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Nature and Role of Change in Anxiety Sensitivity During NRT-Aided Cognitive-Behavioral Smoking Cessation Treatment

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This study evaluated the associations between change in anxiety sensitivity (AS; fear of the negative consequences of anxiety and related sensations) and lapse and relapse during a 4-week group NRT-aided cognitive-behavioral Tobacco Intervention Program. Participants were 67 (44 women; M (age) = 46.2 years, SD = 10.4) adult daily smokers. Results indicated that participants who maintained high levels of AS from pretreatment to 1 month posttreatment, compared to those who demonstrated a significant reduction in AS levels during this time period, showed a significantly increased risk for lapse and relapse. Further inspection indicated that higher continuous levels of AS physical and psychological concerns, specifically among those participants who maintained elevated levels of AS from pre- to posttreatment, predicted significantly greater risk for relapse. Findings are discussed with respect to better understanding change in AS, grounded in an emergent taxonic-dimensional factor mixture model of the construct, with respect to lapse and relapse during smoking cessation.
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Nature and Role of Change in Anxiety
Sensitivity During NRT-Aided Cognitive-
Behavioral Smoking Cessation
Treatment
Yaara Assayag a , Amit Bernstein b , Michael J. Zvolensky b , Dan
Steeves c & Sherry S. Stewart d
a University of Haifa, Haifa, Israel
b The University of Vermont, Burlington, VT, United States
c Capital Health Addiction Prevention and Treatment Services,
Halifax, Canada
d Dalhousie University, Halifax, Canada
Published online: 01 Mar 2012.
To cite this article: Yaara Assayag , Amit Bernstein , Michael J. Zvolensky , Dan Steeves &
Sherry S. Stewart (2012) Nature and Role of Change in Anxiety Sensitivity During NRT-Aided
Cognitive-Behavioral Smoking Cessation Treatment, Cognitive Behaviour Therapy, 41:1, 51-62, DOI:
10.1080/16506073.2011.632437
To link to this article: http://dx.doi.org/10.1080/16506073.2011.632437
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Nature and Role of Change in Anxiety Sensitivity
During NRT-Aided Cognitive-Behavioral Smoking
Cessation Treatment
Yaara Assayag
1
, Amit Bernstein
2
, Michael J. Zvolensky
2
, Dan Steeves
3
and
Sherry S. Stewart
4
1
University of Haifa, Haifa, Israel;
2
The University of Vermont, Burlington, VT, United
States;
3
Capital Health Addiction Prevention and Treatment Services, Halifax, Canada;
4
Dalhousie University, Halifax, Canada
Abstract. This study evaluated the associations between change in anxiety sensitivity (AS; fear of the
negative consequences of anxiety and related sensations) and lapse and relapse during a 4-week
group NRT-aided cognitive-behavioral Tobacco Intervention Program. Participants were 67 (44
women; M
age
¼46.2 years, SD ¼10.4) adult daily smokers. Results indicated that participants who
maintained high levels of AS from pretreatment to 1 month posttreatment, compared to those who
demonstrated a significant reduction in AS levels during this time period, showed a significantly
increased risk for lapse and relapse. Further inspection indicated that higher continuous levels of AS
physical and psychological concerns, specifically among those participants who maintained elevated
levels of AS from pre- to posttreatment, predicted significantly greater risk for relapse. Findings are
discussed with respect to better understanding change in AS, grounded in an emergent taxonic-
dimensional factor mixture model of the construct, with respect to lapse and relapse during smoking
cessation. Key words: smoking; anxiety sensitivity; treatment outcome; smoking cessation
Received 14 June 2011; Accepted 29 September 2011
Correspondence address: Amit Bernstein, PhD, Department of Psychology, University of Haifa, Mount
Carmel, Haifa 31905, Israel, Tel: 972-4-824-9659, Fax: 972-4-824-0966. E-mail: abernstein@
psy.haifa.ac.il
Empirical evidence suggests that anxiety
psychopathology co-occurs with smoking at
rates that exceed those found in the general
nonpsychiatric population (Amering et al.,
1999; Degenhardt, Hall, & Lynskey, 2001; de
Graaf, Bijl, Smit, Vollebergh, & Spijker, 2002;
Goodwin & Hamilton, 2002; Lasser et al.,
2000). Yet, we lack knowledge regarding how
anxiety risk factors relate to smoking behavior
(Zvolensky & Bernstein, 2005).
One cognitive construct that is relevant to
better understanding smoking and anxiety
relations is anxiety sensitivity (AS). Anxiety
sensitivity is implicated in the development
and maintenance of panic and related anxiety
disorders (McNally, 2002). The global AS
construct encompasses lower-order fears of
physical, mental, and publicly observable
anxiety experiences (Zinbarg, Barlow, &
Brown, 1997). This construct has been
conceptualized as a malleable, albeit relatively
stable, individual difference factor related to
sensitivity to aversive internal states (Reiss &
McNally, 1985). Research suggests that AS
increases the risk for more intense anxiety
symptoms and anxiety psychopathology (e.g.,
Schmidt et al., 2010). Notably, AS changes in
response to stressful conditions and clinical
intervention (Bernstein & Zvolensky, 2007).
That is, AS may increase in response to
stressful life events (Marshall, Miles, &
Stewart, 2010) and decrease in response to
certain clinical interventions such as inter-
oceptive exposure and cognitive restructuring
q2012 Swedish Association for Behaviour Therapy ISSN 1650-6073
http://dx.doi.org/10.1080/16506073.2011.632437
Cognitive Behaviour Therapy Vol 41, No 1, pp. 51–62, 2012
Downloaded by [Dalhousie University] at 08:16 19 July 2013
(Otto & Reilly-Harrington, 1999). Although
numerous studies have found that change in
AS is a key cognitive-based mechanism for
improvement with cognitive-behavioral
therapy for panic disorder and related anxiety
conditions (e.g., Barlow, Craske, Cerney, &
Klosko, 1989; Schmidt & Woolaway-Bickel,
2000; Taylor & Cox, 1998; Westling & Ost,
1999), there has been little study of AS change
processes in smoking cessation. This limi-
tation is unfortunate, as this cognitive factor is
related to important aspects of smoking
behavior. For example, AS is correlated with
smoking motives to reduce negative affect
(Battista et al., 2008; Comeau, Stewart, &
Loba, 2001; Leyro, Zvolensky, Vujanovic, &
Bernstein, 2008; Novak, Burgess, Clark,
Zvolensky, & Brown, 2003; Stewart, Karp,
Pihl, & Peterson, 1997; Zvolensky, Bonn-
Miller, Bernstein, & Marshall, 2006) and
outcome expectancies for negative affect
reduction (e.g., beliefs such as smoking will
reduce negative affect; Brown, Kahler, Zvo-
lensky, Lejuez, & Ramsey, 2001; Gregor,
Zvolensky, McLeish, Bernstein, & Morissette,
2008). Other work suggests that higher levels
of AS may amplify or maintain the effects of
acute nicotine withdrawal (Marshall, John-
son, Bergman, Gibson, & Zvolensky, 2009;
Vujanovic & Zvolensky, 2009), especially in
the context of elevated state anxiety (Johnson,
Stewart, Rosenfield, Steeves, & Zvolensky, in
press). Moreover, high AS smokers, compared
to low AS smokers, perceive the prospect of
quitting as more difficult (Zvolensky et al.,
2007c) and show less success in quitting
(Brown, et al., 2001; Mullane et al., 2008;
Zvolensky et al., 2007a; Zvolensky, Bonn-
Miller et al., 2006; Zvolensky, Stewart,
Vujanovic, Gavric, & Steeves, 2009b).
Notably, research is yet to evaluate the
nature of change in AS and its relation to
lapse/relapse within evidenced-based smoking
cessation intervention. To evaluate the role(s)
of AS change with respect to smoking
cessation, it is necessary to consider its latent
structure. Factor analytic study has generally
documented that AS may be composed of a
global, higher-order factor with a number of
lower-order facets including physical, psycho-
logical, and social concerns (Zinbarg et al.,
1997). Several taxometric studies have found
that AS may be a taxonic (dichotomous latent
class variable) structure, composed of two
categorically discrete latent AS groups or
forms of AS: a high-risk group or maladaptive
form of AS (approximately 9% 18% of the
general population) and a low-risk group or
normative form of AS (approximately 82%
91% of the general population; e.g., Bernstein,
Leen-Feldner, Kotov, Schmidt, & Zvolensky,
2006; Bernstein, Zvolensky et al., 2006;
Schmidt, Kotov, Lerew, Joiner, & Ialongo,
2005). However, other taxometric work has
failed to detect taxonicity, suggesting that AS
may be dimensional (Asmundson, Weeks,
Carleton, Thibodeau, & Fetzner, 2011; Bro-
man-Fulks et al., 2008, 2010). Research
integrating taxometric and exploratory and
confirmatory factor analytic methods has
found that individual differences within each
taxometrically-derived taxonic latent AS class
(i.e., within-class variability) demonstrate
dimensional latent individual differences
(Bernstein et al., 2007). Moreover, factor
mixture modeling (FMM; Bernstein et al.,
2010; Muthe
´n, 2008)
1
has provided empirical
evidence for a taxonic-dimensional model of
AS.
Overall, research on the latent structure of
AS appears to suggest that associations
between AS and smoking cessation outcome
may function as a taxonic, dichotomous two-
class variable, and that each categorical class
demonstrates a unique within-class, multi-
dimensional factor structure. It is important
that the operational definition of AS and
vulnerability for poor smoking cessation
outcome be linked to the FMM-based
taxonic-dimensional model of AS individual
differences, for a number of reasons, as has
been discussed extensively in the larger
literature on the latent structural study of
psychological constructs (Zvolensky, Bern-
stein, & Johnson, 2009). For example, failure
to distinguish between latent AS classes—only
one of which may be related to risk for poor
smoking cessation outcome—may increase the
probability of observing an attenuated associ-
ation between AS and smoking cessation
outcome. Also, failure to integrate the FMM-
based latent structural model of AS may result
in arbitrary determination of at-risk status as a
function of AS levels at pretreatment as well as
in arbitrary operationalization of clinically
significant change in AS (Bernstein & Zvo-
lensky, 2007; Zvolensky, Johnson, & Bern-
stein, 2009). Clinically, failure to integrate the
52 Assayag, Bernstein, Zvolensky, Steeves and Stewart COGNITIVE BEHAVIOUR THERAPY
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latent structural model of AS with respect to
AS-smoking cessation research may limit
the capacity to guide early identification of
specific individuals at-risk for poor smoking
cessation outcome, and accordingly provide
them with specialized smoking cessation
treatment (Bernstein et al., 2007, 2010;
Zvolensky, Yartz, Gregor, Gonzales, &
Benstein, 2008b). Thus, just as it was essential
for operational definitions of AS to mirror
latent structural study of AS conducted
through factor analysis over the past two
decades, it is no less important for the ongoing
study of AS to similarly reflect emergent latent
structural methods that are now capable of
modeling categorical and continuous individ-
ual differences in AS.
The purpose of the present study was to
better understand the role of change in AS for
smoking cessation outcomes during a com-
munity-based smoking cessation intervention.
We had two interrelated and complementary
aims. First, we sought to empirically docu-
ment the degree of change in AS among adult
smokers receiving smoking cessation treat-
ment—from baseline (prequit) to 1 month
posttreatment (1.5 month postquit day). One
month post-treatment follow-up specifically,
rather than later prospective outcomes, was
evaluated for a number of reasons (e.g.,
limited attrition, accuracy of retrospective
reports over time). Moreover, as reported in
the “Results” section, the observed rates of
lapse and relapse were very high at the 1
month posttreatment time point in the present
study. Thus, long-term follow-up would not
facilitate inclusion of observations (outcomes)
potentially censored at the 1-month time
point. Second, we sought to test the hypothesis
that change in AS would be significantly
associated with lower point-prevalence rates
of lapse and relapse to regular smoking at 1
month posttreatment. This hypothesis was
based on existing theory (Zvolensky &
Bernstein, 2005) and related empirical work
(Brown et al., 2001), suggesting reduced
sensitivity to anxiety may be related to better
cessation outcome and vice versa.
Method
Participants
Participants included 123 daily cigarette
smokers (84 women; M
age
¼45.93 years;
SD ¼10.34) living in the Halifax Regional
Municipality in the Canadian province of
Nova Scotia. Participants were recruited
from a group of adults attending a structured
4-week group Tobacco Intervention Program
offered through Addiction Prevention and
Treatment Services, Capital District Health
Authority. All daily smokers who were
attending the smoking cessation treatment
program were invited to participate in our
study. On the basis of recent FMM findings, at
baseline 85 participants (69%) demonstrated
clinically elevated levels of AS (combined ASI
physical and psychological concerns .12)
(Bernstein et al., 2010) and were thus selected
as the sample of interest for our study—
participants at-risk for poor smoking cessation
outcome as a function of high-AS or
maladaptive levels of AS at pretreatment
(Zvolensky & Bernstein, 2005). Of these 85
participants, 12 registered to participate in
the study but did not engage in treatment
nor attempt to quit, another 5 could not be
successfully contacted at 1 month posttreat-
ment by the research team, and 1 provided
missing data at 1 month posttreatment.
Consequently, a final sample of 67 participants
(44 women; M
age
¼46.2 years; SD ¼10.4)
was included in the present study—individuals
with high AS at pretreatment, who engaged in
treatment and attempted to quit, and who
were successfully contacted by researchers at
posttreatment follow-up.
Participants (N¼67) reported attaining
the following levels of education: 42.4% had
completed high school, 31.8% had completed
college (community college or technical
schooling), 13.6% had completed university
(traditional 4-year schooling), 9.1% had
completed junior high school, and 3% had
completed elementary school. With regard
to marital/relationship status, 47.8% of the
sample reported being married/cohabiting
with a partner, 31.3% reported being separ-
ated/divorced/widowed, and 20.9% reported
being single.
Participants reported smoking an average
of 15.4 (SD ¼9.2) cigarettes per day and
endorsed relatively high levels of nicotine
dependence (M¼6.2, SD ¼2.1), as indexed
by the Fagerstro
¨m Test for Nicotine Depen-
dence (Fagerstro
¨m, 1978; Heatherton,
Kozlowski, Frecker, & Fagerstrom, 1991).
They also reported initiating daily smoking at
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a mean age of 16.4 years of age (SD ¼4.3) and
smoking regularly for an average of 29.2 years
(SD ¼10.0). In terms of smoking cessation,
participants endorsed an average of 6.3
(SD ¼15.8) lifetime quit attempts lasting at
least 12 hours in duration. The average longest
lifetime period of smoking abstinence after a
quit attempt among participants was 1.0 years
(SD ¼2.9). Baseline AS levels, as indexed by
the Anxiety Sensitivity Index (ASI; Peterson &
Reiss, 1992) were in the elevated clinical range
(mean ASI total score ¼33.3, SD ¼11.7).
Measures
Descriptive demographic data. Participants
provided demographic and related personal
background information (age, gender, marital
status, educational attainment, occupation,
etc).
Smoking History Questionnaire.(SHQ;
Brown, Lejuez, Kahler, & Strong, 2002). The
SHQ is a self-report questionnaire used to
assess smoking history and pattern. It includes
items pertaining to smoking rate, age of onset
of smoking initiation, and years of being a
daily smoker. The SHQ has been successfully
used in previous studies as a measure of
smoking history (Zvolensky, Lejuez, Kahler,
& Brown, 2004). Smoking rate (i.e., average
number of cigarettes smoked per day in the
last week) was evaluated in the present
analyses as a means to control for prequit
baseline smoking levels in planned analyses
predicting the role of change in AS on point-
prevalence lapse and relapse outcomes.
Fagerstro
¨m Test for Nicotine Dependence
(FTND; Fagerstro
¨m, 1978). The FTND is a
six-item scale designed to assess gradations in
tobacco dependence (Heatherton et al., 1991).
It has shown good internal consistency, positive
relations with key smoking variables (e.g.,
Heatherton et al., 1991), and high degrees of
testretest reliability (Pomerleau, Carton,
Lutzke, Flessland, & Pomerleau, 1994). Higher
scores indicate greater levels of nicotine
dependence. FTND was evaluated in the
present analyses as a means to control for
prequit levels of nicotine dependence in planned
analyses predicting role of change in AS on
point-prevalence lapse and relapse outcomes.
Smoking status outcomes. Self-reported lapse
and relapse were measured at 1 month
posttreatment, using a standardized smoking
status interview. Lapse was operationalized as
retrospective self-report of smoking any
amount following quit day (“Have you had
any slips or lapses since your first quit attempt
in the Tobacco Intervention Program?”)
(Shiffman et al., 1996). Relapse was operatio-
nalized as self-report of current regular
smoking status at the 1 month posttreatment
follow-up session (“Are you currently a
smoker?”) and reporting currently regularly
smoking at least one cigarette per day in the
past week (Ossip-Klein et al., 1986).
Anxiety Sensitivity Index (ASI; Peterson &
Reiss, 1992). The ASI is used to evaluate AS
levels. It is a 16-item measure in which
respondents indicate on a 5-point Likert-type
scale (0 4) the degree to which they have fear
of anxiety symptoms (based on beliefs that
such symptoms are physically dangerous or
may lead to harmful consequences). It
contains three factor-analytically derived sub-
scales: physical concerns (“It scares me when
my heart beats rapidly”), psychological con-
cerns (“It scares me when I am unable to
keep my mind on a task”), and social concerns
(“Other people notice when I feel shaky”)
(Stewart, Taylor, & Baker, 1997). The ASI has
demonstrated sound internal consistency,
test retest reliability, excellent convergent
validity with related measures (Zinbarg,
Mohlman, & Hong, 1999), as well as incre-
mental predictive validity relative to negative
affectivity, neuroticism, and trait anxiety
(McNally, 1996). It was administered at
baseline and at 1 month posttreatment.
Procedure
The current study is a secondary analysis of
data collected in a larger investigation
(Zvolensky et al., 2009b). Neither the present
smoking cessation outcomes (i.e., 1 month
posttreatment cessation outcomes) nor the
aims of the present study involving the
relations between prospective change in AS
and vulnerability for lapse and relapse have
been previously tested or reported.
In the initial phase of the study, smokers
attending an information session about the
Tobacco Intervention Program offered
through Capital Health (i.e., potential smok-
ing cessation treatment seekers) were recruited
for study participation. Potential participants
were informed about the nature and purpose
of the study and were invited to participate in
the research portion of the smoking cessation
54 Assayag, Bernstein, Zvolensky, Steeves and Stewart COGNITIVE BEHAVIOUR THERAPY
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treatment program. All participants were
provided with a $10 movie pass as
compensation.
Two weeks following the initial information
session, eligible participants took part in the
study at their first (pre-cessation) meeting of
the Tobacco Intervention Program group. At
this first (pre-cessation) meeting, participants
were instructed to complete a questionnaire
packet. In addition, they were offered the
chance to receive nicotine replacement therapy
(NRT). Nearly all participants chose to
receive NRT (98.5%). The NRT dose—
Nicotine replacement gum (2 mg or 4 mg) or
nicotine replacement skin patch dose (7 mg,
14 mg, or 21 mg)—was determined by the
respondent’s level of measured nicotine
dependence and was delivered over the course
of treatment in line with evidence-based
standards to complement the cognitive-beha-
vioral smoking cessation intervention (Mul-
lane et al., 2008).
The program consisted of one 90-minute
counseling/support group session per week
for 4 weeks: 60 minutes for the intervention
and 30 minutes for assessment. The manua-
lized treatment included standardized evi-
dence-based behavioral and cognitive
strategies and NRT assessment and treat-
ment. In addition, the program included
education on coping strategies to address
withdrawal symptoms, cravings and triggers,
relapse prevention and maintenance, and
healthy lifestyle practices (see Mullane et al.
(2008) for a more detailed description of the
intervention).
The overall study time line involved session
one (T1), session two (and quit week) (T2),
session three (T3), and session four (T4). A 1-
week period separated each of the treatment
sessions. Treatment was followed by a 1
month posttreatment follow-up-assessment
(T5) (i.e., 8 weeks following T1). At T5 (1
month posttreatment follow-up), participants
were asked to report their smoking status.
Participants who lapsed/relapsed were asked
to complete the FTND; all participants
completed the ASI at T1 and T5.
Results
Change in AS from pretreatment (T1)
to 1 month posttreatment (T5)
To evaluate the degree of change in AS from
baseline (T1) to 1 month posttreatment (T5),
we (a) calculated the mean change in the
combined AS physical and psychological
concerns score from baseline to 1 month
posttreatment (T5) and (b) evaluated the
number of participants who, at 1 month
posttreatment (T5), demonstrated reduced-to-
normative levels of AS (reduced-normative AS
group) or maintained clinically elevated levels
of AS (maintained-maladaptive AS group)
(Bernstein et al., 2010) (Table 1). Thus, we
identified two subgroups of smokers. Based on
FMM data, the first subgroup demonstrated
elevated levels of AS at preintervention (base-
line) and markedly reduced, normative levels
of AS at 1 month posttreatment (Bernstein
et al., 2010); this subgroup is referred as the
reduced-normative AS group throughout this
paper. The second subgroup also demon-
strated elevated levels of AS at preintervention
but maintained elevated levels of AS post-
treatment (Bernstein et al., 2010); this
subgroup is referred as the maintained-
maladaptive AS group throughout this paper.
Specifically, among participants who
demonstrated maladaptive levels of AS
Table 1. Pre- and posttreatment ASI combined physical and psychological concerns total scores by AS groups
at 1 month posttreatment
Pretreatment Posttreatment
Percent of cases Mean (SD) Range Mean (SD) Range
Reduced-normative AS group
a
43.3% (n¼29) 19.0 (6.8) 13– 46 6.9 (3.7) 0– 12
Maintained-maladaptive AS group
b
56.7% (n¼38) 27.0 (8.9) 13– 46 22.2 (8.4) 1341
a
Reduced-normative AS group refers to participants who demonstrated robust therapeutic change in AS from
pre- to posttreatment.
b
Maintained-maladaptive AS group refers to participants who maintained maladaptive levels of AS from pre- to
posttreatment.
VOL 41, NO 1, 2012 Anxiety Sensitivity and Smoking Cessation 55
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physical and psychological concerns (com-
bined score .12) at baseline (mean
(SD)¼24.6 (9.6), range ¼1348) (a) 43.3%
(n¼29) demonstrated normative levels of AS
(,13) at 1 month posttreatment (mean (SD)
¼18.9 (3.7), range ¼0 12), i.e., the reduced-
normative AS group and (b) 56.7% (n¼38)
demonstrated maintained maladaptive levels
of AS (.12) at 1 month posttreatment
(mean (SD)¼22.2 (8.4), range ¼13 41), i.e.,
the maintained-maladaptive AS group (see
Table 1).
We then assigned participants to “high-
confidence” latent AS groups based on more
conservative (extreme) cutoff values so as to
decrease the potential of latent class misclassi-
fication based on a single cutoff value
(Bernstein et al., 2010). Among participants
who demonstrated maladaptive levels of AS
physical and psychological concerns (com-
bined score .15) at baseline (mean
(SD)¼25.6(8.6), range ¼16 46) (a) 23.6%
(n¼13) demonstrated normative levels of AS
(,11)at1monthposttreatment(mean
(SD)¼5.2 (2.9), range ¼09), i.e., high-
confidence reduced-normative AS group, (b)
43.6% (n¼24) demonstrated maintained
maladaptive levels of AS at 1 month posttreat-
ment (mean (SD)¼26.9 (6.9), range ¼17
41), i.e., high-confidence maintained-maladap-
tive AS group, and (c) 32.7% (n¼18)
demonstrated levels of AS at 1 month
posttreatment that fell somewhere between
the “high-confidence” normative and mala-
daptive AS groups (mean (SD)¼12.8(1.5),
range ¼1115).
Categorical between-group change in
AS from pre- to posttreatment and
point-prevalence lapse and relapse
2
Consistent with FMM findings, high-confi-
dence low- and high-AS cutoff values (,11
and .15) were used for conducting the
planned between-group tests. These cutoff
values help ensure the internal validity of
between-group tests by limiting the possibility
of participant misclassification to either latent
AS group (Bernstein et al., 2010). As predicted,
at 1 month posttreatment, the maintained-
maladaptive AS group demonstrated signifi-
cantly elevated lapse rates (n¼24/24, 100%
lapsed) relative to the reduced-normative AS
group (n¼9/13, 69.2% lapsed) [x
2
(1) ¼8.3,
p,.01]. Furthermore, as predicted, the
maintained-maladaptive AS group demon-
strated significantly elevated relapse rates
(n¼19/24, 79.2% relapsed) relative to the
reduced-normative AS group (n¼7/13,
53.8% relapsed) [x
2
(1) ¼2.6, one-tailed
p,.05]; specifically, the rate of abstinence
among the reduced-normative AS group was
more than twice the rate observed among
the maintained-maladaptive AS group (i.e.,
46.2% stayed quit vs. 20.8% stayed quit,
respectively). Continuous AS physical and
psychological concerns within reduced-norma-
tive and maintained-maladaptive AS groups and
point-prevalence relapse. Consistent with
FMM findings, the single cutoff value (,13
and .12) was used for guiding within-
group tests (Bernstein et al., 2010). This cutoff
value was chosen a priori to reduce type II
errors likely in evaluation of analyses con-
ducted within each AS subgroup separately.
Indeed, unlike analyses of between-
group effects completed among the entire
sample, these tests between continuous AS
physical and psychological concerns and
smoking outcomes are conducted within each
AS latent group separately (Bernstein et al.,
2010). Further, reliance on the single cutoff
value approach for AS class assignment was
important in so far as null findings were
expected among the low-AS subgroup and
maximized statistical power was thus import-
ant to conduct such a test reliably. As
predicted, at 1 month posttreatment, among
the maintained-maladaptive AS group,
greater continuous combined AS physical
and psychological concerns scores were
significantly related to elevated risk for relapse
(OR ¼.85, 95% CI ¼.74 to .96, p,.01). In
contrast, at 1 month posttreatment, among
the reduced-normative AS group, greater
continuous AS physical and psychological
concerns scores evidenced a nonstatistically
significant trend in terms of a decreased risk
for relapse (i.e., elevated probability of staying
quit) (OR ¼1.24, 95% CI ¼.98 1.6,
p¼.07).
Alternative one-class continuous model
of AS change and point-prevalence
lapse and relapse
We also evaluated whether, when collapsing
across AS groups, change in combined AS
56 Assayag, Bernstein, Zvolensky, Steeves and Stewart COGNITIVE BEHAVIOUR THERAPY
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physical and psychological concerns scores
from baseline to 1 month posttreatment
predicted risk for lapse and relapse. As
predicted, when collapsing across AS groups,
degree of change in continuous AS scores
from pre- to posttreatment did not similarly
predict risk for lapse or relapse (OR
lapse
¼.93,
95% CI ¼.86 1.0, p¼ns OR
relapse
¼1.0,
95% CI ¼.98 1.01, p¼ns).
Discussion
As expected, there was evidence of change in
AS, and individual differences in observed
change, over the course of the evidence-based
pharmacologically aided cognitive-behavioral
community-based smoking cessation interven-
tion. Indeed, a notable proportion of partici-
pants (43.3%) who demonstrated maladaptive
levels of AS at pre-treatment demonstrated
change in AS—prospectively moving from
maladaptive levels of AS at pre-treatment to
normative levels of AS at 1 month posttreat-
ment (reduced-normative AS group). Yet, it
also was striking that a majority of partici-
pants (56.7%) maintained maladaptive levels
of AS at 1 month posttreatment (maintained-
maladaptive AS group). This work is broadly
consistent with research suggesting AS can
change in response to life events (Marshall
et al., 2010) and uniquely extends it to
smoking cessation.
Second, as predicted, the maintained-mala-
daptive AS group demonstrated significantly
elevated rates of lapse to smoking relative to
the reduced-normative AS group. In addition,
participants who demonstrated maintained-
maladaptive AS demonstrated greater rates of
relapse to smoking relative to participants
who demonstrated reduced-normative AS.
Thus, elevated levels of maintained AS were
related to an increased risk of relapse during a
4-week cognitive-behavioral group Tobacco
Intervention Program. This work adds to the
empirical literature suggesting AS may be a
risk factor for poor smoking cessation out-
come (Brown et al., 2001; Mullane et al., 2008;
Zvolensky et al., 2007) and suggests that
degree of change in this cognitive factor is an
important explanatory process for smoking
cessation outcome.
Third, among the maintained-maladaptive
AS group, greater continuous levels of AS
physical and psychological concerns were
significantly related to greater levels of risk
for relapse. In contrast, among the reduced-
normative AS group, greater continuous levels
of AS physical and psychological concerns
were predictive of decreased risk for relapse
(i.e., increased probability of staying quit); this
effect neared, but did not reach, statistical
significance. These findings are generally
consistent with the dimensional component
of the AS taxonic-dimensional hypothesis
(Bernstein et al., 2010; Bernstein, Zvolensky,
Stewart, & Comeau, 2007). Although the
latter findings were unexpected, they are
consistent with the perspective that it may be
important to discriminate between the latent
forms of AS because greater levels of the
normative form of AS may be adaptive,
whereas greater continuous individual differ-
ences in levels of AS among the high-AS taxon
class may confer vulnerability (Bernstein,
Zvolensky, et al. 2007; Bernstein et al., 2007).
The observed findings offer novel theoreti-
cal and clinical guidance. Clinically, despite
evidence-based smoking cessation treatment,
those participants who did not demonstrate
clinically significant reductions (movement
between high- to low-AS groups from pre- to
postintervention) in AS lapsed to smoking,
and demonstrated markedly elevated risk for
relapse, relative to participants who did
demonstrate such change. These findings
point to the potential importance of continu-
ing to develop specialized smoking cessation
intervention(s) for certain segments of the
smoking population who may benefit through
psychosocial or pharmacological tactics tar-
geting AS reduction (Zvolensky et al., 2008b;
Zvolensky, Bernstein, Yartz, McLeish, &
Feldner, 2008a; Zvolensky & Yartz, 2007).
Theoretically, these data support the concep-
tual and operational utility of the AS taxonic-
dimensional model (Bernstein et al., 2007,
2010) with respect to smoking cessation
outcomes. Therefore, AS and smoking cessa-
tion outcome associations are likely to be
inaccurately characterized in the event that the
construct is conceptualized and measured
exclusively as a single continuous latent
variable. Indeed, reliance on a one-class
dimensional model of AS may fail to most
sensitively and specifically identify smokers at
risk for poor smoking cessation outcome as a
function of AS as well as to estimate degree of
risk for poor outcome as a function of AS
VOL 41, NO 1, 2012 Anxiety Sensitivity and Smoking Cessation 57
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levels. The admixture of AS classes that results
from reliance on the traditional one-class
dimensional model of AS—and consequent
admixture of individual differences in AS both
unrelated and related to poor smoking
cessation outcome—threatens valid inferences
regarding relations between AS and smoking
cessation outcome.
The present study has a number of
limitations. First, the sample population was
composed of demographically homogenous
and adult self-selected treatment seekers from
one region of Canada. To broaden the
generalizability of the present findings, it is
important that future research extend this
work to more diverse populations as well as to
a variety of more diverse community and
treatment settings. Second, the measurement
methodology in the present study relied
exclusively on self-report measures. Determi-
nation of lapse and relapse was based on
participants’ retrospective self-report and did
not include biochemical verification of smok-
ing status. Although past work has indicated
that such self-reported smoking behavior is
reliable (McLeish, Zvolensky, & Bucossi,
2007), and the participants had no explicit
incentive to report abstinence in the present
investigation, future work could be strength-
ened by including biochemical verification
procedures. Notably, to reduce demand
characteristics in the present study, research-
ers, and not the treatment providers, con-
ducted the post-cessation assessment; and
indeed, reported rates of lapse and relapse
suggest that participants were not likely
underreporting. Third, the present sample
was relatively small in size. A larger sample
may be important to examine the reliability of
the observed findings as well as would increase
the statistical power of analyses. Such study
would also facilitate evaluation of the role of
gender for the observed phenomena, but we
lack statistical power in the present data to
reliably evaluate the observed effects by
gender (Cohen, 1992). Additionally, though
in the present study women were over-
represented, evaluation of the role(s) of gender
on the observed effects may be facilitated by a
sampling strategy in which a similar number
of men and women are recruited. Fourth, the
present study did not evaluate the therapeutic
mechanisms through which AS changed
within the present community-based smoking
cessation treatment nor why only some
individuals demonstrated change in AS
whereas others did not? One possibility is
that the degree of exposure to nicotine
deprivation and related withdrawal symp-
toms, facilitated by key cognitive-behavioral
and pharmacological elements of the inter-
vention, may have functioned to (unintention-
ally) extinguish emotional responsivity to such
cues. Another nonmutually exclusive possi-
bility is that the cognitive-behavioral (e.g.,
approach-oriented coping) and pharmacologi-
cal elements of the treatment resulted in
therapeutic reduction in AS (prequit) and that
such reduced sensitivity facilitated greater
probability of maintained cessation by redu-
cing dysregulated responding (e.g., impulsive
pursuit of negative reinforcement via smok-
ing) to aversive elements of cessation (e.g.,
withdrawal symptoms, loss of smoking as a
coping strategy to reduce negative affect or
anxiety). Fifth, the timing of the measurement
of AS and smoking cessation did not permit a
test of their temporal precedence or order of
change. Thus, one alternative account of the
observed findings is that not lapsing and not
relapsing led to reductions in AS or that
returning to smoking post-cessation led to
maintained elevated levels of AS. For ex-
ample, it is possible that by not “escaping”
from the anxiety sensations through an
avoidance response (smoking), those who do
not relapse learn that arousal sensations are
not to be feared and thus reduce their AS. To
address this question, future research may
usefully evaluate AS in the context of other
affect and smoking variables in one over-
arching model over the course of treatment
using time sampling approaches. In addition,
earlier FMM study of AS used ASI-3 (Taylor,
Zvolensky et al., 2007), whereas the present
study measured AS via the original ASI
(Peterson & Reiss, 1992). Notably, recent
FMM study has replicated the taxonic-
dimensional model of AS, using the original
ASI (Bernstein, Stickle, & Schmidt, 2011).
Finally, variables such as life stress, trauma
exposure, psychopathology, and alternative
psychotherapy were not assessed in the present
study. Future work may be designed to
evaluate the possibility that change in AS
may be a proxy factor, rather than a direct
causal risk factor, for poor smoking cessation
outcome.
58 Assayag, Bernstein, Zvolensky, Steeves and Stewart COGNITIVE BEHAVIOUR THERAPY
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Acknowledgements
Dr. Bernstein recognizes the funding support
from the Israeli Council for Higher Education
Yigal Alon Fellowship, the European Union
FP-7 Marie Curie Fellowship International
Reintegration Grant, Psychology Beyond
Borders Mission Award, the Israel Science
Foundation, the Rothschild-Caesarea Foun-
dation’s Returning Scientists Project at the
University of Haifa, and a National Institute
on Drug Abuse (NIDA) Clinical LRP award.
Ms. Assayag recognizes the support of the
University of Haifa Graduate School. Dr.
Stewart was supported by a Killiam Research
Professorship from the Dalhousie University
Faculty of Science at the time this research was
conducted. Data collection was supported by
an Idea Research Grant from the Canadian
Tobacco Control Research Initiative (15683)
awarded to Dr. Stewart, Dr. Zvolensky, and
Mr. Steeves. Dr. Zvolensky recognizes fund-
ing support from NIDA (R01 DA027533-01,
R01 MH076629-01).
The authors thank the clients and therapists
from the Tobacco Intervention Program (at
Capital Health Addiction Prevention and
Treatment Services) and Ellen Rhyno and
Jennifer Mullane who assisted with data
collection.
Notes
1. FMM may have a number of significant advantages
relative to coherent cut kinetic (CCK) taxometric
methods as well as relative to other latent mixture
modeling techniques (Bauer & Curran, 2004; Lubke
& Tueller, 2010; Muthe
´n, 2008). Unlike other more
commonly employed data analytic strategies such as
CCK taxometrics, K-means clustering, latent class
and latent profile analyses, and factor analysis, FMM
facilitates the concurrent modeling of various models
that incorporate latent class (categorical) structure
and within-class continuity. Thus, FMM is not
limited to testing (a) whether a latent variable is
either a dichotomous categorical (taxonic) or con-
tinuous (i.e., CCK taxometrics) variable, (b) the
relative fit of various continuous models (i.e., factor
analysis) assuming a single latent homogeneous
population, or (c) relative fit of various categorical
models that lack within-class continuity due to
assumption of local independence (i.e., K-means
clustering, latent class/profile analysis). Rather,
FMM permits arguably more construct valid and
flexible latent structural modeling of various possible
categorical and continuous structures simultaneously.
Furthermore, and unlike CCK taxometrics, FMM
offers a model-based approach in which latent
structural models are compared and contrasted in
terms of multiple, well-established, objective fit
indices. In addition, unlike CCK taxometrics, and
similar to other model-based mixture techniques,
FMM imposes no limit on the number of possible
latent classes that may underlie a construct’s putative
population heterogeneity or latent class structure.
Finally, because FMM incorporates mixture model-
ing and factor analytic techniques, it is rooted in
extensive and well-established quantitative theory
and methods.
2. We planned to conduct two logistic regression
analyses in which baseline (prequit) daily smoking
rate and nicotine dependence were (separately)
entered in step one of the logistic regression equation;
the posttreatment AS group status variable (reduced-
normative AS group vs. maintained-maladaptive AS
group) was entered as a categorical group variable in
step two of the equation; and either rates of lapse
(vs. no lapse or abstinence) or rates of relapse (vs.
abstinence) served as the dependent variables. In the
event of significant associations between pretreatment
smoking rate or nicotine dependence and lapse and
relapse outcomes, this data analytic approach was
intended to facilitate a test of the incremental effect
of between-group differences (reduced-normative
AS group vs. maintained-maladaptive AS group) on
lapse and relapse outcomes, above and beyond the
variance accounted for by baseline levels of smoking
or nicotine dependence. However, neither pretreat-
ment (baseline) smoking rate nor nicotine dependence
were significantly related to the studied dependent
variables (lapse and relapse outcomes) and thus were
omitted as covariates (Tabachnick & Fidell, 2005).
References
Amering, M., Bankier, B., Berger, P., Griengl, H.,
Windhaber, J., & Katschnig, H. (1999). Panic
disorder and cigarette smoking behavior.
Comprehensive Psychiatry,40(1), 3538. doi:
10.1016/S0010-440X(99)90074-3.
Asmundson, G. J. G., Weeks, J. W., Carleton,
R. N., Thibodeau, M. A., & Fetzner, M. G.
(2011). Revisiting the latent structure of the
anxiety sensitivity construct: More evidence of
dimensionality. Journal of Anxiety Disorders,
25, 138147.
Barlow, D. H., Craske, M. G., Cerney, J., &
Klosko, J. (1989). Behavioral treatment of panic
disorder. Behavior Therapy,20, 261282.
Battista, S., Stewart, S. H., Fulton, H., Steeves, D.,
Darredeau, C., & Gavric, D. (2008). A further
investigation of the relations of anxiety sensitivity
to smoking motives. Addictive Behaviors,33.
1402– 1408, doi: 10.1016/j.addbeh.2008.06.016.
Bauer, D. J., & Curran, P. J. (2004). The integration
of continuous and discrete latent variable
models: Potential problems and promising
opportunities. Psychological Methods,9, 329,
doi: 10.1037/1082-989X.9.1.3.
Bernstein, A., Leen-Feldner, E. W., Kotov, R.,
Schmidt, N. B., & Zvolensky, M. J. (2006). A
test of a panic- relevant diathesisstress model
using a taxonic index of anxiety sensitivity.
VOL 41, NO 1, 2012 Anxiety Sensitivity and Smoking Cessation 59
Downloaded by [Dalhousie University] at 08:16 19 July 2013
In A. J. Sanfelippo (Ed.), Panic disorders: New
research (pp. 1540). Hauppauge, NY: Nova
Science Publishing.
Bernstein,A.,Zvolensky,M.J.,Kotov,R.,
Arrindell, W. A., Taylor, S., Sandin, B., Cox,
B. J., Stewart, S. H., Bouvard, M., Cardenas, S.
J., Eifert, G. H., & Schmidt, N. B. (2006).
Taxonicity of anxiety sensitivity: A multi-
national analysis. Journal of Anxiety Disorders,
20, 122.
Bernstein, A., Stickle, T. R., & Schmidt, N. B.
(2011). Factor mixture model of anxiety sensi-
tivity and anxiety psychopathology vulnerability,
Manuscript submitted for publication.
Bernstein, A., Stickle, T. R., Zvolensky, M. J.,
Taylor, S., Abramowitz, J., & Stewart, S.
(2010). Dimensional, categorical, or dimen-
sional-categories: Testing the latent structure
of anxiety sensitivity among adults using
factor-mixture modeling. Behavior Therapy,
41, 515529. doi: 10.1016/j.beth.2010.02.003.
Bernstein, A., & Zolensky, M. J. (2007). Anxiety
sensitivity: Selective review of promising
research and future directions. Expert Review
of Neurotherapeutics,7, 97– 101. doi:
10.1586/14737175.7.2.97.
Bernstein, A., Zvolensky, M. J., Norton, P. J.,
Schmidt, N. B., Taylor, S., Forsyth, J. P. ... &
Cox, B. (2007). Taxometric and factor analytic
models of anxiety sensitivity: Integrating
approaches to latent structural research.
Psychological Assessment,19, 74 87. doi:
10.1037/1040-3590.19.1.7.
Bernstein, A., Zvolensky, M. J., Stewart, S. H., &
Comeau, N. (2007). Taxometric and factor
analytic models of anxiety sensitivity among
youth: Exploring the latent structure of anxiety
psychopathology vulnerability. Behavior
Therapy,38, 269283. doi:
10.1016/j.beth.2006.08.005.
Broman-Fulks, J. J., Green, B. A., Olatunji, B. O.,
Berman, M. E., Arnau, R. C., Deacon, B. J., &
Sawchuk, C. N. (2008). The latent structure of
anxiety sensitivity-revisited. Assessment,15,
188203, doi:10.1177/1073191107311284.
Broman-Fulks, J. J., Deacon, B. J., Olatunji, B. O.,
Bondy, C. L., Abramowitz, J. S., & Tolin, D. F.
(2010). Categorical or dimensional: A re-
analysis of the anxiety sensitivity construct.
Behavior Therapy,41, 154171, doi:10.1016/j.-
beth.2009.02.005.
Brown, R. A., Kahler, C. W., Zvolensky, M. J.,
Lejuez, C. W., & Ramsey, S. E. (2001). Anxiety
sensitivity: relationship to negative affect
smoking and smoking cessation in smokers
with past major depressive disorder. Addictive
Behaviors,26, 887899. doi: 10.1016/S0306-
4603(01)00241-6.
Brown, R. A., Lejuez, C. W., Kahler, C. W., &
Strong, D. (2002). Distress tolerance and
duration of past smoking cessation attempts.
Journal of Abnormal Psychology,111, 180 185.
doi: 10.1037//0021-843X.111.1.180.
Cohen, J. (1992). A power primer. Psychological
Bulletin,112, 155159. doi: 10.1037/0033-
2909.112.1.155.
Comeau, N., Stewart, S. H., & Loba, P. (2001). The
relations of trait anxiety, anxiety sensitivity, and
sensation seeking to adolescents’ motivations
for alcohol, cigarette, and marijuana use.
Addictive Behaviors,26, 803825. doi:
10.1016/S0306-4603(01)00238-6.
Degenhardt, L., Hall, W., & Lynskey, M. (2001).
Alcohol, cannabis, tobacco use among Austra-
lians: A comparison of their associations with
other drug use and use disorders, affective
and anxiety disorders, and psychosis. Addiction,
96, 16031614. doi: 10.1046/j.1360-
0443.2001.961116037.x.
de Graaf, R., Bijl, R. V., Smit, F., Vollebergh,
W. A., & Spijker, J. (2002). Risk factors for
12-month comorbidity of mood, anxiety, and
substance use disorders: Findings from the
Netherlands mental health survey and incidence
study. American Journal of Psychiatry,159,
620629.
Fagerstrom, K. O. (1978). Measuring degree of
physical dependence to tobacco smoking with
reference to individualization of treatment.
Addictive Behaviors,3, 235241. doi:
10.1016/0306-4603(78)90024-2.
Goodwin, R., & Hamilton, S. P. (2002). Cigarette
smoking and panic: The role of neuroticism.
The American Journal of Psychiatry,159(7),
12081213.
Gregor, K. G., Zvolensky, M. J., McLeish, A.,
Bernstein, A., & Morissette, S. B. (2008).
Anxiety sensitivity and perceived control over
anxiety-related events: Associations with smok-
ing outcome expectancies and perceived cessa-
tion barriers among daily smokers. Nicotine
and Tobacco Research,10, 627 635. doi:
10.1080/14622200801978706.
Heatherton, T. F., Kozlowski, L. T., Frecker, R. C.,
& Fagerstrom, K. O. (1991). The Fagerstrom
test for nicotine dependence: A revision of the
Fagerstrom Tolerance Questionnaire. British
Journal of Addiction,86, 11191127.
Johnson, K. A., Stewart, S., Rosenfield, D.,
Steeves, D., & Zvolensky, M. J. (2011).
Prospective Evaluation of the Effects of Anxiety
Sensitivity and State Anxiety in Predicting
Acute Nicotine Withdrawal Symptoms During
Smoking Cessation. Psychology of Addictive
Behaviors, Advance online publication. doi:
10.1037/a0024133.
Lasser, K., Boyd, J. W., Woolhandler, S., Himmel-
stein, D. U., McCormick, D., & Bor, D. H.
(2000). Smoking and mental illness.Journal of the
American Medical Association,284, 2606– 2610.
doi: 10.1016/S0091-3057(01)00677-3.
Leyro, T. M., Zvolensky, M. J., Vujanovic, A., &
Bernstein, A. (2008). Anxiety sensitivity and
smoking motives and outcome expectancies
among adult daily smokers: Replication and
extension. Nicotine and Tobacco Research,10,
985994. doi: 10.1080/14622200802097555.
60 Assayag, Bernstein, Zvolensky, Steeves and Stewart COGNITIVE BEHAVIOUR THERAPY
Downloaded by [Dalhousie University] at 08:16 19 July 2013
Lubke, G. H., & Tueller, S. J. (2010). Latent class
detection and class assignment: A comparison
of the MAXEIG taxometric procedure and
factor mixture modeling approaches. Structural
Equation Modeling: A Multidisciplinary Journal,
17, 605628.
Marshall, E. C., Johnson, K., Bergman, J., Gibson,
L. E., & Zvolensky, M. J. (2009). Anxiety
sensitivity and panic reactivity to bodily
sensations: Relation to quit-day (acute) nicotine
withdrawal symptom severity among daily
smokers making a self-guided quit attempt.
Experimental and Clinical Psychopharmacology,
17, 356364. doi: 10.1037/a0016883.
Marshall, G. N., Miles, J. N. V., & Stewart, S. H.
(2010). Anxiety sensitivity and PTSD symptom
severity are reciprocally-related: Evidence from
a longitudinal study of physical trauma
survivors. Journal of Abnormal Psychology,
119, 143150. doi: 10.1037/a0018009.
McLeish, A. C., Zvolensky, M. J., & Bucossi, M. M.
(2007). Interaction between smoking rate and
anxiety sensitivity: Relation to anticipatory
anxiety and panic-relevant avoidance among
daily smokers. Journal of Anxiety Disorders,21,
849859. doi: 10.1016/j.janxdis.2006.11.003.
McNally, R. J. (1996). Anxiety sensitivity is distinct
from trait anxiety. In R. M. Rapee (Ed.),
Current controversies in the anxiety disorders
(pp. 214227). New York, NY: Guilford.
McNally, R. J. (2002). Anxiety sensitivity and panic
disorder. Biological Psychiatry,52, 938946.
doi: 10.1016/S0006-3223(02)01475-0.
Muthe
´n, B. (2008). Latent variable hybrids: Over-
view of old and new models. In G. R. Hancock
& K. M. Samuelsen (Eds.), Advances in latent
variable mixture models (pp. 124). Charlotte,
NC: Information Age Publishing.
Mullane, J. C., Stewart, S. H., Rhyno, E., Steeves,
D., Watt, M., & Eisner, A. (2008). Anxiety
sensitivity and difficulties with smoking cessa-
tion. In A. M. Columbus (Ed.), Advances in
psychology research. (vol. 54, pp. 141 155).
Hauppage,NY: Nova Science.
Novak, A., Burgess, E. S., Clark, M., Zvolensky,
M. J., & Brown, R. A. (2003). Anxiety sensitivity,
self-reported motives for alcohol and nicotine
use, and level of consumption. Journal of Anxiety
Disorders,17, 165180. doi: 10.1016/S0887-
6185(02)00175-5.
Ossip-Klein, D. J., Bigelow, G., Parker, S. R.,
Curry, S., Hall, S., & Kirkland, S. (1986). Task
force 1: Classification and assessment of
smoking behavior. Health Psychology,5,
311, PMID: 3582323.
Otto, M. W., & Reilly-Harrington, N. A. (1999).
The impact of treatment on anxiety sensitivity.
In S. Taylor (Ed.), Anxiety sensitivity: Theory,
research, and treatment of the fear of anxiety
(pp. 321336). Mahwah, NJ: Lawrence Erl-
baum Associates.
Peterson, R. A., & Reiss, S. (1992). Anxiety
Sensitivity Index manual (2nd ed). Worthington,
OH: International Diagnostic Systems.
Pomerleau, C. S., Carton, S. M., Lutzke, M. L.,
Flessland, K. A., & Pomerleau, O. F. (1994).
Reliability of the Fagerstro
¨m Tolerance Ques-
tionnaire and the Fagerstro
¨m Test for nicotine
dependence. Addictive Behaviors,19, 3339.
doi: 10.1016/0306-4603(94)90049-3.
Reiss, S., & McNally, R. J. (1985). Expectancy
model of fear. In S. Reiss & R. R. Bootzin
(Eds.), Theoretical issues in behavior therapy
(pp. 107121). San Diego, CA: Academic Press.
Schmidt, N. B., Kotov, R., Lerew, D. R., Joiner, T.
E., & Ialongo, N. S. (2005). Evaluating latent
discontinuity in cognitive vulnerability to panic:
A taxometric investigation. Cognitive Therapy
and Research,29, 673691, doi:
10.1007/s10608-005-9632.
Schmidt, N. B., Keough, M. E., Mitchell, M. A.,
Reynolds, E. K., MacPherson, L., Zvolensky,
M. J., & Lejuez, C. W. (2010). Anxiety
sensitivity: Prospective prediction of anxiety
among early adolescents. Journal of Anxiety
Disorders,24, 503508. doi: 10.1016/j.janx-
dis.2010.03.007.
Schmidt, N. B., & Woolaway-Bickel, K. (2000). The
effects of treatment compliance on outcome in
cognitive-behavioral therapy for panic disorder:
Quality versus quantity. Journal of Consulting
and Clinical Psychology,68, 13–18. doi:
10.1037/0022-006X.68.1.13.
Shiffman, S., Gyns, M., Richards, T. J., Paty, J. A.,
Hickcox, M., & Kassel, J. D. (1996). Tempta-
tions to smoke after quitting: A comparison of
lapsers and maintainers. Health Psychology,15,
455461. doi: 10.1037/0278-6133.15.6455.
Stewart, S. H., Karp, J., Pihl, R. O., & Peterson,
R. A. (1997). Anxiety sensitivity and self-
reported reasons for drug use. Journal of
Substance Abuse,9, 223240. doi:
10.1016/S0899-3289(97)90018-3.
Stewart, S. H., Taylor, S., & Baker, J. M. (1997).
Gender differences in dimensions of anxiety
sensitivity. Journal of Anxiety Disorders,11,
179200. doi: 10.1016/S0887-6185(97)00005-4.
Tabachnick, B. G., & Fidell, L. S. (2005). Using
multivariate statistics (5th ed). New York, NY:
Allyn & Bacon.
Taylor, S., & Cox, B. J. (1998). An expanded
Anxiety Sensitivity Index: Evidence for a
hierarchic structure in a clinical sample. Journal
of Anxiety Disorders,12, 463–483. doi:
10.1016/S0887-6185(98)00028-0.
Taylor, S., Zvolensky, M. J., Cox, B. J., Deacon, B.,
Heimberg, R. G., Ledley, D. R., et al., (2007).
Robust dimensions of anxiety sensitivity:
development and initial validation of the
Anxiety Sensitivity Index-3. Psychological
Assessment,19, 176188, doi: 10.1037/1040-
3590.19.2.176.
Vujanovic, A. A., & Zvolensky, M. J. (2009).
Anxiety sensitivity, acute nicotine withdrawal
symptoms, and anxious and fearful responding
to bodily sensations: A laboratory test. Exper-
imental and Clinical Psychopharmacology,17,
181190. doi: 10.1037/a0016266.
VOL 41, NO 1, 2012 Anxiety Sensitivity and Smoking Cessation 61
Downloaded by [Dalhousie University] at 08:16 19 July 2013
Westling, B. E., & Ost, L. -G. (1999). Brief cognitive
behaviour therapy of panic disorder. Scandina-
vian Journal of Behaviour Therapy,28, 49 57.
doi: 10.1080/028457199440007.
Zinbarg, R. E., Barlow, D. H., & Brown, T. A.
(1997). Hierarchical structure and general
factor saturation of the anxiety sensitivity
index: Evidence and implications. Psychological
Assessment,9, 277 284. doi: 10.1037/1040-
3590.9.3.277.
Zinbarg, R. E., Mohlman, J., & Hong, N. N.
(1999). Dimensions of anxiety sensitivity. In S.
Taylor (Ed.), Anxiety sensitivity: Theory,
research, and treatment of the fear of anxiety
(pp. 83114). Mahwah, NJ: Lawrence Erlbaum
Associates.
Zvolensky, M. J., & Bernstein, A. (2005). Cigarette
smoking and panic psychopathology. Current
Directions in Psychological Science,14,
301305. doi: 10.1111/j.0963-7214.2005.00386.
Zvolensky, M. J., Bernstein, A., & Johnson, K.
(2009a). Empirical approaches to the study and
classification of anxiety psychopathology. In D.
McKay, J. Abramowitz, S. Taylor, & G.
Asmundson (Eds.), Current perspectives on the
anxiety disorders: Implications for the DSM-V
and beyond (pp. 153179). New York, NY:
Springer.
Zvolensky, M. J., Bernstein, A., Jurado, S. C.,
Colotla, V. A., Marshall, E. C., & Feldner,
M. T. (2007a). Anxiety sensitivity and early
relapse to smoking: A test among Mexican
daily, low-level smokers. Nicotine & Tobacco
and Research,9, 483491. doi:
10.1080/14622200701239621.
Zvolensky, M. J., Bernstein, A., Yartz, A. R.,
McLeish, A., & Feldner, M. T. (2008a).
Cognitive-behavioral treatment of comorbid
panic psychopathology and tobacco use and
dependence. In S. H. Stewart & P. Conrod
(Eds.), Anxiety and substance use disorders: The
vicious cycle of comorbidity (pp. 177 200). New
York, NY: Springer.
Zvolensky, M. J., Bonn-Miller, M. O., Bernstein,
A., & Marshall, E. C. (2006). Anxiety sensitivity
and abstinence duration to smoking. Journal of
Mental Health,15, 659670.
Zvolensky, M. J., Forsyth, J. P., Bernstein, A., &
Leen-Feldner, E. W. (2007b). A concurrent test
of the anxiety sensitivity taxon: Its relation to
bodily vigilance and perceptions of control
over anxiety-related events in a sample of young
adults. Journal of Cognitive Psychotherapy,21,
7290. doi: 10.1891/088983907780493322.
Zvolensky, M. J., Lejuez, C. W., Kahler, C. W., &
Brown, R. A. (2004). Nonclinical panic attack
history and smoking cessation: An initial
examination. Addictive Behaviors,29,
825830. doi: 10.1016/j.addbeh.2004.02.017.
Zvolensky, M. J., Stewart, S. H., Vujanovic, A. A.,
Gavric, D., & Steeves, D. (2009b). Anxiety
sensitivity and anxiety and depressive symp-
toms in the prediction of early smoking lapse
and relapse during smoking cessation treat-
ment. Nicotine & Tobacco Research,11,
323331. doi: 10.1093/ntr/ntn037.
Zvolensky, M. J., Vujanovic, A. A., Bonn-Miller,
M. O., Bernstein, A., Yartz, A. R., Gregor,
K. L., ...Gibson, L. E. (2007c). Incremental
validity of anxiety sensitivity in terms of
motivation to quit, reasons for quitting, and
barriers to quitting among community-recruited
daily smokers. Nicotine and Tobacco Research,
9, 965975. doi: 10.1080/14622200701540812.
Zvolensky, M. J., Yartz, A. R., Gregor, K.,
Gonzales, A., & Bernstein, A. (2008b). Inter-
oceptive exposure-based cessation intervention
for smokers high in anxiety sensitivity: A case
series. Journal of Cognitive Psychotherapy,22,
346365. doi: 10.1891/0889-8391.22.4.346.
Zvolensky, M. J., Bernstein, A., & Johnson, K.
(2009). Empirical approaches to the study and
classification of anxiety psychopathology. In D.
McKay, J. Abramowitz, S. Taylor, & G.
Asmundson (Eds.), Current perspectives on the
anxiety disorders: Implications for the DSM-V
and beyond (pp. 153179). New York: Springer.
62 Assayag, Bernstein, Zvolensky, Steeves and Stewart COGNITIVE BEHAVIOUR THERAPY
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... Anxiety sensitivity is a relatively stable individual trait predisposing individuals to focus on internal bodily feelings of distress and to believe that anxiety and the bodily symptoms they experience from anxiety are uncommon or indicate an underlying threat to their health [14,15]. People who smoke and have high anxiety sensitivity can experience higher nicotine withdrawal symptoms and more intense cravings when they quit smoking [16], they are more prone to smoke when they have smoking-related thoughts, feelings, and sensations during cessation attempts, and they are more likely to smoke again soon after they have initiated a quit attempt [17][18][19]. Anxiety sensitivity is prevalent in up to a third of people who smoke across all races and ethnic groups [20,21]; however, Black people who smoke and have higher levels of anxiety sensitivity report experiencing the internal physical symptoms of nicotine withdrawal more intensely than Hispanic and White people who smoke [22,23]. Black people who smoke were also more likely to perceive these symptoms were out of their control or were worsened by environmental stressors such as racial discrimination [22,23]. ...
... Black people who smoke were also more likely to perceive these symptoms were out of their control or were worsened by environmental stressors such as racial discrimination [22,23]. Such processes could contribute to Black people being less successful in quitting smoking or put them more at risk of returning to smoking to help alleviate stress and anxiety [19]. ...
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Background At least half of smokers make a serious quit attempt each year, but Black adults who smoke are less likely than White adults who smoke to quit smoking successfully. Black adults who smoke and have high anxiety sensitivity (an individual difference factor implicated in smoking relapse and culturally relevant to Black adults) are even less successful. The Mobile Anxiety Sensitivity Program for Smoking (MASP) is a smoking cessation smartphone app culturally tailored to Black adults who smoke to increase smoking cessation rates by targeting anxiety sensitivity. Objective This study examined the acceptability and feasibility of the MASP smartphone app following a 6-week pilot test through postintervention qualitative interviews. Methods The MASP smoking cessation app was adapted from an evidence-based app by adding culturally tailored narration and images specific to the Black community, educational content on tobacco use in the Black community and the role of menthol, culturally tailored messages, and addressing tobacco use and racial discrimination. The MASP app was piloted with 24 adults with high anxiety sensitivity who identified as Black, smoked daily, and were not currently using medications or psychotherapy for smoking cessation. At the end of the 6-week pilot test, 21/24 participants (67% female; 95.2% non-Hispanic; mean age=47.3 years; 43% college educated; 86% single or separated) completed an audio-recorded semistructured interview assessing the acceptability and utility of the app, individual experiences, barriers to use, the cultural fit for Black adults who wanted to quit smoking, and identified areas for improvement. Transcribed interviews were coded using NVivo (Lumivero), and then analyzed for themes using an inductive, use-focused process. Results Most participants (17/21, 81%) had smoked for more than 20 years and 29% (6/21) of them smoked more than 20 cigarettes daily. Participants felt the MASP app was helpful in quitting smoking (20/21, 95%) and made them more aware of smoking thoughts, feelings, and behaviors (16/19, 84%). Half of the participants (11/21, 52%) thought the combination of medication and smartphone app gave them the best chance of quitting smoking. Themes related to participant experiences using the app included establishing trust and credibility through the recruitment experience, providing personally tailored content linked to evidence-based stress reduction techniques, and self-reflection through daily surveys. The culturally tailored material increased app relevance, engagement, and acceptability. Suggested improvements included opportunities to engage with other participants, more control over app functions, and additional self-monitoring functions. Conclusions Adding culturally tailored material to an evidence-based mobile health (mHealth) intervention could increase the use of smoking cessation interventions among Black adults who want to quit smoking. Qualitative interviews provide mHealth app developers important insights into how apps can be improved before full study implementation and emphasize the importance of getting feedback from the target population throughout the development process of mHealth interventions. Trial Registration ClinicalTrials.gov NCT04838236; https://clinicaltrials.gov/ct2/show/NCT04838236
... 8,12,13 Unlike adolescents, several studies in adults reported a significant association between anxiety sensitivity and tobacco use, in addition to other personality traits. 14,15 Moreover, adolescent smoking is linked with impulsivity traits according to the meta-analyses including fifty-one studies. 16 On the contrary, Malmberg et al. 17 reported that impulsivity and anxiety sensitivity did not affect smoking behavior during adolescence, while sensation seeking and hopelessness were related to tobacco use. ...
... When asked about the future, the percentages of participants that responded as "definitely not smoking", "probably not smoking", "probably smoking", and "definitely smoking" were 53.1% (n=103), 21.6% (n=42), 17.5% (n=34), and 7.7% (n=15), respectively. The median age of first smoking in adolescents who smoked at least once was 13 (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17) years. The mean number of cigarettes smoked per day by regular smokers was 15.3 (±8.1). ...
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Background: Smoking is one of the most important public health problems among young people. Potential risk factors that may cause vulnerability to smoke in youth should be well known and investigated. The aim of the present study was to evaluate the associations of current smoking behavior and future smoking intention with high-risk personality traits for substance abuse in a clinical sample of Turkish adolescents, and also evaluate nicotine dependence and smoking characteristics with the personality traits in a subsample of regular smokers. Methods: A cross-sectional study was adopted in which 196 participants took part (aged 14-18 years with a mean of 16.7 years). The assessment consisted of a sociodemographic questionnaire that also questions current smoking behavior and future smoking intention; and additionally, two self-administered instruments including the Substance Use Risk Profile Scale (SURPS) for all participants, and Fagerström Test for Nicotine Dependence (FTND) for only regular smokers. Results: Regular smokers scored higher than never smokers on the lack of self-contentment subscale of SURPS (F(2)=3.30, p=.039). Future smoking intention was found to be associated with nicotine dependence (F(3)=6.67, p=.001). Regular smokers with high levels of nicotine dependence had higher levels of impulsivity and smoked more cigarettes per day than those with low levels of nicotine dependence (t=2.489, p=.017; and t=3.530, p=.001, respectively). The structural equation models (SEM) were created based on these results and the personality theory for substance abuse. The SEM results showed that the first evidence that lack of selfcontentment positively influences regularly smoking behavior and impulsivity positively influences future smoking intention through nicotine dependence. Conclusions: Lack of self-contentment and impulsivity may mediate the transition from current smoking behavior to future tobacco use disorders in Turkish adolescents. The assessment and intervention of selfdiscontentment and impulsivity can be beneficial in reducing the current smoking behavior in Turkish adolescents.
... The sub-scales of the study (the number of questions in each dialect) include fear of physical worries (3-4-6-8-9-10-11-14), fear of lack of cognitive control (2-12-15-16), and fear of observing anxiety by others (1-5-7-13). They are calculated based on a five-degree Likert spectrum with a minimum possible score of 16 and a maximum of 80. Numerous studies have confirmed that internal stability and credibility are appropriate (Assayag et al., 2012). Its three scales have a high correlation with each other (0/83). ...
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Objective: The present study aimed to predict social anxiety based on parent-child conflict and the mediating role of anxiety sensitivity. Methods: The research methodology employed was structural equation modeling with the primary objective being to investigate anxiety sensitivity, social anxiety, and parent-child conflict among second-year high school students in Khorram Abad city during the academic year 2023-2024. A sample of 350 students was randomly selected using cluster sampling. The instruments utilized included the anxiety sensitivity questionnaire Floyd et al, social anxiety assessment Connor et al, and parent-child conflict measurement Fine et al Data analysis was conducted using SPSS26 and AMOS24 software. Results: The results indicated that parent-child conflict had a direct, positive, and significant impact on students' social anxiety (β₌0.44; p<0.01). Furthermore, parent-child conflict directly influenced students' anxiety sensitivity (β₌0.68; p<0.01). Additionally, anxiety sensitivity had a direct and significant correlation with students' social anxiety (β₌0.41; p<0.01). Overall, the findings suggest that the research model fits well. Conclusion: The findings of the study show that conflicts between parents and children, along with sensitivity to anxiety, are important factors that can predict the level of social anxiety in students.
... AS has also been implicated as a contributing factor in smoking initiation, maintenance, and relapse [38,39]. Emerging data indicate that AS is elevated in both Black adults who smoke and people with HIV/AIDS who smoke [40], placing this group at greater odds of early lapse and relapse [41,42]. Without appropriate interventions to address susceptibility to the negative impact of interoceptive stress, Black adults with HIV who smoke and have elevated AS may be inclined to return to smoking to alleviate abstinence-induced increases in anxiety and to manage uncomfortable HIV-related bodily symptoms that may increase with smoking cessation. ...
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Background Black adults who smoke and have HIV experience immense stressors (eg, racial discrimination and HIV stigma) that impede smoking cessation success and perpetuate smoking-related health disparities. These stressors also place Black adults who smoke and have HIV at an increased risk of elevated interoceptive stress (eg, anxiety and uncomfortable bodily sensations) and smoking to manage symptoms. In turn, this population is more likely to smoke to manage interoceptive stress, which contributes to worse HIV-related outcomes in this group. However, no specialized treatment exists to address smoking cessation, interoceptive stress, and HIV management for Black smokers with HIV. Objective This study aims to test a culturally adapted and novel mobile intervention that targets combustible cigarette smoking, HIV treatment engagement and adherence, and anxiety sensitivity (a proxy for difficulty and responsivity to interoceptive stress) among Black smokers with HIV (ie, Mobile Anxiety Sensitivity Program for Smoking and HIV [MASP+]). Various culturally tailored components of the app are being evaluated for their ability to help users quit smoking, manage physiological stress, and improve health care management. Methods This study is a pilot randomized controlled trial in which Black combustible cigarette smokers with HIV (N=72) are being recruited and randomly assigned to use either (1) the National Cancer Institute’s QuitGuide app or (2) MASP+. Study procedures include a web-based prescreener; active intervention period for 6 weeks; smartphone-based assessments, including daily app-based ecological momentary assessments for 6 weeks (4 ecological momentary assessments each day); a video-based qualitative interview using Zoom Video Communications software at week 6 for participants in all study conditions; and smartphone-based follow-up assessments at 0, 1, 2 (quit date), 3, 4, 5, 6, and 28 weeks postbaseline (26 weeks postquitting date). Results Primary outcomes include biochemically verified 7-day point prevalence of abstinence, HIV-related quality of life, use of antiretroviral therapy, and HIV care appointment adherence at 26 weeks postquitting date. Qualitative data are also being collected and assessed to obtain feedback that will guide further tailoring of app content and evaluation of efficacy. Conclusions The results of this study will determine whether the MASP+ app serves as a successful aid for combustible cigarette smoking cessation, HIV treatment engagement, and physiological stress outcomes among Black people with HIV infection. If successful, this study will provide evidence for the efficacy of a new means of addressing major mental and physical health difficulties for this high-risk population. If the results are promising, the data from this study will be used to update and tailor the MASP+ app for testing in a fully powered randomized controlled trial that will evaluate its efficacy in real-world behavioral health and social service settings. Trial Registration ClinicalTrials.gov NCT05709002; https://clinicaltrials.gov/study/NCT05709002 International Registered Report Identifier (IRRID) PRR1-10.2196/52090
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Background and Objectives: Addiction is a social issue and a fundamental health challenge which the average age of its onset has decreased. Psychological factors play a key role in predisposition to drug use. Therefore, this study aimed to analyze the pathway of drug use readiness, considering anxiety sensitivity and sensation seeking with the mediating role of negative affectivity among students. Materials and Methods: This descriptive study employed structural equations modeling. The statistical population comprised Lorestan University’s students during the academic year 2022-2023. Three-hundred and eighty four students met the inclusion criteria and were selected using the convenience sampling method. Research tools used included Floyd et al.’s Anxiety Sensitivity Scale, Zuckerman's Sensation Seeking Scale, Watson et al.'s Negative Affectivity Assessment, and Weed et al.'s Addiction Readiness Scale. Data analysis was conducted through structural equations modeling. Results: The findings indicated that anxiety sensitivity and excitement seeking had a direct, positive, and significant impact on drug use readiness with β=0.25 (p<0.001) and β=0.30 (p<0.001), respectively. Furthermore, anxiety sensitivity and sensation seeking were directly linked to negative affectivity with β=0.26 (p<0.001) and β=0.25 (p<0.001), respectively. Lastly, negative emotionality significantly and directly influenced the willingness to use drugs with β=0.29 (p<0.001). Conclusion: The current study findings indicated that sensation seeking, anxiety sensitivity, and negative affectivity are the significant predictors of drug use. It is recommended that experts develop therapeutic and educational programs to enhance students' awareness and coping skills.
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Objective: This study aimed to determine the mediating role of difficulty in emotion regulation in the relationship between anxiety sensitivity and a sense of coherence with readiness to use drugs in students. Method: The method of descriptive-correlation research was structural equation modeling. The statistical population included all students of Lorestan University, and based on Morgan's table, 384 students were selected according to the entry and exit criteria by available sampling method. The research tools included questionnaires of anxiety sensitivity, sense of coherence, abbreviated version, short form of the scale of difficulty in emotion regulation and preparedness for addiction were completed. In order to analyze the research model, AMOS-24 software was used with the method of structural equation modeling. Results: The findings showed that Anxiety sensitivity and sense of coherence had a direct and significant effect on readiness to use drugs, and difficulty in regulating emotions played a role in the relationship between anxiety sensitivity and sense of coherence with readiness to use drugs. Were considered significant mediators. In short; The results showed that the research model had a good fit. Conclusion: According to the findings, individuals who were more inclined to use drugs exhibited higher levels of anxiety sensitivity and difficulty in regulating emotions, and conversely, lower levels of sense of coherence. Given that sense of coherence plays a pivotal role in the regulation of emotions and anxiety management, it is recommended that university-level trainers and counselors provide the necessary training to students to enhance their sense of coherence. Therefore, it is crucial to pay attention to these variables in order to reduce students' readiness to use drugs.
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Objective: Nicotine metabolism has important effects on sleep. People who quit smoking due to nicotine withdrawal during the smoking cessation process may experience different sleep disorders. Side effects of pharmacological agents used to quit smoking (Varenicline, Bupropion and Nicotine Replacement Therapy [NRT]) on sleep quality are also known. The aim of this study is to investigate the relationship between smoking cessation and the preferred treatment approach with sleep disorders. Material and Methods: 520 participants who applied to OMU Family Medicine Smoking Cessation Clinic in 2019 were accepted as the study population. Demographic data of all participants in the survey, smoking characteristics (Fagerstrom Nicotine Dependency Test score [FNDT], pack / year, etc.), sleep characteristics (sleep duration, evening awakenings, etc.) and Pittsburg Sleep Quality Index (PSQI) at their first visit and one recorded months later. Standard treatment of our clinic was applied to all participants. 387 volunteers (71.6%) without any data loss were accepted as the study group. Results: 165 of 387 (71.6%) people quit smoking in the first month (42.6%). Varenicline was used in 102 (61.8%), Bupropion in 25 (15.1%) and NRT alone in 38 (23.0%) of these patients. Mean sleep time (hours) did not change in this group before and after quitting (6.4 ± 4.8 hours versus 6.3 ± 5.0 hours p> 0.05). There was no difference between the mean PSQI scores of the patient groups receiving different treatments one month later (p> 0.05). Complaints of insomnia (n=5, 17.5%) and drowsiness (n=4, 14.6%) were more common in patients who received Varenicline (x2=12,145, p <0,001). Conclusion: No difference was detected in the sleep quality of patients who were used different treatment options to quit smoking in the first month.
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Cognitive-behavioral therapy (CBT) is skill based and assumes active patient participation in regard to treatment-related assignments. The effects of patient compliance in CBT outcome studies are equivocal, however, and 1 gap in the literature concerns the need re account for the quality versus the quantity of assigned work. In this study, both quality and quantity of home-based practice were assessed to better evaluate the effects of treatment compliance in patients with panic disorder (N = 48) who participated in a 12-session CBT protocol. Patient estimates of compliance were not significantly associated with most outcome measures. On the other hand, therapist ratings of compliance significantly predicted positive changes on most outcome measures. Moreover, therapist and independent rarer estimates of the quality of the participant's work, relative to the quantity of the work, were relatively better predictors of outcome.
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The Anxiety Sensitivity Index (ASI) is one of the most widely used measures of the construct of anxiety sensitivity. Until the recent introduction of a hierarchical model of the ASI by S. O. Lilienfeld, S. M. Turner, and R. G. Jacob (1993), the factor structure of the ASI was the subject of debate, with some researchers advocating a unidimensional structure and others proposing multidimensional structures. In the present study, involving 432 outpatients seeking treatment at an anxiety disorders clinic and 32 participants with no mental disorder, the authors tested a hierarchical factor model. The results supported a hierarchical factor structure consisting of 3 lower order factors and 1 higher order factor. It is estimated that the higher order, general factor accounts for 60% of the variance in ASI total scores. The implications of these findings for the conceptualization and assessment of anxiety sensitivity are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Context Studies of selected groups of persons with mental illness, such as those who are institutionalized or seen in mental health clinics, have reported rates of smoking to be higher than in persons without mental illness. However, recent population-based, nationally representative data are lacking.Objective To assess rates of smoking and tobacco cessation in adults, with and without mental illness.Design, Setting, and Participants Analysis of data on 4411 respondents aged 15 to 54 years from the National Comorbidity Survey, a nationally representative multistage probability survey conducted from 1991 to 1992.Main Outcome Measures Rates of smoking and tobacco cessation according to the number and type of psychiatric diagnoses, assessed by a modified version of the Composite International Diagnostic Interview.Results Current smoking rates for respondents with no mental illness, lifetime mental illness, and past-month mental illness were 22.5%, 34.8%, and 41.0%, respectively. Lifetime smoking rates were 39.1%, 55.3%, and 59.0%, respectively (P<.001 for all comparisons). Smokers with any history of mental illness had a self-reported quit rate of 37.1% (P = .04), and smokers with past-month mental illness had a self-reported quit rate of 30.5% (P<.001) compared with smokers without mental illness (42.5%). Odds ratios for current and lifetime smoking in respondents with mental illness in the past month vs respondents without mental illness, adjusted for age, sex, and region of the country, were 2.7 (95% confidence interval [CI], 2.3-3.1) and 2.7 (95% CI, 2.4-3.2), respectively. Persons with a mental disorder in the past month consumed approximately 44.3% of cigarettes smoked by this nationally representative sample.Conclusions Persons with mental illness are about twice as likely to smoke as other persons but have substantial quit rates.
Article
The aim of the present pilot study was to investigate if it is possible to treat patients having panic disorder with or without mild agoraphobia in a brief, four-session format without losing clinical efficacy. Ten patients fulfilling the DSM-III-R criteria for this disorder received cognitive-behaviour therapy based on the Clark (1989) treatment, but reduced from 12 to 4 sessions (1 hour a week for four weeks). The reduction was achieved by focusing only on the patients' core misinterpretation of bodily sensations and adding extensive homework compared to the original treatment. Patients were assessed pre- and post-treatment and at a 6-month follow-up with assessor ratings of anxiety and depression, self-observation of panic attacks and self-report measures of panic attacks, agoraphobia, general anxiety, agoraphobic cognitions, anxiety sensitivity and depression. The results show that the patients improved significantly on all measures and that this improvement was maintained at the follow-up. On four measures there was even further significant improvement from post-treatment to follow-up. Seventy percent of the patients were panic-free at post-treatment and 90% were panic-free at follow-up.