Predictors of mental distress among substance abusers receiving inpatient treatment.

Abstract

Mental distress measured by the HSCL-10 is used as an indicator of psychiatric disorders in population studies, where a higher level of mental distress has been shown to be related to demographic factors such as living conditions and level of education. The first aim of the study was to explore whether mental distress could be a valuable concept in substance use treatment. The second aim of the study was to explore to what degree mental distress among substance users at admission to treatment could be explained by the same demographic factors as in population studies, or whether treatment differences or differences in substance use would be better predictors of mental distress in this population.
Patients (N = 185) who received inpatient substance use treatment in five different settings in Northern Norway participated in the study. HSCL-10 was used as a measure for mental distress at admission to treatment. The self-report measures AUDIT, DUDIT and DUDIT-E were used for measuring substance use and readiness for treatment. The patients' clinicians reported demographic and treatment factors. A three-block hierarchical multiple regression analysis was conducted to determine potential predictors of mental distress. Block 1 included demographic variables, Block 2 included treatment variables, and Block 3 substance use variables.
Patients generally reported a high level of mental distress at admission to treatment, and 83% reported mental distress higher than the established cut-off level. Being female, having previously received psychiatric treatment, having a higher score on DUDIT and AUDIT, and using a larger number of substances all predicted a higher level of mental distress. The model explained 32% of the variance in mental distress.
Mental distress measured by the HSCL-10 can be a valuable concept in substance use treatment. The HSCL-10 can be useful in screening for patients who are in need of further assessment for psychiatric disorders. Female gender, previous psychiatric treatment, and higher use of substances all predicted a higher level of mental distress. The study underlines the importance of assessing the mental health of patients in substance use treatment.

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Open Access
RESEARCH
Predictors of mental distress among substance
abusers receiving inpatient treatment
© 2010 Hoxmark et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.
Research
Ellen Hoxmark1,2, Mary Nivison1 and Rolf Wynn*2,3
Abstract
Background: Mental distress measured by the HSCL-10 is used as an indicator of psychiatric disorders in population
studies, where a higher level of mental distress has been shown to be related to demographic factors such as living
conditions and level of education. The first aim of the study was to explore whether mental distress could be a valuable
concept in substance use treatment. The second aim of the study was to explore to what degree mental distress
among substance users at admission to treatment could be explained by the same demographic factors as in
population studies, or whether treatment differences or differences in substance use would be better predictors of
mental distress in this population.
Methods: Patients (N = 185) who received inpatient substance use treatment in five different settings in Northern
Norway participated in the study. HSCL-10 was used as a measure for mental distress at admission to treatment. The
self-report measures AUDIT, DUDIT and DUDIT-E were used for measuring substance use and readiness for treatment.
The patients' clinicians reported demographic and treatment factors. A three-block hierarchical multiple regression
analysis was conducted to determine potential predictors of mental distress. Block 1 included demographic variables,
Block 2 included treatment variables, and Block 3 substance use variables.
Results: Patients generally reported a high level of mental distress at admission to treatment, and 83% reported
mental distress higher than the established cut-off level. Being female, having previously received psychiatric
treatment, having a higher score on DUDIT and AUDIT, and using a larger number of substances all predicted a higher
level of mental distress. The model explained 32% of the variance in mental distress.
Conclusions: Mental distress measured by the HSCL-10 can be a valuable concept in substance use treatment. The
HSCL-10 can be useful in screening for patients who are in need of further assessment for psychiatric disorders. Female
gender, previous psychiatric treatment, and higher use of substances all predicted a higher level of mental distress. The
study underlines the importance of assessing the mental health of patients in substance use treatment.
Introduction
Clinical and epidemiological studies indicate high rates of
co-occurring psychiatric disorders among people with
substance use disorders (SUD) [1-6]. Psychiatric comor-
bidity is the co-occurrence of one or more psychiatric
disorders during a period of time [7]. Comorbidity
between anxiety disorders, depressive disorders, and
SUD is particularly common [8]. In population studies,
co-occurring psychiatric disorders are seen in 30-40% of
people with alcohol disorder and 40-50% of those abusing
other substances [1-3,9-11]. The incidence of psychiatric
disorders among individuals with SUD in treatment is
even higher [6]. In a prior study, Landheim et al. [12]
studied a treatment-seeking sample of patients with SUD
in two counties in the southern part of Norway, and
found a prevalence of any Axis 1 disorder of 85%; thereof
60% for affective disorders and 78% for anxiety disorders.
Psychiatric disorders have in several studies been found
to influence the long-term course of SUD [13-15], and
treatment of these disorders affects outcomes of sub-
stance use treatment [16]. In a follow-up six years after
treatment, Landheim et al. [17] found that major depres-
sion together with early onset of SUD were independent
predictors of relapse. In another recent longitudinal study
of patients with heroin dependence, major depression
was the diagnosis most consistently associated with poor
outcomes after three years [18].
* Correspondence: rolf.wynn@gmail.com
2 Institute of Clinical Medicine, University of Tromsø, 9037 Tromsø, Norway
Full list of author information is available at the end of the article

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Given the high rates of co-occurring disorders, and the
impact these disorders have on treatment, it is crucial to
detect who is in need of further assessment and treat-
ment for psychiatric disorders as soon as possible after
admission to substance use treatment. Patients entering
substance use treatment should routinely be screened for
comorbidity [19].
The screening of psychiatric disorders among sub-
stance abusers is nevertheless problematic because of the
symptom overlap of substance-induced symptoms and
symptoms of depression and anxiety. The relationship
between anxiety symptoms, affective symptoms and sub-
stance-induced symptoms is complex. Substances can be
used as self-medication and thereby conceal symptoms of
anxiety and depression, or symptoms can be a result of
substance abuse [20]. An example of the latter is that
symptoms of anxiety and depression among alcohol
dependent patients at admission to treatment often have
been shown to spontaneously recede during treatment
[21,22].
Mental distress can be used as a measure for detecting
individuals in the general population who are in need of
further examination or psychiatric treatment. The Hop-
kins Symptoms Checklist-10 (HSCL-10) [23] is a screen-
ing instrument for detecting mental distress, commonly
used in population studies. The HSCL-10 is based on the
original HSCL-90 version, using two out of originally
nine dimensions [24,25]. In a Norwegian population
study, the established cut-off for HSCL-10 yielded a prev-
alence rate of 11.4% [23]. The literature suggests that 50 -
60% of the "cases" identified by instruments like HSCL-10
most likely will qualify for one or more psychiatric diag-
noses following a clinical assessment [26].
The level of mental distress has been found to be higher
among women, among people with little education, and
among the unmarried and those living alone [27-31]. A
higher level of mental distress has also been shown to be
related to economic problems [32], poor social support
[33] and belonging to an ethnic minority [34]. Typically,
those in lower socio-economic groups have worse health
and higher mortality than those in higher socio-eco-
nomic groups [35]. SUD and other psychiatric disorders
are generally associated with a variety of psychosocial
risk factors [36-38]. The National Comorbidity Survey
(1990 - 1992) demonstrated that not having an occupa-
tion was the demographic factor with the strongest asso-
ciation with SUD [39].
Aims of the study
In this study, we measured mental distress one week prior
to admission to treatment. The first goal of the study was
to detect the level of mental distress among substance
abusers seeking inpatient treatment, and thereby examine
whether mental distress at admission to treatment could
be a valuable concept in substance use treatment. The
second goal of this study was to explore what impact
demographic variables, treatment variables, and sub-
stance use variables had on mental distress.
Methods
Treatment settings and participants
Treatment for SUD in Northern Norway is given primar-
ily in inpatient settings, e.g. only 2% of the referrals to
substance use treatment in the area during the first half of
2005 were referrals to out-patient clinics [40]. The pres-
ent study was conducted in five public inpatient units for
treatment of SUD in Northern Norway. These consti-
tuted the inpatient treatment offered for patients with
SUD within the largest hospital in Northern Norway. The
units serviced primarily patients in the Districts of Nord-
land, Troms, and Finnmark (500 000 inhabitants), and
included approximately 60% of the available treatment
beds for SUD patients in the whole region. One of the
units was a therapeutic community, one a short-term/
acute (up to six weeks) unit, one unit specialized in the
assessment and treatment of dual diagnosis, and two
were long-term (six months) units. All units treated men
and women and patients with all types of SUD. In the
units, treatment was given in both group and individual
settings. Patients were treated with a combination of net-
work-based approaches, psychological therapies and
pharmacological treatment, although the different ele-
ments were given different emphasis in the various units.
The number and proportion of participants from each
unit is shown in Table 1. A large proportion of the
patients had been treated in other units previously. Each
unit was small, and it was necessary to pool data from dif-
ferent units to achieve a substantial number of subjects,
and to cover a wider range of patients.
Patients were recruited on entry to the units. In the
study period, 330 patients were admitted to the units.
Patients who were considered not able to give an
informed consent (N = 18) or whose hospital stay was too
short to be included (N = 31) were not asked to partici-
pate. In all 201 patients agreed to participate and signed
an informed consent form. Subjects (N = 16) with three
or more missing items in HSCL-10 were excluded from
the analyses. The final sample thus consisted of 185
respondents. This gave a participation rate of 56%. The
majority of the sample were men (71%) and the average
age in the sample was 38 (SD = 11.2; range 18 - 63 years).
97% of the sample was born in Norway, 96% of their
mothers and fathers were also born in Norway. Our sam-
ple, compared with the whole sample of SUD patients
seeking treatment in Northern Norway in the same
period of time, did not differ significantly with regard to
gender, age, education, occupation, living condition, mar-
ital status, current medical treatment, previous substance

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use or psychiatric treatment, or admittance under legal
circumstances.
Measures
Dependent variable: mental distress
Symptoms of mental distress occurring the last week
before admission were measured using the HSCL-10 [23].
The original Hopkins Symptom Check List (HSCL-90)
was a self-rating questionnaire that assessed psychopa-
thology and mental distress, and consisted of 90 items
that formed nine symptom dimensions or scales [24,25].
The HSCL-90-R has proven to be an adequate screening
instrument for comorbid psychopathology among
patients with SUD [41-45]. The HSCL-10 is a shortened
version of the HSCL-90-R consisting of two (anxiety and
depression) of the original nine symptom dimensions
[23]. The HSCL-10 has shown good psychometric prop-
erties, has performed almost as well as the full HSCL-90
version, and has shown good qualities in detecting mental
distress in the general public [23,46].
The HSCL-10 consists of 10 items on a four-point scale,
ranging from 1 (not at all) to 4 (extremely). The partici-
pants reported on the following questions: Have you in
the course of the past week been troubled by feeling: sud-
denly scared for no reason, fearful, faint or dizzy, tense or
keyed up, guilty, difficulties falling asleep, blue, worth-
lessness, that everything is an effort, hopeless about the
future. The average item score (General Severity Index)
was calculated by dividing the total score with the num-
ber of items answered, thus the score ranged between
1.00 and 4.00. When one or two items were missing we
divided the individual total sum with the number of the
items the individual had answered (i.e. eight or nine). An
average score of 1.85 or above has shown to be a valid
predictor of mental distress in the normal population
[23]. The scale was used as a continuous variable in our
study.
Predictors
Use of substances was measured by the Alcohol Use Dis-
orders Identification Test (AUDIT) [47] and the Drug Use
Disorders Identification Test (DUDIT) [48]. Both are
screening instruments for identifying persons with SUD.
Both instruments are standardized and based on selected
criteria for substance abuse, harmful use and depen-
dency, according to the ICD-10 and DSM-IV diagnostic
systems. Treatment motivation and current use of spe-
cific substances were measured by the self-report Drug
Use Disorders Identification Test - Extended (DUDIT-E)
[49]. A Motivational Index was formed from three factors
in DUDIT-E (positive and negative aspects relating to
substance use, and treatment readiness). Use of specific
substances was dichotomized between using the sub-
stance twice a week or more often, and using the sub-
stance less often [50]. The number of substances was
measured by adding up the number of drugs used twice a
month or more often (as reported on DUDIT-E) in addi-
tion to alcohol used twice a week or more often (as
reported on AUDIT).
Demographic information and the patients' treatment
histories were assessed using the Norwegian National
Client Assessment Form [51]. Variables in this form
include age, sex, occupation, housing, and previous treat-
ment. This form is routinely completed for all patients
admitted to substance use treatment in Norway.
Procedures
From September 2007 to December 2008, all patients
being treated in the units, and who were considered able
to give an informed consent, were given written and oral
information about the study, and invited to participate in
the study by one of the research collaborators who
worked in the units. The participating patients completed
a questionnaire as soon after admittance as possible,
depending on withdrawal symptoms or other symptoms.
Table 1: Participation in the different units
UnitAdmitted in the
period of inclusion
Participating in study The proportion of
participators from
each unit (%)
Mean age (SD)
Dual diagnosis ward43 13 3029.15 (7.7)
Therapeutic
community
37 267027.50 (6.60)
Short term unit 1225848 37.72 (11.78)
Long term unit 153 4279 41.26 (9.27)
Long term unit 275 466141.83 (10.24)
Total 330185 5637.51 (11.16)

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The questionnaire asked about conditions prior to admit-
tance. It included questions about substances used
(AUDIT, DUDIT, DUDIT-E), mental distress (HSCL-10)
and motivation for treatment (DUDIT-E). As compensa-
tion for filling out the questionnaire, the participants
could choose between one cinema ticket or two lottery
tickets. Through the informed consent procedure, the
participants granted us access to the clinicians' assess-
ments and other routinely collected data. This included
information on demographic variables and previous
treatment.
Analyses
All analyses were conducted using the Statistical Package
for Social Sciences 16.0 (SPSS 16.0). Reliability was
assessed with Cronbach alpha [52]. Descriptive statistics
were used to examine the frequency of substance use
[53]. Correlational analyses and t-tests were used to iden-
tify substance abuse and demographical factors associ-
ated with mental distress. A hierarchical multiple
regression analysis was conducted with the score on
HSCL-10 as the dependent variable, and demographic
variables, treatment variables and substance abuse vari-
ables as predictors. Regression diagnostics were per-
formed to test for collinearity, outliers and the overall fit
of the models.
The study was reviewed and approved by the Regional
Committee for Medical Research Ethics (REK Nord) and
by the Norwegian Social Science Data Services (NSD).
Results
Mental distress and substance abuse
A high proportion of the participants scored above the
cut-off point for HSCL-10 (N = 154, 83%). The mean
score was 2.58 points (SD = 0.75). The internal consis-
tency of the HSCL-10 was high in the sample (Cronbach's
alpha = 0.90). Level of mental distress measured by the
HSCL-10 did not differ significantly between the five par-
ticipating units (Table 2).
Alcohol (61%) and hypnotics (60%) were the most com-
mon substances, followed by cannabis (46%), analgesics
(46%), amphetamine (35%) and opiates (33%). Only a
small proportion of the sample reported using cocaine
(7%), hallucinogens (4%), GHB and other substances (3%)
or solvents (0.5%). A high proportion of the sample con-
sisted of poly-substance abusers, with 74% using two or
more substances and 58% using three or more substances
twice a week or more often. There were significant differ-
ences in the severity of substance abuse between the par-
ticipating units. Patients in the therapeutic community
reported a higher score on DUDIT than the rest of the
sample, a higher number of substances used, and a lower
score on AUDIT. The patients in the short term unit
reported a lower score on AUDIT and a higher score on
DUDIT than the rest of the sample whereas patients in
the dual diagnosis ward reported a higher score on
DUDIT than the rest of the sample. The patients in the
two long term units reported a higher score on AUDIT, a
lower score on DUDIT and a lower number of substances
used than the rest of the sample.
Predictors of mental distress
As a preliminary step in the statistical analysis, we per-
formed univariate correlational analyses and t-tests
between individual HSCL-10 scale scores and three types
of variables: demographic variables (age, gender, marital
status, living conditions, employment, and education),
treatment variables (motivational index, previous sub-
stance use and psychiatric treatment, prescribed medica-
tion for psychiatric problems last four weeks before
admission, and legal circumstances at admission) and
severity of substance abuse (score on AUDIT, DUDIT
and number of substances used) (Table 3). We found sig-
nificant correlations and t-test differences between the
HSCL-10 scores and previous treatment for psychiatric
problems, prescribed medication for psychiatric prob-
lems last four weeks before admission, score on DUDIT,
number of substances used, gender, and employment. An
interaction effect between previous treatment for psychi-
atric problems and prescribed medication for psychiatric
problems last four weeks was resolved by including an
interaction variable in the subsequent regression analysis.
We then performed a hierarchical multiple regression
analysis with the demographic variables and the signifi-
cant treatment variables together with variables concern-
ing severity of substance abuse as predictors and HSCL-
10 as the dependent variable (Table 4). The demographic
variables age, sex, never married, living conditions,
employment and education were entered into the first
block and accounted for 8% of the variance in HSCL-10
scores [F(6,178) = 2.63]. The second block included pre-
vious treatment for psychiatric problems, prescribed
medication for psychiatric problems the past four weeks
and interaction between the two variables, and explained
an additional 9% of the variance [F(9,175) = 4.08]. Block
three added measures of severity of substance abuse
(DUDIT, AUDIT and number of substances) and
explained an additional 15% of the variance [F(12,172) =
6.72].
Summary statistics for the complete model are pre-
sented in Table 5. The final regression model accounted
for a significant 32% of the explained variance in HSCL-
scores [F(12,172) = 12.26]. Previous psychiatric treatment
(p = 0.037), score on AUDIT (p = 0.007) and DUDIT (p =
0.05) and number of substances used (p = 0.013) were sig-
nificantly related to the score on HSCL-10 in the com-
plete model. Gender (p = 0.014) was the only
demographic variable that was a significant predictor in

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this model. Women, patients who had a previous experi-
ence of psychiatric treatment, patients with a higher
score on AUDIT and DUDIT, and those using a higher
number of substances, reported higher HSCL-10 scores.
Discussion
Symptoms of mental distress were highly prevalent
among patients with SUD being admitted to inpatient
treatment. We found that more than 80% of the patients
had a level of mental distress above the established cut-
off level of 1.85 on the HSCL-10. The level in the normal
population has been estimated to 11.4% [23]. The level of
mental distress in our study corresponds to the preva-
lence of Axis 1 disorders found by Landheim et al. [12],
but is higher than is found in substance abusers in popu-
lation studies [2,9,11]. Previous studies have estimated
that around 50 - 60% of the "cases" identified by screening
instruments such as HSCL-10 actually qualify for a psy-
chiatric diagnosis. While many of the patients with a
score on mental distress above cut-off probably were in
need of some type of psychiatric treatment, it is likely that
this cut-off level also captures patients who are not in
need of specialized psychiatric services [26]. The high
rates of mental distress found in this study could reflect
the fact that starting treatment is a stressful experience.
Further studies should be performed in order to examine
which cut-off level on the HSCL-10 that is optimal for
clinical use for SUD inpatients.
Being female was the only demographic factor that sig-
nificantly predicted the HSCL-10 scores. Surveys in the
general public generally report a higher level of mental
distress for women than for men [23,27,29,30]. Our study
had similar results: women reported a higher degree of
mental distress according to the HSCL-10 compared to
men. It remains an open question as to whether women
actually experienced more distress than men, or whether
men underreported their distress. The indicators of social
situation used in this study are the same as have been
shown to influence the level of mental distress in the gen-
eral population: marital status, education, living condi-
tions, and occupation [23,28]. In the preliminary
univariate analyses only occupation was significant,
which means that patients gainfully employed or under
education reported a significantly lower level of mental
distress compared to the unemployed. In the regression
analysis, this factor no longer predicted mental distress.
Typically, those in lower socio-economic groups have
worse health and higher mortality than those in higher
socio-economic groups [35]. The reason that socio-eco-
nomic status does not predict the level of mental distress
in this sample may be that substance abusers in treatment
generally have a lower socio-economic status than the
general population [37,38].
We were interested in how previous and current treat-
ment for psychiatric problems would influence the level
of mental distress at admission to treatment, as these fac-
tors were believed to be associated with a particularly
vulnerable sub-group of patients (i.e. patients that had
demonstrated a need for some form of psychiatric treat-
ment). However, after controlling for an interaction effect
between previous and current treatment for psychiatric
problems, we found that only previous psychiatric treat-
ment predicted a higher level of mental distress, whereas
current psychiatric treatment did not. Although we do
not have a clear cut explanation for this finding, it may be
that patients who are currently in psychiatric treatment
in part are protected against especially high levels of
mental distress, while having undergone such treatment
in the past does not offer the same protection - which is
why they have an increased level of mental distress at
admission.
The most powerful predictor for mental distress at
admission to treatment was the participants' level of sub-
stance abuse. Level of alcohol use as measured by the
Table 2: Scores on HSCL-10, AUDIT, DUDIT and DUDIT-E according to unit
UnitMean score
HSCL-10 (SD)
Mean score
AUDIT (SD)
Mean score
DUDIT (SD)
Mean score
DUDIT-E (SD)
Mean number of
substances (SD)
Dual diagnosis
ward
2.92 (0.71)17.31 (9.72) 29.23* (10.16)6.86 (5.88) 2.92 (1.61)
Therapeutic
community
2.75 (0.42)12.12* (9.73) 35.04** (6.76)7.07 (4.51)4.12** (1.99)
Short term unit2.71 (0.69)12.72** (12.60) 24.82* (14.20)4.22 (3.23)2.93 (1.57)
Long term unit 1 2.36 (0.86)23.17** (8.98)12.08** (13.93)3.93 (4.79)2.07* (1.76)
Long term unit 2 2.42 (0.78)21.58* (10.98) 14.33** (15.34)5.15 (8.82)2.09** (1.93)
Total 2.58 (0.75) 17.51* (11.77)21.14 (15.57)5.13 (5.73)2.69 (1.88)
*p < 0.05; **p < 0.01.

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AUDIT, the level of drug use as measured by the DUDIT
and the number of substances used all predicted a higher
level of mental distress. A question one may ask is to what
degree the level of mental distress results from the use of
substances or from stress related to admission to treat-
ment, and whether these symptoms could be reduced
during substance abuse treatment. Previous studies have
indicated that psychiatric symptoms can be substantially
reduced during substance abuse treatment [21,22]. Even
though the predictors connected to severity of substance
use were the most powerful predictors in our study, these
are the predictors that most likely will loose their power
during treatment.
The high prevalence of mental distress that was found
in this study among substance abusers in treatment
emphasizes that it is necessary to screen, assess, and treat
psychiatric disorders in substance use treatment facilities.
Expertise in assessing and treating these disorders should
therefore be available in substance use treatment.
Strengths and limitations
This is one of few studies in Norway that survey mental
distress among substance abusers in treatment, and the
first in the northern part of Norway. This part of Norway
is a remote area with a particularly high incidence of
amphetamine use. Our study covered the range of treat-
Table 3: HSCL-scores in relation to demographic characteristics, current substance use, patterns of substance use, and
treatment history for 185 substance abusers (univariate analyses)
N = 185 M or nRange, % or SDtrSig
Demographic characteristics
Mean age (years) 38(18 - 63)-.13 0.069
Male 131(71%) 3.08
0.002
Gainfully employed40(22%) 1.97
0.050
Single, never married156(84%) 0.380.707
Living alone 121(65%) 1.700.083
Post-school qualification 99(54%)0.0040.997
Severity and pattern of substance use
AUDIT17.51 (11.77)0.060.426
DUDIT21.14 (15.57)0.36
0.001
Number of substances used 2.7(1.9)0.36
0.001
Treatment history
Undergoing medical treatment for psychiatric
problems
92(50%)3.57
0.001
Previous treatment for psychiatric problems 126 (68%)3.82
0.001
Previous substance abuse treatment154(83%)1.10 0.273
Admitted under legal circumstances4(2%) 1.25 0.213
Motivation for treatment (DUDIT-E) (N = 146) 5.13 (5.73)0.130.122
Table 4: Determinants of HSCL-10--scores: contributions of each variable block to changes in R2
Determinant
R2
ΔR2
Fdf
ΔF
Sig ΔF
Block 1: Demographics0.0810.0812.6286,1782.628
0.018
Block 2: Previous psychiatric
treatment
0.1740.0926.5079,1754.083
0.001
Block 3: Substance abuse severity0.3190.146 12.25812,1726.718
0.001
A hierarchical multiple regression strategy was used in which blocks of variables were added to the regression equation sequentially. R2, F
and df refer to the overall regression equation after each block has been entered into the model; ΔR2, ΔF, and significance ΔF describe the
contributions of each individual block.

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ment facilities that is most commonly offered substance
abusers in the area. Northern Norway is a relatively well
defined catchment area where most of the treatment is
given in inpatient settings.
A limitation in the study was the relatively low partici-
pation rate. Another limitation was that we assessed
mental distress the last week prior to admittance to treat-
ment. It is possible that the level of mental distress before
entering treatment was influenced by stress connected to
treatment admission, as well as influenced by substances
used or withdrawal symptoms.
Conclusions
Substance abusers seeking inpatient treatment reported
on average a high level of mental distress as measured by
the HSCL-10. An increased severity in the use of sub-
stances, a higher number of substances used, having pre-
viously received treatment for psychiatric disorders, and
being female all predicted a higher level of mental dis-
tress. The findings in this study suggest that mental dis-
tress measured by the HSCL-10 could be a valuable
concept in substance use treatment by identifying
patients who are in need of further examination and
treatment for their psychiatric disorders. The study
underscores the importance of screening, assessing, and
treating psychiatric disorders in SUD patients, and also
the importance of having the appropriate expertise avail-
able in substance use treatment facilities.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
EH participated in designing the study, collecting the data, analysing and inter-
preting the data, and in drafting and revising the manuscript. MN participated
in designing the study, interpreting the data, and drafting and revising the
manuscript. RW participated in designing the study, analysing and interpreting
the data, and in drafting and revising the manuscript. All authors read and
approved the final manuscript.
Acknowledgements
We thank the participating patients and staff. The study was supported finan-
cially by the Northern Norway Regional Health Authority (Helse Nord RHF).
Author Details
1Department of Substance Use and Specialized Psychiatric Services, University
Hospital of Northern Norway, 9291 Tromsø, Norway, 2Institute of Clinical
Medicine, University of Tromsø, 9037 Tromsø, Norway and 3Psychiatric
Research Centre of Northern Norway, University Hospital of Northern Norway,
9291 Tromsø, Norway
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This article is available from: http://www.substanceabusepolicy.com/content/5/1/15© 2010 Hoxmark et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Substance Abuse Treatment, Prevention, and Policy 2010, 5:15
Table 5: Final stage in the hierarchical multiple regression of mental distress measured by HSCL-10
DeterminantBSE Standardized B
p
Gender-0.2700.109 -0.165
0.014
Age0.0030.0050.050 0.525
Gainfully employed-0.057 0.118-0.0320.628
Never married-0.1930.139-0.0940.167
Living alone -0.0130.110 -0.0080.908
Post school
qualifications
-0.0810.101 -0.0550.424
Current medical
treatment
0.1100.1900.0740.565
Previous psychiatric
treatment
0.2910.1390.182
0.037
AUDIT Sum0.0120.0050.196
0.007
DUDIT Sum0.013 0.0050.283
0.005
Number of substances
used
0.0860.0340.217
0.013

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doi: 10.1186/1747-597X-5-15
Cite this article as: Hoxmark et al., Predictors of mental distress among sub-
stance abusers receiving inpatient treatment Substance Abuse Treatment, Pre-
vention, and Policy 2010, 5:15