A pilot study of Screening, Brief Intervention, and Referral for
Treatment (SBIRT) in non-treatment seeking smokers with HIV
Karen L. Cropseya,⁎, Peter S. Hendricksa, Bianca Jardinb, C. Brendan Clarka, Nandan Katiyara, James Williga,
Michael Mugaveroa, James L. Rapera, Michael Saaga, Matthew J. Carpenterb
aUniversity of Alabama at Birmingham, USA
bMedical University of South Carolina, USA
H I G H L I G H T S
• People living with HIV/AIDS report a lower motivation to quit smoking.
• Providing NRT to unmotivated smokers has been shown to be effective.
• This pilot study provided NRT to unmotivated smokers living with HIV/AIDS.
• This pilot study shows the feasibility of an SBIRT model in a busy HIV/AIDS clinic.
a b s t r a c ta r t i c l ei n f o
Introduction: PLHIV have higher rates of smoking and lower motivation to quit smoking; thus to impact
smoking rates, cessation interventions need to be acceptable to a wider range of PLHIV smokers as well as
feasible to implement in a busy clinical setting. The purpose of this study was to evaluate the acceptability,
feasibility, and effects of a Screening, Brief Intervention, and Referral for Treatment (SBIRT) model in an
HIV/AIDS clinic among a sample of PLHIV.
Methods: PLHIV smokers (N = 40) were randomized at baseline, irrespective of their self-reported discrete
smoking cessation motivation status, to receive either 8-weeks of combination nicotine replacement therapy
(NRT) in conjunction with brief counseling (SBIRT framework) (n = 23)orusualcare(n = 17).Smokingout-
come measures included cigarettes smoked per day, nicotine dependence, smoking urge, and smoking with-
Results: The SBIRT intervention appeared to be acceptable and feasible, and produced medium to large reduc-
tions in cigarettes smoked per day, physical nicotine dependence, smoking urge, and smoking withdrawal
symptoms, even for smokers not ready to quit within 6 months.
Conclusions: Findings provide preliminary support for the integration of an SBIRT model in an HIV/AIDS clinic
setting to screen and provide active treatment to all smokers, regardless of readiness to quit smoking. Given
the high prevalence and incredible health burden of continued smoking in this population, identifying brief
and effective interventions that are easily translated into clinical practice represents an enormous challenge
that if met, will yield significant improvements to overall patient outcomes.
© 2013 Elsevier Ltd. All rights reserved.
In the U.S., 40–70% of people living with HIV/AIDS (PLHIV) are cur-
rent smokers, a striking disparity compared with a national prevalence
estimate of 21% in the general population (Benard et al., 2007;
Burkhalter, Springer, Chhabra, Ostroff, & Rapkin, 2005; Crothers et al.,
2005; Durazzo et al., 2007; Elzi et al., 2006; Lifson et al., 2010; Nahvi
& Cooperman, 2009; Niaura et al., 2000; Webb, Vanable, Carey, &
Blair, 2007). Medical advances in the treatment of HIV have resulted
in substantial increases in life expectancy among PLHIV (Lau, Gange,
& Moore, 2007; Lifson et al., 2010; Palella et al., 2006) and as a con-
sequence PLHIV smokers are now, more than ever, at heightened risk
for tobacco-related health harms. Continued smoking among PLHIV
is associated with numerous adverse health outcomes, including bacte-
rial and opportunistic infections, pneumonia, Chronic Obstructive
Pulmonary Disease (COPD), emphysema, lung cancer, and increased
all-cause mortality (Crothers et al., 2005; Durazzo et al., 2007; Elzi
Addictive Behaviors 38 (2013) 2541–2546
⁎ Corresponding author at: Department of Psychiatry & Behavioral Neurobiology,
University of Alabama at Birmingham, 401 Beacon Parkway West, Birmingham, AL
35209, USA. Tel.: +1 205 917 3786x205; fax: +1 205 943 0853.
E-mail address: firstname.lastname@example.org (K.L. Cropsey).
0306-4603/$ – see front matter © 2013 Elsevier Ltd. All rights reserved.
Contents lists available at SciVerse ScienceDirect
et al., 2006; Fiore et al., 2008; Lifson et al., 2010; Niaura et al., 2000;
Pines, Koutsky, & Buskin, 2011; Rahmanian et al., 2011).
quality of life (Crothers et al., 2005; Ingersoll, Cropsey, & Heckman,
2009), increased pain (Turner et al., 2001), and diminished cognitive
functioning (Turner et al., 2001). Moreover, both uncontrolled HIV
infection and antiretroviral therapy may confer an elevated risk for
cardiovascular disease that is further exacerbated by cigarette use
(Elzi et al., 2006; Lifson et al., 2010).
Despite scientific advances contributing to longer life expectancy
in PLHIV (Niaura et al., 2000), many PLHIV continue to feel that
they will not live long enough to reap the health benefits associated
with smoking cessation (Burkhalter et al., 2005; Mamary, Bahrs, &
Martinez, 2002; Reynolds, Neidig, & Wewers, 2004). In addition,
PLHIV smokers are a population who face unique barriers to smoking
cessation, such as comorbid drug and alcohol use and mental illness
(Bing et al., 2001), lower socioeconomic status (Diaz et al., 1994;
Karon, Fleming, Steketee, & De Cock, 2001), lower quality of life
(Fang, Hsiung, Yu, Chen, & Wang, 2002), inadequate social support
(Gostin & Webber, 1998), and reliance on cigarettes to cope with
the stress associated with their illness (Reynolds et al., 2004). In addi-
tion to patient barriers, few HIV providers have received training
to treat tobacco dependence (Shuter, Bernstein, & Moadel, 2012)
and less than half of HIV providers reported assessing tobacco use
and dependence among their patients (Tesoriero, Gieryic, Carrascal,
& Lavigne, 2010). However, 94% of HIV providers indicated that they
would be willing to provide smoking cessation services, but 65%
believed that patient resistance was their primary barrier to doing
so. A study conducted at several HIV clinics in New England found
that only 20% of PLHIV smokers were considering quitting in the
near future (Niaura et al., 2000). This stands in stark contrast to the
high levels motivation to quit noted in the general population of
smokers, almost 50% of whom are attempting to quit smoking at
any given time (Herzog & Blagg, 2007).
To produce significant changes in smoking rates in the PLHIV
population, cessation studies will need to be both acceptable to the
larger segment of PLHIV smokers who are not interested in receiving
treatment as well as feasible to implement in busy HIV clinics. With
the exception of one study that recruited motivated and unmotivated
PLHIV smokers (Lloyd-Richardson et al., 2009), previous studies have
provided intensive treatments to PLHIV seeking treatment to quit
smoking (Cummins, Trotter, Moussa, & Turham, 2005; Elzi et al.,
2006; Ingersoll et al., 2009; Lloyd-Richardson et al., 2009; Vidrine,
Arduino, Lazev, & Gritz, 2006; Vidrine, Marks, Arduino, & Gritz,
2012; Wewers, Neidig, & Kihm, 2000). However, providing cessation
services, including nicotine replacement therapy, to non-treatment
seeking smokers from the general population has been shown to
increase quit attempts and cessation rates (Carpenter et al., 2011).
In addition, while screening individuals seeking medical care in
primary care and specialty settings for cigarette use is becoming more
routine (Aveyard, Begh, Parsons, & West, 2012; Fiore et al., 2008), provi-
sion of smoking cessation interventions is generally only provided to
smokers expressing motivation to make a cessation attempt (Fiore et al.,
at the time of their medical visit are generally provided no active inter-
vention other than brief physician advice to quit (Fiore et al., 2008).
lic health model for the screening of substance abuse and delivery of
low-intensity substance abuse treatments in the primary care setting
(Babor et al., 2007). SBIRT is particularly well-suited to HIV settings,
since both PLHIV, as well as providers, are focused on HIV disease man-
until tobacco-related illness is detected or until the patient expresses in-
terest in quitting. Because detection and treatment of cigarette use prior
to the onset of smoking-related disease are critical to PLHIV smokers,
the evaluation of SBIRT among PLHIV smokers warrants consideration.
The current investigation was a pilot study designed to evaluate
the acceptability, feasibility, and effects of integrating the SBIRT
model in a busy HIV clinic among PLHIV smokers who were random-
ized to either the SBIRT model or usual care (described later) for
smoking cessation. The intervention chosen for this study was predi-
cated on the notion that motivation to quit smoking varies on a
moment-to-moment basis (e.g., Hughes, Keely, Fagerstrom, & Callas,
2005; Peters & Hughes, 2009), and therefore: 1) interest in quitting
when a patient is in clinic should not be required for the provision
of an active smoking cessation intervention; and 2) some sort of quit
aid (e.g., pharmacotherapy) should be readily available when motiva-
tion to quit is high, which is likely to occur outside of the clinic setting.
Participants in the SBIRT model of the current study were therefore
provided with two forms of nicotine replacement therapy for use
at their own discretion and brief smoking cessation counseling
irrespective of their motivational status at baseline. It was hypothe-
strate a decrease in cigarette consumption, nicotine dependence, urge
ing usual care. Furthermore, to examine motivation to quit, we evalu-
ated the relationship between the Stages of Change algorithm (Etter &
Perenger, 1999; Herzog, 2008; Herzog & Blagg, 2007; Prochaska &
DiClemente, 1983; West, Hajek, Stead, & Stapleton, 2005), which cat-
egorizes smokers into discrete motivational stages, and smoking out-
comes. In the transtheoretical model, individuals are believed to cycle
through stages of readiness to quit including: precontemplation (not
even thinking of quitting smoking), contemplation (wanting to quit
but not ready to engage in a quit attempt), preparation (in anticipa-
tion of quitting, starting to make changes, e.g., telling friends and fam-
ily), action (actively engaging in a quit attempt), and maintenance
(quit smoking and trying to prevent relapse). Under the Stage of
Change model, individuals who are further along on the model (e.g.,
contemplation or preparation) are believed to be more likely to suc-
cessfully make the change than individuals in an earlier stage of the
model (e.g., precontemplation; Prochaska & DiClemente, 1983). It
was hypothesized that participants' discrete motivational stage at
the time of their clinic visit would not significantly impact their
smoking behavior at follow-up time points.
2.1. Participant eligibility and recruitment
Participants were recruited through the UAB HIV Clinic, which
is the largest HIV clinic in Alabama. Potential participants, self-
reported smokers, were approached between July, 2011 and October,
2011 for participation. Participants who smoked at least five ciga-
rettes per day and were engaged in HIV care at the clinic were invited
to participate. Participants were excluded from participation if they
had recently quit smoking, were pregnant or breastfeeding, less
than 19 years of age, reported a history of allergic reaction or sensitiv-
ity to nicotine replacement, were non-English speaking, or were in
too poor of health to safely use nicotine replacement.
Of the 92 individuals who were approached, 83 were eligible to
participate, and 40 enrolled in the study (48%). Enrolled participants
included 23 participants in the SBIRT treatment condition and 17 in
the usual care comparison condition and were assigned to groups
using a random numbers table. Overall, 19 (47.5%) participants
were male, 23 (57.5%) were Black, and the average age was 44.5
(SD = 9.9) years old. Of the 52 individuals who did not participate,
17 (33%) reported that it was too far to drive to the clinic for extra
visits, 15 (29%) initially scheduled an appointment but did not show
for their baseline assessment, 11 (21%) reported no interest in par-
ticipating in the research study, seven (13%) were no longer smoking,
one (2%) was medically excluded by their provider, and one (2%) was
incarcerated at the time of their baseline appointment. Compared to
K.L. Cropsey et al. / Addictive Behaviors 38 (2013) 2541–2546
individuals who declined or were ineligible to participate, a higher
numberof women (52.5%versus 5.8%; p b .001) and African Americans
(59.0% versus 32.7%; p = .012) enrolled in the study. There were no
differences between enrolled and declined participants in age, health
insurance status, substance abuse status, alcohol use, depression, anxi-
ety, viral load, or CD4 count.
As part of the Centers for AIDS Research (CFAR) Network of
Integrated Clinical Systems (CNICS), ongoing computerized patient
reported outcomes (PROs) that included several questions about
current and past smoking behavior were collected every six months
for clinical and research purposes. Potential participants who indicat-
ed current smoking on their most recent PRO assessment were
initially identified through a computer search. Research staff were
given a list of potential enrollees who were scheduled for upcoming
routine office visits, and approached these individuals during their
clinic appointment for consent and enrollment in the study. Enrolled
participants completed additional baseline measures either the day
of their clinic visit or during a mutually convenient return visit to the
clinic. After completing baseline measures, participants were randomly
assigned to either the usual care condition or the SBIRT model. The
usual care condition was a no-treatment control other than standard
HIV medical care, including regular HIV treatment with their provider.
Participants in the usual care condition received no smoking cessation
intervention from the research team and were only required to com-
ine and drug screens, and a breath sample to measure expired carbon
monoxide (eCO) at time intervals that corresponded to the treatment
condition (i.e., baseline, two weeks, four weeks, and eight weeks).
The SBIRT intervention was eight weeks in length and incorporated
the same follow-up schedule as above (e.g., assessment at baseline,
two weeks, four weeks, and eight weeks). At each of the first three visits
(through week four), participants were provided enough free nicotine
replacement treatment (NRT; combination 14 mg patches and 2 mg
lozenges to use together or separately) to last until their next visit. A
bachelor's level research assistant provided a one time, brief, individual
20-minute informational session about the importance of quitting or re-
ducing smoking, techniques for cutting down, and strategies for relapse
prevention. Participants were provided verbal instructions on the use
of NRT, including how to use the two forms of NRT together, and told
that they could use the products for a variety of purposes, including to
quit smoking, reduce cigarette use, or to use in situations where they
cannotsmoke(e.g.,public places).Theresearchassistantand participant
collaboratively problem-solved around barriers of NRT use, and dis-
cussed possible problems that may interfere with quit attempts, if the
participant did decide to try and quit. In addition, all intervention par-
ticipants were given a workbook which included a daily smoking diary,
behavioral techniques used to quit or reduce smoking, and tips for over-
er, etc.). The workbook was modified from the treatmentprogram used
& Crews, 2012). All participants, regardless of condition, received
$20.00 for their baseline, week two, and week four appointments, and
$40.00 for their week eight appointment for a potential total of $100
disbursed over eight weeks. This study was approved by the University
of Alabama at Birmingham Institutional Review Board.
PROs included basic smoking information (smoking status and
number of cigarettes smoked per day), clinical markers of HIV disease,
adherence to antiretroviral medication, depression and anxiety scores,
and substance abuse screening questions (Kitahata et al., 2008). PROs
are collected through an open-source, web-based software system
using touchscreen desktop computers. This method has been used
with success for several years at the study site, even with patients
with very limited prior computer experience, in a high volume, clinical
setting (Crane et al., 2007; Lawrence et al., 2010). For the purposes
of this study, the participant's most recent PRO was combined with
their baseline measures to reduce burden. PRO information provided
to investigators included the participant's basic demographics, most
recent responses for alcohol use (Alcohol Use Disorders Identification
Test; AUDIT-C), history of substance abuse (ASSIST), CD4 count, viral
load, and the Patient Health Questionnaire (PHQ-9) scales for depres-
sion (PHQ-9D) and anxiety (PHQ-A). The PHQ scales were dichoto-
mized due to the limited number of participants and the frequency of
responses. Additionally, viral load was dichotomized into detectable
(>50 copies/mL) and undetectable (b50 copies/mL), in accordance
with clinical use of this biomarker.
At each appointment, participants were given the Fagerström
Test for Nicotine Dependence (FTND; Heatherton, Kozlowski, Frecker,
& Fagerström, 1991), the Questionnaire of Smoking Urges-Brief Form
(QSU;Tiffany & Drobes,1991),and the MinnesotaNicotine Withdrawal
Scale-Revised (MNSW-R; Hughes & Hatsukami,1986).Participants also
answered questions about their smoking history including cigarettes
smoked per day (cpd), length of time smoking, and previous number
of quit attempts, and completed the Stage of Change-Short Form
(SOC-SF; DiClemente et al., 1991). Finally, participants exhaled into a
monitor for an eCO test and provided a urine sample for cotinine and
drug screening at every time point.
2.4. Data analysis
ANOVA and chi-square analyses were used to determine equiva-
lence between groups on baseline characteristics. A repeated measures
ANCOVA was then used to compare treatment conditions across ciga-
for significant covariates. As this was a pilot study designed to evaluate
the acceptability and feasibility of the experimental intervention, as
well as to estimate its effects (i.e., rather than detect statistically signif-
icant differences between the treatment and comparison conditions),
effect size was the primary outcome of interest. Eta-squared (η2) was
used a measureof effect with.01, .06, and .14 representingsmall, medi-
um, and large effects, respectively (Cohen, 1998). To estimate the
impactofdiscrete motivationalstatusontheeffects of treatmentcondi-
tion, a baseline question from the SOC-SF was dichotomized into inten-
tion to quit within 30 days or 6 months or more (which included one
person who reported no intention to quit smoking). This process
yielded four groups (SBIRT group/30 days; SBIRT group/6 months;
usual care/30 days; usual care/6 months) that were compared on
smoking outcomes. One person from the usual care group was dropped
due to incomplete data on most measures. Five treatment completers
had missing data points on one or more of these scales. We imputed
these missing data points via average of the scale on the previous and
subsequent weeks. Eleven individuals did not complete all sessions.
We conducted an intent-to-treat analysis and carried forward their
last values to be able use the total sample of 39 individuals. However,
4 individuals did not have baseline measures of anxiety, which was a
significant covariate, and were dropped. Thus, the retained sample
consisted of 21 SBIRT and 14 usual care participants. We also analyzed
the data with only completers (28 total; 14 in each group) and found
a similar pattern of results. All analyses were conducted using IBM
SPSS Statistics 20.
3.1. Baseline comparisons between SBIRT versus usual care
There were no differences between the SBIRT and usual care groups
in terms of age, gender, race, viral load, CD4 count, health insurance
K.L. Cropsey et al. / Addictive Behaviors 38 (2013) 2541–2546
status, age of first cigarette, age of smoking daily, smoking dependence,
number of cigarettes smoked daily, or depressive symptoms. However,
the SBIRT group was more likely to report anxiety symptoms (38.1%
versus 7.1%, p = .040) aswell ashistory of substanceabuse (68.8% ver-
sus 39.1%, p = .038). These variables were entered into the repeated-
measures ANOVA as covariates.
3.2. Comparison between treatment completers and noncompleters
Individuals who completed all sessions (treatment completers;
N = 28; 14 in each condition) and noncompleters (N = 12) were
comparable on most demographic and other baseline characteristics
with the exception that treatment completers were more likely to be
women (64.3% versus 25.0%; p = .023), Black (71.4% versus 27.3%;
p = .012), and smoke fewer cigarettes per day at enrollment
(means = 14.6 vs. 25.5, p = .004).
3.3. Smoking outcomes
Fig. 1 (panels A–D) illustrate the effects of treatment condition on
smoking outcomes. As indicated in the figures, the SBIRT group
reported: fewer cigarettes smoked per day (η2 = .07; p = .13); lower
physical nicotine dependence (η2 = .18, p = .01) and a greater rate
of decreasing physical dependence across time (η2 = .14, p = .005);
lower smoking urge (η2 = .16, p = .01) and a greater rate of decreas-
ing smoking urge across time (η2 = .11, p = .02) compared to the
usual care group. Rate of change in cigarettes smoked per day did not
appear to differ between the SBIRT and usual care conditions (η2 =
.007, p = .71); however withdrawal symptoms (η2 =.07, p = .13)
and withdrawal symptoms across time (η2 = .02, p = .51) both dem-
onstrated small to medium effect size differences between the two
3.4. Discrete motivational stage and smoking outcomes
Discrete motivation status had a minimal effect on SBIRT condition
for cigarettes smoked per day across time (η2 = .02, p = .95).
However, a medium effect size was shown for level of nicotine depen-
dence across time (η2 = .16, p = .09), with individuals in both SBIRT
arms decreasing their level of nicotine dependence, regardless of
their readiness to quit compared to the usual care group. Similarly,
a medium effect size was shown for smoking urges (η2 = .15,
p = .13), with both SBIRT groups, regardless of readiness to quit,
reporting less smoking urges. Finally, a medium effect size is seen for
groups across time for withdrawal symptoms (η2 = .06, p = .78),
with participants who received SBIRT who did want to quit for at least
6 months or more demonstrating the greatest reductions in nicotine
The current research was a pilot study designed to evaluate the
feasibility, acceptability, and effects of an SBIRT intervention, includ-
ing the provision of combination NRT regardless of readiness to quit
Fig. 1. Treatment versus usual care on measures of smoking. Note: Scale scores are labeled along the Y axis while the weeks are shown across the x axis.
K.L. Cropsey et al. / Addictive Behaviors 38 (2013) 2541–2546
smoking, among PLHIV smokers engaged in HIV medical care. The
SBIRT treatment appeared both feasible and acceptable as evidenced
by rapid recruitment (3 participants per week representing 48% of
eligible participants) and high retention of participants (70% com-
pleted all sessions). This rate of recruitment is higher than in most
clinical trials for smoking cessation. For example, in an examination
of clinical enrollment in a clinical trial for smoking cessation, Dahm
et al. (2009) found that only 33% of screened individuals were eligible
for enrollment and, of eligible participants, only 37% were subse-
quently enrolled in a standard clinical trial for smoking cessation.
Our eligibility rate of over 90% and subsequent enrollment of almost
50% of eligible participants exceeds most clinical trials, suggesting
that this approach is both acceptable and feasible to implement
widely in primary care.
In addition to high acceptability and feasibility, we observed
important clinical changes resultingfrom this intervention.Specifically,
participants in the SBIRT intervention demonstrated lower levels of
cigarette use, physical nicotine dependence, urges to smoke, and with-
drawal symptoms. Interesting, while the self-reported rate of cpd
declined for both SBIRT and usual care groups across time, FTND, QSU,
and MNWS all remained elevated across time for the usual care group.
Thus, the overall pattern of results suggests moderate to strong effects
of the SBIRT condition relative to the usual care condition. Moreover,
study findings are also consistent with other studies that have also
found support for the clinical utility of NRT in PLHIV (Cummins et al.,
2005; Elzi et al., 2006; Wewers et al., 2000).
The initial evidence from this pilot indicates that provision of an
active treatment, regardless of the participant's self-reported discrete
smoking cessation motivational status at baseline, was effective in
bringing about reported changes to smoking behaviors including
decreased cigarette use, dependence, craving, and withdrawal. These
findings confirm more recent evidence suggesting that active interven-
tions can be provided to all individuals regardless of their stage of
change (Carpenter, Alberg, Gray, & Saladin, 2010; West et al., 2005).
Indeed, a recent meta-analysis of the efficacy of stage-based in-
terventions demonstrated little benefit of stage-based interventions
over non-stage-based treatments (Cahill, Lancaster, & Green, 2010).
The particular treatment approach used in the current study was
unique and carries important implications for implementation in
routine clinical practice settings. Unlike many existing interventions
(e.g., Elzi et al., 2006), the SBIRT model of treatment of the current
study did not distribute NRT in the context of extended counseling,
which may boost its transportability into busy clinical care settings.
For instance, NRT can be provided with minimal behavioral instruc-
tion, with more detailed tips for quitting provided in accompanying
literature. This SBIRT model of treatment could significantly extend
treatment to all smokers, regardless of self-reported motivation
to make behavioral changes, which would be a similar treatment
model applied to other chronic diseases (e.g., hypertension, diabetes).
Using SBIRT in this setting to identify and treat smokers was not time
intensive, costly, or dependent on the skills of a highly trained tobac-
co treatment specialist. If these pilot data are successfully replicated
in a larger clinical trial, any healthcare provider (physician, nurse, social
worker, intakecoordinator) or non-healthcareprovider(e.g., bachelor's
levelassistant, aswasthecaseinthis study) could implementtheinter-
vention in a few minutes, especially since select NRT products are gen-
erally well-tolerated, safe, and available without a prescription.
While the preliminary results of this study suggest that this
approach was acceptable, feasible, and efficacious, it is important to
recognize the limitations inherent in the current design. First, consis-
tent with a pilot design, the sample size was small. As a result, our
study was not powered on clinical outcomes of more direct interest
such as quit attempts and cessation. While we acknowledge this as
a limitation, we also believe it is always necessary to first demonstrate
the feasibility of an approach before expending the vast amount of
resources typically required for a cessation study (Carpenter et al.,
2010). Moreover, while we did not focus exclusively on quit attempts
and cessation, we did use well-established proxy measures of the latter
outcomes (Vangeli, Stapleton, Smit, Borland, & West, 2011). Nonethe-
less, future randomized controlled trials employing larger samples
and longer follow-up periods will be necessary to examine the efficacy
of this intervention on quit attempts and ultimate cessation. Second,
while we assumed that allowing participants to use NRT for whatever
function they desired (e.g., to quit, cope with smoking restrictions)
would result in recruiting a more representative sample across the
motivationalspectrum, we cannot definitivelyconclude thatindividuals
who elected to not enroll in this study would have been as likely to
engage in use of these products for cessation, reduction, or to use in
smoking-restricted areas. However, based on the routine clinical mea-
sures collected in clinic, those who elected to not enroll in the trial
were similar to participants on key measures of substance use, mental
health, and HIV clinical markers although other important differences
that we did not measure may have been present. Finally, while we did
track provision of NRT, we did not closely monitor how or for what
purpose participants elected to use these products. However, whether
the person used the product in a way to promote cessation was not
evant. While a future study will monitor how the products were used,
the results of this study demonstrated that provision of these products,
regardless of how they were used, still brought about desired effects.
In sum, the prevalence of cigarette use among PLHIV is alarmingly
high and linked with a number of severe health problems. With con-
tinued improvements in HIV treatment and care, PLHIV smokers will
benefit more than ever from smoking reduction and/or abstinence.
At present, however, there is a lack of well-controlled studies to ex-
amine the impact of smoking cessation treatments among PLHIV.
While further research is needed, the preliminary results of the cur-
rent study suggest that use of an SBIRT framework for providing a
brief informational session plus NRT in HIV clinics, regardless of read-
iness to change smoking behavior, is a promising approach. If proven
efficacious, this relatively simple model has strong potential for wide-
spread dissemination that could substantively advance improved
health and clinical outcomes for this patient population.
Role of funding sources
Dr. Cropsey was supported by grant R01CA141663 and the funding from this study
was provided by the Centers for AIDS Research (CFAR).
Dr. Hendricks was supported by grant R34DA031936.
Dr. Carpenter was supported by grant K23DA020482.
Dr. Mugavero has received consulting fees (advisory board) from Bristol-Myers
Squibb, Gilead Sciences and Merck Foundation, and grant support (to UAB) from
Bristol-Myers Squibb, Pfizer, Inc, Tibotec Therapeutics, and Definicare, LLC.
Drs. Cropsey and Carpenter designed the study and Mr. Katiyar wrote the protocol.
Mr. Katiyar and Drs. Jardin, Hendricks, and Cropsey conducted literature searches. Drs.
Cropsey, Clark, and Hendricks conducted the statistical analysis. Drs. Cropsey and
Jardin wrote the first draft of the manuscript and all authors contributed to and have
approved the final manuscript.
Conflict of interests
None of the authors has any conflicts of interest or competing interests to declare.
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