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Lower versus higher frequency of sessions
in starting outpatient mental health care
and the risk of a chronic course; a
naturalistic cohort study
Bea Tiemens
1,2*
, Margot Kloos
1
, Jan Spijker
1,2,3
, Theo Ingenhoven
4
, Mirjam Kampman
1,2,5
and
Gert-Jan Hendriks
1,2,5,6
Abstract
Background: An adequate frequency of treatment might be a prerequisite for a favorable outcome. Unfortunately,
there is a diversity of factors that interfere with an adequate frequency of sessions. This occurs especially in the first
phase of treatment, while the first phase seems vital for the rest of treatment. The aim of this naturalistic study was
to explore the impact of the initial frequency of treatment sessions on treatment outcome in a diverse mental
health care population.
Methods: Anonymized data were analyzed from 2,634 patients allocated for anxiety disorders, depressive disorders,
and personality disorders to outpatient treatment programs in a large general mental health care facility. Patients’
treatment outcome was routinely monitored with the Outcome Questionnaire-45 (OQ-45.2), every 12 weeks.
Frequency of sessions was assessed for the first three months of treatment. Using Cox-proportional-hazard models,
we explored the associations between initial frequency and improvement (reliable significant change) and recovery
(reliable and clinically significant change).
Results: Improvement and recovery were associated with symptom severity and functional impairment at start of
treatment, the year the treatment started, number of measurements, the treatment program (anxiety disorders,
depressive disorders, and personality disorders) and receiving group therapy other than psychotherapy.
In all diagnostic groups, both improvement and recovery were associated with a higher frequency of sessions
during the first three months of treatment. For improvement, this effect diminished after three years in treatment;
however, for recovery this association was sustained.
Conclusions: In addition to severity at start of treatment and other predictors of outcome, a low frequency of
initial treatment sessions might lead to a less favorable outcome and a more chronic course of the mental disorder.
This association seems not to be limited to a specific diagnostic group, but was found in a large group of patients with
common mental disorders (depression and anxiety disorders) and patients with a personality disorder. Despite
organizational obstacles, more effort should be made to start treatment quickly by an effective frequency of session.
Keywords: Session frequency, Depression, Anxiety, Personality disorder, Chronicity
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* Correspondence: b.tiemens@propersona.nl
1
Pro Persona Research, Renkum, The Netherlands
2
Behavioural Science Institute, Radboud University, Nijmegen, The
Netherlands
Full list of author information is available at the end of the article
Tiemens et al. BMC Psychiatry (2019) 19:228
https://doi.org/10.1186/s12888-019-2214-4
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Background
In the last decades, remarkable progress has been made
in outpatient mental health care with the introduction of
evidence-based, clinical guidelines for mental disorders.
Nevertheless, in everyday practice, a large number of
patients do not benefit from their treatment [1]. Despite
having received treatment, a considerable proportion of
patients suffer from their symptoms for a very long time
and develop persisting symptoms and impairments, for
instance in functioning in their social roles [2–4]. On
the one hand, it has often been suggested that
differences in treatment outcome between mental health
care practice and randomized controlled trials (RCT) are
attributable to the different populations, but this has not
been empirically confirmed [5]. On the other hand,
reasons for responding or not responding to treatment
are generally sought in patient characteristics. However,
even the most obvious patient characteristics are not un-
equivocally predictive of treatment outcome. For example,
for depression or anxiety sometimes gender is a predictor
of treatment outcome [6], but often not [7,8]. Sometimes
age seems a predictor [7], but often not [6,8]. For both
depression and anxiety, functional impairment or (absence
of) work often is a predictor [7–9], just like having a co-
morbid personality disorder [6,8,10]. Severity of symp-
toms at the start of treatment is supposed to be an
important predictor of treatment outcome as found for
social anxiety [11], depression [9] and adjustment disor-
ders [12], but not in a very large individual patient data
meta-analysis for depression [13]. In the current study, we
addressed another, often neglected, potential reason for
the difference in treatment outcome between mental
health care practice and randomized controlled trials, viz.,
a low dose of the initial treatment.
Dose-effect models of psychotherapy, as described in
the 1980s, showed that most improvement occurs dur-
ing the initial stage of treatment [14]. However, these
models depict an average improvement curve, and do
not distinguish between different patterns of change as
was shown in Barkham et al.’s[7] good-enough-level
model. These authors found many variations in change
patterns, especially in the early phase of treatment. This
finding was confirmed by Rubel et al. [15] who found
that the largest variation in change patterns occurred
during the first six sessions of outpatient psychotherapy.
The largest improvement, as in the dose-effect model,
was found in the first phase of treatment. In later
phases, i.e., sessions 7–12 and 13–18, the majority of pa-
tients showed either a small improvement, or no change
at all. Moreover, the patients whose problems deterio-
rated in the first phase of treatment generally did not
improve substantially in the latter phases. The studies of
Barkham et al. and Rubel et al. included patients who re-
ceived outpatient treatment for a variety of problems,
but these were mainly common mental disorders such as
depression or anxiety disorders. However, similar patterns
of change were found in the treatment of patients with
personality disorders not otherwise specified, regardless of
the treatment modality being used [16]. Improvement was
greatest in the first 12 months of treatment.
The focus on these patterns of change in the first
phase of treatment is relevant because a patient’
s early
change pattern seems to be a predictor of the final out-
come of treatment. In different patient groups and set-
tings, early treatment response has been found to be
strongly related to a positive outcome [17–19]. This pre-
dictive indicator of treatment response might even occur
very soon after the start of treatment, e.g., within the
first month or even after only a few sessions [12,20].
In studies showing the variation in and predictive
power of early change in outpatient treatment, the first
phase of treatment was usually defined in terms of either
the first three-to-six sessions or some other specific
initial time period. According to most evidence-based
protocols, weekly sessions are recommended, e.g., five
sessions is similar to five weeks or eight weeks refers to
eight sessions. However, in routine mental health care,
weekly sessions often are not possible because of waiting
lists and scheduling (planning) difficulties in mental
health care agencies resulting from patients’or thera-
pists’vacations and sick leaves or patients’other prac-
tical difficulties. The importance of the frequency of
sessions might also be underestimated, even though in a
meta-regression analysis Cuijpers et al. [21] confirmed
the importance of the frequency of sessions. They found
among patients being treated for depression a very
strong association between the number of sessions per
week and the treatment effect size. On the other hand,
the total number of sessions and the duration of the
therapy were hardly or not at all associated with
treatment outcome, but increasing the frequency of the
sessions from one per week to two per week increased
the effect size by .45. There is some evidence among pa-
tients with a social anxiety disorder that less intensive
treatment is less effective than therapy delivered in
weekly sessions [22]. Erekson et al. found similar results in
the case of psychotherapy delivered in a naturalistic set-
ting to students with a variety of psychological problems,
mainly adjustment, anxiety, or depression related [23].
Additionally, Omar et al. conducted a systematic review of
studies with patients with borderline personality disorder
[24]. They reported better outcomes in terms of self-harm,
depression, and social functioning when patients received
more than one individual session per week or when pa-
tients received group-based sessions.
In summary, the following evidence served as the back-
drop of the present study: (a) the largest improvement in
symptoms occurs in the first phase of treatment, (b)
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during later phases of treatment there is little additional
change in symptoms, (c) improvement or lack of improve-
ment in the first phase of treatment is associated with final
treatment outcome, and (d) the frequency of sessions is
associated with final outcome. We were interested in
identifying the association between the rapidity with
which therapy starts (in terms of frequency of sessions)
and the speed of recovery. This study was designed to an-
swer two specific questions: If a low frequency of sessions
in the first phase of treatment leads to an unfavorable pat-
tern of change in this phase, is this pattern associated with
both slow recovery in the following phases of treatment
and even with a chronic course of the illness? If there is
an overall association between speed of initial treatment
and the speed of recovery, is this pattern similar among
patients with depression, an anxiety disorder, or a person-
ality disorder? Most of the studies mentioned so far
mainly concerned patients with depression or an anxiety
disorder. The current study also included data from pa-
tients with a personality disorder because of the high co-
morbidity with depression and anxiety and because some
studies have shown that the presence of a personality dis-
order has a negative effect on the outcome of depression
or an anxiety disorder [6,8,10]. In fact the question of the
present study is, can some more general pattern of change
be identified that should be taken into account during
treatment planning?
In the present study, we analyzed data from Routine
Outcome Monitoring (ROM) of patients being treated in
the outpatient treatment programs for a depressive dis-
order, an anxiety disorder, an obsessive-compulsive dis-
orders, or a personality disorder in a large mental health
care institution in the east of the Netherlands. In this
naturalistic study in which we used data from patients
who started treatment during five consecutive years, we
expected to find an association between frequency of
sessions in the first phase of treatment, the speed of
recovery, and the final treatment outcome.
Methods
Design
The aim of the study was to test our hypothesis about the
association between the frequency of sessions in the first
phase of treatment and the speed of recovery and final
outcome. Therefore, we conducted a retrospective cohort
study in a naturalistic setting for three broad diagnostic
groups: outpatients who were allocated to treatment for a
depressive disorder, an anxiety disorder (including obses-
sive-compulsive disorder and post-traumatic stress dis-
order), or a personality disorder.
Patient population and procedure
Data were collected in a large mental health care facility
in the eastern part of the Netherlands. This facility offers
treatment that is reimbursed by basic health care insur-
ance. Requirements for reimbursement were that (a) the
patient had been referred by his or her general practi-
tioner and (b) the patient’s symptoms met the criteria
for a DSM-IV diagnosis (or a DSM-5 diagnosis, which
was implemented in the Netherlands in 2017). During
each patient’s intake, the diagnosis was assessed and
confirmed in a semi-structured clinical interview (Dutch
version of M.I.N.I. 5.0.0 [25] and SCID-II). Patients were,
depending on their primary DSM-IV diagnosis, allo-
cated to one of the specialized treatment programs.
These programs are based on the evidence-based
Dutch multidisciplinary guidelines for mental health
care (https://www.ggzrichtlijnen.nl). In this study, data
were included from outpatients treated for a depres-
sive disorder, an anxiety disorder (including obsessive-
compulsive disorder and post-traumatic stress dis-
order), or a personality disorder. Treatment consisted
of psychotherapy with or without medication. Most
patients received individual therapy, but a small
proportion of the patients received group therapy.
Each of the therapists was a qualified psychotherapist,
psychologist, psychiatrist, or psychiatric nurse.
Data were obtained from the electronic registration
system and from routine outcome monitoring (ROM),
which is a part of usual care. Patients were routinely
asked to fill out the Outcome Questionnaire-45 (OQ-
45.2) at the registration for treatment, at the onset of
treatment, after every three months (12 weeks), and at
the end of treatment. At each assessment point, patients
received an e-mail message from the electronic ROM
system with a link to the questionnaire. Patients for
whom an e-mail address was not available received a let-
ter with a description of the procedure for logging into
the ROM system and filling out OQ-45.2. Patients who
did not have access to a computer or Internet connec-
tion were offered the opportunity to fill out the paper
version of the OQ-45.2 or to use one of the special
ROM computers at the location where they received
their treatment.
Data from patients who started treatment in 2011,
2012, 2013, 2014, or 2015 was included in the study. In
order for the sample to resemble the usual patient
population, no exclusion criteria were used.
Ethical approval for conducting the study was not re-
quired because the measures and assessment procedure
were part of usual care and anonymized data were used.
Information which does not relate to an identified or
identifiable natural person does not fall under the
European General Data Protection Regulation. At the
intake all patients of the mental health care facility
were informed about the organization’s policy on the
use of anonymized data for improvement of the
quality of care through scientific research. Patients
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then had the opportunity to decline having their anon-
ymized data used for scientific research. The data of pa-
tients who had declined were removed from the dataset.
Definition of session-frequency categories
Frequency of sessions was assessed during the first three
months of treatment. Because, patients filled out the
OQ-45 every three months, unless the treatment was
terminated earlier, this was the first possibility to meas-
ure improvement or recovery.
The number of sessions was counted from the start of
the treatment in the respective treatment programs. To
achieve uniformity in the study period in the three pro-
grams, we excluded the intake session or other contacts
before the actual treatment started. When waiting lists
were long, sometimes a patient had contacts with a ther-
apist during the waiting period, but these were not
counted as prescribed treatment contacts. In the three
months from the start of the actual treatment, all face-
to-face treatment contacts (both psychotherapy and
pharmacotherapy contacts) were counted.
In order to be able to distinguish between different
frequency conditions in the Kaplan Meier survival
curves, we divided the number of sessions in the first
three months into categories. We found a large variation
in the number of sessions, which ranged from 1 to 65
(mean = 9.3, sd = 7.7; see Table 1). We constructed five
categories: 1 to 3 sessions (i.e., a maximum of one ses-
sion per month); 4 to 6 sessions (a maximum of two ses-
sions per month); 7 to 9 sessions; 9 to 12 sessions (a
maximum of one each week); and more than 12 sessions
(more than one session per week).
Outcome measures
Treatment outcome was measured with the Outcome
Questionnaire-45 (OQ-45.2) [26][27], which is a self-re-
port questionnaire for general psychopathology and
functioning. The OQ-45.2 is designed for repeated
measurement of clients’progress during therapy in three
domains: symptom distress (SD), interpersonal relation-
ships (IR), and social role (SR). Each of the 45 items is
answered on a five-point Likert scale ranging from never
(a score of 0)toalmost always (score of 4), according to
the patient’s recollection of the preceding week. An
overall total score is calculated by adding the item
scores. The total score can range from 0to 180. Higher
scores reflect more severe distress; a decrease in the
total score indicates improvement. The Dutch transla-
tion of the OQ-45.2 was used; it has satisfactory psycho-
metric properties [27]. The Dutch OQ discriminates
between functional and dysfunctional populations and
the concurrent validity showed proper values for the
total score and the SD subscale, but was moderate for
the IR and SR subscales. The OQ showed high
sensitivity to change on all subscales, ranging from
Cohen’s d = 0.77 to 1.33 (total score). Test-retest reliabil-
ity was in the clinical population 0.79 for the OQ total
score and for the three domains 0.76 (SD) 0.83 (IR), and
0.74 (SR). Internal consistency (Cronbach’s alpha) was
0.93 for the OQ total score and for the three domains
0.91 (SD) 0.80 (IR), and 0.69 (SR) [26]. In the cohort of
the current study (N= 2,634) Cronbach’s alpha’s were
similar; 0.93, 0.91, 0.79 and 0.66.
Data from each patient were included if there were at
least two OQ-45.2 measurements, one at the start of
treatment and one either at one of the 12-week
assessments or the end-of-treatment assessment. If the
measurement at the start of treatment was missing, the
nearest measurement, for instance the measurement
during intake, was used if the time between this
Table 1 Patient characteristics and potential confounders
Characteristic Categories N (%) or
Mean (SD)
N= 2,634
Sex Male 981 (37.2%)
Female 1653 (62.8%)
Age (in years) 36.1 (12.0)
Year treatment started 2011 429 (16.3%)
2012 765 (29.0%)
2013 871 (33.1%)
2014 446 (16.9%)
2015 123 (4.7%)
Diagnostic program Anxiety 1238 (47.0%)
Depression 922 (35.0%)
Personality disorders 474 (18.0%)
Number of sessions in the
first 3 months
Range from 1 to 64 9.3 (7.7)
1–3 421 (16.0%)
4–6 650 (24.7%)
7–9 324 (12.3%)
10–12 701 (26.6%)
> 12 538 (20.4%)
At least 1 pharmacotherapy
contact
774 (29,4%)
Number of available
measurements
4.2 (2.4)
Group treatment No group treatment 1942 (73.7%)
Psychotherapy group 157 (6.0%)
Another kind of
group
535 (20.3%)
OQ-45 total score at start 87.4 (23.4)
GAF score at start 54.9 (8.1)
Improved 1149 (43.6%)
Recovered 649 (24.6%)
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measurement and the start of treatment did not exceed
six weeks.
Positive outcome was defined in two ways, namely im-
provement or recovery. Improvement and recovery were
based on the difference between the OQ-45.2 total score
at the start of treatment and the OQ-45.2 total score at
one of the 12-week assessments or at the end-of-treat-
ment assessment. At the first moment during treatment
when the difference score reached the criteria for im-
provement or recovery, the difference score was consid-
ered a positive outcome. The criteria for improvement
and recovery were based on Jacobson and Truax’s cri-
teria for reliable and clinically significant change [28].
To determine which change on a questionnaire score is
an actual change and not just random fluctuation, Jacob-
son and Truax have proposed the Reliable Change Index
(RCI). The RCI is calculated as the difference between
the OQ-45.2 total score at the start of treatment and the
OQ-45.2 total score at one of the 12-week assessments
or at the end-of-treatment assessment, divided by the
standard error of measurement. If the RCI is greater
than 1.96, the change is considered statistically signifi-
cant and the patient changes reliably. Furthermore,
Jacobson and Truax defined clinical significant change
as ‘the extent to which therapy moves someone outside
the range of the dysfunctional population or within the
range of the functional population.’This requires a cut-
off value for a specific instrument. The definition of re-
covery therefore, has more meaning and is somewhat
‘harder’, than the definition of improvement. Improve-
ment could therefore be better described as ‘experien-
cing improvement’. However, for the readability in this
article we only use improvement.
Improvement or reliable change on the OQ-45.2 was
defined as a decrease by 14 points or more in the total
score. Recovery was defined both as a decrease by 14
points or more in the total score and by having a total
score less than the cut-off score for differentiation be-
tween the clinical and normal score ranges. The cut-off
score for the Dutch version of the OQ-45.2 is ≤55 [27].
Because the measures were administered every 12
weeks, the speed of improvement or recovery was mea-
sured in an approximate way. It could appear in the ana-
lyses only every 12 weeks, or when treatment was
terminated. This, however, was similar for all three of
the treatment programs and for the different frequency
categories.
Potential confounders
Based on earlier mentioned potential predictors, ad-
justed analyses included the following variables: sex [6],
age [7], functional impairment [7–9], severity of symp-
toms (OQ.45–2) at start of treatment [10][9][11] and
group therapy [24]. Because all of these variables could
have affected treatment outcome, they were included as
covariates in the Cox proportional hazards model. Year
of start of treatment, treatment program, and group
therapy were also included because during the study
period there were changes in the treatment protocols for
the different diagnostic groups at the mental health care
facility, and these changes could have affected treatment
outcome. Group treatment was divided into a psycho-
therapy group or another kind of group, such as a sup-
portive group or creative and psychomotor therapy. The
number of available measurements was included because
if a patient had many assessments, this might have in-
creased the opportunity to detect improvement and re-
covery. Global Assessment of Functioning (GAF) at start
of treatment was used as measure for functional impair-
ment. The GAF scale was included in DSM-IV and rated
for each patient at intake. Scores range from 100 (ex-
tremely high functioning) to 1 (severely impaired). Fi-
nally, medication could have influenced the number of
sessions (pharmacotherapy contacts) as well as treat-
ment outcome. Therefore, a variable ‘medication con-
tact, yes/no’, based on the presence of pharmacotherapy
contacts was also included as covariate.
Analyses
We did not take patients’outcome at the end of treat-
ment into account, because it would not have distin-
guished between fast and slow responders to treatment.
Instead, we used Kaplan-Meier survival analyses to iden-
tify the proportion of patients who had recovered at
each month of treatment and Cox regression analyses to
test the association between the number of sessions dur-
ing the first phase of treatment and the potential
confounders.
Data were analyzed using SPSS Version 20. To esti-
mate the mean time to improvement and recovery of
symptoms for the various session-frequency categories,
Kaplan-Meier survival analyses were performed. Models
were evaluated using the Chi-square of the log-rank
(Mantel-Cox) test. Cox proportional-hazards regression
models were used to estimate the hazard ratio for im-
provement of symptoms during treatment and recovery,
according to the frequency of sessions during the first
months of treatment. When patients did not improve or
recover during treatment, their data were censored after
the last assessment with the OQ45. We employed the
enter method to include all of the covariates in one step
in the Cox-proportional-hazard models. The comparison
of models was based on the Wald statistic.
Results
Patients
Data from 2,634 patients were available for analysis. The
characteristics of these patients are shown in Table 1.
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62.8% (n= 1,653) of the sample were females, and their
mean age was 36 years. 47.0% (n= 1,238) of the patients
were offered treatment for an anxiety disorder; 35.0%
(n= 922), treatment for a depressive disorder; and 18.0%
(n= 474), treatment for a personality disorder (mainly
personality disorder NAO, 65.1%, and cluster C, 30.6%).
29.4% of the patients had at least one pharmacotherapy
contact. The mean number of treatment sessions in the
first three months was 9.3 (sd = 7.7) 26.3% of the sample
received group therapy in addition to individual therapy.
The mean number of available measurements with the
OQ-45.2 for each patient was 4.2. The mean total score
on the OQ-45.2 at the start of the treatment was 87.4
(sd = 23.4) (high/very high), and the mean GAF score
was 54.9 (sd = 8.1) (moderate symptoms or problems in
functioning). At the final assessment, 24.6% of the
patients had recovered, and 43.6% showed a clinically
significant improvement in symptoms, social role, and
interpersonal relationships. In these 43.6% the recovered
patients were included.
Kaplan-Meier survival analyses
The Kaplan-Meier survival analyses showed differences
in survival distributions for improvement (log-rank Chi-
square = 28.2, p< 0.001) and recovery (log-rank Chi-
square = 28.8, p< 0.001) according to session frequency
in the first three months. Because of the possibility of
differences between the frequency categories on baseline
measurements, Cox’s proportional-hazards regression
was used to control for potentially confounding factors.
Cox’s proportional-hazards regression analysis
Table 2shows the results of the Cox’s proportional-haz-
ards regression analysis. Compared to the group with 1–
3 sessions in the first three months, the hazard ratios for
improvement varied from 1.28 (95% CI = 1.08–1.53) for
the group with 4 to 6 sessions to 1.62 (95% CI = 1.35–
1.95) for the group with more than 12 sessions in the
first three months of treatment. Hazard ratios for recov-
ery ranged from 1.46 (95% CI = 1.11–1.92) to 2.04(95%
CI = 1.53–2.72) for the groups with an increasing fre-
quency of sessions during the first three months of
treatment.
Other independent variables that were associated with
improvement and recovery were the year in which the
treatment was started, the number of available measure-
ments, having received group therapy in groups other
than psychotherapy groups, and OQ-45.2 and GAF base-
line scores. Mean baseline severity (OQ-45.2) differed
between the frequency groups, but there was no
interaction effect on outcome. Having pharmacotherapy
contacts was not associated with improvement or
recovery. The kind of diagnosis-specific treatment was
associated only with improvement and not with
recovery. The chance of improvement in the treatment
programs was lower for patients with depression or a
personality disorder than in the treatment program for
patients with an anxiety disorder, obsessive-compulsive
disorder, or post-traumatic stress disorder. Nevertheless,
adjustments for these variables did not change the direc-
tion of the hazard ratios for session frequency. Session
frequency in the first three months of treatment
remained a significant predictor of treatment outcome,
as shown by the adjusted hazard ratios in Table 2.
Figures 1and 2show the survival functions based on
the adjusted hazard function of the Cox proportional
hazard model. The results were independent of the diag-
nostic group, similar patterns were found in the survival
curves for the individual three treatment programs.
The interactions between frequency groups and diag-
nostic groups were neither significant for improve-
ment (p= 0.61) nor for recovery (p=0.82).
Because a longer episode increases the risk of
chronicity [29], the risk after 12 months treatment
can be interpreted as an indication for treatment
resistance or chronicity. In the different categories of
session frequency, we fitted stratified Cox models to
the strata function for each category. The estimated
baseline hazard functions for each stratum allowed us
to compare the hazard proportions for improvement
and recovery of patients after 12 months of treatment
(see Table 3). From the lowest to the highest fre-
quency category, the proportion of improved patients
increased from 50.3 to 75.2% and the proportion of
recovered patients increased from 26.6 to 45.9%.
Discussion
The aim of this study was to assess whether there is an
association between frequency of sessions in the first
three months of treatment and speed of recovery, and
whether the association is the same for patients with de-
pression, an anxiety disorder, or a personality disorder.
Two outcome measures were used: (a) improvement,
which was defined as a reliable, significant change, and
(b) recovery, which was defined as a reliable, clinically
significant change. Both outcome measures were associ-
ated with frequency of treatment sessions in the first
three months of treatment.
Patients improved or recovered faster if their treat-
ment was provided in a higher frequency of sessions
during the first three months as compared to a lower
frequency of treatment sessions. After one year, 25%
more patients had improved in the highest frequency
group than in the lowest frequency group, and 20%
more patients had recovered in the former group than
in the latter. After three years, in the lowest frequency
group, as compared to the higher frequency groups, a
substantially larger proportion of the patients had not
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recovered and were still in treatment. These results pro-
vide an initial indication that a low frequency of sessions
at the beginning of treatment might lead to a more
chronic course of the disorder in a substantial propor-
tion of patients. Moreover, this pattern was similar in
the three different diagnostic groups.
Although the association between session frequency
and outcome was the same in the three diagnostic
groups, the chance of improvement was lower in the
programs for depression and personality disorder than
in the treatment program for patients with an anxiety
disorder, obsessive-compulsive disorder, or post-trau-
matic stress disorder. This is in line with other studies
that show larger effect sizes in patients with anxiety dis-
orders than in patients with depression for disorder spe-
cific interventions, but not for transdiagnostic
psychological treatments [30], and in line with studies
that show that having a comorbid personality disorder
has a worse effect on treatment outcome [6,8,10].
As expected severity at start of treatment as measured
with the OQ-45.2 and the GAF scores were related with
improvement and recovery. In accordance with other
studies [7–9] less functional impairment as measured
with the GAF, increased the chance of improvement and
recovery, but this was different for the OQ-45.2. The
higher the OQ-45.2 score at start the higher the chance
of improvement, but the lower the chance of recovery.
As Hiller et al. [31] stated, the disadvantage of the RCI
(the definition of improvement) is that it is independent
of the initial score. Patients with higher initial scores in
general tend to achieve larger improvements than
patients with lower scores and therefore reach more easy
a reliable change. The clinical significant change
(recovery) does not have this disadvantage, because for
recovery the score has to decrease until the cutoff
between clinical and normal scores.
Some treatment variables were associated with im-
provement and recovery. The chance of improvement
Table 2 Adjusted hazards ratios for recovery and Improvement (Cox regression analysis)
1
Characteristic Categories Improvement Recovery
Number of sessions in the first 3 months 1–3 (ref)
2
4–6 1.28 (1.08–1.53) 1.46 (1.11–1.92)
7–9 1.30 (1.06–1.59) 1.32 (0.96–1.83)
10–12 1.52 (1.28–1.81) 1.72 (1.31–2.26)
> 12 1.62 (1.35–1.95) 2.04 (1.53–2.72)
Sex Male (ref)
Female 1.01 (0.90–1.12) 1.05 (0.89–1.23)
Age in years 1.00 (1.00–1.01) 1.00 (0.99–1.00)
Year treatment started 2011 (ref)
2012 1.49 (1.26–1.76) 1.41 (1.11–1.80)
2013 1.55 (1.31–1.83) 1.54 (1.20–1.97)
2014 1.99 (1.65–2.41) 1.89 (1.42–2.52)
2015 2.63 (1.98–3.49) 2.39 (1.54–3.70)
Diagnostic program Anxiety (ref)
Depression 0.85 (0.76–0.96) 0.99 (0.82–1.19)
Personality disorders 0.72 (0.61–0.85) 0.79 (0.62–1.02)
Pharmacotherapy contact No (ref)
Yes 0.97 (0.86–1.09) 0.88 (0.73–1.05)
Number of available measurements 0.86 (0.84–0.88) 0.89 (0.86–0.92)
Group therapy No group therapy (ref)
Psychotherapy group 0.85 (0.68–1.06) 0.94 (0.67–1.31)
Another kind of group 0.80 (0.70–0.92) 0.78 (0.63–0.96)
OQ-45 total score at start 1.01 (1.01–1.01) 0.99 (0.99–0.99)
GAF score at start 1.01 (1.01–1.02) 1.02 (1.01–1.03)
1
Data are presented as hazards ratios with corresponding 95% confidence intervals, adjusted for age, sex, year treatment started, diagnostic program, presence of
medication contacts, total number of OQ45 measurements, group therapy, OQ45 and GAF scores at the start of treatment
2
Ref = reference category
Tiemens et al. BMC Psychiatry (2019) 19:228 Page 7 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Fig. 1 Survival function for improvement according to session frequency categories
Fig. 2 Survival function for recovery according to the session frequency categories
Tiemens et al. BMC Psychiatry (2019) 19:228 Page 8 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
and recovery increased with each following year in
which the treatment started. This probably reflects the
process of continuous improvement of the treatment
programs during these years. An alternative explanation
might be that in the more recent years patients with a
more chronic course of their disorder were not yet in-
cluded. Participating in group treatment was another
variable associated with outcome. In this study group
treatments were divided into group psychotherapy and
other kind of groups, such as a supportive group, art
therapy or psychomotor therapy. Omar et al. found bet-
ter outcomes among patients with borderline personality
disorder who received more than one individual session
per week or when patients received group-based sessions
[23]. In the present study patients receiving care in the
other groups (not group psychotherapy) had a lower
chance of improvement and recovery. These kind of
supportive, creative and psychomotor therapy groups are
mainly provided as add-on therapy to patients with se-
vere mental illness, which may explain this less favorable
course. The number of available measurements was
included in the analyses because if a patient had more
assessments, this might have increased the opportunity
to detect improvement and recovery. However, the op-
posite was found. The more measurements the lower
the chance of improvement and recovery. More
measurements also relate to a longer treatment course
and therefore to a later moment of improvement and
recovery.
The results in the current study corroborate earlier
findings for depressive disorders [21], anxiety disorders
[22], and borderline personality disorders [24]. Other
naturalistic studies with heterogeneous samples showed
similar results. However, these studies were conducted
mainly with student populations [23,32]. Most studies
focused on frequency of sessions during the entire
course of therapy rather than the first three months.
Only Kraft et al.’s study [33] investigated the impact of
session frequency in the first three months, as in our
study. They found that the distribution of sessions
during the first three months was similar for the three
modalities of psychotherapy (psychodynamic, cognitive
behavioral, and psychoanalytic) that they assessed, and it
was not related to baseline severity. Although patients
with fewer sessions in the first three months of psycho-
analytic therapy improved somewhat more than patients
with more sessions, patients who had fewer weeks with
psychotherapy in the early phase of treatment subse-
quently improved at a slower rate. Patients showed bet-
ter outcomes when their treatment started continuously,
that is few weeks without psychotherapy, but at a rather
slow pace. This finding was not seen in the other two
forms of psychotherapy, where frequency or weeks
without psychotherapy did not predict subsequent
improvement.
There are several explanations for the benefit of
starting treatment at a higher dose. Bruijniks et al., for
instance, hypothesize two mechanisms of change [34].
First, a faster start of treatment may be associated with a
faster development of the therapeutic alliance, which, in
turn, is positively associated with treatment outcome
[35]. The second mechanism refers to the learning
process. Higher session frequency may increase the
learning process, so that patients are better able to recall
the content of the sessions and apply it in their everyday
lives. In addition, Erekson et al. hypothesize, based on
behavioral theory, that continuous reinforcement is
most effective for learning new behavior, and longer
gaps between treatment sessions lead to a discontinu-
ity in learning [23]. The research underlying Kluger
and DeNisi’s feedback intervention theory confirms
that frequent messages augment the effect of feedback
on learning [36].
The practical implications of the present study are im-
portant: to prevent a less favorable or a chronic course it
is crucial to start the treatment not long after admission
and to keep the frequency of the treatment sessions
high. Therefore, it is first necessary to instruct both pa-
tients and therapists about the importance of a treat-
ment intensity of at least one session per week during
the first three months. Second, also managers should be
instructed. As decreasing treatment intensity and session
frequency is often used by managers to increase the
caseload per therapist and to solve waiting lists, the
current study seems to indicate that the opposite is true.
Doing so will increase treatment time and a more
chronic course in patients and will in fact lead to
both increasing treatment time and increasing waiting
lists (it takes more time to reach improvement).
Both the strengths and limitations of this study are re-
lated to its naturalistic design in a real-life mental health
care facility. One strength is that this naturalistic nature
of the design and setting increased the ecological validity
and generalizability of the results. A second strength is
that we were able to utilize data from highly prevalent
diagnostic categories in large numbers. This allowed us
to explore the association between session frequency
and outcome and the association between session
Table 3 Hazard proportion improvement and recovery after
12 months, stratified by frequency level
Session frequency in the first 3 months Improvement Recovery
1–3 50.3% 26.6%
4–6 60.3% 34.5%
7–9 63.2% 34.1%
9–12 69.7% 38.9%
> 12 75.2% 45.9%
Tiemens et al. BMC Psychiatry (2019) 19:228 Page 9 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
frequency and risk of a chronic course in patients suffer-
ing from depression, an anxiety disorder, or a personality
disorder.
The major limitation of this study was the lack of
experimental controls in the design. The patients, for
example, were not randomly assigned to the different
frequency groups. Although we were able to control for
potential confounders, such as patient characteristics,
which might have been associated with session fre-
quency and treatment outcome, we could not control
for assessment procedures, nor therapists’selective allo-
cation of patients to treatments. Moreover, it was impos-
sible to control for all of the potentially confounding
patient characteristics, such as duration of symptoms at
the start of treatment. If the treatment of patients with
more chronic problems had been systematically started
at a lower frequency, chronicity might have been a
stronger predictor of a chronic course than a low fre-
quency of sessions at the onset of treatment. Further-
more, a low frequency of treatment sessions is often
caused by practical or organizational problems, such as,
a vacation or sick leave of a patient or therapist, waiting
lists, and organizational difficulties. Because it was im-
possible to control for these variables, we do not know
whether they were randomly distributed or more
common in certain programs or treatment teams.
We also were unable to control for patients not
attending their scheduled appointments (no-show) as a
cause for low frequency of treatment sessions. Defife
and colleagues [37] identified four groups of reasons for
missed appointments: either medical or psychiatric
clinical problems (28%); practical difficulties, such as
work conflicts, transportation problems, and family is-
sues (26%); motivational issues (18%); and adverse treat-
ment responses, such as difficulties with the therapist or
a negative response to the diagnosis or the recom-
mended treatment plan (13%). Additionally, Murphy and
colleagues [38] found that concerns about self-disclosure
were related to nonattendance of the first appointment.
A positive attitude toward therapy predicted increased
rates of attendance among less depressed patients, but
not among patients with severe depression.
Another limitation of the study is that assessments oc-
curred only every 12 weeks. Because patients often com-
pleted the OQ-45.2 somewhat earlier or later than the
scheduled time, the survival curves do not show events
exactly every 12 weeks. This lack of uniformity might
have affected the Kaplan-Meier curves. Nevertheless, we
have no reason to believe that this effect differed among
the five categories of session frequency. Because the
number of assessments differed among patients and
might have been associated with the occurrence of an
event, we controlled for the number of assessments in
the Cox regression analysis. Doing so, however, did not
change the association between session frequency in the
first three months and the speed of improvement or
recovery.
Conclusions
The mechanisms discussed above can account for the
finding that a slow start of treatment is associated with
slow improvement in the first phase of treatment. How-
ever, the results of the present study suggest that a slow
start of treatment also affects the course of treatment in
the long term and might increase the risk of treatment
resistance, a persistent course of symptoms and poor
prognosis. The clinical implications of this finding seem
obvious. A quick start of treatment and adequate fre-
quency of sessions in the initial phase of treatment for pa-
tients with a depressive disorder, an anxiety disorders, or a
personality disorder may not only decrease patients’symp-
toms and suffering faster, but it may also reduce the length
of treatment and health care costs and can help to resolve
waiting lists. Studies with more rigorous research designs
are needed to confirm these hypotheses.
Abbreviations
CI: Confidence Interval; DSM-IV: Diagnostic and Statistical Manual of Mental
Disorders 4th edition; GAF: Global assessment of functioning;
IR: Interpersonal relations; M.I.N.I. 5.0.0: Mini-International Neuropsychiatric
Interview version 5.0.0; OQ-45.2: Outcome Questionnaire-45; RCI: Reliable
change index; RCT: Randomized controlled trial; ref.: Reference category;
ROM: Routine outcome monitoring; SCID-II: Structured Clinical Interview for
DSM-IV Axis II Personality Disorders; sd: Standard deviation; SD: Symptom
distress; SR: Social role
Acknowledgements
Not applicable.
Authors’contributions
All authors were involved in the conception, research questions and design
of the study. MK and BT constructed the dataset and performed the
analyses. All authors interpreted and discussed the results. BT and MK wrote
the first draft of the manuscript. All authors read, revised and approved the
first manuscript and the revisions and gave final approval of the version to
be published.
Funding
Not applicable.
Availability of data and materials
The dataset used and/or analysed during the current study is available from
the corresponding author on reasonable request.
Ethics approval and consent to participate
Data from the electronic registration systems were used anonymously.
Information which does not relate to an identified or identifiable natural
person does not fall under the European General Data Protection Regulation
[39]. Patients were not submitted to any specific action or intervention for
the study, measures and assessment procedure were part of usual care.
Therefore, according to Dutch Law on Medical Ethics [40], no specific
informed consent or a review of a Medical Ethics Committee was required.
Consent for publication
Not applicable, anonymized data were use.
Competing interests
The authors declare that they have no competing interests.
Tiemens et al. BMC Psychiatry (2019) 19:228 Page 10 of 12
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Author details
1
Pro Persona Research, Renkum, The Netherlands.
2
Behavioural Science
Institute, Radboud University, Nijmegen, The Netherlands.
3
Depression
Expertise Centre, Pro Persona Mental Health Care, Nijmegen, The
Netherlands.
4
Personality disorder Expert Centre, Arkin Mental Health Care,
Amsterdam, The Netherlands.
5
Overwaal Centre of Expertise for Anxiety
Disorders, OCD and PTSD, Pro Persona Mental Health Care, Nijmegen, The
Netherlands.
6
Department of Psychiatry, Radboud University Medical Centre,
Nijmegen, The Netherlands.
Received: 16 December 2018 Accepted: 16 July 2019
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