The American Journal on Addictions, 20: 366–372, 2011
Copyright C ?American Academy of Addiction Psychiatry
ISSN: 1055-0496 print / 1521-0391 online
Quality of Life among Treatment Seeking
Rachel Gonzales, PhD, MPH,1Alfonso Ang, PhD,2Deborah C. Glik, ScD,3
Richard A. Rawson, PhD,1Stella Lee, BS,1Martin Y. Iguchi, PhD,3for the Methamphetamine
Treatment Project Corporate Authors
1Integrated Substance Abuse Programs, University of California, Los Angeles, California
2David Geffen School of Medicine, University of California, Los Angeles, California
3School of Public Health, University of California, Los Angeles, California
As the number of men and women entering treatment for
ment efforts for improving such outcomes. To date, QOL as-
sessments among methamphetamine (MA) dependent users
are limited. This paper examines QOL health status among
a sample of 838 treatment seeking MA users at admission.
Using regression analysis, predictors of QOL are examined
among MA users. Predictors of poor QOL among MA users
at treatment admission included being female, white, high
school educated or more, married, experiencing psychosocial
ing a high frequency of both MA and polydrugs for 15 days
or more in the past month, chronicity of MA and polydrug
use, injection use, and having co-morbid medical and psy-
chiatric impairment. Employment status was the only factor
related to better health status perceptions. This study ex-
pands the scope of scholarly examination of MA-dependent
users entering treatment, as there has not been a development
of coherent profiles of QOL among representative samples
of clinical MA-abusing populations to date. (Am J Addict
Viewing and managing substance abuse disorders as
health problems1has established the need for expanding
assessment measurements used for planning and evaluat-
Received June 18, 2010; revised July 8, 2010; accepted
August 5, 2010.
A complete list of the members of the Methamphetamine
Treatment Project is given at the end of this paper. Contents are
solely the responsibility of the authors, and do not necessarily
represent the official views of the funding agency. Address corre-
spondence to Dr. Gonzales, 1640 S. Sepulveda Blvd., Suite 200,
Los Angeles, CA 90025. E-mail: email@example.com.
ing treatment programs. Assessment measures most widely
used in substance abuse treatment planning and evalua-
tions have typically focused on the following core areas:
substance use behaviors, criminal involvement, employ-
ment and educational status, social/family relationships,
as well as medical and psychiatric functioning.2,3A com-
mon measure routinely used in public health for planning
and evaluation of programs is quality of life (QOL) or
patient perceived health status.4,5Given the wealth of re-
search establishing the substantial strains of substance use
on co-occurring medical disabilities, mental health prob-
lems,6and legal issues7,8it can be inferred that substance-
dependent individuals may be at heightened risk for poor
abuse treatment community is methamphetamine (MA).10
MA-admissions to publicly funded treatment programs
have remained fairly stable over the past years, wavering
ical and behavioral research with MA-dependent individu-
als imply that these individuals may be especially vulnera-
ble for poor QOL or health status perceptions. Specifically,
ditions affecting multiple organ systems12and psychiatric
co-morbidity13including cardiovascular and neurological
complications as well as psychosis and depression, suici-
dal ideations, auditory hallucinations, and paranoia.14,15
A recent investigation of MA-related emergency depart-
ment visits found that mental health problems, trauma,
skin infections, and dental pathology were the most com-
mon health issues associated with MA use.16
To date, there is limited research on QOL or patient
perceived health status among MA-dependent individu-
als. Brecht and colleagues17have reported on the health
status of MA users, although the measurement used was
general and not specific to QOL standardized assessment,
such as the Short Form Health Survey (SF-36, SF-20, and
SF-12) or the Nottingham Health Profile (NHP). Using
data from a multisite randomized clinical trial, this study
assesses QOL or perceived health status using the SF-36
among a MA-dependent clinical sample at admission to
outpatient treatment programs.
The sample is comprised of 838 MA-dependent indi-
viduals who participated in a Methamphetamine Treat-
ment Project (MTP) between 1999 and 2001.18Eligibility
for MTP participation included meeting substance depen-
dence Diagnostic and Statistical Manual of Mental Dis-
orders, 4th edition (DSM-IV) criteria for MA, using MA
within the month before treatment entry, geographic prox-
ciency. Upon admission, MTP participants were randomly
assigned to receive a 16-week treatment using the Matrix
Model or treatment as usual19in eight outpatient treat-
ment programs within California, Montana, and Hawaii.
The study was conducted under the review and approval of
the Institutional Review Board (IRB) of the University of
California, Los Angeles, as well as the local IRBs for each
participating treatment site.
Data used for this study were collected from the
SF-3620and Addiction Severity Index (ASI) fifth edition.21
The SF-36 is a generic self-report measure of QOL. It is
comprised of 36 items assessing perceived health status
across four physical subscales measuring physical func-
tioning, role limitations due to physical functioning, bodily
pain, and general health, as well as four mental subscales
measuring vitality, social functioning, role limitations due
for these eight subscales are combined into two summary
scales—physical component summary (PCS) and mental
component summary (MCS).22Scales are scored from 0 to
100, with higher scores indicating better QOL or perceived
tidimensional instrument that collects sociodemographic,
psychosocial, and drug use information.21The ASI gauges
problem severity by calculating composite scores across
seven domains: drug, alcohol, legal, family, employment,
medical, and psychiatric domains ranging from 0 (no prob-
lem) to 1 (extreme severity), with higher scores indicative
of more impairment.
Multiple linear regression was performed to exam-
ine predictors of QOL or perceived health status among
the MA-dependent sample at treatment admission. Pre-
dictor variables assessed for were measured by the ASI
at treatment admission and included sociodemographic,
psychosocial, drug use severity, and psychiatric and med-
ical factors that have been shown to affect treatment out-
comes.23,24Gender, age, race, marital status, living sit-
uation, educational attainment, employment status, and
religious preference comprised the sociodemographic vari-
ables. Psychosocial variables included lifetime trauma as
indicated by experiencing physical, emotional or sexual
abuse, lifetime suicide as defined by attempting suicide at
least once over the course of one’s life, and family and so-
cial conflict in the month prior to treatment entry. Drug
use severity measures included frequency of MA and poly-
drug use, drug use chronicity (lifetime use of both MA
and polydrugs), route of administration, and number of
past treatments for substance abuse. Measures of psychi-
atric and medical impairment measured by ASI composite
scores were also included.
Regression diagnostics showed that all key assumptions
of independence, linearity, homoscedasticity, and normal-
ity were met and no multicollinearity problems were en-
countered when tolerance and variance inflation factors
were analyzed. The Statistical Package for Social Sciences
level (2-tailed) set at p < .05 for statistical significance.
formed on all participants (N = 838) and 100% met crite-
ria for MA dependence. Females represented roughly half
of the sample (51.1%). Most patients were White (63%).
Other ethnic groups represented included Hispanic (18%),
Asian/Pacific Islander (14.1%), African American (1.9%),
and Native American/Alaskan Indian (3.0%). The average
age of the sample was 31.4 ± 8.03 years (range 18–60).
Approximately 17.2% of the sample were married, almost
half (49.9%) had never been married, and 33.1% were di-
vorced/separated/or widowed. The majority of the sample
was employed (73.3%) and 77.7% had a high school edu-
cation or more. Less than a quarter (19.5%) of the sample
reported not having stable living arrangements. In addi-
tion, a majority of participants reported having a religious
sample also reported experiencing a high level of interper-
(45.3%) during the prior month of treatment admission.
Drug Use Severity Factors
The frequency of MA use averaged 12 (SD = 9.0) days
and 5 (SD = 7.0) days for polydrug use in the month prior
Gonzales et al.July–August 2011367
to admission. Use greater than or equal to 15 days in the
month prior to admission was fairly moderate for MA
use (38%) and relatively low for polydrug use (15%). The
of the sample reported both polydrug use and MA use for
lifetime use for MA was 7.4 (sd = 6.0) years and 6.6 (sd =
7.0) years for polydrug use. The most common route of
administration for MA was smoking (65.2%), followed by
injecting (24%) and intranasal use (10.2%). Approximately
to their current treatment enrollment.
Psychiatric and Medical Factors
The amount of psychiatric and medical impairment re-
ported among the MA sample at treatment admission was
moderate, averaging 0.21 ± 0.30 and 0.23 ± 0.21, respec-
tively as measured by the ASI composite scales.
QOL at Treatment Admission
Using the SF-36, approximately 44% of the MA sam-
ple rated their health as “good,” 25% reported it as “fair
or poor,” while only 7% rated it as “excellent.” Table 1
presents comparative differences in QOL or patient per-
ceived health status between the MA sample at treatment
admission and the normative U.S. population.25Using cal-
culated z-scores and 95% confidence intervals, the clinical
MA sample had significantly lower perceptions of health
status/QOL across each of the mental and physical health
SF-36 scales, with the exception of physical functioning
compared to normative U.S. data. Scores were particularly
Given that preliminary analyses showed very similar re-
sults for the eight SF-36 subscales and two component
dictors of QOL (sociodemographic, psychosocial, drug use
severity, and psychiatric/medical factors) using the com-
ponent scales—PCS and MCS.
Predictors of QOL at Treatment Admission
Table 2 displays results predicting perceived physical
health status at treatment admission. The model was
significant (F = 12.45620,797, p < .001), accounting for
23.8% of explained variance. As shown, controlling for
all factors, significant predictors of poor physical health
status perceptions as measured by the PCS included female
gender (b = −1.493, p < .01), lifetime suicide history
(b = −.655, p < .05), and existing medical impairment
(b = −13.327, p < .001).
Table 3 displays results predicting perceived mental
health status at treatment entry measured. The model was
significant (F = 21.83720,797, p < .001), accounting for
35.4% of the explained variance. Accounting for all pre-
dictors, female gender (b = −1.444, p < .05), white race
(b = −2.507, p < .01), higher education (≥12) (b = −2.785,
p < .01), married status (b = −2.387, p < .05), lifetime
trauma (b = −.2.257, p < .05), suicide history (b = −3.022,
p < .001), family conflict (b = −1.836, p < .05), social
conflict (b = −2.530, p < .01), baseline MA drug use fre-
quency (≥15 days in past month) (b = −4.336, p < .001),
baseline polydrug use frequency (≥15 days in past month)
(b = −2.829, p < .05), injection route (b = −2.668, p <
.01), and psychiatric impairment (b = −20.217, p < .001)
were significant predictors of poor mental health status
TABLE 1. Comparative analysis of MA sample SF-36 scores at treatment admission with normative population
SF-36 scores for
(N = 838)
SF-36 scores for
(N = 2,474)Mean difference95% CI
51.4 ± 21.5
63.2 ± 28.8
53.9 ± 42.9
58.9 ± 21.6
39.2 ± 13.1
60.9 ± 21.0
83.3 ± 22.7
81.3 ± 33.0
74.7 ± 18.1
50.0 ± 10.0
85.7 ± 19.3
67.7 ± 38.7
70.2 ± 25.9
63.9 ± 20.8
50.6 ± 9.0
85.2 ± 23.3
81.0 ± 34.0
75.2 ± 23.7
72.0 ± 20.3
50.0 ± 10.0
VT = Vitality; SF = Social Functioning; RE = Role Emotional; EWB = Emotional Well Being; MCS = Mental Component Summary; PF = Physical
Functioning; RP = Role Physical; BP = Bodily Pain; GH = General Health; PCS = Physical Component Summary.
Note: U.S. analytic sample using SF-36 user’s manual; Range: 0–100.∗p < .05.
368Quality of Life among Methamphetamine UsersJuly–August 2011
TABLE 2. Unstandardized parameter estimates (b) and standard er-
rors (SE) from linear regressions of PCS†
Education (12 +)
Age-centered (mean age, 33 yrs)
Drug use severity
MA use ≥15 dy
Lifetime MA use ≥ 6 yr
Polydrug use ≥15 dy
Lifetime polydrug use ≥5 yr
†Outcome: high score: better functioning.∗p < .05,∗∗p < .01,
∗∗∗p < .001.
perceptions as measured by the MCS. Additionally, being
health status (b = 1.543, p < .05).
QOL research among substance abusers in general re-
mains an area of inquiry in need of more investigation.
This paper examined QOL or perceptions of health status
among a MA-dependent clinical sample entering outpa-
tient treatment. Given the standardization of the SF-36,
it is a very useful tool for comparing norms or mean dif-
ferences in QOL among different populations; however to
of MA-dependent users compared with population norms.
Using the SF-36, results highlight that, on average, MA
users reported significantly poorer QOL/perceived health
status compared with normative population data, espe-
cially among the mental health subscales, roughly 10–12
points lower. However, the physical health status reported
among the MA sample was not that different relative to
normative rates. This result may be due to the youthfulness
of the MA sample (average age was 33) compared to the
TABLE 3. Unstandardized parameter estimates (b) and standard er-
rors (SE) from linear regressions of MCS†
Education (12 +)
Age-centered (mean age, 33 yrs)
Drug use severity
MA use ≥15 dy
Lifetime MA use ≥ 6 yr
Polydrug use ≥15 dy
Lifetime polydrug use ≥5 yr
†Outcome: high score: better functioning.∗p < .05,∗∗p < .01,
∗∗∗p < .001
general population used in the Medical Outcomes Study
(average age was 55). Moreover, while age seems to play a
role in explaining QOL among the general population and
other studies with older substance dependent users,26–28
when entered in the predictive models in this study, it did
not have any explanatory value in the mental or physical
Regression model findings are useful from a clinical per-
spective as they offer insight into factors related to QOL or
try. Sociodemographic factors that were significant predic-
While previous studies support the notion that women MA
users are likely to have poorer mental and physical health
status perceptions than men,27,29–32this finding is impor-
tant as differences in QOL/health status perceptions may
relate to treatment adherence or posttreatment outcomes,
hence should be considered at treatment planning.
grade or higher) were more likely to have poorer mental
health status perceptions compared to those with lower
educational levels was unanticipated and not supported
by the literature,33as lower levels of education tend to be
Gonzales et al.July–August 2011369
speculation for this result is that drug use among highly
educated persons may lead to a sense of failure in terms
of not being able to successfully fulfill the roles and health
Hence, the perception of health states of the more educated
health status more than less educated persons, who may
not have set originally high goals and aspirations. Given
this finding, providers should examine treatment outcome
expectancies of MA patients with more education as this
area may also be jeopardized due to accomplishment or
The finding that married MA users had poorer men-
tal QOL was also not anticipated, as the literature shows
married people, in general are healthier than unmarried
people and it is unmarried persons who are supposed to
have higher morbidity and mortality health-related out-
comes.28A possible explanation for this counterintuitive
finding with MA users is that MA use can be related to
ported by the high interpersonal social conflict reported
among the sample; hence, this conflict may be a root fac-
tor for marital distress and the resulting poor health status
relationships, as is commonly found among MA users.34
Consistent with previous literature in the area of trauma
and interpersonal wellness,26,35this study also found that
MA users with history of trauma (including sexual, phys-
ical, and emotional abuse), lifetime suicidal past attempts,
and social conflict had poorer mental health perceptions
compared to those without such interpersonal distress.
Findings also confirm the established finding that past sui-
cide behavior is an important psychosocial predisposing
risk factor for poor mental health status.36Likewise, the
finding that social conflict at treatment admission signif-
icantly predicted poor physical health status is supported
by other health outcome studies in the literature,37,38which
show that one’s physical health is greatly dependent on in-
This study also found that QOL/health status percep-
sion as measured by proxy measures of frequency, chronic-
ity, and route of use. Specifically, the frequency of MA and
polydrug use (in the month before admission) as defined
by a clinical threshold of greater or equal to 15 days was
tions among the sample. Similarly, MA users with longer
histories of MA and polydrug use (defined by 6 or more
lifetime years) reported poorer health status perceptions
at admission. These findings are similar to a recent study
with poorer QOL at admission compared to noninjection
use, a finding that has been supported by a growing body
of studies in the literature looking at the clinical and health
implications associated with route of administration.40,41
Because studies have demonstrated that psychiatric and
medical impairment measured by ASI composite scores
can serve as a sufficient screener for physical and men-
tal health impairment in drug-dependent patients,42this
study assessed the extent to which medical and psychiatric
impairment (measured by ASI composite scores) affected
QOL/health status perceptions at treatment entry. Con-
firming the inverse relationship between comorbidity and
QOL found in previous studies with drug users,43–45this
study also found that MA users with high medical and
psychiatric dysfunction before treatment entry had poorer
health status perceptions. From a clinical perspective, as-
drug users prior to treatment entry is important given the
high prevalence of co-occurring psychiatric and medical
disorders among such individuals46and the influence these
factors have in contributing to one’s treatment success or
failure.47Furthermore, although the existence of this asso-
ciation makes logical sense, it still has to be demonstrated
and thoroughly studied to find ways of improving care for
patients with substance abuse and co-occurring medical
and psychiatric symptoms.
The data reported in this paper are based on patient
self-report. This is limiting especially for the measures that
assess physical and mental health impairment as these are
not objective measures that assess the extent to which
actual clinically determined medical and psychiatric co-
can impact perceived health status. Because this is the first
study to look at QOL among a MA-dependent treatment
sample, there are no other studies to reference, so impli-
cations as to why MA users rate their physical health as
nonproblematic or why having a higher education is corre-
lated with poorer QOL is left open for exploration.
Because the health status of MA-dependent persons
is associated with multiple individual and social prob-
lems, there are other unmeasured factors worth consid-
ering in future research with Health-Related Quality of
Life (HRQOL)-related studies among MA users. Future
research for example, can look at measures of income and
poverty, homelessness status, and social support structures
to get a better sense of how more macro-level factors play
a role in shaping and influencing the QOL of MA users.
While this study used lifetime suicide and trauma to con-
textualize “life events” that can impact the health status of
individuals, future studies can explore the impact of cur-
rent suicide ideation and current trauma experiences on
QOL health status perceptions as well. This study did not
investigate the impact of legal issues on one’s health status
370Quality of Life among Methamphetamine Users July–August 2011
individuals in the criminal justice system.48Not only does
time in jail and prison exact a high cost to society, such
confinement also has deleterious consequences on an indi-
vidual’s well-being.49Hence, criminal justice involved MA
MA-dependent users entering treatment, as there has not
been a development of coherent profiles of QOL among
representative samples of clinical MA-abusing populations
to date. The results from this study are especially useful
to treatment providers, since MA is a drug that has re-
ceived heightened attention from national, state, and lo-
cal public health authorities as a major health threat and
the routine monitoring of patient “health” is an important
goal of treatment programs. From a treatment planning
perspective, routine monitoring of health status can iden-
tify target areas for health promotion and intervention.
Results highlight some important clinical determinants of
QOL that should be considered with MA-dependent clin-
ical samples at treatment entry as targets of change, in-
cluding drug severity behaviors (ie, frequency of MA use,
polydrug use, and injection behaviors), interpersonal fam-
ily/social dysfunction, and medical and psychiatric co-
morbidities. Overall, a thorough understanding of QOL
among MA users and related factors can benefit providers
by being able to identify risks and barriers that can serve
to exacerbate substance dependence and worsen treatment
The research presented in this paper was supported by
grant numbers TI 11410, TI 11411, TI 11425, TI 11427, TI
11440, TI 11441, TI 11443, and TI 11484 from the Center
for Substance Abuse Treatment (CSAT), Substance Abuse
and Mental Health Services Administration (SAMHSA),
The MTP Corporate Authors: M. Douglas Anglin, PhD;
Richard A. Rawson, PhD; Patricia Marinelli-Casey, PhD;
Joseph Balabis, BA; Richard Bradway; Alison Hamil-
ton Brown, PhD; Cynthia Burke, PhD; Darrell Christian,
PhD; Judith Cohen, PhD, MPH; Florentina Cosmineanu,
MS; Alice Dickow, BA; Melissa Donaldson; Yvonne Fra-
zier; Thomas E. Freese, PhD; Cheryl Gallagher, MA;
Gantt P. Galloway, PharmD; Vikas Gulati, BS; James Her-
rell, PhD, MPH; Kathryn Horner, BA; Alice Huber, PhD;
Martin Y. Iguchi, PhD; Russell H. Lord, EdD; Michael
J. McCann, MA; Sam Minsky, MFT; Pat Morrisey, MA,
MFT; Jeanne Obert, MFT, MSM; Susan Pennell, MA;
Chris Reiber, PhD, MPH; Norman Rodrigues, Jr.; Jan-
ice Stalcup, MSN, DrPH; S. Alex Stalcup, MD; Ewa S.
Stamper, PhD; Janice Stimson, PsyD; Sarah Turcotte
and Human Services,
Manser, MA; Denna Vandersloot, MEd; Ahndrea Weiner,
MS, MFT; Kathryn Woodward, BA; Joan Zweben, PhD.
Declaration of Interest
The authors report no conflicts of interest. The authors
alone are responsible for the content and writing of this
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