indicators as important measures of treat-
ment effectiveness and patient satisfaction.
Ware stated that ‘‘In addition to traditional
measures of survival, clinical endpoints,
oday, there is a great deal of interest
in health-related qualityoflife
and disease-and-treatment specific symp-
toms and problems, the law mandated mea-
sures of functional status and well-being
recently, the health care field has become
more focused on evaluating the efficacy
Health-related Quality of Life
for Adults Participating in
Outpatient Substance Abuse
Thomas J. Morgan, Psy.D., Jon Morgenstern, Ph.D., Kimberly A.
Blanchard, Ph.D., Erich Labouvie, Ph.D., Donald A. Bux, Ph.D.
ment effectiveness with substance abuse clients. The SF-36 Health Survey is
a self-report measure assessing subjective health status along physical and
mental health dimensions. Subjects were 252 adults in an outpatient,
randomized clinical trial for substance abuse treatment. Subjects reported
significantly more impairments in functioning when compared to U.S. popu-
lation norms, but differences disappeared after three months of treatment.
There was little support that quality of life functioning was significantly
related to substance use during treatment. Results highlight the importance
ðAm J Addict 2003;12:198?210Þ
Received September 11, 2002; accepted November 8, 2002.
From the Center of Alcohol Studies, Rutgers, The State University of New Jersey, Piscataway (Drs. Morgan
and Labouvie); Department of Psychiatry, Mount Sinai School of Medicine, New York (Dr. Morgenstern);
and The National Center on Addiction and Substance Abuse, Columbia University, New York (Drs.
Blanchard and Bux). Presented as a poster at the 23rd Annual Scientific Conference of the Research Society
on Alcoholism, Denver, Colo., June 24?29, 2000. The views presented here are those of the authors
and not necessarily those of the National Institute of Alcohol Abuse and Alcoholism. Address correspondence
to Dr. Morgan, Center of Alcohol Studies, Rutgers, The State University of New Jersey, 607 Allison Road,
Piscataway, NJ 08854-8001. E-mail: firstname.lastname@example.org.
The American Journal on Addictions 12:198?210, 2003
Copyright #American Academy of Addiction Psychiatry
ISSN: 1055-0496 print / 1521-0391 online
Measuring changes in quality of life, such
as physical, mental, and social health, can
provide a common yardstick to measure
outcomes and determine the human and
assessing quality of life involves more than
a simple description of a patient’s health;
rather, quality of life is seen as how patients
perceive and react to their health status as
well as to other nonmedical areas of their
Since the early 1980s, there has been
an explosion of studies and reviews that
have focused on quality of life issues in the
health care ¢eld.2,4,5However, relatively
little has been done in the addictions ¢eld
to integrate health-related quality of life
into the assessment of outcomes. This is
surprising, given the long-standing aware-
ness that individuals with addiction prob-
lems typically have a host of physical,
emotional, and role functioning problems
as a result of their substance use.6?11
Longabaugh et al.8emphasized that
traditional de¢nitions of outcome for
alcoholism treatment generally focus on
whether the subjects are drinking or not.
One would expect that reductions in
alcohol use would be related to improve-
ments in other areas of quality of life, such
as general physical health, social role, and
emotional functioning. However, results
have been inconclusive. Reviews of the
literature on alcoholism have shown that
alcoholics often fail to improve in other life
areas even after reducing or stopping use
and that alcoholics can achieve improved
life circumstances even without absti-
nence.12,13Also, some studies have shown
a weak relationship between substance use
and other life functioning.9,14Longabaugh
et al.8note that this issue has not been
resolved empirically or conceptually.
Longabaugh and colleagues8do pro-
vide a well-articulated, conceptual model
for assessing health-related quality of life in
alcohol treatment research. The authors
begin by de¢ning alcoholism-related qual-
ity of life as:
...the totality of characteristics of
the way of life of an individual or
group with a particular reference
to (1) clinical status with respect to
substance use, (2) problems speci¢c
to the disorder, and (3) generic
health measures focusing on gen-
eral functioning and health percep-
tions usually valued regardless of a
person’s age or health state (p. 120).
Further, Longabaugh et al.8de¢ne the
clinical status of an individual with respect
to substance use as including the frequency,
amount, and pattern of substance use. Dis-
order-speci¢c problems are consequences
the individual experiences that are speci¢-
cally attributed to his/her substance use.
Finally, the area of general functioning
includes both physical, psychological, and
social role functioning.
A myriad of instruments are available
today to measure health-related quality of
life functioning in patients with medical
and/or psychiatric conditions. A few of
these measures have been used with
addictions populations, and the SF-3615
would appear to be a useful measure of
general functioning according to the con-
ceptual model of Longabaugh and col-
leagues. In the addictions ¢eld, results from
the literature using the SF-36 suggest the
following in relation to Longabaugh’s
quality of life model:
Clinical status: With both clinical and
reported that the severity of alcohol diag-
nosis is related to quality of life fun-
ctioning. Results suggest that individuals
with alcohol dependence have lower qual-
ity of life functioning than those with
alcohol abuse diagnoses.16?18
Disorder-speci¢c problems: There is some
evidence that the consequences of alcohol
use are related to quality of life functioning.
Morgan et al.
THE AMERICAN JOURNAL ON ADDICTIONS199
Two studies have reported that clients
experiencing more alcohol-related conse-
quences tended to have signi¢cantly poorer
General functioning: When compared to
population norms, clinical populations
show signi¢cantly lower health-related
quality of life functioning. These di¡er-
ences exist across a wide range of function-
ing, especially in psychological and social
role-functioning dimensions.20?23The role
of comorbid psychopathology has been
important in assessing health-related qual-
ity of life functioning for individuals with
alcohol problems. After the e¡ects of psy-
chiatric comorbidity were controlled, the
e¡ect of having an alcohol disorder was
not associated with poorer quality of life
To date, there are some striking
limitations in the studies of health-related
quality of life in the addictions ¢eld. In par-
ticular, most studies have focused on
populations with alcohol problems. We
found only three published studies that
have examined quality of life functioning
in drug abuse samples. Ryan and White22
studied clients enrolled in a methadone
maintenance program in Australia. In the
U.S., Garg et al.21examined a mixed
alcohol and drug sample from a psychiatric
treatment center, while Stein et al.23exam-
ined the reliability of the SF-20 (a
shortened version of the SF-36) in a mixed
alcohol and drug abuse treatment-seeking
In addition, little is known about the
quality of life functioning in United States
substance abuse treatment populations, as
most studies of clinical populations have
been conducted outside the U.S.16,17,20,22,26
Exceptions are the studies by Garg and
colleagues21and Stein et al.23In Garg et
al., the authors suggest that women and
patients treated in an in-patient detoxi¢-
cation program experienced higher levels
of mental health impairment, as measured
by the SF-36, at the beginning of treat-
ment. Results in the Stein et al. study
suggest the SF-20 was a reliable measure
with a mixed alcohol and drug treatment
Finally, we found only one study that
functioning over the course of substance
abuse treatment.21Garg and colleagues did
examine changes in SF-36 scores after six
months of treatment. Results suggested no
component summary scores but signi¢cant
improvements in mental component sum-
mary scores after six months of treatment.
In the Garg study, the authors did not
examine the relationship between reduc-
tions in substance use and improvements in
SF-36 scores after six months.
In this study, we hope to address some
of the limitations of the health-related qual-
ity of life literature mentioned above.
Speci¢cally, this study will address the
between adults entering outpatient
alcohol and drug treatment and U.S.
2. To assess changes in subjects’ health-
related quality of life after 3 months
of substance abuse treatment.
3. To examine the relationship between
reductions in substance use, at the
end of treatment, and improvements
in health-related functioning.
seeking treatment as part of a substance
abuse treatment dissemination study. Two
methods were used to recruit participants.
participants (n¼149) from an intensive
abuse treatment program located in central
200VOLUME 12 ? NUMBER 3 ? MAY?JUNE 2003
Health-Related Quality of Life
New Jersey. The second method consisted
of recruiting participants (n¼103) from
various community venues through media
advertisements and community referrals.
Labouvie, and Hayaki27for a more com-
plete description of the methods used in
as designed for the substance abuse
treatment dissemination study, aimed to
substance-abusing patients seeking com-
munity outpatient treatment who could
bene¢t from cognitive behavioral treatment
and whose life circumstances would not
interfere with study participation. Patients
were eligible for the study if they were
DSM-IV substance use disorder diagnosis
in the prior twelve months, used substances
at least once in the sixty days prior to
recruitment, expressed a willingness to
attempt to quit rather than simply reduce
their use, evidenced geographical stability,
had at least a sixth-grade reading level,
and were able to provide a collateral
who could locate their whereabouts.
Patients were excluded if they met any
of the following conditions: regular use of
intravenous drugs in the prior six months;
received more than seven days of inpatient
or than two weeks of intensive outpatient
treatment in the prior month; received
methadone, Antabuse, or naltrexone; were
grossly cognitively impaired; were cur-
suicide or homicide risk; had a life
threatening or unstable medical condition;
or for whom incarceration was impending.
The selection criteria,
The SF-36 Health Survey (SF-36)15.
SF-36 is a self-report, global measure of
health-related quality of life that measures
current health status in eight domains: gen-
eral health, mental health, pain, physical
role functioning, social role functioning,
role limitations due to physical problems,
role limitations due to emotional problems,
and vitality. According to the authors,
these domains were selected as representa-
tive of those most frequently measured
in health surveys and as most sensitive
to treatment-related change in functio-
ning.28See Table 1 for a brief description
and sample items within each domain.
All scores were calculated based on
scoring algorithms detailed in the user’s
manual.28For each of the eight subscales,
transformed scores range from 0 to 100
and represent the percentage of the total
possible score that can be achieved. Higher
transformed scores indicate higher quality
of life functioning.
The SF-36 has been shown to have
good reliability and validity.29,30In addition
to the SF-36’s psychometric strengths, it is
quick, easy to administer, and has popu-
lation norms for a wide range of medical
(including psychiatric) conditions.
assess alcohol and drug use for the six
months prior to treatment entry and
three months of treatment to determine
the percentage of days alcohol and drugs
were consumed (actual days of use divided
by days of possible use).
The TLFB was used to
Addiction Severity Index: Alcohol and Drug
Composite scores were
calculated to assess alcohol and drug
severity over the past thirty days. The
alcohol and drug composite scores were
combined to provide an overall substance
use severity composite score and could
range from 0.0 to 2.0.
The Structured Clinical Interviewfor DSM-IV
were assessed using the alcohol and drug
THE AMERICAN JOURNAL ON ADDICTIONS201
Morgan et al.
sections of the SCID. In the case of
diagnoses for more than one substance, pri-
mary substance use diagnosis was deter-
mined by taking the substance for which
subjects met the greatest number of depen-
Addiction Severity Index: Psychiatric Section
Current psychiatric status was
Composite scores can range from 0.0 to
1.0, with higher scores indicating poorer
After participants consented to the
study, they completed a 2?4 hour baseline
assessment. Participants were then ran-
domly assigned to one of three study treat-
ment conditions consisting of twelve
individual sessions taking place over a
13-week period. Participants received an
SF-36 SubscaleNumber of Items Description of SF-36 Subscales*
Physical Functioning 10 items (Alpha¼.92) Extent health limits physical
activities. ‘‘Does your health limit
you in lifting or carrying
Extent physical health interferes with
work/regular activities. ‘‘Have
you cut down on time,
accomplished less, or had di⁄culty
with work or other activities?’’
Intensity of pain and e¡ects of pain
on normal life. ‘‘How much body
pain and how much did it interfere
Evaluation of current health
outlook. ‘‘In general, how is your
health? Do you expect your health
to get worse?’’
Assessing levels of energy/vitality.
‘‘Do you feel tired or worn out?
Do you have a lot of energy and
feel full of pep?’’
Extent physical/emotional problems
interfere with social activities.
interfered with activities with
family, friends, neighbors, or
Extent emotional problems interfere
with activities. ‘‘Have you...not
Extent individuals experience
depression, anxiety, and gene
positive a¡ect. ‘‘Have you felt
downhearted or blue?’’
Role-Physical 4 items (Alpha¼.85)
Body Pain 2 items (Alpha¼.86)
General Health 5 items (Alpha¼.75)
Vitality4 items (Alpha¼.72)
Social Functioning 2 items (Alpha¼.65)
Role-Emotional 3 items (Alpha¼.80)
Mental Health5 items (Alpha¼.83)
*Scores range from 0?100. Higher scores indicate better functioning.
202VOLUME 12 ? NUMBER 3 ? MAY?JUNE 2003
Health-Related Quality of Life
in-person follow-up thirteen weeks after
their assignment to treatment. All partici-
pants were followed once randomized
regardless of their participation in study
treatments. By the end of treatment, 203
follow-up rate of 81%. The study design
and treatments are described in more detail
Labouvie, & Hayaki.27
Baseline scores on the SF-36 were com-
pared to scores of a U.S. normative sample
provided in the SF-36 scoring manual.28
Independent sample t-tests were used to
compare the SF-36 scores from the U.S.
normative group and study treatment
sample. E¡ect sizes of the di¡erences bet-
ween the two groups were also calculated;
small (.20?.49), medium (.50?.79), and
large e¡ects (>.80) were de¢ned according
Identifying changes in quality of life
over the course
accomplished by comparing pre- and
post-treatment scores on the SF-36. Di¡er-
ences between baseline and end of treat-
ment SF-36 scores were examined by
performing dependent measures t-tests and
calculating e¡ect sizes. In addition we cat-
egorized participants as ‘‘impaired’’ on the
eight SF-36 subscales if the participant’s
score fell below the 25th percentile, based
on the U.S. norms. We believed using
these impairment groups would be more
meaningful for identifying problems in
quality of life functioning than using a con-
tinuous measure. De¢ning participants as
impaired, using the 25th percentile, was
based on previous work by Danzinger
et al.35as well as criteria provided in the
SF-36 manual. In order to examine the
relationship between end of treatment
SF-36 functioning and
during treatment, we used Pearson corre-
lation and logistic regression analyses. In
the regression analyses, we used the end of
treatment impairment status as the depen-
dent variable and entered the baseline
impairment status and the within treatment
percent days abstinence. Due to the skewed
distribution for the percent days abstinence
variable, we log transformed the substance
use data and used this variable for all sub-
Of the total sample (N¼252), 37.7%
were female, 51.4% were African American,
75% were unmarried, 75.4% had at least
graduated high school, 47.2% were emp-
loyed, and the median family income was
$25,000?29,000. The mean age of the
sample was 35.9 (SD¼9.1). All partici-
pants met criteria for a DSM-IV substance
use disorder within the prior twelve
months: 91.7% met criteria for at least one,
and 33.7% met criteria for more than one
dependence disorder. Participants were
classi¢ed based on primary substance prob-
lem as follows: 41.3% (n¼104) alcohol,
36.1% (n¼91) cocaine, 16.3% (n¼41) her-
oin, 6% (n¼15) marijuana, and .4%
(n¼1) sedatives. On average, participants
met 5.6 (SD¼2.2) out of seven depen-
dence criteria for their primary problem
and used substances 45% (SD¼31.4) of
days during the six months prior to treat-
ment entry, and 63.5% had prior substance
abuse treatment. Table 2 describes the total
sample recruited for the study.
alcohol and drug use data were con¢rmed
via a collateral interview and urine screens.
The percent agreement between collaterals’
and subjects’ report of substance use was
93.2% (kappa¼.73), and agreement be-
tween urine screens and self-reported use
of any substance (de¢ned as any outcome
other than a positive urine screen, but
THE AMERICAN JOURNAL ON ADDICTIONS203
Morgan et al.
(kappa¼0.80). Thus, data suggest that
self-report of substance use was, for the
most part, valid in this study.
Comparison of SF-36 Functioning with a
Independent sample t-tests were con-
ducted, and results showed that our sample
scored signi¢cantly lower than the U.S.
population norms on the Role-Physical,
General Health, Vitality, Social Function-
ing, Role-Emotional, and Mental Health
subscales of the SF-36. Using Cohen’s
of e¡ect sizes, the Role-
Physical, General Health, and Vitality
subscales showed small e¡ects (.20?49).
Moderate e¡ects (.50?79) were seen for the
Social Functioning and Role-Emotional
subscales, while a large e¡ect (>.80) was
present for the Mental Health subscale (see
Rates of Impairment at Baseline and
End of Treatment
On each of the eight SF-36 subscales,
participants were de¢ned as impaired in
functioning based on scoring below the
25th percentile on the U.S. norms. For the
four physical functioning subscales, base-
line rates of impairment ranged from 20.8%
to 33.6% of the participant population.
For the four mental health functioning
TABLE 2. Participant Characteristics
CharacteristicTotal Sample (n¼252)
Gender (percent female)
Education level (high school
Marital status (married/living
Primary substance problem
Percent use days
Drinks per drinking day*
ASI alcohol severity score*
Years regular drinking*
ASI drug severity scorey
Years regular drug usey
Prior substance abuse treatment
*These means were computed for participants who had alcohol as their pri-
mary substance of use (n¼104).
yThese means were computed for participants who had a drug as their pri-
mary substance of use (n¼148).
204VOLUME 12 ? NUMBER 3 ? MAY?JUNE 2003
Health-Related Quality of Life
subscales, rates of impairment ranged from
35.2% to 62.4% of the participants.
At the end of treatment, rates of
impairment were reduced on all eight
SF-36 subscales (see Table 4). For the four
physical functioning subscales, end of treat-
ment rates of impairment ranged from
population. For the four mental health
functioning subscales, rates of impairment
ranged from 16.7% to 36.0% of the
participants. On all SF-36 subscales, rates
of baseline impairment were not signi¢-
cantly di¡erent between participants who
did and did not show up for the end of
Changes in SF-36 Functioning
Dependent t-tests were conducted for
the 199 participants that had both baseline
and end of treatment SF-36 scores. Results
SF-36 Health Survey Subscale Scores for U.S. Population Norms and Study Participants at
SF-36 Health Surveysubscales
*small e¡ect size (.20?.49).
ymedium e¡ect size (.50?.79).
zlarge e¡ect size (>.80).
and Endof Treatment
Rates of Impairment for SF-36 Health Survey Subscales for Study Participants at Baseline
SF-36 Health Survey Subscales
*Across all 8 SF-36 subscales, chi-square analyses revealed no signi¢cant di¡erences in baseline impairment
status between participants that did and did not appear for end of treatment follow-up.
THE AMERICAN JOURNAL ON ADDICTIONS205
Morgan et al.
for all eight SF-36 domains showed signi¢-
cant increases in functioning by the end of
treatment (see Table 5). E¡ect size analyses
also were conducted on the eight SF-36
subscales for baseline and end of treatment
scores. Negligible e¡ects were found for
the Physical Functioning and Body Pain
subscales. Small e¡ects were found for the
Role-Physical, General Health, and Vitality
subscales while moderate e¡ects were
found forthe Social
Role-Emotional, and the Mental Health
Evaluating Changes in Substance Use
as Related to
End of Treatment Impairment Status
Logistic regression analyses were con-
ducted to evaluate the relationship between
substance use during treatment and end of
on the SF-36 subscales. Separate logistic
regression analyses were conducted for each
subscale, entering the baseline impairment
status for that subscale and the log trans-
formed total percent days abstinent during
treatment. Substance use during treatment
was not signi¢cantly associated with end of
treatment impairment status on any of the
relationship between substance use during
treatment and the continuous scores from
each of the eight subscales from the end of
treatment SF-36. In only the Mental Health
subscale was there a signi¢cant relationship
between substance use during treatment
and quality of life functioning. In the
regression analysis, percent days abstinence
during treatment and baseline Mental
Health scores were entered and accounted
for 28% of the overall variance in end of
(2,195)¼38.99, p<.0001). Percent days
abstinence during treatment accounted
uniquely for 4.8% of the variance in end of
treatment Mental Health scores.
Consistent with reports from other studies
using the SF-36 with substance use clinical
SF-36 Health Survey Subscale
*small e¡ect size (.20?.49).
ymedium e¡ect size (.50?.79).
206VOLUME 12 ? NUMBER 3 ? MAY?JUNE 2003
Health-Related Quality of Life
populations19?22our results show clients
entering treatment reported signi¢cantly
more impairment in most of the SF-36
health domains, especially in the mental
and role functioning areas.
It was striking that the SF-36 scores
from other treatment samples appeared
substantially lower than our study sample.
Due to di¡erent norm groups and a lack of
statistical information in these studies, a
statistical comparison of the e¡ect size dif-
ferences was not possible. The di¡erences
between the current sample and at least
attributed to the fact that the SF-36 was
administered in di¡erent countries. Due to
the popularity of the SF-36, the instrument
has been translated into di¡erent languages
and we are not aware of any published in-
formation about the comparability of the
SF-36 across cultures. Also, in the Ryan
and White study,22the treatment sample
could be considered having more severe
problems in functioning, as they were
treating methadone maintenance clients.36,37
All SF-36 scale scores were substan-
tially higher in our sample than those
reported by Garg et al.,21even though the
levels of care for the two samples were
comparable. However, the sample in the
Garg study may have shown more impair-
ment due to being recruited from a psychi-
may have had a greater in£uence on
impairment. Additionally, the sample in
the Garg study di¡ered from our study
sample on many demographic charac-
teristics, such as age, gender, ethnicity, and
After treatment, signi¢cant improve-
ments in SF-36 scores were seen, and our
study participant’s scores on all SF-36
subscales were no longer di¡erent from the
U.S. population norms. Additionally, sub-
stantial decreases were seen in the rates of
impairment across all SF-36 subscales,
especially in the social, emotional, and
mental health functioning domains.
Longabaugh et al.8posed the question
whether health-related quality of life is
directly improved as a function of absti-
nence or reductions in alcohol and drug
use. The results of this study o¡er data to
answer this question. In our sample,
although signi¢cant improvements in sub-
stance use outcome were seen, changes in
alcohol and drug consumption were gener-
changes in quality of life impairment status
at the end of treatment. We found only a
weak relationship between substance use
during treatment and the continuous
measure of mental health functioning.
There may be several explanations for
these results. One explanation is that a
relationship between substance use and
impairment in quality of life is present but
obscured due to the restriction of range in
substance abuse outcomes. Within treat-
extremely positive, as the mean percent
days of abstinence from alcohol and drugs
was 89% (SD¼22.93). In addition, as
McLellan et al.9suggest, it may take longer
periods of time for individuals with
addictions problems to experience im-
provements, especially in social and role
functioning. Thus, examining the relation-
ship of quality of life functioning and sub-
stance use at follow-up points further away
from the end of treatment may be a better
test. For example, assessing participants six
or twelve months after treatment will
address the issue of restrictions of range in
assessing quality of life functioning after
longer periods of time is likely to allow
some individuals the needed time to repair
social and role functioning impairments.
These results are consistent with con-
clusions from Emerick,12Pattison,13and
McLellan et al.,9which suggest there are
di¡erential e¡ects for individuals within
substance abuse treatment samples. For
example, at the end of treatment in our
THE AMERICAN JOURNAL ON ADDICTIONS207
Morgan et al.
subjects who were not impaired on SF-36
subscales were also using substances, while
between 33.3%?55.9% of the subjects who
impaired. An individual’s current substance
use may not be the only factor contributing
to impairment in quality of life func-
tioning. Additional factors such as the
severity of substance use, length of sub-
stance use history, and/or other client
characteristics (ie age, medical history, psy-
chiatric history) may also play an important
role in the impairment of functioning for
individuals with addictions.
Finally, there may be other factors that
are related to improvement in functioning
beyond just abstinence from substances. As
McLellan et al.9point out, abstinence from
substances may be necessary but not suf-
¢cient for improvements in other areas of
life functioning. Other factors such as
utilization of ancillary services (medical,
psychiatric, vocational) and family and
functioning even with substance use.
Using the continuous SF-36 scores,
there typically was no signi¢cant associ-
ation between substance use during treat-
ment and quality of life functioning at the
end of treatment. The sole exception was
the continuous score on the Mental Health
subscale: improvements in substance out-
improvements in end of treatment Mental
Health functioning. It may be that the
mental health dimension is more respon-
sive to reductions in use or abstinence from
alcohol and drugs than other health-related
quality of life dimensions. It is likely that
the same change processes contributing to
positive changes in substance use are also
in£uencing changes in participant’s emo-
tional health. It will be important to exam-
ine whether this improvement in mental
health functioning is sustained over longer
periods of time. Finally, it is not surprising
that the relationship between substance
use outcomes and mental health function-
ing was signi¢cant in the continuous
measure and not in the dichotomous
impairment variable. When compared to
dichotomous variables will have weaker
relationships due to the attenuation of the
range. Since health-related quality of life
functioning is generally not related to sub-
stance use, it would seem important to
include the SF-36 as another indicator
assessing treatment outcome.
important; in the health care ¢eld, there is
more interest in assessing patient’s func-
tional status, and well-being, as well
as traditional disease-speci¢c symptoms.
Additionally, in the addictions ¢eld, it is
becoming more and more evident that
even with abstinence, many patients can
continue to experience physical, social,
and role functioning impairments. It will
be important to assess these domains and
provide appropriate treatment referrals
The primary ¢ndings of interest in this
study were that subjects entering substance
abuse treatment reported signi¢cantly more
impairments in health-related quality of life
functioning than U.S. population norms.
These di¡erences are especially pronounced
in the mental health and role functioning
domains. Additionally, after a three-month
treatment period, subjects showed signi¢-
cant improvements in their substance use
as well as health-related quality of life
functioning, particularly in the mental
For many years, there has been an
interest in integrating health-related quality
of life assessments into the health care ¢eld,
although the literature in the addictions
¢eld has been particularly limited in the
U.S. It will be important to conduct
further research using psychometrically
208VOLUME 12 ? NUMBER 3 ? MAY?JUNE 2003
Health-Related Quality of Life
measures in clinical programs. In future
studies, standard information on medical
and psychiatric service utilization will need
to be collected. It will be important to
assess the contribution of client use of
ancillary services to changes in quality of
life functioning, as there may be important
implications for treatment planning.
This study had several limitations in
addition to those previously mentioned.
Although our sample was fairly hetero-
limited, as we excluded those clients who
chiatric or organic impairment, or used
drugs intravenously. Also, we examined
quality of life functioning three months
occurred in subjects’ substance use patterns
and global functioning; at this time, we do
not know whether these changes in quality
of life will be sustained. An important con-
tribution to the literature will be examining
the changes of quality of life functioning
overalongerperiod of time.
This research was supported by research
grant R01-AA10268-06 (Dr. Morgenstern)
from the National Institute of Alcohol Abuse
The authors would like to thank Janine
Swingle, Ph.D., Chris Dasaro, M.A., and
Fred Meunch, M.A. for their thoughtful review
and input in earlier versions of this manuscript.
In addition, they greatly appreciate the support
M.P.A., Michael Bizzarro, LCSW, and
Carlton Ryder, M.Div., at Trinitas Hospital,
1. Ware JE. The status of health assessment 1994.
Annu Rev Public Health. 1995;16:327?354.
2. Testa MA, Simonson DC. Assessment of
3. Gill TM, Feinstein AR. A critical appraisal of
the quality of quality-of-life measurements.
4. Foster JH, Powell JE, Marshall EJ, Peters TJ.
Quality of life in alcohol-dependent subjects?a
review. Qual Life Res. 1999;8:255?261.
5. Muldoon MF, Barger SD, Flory JD, Manuck
SB. What are quality of life measurements
measuring? Br J Addict. 1998;316:542?545.
6. Bowen OR. Raising public awareness about
the extent of alcohol-related problems: an
7. Harley DA, Hanley-Maxwell C. Improving
employment outcomes for chronic alcoholics:
applying the supported employment model.
Int J Addict. 1994;29:667?673.
8. Longabaugh R, Mattson ME, Connors GJ,
Cooney NL. Quality of life as an outcome vari-
able in alcoholism treatment research. J Stud
9. McLellan AT, Luborsky L, Woody GE,
O’Brien CP, Krun R. Are the addiction-related
problems of substance abusers really related?
J Nerv Ment Dis. 1981;169:232?239.
10. Moos RH, Moos BS. The process of recovery
from alcoholism, III: comparing functioning
in families of alcoholics and matched control
families. J Stud Alcohol. 1984;45:111?118.
11. Harwood H, Fountain D, Livermore G, The
Lewin Group. The Economic Costs of Alcohol
and Drug Abuse in the United States, 1992.
Rockville, Md: National Institute of Drug
12. Emrick CD. A review of psychologically
oriented treatment of alcoholism, I: the use
and interrelationships of outcome criteria and
drinking behavior following treatment. J
Stud Alcohol. 1974;35:523?549.
ism treatment goals. Addict Behav. 1976;
Posttreatment experiences and treatment out-
come of alcoholic patients six months and
two years after hospitalization. J Consult Clin
RH, Mewborn CR.
THE AMERICAN JOURNAL ON ADDICTIONS209
Morgan et al.
15. Ware JE, Sherbourn CD. The MOS 36-item
short-form health survey (SF-36), I: conceptual
framework and item selection. Med Care.
16. McKenna M, Chick J, Buston M, Howlett H,
Patience D, Ritson B. The SECCAT survey,
I: the costs and consequences of alcoholism.
Alcohol Alcohol. 1996;31:565?576.
17. Patience D, Buxton M, Chick J, Howlett H,
McKenna M, Ritson B. The SECCAT survey,
II: the alcohol-related problems questionnaire
as a proxy for resource costs and quality of
life in alcoholism treatment. Alcohol Alcohol.
18. Volk RJ, Cantor SB, Steinbauer JR, Cass AR.
Alcohol use disorders, consumption patterns,
and health-related quality of life of primary
19. Romeis JC, Waterman B, Scherrer JF, et al. The
impact of sociodemographics, comorbidity and
symptom recency on health-related quality of
life in alcoholics. J Stud Alcohol. 1999;60:
20. Daeppen JB, Krieg MA, Burnand B, Yersin B.
MOS-SF-36 in evaluating health-related quality
of life in alcohol-dependent patients. AmJDrug
Alcohol Abuse. 1998;24:685?694.
21. Garg N, Yates WR, Jones R, Zhou M, Williams
S. E¡ect of gender, treatment site, and psychi-
atric comorbidity on quality of life outcome
in substance dependence. Am J Addict. 1999;8:
22. Ryan CF, White JM. Health status at entry to
methadone maintenance treatment using the
SF-36 health survey questionnaire. Addiction.
23. Stein MD, Mulvey KP, Plough A, Samet JH.
The functioning and well being of persons
who seek treatment for drug and alcohol
abuse. J Subst Abuse. 1998;10:75?84.
24. Johnson JG, Spitzer RL, Williams JB, et al.
Psychiatric comorbidity, health status, and
functional impairment associated with alcohol
abuse and dependence in primary care patients:
¢ndings of the PRIME-MD-1000 Study. J Con-
sult Clin Psychol. 1995;63:133?140.
25. Spitzer RL, Kroenke K, Linzer M, et al.
Health-related quality of life in primary care
patients with mental disorders: results from
the PRIME-MD 1000 Study. JAMA. 1995;
relapse to heavy drinking in alcohol-dependent
subjects following alcohol detoxi¢cation?the
role of quality of life measures, ethnicity,
social class, cigarette and drug use. Addict
27. Morgenstern J, Blanchard K, Morgan TJ,
Labouve E, Hayaki J. Testing the e¡ectiveness
of cognitive behavioral treatment for substance
abuse in a community setting: within treatment
outcomes. J Consult Clin Psychol. 2001;69:
28. Ware JE, Snow KK, Kosinski M, Gandek B.
SF-36 Health Survey: Manual and Interpretation
Guide. Boston, MA: New England Medical
Center Health Institute; 1993.
29. Brazier JE, Harper R, Jones NMB, et al.
questionnaire: new outcome measure for pri-
mary care. Br J Addict. 1992;305:160?164.
30. McHorney CA, Ware JE, Lu JFR, Sherbourne
D. The MOS 36-item short-form health
survey (SF-36), III: tests of data quality, scaling
assumptions, and reliability across diverse
patient groups. Med Care. 1994;32:40?66.
31. Sobell LC, Sobell MB, Leo GI, Cancilla A.
Reliability of the Timeline Method: assess-
drinking and a comparative evaluation across
several populations. Br J Addict. 1988;83:
32. McLellan AT, Kushner H, Metzger D, et al.
The ¢fth edition of the Addiction Severity
Index. J Subst Abuse Treat. 1992;9:199?213.
33. First MG, Spitzer RL, Gibbon M. Structured
Clinical Interview for DSM-IV. New York: Bio-
metrics Research Department, New York State
Psychiatric Institute; 1996.
34. Cohen J. Statistical Power Analysis for the
35. Danzinger S, Cocoran M, He£in C, et al.
Barriers to Employment of Welfare Recipients.
Unpublished manuscript. Ann Arbor, MI: Uni-
versity of Michigan, Poverty Research and
Training Center; 2000.
36. McLachlan C, Crofts N, Wodak A, Crowe S.
The e¡ects of methadone on immune function
37. Reiger DA, Farmer ME, Rae DS, Locke BZ,
Keith SJ, Judd LL, Goodwin FK. Comorbidity
of mental disorders with alcohol and other
drug abuse: results from the Epemiologic
Catchment Area (ECA) study. JAMA. 1990;
210VOLUME 12 ? NUMBER 3 ? MAY?JUNE 2003
Health-Related Quality of Life
Page 14 Download full-text