Soyez Et Al 2006 Motivation and Readiness for Therapeutic Community Treatment Psychometric Evaluation of the Dutch Translation of the Circumstances Motivation Readiness and Suitability

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Regular article

Motivation and readiness for therapeutic community treatment:

Psychometric evaluation of the Dutch translation of the Circumstances,

Motivation, Readiness, and Suitability scales

Veerle Soyeza,4, George De Leon b, Yves Rosseelc, Eric Broekaert a

a Department of Orthopedagogics, Ghent University, H. Dunantlaan 2, 9000 Gent, Belgium

bCenter for Therapeutic Community Research (CTCR), National Development and Research Institutes, Inc., 71 West 23rd street, New York, NY 10010, USAc Department of Data Analysis, Ghent University, H. Dunantlaan 1, 9000 Gent, Belgium

Received 15 April 2005; received in revised form 16 January 2006; accepted 8 February 2006

Abstract

There is empirical evidence that treatment motivation and readiness are closely linked to retention. Several instruments have been

developed to measure these concepts; such instruments can reliably assess the stages of motivation and readiness, and predict treatment

retention and outcome. However, limited efforts have been undertaken in Europe to translate those instruments and to determine their

reliability and validity. In this study, the psychometric properties of a Dutch translation of the Circumstances, Motivation, Readiness,

and Suitability (CMRS) scales by De Leon and Jainchill [Journal of Psychoactive Drugs 8 (1986) 203–208] and the shortened CMR

Intake Version are illustrated in a Flemish sample of therapeutic community residents (n = 207). Exploratory factor analyses confirm three

CMR subscales, although confirmatory factor analysis reveals only a moderate fit for both the CMRS and the CMR. In contrast, the

predictive power of the instrument is strong, specifically for 1-year retention. Significant correlations were found between CMRS measures

and age, drug severity, legal referral, and social problems. It is concluded that the Dutch translation of the CMRS and the CMR can be

employed as a valid indicator of treatment motivation and readiness, although additional research concerning factorial structures is needed.

D 2006 Elsevier Inc. All rights reserved.

Keywords: Treatment readiness and motivation; Assessment; Therapeutic communities; Psychometric properties; CMRS

1. Introduction

Retention has always been an important issue in

substance abuse treatment: Longer retention generally

predicts better follow-up results (Simpson, Joe, Broome,

et al., 1997; Simpson, Joe, & Brown, 1997). This is

not different for therapeutic communities (TCs): Severalstudies have illustrated that the effectiveness of TC treat-

ment is highly correlated with retention (Condelli, 1994;

Condelli & De Leon, 1993; Condelli & Hubbard, 1994; De

Leon, 1991; Kooyman, 1993). Parallel to this finding,

numerous researchers started looking for factors influencing

dropout and retention. Since the beginning of the 1980s,

dynamic variables—specifically motivation and readiness

t o change—have been considered crucial in this context

(Condelli & De Leon, 1993). Clients’ motivational status

has been found to be a consistent predictor of retention in

different treatment modalities (Cox & Klinger, 1988; De

Leon, Melnick, Kressel, & Jainchill, 1994; Joe, Simpson, &

Broome, 1998; Ryan, Plant, & O’Malley, 1995; Simpson &Joe, 1993). More recently, the role of motivation in the

treatment process has also been studied (Cox & Klinger,

1988; De Leon et al., 1994; Ryan et al., 1995; Simpson &

Joe, 1993).

In line with the growing acceptance of treatment

motivation and readiness as vital factors for treatment

retention, a number of instruments that are able to measure

these concepts have been developed in research on smoking

and alcoholism, methadone maintenance treatment, and TC

0740-5472/06/$ – see front matter D 2006 Elsevier Inc. All rights reserved.

doi:10.1016/j.jsat.2006.02.007

4 Corresponding author. Tel.: +32 9 264 63 64; fax: +32 9 264 64 91.

E-mail address: [email protected] (V. Soyez).

Journal of Substance Abuse Treatment 30 (2006) 297–308



treatment (for a more elaborate overview, see NEDTAC,

1999). There is evidence that these instruments can reliably

assess the stages of motivation and readiness, and predict

treatment retention and outcome. One of the first existing

scales is the University of Rhode Island Change Assessment

(URICA) scale (McConnaughy, Prochaska, & Velice, 1983),

a general stages-of-change model that was initially gener-ated for measuring motivation in smokers and alcoholics.

Like the URICA, the Stages of Change Readiness and

Treatment Eagerness Scale (Miller & Toningan, 1996)

focuses on the stages of change developed by Prochaska,

DiClemente, and Norcross (1993); the instrument was

developed for use in alcohol treatment programs, but it

was later adapted for cocaine users and other drug users.

Other well-known instruments that were originally con-

structed to measure motivation in alcohol populations are

t he following: the Readiness to Change Questionnaire

(Heather, Gold, & Rollnick, 1991), the Motivational

Structure Questionnaire (Cox & Klinger, 1988), and theTreatment Motivation Questionnaire (Ryan et al., 1995).

The Circumstances, Motivation, Readiness, and Suitability

(CMRS) scales (De Leon & Jainchill, 1986) and the TCU

Motivation for Treatment scale (Simpson & Joe, 1993),

which have common roots and are conceptually related

(De Leon & Jainchill, 1986; De Leon, Melnick, & Hawke,

2000; Joe et al., 1998), were developed to measure

motivation and treatment readiness in abusers of illegal

substances. Although the CMRS was originally designed for

use in a specific setting (i.e., TCs), it also proved to be

applicable in other settings.

All of the instruments previously mentioned were

developed for and validated in North American populations.Research with those instruments offered empirical evidence

for theoretical and clinical assumptions about treatment

motivation and readiness, and their influences on retention.

This link between motivation and treatment retention was

easily accepted in Europe, although limited efforts have

been undertaken there to formally measure motivational

concepts. Until a few years ago, hardly any new instruments

were developed; existing instruments were only translated

occasionally, and psychometric characteristics were deter-

mined to a limited extent. However, such studies might

be important because the European drug scene clearly

differs from the American scene. For example, problemdrug users in the European Union are still mostly primary

opiate users; the prevalence of cocaine and crack use is

considerably lower than in the United States, except in some

large cities in S pain, Germany, and The Netherlands

(EMCDDA, 2003).

In the last 5 years, there had been some initiatives in

Dutch-speaking countries to translate and validate a number

of existing motivation and readiness instruments (De

Fuentes-Merillas, De Jong, & Schippers, 2002; De Jonge,

Schaap, & Schippers, 2002; De Weert-Van Oene, Schippers,

De Jong, & Schrijvers, 2002; Franken & Hendricks, 1999).

In this study, the psychometric properties (reliability, factor

structure, and validity) of a Dutch translation of the CMRS

scales of De Leon and Jainchill (1986) and the shortened

CMR Intake Version (De Leon et al., 1994; De Leon,

Melnick, Thomas, Kressel, & Wexler, 2000) are illustrated

in a Flemish sample of substance abusers. The CMR is an

18-item factored version derived from the original 42-item

CMRS in which the Suitability (S) scale was eliminatedand the other scales were shortened. Whereas the Circum-

stances (C), Motivation (M), and Readiness (R) scales are

general measures of motivation for t reatment, the S-scale is

specific to long-term TC treatment (Melnick, Hawke, & De

Leon, 2003).

The CMRS and the CMR are self-administered instru-

ments and employ Likert-type items rated on a 5-point scale

ranging from 1 = strongly disagree to 5 = strongly agree .

The items in the C-scale measure external conditions or

reasons that influence people to seek treatment, such as

actual losses and fears regarding negative events. After

factor analysis, it became clear that two C-scales could beidentified: external b pressure to ent er treatment Q and

external b pressure to leave treatment Q (De Leon, Melnick,

Thomas, et al., 2000). Motivational items evaluate a client’s

inner reasons for change. The readiness items assess the

perceived need for treatment as opposed to other self-change

options, such as self-reliance (will power) and use of

external supports (De Leon et al., 1994). Suitability items

(only CMRS) examine the perceived applicability of

residential TC treatment. In studies wherein the 42-item

version of the CMRS was used, a linear relationship

between motivation and both short-term and long-term

retention in a large urban TC was illustrated (De Leon et al.,

1994). The predictive validity of the CMRS was confirmedin additional studies among various ethnic groups (De Leon,

Melnick, Schoket, & Jainchill, 1993), age groups (Melnick,

De Leon, Hawke, Jainchill, & Kressel, 1997), and abusers

of different illegal substances (De Leon, Melnick, &

Kressel, 1997). CMR scales were factor-analyzed and

proved to be unidimensional (motivation and readiness) or

bidimensional (circumstances) for several subgroups of

substance abusers; the scales had good (predictive) validity

(Melnick et al., 2003).

As mentioned before, the CMR(S) had already been

tr anslated into Dutch and used in some research projects

(Franken & Hendricks, 1999; P. Peters, H. Nijman, &T. Schuurmans, personal communication, September 13,

1996). In Franken and Hendricks (1999), it was shown

that clients with negative inpatient detoxification outcome

(i.e., who were not referred to further treatment) were more

likely to perceive (at the start of their detoxification) that

they were less suitable for long-term residential treatment

than clients with a positive outcome. In a second study

(P. Peters, H. Nijman, & T. Schuurmans, personal commu-

nication, September 13, 1996), significant correlations

were found between retention and motivation, readiness,

and the total CMRS score for clients entering detoxification

units. However, the psychometric properties of this Dutch

V. Soyez et al. / Journal of Substance Abuse Treatment 30 (2006) 297–308298



translation of the CMRS were never established. The

purpose of our study is, therefore, to test if the motivation

and readiness constructs underlying the CMR(S) scales can

be found in a Flemish sample as well, and, consequently, if

the use of those instruments is useful in a European

population. The construct validity of the CMR(S) has never

been the focus of study, even in American populations. It was, therefore, an additional aim to provide data bearing

upon construct validity.

As this study was conducted in a specific long-term

residential TC setting, the CMRS was used as starting point.

2. Materials and methods

2.1. Sample

Data for this study were collected as part of a larger

research project on the influence of social networks ontreatment retention and success. The project was conducted

within four drug-free TCs in the Dutch-speaking part of

Belgium (Flanders). Two hundred sixty-seven people

(261 unique individuals) started treatment between May 1,

2000, and April 30, 2002, in one of those TCs. Thirteen

clients (5.0%) did not provide consent; of the 248 clients

who gave written informed consent to participate, 81.9%

(n = 203) completed all instruments used in this study.

Treatment reentry with more than a 6-month interval was

considered as a new treatment period; based on this line of

reasoning, four clients completed the CMRS twice. Thus,

dat a on 207 cases are reported in this study.

Table 1 gives an overview of the main client character-istics. Significant differences between TCs were found for

age (slightly older residents in TC4), F (3, 201) = 3.20,

p b .05, and sex ratio (more women in TC1 and TC3

compared to TC2 and TC4), v2(3) = 9.29, p b .05. Low

composite scores for alcohol and drugs can be explained by

the fact that most clients were in a drug-free detoxification

unit 30 days before entering the TC, so they did not have the

possibility of using any drugs for some weeks.

The 45 clients who are not included in the study are

mainly early dropouts (dropout within the first 14 days)

(see Table 1).

The four TCs in the study are traditional long-termtreatment modalities with a planned duration of stay

between 12 and 14 months. The mean time in program

(TIP) for our sample was about 8 months (242 days,

SD = 184 days), with a median of about 6 months

(188 days). There were no significant differences between

the four TCs for treatment retention, and neither for the

absolute number of days (TIP), F (3, 203) = 1.88, p = .13,

nor for the logarithm of TIP (LogTIP), F (3, 203) V 1.

Almost 8% of the clients in the study (7.7%) had left

treatment within the first 30 days; 25.6% of them had

dropped out after 3 months. After 1 year, 72.9% of the

clients had left the TC.

Despite some specific program characteristics, all four

centers follow traditional TC principles, as described in the

literature (De Leon, 2000; Kooyman, 1993).

2.2. Instruments

For the purpose of this study, the original CMR(S) wastranslated by three independent translators. The three

versions were compared and integrated into one; this

integrated version was subject to backtranslation.

All items of the original 42-item CMRS and the 18-item

version CMR were initially maintained. For the CMRS, this

means that there are eight items in the C-scale, 12 in the

M-scale, 8 in the R-scale, and 14 in the S-scale. The C-scale

of the CMR contains six items (three in C1 and three in C2),

the M-scale contains five items, and the R-scale contains

seven items.

Correlations between the CMR and the CMRS were

measured. The correlation between the 18-item and the42-item instruments was .92 (total score), with individual

scale score correlations ranging from .83 (motivation) to

.97 (readiness).

Apart from the CMR S, all clients were also interviewed

by means of EuropASI (Kokkevi & Hartgers, 1995), which

is the European adaptation of the fifth edition of the

Addiction Severity Index (McLellan, Luborsky, O’Brien,

& Woody, 1980). The EuropASI is a semistructured

interview producing a multidimensional client profile by

examining problems and their severity in seven areas of

functioning (medical health, employment/support, alcohol

use, drug use, legal problems, family/social relationships,

and psychological problems). Each of the dimensionsincludes lifetime measures, which can serve as predictor

variables, and past 30 days measures, which can serve as

baseline and outcome measures. Scoring is based on two

indices: (1) interviewers’ severity rating, which also

includes client-reported ratings of problem severity and

need for additional treatment; and (2) composite scores

(range, 0–1), which are arithmetically based indicators of

current problem severity.

Information on retention, which was made operational as

the total number of days a client stayed in primary treat-

ment, was gathered directly from treatment programs’ files.

In case of dropout followed by reentry within 30 days or less, the total TIP was the sum of days in treatment during

the respective periods. One of the treatment units in the

study has an induction phase preceding primary TC treat-

ment. As this induction phase is not a treatment phase by

itself (all clients entering this phase are assumed to enter the

TC), it was considered as TC treatment within this study.

2.3. Procedure

It was our intention to administer the CMRS within

2 weeks of admission; EuropASI interviews were adminis-

tered within the first 4 weeks of treatment. Staff members

V. Soyez et al. / Journal of Substance Abuse Treatment 30 (2006) 297–308 299



(or occasionally a member of the research team) asked the

client, as quickly as possible after admission, for informed

consent for participation in the study and gave them

the CMRS.

The EuropASI was administered in a face-to-face inter-

view by trained staff members. In three of four TCs, the

EuropASI was part of the standard assessment procedure. In

the fourth TC, staff members were specifically trained to

conduct the interviews.

2.4. Data analysis

The analysis addressed the validity and reliability of the

instrument. As it was the aim to replicate earlier American

studies on the CMR(S), it was decided to conduct mainly

the same analyses as in those existing studies.

First, the internal structures of the four CMRS scalesand the three CMR scales were examined. An explorative

factor analysis was used to explore the dimensionality of

the scales. Principal axis extraction was conducted in the

total item pool in the first place and in each of the

dimensions separately in the second place. In addition,

confirmatory factor analysis (CFA; Jfreskog & Sfrbom,

1999) was used to study the factorial validity of the CMRS

and the CMR. In evaluating model fit, the model chi-square

statistic was supplemented with both an absolute and an

incremental fit index (Bollen, 1989; Hu & Bentler, 1998).

Absolute fit indices evaluate how well an a priori model

reproduces sample data. The root mean square error of approximation (RMSEA; Browne & Cudeck, 1993) will be

reported, for which a value of 0.06 or lower indicates a

good fit. Incremental fit indexes evaluate model fit by

comparing a target model to a baseline model. Typically,

the null model in which all the observed variables are

uncorrelated is used as a baseline model. We will report the

comparative fit index (CFI; Bentler, 1990), for which

values of 0.90 and 0.95 or higher indicate a reasonable and

a good fit, respectively (Hu & Bentler, 1999).

Because the inspection of univariate skewness and

kurtosis measures revealed that (multivariate) normality

assumption did not hold for these data, the distribution of

the test statistics to evaluate model fit might be distorted.Therefore, we used the scaled test statistic of Satorra and

Bentler (1994) to correct the normal theory statistics to yield

more accurate behaviors.

Secondly, predictive validity was addressed. Pearson

correlations between the CMR(S) and retention were

assessed ( p b .05 was considered significant). Analyses

utilized two measures of retention: a continuous variable

(the number of days in treatment) and three dichotomous

variables (1-month, 3-month, and 12-month retention as

predictors of early, intermediate, and late dropout, respec-

tively). The predictive power at 1 month, 3 months, and

12 months was analyzed using a Mantel–Haenszel test for linearity.

A number of variables from the EuropASI were also

correlated with CMR(S) scale scores to consider construct

validity. The measures used for validation were EuropASI

severity scores and a number of selected EuropASI

variables, which have been reported in the literature as

influencing motivation and readiness: age (Melnick et al.,

1997), drug severity (De Weert-Van Oene et al., 2002;

Melnick, De Leon, Thomas, Wexler , & Kressel, 2001),

criminal history (Melnick et al., 2001), and social relations

(Gerdner & Holmberg, 2000; Griffith, Knight, Joe, &

Simpson, 1998). Specifically for age, four category groups

Table 1

Client characteristics

Study sample

(n = 207)

Not included

(n = 45)

Sociodemographic data

Sex (% female) 15.1 15.6

Age [mean (SD)] 26.4 (6.32) 26.5 (5.56)

Primary drug used (%)

Opiates 20.8 –

Cocaine 6.4 –

Alcohol + drug 16.3 –

Polydrug use 41.1 –

Ever injected (%) 64.4 –

Highest level of education

(% primary school

degree or lower)

49.5 –

Legal referral (%) 37.7 –

EuropASI severity scores

[mean (SD)]

Medical health 2.47 (2.06) –

Education/employment 3.67 (1.85) –

Alcohol 3.34 (2.63) –

Drug 6.65 (1.39) –

Legal 3.69 (2.31) –

Family/social 5.01 (1.68) –

Psychological 4.35 (2.19) –

EuropASI composite scores

[mean (SD)]

Medical health .30 (0.32) –

Education/employment .92 (0.22) –

Alcohol .14 (0.21) –

Drug .17 (0.09) –

Legal .32 (0.28) –

Family/social

Family .27 (0.26) –

Social .18 (0.21) –

Psychological .13 (0.09) –

Number of days in treatment

(TIP/LogTIP)

[median (mean/ SD)]

Total group (all TCs) 188 (242/184); 2.27

(2.21/0.47)

19 (48/66); 1.28

(1.24/0.68)

TC1 217 (277/214); 2.33

(2.24/0.50) (n = 66)

4 (10/17); 0.60

(0.72/0.49) (n = 15)

TC2 189 (231/178); 2.27

(2.17/0.50) (n = 72)

23 (59/77); 1.36

(1.32/0.76) (n = 13)

TC3 199 (250/172); 2.30

(2.25/0.41) (n = 34)

84 (84/24); 1.91

(1.91/0.13) (n = 2)

TC4 163 (200/131); 2.21

(2.18/0.37) (n = 35)

34 (66/77); 1.53

(1.53/0.54) (n = 15)




were constructed: b18, 19–23, 24–28, and z29 years. It

was expected that both the M-scale and the R-scale of the

CMR(S) would correlate with previously mentioned Euro-

pASI measures.

3. Results

3.1. CMRS

3.1.1. Internal consistency

3.1.1.1. Explorative factor analysis. Exploratory factor

analysis (using principal axis factoring) with Varimax

rotation of the 42 items of the CMRS yielded 11 factors

with eigenvalues greater than 1.0, explaining 55.9% of the

original variance. One factor clearly contained the majority

of suitability items (11 of 14). Three factors contained amajority of circumstances items, four factors contained most

of the motivation items, and two factors contained a

majority of the readiness items. Interpretation of the

remaining factors was less obvious.

Additional factor analyses on each of the subscales

separately yielded similar results: All of the four scales

proved to be divided in subscales. The C-scale was three-

dimensional. The three C-subscales together explained

49.6% of the variance of this scale. Eigenvalues were

3.15, 1.35, and 1.01, respectively. Item C1 (I am sure I

would go to jail if I did not enter treatment) had a negative

loading (0.461) on one of the C-subscales. The M-scale

proved to be four-dimensional; subscales had eigenvaluesof 3.63 (two items), 1.77 (three items), 1.27 (three items),

and 1.09 (two items). In total, 43.3% of the variance of

this scale was explained by those four factors together.

Again, one item (M12: I still have to change a couple of

things about myself) had a negative loading (0.477).

Both the R-scale and the S-scale were two-dimensional.

Eigenvalues were 3.82 and 1.06, and 6.06 and 1.46 on the

R-subscale and the S-subscale, respectively. The two factors

of the R-scale explain together 49.5% of the variance;

46.9% of the variance of the S-scale was explained by the

two main factors. Factor analyses indicated that the differ-

ent scales are adjacent to each other, and interscale Pearsoncorrelations confirmed this. Table 2 gives an overview of

these correlations.

3.1.1.2. Confirmative factor analysis. The factorial structure

of the full 42-item version of the CMRS was examined

using CFA. Only one a priori model was specified and

fitted to the data. This model contained four factors cor-

responding with the C-, M-, R-, and S-subscales. The fac-

tors were assumed to correlate. The fit of this model was

low to moderate, v2{SB} = 1,642, df = 813, CFI = 0.69,

RMSEA = 0.071. As the model assumed that the factors

(i.e., subscales) were homogeneous and one-dimensional,

this low fit was expected given the findings of exploratory

factor analysis, which strongly suggested that the subscales

of the CMRS were rather multidimensional. Additional

analyses in which cross-loadings among factors were

accepted did not improve marginal fit indices.

3.1.1.3. Reliability. Cronbach a coefficients for each of thefour CMRS subscales and for the total score were

calculated. The total a (.92) is high. a Coefficients for the

different subscales are .71 (circumstances), .73 (motivation),

.81 (readiness), and .88 (suitability), respectively.

3.1.2. Predictive validity

3.1.2.1. Correlational analyses. Table 3 contains the

correlations between each of the four subscales, and various

measures of retention.

For continuous retention variables, all of the TIP and

LogTIP correlations with the scores for the separate scales (C,M, R, and S) and with the total score are significant ( p b .01).

Considering the different dichotomous measures for

retention, correlations with long-term retention again

reached significance for all scores for separate scales

and for the total score ( p b .01; S-scale, p b .05).

Correlations with the R-scale were not significant for

1-month and 3-month retention; C-, M-, and S-scales, as

well as the total score, correlated significantly with short

and intermediate retention.

3.1.2.2. CMRS scores and predictive power. Previous

research with the CMRS and the CMR shows that dropout prediction is clinically meaningful when specific cutoff

scores are used (De Leon et al., 1994): The mean and the

variance of the CMRS scale scores and the total score are

utilized to classify four groups in terms of risk for dropout.

The low group (L) is composed of scores that fall 1 SD or

more below the mean. The moderately low group (ML)

consists of scores between the mean and 1 SD below the

mean. The moderately high group (MH) consists of scores

between the mean and 1 SD or more above the mean.

Finally, the high group (H) is composed of scores 1 SD or

more above the mean.

Table 4 summarizes the relationship between CMRSscores (each scale separately, the total score, and the

motivation readiness score) and 1-month, 3-month, and

1-year retention for the four group levels in the study sample

(Mantel–Haenszel test for linearity).

Significant linear relationships are shown for almost all

separate scale scores, the total score, and the motivation

readiness score at 1 month, 3 months, and 1 year. The

relationship for the R-scale is not significant at 1 and

3 months. There are only five cells that do not conform to

the correct direction (circumstances H at 1 month, total

CMRS score H at 3 months, MR score ML at 3 months, and

circumstances ML and H at 1 year).




Generally, it can be said that higher CMRS scores are

consistently related to remaining in treatment. The relation-

ship for 1-year retention is particularly impressive: The

percentage of clients who have a high score (36%) and

remain in treatment for 1 year is almost three times higher

than the percentage of those with a low score (12.5%).

For separate subscales, similar ratios are found, although they

are little lower for the C-subscale (2.1). The S-scale ratio

is 6.2.

3.1.2.3. Survivor correlations. However, it is possible that

correlations with 1-year retention are purely due to the

effects of the initial 30- or 90-day differences. To remove

any confounding effect of these initial dropout rates on

1-year retention, all correlational analyses were reperformed

for 30-day (n = 191) and 90-day (n = 154) survivors.

Previous findings (for the total study sample) were generally

confirmed in these survivor analyses. A significant linear

trend was found for all separate CMRS scale scores, the

total score, and the MR score (not shown). For the MR

score, for example, 46.6% of the highest scoring 30-day

survivors remained in treatment for 1 year, compared to

only 14.8% of the lowest scorers. Similar numbers were

found for 90-day survivors, where 53.8% of the highest

scorers—and only 19.0% of the lowest scorers—remained

in treatment for 1 year.

Consequently, it can be concluded that there is a large

and significant difference in dropout by initial score on the

CMRS among 30- and 90-day survivors, and that the long-

term differences are not an arithmetic artifact of initial 30- or

90-day differences.

3.1.3. Construct validity

3.1.3.1. Correlational analyses. Several EuropASI variables

were correlated with all CMRS measures (see Table 4). The

strongest correlations were found for drug-related variables.

All CMRS measures correlated significantly ( p b .01;

C-scale, p b .05) with the severity score for drug problems.

Clients who had more treatment periods for drug problems

in the past scored higher on all subscales, except on the

C-scale. Specifically for intravenous drug users, the longer

Table 3

Correlations between CMRS subscales and different measures of retention, and those between CMRS subscales and different EuropASI measures

Circumstances Motivation Readiness Suitability Total M + R C + M + R

Retention measures

TIP .2144 .2544 .2344 .2244 .2744 .2544 .2744

LogTIP .2344 .2744 .1944 .2444 .2844 .2444 .2744

Retention, 30 days .1744 .2144 .08 .1844 .1944 .164 .1844

Retention, 120 days .164 .154 .08 .2044 .1844 .134 .154

Retention, 360 days .154 .2144 .1844 .164 .2144 .2144 .2244

EuropASI measures

Sex .12 .11 .07 .144 .144 .10 .12

Age .04 .12 .164 .11 .12 .154 .12

Severity scoresMedical .004 .02 .001 .001 .01 .01 .01

Education .134 .11 .144 .1844 .1744 .144 .154

Alcohol .144 .164 .06 .12 .154 .12 .144

Drugs .154 .2144 .1744 .2144 .2344 .2144 .2144

Legal .08 .06 .04 .04 .005 .01 .02

Family .08 .10 .10 .07 .10 .11 .11

Psychological .10 .02 .007 .01 .01 .02 .07

Years injected .2144 .11 .2344 .1744 .2144 .1744 .2144

Previous treatment .11 .164 .134 .154 .1744 .154 .144

Legal referral .1844 .07 .1844 .09 .144 .12 .154

Close relation .07 .154 .10 .12 .134 .144 .134

Social problems .164 .144 .12 .12 .164 .144 .164

4 Pearson correlation, significant at p b .05.

44 Pearson correlation, significant at p b .01.

Table 2

CMRS interscale correlations

Circumstances Motivation Readiness Suitability Total

Circumstances .47444 .60444 .54444 .75444

Motivation .72444 .66444 .75444

Readiness .70444 .92444

Suitability .90444

444 p b .001.




they had injected drugs, the lower were their scores on all

subscales (significant correlations at p b .01, except for the

M-scale). A higher severity score for alcohol problems

correlated to higher circumstances and motivation scores,

and a higher total score ( p b .05).

Legally referred clients had significant lower scores on

the C-scale and the R-scale ( p b .01) and their total score,and the C + M + R score was lower as well ( p b .05).

However, there were no significant correlations with the

severity score for legal problems, or with the total number

of lifetime arrests and total number of lifetime convictions

(not shown). Lifetime social problems (with family and

significant others) correlated positively ( p b .05) with all

scales, except with the R-scale and the S-scale. On the

contrary, positive correlations with the M-scale and the

sum scores were found for the total number of close

relations they had. The severity score for family and social

problems did not correlate with any of the CMRS

measures. The severity score for education/employment revealed positive correlations for all measures, except for

the M-scale.

Women assessed themselves as less suitable for TC

treatment and had a lower total CMRS score ( p b .05).

Older clients seemed to be more ready for treatment and had

a significantly higher MR score ( p b .05).

3.2. CMR

As the S-scale was designed to examine the perceived

applicability for residential TC treatment, it was necessary

to eliminate this subscale to make the instrument useful in

other treatment settings. The other three subscales (C, M,

and R) were subject to fact or analysis. This resulted in a

reduced pool of 18 items (De Leon, Melnick, & Hawke,

2000; De Leon, Melnick, Thomas, et al., 2000). The 18-item

factor-based CMR, instead of the CMRS, is now used in

most studies.

3.2.1. Internal consistency

3.2.1.1. Explorative factor analysis. Exploratory factor

analysis (using principal axis factoring) with Varimax

rotation of the 18 items of the CMR yielded four factors

with eigenvalues greater than 1.0, explaining 46.8% of the

original variance.

However, almost all items can be classified under the

first two factors. The first factor (explaining 15% of

the variance) contains all motivation items and a majority

of the readiness items. The second factor (explaining 14% of

the variance) contains mostly circumstances items. Theinterpretation of the last two factors is less obvious.

On the other hand, if the analysis is conducted on each

of the dimensions separately, only the C-scale proves to

Table 5

CMR interscale correlations

Circumstances Motivation Readiness Total

Circumstances .30444 .55444 .77444

Motivation .65444 .75444

Readiness .92444

444 p b .001.

Table 4

One-month, 3-month, and 1-year retention by CMRS scale scores

Low (%) Moderately low (%) Moderately high (%) High (%) Total (%)/significance

1-month retention

Circumstances 82.1 88.9 95.4 92.2 92.34

Motivation 81.3 88.9 96.3 100.0 92.3444

Readiness 85.7 90.8 93.7 97.1 92.3

Suitability 84.6 88.4 95.5 100.0 92.34

Total CMRS score 84.4 84.9 96.9 100.0 92.34

MR score 90.0 84.6 96.3 100.0 92.34

3-month retention

Circumstances 53.8 80.6 79.3 76.2 74.44

Motivation 62.5 66.7 81.7 83.3 74.44

Readiness 67.9 69.2 78.5 80.0 74.4

Suitability 57.7 65.2 83.1 87.0 74.4444

Total CMRS score 62.5 67.9 80.4 80.0 74.44

MR score 70.0 67.7 76.8 85.7 74.44 ( p = .062)

1-year retention

Circumstances 15.4 13.9 34.2 33.3 27.14

Motivation 12.5 17.5 36.6 36.7 27.14

Readiness 14.3 23.1 27.8 42.9 27.14

Suitability 7.7 21.7 31.5 47.8 27.1444

Total CMRS score 12.5 18.9 34.0 36.0 27.14

MR score 13.3 19.6 32.9 46.7 27.1444

Note: The probability value reflects linearity across the low, moderately low, moderately high, and high groups.

4 Mantel–Haenszel, significant at p b .05.







remain in treatment for 1 year is 3.6 and 4.6 times,

respectively, the percentage of low scorers.

3.2.2.3. Survivor correlations. Like for the CMRS, all

correlational analyses were reperformed for 30- and 90-day

survivors to remove the confounding effects of initial

dropout rates. Significant linear trends were found for all

subscale scores, the total score, and the MR score (not

shown). The long-term predictive power of the MR score

was impressive: 50% of the highest scorers among 30-daysurvivors remained in treatment for 1 year, compared to

12.5% of the lowest scorers. Among 90-day survivors, the

difference between the two groups was 57.1% (highest

scorers) compared to 15.0% (lowest scorers).

3.2.3. Construct validity

3.2.3.1. Correlational analyses. The correlations found (see

Table 6) were largely similar to those with the CMRS.

However, less powerful correlations were found for the

education/employment severity score (only the total CMR

score was significantly correlated; p b .05). Lifetime problems with significant others and the severity score for

alcohol problems did not reveal any significant correla-

tions anymore.

Women had lower scores on C- and M-subscales

( p b .05), whereas older clients scored higher on all

subscales, except on the C-scale ( p b .001).

4. Discussion

In this study, the psychometric properties of a Dutch

translation of the CMR(S) were studied. In the first step,

the factorial structure of both the CMRS and the CMR

was addressed. The second step examined the validity of

the Dutch version. The findings for each step are dis-

cussed separately.

4.1. Factor structure

Exploratory and confirmatory factor analyses were

conducted. As the CMR is a factored version of the CMRS,

results for this instrument are of particular interest. Findingsfor exploratory factor analysis were satisfactory and in line

with the results of preliminary American studies. These

studies identified one bidimensional (circumstances) and

two unidimensional (motivation and readiness) scales in a

long-term residential sample (n = 668). This four-factor

structure was tested across other treatment samples (short-

term residential, n = 258; referral agency, n = 672;

correctional facility, n = 503) by means of confirmatory

factor analyses, which revealed f it indices ranging from

0.86 to 0.95 (Melnick et al., 2003).

In this study, exploratory factor analysis clearly sup-

ported the four-factor conceptualization of the CMR. It wasfound that the C-scale was bidimensional. However, these

two dimensions were not in accordance with the pressure-

to-enter-treatment (and pressure-to-leave-treatment) factors

that were found in studies by De Leon et al. This different

finding may probably be explained by the heterogeneity

inherent in the C-scale; although the scale generally refers to

external conditions or reasons that influence people to seek

treatment, some of the items in this scale have little in

common with each other. This may produce different results

on factor analyses in different subpopulations.

The M-scale and the R-scale were unidimensional.

When the total item pool was subject to factor analysis, the

Table 7

One-month-, 3-month, and 1-year retention by CMR scale scores

Low (%) Moderately low (%) Moderately high (%) High (%) Total (%)/significance

1-month retention

Circumstances 82.5 90.2 97.0 92.3 92.34

Motivation 84.8 91.1 95.1 94.4 92.3

Readiness 83.3 96.2 91.8 96.4 92.3

Total CMR score 85.3 88.9 96.1 92.3 92.3

MR score 85.7 80.0 95.9 100.0 92.34

3-month retention

Circumstances 53.8 85.4 80.0 65.4 74.4

Motivation 66.7 78.6 74.4 75.0 74.4

Readiness 66.7 69.2 75.3 89.3 74.44

Total CMR score 67.6 68.9 79.6 72.0 74.4

MR score 71.4 68.4 75.5 87.5 74.4

1-year retention

Circumstances 15.0 22.0 34.0 29.9 27.14 ( p = .052)

Motivation 12.1 30.4 24.4 41.7 27.14

Readiness 13.3 17.3 30.9 46.4 27.1444

Total CMR score 8.8 24.4 33.0 32.0 27.14

MR score 10.7 24.6 27.6 50.0 27.14

Note: The probability value reflects linearity across the low, moderately low, moderately high, and high groups.4 Mantel–Haenszel, significant at p b .05.





M-scale and the R-scale were mainly part of one single

factor. This finding suggests multicollinearity and inter-

relation between those two scales—a finding that was

confirmed by significant Pearson correlations between the

different subscales. Furthermore, such a scale correlation

can theoretically be expected (motivation reflects inner

reasons to change, which are precursors to actually seekingtreatment [readiness]) (De Leon & Jainchill, 1986; De Leon

et al., 1994) and was supported in earlier studies (De Leon

et al., 1994). Other authors have stressed the importance

of differ entiating between motivation and readiness

as well (Joe, Broome, Rowan-Szal, & Simpson, 2002).

Thus, our results support the presumption that motivation

and readiness are clearly interrelated, although sepa-

rate, constructs.

In spite of previous findings, in confirmatory factor

analyses, only a moderate fit for the tested models could

be found. The fit of the CMR was better than that of the

CMRS (although still moderate) and was lower than that reported in the literature (Melnick et al., 2003). Chi-square

test statistic was significant ( p b .001) for both models

tested. However, this statistic is extremely sensitive to

sam ple size and minor depart ures from multivariate normal-

ity (Bentler & Bonnett, 1980).

4.2. Construct validity

The present study provided impressive results supporting

the construct validity of the CMR(S) (see Tables 3 and 6).

CMR(S) scores were significantly correlated with a number

of EuropASI variables, which are in accordance with

the conceptualization of the CMR scales, as discussedin the literature (De Leon, Melnick, & Hawke, 2000).

For example, intrinsic motivation (problem recognition

and an expressed wish to change) is higher in those who

have more negative experiences associated with their drug

use. These include older clients, those with severe drug

use histories, those with more social and relational prob-

lems, and those who are not legally coerced into treatment.

Women seem to be slightly less motivated (CMR). They

perceive themselves as less suitable for TC treatment—

a finding that is in line with the conclusion of other

studies that women in TCs have specific characteristics and

treatment needs (De Leon & Jainchill, 1991; De Wilde et al.,2004; Ravndal & Vaglum, 1994). It is important to mention

in this context that suitability is not a motivational variable,

but only a treatment perception variable that can possibly

influence dropout. On the other hand, Joe et al. (2002) found

that programs with a higher concentration of women tended

to have a higher average rating of treatment readiness.

Although such interpretations are speculative in treatment

environments where more attention is given to women’s

needs, their perception of the treatment setting’s suitability

and probably their motivation and readiness may increase.

There is no agreement on the correlation between

motivation and social relations/social situation in the

literature. Although Griffith et al. (1998) suggest that

poor family relations indirectly predict higher motiva-

tion, Gerdner and Holmberg (2000) concluded that social

problems (including social relations) in alcoholics were

related to less motivation to treatment. However, those

differences may be caused by the use of divergent opera-

tional definitions of the social relationship variable. Inour study, lifetime relational problems with family and

significant others were correlated to a higher score on

several CMRS scales, but those correlations were not

confirmed for the CMR. On the other hand, the ability to

have closer relationships was clearly related to higher

motivation scores, although not to higher readiness scores.

Finally, younger clients proved to be less motivated and

r eady for treatment— a finding supported by earlier studies

(Melnick et al., 1997).

Impressive results on construct validity highlight the

potential for multidimensional strategies to understand

motivation. As suggested in the literature (e.g., De Leon,Melnick, & Hawke, 2000), studies on the development of

profiles based on combinations of EuropASI variables,

motivation readiness, and suitability variables as predictors

of retention and outcome are needed.

4.3. Predictive validity

The results in Tables 2 and 4 indicate that both the

CMRS and the CMR have good predictive validity with

respect to retention. Continuous measures of retention

revealed strong correlations with all CMR(S) subscales

and summated scores. However, in contrast to earlier studies

by De Leon et al. (1997), De Leon et al. (1994), De Leon,Melnick, Thomas, et al. (2000), and Melnick et al. (1997) in

which the CMRS and the CMR mainly predicted early

retention (30 and 90 days), in our study, predictive validity,

specifically for the CMR, was strongest for long-term

(1 year) retention.

This contrast with American studies may be partly

explained by time of testing, which yielded spuriously low

early dropout rates. The CMR(S) instrument was adminis-

tered about 2 weeks after admission. Therefore, the study

sample did not include those who left treatment within the

first 14 days, a period of char acteristically high dropout

(De Leon & Schwartz, 1984). Consequently, at 1 and3 months, there was little variance in retention: Only 7.7%

of the study sample left treatment within 1 month; after

3 months, the dropout rate was 25.7%. In American research

studies, the CMR is usually administered within 48 h of

admission, yielding higher early dro pout rates. For example,

in a study by De Leon et al. (1997), 24.7% of the clients had

already dropped out of treatment within the first 30 days,

and over 40% had dropped out by 90 days. The higher

dropout rates within the first 90 days yielded significant

CMR predictions for 3-month and 1-year retention. In this

study, the dropout at 1 year (about 63%) was sufficient to

yield better CMR predictions.




The hypothesis that time of testing weakened early

predictions is supported by the data of nonparticipants (i.e.,

those who did not give consent or those without complete

data; n = 58; see also Table 1). Their inclusion into the total

sample inflates early dropout rates to levels comparable to

American studies. For example, of the total sample, 19.1%

had left treatment within 1 month; 37.5% had left treatment within 3 months. Fifty-five percent of the nonparticipant

group had left treatment in the first month. This group had a

mean retention of only 70 days (median = 19 days,

SD = 106 days) and thus stayed a significantly shorter time

in treatment compared to the study sample, t (266) = 17.98,

p b .001. Although complete CMR data were not obtained

on these early dropouts, a reasonable inference is that they

are less motivated for long-term treatment. The possible

effects of this sizeable proportion of early dropouts who are

not included in the study should be considered when

interpreting the results of the study presented here.

Finally, low variance in early dropout can also explainwhy, in case of the CMR, the C-scale is the only predictor for

early (1 month) retention. This scale reflects external

pressures on retention, which are clearly less relevant at

12 months than are intrinsic motivation and readiness factors.

Overall, psychometric findings indicate that the Dutch

version of the CMR(S) yields moderate factorial structure

and good predictive validity. This distinction deserves

additional investigations. Probably, part of the explanation

can be found in the origin of the instrument: The underlying

concepts of the CMRS and the original item pool were

conceived and developed to predict retention in TC treat-

ment. The different subscales were, in fact, not theoretically

deduced. It has been argued in the literature that such aninductive strategy of test construction renders less optimal

psychometric results than a str ategy where a deductive

approach is used (Burisch, 1984). Thus, predictive validity

could be expected, whereas obtaining confirmed factors

may be more difficult. It seems that such confirmed factors

require other items relating to broader concepts, regardless

of their predictive relevance.

A moderate factorial validity suggests that the subscales

might not be unidimensional—a condition needed for taking

summated scores. It is, therefore, recommended to improve

both time-convergent and time-divergent properties of the

scales by identifying and removing weak/conflicting items.Such analysis was performed and resulted in two revised

scales: one (based on the CMRS) containing 15 items and

another (based on the CMR) containing 12 items. The two

revised scales revealed a better fit, CMRS: v 2{SB} = 92.57,

df = 84, p = .24, CFI = 0.989, RMSEA = 0.022; CMR:

v2{SB} = 75.70, df = 51, p = .014, CFI = 0.946, RMSEA =

0.048, whereas the predictive validity of the scales largely

remained. However, as our study sample was relatively

small, which may have limited the potential for obtaining a

strong factor structure, and as there were no possibilities to

cross-validate the revised scales, it was decided not to

present the results of these analyses here. It may be more

appropriate to use the unchanged CMR scales in clinical

practice, until further study and analysis confirm the strength

of the revised scales. Based on the results of exploratory

factor analysis, the CMR is preferable to the CMRS. The

results of this analysis, together with strong predictive

validity, offer sufficient statistical support for the decision to

maintain the original scales. Specifically for TC settings, theS-scale could be added to the CMR instrument, as this

subscale proved to be powerful in predicting retention.

In conclusion, based on previous findings and in spite of

the difficulties we encountered with obtaining confirmed

factors, our conclusion is that the CMR(S) appears to be a

valid instrument for Flemish Dutch-speaking samples.

Additional research is needed to define the broader Euro-

pean applicability of the instrument. This research should be

guided by the limitations of this study. Revised scales with

better factorial validity need to be constructed and cross-

validated. However, a much larger study sample is needed to

make decisions about such scales. A larger study samplewill also meet the problem of low variance encountered at

present. Furthermore, it is important that the instrument is

administered earlier in treatment to counter low variance in

the early dropout group.

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Soyez Et Al 2006 Motivation and Readiness for Therapeutic Community Treatment Psychometric Evaluation of the Dutch Translation of the Circumstances Motivation Readiness and Suitability