Infectious Disorders – Drug Targets, 2011, 11, 167-174
1871-5265/11 $58.00+.00 © 2011 Bentham Science Publishers Ltd.
HIV Treatment Adherence, Drug Resistance, Virologic Failure: Evolving
Jean B. Nachega1,2,*, Vincent C. Marconi4, Gert U. van Zyl2,3, Edward M. Gardner5,
Wolfgang Preiser2,3, Steven Y. Hong6, Edward J. Mills7 and Robert Gross8
1Department s of International Health and Epidemiology, Johns Hopkins Bloomberg School of Public Health, Balti-
more, MD, USA; 2The Department of Medicine and Centre for Infectious Diseases , and 3Department of Pathology, Di-
vision of Medical Virology, Stellenbosch University, Faculty of Health Sciences, Cape Town, South Africa; 4Emory Uni-
versity School of Medicine, Atlanta, Georgia, USA; 5Denver Public Health and The University of Colorado, Denver,
USA; 6Tufts University School of Medicine, Boston, USA; 7British of Columbia-Centre for Excellence on HIV/AIDS,
University British of Columbia, Vancouver, Canada; 8Department of Medicine, Division of Infectious Diseases and Cen-
ter for Clinical Epidemiology and Biostatistics, University of Pennsylvania, School of Medicine, Philadelphia, PA, USA
Abstract: Poor adherence to combined antiretroviral therapy (cART) has been shown to be a major determinant of vi-
rologic failure, emergence of drug resistant virus, disease progression, hospitalizations, mortality, and health care costs.
While high adherence levels can be achieved in both resource-rich and resource-limited settings following initiation of
cART, long-term adherence remains a challenge regardless of available resources. Barriers to optimal adherence may
originate from individual (biological, socio-cultural, behavioral), pharmacological, and societal factors. Although patients
and providers should continuously strive for maximum adherence to cART, there is accumulating evidence that each class
of antiretroviral therapy has specific adherence-drug resistance relationship characteristics allowing certain regimens more
flexibility than others. There is not a universally accepted measure for cART adherence, since each method has distinct
advantages and disadvantages including cost, complexity, accuracy, precision, intrusiveness and bias. Development of a
real-time cART adherence monitoring tool will enable the development of novel, pre-emptive adherence-improving
strategies. The application of these strategies may ultimately prove to be the most cost-effective method to reduce morbid-
ity and mortality for the individual and decrease the likelihood of HIV transmission and emergence of resistance in the
Keywords: HIV, antiretroviral therapy adherence, virologic failure, drug resistance, outcomes.
which individuals take medications as prescribed. Optimal
adherence to combination antiretroviral therapy (cART) can
be defined based on the virologic (measured by HIV RNA
viral load), immunologic (measured by CD4 T-cell count),
and clinical outcomes of patients whose adherence was
measured during longitudinal studies. For the currently out-
moded unboosted protease inhibitor (PI)-based cART,
Paterson et al. described the highest likelihood of treatment
success in patients who take ?95% of the medications pre-
scribed by their physician . In contrast, accumulating data
shows that cART based on non-nucleoside reverse tran-
scriptase inhibitors (NNRTIs) or boosted PIs have high rates
of suppression at moderate levels of adherence (70-90%) [2-
It is now widely appreciated that adherence to antire-
troviral therapy is the critical determinant of HIV treatment
outcomes. Adherence to cART had been shown to be a ma-
jor predictor of achieving adequate suppression of HIV rep-
lication [1-6], required to minimize the emergence of drug
Medication adherence typically refers to the extent to
*Address correspondence to this author at the Johns Hopkins University,
Bloomberg School of Public Health, 615 North Wolfe Street, Suite W5031,
Baltimore, Maryland 21205, USA; Tel: +1 410-955-2378; Fax: 410-502-
6733, E-mail: firstname.lastname@example.org
resistance (DR) , disease progression , and death [9-
11]. Recently, there has been increasing discussion regarding
the public health implications of antiretroviral therapy utili-
zation and adherence as applied in ‘test and treat’ HIV pre-
vention strategies . Here, we will explore these princi-
ples in further detail. In addition, we will review levels of
adherence to antiretroviral therapy in different populations,
the association between adherence and the development of
antiretroviral resistance mutations, the impact of adherence
on the cost of medical care, and finally discuss the instru-
ments used to measure adherence and their potential utility
to impact HIV treatment outcomes in the future.
2. ADHERENCE AS MAJOR DETERMINANT OF HIV
TREATMENT OUTCOMES: CLINICAL AND PUBLIC
tion include biology, behavior, and social or structural is-
sues. A conceptual "pathway" model of successful HIV
treatment determinants and outcomes illustrates the critical
role of medication adherence Fig. (1). Biological determi-
nants of adherence include predisposition to drug adverse
effects (e.g., Abacavir hypersensitivity reaction and HLA
B*5701) . Behavioral determinants include issues such
as maintenance of routines [14-15]. Social issues include
stigma in the local community regarding HIV infection [16-
Some determinants of effective treatment of HIV infec-
168 Infectious Disorders – Drug Targets, 2011, Vol. 11, No. 2
Nachega et al.
17]. Structural issues relate to the health care system which
includes the development and availability of potent medica-
tions, adoption of guidelines for correct prescribing of these
drugs, and regular patient access to health care and medica-
tions [18-20]. Optimizing all of these factors will most likely
lead to the highest levels of adherence possible.
Fig. (1). Determinants of HIV Treatment Success and Outcomes.
ity of cART regimens. Fortunately, a South African patient
initiating cART today is typically prescribed three individual
tablets once a day: Tenofovir (TDF) 300mg + Lamivudine
(3TC) 300 mg or Emtricitabine (FTC) 200 mg + Efavirenz
(EFV) 600mg . The pill burden can be simplified further
by using medications that combine several drugs in a single
pill as fixed-dose combinations (FDC). In other settings such
as high-income countries, a one pill once a day combination
of EFV + FTC + TDF in the same dosage as the individual
tablets is commonly used .
The pathway to adherence is threatened by the complex-
adherent to cART, a patient can miss no more than one out
of the 30 doses per month. In addition, for maximal efficacy,
specific cART doses must be taken at the prescribed time.
When patients do not accurately adhere to their regimen
schedule and instead take their drugs too late or too early or
miss doses completely, blood concentrations can drop below
the level necessary to fully suppress HIV, which may lead to
the emergence of drug-resistance, disease progression and
death, or rise to levels that are hazardous to the patient be-
cause of drug toxicity [23-24]. Unfortunately, how precisely
the timing needs to be followed before virologic failure is
not fully characterized and likely differs by HIV drug/ regi-
men . A significant body of evidence has demonstrated
the relationship between the presence of acquired HIVDR
and AIDS/death outcomes [26-35]. In addition, data from
CDC’s HIV Outpatient Study showed that patients who had
resistance testing survived longer than those who did not.
However, it is unlikely that testing per se was life-saving but
served as an indicator of better care and better access to
newer drugs .
Evidence from observational studies among heterosexual
populations and men who have sex with men suggests that
effective cART in highly adherent patients may greatly re-
On a once daily cART regimen, in order to remain >95%
duce sexual transmission of HIV from infected individuals to
their sexual partners [37-38]. This concept has been explored
in a modeling exercise that simulated the effects of a hypo-
thetical “test-and-treat” strategy in which universal voluntary
HIV testing is combined with immediate cART for infected
persons regardless of their CD4 T-cell count. Based on these
modeling data, and assuming sustained high levels of adher-
ence with broad coverage and uptake, cART could reduce
HIV transmission, and hence potentially curb the HIV epi-
demic by decreasing the incidence of HIV to less than one
case per 1,000 people per year by 2016 [39-42]. However,
achieving full access to cART and long-term ART adherence
support for all at-risk populations may prove to be more dif-
ficult than any mathematical model could predict [40-41]
and such approaches still raise concerns about individual
rights, toxicity, drug resistance, financing. Also, as for all
mathematical models, the voluntary “test-and-treat model is
based on a number of assumptions that required to be vali-
dated by research. Indeed, feasibility studies are already un-
derway in both developed and developing countries with
preliminary results anticipated in the next few years.
ing up of cART access. This depends on political will, local
infrastructure and available resources. These aspects are im-
portant not just for delivering cART and providing health
care, but in promoting and monitoring treatment adherence
. Required aspects of infrastructure include not only
mechanisms to obtain and dispense drugs, but also to teach
patients about adverse effects, adherence and lifestyle modi-
fications to improve treatment effectiveness. There is an ur-
gent need for the development and implementation of simpli-
fied, standardized treatment and monitoring algorithms that
will facilitate roll-out and scale-up of programs and enable
counseling and follow-up of patients.
The major issue facing the developing world is the scal-
3. LEVELS AND DETERMINANTS OF ANTIRETRO-
VIRAL THERAPY ADHERENCE IN DEVELOPED
COMPARED WITH DEVELOPING COUNTRIES
antiretroviral therapy adherence in poverty-affected regions
of the world as expressed by selected high-level international
agency decision-making bodies. These opinions arguably
contributed to the delay in cART roll-out in resource-limited
settings [44-46]. Furthermore, until Mills and colleagues
conducted a meta-analysis to assess adherence in Africa,
comprehensive assessments of levels of cART adherence
were limited or based on anecdotes and personal observa-
tion. In this meta-analysis, reported levels of adherence were
measured in a variety of ways, including pill-counts, phar-
macy refill data, Medication Event Monitoring System
(MEMS), and self-report . On average, 77% of African
patients (95% Confidence Interval [CI]: 68-85%) met the
standard definition of good adherence (?80%) compared to
55% (95% CI: 49-62%) of North American patients. These
findings have encouraged international assistance regarding
improved access to cART and were referred to by former
U.S. President Bill Clinton at the 2006 IAS Conference as
the “nail in the coffin” on discrimination regarding drug ac-
Given the individual and public health benefits associated
with adherence to cART, there is a need for a greater under-
Historically, there has been an expectation of poor
Retention in Care
Access to Care
Increased Immune Activation
New Resistance Mutations
↑ ↑ Community Transmission
Poor QOL and High Mortality
Ongoing Viral Replication
Host Immune and
Inhibition of Viral Replication
Decreased Immune Activation
Halted Disease Progression
↓ Community Transmission
Improved QOL and Survival
Cost-Effectiveness of cART
HIV Treatment Adherence, Drug Resistance, Virologic Failure Infectious Disorders – Drug Targets, 2011, Vol. 11, No. 2 169
standing of actual adherence rates within specific popula-
tions. Moreover, it is vital to examine reasons for poor ad-
herence and possible motivators to improve adherence so as
to inform the design of adherence-improving interventions.
A review of the literature shows that prevalent factors asso-
ciated with poor treatment adherence in resource-rich and
limited settings include untreated depression, active sub-
stance abuse, poor insight into disease and treatment, being
an adolescent or young adult, higher pill burden and more
frequent dosing, and forgetfulness . In addition, the fol-
lowing risk factors for non-adherence were more prevalent in
sub-Saharan Africa: cost or structural barriers such as phar-
macy stock-outs or lack of transportation means to the health
facility for cART refills [50-51]; food insecurity ; non-
disclosure to a loved one or fear of being stigmatized .
Studies report that the majority of patients accessing cART
have disclosed their HIV status to family or friends and that
those who have not disclosed appear to have worse outcomes
. Patients who do not disclose their infection to their
intimate partner or household may have frequent treatment
interruptions due to the fact that tablets must be hidden and
not taken in the presence of others. Encouraging voluntary
HIV status disclosure in a community with access to ART
may result in improved uptake of voluntary counseling and
testing (VCT) and may help decrease stigma and improve
adherence. Of note, very few interventions have been de-
signed that have successfully demonstrated improved adher-
ence, and most have been limited to North American settings
 Development of effective, culturally-sensitive cART
adherence interventions in developed and developing world
settings is an important area of ongoing and future research
4. RELATIONSHIP BETWEEN ANTIRETROVIRAL
THERAPY ADHERENCE, DRUG CLASS AND DRUG
receive major clinical and public health attention because
resistant HIV not only threatens the patient in which it de-
velops but can be transmitted to others . Widespread
resistance has the potential to undermine our ability to fight
the HIV/AIDS pandemic by rendering first-line treatments
ineffective. This is especially important in the developing
world where second-line and salvage regimens are either
extremely expensive, unavailable, or both .
The phenomenon of HIV drug resistance continues to
quired (secondary) or transmitted (primary). Acquired
HIVDR occurs when mutations develop to drugs in indi-
viduals who have received ARV, often because of poor ad-
herence, treatment interruptions, inadequate drug concentra-
tions, or use of sub-optimal drug combinations leading to
treatment failure. Transmitted HIVDR occurs in the context
of HIV-infected individuals who have never received ART,
and occurs when individuals are newly infected with a drug-
resistant virus. If virus replication is not suppressed by medi-
cation, millions of viruses harboring different mutations arise
each day owing to the high error rate of the reverse transcrip-
tion process and the lack of genetic proofreading. Although
many of these mutations have a detrimental effect on viral
survival, occasionally, a mutation results in an altered viral
protein which renders viral replication less susceptible to
HIV drug resistance (HIVDR) can be classified as ac-
inhibition by a particular antiretroviral drug. In the presence
of drug, cART inhibits replication of the wild-type strain, but
mutant viral strains with reduced susceptibility continue to
replicate and become the predominant circulating viral popu-
lations in the individual Fig. (2).
Fig. (2). Emergence of Resistant Viral Population due To Selective
invariably breeds drug resistance. However, the relationship
between adherence and resistance is much more complex
and follow an inverted “U-shaped” curve. At the highest
levels of adherence, the threat of resistance is lowest because
mutations cannot occur without replication. However, at
lower levels of adherence the complex interplay between
potency, viral fitness after mutation, the genetic barrier to
resistance of cART components, and the other regimen com-
ponents determine whether or not resistant virus will be cir-
culating Fig. (3). Even relatively small degrees of non-
adherence are thought to substantially increase resistance.
It is grossly apparent that non-adherence to medication
Fig. (3). Inverted “U-Shaped” Hypothetical Curve of the Relation-
ship Between Probability of Drug Resistance and HIV Treatment
The complexity of this relationship is in part determined
by the relative fitness of resistant compared with wild type
virus. Most mutant strains are less fit than the wild-type
strains, which means a certain level of selection pressure is
required before the mutant strains are able to out-compete
the wild-type strains in order to predominate. As a result,
low levels of adherence do not impose the necessary selec-
tion pressure on the viral population to favor the resistant
170 Infectious Disorders – Drug Targets, 2011, Vol. 11, No. 2
Nachega et al.
less fit strains than the wild-type fitter strains and thus emer-
gence of resistance is less likely. Of course low adherence is
not advisable since it allows wild-type virus to replicate un-
checked, leading to disease progression. This inverted ‘U-
shaped’ relationship leaves moderately adherent patients at
the greatest risk for the development of resistance .
relationship between adherence and drug resistance differs
depending on the antiretroviral drug class Fig. (4). Indeed,
they have shown that NNRTI-based drug regimens are more
likely to produce resistance than PI-based because of several
factors. The high potency and long half-life of NNRTIs may
lead to better virologic suppression at moderate adherence
levels, but paradoxically lead to the development of antiret-
roviral drug resistance during a treatment interruption of
triple therapy containing NRTIs and NNRTI lasting more
than 48 hours . During a treatment interruption, the
comparatively short half-lives of the NRTIs in the regimen
lead to prolonged NNRTI monotherapy. The low genetic
barrier for resistance of NNRTIs allows resistant virus to
accumulate rapidly. Also, NNRTIs inhibit RT allosterically,
by binding to an area outside the active (substrate binding)
site, thus NNRTI resistance mutations have little effect on
RT’s overall function and hence little impact on viral fitness.
Work by Bangsberg and others [59-63] has found that the
Fig. (4). Probability of Resistance by Adherence Level and Class of
Antiretroviral Therapy Regimen (adapted from reference 60, with
permission from Oxford University Press, June 30, 2010).
A study in Kampala, Uganda , of patients purchasing
generic fixed-dose NNRTI-based cART found that 65% had
a treatment interruption of greater than 48 hours as evaluated
by electronic adherence monitoring, and these treatment in-
terruptions accounted for 90% of missed doses. Eight of the
62 (13%) participants who had treatment interruptions expe-
rienced treatment failure due to selection of drug resistant
virus, compared to none of the 33 participants without treat-
ment interruptions greater than 48 hours. Importantly, there
was also a significant decrease in virologic suppression rates,
from 80% to 50%, for patients with >95% adherence versus
<95% adherence, respectively. As a consequence, the threat
of resistance to first-generation NNRTIs is highest at low
levels of adherence, rather than at moderate adherence, be-
cause even the lowest concentrations of these NNRTIs create
enough selection pressure to affect HIV. Protease inhibitors
(PIs) and most nucleoside reverse transcriptase inhibitors
(NRTIs) require multiple mutations, each of which alter en-
zyme function and could make the virus less fit . These
drugs also have more rapid clearance. It is therefore not sur-
prising that NNRTI resistance is seen more often than PI or
NRTI resistance. Reported mutations to NNRTIs, NRTIs,
PIs, Entry and Integrase Strand Transfer Inhibitors are up-
dated regularly by the International AIDS Society (IAS)-
USA Drug Resistance Group  and can be accessed at
IAS-USA’s website .
5. NON-ADHERENCE TO ANTIRETROVIRAL THE-
RAPY AND ITS IMPACT ON HEALTH CARE COSTS
was associated with lower monthly health costs in a private
managed care program in South Africa, mainly due to
reduced hospital admissions. In contrast, in a U.S. study by
Gardner et al. , better adherence to cART was associated
with higher direct medical costs despite lower rates of
hospitalization in more adherent individuals. The differences
in the relative contribution of cART costs to overall costs
probably accounts for the apparent discrepancy among the
studies conducted in South-Africa (where the cART cost
component accounted only for 9% of total costs) and in the
U.S. (where ART costs represent 60% of total costs). This
hypothesis is supported by the fact that overall health care
utilization was lower in both the South African and U.S.
populations in the setting of better adherence. Other possible
explanations include different study methodology, variations
in the epidemiology of HIV infection, variations in CD4 T-
cell count at initiation of antiretroviral therapy, structural
dissimilarities between health care systems, and differences
in health resources consumption. A retrospective cohort
analysis within the Adherence sub-study of the Italian
Cohort Naïve Antiretroviral (AdICoNA) found that mean
annual hospital expenses were significantly higher for non-
adherent compared to adherent patients (417 1250 Euro vs.
192 670 Euro; p<0.01). Hence, in this cohort, mostly at early
stages of HIV infection and followed-up in Europe, savings
in cART costs were associated with non-adherence and
offset by the increased risk of hospitalization and the rise in
inpatient costs .
Nachega et al.  found that greater adherence to cART
limited and resource-rich settings [71-73]. The data discus-
sed above showed that in resource-limited settings, where
cART comprises a smaller proportion of overall health care
costs, excellent adherence to antiretroviral therapy is cost
saving . In resource rich settings, better adherence
decreases health care utilization, but is not cost saving .
However, it is important to note that no formal cost-
effectiveness analyses of adherence to antiretroviral therapy
have been completed to date. When cost-utility and cost
savings that are unmeasurable in system-level studies are
taken into account, it is very likely that adherence to
antiretroviral therapy will be cost-effective in all settings.
Indeed, in United States, the cost-effectiveness of a weekly
home visit nursing intervention on antiretroviral adherence
(for as much as $1,000 per person) using data from a ran-
domized controlled clinical trial as input to a computer-based
state transition model of HIV disease, showed that the in-
cremental cost-effectiveness ratio was $14,100 per quality-
adjusted life year gained compared with standard care.
Therefore, adherence interventions with modest effective-
ness are likely to provide long-term survival benefit to pa-
Antiretroviral therapy is cost-effective in resource-
HIV Treatment Adherence, Drug Resistance, Virologic Failure Infectious Disorders – Drug Targets, 2011, Vol. 11, No. 2 171
tients and to be cost-effective compared with other uses of
HIV care funds .
6. MEASURING ANTIRETROVIRAL THERAPY AD-
studies have empirically studied adherence measurement
tools [75-78]. Common methods of adherence measurement
include pill counts, pharmacy record reviews, self-report
measures, electronic monitoring and therapeutic drug moni-
toring (TDM) [79-80]. To date, there is not a universally
accepted tool to measure cART adherence, since each
method has distinct advantages and disadvantages including
cost, complexity, accuracy, intrusiveness and bias (Table 1).
Oyugi et al.  evaluated different adherence measurement
tools including patient self-report, pill count and MEMS
caps, which is an electronic monitoring system. In this pilot
study they found excellent agreement between the three
measurement tools in a Ugandan HIV cohort with docu-
mented high levels of cART adherence. In contrast, Gill et
al.  found large discrepancies among estimated adher-
ence for different methods when reviewing several cohorts in
resource-limited settings. They constructed a relative hierar-
chy of adherence measurement methods, and reported that
Although adherence is of critical clinical importance, few
physician assessment and self-report were the least accurate,
pill counts were intermediate, and electronic monitoring pro-
vided the most accurate surrogate of cART adherence. This
is similar to the conclusions from a U.S. study which deter-
mined that MEMS underestimated adherence while pill
counts and patient self-report overestimated adherence .
of adherence in a real-life setting, studies of adherence typi-
cally rely on limited assessment of criterion-related forms of
validity such as predictive or concurrent validity. That is, in
most cases, validation of an adherence measure is based on
how strongly the measure is associated with virologic or
other laboratory and clinical outcomes or how well a particu-
lar measure compares to other adherence measures .
While the ability of measures to predict virologic outcomes
is important, it is problematic when the measure is not in fact
assessing behavior. For example, if an individual fails ther-
apy due to acquisition of resistant virus, interventions to im-
prove adherence behavior will not be relevant. In addition,
some have argued that virologic failure is an inadequate in-
dicator of non-adherence, as several other factors (e.g., viral
load level at initiation of cART, potency of the therapy pre-
scribed, individual differences in absorption, and drug inter-
actions) also influence virologic outcomes.
As there is currently no gold standard objective measure
Table 1. Antiretroviral Therapy Adherence Monitoring Tools: Accuracy, Advantages and Disadvantages
Detection of Ad-
Setting of Use Cost
Specific, Very Insensitive.
Clinical Practice &
Pharmacy Refill or Claim
Specific, Fairly Sensitive &
No Could be
Announced or Unannounced
Fairly Specific, Fairly Sensi-
tive, Fair Reliability
Caps (MEMS caps)
Specific, Too Sensitive &
Yes No Research High
Electronic Web-Enabled Pill
(Med-eMonitor; Wise Pill;
Specific, Too Sensitive Yes Yes Research High
Directly Observed or Admin-
Specific, Sensitive and Reli-
Monitoring of Antiretroviral
Drug Concentration (Blood,
Urine, Hair, etc.)
Specific, Sensitive, Reliable Yes Yes Research High
172 Infectious Disorders – Drug Targets, 2011, Vol. 11, No. 2
Nachega et al.
used cART adherence measurement tools in resource-limited
settings. These tools can be useful over and above their util-
ity in alerting providers to the need for adherence interven-
tion. Indeed, Bisson et al.  reported that pharmacy refill-
based adherence levels outperformed CD4 T-cell count
changes as a predictor of virologic failure in the first year
following cART initiation for patients in Cape Town, South
Africa, enrolled in the private sector Aid for AIDS disease
management program. In light of this success, there is a need
for of the practical implementation of novel, feasible, and
cost-effective adherence monitoring tools capable of captur-
ing real-time adherence behavior, which are useful in both
resource-limited and resource-rich settings and useful for
routine application in clinical care and research studies .
Further development of these tools for real-world real-time
adherence assessment, linked with interventions to improve
adherence when necessary, require further study and will be
critically important to the long-term successful utilization of
currently available antiretroviral medications.
Self-report or pharmacy refills are the most commonly
in the success or failure of therapy for HIV infection. Many
barriers to adherence exist and many are shared by devel-
oped and developing world settings. No single method for
measurement or estimation of adherence has been widely
accepted. Further, the relation between adherence and treat-
ment outcomes is complex and likely varies by drug and
maybe even by individual. Identifying a simple and afford-
able method for accurately measuring adherence will facili-
tate the development of effective, pre-emptive adherence
interventions. If applied widely, these interventions will
likely prove to be cost-effective in reducing morbidity and
mortality when treating large populations in both resource-
rich and resource-limited settings.
Adherence to antiretroviral treatment plays a crucial role
for Allergy and Infectious Disease (NIAID-NIH), Division
of AIDS (DAIDS): K23 AI 068582-01(JBN); and The Euro-
pean Developing Countries Clinical Trial Partnership
(EDCTP) Senior Fellowship Award: TA-08-40200-021
(JBN); the National Institute for Allergy and Infectious Dis-
ease: T32 AI007438-16 and L30 AI080268-02 (SYH); the
NIAID-NIH K01-AI067063 (EMG); the NIMH-NIH R34
MH083592-01A1 (EJM); P30 AI45008 and Agency for
Health Research and Quality (AHRQ) U18 HS016946 (RG).
Funding Sources: The United States National Institutes
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Received: April 02, 2010 Accepted: August 10, 2010