Treatment Outcome in Patients Receiving Assertive Community
H. E. Kortrijk•C. L. Mulder•B. J. Roosenschoon•
Received: 10 February 2009/Accepted: 2 October 2009/Published online: 22 October 2009
? The Author(s) 2009. This article is published with open access at Springerlink.com
ill patients treated in assertive community treatment (ACT)
teams, we investigated how treatment outcome was asso-
ciated with demographic factors, clinical factors, and
motivation for treatment. To determine psychosocial out-
come, patients were routinely assessed using the Health of
the Nation Outcome Scales (HoNOS). Trends over time
were analyzed using a mixed model with repeated mea-
sures. The HoNOS total score was modeled as a function of
treatment duration and patient-dependent covariates. Data
comprised 637 assessments of 139 patients; mean duration
of follow-up was 27.4 months (SD = 5.4). Substance
abuse, higher age, problems with motivation, and lower
educational level were associated with higher HoNOS total
scores (i.e., worse outcome). To improve treatment out-
come, we recommend better implementation of ACT, and
also the implementation of additional programs targeting
subgroups which seem to benefit less from ACT.
In an observational study of severely mentally
Treatment outcome ? HoNOS
Assertive community treatment ? SMI ?
Assertive community treatment (ACT) is an intensive
treatment model in which multidisciplinary teams provide
community care for non-motivated patients with a severe
mental illness (Bond et al. 2001). If correctly implemented,
ACT is regarded as an evidence-based intervention
(McHugo et al. 1999). Its primary objectives are to reduce
hospital admissions, keep patients in contact with services,
and improve psychosocial outcome (Marshall and Lock-
Several studies, most of them American, have provided
evidence for the effectiveness of ACT (Burns and Santos
1995), whose main effects were to reduce admissions and
to keep patients in contact with the mental health services.
ACT’s effects on symptoms, housing stability, and sub-
jective quality of life were less clear (Marshall and Lock-
wood 1998). However, in European studies that compared
it with standard community care, ACT had no effects on
psychiatric hospital use, symptoms, or quality of life (Kent
and Burns 2005; Sytema et al. 2007).
Despite the lack of European evidence for its beneficial
clinical effects, ACT has been widely implemented in
Great-Britain and other European countries (Killaspy et al.
2006), including the Netherlands. For this reason, with
regard to ACT’s effect on symptom-reduction, functioning
and quality of life, it should be established which patients
may benefit from ACT and which do not.
Several studies which defined treatment outcome as
level of symptoms, level of functioning, employment and
quality of life have identified the predictive factors
H. E. Kortrijk (&) ? C. L. Mulder ? B. J. Roosenschoon
Parnassia Bavo Group, BavoEuropoort, Westersingel 94,
3015 LC Rotterdam, The Netherlands
C. L. Mulder
Department of Psychiatry, Erasmus MC, University Medical
Center Rotterdam, Rotterdam, The Netherlands
C. L. Mulder
Municipal Health Center Rotterdam Rijnmond, Rotterdam,
University Medical Center Groningen, Department
of Psychiatry, University of Groningen, Groningen,
Community Ment Health J (2010) 46:330–336
associated with poor response to various types of treatment
(including ACT). Briefly, these studies identified nine such
factors: (1) male gender (Grossman et al. 2006); (2) age
(Roberts et al. 2000); (3) low educational level (Lauronen
et al. 2007); (4) concomitant substance abuse (Dixon 1999;
Drake et al. 1993; Batel 2000; Greenfield et al. 2006); (5)
early manifestations of symptoms (Remschmidt et al.
1994); (6) negative symptoms (Wieselgren et al. 1996); (7)
lack of awareness of symptoms (Rossi et al. 2000); (8) poor
treatment compliance (Gerlach 2002); and (9) duration of
untreated psychosis (Singh 2007).
However, to our knowledge, no studies have specifically
investigated the influence of these predictive factors on
psychosocial outcome in the context of ACT. Using an
observational study design in patients receiving ACT over
a two to 3-year period, we therefore examined the influence
of three of these predictors on treatment outcome, which
was defined as level of symptoms and social functioning
over time (Health of the Nation Outcome Scales (HoNOS)
total score). We used the following predictors: substance
abuse, motivation for treatment, and demographic factors
(age, ethnicity, level of education, and gender).
The study involved patients from six ACT teams in the city
of Rotterdam, the Netherlands. There were three criteria for
treatment by an ACT team: (1) age 18 or older, (2) diag-
nosis with a severe mental illness (usually a psychotic or
bipolar disorder, with or without a comorbid addiction
disorder); and (3) lack of motivation for treatment at the
start of ACT, which made assertive outreach necessary.
Data were collected as part of a routine outcome-mon-
itoring (ROM) procedure, and were used in clinical prac-
tice to discuss treatment outcome with the patient and the
clinician. The collection of routine outcome monitoring
data, which was done by independent raters with a Master’s
degree in psychology, was approved by the Dutch Com-
mittee for the Protection of Personal Data. All data were
To assess the fidelity of the six treatment programs to ACT,
we used the Dartmouth Assertive Community Treatment
Scale (DACTS), which assesses fidelity on the basis of 28
items using anchored five-point scales (Teague et al. 1998;
Salyers et al. 2003; Bond and Salyers 2004). Psychometric
properties such as internal consistency, inter-rater reli-
ability and sensitivity to change over time have been found
to be acceptable (Winter and Calsyn 2000; Bond and Sal-
yers 2004). A mean score of all items between 0 and 2.9
means that a treatment team has failed to implement ACT;
a score between 3.0 and 4.1 means that ACT has been
implemented to a moderate degree, and a score between 4.2
and 5 means that it has been fully implemented (Teague
et al. 1998; Salyers et al. 2003).
Data were collected over the period from January 2003 to
August 2008. At the start of the treatment and then at 6-
month intervals, patients were assessed using the Health of
Nation Outcome Scales to determine psychosocial outcome
(HoNOS; Wing et al. 1998; Mulder et al. 2004). To this we
added one additional observer-rated item to assess moti-
vation for treatment.
Health of the Nation Outcome Scales was originally
developed as a standardized assessment tool for routine use
by the mental-health services. It consists of 12 observer-
rated scales, each using five points from 0 (no problem) to
4 (severe/very severe), and thus yielding a total score from
0 to 48. The psychometric properties of the English and
Dutch HoNOS total scores have been found to be accept-
able (Wing et al. 1998; Mulder et al. 2004). HoNOS covers
the following domains: (1) overactive, aggressive, disrup-
tive or agitated behaviour, (2) non-accidental self-harm, (3)
problem drinking and drug-taking, (4) cognitive problems,
(5) physical illness and disability, (6) hallucinations and
delusions, (7) depressed mood, (8) other psychological
symptoms, (9) relationship problems, (10) problems with
activities of daily living, (11) problems with living condi-
tions, and (12) problems with occupation and activities.
The scale for assessing motivation for treatment was
adapted from the Severity of Psychiatric Illness scale
(Lyons 1998; Mulder et al. 2005), and was scored in five
categories in the same way as the HoNOS scale: (0) strong
motivation: significant degree of motivation for treatment;
(1) clear motivation: there may be some hesitation, but this
does not lead to problems with motivation; (2) some
motivation: there is motivation for treatment but also
ambivalence or mild passive resistance; (3) poor motiva-
tion: the individual appears not to be motivated and there is
passive resistance; and (4) no motivation/resistance: the
individual actively resists treatment. On the basis of an
interview with the patient and the clinician, the motivation
for treatment scale was scored by independent raters who
were not involved in the patients’ treatment.
To assess substance abuse, patients were routinely
assessed on the basis of two items—alcohol use and drug
Community Ment Health J (2010) 46:330–336331
use—taken from the Camberwell Assessment of Need
(CAN). The ratings were based on the interviewee’s per-
spective (as opposed to the patient’s). The CAN severity
ratings are 0 (no need), 1 (met need) and 2 (unmet need)
(Wennstro ¨m 2008).
We collected socio-demographic and diagnostic data on
gender, age, ethnicity (according to the definition of the
Statistics Netherlands: i.e., parents’ countries of birth),
level of education, and DSM-IV-TR diagnoses as made by
the psychiatrists of the ACT team.
SPSS version 15.0 was used for all analyses. Treatment
outcome was defined as the HoNOS total score. Linear
Mixed Models with repeated measures were used to assess
the association of the predictors and psychosocial func-
tioning over time.
Factors of primary interest included time (treatment
duration) and psychosocial functioning (HoNOS total
score). To capture a curvilinear decline which would
assume a more rapid change in the early months, the model
also included a square-root transformation of time.
Predictors All covariates were selected on the basis of a
theoretically or empirically documented association with
treatment outcome. Demographic information included
education, age and ethnicity; other covariates were prob-
lems with motivation and substance abuse at baseline.
Model For the initial specification of the model, we
included linear time, square-root time, HoNOS total score,
demographics (age, level of education and ethnicity),
motivation at baseline, and substance abuse at baseline.
Fixed factors To obtain the most parsimonious model,
fixed effects were dropped in subsequent iterations and
eliminated, since each effect was either not significantly
related to the HoNOS total score, or did not appreciably
alter outcome (likelihood ratio test; Fitzmaurice et al.
2004). Patient’s identification number was used as a ran-
dom factor (random intercept deviation). Random effects
were modeled if they significantly contributed to the model
(likelihood ratio test).
Final model The fixed effects in the final model were
intercept, time and a square-root transformation of time
(which fitted the data better than a linear time slope alone);
motivation at baseline; substance abuse at baseline; age;
and level of education. Repeated measures were modeled
on the assumption of a first-order autoregressive covariance
structure (based on REML) (Fitzmaurice et al. 2004).
Lastly, in an effort to replicate and supplement earlier
findings (Grossman et al. 2006), we performed a variation
of the primary analyses for men and women separately.
Because the sample included only a small number of
women, we included all covariates from the model (as
defined above), not just covariates that were statistically
significant. Non-significant results for the smaller group
were examined to ascertain whether their size (b) and
direction were similar to those of the larger group.
Although non-significant results might indicate that the
sample size was not great enough to allow comparison
between the groups, any differences in their magnitude or
direction indicates that the results are not explained solely
by sample size.
To test whether the differences in associations were sig-
the full model as an interaction term with all covariates
(substance abuse, age, level of education and motivation,
linear time, and square-root transformation of time). In this
model, a significant interaction would indicate dissimilari-
ties in the associations for men and women between the
covariates and the HoNOS total score over time.
The data included 637 assessments from a total of 139
patients. On average, assessments were 6.9 months apart
(SD = 1.4). The mean treatment duration of follow-up was
27.4 months (SD = 5.4). The mean age was 38.3 years
(SD = 9.5). Diagnosis was schizophrenia or other psy-
chosis for 72.3% of the patients. The patients’ character-
istics are described in Table 1.
The mean of the total DACTS scores of the six ACT teams
was 3.5 (range: 3.4–3.6), meaning that ACT had been
implemented with moderate success. The lowest scores
were awarded to various categories pertaining to substance
abuse: substance-abuse specialist on staff (m = 2.8), indi-
vidualized substance-abuse treatment (m = 2.8), dual-dis-
order treatment groups (m = 1.2) and dual disorders (dd)
model (m = 3).
Determinants of Treatment Outcome for the Whole
In the final model, the following predictors were signifi-
cantly associated with the HoNOS total score: substance
abuse at baseline (CAN score 2: serious problem on items
12 (alcohol) or 13 (drugs) versus 0: no problem or 1:
intervention); motivation for treatment at baseline; educa-
tion level (no education or elementary school versus lower
high school and over); and age (\30 years versus
332Community Ment Health J (2010) 46:330–336
Analysis of changes during follow-up in the HoNOS
total score revealed a significant improvement over time
(Table 2: linear time: F = 7.841, P = .005, square-root
time: F = 14.534, P\.000). Of all predictors, substance
abuse at baseline was most strongly associated with the
HoNOS total score: the main effect was (b = 3.47,
F = 24.414, P\.001). Because the HoNOS incorporates
problematic alcohol use and drug taking it is evident that
the HoNOS total score will positively correlate with sub-
stance abuse. Therefore we did 2 analyses, (1) on the
relation between the HoNOS total score (including
problematic alcohol use and drug taking (above analysis)
and substance abuse and (2) on the relation between the
HoNOS total score (excluding problematic alcohol use and
drug taking) and substance abuse. The second analysis
shows that, substance abuse still remains a predictive factor
(b = 1.60, F = 5.874, P = .017).
The results also showed that age was independently
associated with the HoNOS total score (b = 2.26, F =
7.341, P = .007), meaning that older patients had higher
overall HoNOS total scores. Problems with motivation at
baseline were also associated with higher overall HoNOS
total scores (b = .733, F = 6.460, P = .012). Lastly, anal-
yses revealed that the level of education was significantly
associatedwithHoNOStotalscore(b = -1,916,F = 5.028,
P = .027), as patients without education or elementary
school had higher overall HoNOS total scores than patients
whose education level was lower high school or above.
Gender and Outcome
Table 2 also shows the men and women’s respective levels
of psychosocial functioning. The results showed differ-
ences in the significance and direction of the associations.
In men, poorer treatment outcome was predicted by sub-
stance abuse, age (30 or older), and level of education (no
education, or elementary school only). In women, the
pattern of associations was different, in that only substance
abuse and problems with motivation for treatment were
strongly and significantly associated. In addition, there was
also a non-significant association with age, in the opposite
direction than that of male patients. Because the associa-
tion with education was also non-significant in women, its
significance was different than it was with men.
The two covariates—time and square-root transforma-
tions of time—were also different for men and women,
men showing a significant decline over time, and women
showing a non-significant decline.
Table 1 Patient characteristics
Male 115 82.7
Level of education
No education/elementary31 22.3
Secondary school 5640.3
Upper high school and over4230.2
Ethnic Dutch and western immigrants 6546.7
Non-western immigrants (parents) 7151.1
Other psychosis15 10.6
Previous voluntary and involuntary admissions
HoNOS total score (baseline)
Not all items available/missingb
Motivation for treatment (baseline)
aSubstance abuse as a primary or secondary diagnosis
bThese patients were included in the analyses
Table 2 Prediction of HoNOS total scores among men and women
b (total) SE
b (women) SE
Intercept26.57** 3.69 29.40** 4.07 18.98*8.99
Linear time 3.27** 1.21 3.98** 1.32-.112.82
-14.56** 3.91 -17.23** 4.27 -1.519.20
Age2.26** .832.55** .89 -2.532.85
-1.92* .85-2.21* .99-.981 1.42
.73*.29 .65.34 1.80** .53
* P\.05; ** P\.01
Community Ment Health J (2010) 46:330–336 333
To test whether the associations of the covariates with
treatment outcome differed between men and women,
gender was added as an interaction term. Our results
showed significant differences between men and women for
substance abuse (F = 23.145, df = 110.874, P\.001),
age (F = 10.299, df = 225,753, P = .002), motivation for
treatment (F = 10.682, df = 121,094, P = .001) and time
(sqrt) (F = 5.997, df = 367.394, P = .015). Level of
education (F = 1.864, df = 143.689, P = .174) and time
(linear) (F = 1.508, df = 387.370, P = .220) revealed no
significant interaction with gender.
The fidelity score of the DACTS model showed that the six
teams had implemented ACT moderately successfully, but
that treatment for dual disorder had been implemented
improved significantly over time, the gains seem to have
been concentrated mainly in the first months of treatment;
later on, the level of functioning appeared to stabilize.
Despite this early improvement, two factors indicate a need
for long-term ACT: patients’ level of functioning over time,
and the risk that their lack of motivation for treatment will
cause their situation to worsen. It should also be stated that
the significant improvement in psychosocial functioning
was restricted to men, although the non-significant results
for women may have been a product of the sample size.
Our analysis also showed that the level of psychosocial
functioning was significantly hampered by substance
abuse, age over 30, low level of education (either no
education, or elementary school only), and problems with
motivation for treatment. In that these patient characteris-
tics were associated with significantly more problematic
functioning over time, our results confirmed earlier find-
ings on treatment outcome in other patients with a severe
mental illness (Dixon 1999; Drake et al. 1993; Batel 2000;
Greenfield et al. 2006; Lauronen et al. 2007; Gerlach 2002;
Roberts et al. 2000). Our finding that older patients had
higher HoNOS total scores may have been due to the fact
that the duration of mental illness (Jenner 2003) or of
untreated psychosis was longer in these patients, each a
factor that has been associated with worse prognosis (Singh
Our study further demonstrated that the pattern with
which these variables were associated with psychosocial
outcome was different between men and women. The
differences between the sexes’ levels of psychosocial
functioning—women tending to have fewer psychosocial
problems over time, but also improving less—may have
been due to a floor effect.
However, the fact that substance abuse had more
adverse consequences for women than for men may have
been because women seemed more prone to perilous
activities, such as turning to prostitution as a means to earn
the money they needed to support their substance use. This
led to problems regarding physical health and daily living
conditions, and is in line with previous research by Rach-
Beisel et al. (1999), who suggested that substance abuse
among women is associated with increased risks for
physical health problems and sexually transmitted diseases.
The third difference between men and women, problems
with motivation for treatment, also resulted in a higher risk
(i.e., stronger association) for psychosocial problems in
women than in men, which may be related to more dis-
ruptive behavior, and which therefore leads women to have
more problems with motivation for treatment.
For men, risk factors were being aged 30 or older, low
level of education, and substance abuse. This is in agree-
ment with findings that older patients had poorer global
functioning (Roberts et al. 2000), and may indicate that
these patients are more at risk of neglecting their personal
care than women are. These findings also supplement those
of Gur et al. (1996) by showing more specifically how the
clinical features of patients with a severe mental illness are
moderated by aging and gender.
The association with low level of education may indi-
cate that such patients have more difficulty managing or
coping with problems in their lives. Neisser et al. (1996)
showed that because educational level was moderately
highly correlated with intelligence, it may also reflect a
patient’s ability to make use of any services on offer, and to
foresee the consequences of their behavior. Because a low
level of education may also lead to greater isolation from
the labour market (Wolbers 2000), it may also complicate
Bhugra et al. (1997) showed that non-western ethnicity
was associated with poorer treatment outcome, a finding
we were unable to replicate, due possibly to differences in
outcome assessment: whereas Bhugra et al. used employ-
ment status, we defined outcome more broadly in terms of
psychosocial functioning as measured by the HoNOS. Our
study therefore suggests that, in terms of psychosocial
functioning over time, non-western immigrants do not
differ from other patients.
Limitations of the Study
We should acknowledge two limitations of the present
study. The first concerns the design. Because this was a
naturalistic follow-up study that used routine outcome-
monitoring data, we had no information on other factors
that may have co-determined the outcomes, such as nega-
tive symptoms, lack of awareness of symptoms, and
334 Community Ment Health J (2010) 46:330–336
duration of untreated psychosis. Neither does the design
make it possible to draw any causal inferences, although
Shrier et al. (2007) suggests that, like randomized con-
trolled trials, an observational study design can also con-
tribute to evidence-based research.
The second limitation concerns the small number of
women in the analyses, which was a product of the sub-
stantial overrepresentation of male patients in the ACT
teams. We therefore checked non-significant results for the
female patients to see if they were similar in magnitude (b)
and direction to those in the larger group. Although non-
significant results may indicate that the sample size was not
enough for purposes of comparing the groups, the differ-
ences in magnitude or direction we found here indicate that
the results were not explained solely by sample size.
Since model fidelity has been shown to be associated with
better outcome (McHugo et al. 1999; McGrew et al. 1994;
Latimer 1999; Bond et al. 2000), our results suggest that
our ACT teams should improve their fidelity with the ACT
model. We also conclude that special attention should be
paid to patients who seem to benefit less from ACT.
Our results emphasize the importance of implementing
the ACT-model fully, including substance abuse treatment
programs. This can be done by implementing IDDT (Drake
et al. 2001), or other substance abuse programs. McHugo
et al. (1999) showed that faithfully implemented dual-dis-
order programs achieved better treatment outcomes. These
recommendations agreed with our DACTS findings, which
also support a better implementation of ACT, especially
with regard to the dual-disorder elements that achieved low
DACTS scores in this study.
Because our results also indicate that treatment outcome
was significantly hampered by low education (including
mental retardation), we propose the implementation of
programs based on behavioral therapy for mentally retar-
ded patients. One example of such a program is token
economy (Comaty et al. 2001), which has also shown to
increase adaptive behavior in schizophrenic patients
(Dickerson et al. 2005).
To address problems of motivation for treatment, we
recommend the structural implementation of Motivational
Interviewing (Martino et al. 2000; Gerlach 2002). The
central purpose of motivational interviewing is to examine
and resolve ambivalence in treatment goals. Research by
Bien et al. (1993) and Brown and Miller (1993) has shown
that patients who were given motivational interviewing had
participated more fully in treatment, and appeared to be
more motivated than those who had not received this
intervention. If motivational interviewing is implemented,
motivationally challenged patients may benefit more from
assertive community treatment.
To meet the special needs of patients in different age
categories, we also argue for the development of innovative
programs such as the differentiation of ACT teams
according to patients’ age (i.e., young, adult and elderly).
Because clinicians working in ACT teams serving a sub-
population such as the elderly, may have special skills for
dealing with specific needs, such as somatic and cognitive
problems. Therefore these teams may be better equipped to
deal with specific problems related to age. Finally, because
several important factors such as problems with recovery
and substance abuse have shown to be different for men
and women (Mangrum et al. 2006; Grossman et al. 2006),
it may be necessary to adopt a gender-specific approach.
This will mean that separate treatment programs are
adapted to the specific needs of men and women.
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