Treatment process components and heroin use outcome among methadone patients

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Treatment process components and heroin use outcome among methadone patients Michael Gossop *, Duncan Stewart, John Marsden National Addiction Centre, The Maudsley/Institute of Psychiatry, 4 Windsor Walk, London SE5 8AF, UK Received 16 August 2002; accepted 18 February 2003

Abstract The study proposes and tests an integrative and directional (structural equations) model to explain how pre-treatment motivation, frequency and content of counselling services, programme perceptions, and methadone dose are related to 1 and 6 months heroin use outcomes among opiate addicts receiving outpatient methadone treatment. Data were collected as part of the National Treatment Outcome Research Study (NTORS). The sample comprised 262 patients who were admitted to, and retained in methadone treatment programmes at 6 months. Structural equation models showed several relationships between treatment process variables and heroin use outcomes at 1 and 6 months follow-up. Programme perceptions and methadone dose were related to reduced heroin use at 1 month; early engagement with treatment services was related to reduced heroin use at 6 months. Pretreatment motivation and engagement with treatment services were indirectly related to reduced heroin use at 1 month through their association with programme perceptions. Short-term (1 month) heroin use was strongly related to heroin outcome at 6 months. In addition to direct effects, treatment factors may have important indirect effects upon subsequent outcomes through their influence upon short-term outcomes. # 2003 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Treatment processes; Engagement; Predictors; Outcome

1. Introduction Changes in behaviour after treatment have often been attributed in a non-specific manner to therapeutic and cognitive processes which may have occurred during and after treatment. For some time there has been broad agreement that we need to identify those treatment factors and treatment processes which affect outcomes (Moos et al., 1990; Simpson et al., 1997a), and to find improved and systematic ways to measure the key aspects of the treatment process (McLellan et al., 1992; Moos, 1997). However, research attention to the associations and interactions between patient characteristics, cognitions and behaviours and treatment process variables has been limited (McLellan et al., 1997), and comparatively few empirical studies have investigated these issues, especially with regard to impact upon

* Corresponding author. Tel.: /44-171-703-5411; fax: /44-171703-8454. E-mail address: [email protected] (M. Gossop).

outcomes. Gottheil et al. (1981) suggested that although there is agreement that many treatment factors may be related to outcome, very few have been identified in research studies. An important research challenge involves the identification and operational definition of treatment process measures which can serve as during-treatment indicators, and which can be used to guide the delivery of clinical services to lead to improved patient outcomes (Simpson et al., 1997a). Among the treatment process concepts which have been identified as of potential importance are ‘treatment dose’, ‘therapeutic relationship’ and ‘treatment engagement’ (Joe et al., 1999; De Leon, 2000). Treatment engagement involves more than just attending treatment sessions: it requires the active clinical participation of the patient. Treatment engagement may be regarded as having both an objective component (e.g. amount of therapeutic contact), and a subjective component (e.g. cognitive involvement, motivation for treatment and patient satisfaction). Both of these treatment engagement components are important

03765-8716/03/$ - see front matter # 2003 Elsevier Science Ireland Ltd. All rights reserved. doi:10.1016/S0376-8716(03)00067-X

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and deserve further research investigation. Joe et al. (1999) suggested that the cognitive components of engagement are treatment process variables which are particularly deserving of further research. The need for an improved understanding of how treatment components and treatment processes affect outcome applies to current knowledge of methadone treatments for opiate dependence. Methadone is widely used in the treatment of opiate addiction, and methadone maintenance treatment (MMT), in particular, has been widely researched. Recent reviews have concluded that methadone maintenance can be effective in reducing illicit heroin use and in reducing other problem behaviours among many opiate addicts (Ward et al., 1992; Farrell et al., 1994; Marsden et al., 1998; Marsch, 1998). In practice, however, it is known that MMTs are highly variable. MMT programmes vary both between countries (Gossop and Grant, 1991) and within countries (Ball and Ross, 1991; Stewart et al., 2000). Programmes differ in methadone dose levels, programme entry criteria, time limits for prescribing, frequency of clinic attendance, the manner of dispensing (supervised or unsupervised), and, especially in the UK, the formulation of the drug used (syrup, tablets or ampoules). Such marked variation in the provision of methadone treatments is of considerable clinical importance, and could be expected to have direct relevance to the nature and probable effectiveness of the these interventions. Heroin use has been found to be inversely related to methadone dose, and the delivery of more treatment services within methadone programmes has been found to lead to better outcomes (Ball and Ross, 1991; McLellan et al., 1993). In a randomised trial of supervised injectable versus oral methadone dispensing, Strang et al. (2000) found similar levels of improvement in both treatment conditions but with higher treatment satisfaction rating among patients in the injectable group. The findings of D’Aunno et al. (1999) suggested that many of the methadone programmes in the United States during the 1980s and 1990s did not use effective practices. This situation may be similar to that of other countries, including the UK. Studies of methadone treatments within NTORS showed marked variation between and within programmes (Stewart et al., 2000), with treatment sometimes being provided not as intended, in low doses, or in other ways which were found to be associated with poorer outcomes (Gossop et al., 2001a). The National Treatment Outcome Research Study (NTORS) investigated outcomes among drug users admitted to treatment services across UK. The characteristics and problems of these clients and their outcomes have been described in previous reports (Gossop et al., 1997, 1998a,b, 2000a,b). Patients receiving methadone treatments showed substantial reduc-

tions in their use of heroin and other illicit drugs at 6 months (Gossop et al., 1997), at 1 year (Gossop et al., 2000c), and at 4
/5 years follow-up (Gossop et al., 2001b). The present study extends previous research within NTORS, and investigates components of treatment engagement in relation to outcome. The study identifies and assesses key treatment and treatment engagement factors, including such cognitive factors as motivation for treatment, and treatment satisfaction, as well as treatment component factors, including frequency and content of counselling, and methadone dose. These factors are investigated in relation to short-term (1 month) and medium term (6 months) heroin use outcomes. The study proposes and tests an integrative and directional model to assist in explaining how treatment engagement and methadone dose are related to heroin use outcomes among opiate addicts receiving outpatient methadone treatment.

2. Method 2.1. Programmes and patients The present sample comprised 262 methadone patients who remained in treatment for at least 6 months, and for whom interview data were available at all 3 of the following interviews: at intake, at 1 month, and at 6 months in-treatment follow-ups. The patients were recruited to community-based methadone treatment programmes in NTORS. The methodology and procedure for NTORS has been described in detail elsewhere (Gossop et al., 1998a,b), and only a brief description is presented in this paper. The 31 programmes were chosen for participation on the basis of their capacity to recruit a sufficient number of cases to the project within the restricted time available, and the location of the service (programmes were to be located throughout UK and in areas in which drug problems and drug treatment services were prevalent). Patients were recruited to the study during a 5-month period in 1995. Patients were eligible if they were: (a) starting a new treatment episode; (b) presenting with a drug-related problem; (c) able to provide an address in the UK for follow-up; (d) had not previously enrolled in the study. 2.2. Measures A structured interview was developed to assess substance use behaviours, physical and psychological health, social circumstances, and treatment history. The interview contained items and scales developed specifically for this project as well as measures adapted from published instruments. Interviews were conducted by clinical staff at the treatment programmes who had been trained in the administration of the interview schedule.

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Drug use measures included in the present study were self-reported frequency of heroin use and cocaine use. Urine screening for substance use was conducted on patients from programmes randomly selected on a onein-two basis, at intake and at follow-up. The results of urine screening provided evidence of the validity of selfreported drug use and these results have been presented elsewhere (Gossop et al., 1997, 1998b). Alcohol use was assessed in terms of the quantity of alcohol consumed per week, measured in UK standard units of alcohol (1 unit /8 g of ethanol). Psychological health symptoms were assessed and are shown as the sum of anxiety and depression subscales from the Brief Symptom Inventory (Derogatis, 1993). In addition to age, gender (1 /male), and ethnicity (1 / white-UK), the relationship status of patients before treatment was also recorded (1 /in a relationship). A measure of whether patients were currently facing legal problems (e.g. being on probation, parole, on bail, awaiting trial/sentence) was also included in the analyses. Data for behaviours prior to intake and 6 months follow-up were collected for the 90-day period prior to interview. Data at 1 month follow-up were collected for the previous 30 days. This presents a problem in terms of the analysis of unconverted frequency scores. Because of the differences in recall period, frequency of heroin and cocaine use are expressed as percentage of days used. 2.2.1. Treatment services A treatment services latent variable was constructed for use in the analyses for both the 1 and 6 months data points. These were based upon measures of frequency of counselling sessions, and of content of counselling sessions. Frequency of counselling was measured in terms of the number of individual counselling sessions received. Seventy-six percent (n/199) of our sample reported at least one individual counselling session during the first month of treatment, and 94% (n/247) reported at least on session during the 3 months before the 6-month interview. Among these patients, the mean number of sessions attended was 4.0 (S.D. /3.7; range: 1
/30) at 1 month and 7.4 (S.D./5.2) at 6 months. The mean duration of individual counselling sessions was 32.6 (S.D./16.6) minutes at 1 month, and 29.4 (S.D./ 14.6) minutes at 6 months. Group counselling is not common in methadone treatment programmes (Gossop and Grant, 1991; Ball and Ross, 1991). Two hundred and twelve patients (81% of our sample) reported not having received any form of group counselling session during the period prior to the 1 and 6 months follow-up. Group counselling was not, therefore, included in the frequency of counselling variable. Content of counselling sessions was assessed in terms of the amount of time spent with staff discussing problems during counselling. Patients were asked to

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report how much time had been spent in sessions discussing a range of problem domains (measured on a four point scale: ‘none’, ‘a little’, ‘quite a lot’, and ‘a great deal’). For this study, two measures of counselling time were employed. The first was time discussing illicit drug problems. A measure of time spent discussing other addiction related issues was constructed by summing scale scores for time spent discussing alcohol, psychological, and legal problems. 2.2.2. Methadone dose The prescribed doses of methadone for each patient were recorded from the clinics’ prescribing records from first dose and throughout the 6-month study period. To allow for initial variations in dose due to induction periods, initial prescribing policies, or titration of initial doses, the first methadone dose measure used in the analyses was the dose prescribed to the patient at the time of the 1 month interview. The other dose measure used in this study was that prescribed at the time of the 6 months interview. The mean dose at 1 month was 51.9 mg, and over three quarters of the patients (79%) were receiving doses of 60 mg or less. The mean dose at 6 months was 51.4 mg, with 77% reporting doses of 60 mg or less. 2.2.3. Pretreatment motivation Motivation for treatment was measured with the ‘‘Taking Steps’’ subscale from the Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES) (Miller and Tonigan, 1996). This scale is based upon the model of stages of change proposed by Prochaska and DiClemente (1986) and consists of a combination of action and maintenance items. The Taking Steps subscale comprised eight items and represents the stage at which individuals make efforts to change their behaviour. 2.2.4. Programme perceptions Five items were employed to measure patients’ perceptions of treatment programmes. Two items concerned the therapeutic goals of treatment: whether the patient knows what to expect from their treatment, and if the patient is being rushed to make changes. Three items measured relationships with staff: whether staff were always willing to help with problems; staff caring about the patient; and staff and patient having different ideas about the aims of treatment. Each item was measured on a 5 point Likert type scale. These measures were used to construct a programme perceptions latent variable for both the 1 and 6 months follow-up points. 2.3. Analyses Structural equation modelling (SEM) procedures were conducted using AMOS 4.0 (Arbuckle, 1999).

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SEM allows questions to be answered in which independent and dependent variables can be either factors or measured variables, and where analysis involves multiple regression of factors. In this form of analysis, relationships between directly measured and latent variables are first hypothesised. Parameters (population covariance matrix) are estimated for the hypothesised model and tested against those of the observed sample for consistency. Analyses were conducted using maximum likelihood estimates. The fit of the model is conventionally evaluated by x2. However, since the x2 value is sensitive to larger sample sizes, other measures of model fit are also reported. The Normed Fit Index (NFI) and Comparative Fit Index (CFI) are scored 0
/1, with values above 0.9 indicating an adequate fit. For the root mean square error of approximation (RMSEA), values less than 0.05 indicate a close model fit. Analyses were first conducted for a hypothesised model. Nonsignificant paths between variables were then deleted and the model re-analysed. The directional relationships between the treatment process variables and heroin use outcomes at shortterm, in-treatment follow-up (1 month), and at mediumterm, in-treatment follow-up (6 months) were tested in the model. Analyses tested specific proposed relationships between the variables. These were: 1) Higher levels of pre-treatment motivation will be positively related to utilisation of treatment services and to higher programme perception scores. 2) Patients with greater utilisation of treatment services will achieve better heroin use outcomes. 3) Higher levels of utilisation of treatment services will be related to higher programme perception scores. 4) Higher programme perception scores will also be related to lower levels of heroin use at follow-up. 5) Higher prescribed methadone doses will be related to reduced heroin use at outcome, and to higher programme perception scores. We also hypothesised that relationships would also exist between variables measured at 1 and 6 months. 1) One month heroin use outcomes will be related to 6 months heroin use outcomes. 2) Greater participation in treatment services at 1 month will be related to lower levels of heroin use at 6 months. 3) Patients utilising more treatment services at 1 month will be likely to utilise more services at 6 months. 4) Patients with higher programme perception scores at 1 month will be more likely to participate in treatment services at 6 months. 5) A positive correlation between methadone doses at 1 and 6 months was specified in the model.

Comparisons of the study sample and the remainder of the NTORS intake cohort were conducted using logistic regression procedures. These results are expressed as odds ratios (OR) with 95% confidence intervals. Relationships between patient intake characteristics and process variables were assessed by multiple linear regression. The distributions of the drug use, alcohol, and individual counselling session variables were found to be positively skewed. For all analyses, these variables were logarithmically transformed to reduce the influence of extreme scores. For each variable the skewness of distribution was reduced, with a better approximation to the normality requirements of the multivariate procedures employed.

3. Results A logistic regression analysis was conducted to compare the pre-treatment characteristics of the intreatment patients in the present sample with those in the remainder of the intake cohort. Included in the analysis were pre-treatment measures of: age, gender, ethnicity, relationship status, motivation for treatment, frequency of heroin and cocaine use, injecting status, weekly consumption of alcohol, psychological health scores, current legal problems, and whether patients had received addiction treatment during the previous 2 years. The regression model was statistically significant (x2[12] /77.84, P B/0.001). Patients in the study sample were less frequent users of heroin (63.1% days used vs. 79.0% days used; OR /0.59, 95% CI /0.44, 0.81), reported lower pre-treatment motivation scores (31.7 vs. 32.5; OR /0.96, 95% CI /0.93, 0.99), were less likely to have current legal problems (31 vs. 45%; OR / 0.63, 95% CI /0.45, 0.90), and were more likely to have received previous addiction treatment (82 vs. 72%; OR /1.53, 95% CI /1.01, 2.31). In the first phase of the structured equation modelling analysis, all hypothesised relationships were tested (see Section 2). The structured equation model was constructed using: pre-treatment motivation, and the following measures at both 1 and 6 months: methadone dose, treatment services (latent variable), programme perceptions (latent variable), and heroin use outcomes. The means, standard deviations, and ranges for each of the variables entered into the structural equation models are shown in Table 1. The full hypothesised model showed an acceptable fit to the data (x2[76] /198.86; NFI/0.98; CFI /0.99; RMSEA /0.08). Some paths in the model were found to be nonsignificant. Pre-treatment motivation was found to be unrelated to participation in treatment services (b// 0.04, P/0.63). The treatment services variable at 1 months was not significantly associated with heroin use at 1 month (b /0.14, P /0.09), or methadone dose (b/

M. Gossop et al. / Drug and Alcohol Dependence 71 (2003) 93
/102 Table 1 Variables included in treatment process model Variables

Mean Standard deviation Range

Pre-treatment motivation score

31.7

5.2

12
/40

1 Month follow-up Frequency of heroin use (% days) Drug sessions score Other sessions score Individual counselling sessions Therapeutic goals Relationship with staff Methadone dose (mg/day)

20.2 1.7 1.8 3.0 7.9 11.5 51.9

25.9 0.9 1.5 3.6 1.2 2.0 23.6

0
/100 0
/3 0
/7 0
/30 3
/10 6
/15 5
/180

6 Months follow-up Frequency of heroin use (% days) Drug sessions score Other sessions score Individual counselling sessions Therapeutic goals Relationship with staff Methadone dose (mg/day)

23.5 1.8 2.0 7.0 7.9 11.8 51.4

28.6 0.7 1.6 5.3 1.2 1.7 27.6

0
/100 0
/3 0
/10 0
/39 4
/10 6
/15 2
/200

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variables included in the analyses were: age, gender, ethnicity, relationship status, frequency of heroin and cocaine use, weekly quantity of alcohol consumed, psychological health, legal problems, and previous addiction treatment. Participation in treatment services was associated with greater levels of drinking and psychological health, legal status at treatment entry, age and gender. There was a statistically significant association between previous addiction treatment and lower programme perception scores.

4. Discussion

0.01, P /0.89). A statistically significant correlation was found between methadone dose prescribed at 1 month and methadone dose at 6 months (r/0.82, P B/0.001). However, none of the hypothesised relationships for methadone dose at 6 months were statistically significant. These non-significant paths were removed and the model was retested for the remaining hypothesised relationships. The revised model was also found to show a good fit (x2[70] /181.59; NFI/0.99; CFI /0.99; RMSEA /0.07). The revised model is shown with standardised regression weights for statistically significant paths in Fig. 1. Greater participation in treatment services was associated with higher programme perception scores at both 1 month (b /0.27) and 6 months (b/0.45). The treatment services latent variable at 1 month was predictive of lower frequency of heroin use at 6 months (b//0.38). Higher doses of methadone were associated with less frequent use of heroin at 1 month (b // 0.12). The programme perceptions latent variable at 1 month was predictive of less frequent heroin use at 1 month (b //0.13), and greater participation in treatment services at 6 months (b/0.34). Higher levels of pre-treatment motivation were related to higher programme perception scores (b/0.13). More frequent use of heroin at 1 month follow-up was predictive of more frequent use at 6 months (b/0.63), and treatment services at 1 and 6 months were also positively related (b/0.57). Regression analyses were conducted to assess the influence of patient characteristics and problems at intake to treatment on engagement with treatment services and programme perception latent variables for the first month of treatment (see Table 2). Intake

A number of cognitive treatment engagement factors and treatment component factors were found to be related to heroin use outcomes. Perhaps more importantly, the results are presented in terms of an integrative, directional model which shows how these factors are related to each other and to treatment outcome. This model indicates both the complexity and dynamic relationship of different factors in their influence upon outcome. In the proposed model, not all of the ‘‘effective’’ treatment components were found to relate directly to outcome, and of those variables that were found to relate to outcome not all did so at both followup points. An example of both the complexity and dynamics of the model is found in the results for treatment services. The treatment services latent variable comprised measures of the frequency and content of counselling sessions, and it was found to have both direct and indirect relationships with heroin use outcomes. A direct inverse relationship was found between treatment services and heroin use outcome at 6 months follow-up. Treatment services were not directly related to 1 month heroin use outcomes, but were positively related to programme perceptions at both 1 and 6 months. Programme perceptions were inversely related to use of illicit heroin at 1 and 6 months follow-ups. The provision of services in addition to the administration of methadone has been shown to lead to improved outcomes (Ball and Ross, 1991; McLellan et al., 1993). Individual counselling sessions are described by Ball and Ross (1991) as ‘‘a foundation of long-term MMT’’ (p. 143), and they constitute one of the most frequent forms of therapeutic contact within methadone programmes. Counselling may be regarded the cornerstone of virtually all treatment modalities (Fiorentine and Anglin, 1996). The number of services received by patients has been found to relate to improvements in treatment effectiveness even after controlling for the influence of patient factors (Ball and Ross, 1991; Woody et al., 1983). McLellan et al. (1993) found that the programmes that provided the most services for a particular problem area showed the best outcome in

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Fig. 1. Model of treatment process and outcome.

that area. Simpson et al. (1995) also reported that programme participation as measured by session attendance was related both to improved drug use outcomes and to higher patient satisfaction ratings. Our results showed a direct inverse relationship between methadone dose and frequency of heroin use at 1 month. Although methadone dose was not directly related to 6 months heroin use outcomes, its indirect influence was reflected through the strong positive

association between frequency of heroin use at 1 and 6 months. This is consistent with the results from other studies which suggest that events occurring very early in treatment can have an effect upon later outcomes even though other factors may be stronger predictors of later outcomes (Joe et al., 1991). Other studies have found that methadone dose is an important treatment factor, and that patients on higher doses achieve significantly better outcomes than those

Table 2 Predictors of treatment services and programme perceptions at 1 month Variable

Age % Male % White UK % In relationship Heroina Cocaine Alcoholb Psychological health % With legal problems % Previous treatment

Value

31.1 (6.8) 70 90 62 63.1 (40.7) 7.9 (20.0) 22.8 (52.1) 5.9 (3.2) 31 82

Treatment services

Programme perceptions

Beta

Beta

0.16** 0.13* 0.06 /0.08 0.00 /0.07 0.19*** 0.19*** 0.22*** 0.10 R2 /0.17

/0.02 0.07 0.04 /0.03 /0.01 /0.01 /0.08 /0.07 /0.04 /0.22** R2 /0.07

Figures in brackets are standard deviations. Levels of statistical significance are shown as: *, P B/0.05; **, P B/0.01; ***, P B/0.001. a Heroin and cocaine are shown as mean percent days used during previous 90 days. b Alcohol is shown as mean units consumed per week.

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on lower levels (McGlothlin and Anglin, 1981; Joe et al., 1994). Ward et al. (1992) suggested that doses of 60 mg or more were associated with longer stays in treatment and reduced heroin use outcomes. Ball and Ross (1991) found that higher methadone doses were related to fewer days of heroin use at follow-up, but methadone dose was not related to such other outcome measures as cocaine use or criminal activity. Similar results have been obtained from double-blind studies. Improved treatment retention rates and less illicit drug use was found among patients randomly assigned to 60 versus 20 mg of methadone (Johnson et al., 1992), among patients randomly assigned to 50 versus 20 mg groups (Strain et al., 1993), and among patients assigned to flexible doses within the ranges 80
/100 versus 40
/50 mg (Strain et al., 1999). Compared with many international studies, the methadone doses prescribed to the NTORS patients were relatively low, with only one third of the patients receiving doses of more than 60 mg. It is possible that if higher doses had been prescribed, a stronger association would have been found between dose and heroin use outcomes. Surprisingly, our results did not show any relationship between methadone dose and programme perceptions. In this respect, methadone dose may be less important than plasma methadone concentration. Wolff et al. (2000) suggested that plasma methadone measurements may assist in making dosage adjustments among patients receiving methadone treatment. Although Hiltunen et al. (1999) reported a correlation between methadone dose and plasma methadone concentration, this association was found only among those patients who expressed dissatisfaction with their treatment, and may be primarily reflective of an association between lower doses and lower satisfaction. Motivation for treatment was related to programme perceptions, but was not found to be directly related to participation in treatment services. Other studies have reported both direct and indirect relationships between motivation and treatment response. Simpson et al. (1997b) reported an indirect relationship between motivation and treatment retention with pre-treatment motivation acting as a predictor of session attendance, which was, in turn, predictive of time in treatment. In a study of drug users assigned to treatment in a criminal justice system programme, Pitre et al. (1998) also found that those with higher motivation for treatment at intake had higher treatment involvement scores regardless of the type of counselling that they received. More direct relationships were reported by Simpson and Joe (1993) who found motivation for treatment to be inversely related to treatment drop-out in methadone programmes, and positively related to treatment retention in residential rehabilitation, outpatient methadone and outpatient drug-free programmes (Joe et al., 1998).

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Shen et al. (2000) also found pre-treatment motivation was related to a range of outcomes. Programme perceptions were found to be inversely related to frequency of heroin use both at 1 and 6 months follow-ups. In the general mental health field, a sizeable body of research has investigated clients’ attitudes towards and perceptions of treatment services (e.g. Koltuv et al., 1978; Macdonald et al., 1988). Less research has been done on the treatment perceptions of substance users. Simpson and Lloyd (1979) studied treatment perceptions of clients in methadone maintenance, therapeutic community and outpatient drugfree programmes, and in a study of methadone maintenance, Joe and Friend (1989) found modest associations between treatment satisfaction, length of treatment and favourable outcome. Fiorentine et al. (1999) found that perceptions of the utility of treatment and ancillary services were related to treatment engagement, and Marsden et al. (2000) found satisfaction with methadone treatment to be associated with time in treatment. The findings that higher levels of treatment motivation were related to programme perceptions, and that programme perceptions were predictive of improved heroin use outcomes at 1 and 6 months, support the suggestion of Brown (1991) that an important task of treatment should be to increase motivation and engagement of patients. The programme perceptions latent variable played an important role within the model. Programme perceptions acted as a cognitive mediator both for the level of motivation for treatment brought to treatment by the patient at intake, and for the patients’ treatment engagement (frequency of sessions and the content of counselling). The magnitude of the relationships between treatment process variables and heroin use outcomes in the model was low both at 1 and 6 months. These results are similar to those reported by McLellan et al. (1994). In the present study, the strongest predictor of heroin use at 6 months was heroin use at 1 month. It has sometimes incorrectly been assumed that short-term outcomes are intrinsically less important or less interesting than longer-term outcomes. Many of the changes which occur during treatment take place very soon after the first contact with treatment. Strang et al. (1997) found improvements in a range of substance use and other problem behaviours during the first month of treatment. Strain et al. (1993) found that the most marked reductions in drug use and other problem behaviours tended to occur within the first month of treatment, with problem levels often remaining relatively unchanged during the subsequent 4 months. Cacciola et al. (1998) also reported significant improvements in a number of outcome areas after 2 months of methadone treatment with no further improvements between 3 and 7 months. Treatment interventions are often able to influence distal outcomes only through mediating factors, and to

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the extent that treatment factors are able to influence short-term outcomes, they may have an important if indirect effect upon subsequent outcomes. Our results also show a correlation between treatment services received at 1 and 6 months. This underscores the importance of encouraging early participation in counselling services to provide a firm foundation for further treatment engagement. The structural equations model showed the directional relationships of a number of treatment process factors which were associated with heroin use outcomes. Broader conceptual frameworks of treatment and recovery often include patient characteristics and problems at intake as potential influences upon outcome. Although patient background factors were not of central interest in this paper, the study also examined their relationship with treatment variables. Patients who were older, female, and who had more severe alcohol, psychological health, and legal problems at the start of treatment received more treatment services. The finding that older patients and women tend to show greater participation in treatment services is consistent with results of other studies (Hubbard et al., 1989; Joe et al., 1990; Anglin et al., 1987; Rowan-Szal et al., 2000). Treatment programmes that provide services directed at problem areas such as alcohol, social, psychiatric problems, have been found to achieve the best outcomes in those areas (McLellan et al., 1993). Programme perception scores were lower among those who had received addiction treatment during the 2 years before intake. This may have adversely affected the treatment responses of patients with extensive treatment histories, especially during the early phase of treatment. Hser et al. (1999) found that relatively poor outcomes among treatment experienced patients were related to greater unmet treatment needs and less compliance with programme rules among these patients compared with those entering treatment for the first time. The results presented in this paper are subject to certain limitations. The study focusses upon the relationship between treatment processes and heroin use outcomes. For this reason, the sample comprised only those patients who had remained in treatment up to the 6 months follow-up point, and who had completed both the 1 and 6 months interviews. These patients differed from the remainder of the intake cohort. They were less frequent users of heroin, reported lower levels of motivation for treatment, were less likely to have a current legal problems, and were more likely to have received previous addiction treatment. In these respects, the study sample was not representative of the full sample who sought treatment. It is possible that reduced measurement error could alter the results to improve the fit of the hypothesised model to the data, and it is possible that the use of more comprehensive and sensitive measures might strengthen some of the re-

ported relationships. However, our results are broadly consistent with studies which have employed a greater range of treatment variables (Joe et al., 1999; Simpson et al., 1997b). The investigation of treatment factors and processes is an important issue for current and for future research. The identification of treatment processes which are related to outcome has practical clinical value since it helps to differentiate the ‘‘active ingredients’’ of treatment from ‘‘inert ingredients’’ (McLellan et al., 1988, 1997). The findings reported in this paper add to the existing literature, and are consistent with the results of other studies which have sought to explore this difficult new area. Nonetheless, current knowledge of the role of treatment processes and their relationship to outcomes is still undoubtedly at an early stage, and more research is required into this field of treatment evaluation research.

Acknowledgements The authors wish to thank Dwayne Simpson (Fort Worth, Texas) for his help and support throughout the project; and Colin Taylor (National Addiction Centre) for his advice on statistical procedures and for his help with the analyses. We would like to thank the staff at the treatment agencies without whose active support NTORS would not have been possible, and the patients for agreeing to take part in the project. Funding for NTORS was provided by the Department of Health. The views expressed in this paper are those of the authors and do not necessarily reflect those of the Department of Health.

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