL,i WAYNE HALL^ & KAREN BYTH^ ' Drug and Alcohol Unit, and ^ Department of Medicine, Westmead Hospital, Westmead, NSW 2145, and ^ National Drug and Alcohol Research Centre, University of New South Wales, PO Box 1, Kensington, NSW 2033, Australia
Abstract The impact of different approaches to methadone maintenance on the level of crime committed by heroin addicts was examined in a cohort of addicts entering methadone treatment. The cohort comprises three groups: 72 subjects (group 1) who were approved for treatment and referred to a long-term programme which tolerated continued illicit drug use in treatment; 159 subjects (group 2) who were referred to an abstinence orientated programme from which clients who continued to use heroin were expelled; and 84 subjects who were rejected as unsuitable or failed to complete the assessment process. Official records of convictions were used to calculate conviction rates in thepre- and post-assessment periods. Differences between groups in conviction rates for drug and property crimes were analysed using Poisson regression. Three variables—age, sex and age of first criminal conviction—were significant predictors of conviction rates and all analyses controlled for these variables. Most of the rejected subjects entered treatment during the study period and it was, therefore, not possible to interpret differences between treated and untreated subjects. Among those who entered treatment, property offence rates actually rose, due to a significant increase in conviction rates in group 2. Subjects in group 1 were retained significantly longer in treatment than those in group 2. Among those who remained in treatment less than 12 months, most offences occurred after leaving treatment. When conviction rates were adjusted for time spent in treatment, the differences between the clinics disappeared. Remaining in treatment in either clinic was associated with a progressive reduction in the rate of convictions; for each year of treatment, the adjusted rate of property offences fell by a factor of 0.69 [95% CI (0.62, 0.78)]. Retention in treatment, rather than entry to treatment, is the key to reducing the criminal involvement of addicts. Programmes with low retention are less effective in achieving this goal. To be most effective, methadone programmes should be orientated towards encouraging clients to remain in treatment.
offenders reported that they were regular or occa-
The close association between heroin use and crime has been documented in many developed countries.''^ Recent Australian studies have found that 40% of a sample of incarcerated male property
sional users of heroin,' and 90% of addicts seeking entry to methadone programmes had convictions for property offences.^ The link has become an accepted popular wisdom; newspaper reports in Australia have attributed most property crime to addicts seeking to fund their drug use.'-*
Correspondence: Dr James Bell, Drug and Alcohol Services, The Prince of Wales Hospital, Cnr High and Avoca St, Rand;.ick,
NSW 2031, Australia.
T L L J I_ LI' ^^ ^as been argued that public Support
methadone programmes has been largely based on 251
J. Bell et al.
the perception that treatment will reduce However, while drug users have reported that during non-addiction periods their involvement in crime falls dramatically,*'' evidence for similar improvement during treatment for addiction has been less consistent. Studies on clients entering methadone programmes have found variable changes in criminal activity. American studies using self-report have usually found marked reductions in criminal activity. "••" One British study using self-report found modest reductions.'^ Studies using official records have been more variable, finding similar marked improvements," modest benefits,''*''^ or in some cases no reduction in arrests among subjects prescribed maintenance opioids." A recent Australian study found that placing addict/criminals on methadone prior to release from prison did not result in any demonstrable reduction in their rate of reoffending and reincarceration." These divergent findings may in part reflect the methodological difficulty of measuring an addict's level of criminal involvement. Another factor which may contribute to seemingly conflicting research findings is that methadone programmes differ considerably in their effectiveness.'" Studies have documented differences between programmes in their effectiveness in retaining people in treatment'* and in reducing illicit drug u s , " and it has been suggested that differences in treatment philosophy, policies and resources mean that some programmes will be more effective than others in reducing the criminal involvement of addicts.^" We had the opportunity of studying the impact of two clinics with markedly differing treatment policies when in 1986 a regional assessment centre was established at Westmead Hospital to process all requests for methadone maintenance. Applicants were assessed using standard criteria, and those approved were referred to the clinic nearest to where they lived. Two of the clinics in the region had markedly different treatment policies. In a previous study ,^' it was found that there were marked differences in retention in treatment between two of the clinics to which patients were referred. We have, therefore, studied the impact on crime of these two programmes to ascertain whether their different policies were associated with different outcomes. We have further compared changes in criminal activity in these two groups of treated patients with changes in the group of addicts who underwent assessment, but were not referred for treatment.
Subjects and methods Subjects were 315 addicts who applied to enter methadone treatment between March 1986 and June 1987, and were assessed at Westmead Hospital Drug and Alcohol Unit. This cohort represents all 72 applicants who in that period were approved and referred to clinic 1, all 159 approved applicants referred to clinic 2, and 84 subjects who either failed to complete assessment (n = 26) or were rejected as unsuitable (n = 58) on the grounds of not having a sufficiently severe problem. Approved subjects were referred to the clinic nearest to which they lived. The two clinics were comparable in size, funding and staffing levels, and were located in adjacent areas of similar, low socioeconomic status. Staff of the assessment unit and the two maintenance clinics met regularly to discuss treatment issues. Clinic 1 was characterized by higher doses, indefinite duration of treatment, and tolerance of continued illicit drug use; the explicit rationale for these policies was that treatment provided some stability for clients who often led chaotic lives. Clinic 2 prescribed lower doses, limited treatment to a maximum of two years, and mandatorily withdrew clients whose urine testing revealed continued use of heroin; the rationale for these policies was to promote rehabilitation through a drug-free lifestyle. From the assessment interviews, there was detailed information available on social and personal history, on history of drug use and treatment, and on criminal convictions. Supplementing this self-report information, for purposes of this study we were allowed access to Police Department records of arrests and convictions up to January 1989, and Health Department records of treatment up to the same time. The study was approved by the hospital Ethics Committee, and careful precautions were taken to preserve the confidentiality of the data collected. For purposes of this study, official records of convictions were used. Convictions were classified in six categories; drug offences (including trafficking), property offences (which includes all acquisitive crime except drug dealing and prostitution, mainly breaking, entering and stealing, theft, fraud, false pretenses), offences against people, traffic offences, technical offences (such as 'failure to appear', 'breach of parole') and soliciting. As a measure of each individuals 'criminality' we calculated his/her rate of convictions for each category of offence. Pre-assessment rates were calculated by dividing the number of convictions in
Criminal activity in methadone
Table 1. Relative risk of pre-assessment convictions by age at assessment Age
Drug offence rates
Property offence rates
0.41 [0.39, 0.44]
0.45 [0.43, 0.46]
each category of offence by the number of years between the first recorded criminal conviction and the age at assessment. Post-assessment crime rates were calculated from assessment to January 1989. The impact of treatment was assessed using Poisson regression, with the statistical analysis package GLIM 3.77. This approach compares each individuals pre- and post-assessment crime rates. Variables examined as potential predictors of change in crime rates were age, sex, educational attainment, age of first drug use, age of first conviction, employment, duration of addiction, crimes rates pre-assessment, entry or non-entry to methadone treatment; and for those who entered treatment, clinic, maximum methadone dose administered, and duration of treatment were also analysed. Results are reported as relative risks.
Results Seventy-two per cent of subjects were males. The mean age was 26.4 years. Only 11% of applicants had been full-time employed for the 6 months prior to assessment, and a further 10% had worked for part of that time; 82% were receiving some form of social security. Seventy-five per cent reported deriving at least some of their income from illegal activities, and 38 out of 86 women reported that prostitution was one of their sources of income. Sixty-six per cent of applicants had left school without completing the school certificate. Most had been using heroin for more than 5 years. Forty-five per cent of subjects reported having abused alcohol, and 80% reported either past or current benzodiazepine abuse.
that those referred to clinic 2 had lower rates of property convictions prior to entering treatment. By official records, 50% of all convictions recorded by this cohort were for acquisitive (property) crime. The next most frequent category was drug offences (26%). Because the number of offences in the remaining categories were small, only the results for property and drug offences are reported.
Factors affecting pre-assessment crime rates Table 1 shows the relative risk (and 95% CI) of conviction per year for pre-assessment drug and property offences across four age categories. Although older subjects tended to have accrued more convictions in both categories, pre-assessment conviction rates were significantly lower with increasing age at assessment, suggesting a diminishing frequency of convictions with increasing age. This is shown in Table 1. Women tended to begin offending later, and to have accrued fewer convictions than men. Although pre-assessment conviction rates declined with increasing age at assessment, duration of addiction was not a significant predictor of crime rates, and nor was age of first drug use. However, the age of first conviction was a significant predictor of conviction rates; the younger the age of first conviction, the higher the pre-assessment conviction rates for both drug and property offences. Therefore, in evaluating the impact of treatment, all analyses adjust for the effect of age, sex and age of first conviction.
There were significant differences between approved and rejected subjects; these are described in The impact of entering treatment on conviction rates more detail in another report. Briefly, rejected Drug offence rates dropped sharply in the post subjects were younger, had used heroin for shorter assessment period, and were weakly correlated with periods, and were less likely to be physically pre-assessment drug offence rates (r = 0.139, dependent on opioids. The only significant differ- p = 0.014 by Spearman rank correlation). Property ence between subjects referred to clinics 1 and 2 was offence rates post-assessment correlated with
J. Bell et al. Table 2. Comparison between those who entered treatment and those who did not—drug offence rates Pre-assessment
0.56 [0.48, 0.66]
0.89 [0.76, 1.02]
offence rates pre-assessment (r = 0.351, p < 0.001 by Spearman rank correlation). Table 2 shows the relative risk of drug offence adjusted for age, sex, and age at first conviction, in the post-assessment period for the treated and nontreated subjects. Prior to assessment, drug offence rates were similar in the treated and untreated groups. In both groups there was a reduction in the rate of drug offence arrests in the post-assessment period, with a significantly greater fall in those who did not enter treatment. Amongst those who entered treatment, the reduction in the rate of drug offence convictions was seen at both clinics. This reduction was a function of the length of time individuals stayed in treatment; the relative risk of conviction for a drug offence in the post-assessment period fell by a factor of 0.95 (0.94, 0.97) for each additional month of treatment. That is, the risk of being arrested for a drug offence fell by 0.56 (0.47, 0.70) for very 12 months an individual remained in treatment. Table 3 demonstrates that in the post-assessment period there was a significant increase in conviction rates for property offences in the group who were referred for treatment, but a marked reduction in those who were rejected as unsuitable or dropped out of the assessment process. This finding was investigated further by examining property offence rates by programme. Table 4 shows that there was a significant difference between clinics in property offence rates pre-treatment; after entering treatment there was a small and non-significant fall in conviction rates for clients of programme 1, and a significant rise in conviction rates for clients of programme 2. This finding was further investigated by examining the relationship between arrest rates postassessment and the length of time for which subjects remained in treatment. After adjusting for duration in treatment, the apparent difference between the clinics disappeared. At both clinics, the risk of
0.20 [0.13, 0.29]
conviction for a property offence fell, relative to pre-treatment rates, by a factor of 0.97 [0.96,0.98] for each month of treatment. That is, the relative risk fell by a factor of 0.69 [0.62, 0.78] for each 12 months of treatment at either clinic. The explanation for the rise in conviction rates after entering treatment despite the progressive fall with increasing duration of treatment is that many subjects remained in treatment only a short time; for subjects remaining less than 12 months, the majority of convictions occurred after leaving treatment. Also contributing to the rise in offence rates after entry to treatment is the fact that there was an exceptionally high rate of arrests very early in treatment in a small number of subjects; 24 subjects accrued 49 property convictions in their first 3 months of treatment, suggesting that they had entered treatment at a time of high criminal activity. The different impact on crime rates after entering treatment is due to the fact that subjects were retained in treatment significantly longer in clinic 1; most subjects entering clinic 2 had left treatment within 12 months, and as a group that drop-outs continued to offend at a high rate after leaving treatment. Using linear regression analysis, it was found that neither drug offence rates nor property offence rates pre-assessment were significant predictors of retention in treatment (for property offences, r^ = 0.005, ns; for drug offences, r^ = 0.005). An alternative way of looking at the impact of entering treatment on criminal activity is to look at the number of individuals in each group who sustained convictions post-assessment. This is illustrated for property convictions in Table 5. This table illustrates that nearly half the subjects in each group were convicted of an offence in the postassessment period. It is a less sensitive way of examining the changes in criminality, as it does not take into account the number of offences committed, only the number of people convicted. The difference between the two clinics does not reach
Criminal activity in methadone maintenance
Table 3. Comparison between those who entered treatment and those who did not—property offence rates Pre-assessment
Post-assessment 1.15 [1.05, 1.27]
0.45 [0.36, 0.56]
1.01 [0.90, 1.12]
Table 4. Comparison of programme rates of property offences Programme 2
Programme 1 Pre-assessment Post-assessment
0.79 [0.72, 0.88] 0.96 [0.81, 1.15]
1.05 0.92, 1.19]
Table 5. The proportion of individuals in each group who committed no property offences Prog. 1
No offences in treatment
No offences post-assessment
4, df=2, NS. Statistical significance, nor do the proportions differ significantly between the treatment and non-treatment groups.
Summary of results (1) People who were not referred for methadone treatment had significantly greater reductions in rates of both drug and property crimes in the post-assessment period than those referred for treatment; indeed, property offence rates actually rose in the treatment group. (2) For those who entered treatment, allowing for the tendency of crime rates to fall with increasing age, there was a progressively reducing risk of arrest leading to conviction with increasing duration of treatment. Among those who left treatment there was a continuing high rate of convictions. (3) The different impact on property crime rates
between the programmes was due to differential retention in treatment. (4) For some subjects, entry to treatment occurs at a time of heightened criminal activity.
Discussion There are problems with the using official records as a measure of criminal activity. Arrest and conviction rates are only a very rough guide to the level of criminal activity, as most criminal acts do not result in conviction. Self-report of criminal activity gives a more sensitive measure.' Insofar as conviction rates underestimate the true extent of criminal activity, their use may make it more difficult to detect differences between groups. This emphasizes the robustness of the findings in this study. A further problem with the use of official records is delay. This study used the date of arrest leading to conviction; this is a temporally accurate measure only in cases where the offender is caught 'red-
J. Bell et al.
handed'; however, what frequently happens is that on arrest a paerson may be charged with a number of more or less recent offences. This may be part of the explanation for the large number of convictions shortly after entering treatment noted in some subjects in this study. Finally, convictions do not represent a random sampling of criminal activity, but are subject to chance, the vagaries of local policing activity, and to different levels of skill in avoiding detection on the part of offenders. Despite these reservations, use of official records has some clear advantages. Self-report relies on the subjects memory, which may be accurate over a reasonably recent interval but is subject to distortion and generalization over a longer period of time.^^ Both drug use and involvement in crime are shrouded in obscurity and myth; there is a powerful folklore that drug addiction drives people to predatory crime, and this may colour the self-report of research subjects. There is reason to believe that this does occur; the levels of predatory crime described in some studies imply that addicts commit vastly more crime than is ever reported.^' The first finding in this study was the marked drop in criminal convictions among those subjects who were not approved for methadone. This finding challenges the apparent effectiveness of prolonged methadone maintenance; it appears that refusing an applicant's request for methadone has a more salutary effect on criminality than offering treatment. Such a conclusion would be consistent with the belief that the optimal response to drug abuse is confrontation, emphasizing to the user the wrongness of their behaviour, rather than condoning and continuing their drug use by prescribing methadone. There are two important restrictions on generalizing from the finding that non-treatment subjects showed more improvement. The first is that this was not a randomized control group. Rather, those who were rejected or dropped out differed from those who were approved. During 1986 and 1987, there was great demand for treatment, and few spaces available; there was, therefore, pressure to be selective, restricting treatment to those with the most severe problems. It is likely that the clinical judgement that rejected patients had less severe problems at the time of assessment was accurate. This study found that many people enter treatment during periods of high criminal activity. It is probable that addicts who seek treatment during
periods of decompensation are more likely to be approved, while those who seek methadone during periods of relatively stable adjustment are more likely to be rejected on the grounds of not having a severe problem. The second problem is that neither entry to treatment, nor rejection from treatment, were stable phenomena. More than half of those who initially either dropped out or were rejected subsequently entered methadone programmes;^'' more than half of those who initially entered treatment had left within 12 months.^' The post-assessment interval thus covers a lengthy treatment period for many 'nontreatment' subjects, and includes a lengthy nontreatment period for many of those in the 'treatment' group. This is a problem in all evaluation studies of drug abuse treatment. Addicts tend to go in and out of treatment, so that in follow-up studies it is difficult to evaluate particular treatment episodes.^' In this study it was not possible to validly compare treated and non-treated groups. However, in the treated subjects it was possible to analyse the influence of treatment factors. The major finding of this study is that allowing for the decline in conviction rates with increasing age, and for the effects of sex and age at first conviction, remaining in methadone treatment is associated with a progressively reducing risk of arrest for property and drug offences. This appears to be causally related to remaining in treatment. Higher rates of property offences preassessment were weakly associated with longer, rather than shorter retention in treatment; it thus does not appear plausible to suggest that more criminal addicts were more likely to drop out of treatment. A previous study^' on this treatment cohort found that the most important variables influencing duration of retention were the clinic to which the subject was referred, and the dose of methadone prescribed. Thus, while client's readiness and ability to change may be important, treatment factors are a powerful influence in retaining clients, and improvements associated with remaining in treatment cannot be simply attributed to client motivation. Causal inference regarding the relationship between crime and treatment must be cautious; for example adverse life events might trigger a client both to return to crime and to drop out of treatment. However, the different impact on crime rates of the two clinics suggests that the falling crime rate with a longer time in treatment is likely to be a treatment
Criminal activity in methadone maintenance effect. The reduction in property crime rates among those remaining in treatment was modest. Although studies utilizing self-report have suggested a rather more dramatic impact of treatment, such studies may be particularly susceptible to 'expectancy bias'—the tendency of the client in treatment to answer according to how he thinks he ought to be behaving.^^ A study reported by Sechrest also used official records, and found modest, retention-dependent reductions in arrest rates;''' however, in that study drug offence rates only dropped after a year in treatment, and rates of other offences did not fall until after 2-3 years of treatment. Most research on the impact of methadone maintenance on criminality has failed to allow for client variables which may influence crime rates. Adjusting for significant client variables, this study found a significant, quantifiable impact of treatment on rates of criminal conviction. A highly controlled programme, which did not tolerate ongoing drug use, was not more efficacious in reducing criminal activity than a tolerant programme; rather, as a result of high attrition from treatment, the more regimented programme was less effective, as people expelled from treatment continued to offend. Although 'non-treatment' subjects exhibited greater reductions in criminality, selection bias and treatment instability make it difficult to interpret these results as showing the superiority of no treatment. What is clear is that it is not entry to treatment, but retention in treatment, which is associated with demonstrable reductions in rates of convictions for property offences. This finding is thus a further contribution to the already extensive evidence that retention is the key to achieving benefit from methadone treatment.^* It argues that to be optimally effective, programme policies should be orientated towards encouraging clients to remain in treatment. With the recognition that the spread of HIV infection is a major public health problem, priorities in drug abuse treatment are changing. There is recognition of the need for programmes to become less occupied with abstinence, and more concerned with reducing the harmful consequences of drug use. On the evidence of this study of criminal activity, more tolerant programmes, far from being less effective in promoting changes in behaviour, are likely to be more effective.
Acknowledgements We would like to thank Jacqueline Carless and Dina Fernandes for their data entry, and Rod Benson for
his assistance with data analysis. Dr John Caplehom assisted in identification of the cohort for study. This work was supported in part by funding from the NSW Directorate of the Drug Offensive and in part by funding from a Quality Assurance Project Grant from the NSW Department of Health.
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