Journal of Psychiatric Research 156 (2022) 690–697
Contents lists available at ScienceDirect
Journal of Psychiatric Research
journal homepage: www.elsevier.com/locate/jpsychires
Does cannabis use impact cognitive behavioural therapy outcomes for
anxiety and related disorders? A preliminary examination
Mélise J. Ouellette a, c, Karen Rowa a, b, c, *, Duncan H. Cameron a, Ashleigh Elcock a,
Noam Soreni a, b, Elizabeth J. Pawluk a, b, Randi E. McCabe a, b, c
a
b
c
Anxiety Treatment and Research Clinic, St. Joseph’s Healthcare, 100 West 5th St., Hamilton, Ontario, L8N 3K7, Canada
Department of Psychiatry and Behavioural Neurosciences, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4L8, Canada
Department of Psychology, Neuroscience, and Behaviour, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4L8, Canada
A R T I C L E I N F O
A B S T R A C T
Keywords:
Cannabis
Marijuana
Cognitive behavioural therapy (CBT)
Anxiety
Cannabis use disorder
Objectives: The current study examined whether cannabis use frequency and cannabis-related problem severity
(as per the Cannabis Use Disorder Identification Test-Revised) predicted outcomes of cognitive behavioural
therapy (CBT) for anxiety and related disorders. It was predicted that greater frequency of cannabis use and
greater cannabis-related problem severity would be associated with dampened treatment outcomes compared to
less severe cannabis use presentations.
Methods: Participants were 253 adults seeking treatment for anxiety and related disorders. Cannabis use was
categorized as non-use (n = 135), infrequent use (using monthly to 4 times per month; n = 45), and frequent use
(using 2 or more times per week; n = 73). Individuals who reported using cannabis completed cannabis use and
cannabis-related problem measures before starting a CBT group. Participants also completed a weekly symptomspecific measure of anxiety symptoms throughout CBT.
Results: As hypothesized, frequent cannabis use was associated with poorer outcomes in CBT for anxiety and
related disorders compared to non-use. Despite this, individuals who used cannabis frequently still experienced a
statistically significant decrease in their anxiety symptoms from pre-to post-CBT, with a large effect size (d =
− 0.87). Cannabis-related problems was not a significant predictor of CBT outcomes.
Conclusions: Cannabis use frequency was associated with poorer CBT outcomes for anxiety and related disorders,
however these individuals still made notable treatment gains. The mechanism driving this relationship remains
unclear. Future studies should attempt to replicate the current findings and examine possible mechanisms.
1. Introduction
Cognitive behavioural therapy (CBT) is considered the gold standard
anxiety and related disorders (i.e., trauma- and stressor related and
obsessive-compulsive and related disorders; Beck, 1993; Otte, 2011)
treatment. CBT provides patients with cognitive and behavioural skills
to manage anxiety and related disorder symptoms, which are practiced
between sessions to enhance outcomes (Kazantzis et al., 2010; Rowa
et al., 2019).
Individuals seeking treatment for anxiety and related disorders often
endorse cannabis use (Ouellette et al., 2019). Cannabis may be used to
manage anxiety symptoms (Simons et al., 1998; Skalisky et al., 2019),
and cannabis use and anxiety may be mutually maintaining (Buckner
et al., 2012; Stewart and Conrod, 2008). For example, individuals with
anxiety may use cannabis as a subtle avoidance strategy to manage their
anxiety symptoms in the short term (but maintains anxiety in the
long-term; Buckner et al., 2019; McManus et al., 2008; Salkovskis et al.,
1999), and to manage symptoms such as cannabis craving and with­
drawal which have been associated with anxiety (American Psychiatric
Association, 2013; Buckner et al., 2012; Cornelius et al., 2008). Addi­
tionally, after therapy for cannabis dependence, residual anxiety
symptoms have been associated with poorer outcomes, while reduced
anxiety has been associated with better outcomes, suggesting that anx­
iety may increase the risk of cannabis relapse (Buckner and Carroll,
2010; Stewart and Conrod, 2008). Taken together, cannabis use and
anxiety appear to be associated and may be important to consider in
treatment planning.
Cannabis may be used to avoid or escape negative emotions (e.g.,
* Corresponding author. Anxiety Treatment and Research Clinic, St. Joseph’s Healthcare, 100 West 5th St., Hamilton, Ontario, L8N 3K7, Canada.
E-mail addresses: ouellemj@mcmaster.ca (M.J. Ouellette), krowa@stjoes.ca (K. Rowa).
https://doi.org/10.1016/j.jpsychires.2022.10.054
Received 10 June 2022; Received in revised form 23 October 2022; Accepted 26 October 2022
Available online 31 October 2022
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M.J. Ouellette et al.
Journal of Psychiatric Research 156 (2022) 690–697
Buckner et al., 2014; Buckner et al., 2019). Avoidance ultimately
maintains anxiety (McManus et al., 2008; Salkovskis et al., 1999) and a
core feature of CBT for anxiety is to approach, rather than avoid,
anxiety-inducing stimuli (Aderka et al., 2013; Riccardi et al., 2017).
Using cannabis as an avoidance strategy may dampen treatment out­
comes for anxiety and related disorders if left unaddressed. Additionally,
there is evidence of cognitive impairments and amotivation associated
with cannabis use (Broyd et al., 2016; Meier and White, 2018) that may
be challenging in a cognitively and motivationally demanding treatment
like CBT.
Research on cannabis use’s impact on CBT outcomes is sparse and
equivocal. Some studies suggest no effect of cannabis use on outcomes of
brief CBT for anxiety and depression and integrated CBT for anxiety and
substance use (Bricker et al., 2007; Ruglass et al., 2017). Notably, these
studies excluded individuals with more severe cannabis use pre­
sentations (e.g., cannabis dependence), which may be an important
factor in treatment outcomes (Bricker et al., 2007; Ruglass et al., 2017).
Other research has reported a moderating effect of baseline cannabis use
and problems on outcomes for those with comorbid Cannabis Use Dis­
order (CUD) and an anxiety disorder (Buckner et al., 2021). An inte­
grated cannabis and anxiety reduction CBT protocol led to better
outcomes than motivational enhancement and CBT (MET-CBT) for CUD
in those who had more severe baseline cannabis use and related prob­
lems, but those with less severe cannabis use and problems experienced
better outcomes with MET-CBT than the integrated protocol. Therefore,
individuals with more severe cannabis use may not experience optimal
treatment outcomes if only one concern is addressed at once. While
research on integrated treatments is highly valuable, traditionally,
treatment for co-occurring anxiety and substance use disorders have
been separate (Brady et al., 2013), thus it is likely that most clinicians
trained in anxiety disorders are not trained in integrated anxiety and
substance use treatments, and refer individuals to substance use-focused
programs (Skinner et al., 2004). Additionally, studies that have found no
impact of cannabis use on outcomes have used brief protocols and no
research has investigated this question using standard protocols. Taken
together, it is important to know if various cannabis use severity levels
dampen CBT outcomes using standard protocols to inform best practices
in this area.
This study’s purpose is to examine whether cannabis use frequency
and cannabis-related problem severity at baseline are associated with
standard-length CBT outcomes for anxiety and related disorders. Higher
cannabis use frequency was predicted to be associated with poorer CBT
outcomes than non-use given the mutually maintaining relationship
between cannabis use and anxiety. It was predicted that individuals with
more severe cannabis-related problems would likely reflect more severe
cannabis-related functional impairment, which would also dampen CBT
outcomes.
week” or “4 or more times a week”, and non-use was defined as denial of
cannabis use in the past 6 months. Cannabis use frequency categories
were chosen to be similar to other studies (e.g., Buckner and Schmidt,
2008; Henry et al., 2014).
2.2. Procedure
Participants were referred to an anxiety and related disorders clinic
for specialized assessment and intervention services. Referred in­
dividuals had the opportunity to provide informed consent to use their
clinical data for research. Participants’ mental health symptoms were
assessed by trained clinicians. Sixty-eight percent of participants were
assessed using the Diagnostic Assessment Research Tool (DART; McCabe
et al., 2017; Schneider et al., 2021), 22% received a psychiatric consult,
and 4% received an assessment from a nurse specialized in anxiety and
related disorders. To address their presenting concerns, individuals were
referred to a symptom-specific CBT group for either social anxiety dis­
order (SAD), generalized anxiety disorder (GAD), panic disorder (PD)
and/or agoraphobia, obsessive-compulsive disorder (OCD), or post­
traumatic stress disorder (PTSD). CBT groups were composed of 12,
2-hour weekly sessions. CBT protocols included psychoeducation and
cognitive and behavioural skills (e.g., exposure to anxiety-inducing sit­
uations) tailored to the disorder being treated. The only protocol
without behavioural skills was the PTSD group as the type of CBT used
was Cognitive Processing Therapy (Resick et al., 2016). Within the two
weeks prior to beginning group CBT, participants completed measures of
cannabis use patterns, cannabis-related problems, anxiety-related
functional impairment, and disorder-specific anxiety symptoms. They
completed weekly symptom-specific anxiety measures throughout CBT.
The institution’s local research ethics board approved the collection and
use of this data, and all participants provided written and informed
consent.
2.3. Measures
The Cannabis Use Disorder Identification Test-Revised (CUDITR) is an 8-item self-report screening tool for CUD in the past 6 months
(Adamson et al., 2010) and was used in this study to reflect
cannabis-related problems. All 8 items were summed for a total score.
Total scores of 13 or above indicate likely CUD (Adamson et al., 2010).
This study’s Cronbach alpha on the CUDIT-R at baseline was 0.81,
suggesting good internal consistency.
Illness Intrusiveness Rating Scale (IIRS) is a 13-item self-report
measure of illness-related daily life disruptions (Devins, 2010; Devins
et al., 1983). It was adapted to measure the functional impact of anxiety
with the question stem of “How much does your anxiety and/or its
treatment interfere with your:” (e.g., health, work). This study’s
pre-treatment alpha value was 0.83 and post-treatment value was 0.90.
The Social Phobia Inventory (SPIN) is a self-report measure of SAD
symptoms (Connor et al., 2000). The current study included only those
with total scores within the “moderate” SAD symptom range and above
(total scores of 31 and above; Moscovitch et al., 2011; Moser et al.,
2008). The SPIN had a Cronbach alpha that ranged from 0.74 to 0.95
from pre-to post-treatment in this study. The Penn State Worry
Questionnaire (PSWQ) is a self-report measure of trait worry and a
screener for GAD symptoms, administered at pre- and post-treatment
(Fresco et al., 2003; Meyer et al., 1990). The PSWQ-Past Week
(PSWQ-PW; Stöber and Bittencourt, 1998) was also administered
weekly throughout CBT. The PSWQ and PSWQ-PW demonstrated good
internal consistency in this study, with Cronbach alphas ranging from
0.85 to 0.97 from pre-to post-treatment. The Panic Disorder Severity
Scale (PDSS) is a self-report measure of PD (Furukawa et al., 2009;
Shear et al., 1997). The current study’s PDSS showed good internal
consistency with Cronbach alphas ranging from 0.76 (acceptable) to
0.97 (excellent). The Obsessive-Compulsive Inventory-Revised
(OCI-R) is a measure of OCD symptoms (Foa et al., 2002). The current
2. Methods
2.1. Participants
Participants were 253 adults seeking treatment for anxiety and
related disorders (i.e., trauma- and stressor related and obsessivecompulsive and related disorders). Based on diagnostic assessment re­
sults by a psychiatrist, clinical psychologist, graduate-level clinical
psychology student, or other mental health professional, they were
referred to a symptom-specific CBT group at the clinic. Additionally,
participants had to score above the cut off of a relevant symptom mea­
sure at pre-treatment, indicating clinically significant symptoms
matching their CBT group.
Participants’ cannabis use was categorized into non-use (n = 135),
infrequent use (n = 45), and frequent use (n = 73) based on self-reported
use frequency on the Cannabis Use Disorder Identification Test-Revised
(Adamson et al., 2010). Infrequent use was defined as using “Monthly or
less” or “2–4 times a month”, frequent use was defined as “2–3 times a
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M.J. Ouellette et al.
Journal of Psychiatric Research 156 (2022) 690–697
study’s Cronbach alpha ranged from 0.55 to 0.83 for the OCI-R, which is
likely a reflection of the small sample size of participants with OCD. The
PTSD Checklist for DSM-5 (PCL-5) measures PTSD symptoms
(Weathers et al., 2013), with total scores between 31 and 33 and above
indicating likely PTSD (Bovin et al., 2016). To be conservative, the
current study used the cut off score of 33 to be included in the study. The
PCL-5 showed good internal consistency with Cronbach alphas ranging
from 0.86 to 0.97 from pre-to post-treatment in the current study.
Given that the SPIN, PSWQ, PDSS, OCI-R, and PCL-5 measure spe­
cific symptoms for some of the most common anxiety and related dis­
orders (Kessler et al., 2012), collectively they provide a broad
representation of core symptoms of the anxiety and related disorders
population.
possible, sample means for non-anxious controls were used to calculate
z-scores to represent the general population mean, which were 48.8 (SD
= 13.8) for the PSWQ (Meyer et al., 1990), 18.82 (SD = 11.10) for the
OCI-R (Foa et al., 2002), and 6.10 (SD = 6.00) for the PDSS-SR (Shear
et al., 2001). The two exceptions were the PSWQ-PW and the SPIN. No
control sample was available for the PSWQ-PW. Given that the baseline
PSWQ and PSWQ-PW scores were comparable between baseline and
session 1, and session 12 and post-treatment (ps > .05), we used a
comparable score from its validation study (Stöber and Bittencourt,
1998) which was the mid-treatment mean of 45.43 (SD = 16.48). The
non-anxious controls’ SPIN score is 12.10 (SD = 9.30). This score is low
compared to sample means for SAD and therefore, results in
overly-inflated z-scores relative to the other disorder-specific samples in
the current study. Additionally, some researchers support a higher
cut-off value of 30 on the SPIN, rather than the proposed cut-off of 22.10
(Moscovitch et al., 2011; Moser et al., 2008). As such, the “mildly-im­
paired” subsample mean of 22.70 (SD = 10.00) was used (Connor et al.,
2000). This method of analysis has been used in previously published
studies (e.g., Milosevic et al., 2022).
2.4. Data analysis
Primary outcomes were analyzed using hierarchical linear modelling
(HLM; Raudenbush & Byrk, 2002). HLM was used because it can address
missing data at Level-1 (i.e., the outcome variable assessing anxiety and
related disorder symptoms) and it is relatively robust to unbalanced
designs. The estimation method was restricted maximum likelihood
(REML).
To determine if cannabis use frequency groups significantly differed
in rates of change in anxiety and related disorder symptom severity
throughout treatment, an HLM was conducted with time (coded with the
unit of measurement as one week) at Level-1 and cannabis use frequency
at Level-2 (where non-use was the reference category, and infrequent
use and frequent use were incorporated as individually dummy-coded
variables). Follow-up individual one-level HLMs were performed to
assess change in symptom severity within each cannabis use category.
An additional HLM analysis was completed to determine the effect of
cannabis-related problems, as assessed by the CUDIT-R (at Level-2), on
change in anxiety and related disorder symptom severity throughout
treatment. This analysis was performed in a sample of all individuals
who endorsed cannabis use (i.e., both frequent and infrequent) to
determine if cannabis use problems had an impact on treatment out­
comes. Effect size for primary analyses is reported as Cohen’s d, to be
interpreted as small = 0.20, medium = 0.50, and large = 0.80 (Cohen,
2013).
A single (3 cannabis frequency use group X 2 Time) repeatedmeasures ANOVA was used to assess the impact of cannabis use status
on improvement in anxiety-related illness intrusiveness from pre-to
post-treatment.
An intent-to-treat approach was used to maximize sample size and
external validity of results. Data were collected weekly from pre-to posttreatment, for a total of 14 time points. Missing symptom data ranged
from 0.0% at pre-treatment to a maximum of 49.4% at post-treatment,
and the overall level of missing data points in the dataset was 32.4%.
These data were estimated using REML. Missing data was not imputed
for Level-2 variables, and only individuals who had complete data at
Level-2 were used in the analysis. Data was not imputed for the repeated
measures ANOVA.
The uneven sample sizes across groups, and the relatively low sample
sizes for the OCD and PD groups, precluded a meaningful analysis within
or across specific disorders. Therefore, z-scores were calculated for each
symptom measure to collapse participants across diagnostic groups. The
z-score formula is z = (participants symptom-specific measure total
score – non-anxious population mean)/non-anxious population’s stan­
dard deviation. Z-scores were calculated using available sample norms
from validation studies for each questionnaire. Together, the symptomspecific anxiety and related disorder measures provide a broad overview
of core symptoms for some of the most common anxiety and related
disorders (Kessler et al., 2012). Due to methodological differences be­
tween validation studies and symptom-specific questionnaires, z-scores
were only used for the full-sample analysis, whereas raw scores were
used for individual group analyses (i.e., descriptive information). Where
3. Results
3.1. Descriptive statistics
Table 1 reports demographics, diagnostics, and baseline CUDIT-R
scores. Of the 253 participants, 148 (58.50%) had at least one addi­
tional diagnosis documented. Table 2 reports mean symptom-specific
measure scores. Fig. 1 demonstrates participants’ CBT group alloca­
tion and number of participants who completed and terminated CBT
early. The CBT retention rate was 77.1% (n = 195), with no difference in
early termination or CBT completion across groups, χ2(2) = 2.50, p =
.29, V = 0.099, or association with CUDIT-R scores H(1) = 0.04, p =
.851, ε2 = 0.000.
3.2. Symptom change over time as a function of cannabis use
Table 3 presents the full results for all HLM models for the primary
analysis assessing the effect of cannabis use frequency or cannabisrelated problem severity on the trajectory of change in anxiety and
related disorder symptom severity throughout CBT. There was a sig­
nificant effect of frequent cannabis use on change in symptoms over time
(b = 0.04, SE = 0.02, t = 2.72, df = 250, p = .007, d = 0.17) but not
infrequent use (b = 0.02, SE = 0.01, t = 1.52, df = 250, p = .129, d =
0.10), relative to non-use. Individuals who use infrequently demon­
strated a non-significant effect when compared against individuals who
use frequently (b = − 0.17, SE = 0.02, t = − 0.89, df = 250, p = .376, d =
− 0.06). These results indicate that frequent cannabis use was associated
with less improvement in anxiety and related disorder symptom severity
throughout treatment compared to non-use, albeit with a small effect
(Fig. 2). Individual one-level HLMs confirmed that the non-use (b =
− 0.13, SE = 0.01, t = − 13.73, df = 135, p < .001, d = − 1.18), infrequent
use (b = − 0.10, SE = 0.01, t = − 8.59, df = 44, p < .001, d = − 1.28), and
frequent use (b = − 0.09, SE = 0.01, t = − 7.42, df = 71, p < .001, d =
− 0.87) groups demonstrated significant reductions in symptom severity
throughout CBT. Therefore, although all three groups experienced sig­
nificant improvements in anxiety and related disorder symptoms from
pre-to post-treatment, the rate of change was significantly slower in
individuals who use cannabis frequently compared to those who do not
use cannabis. Notably, when examining end-of-treatment symptomspecific measure raw score means, two diagnostic groups had mean
scores representing subclinical symptoms and three groups had means
above clinical cut offs. Therefore, overall the sample was considered as
“improved but not recovered” as per Jacobson et al. (1999). Z scores at
each timepoint are reported in Table 4.
Cannabis-related problem severity, as per the CUDIT-R, did not
significantly predict anxiety and related disorder symptom change in the
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M.J. Ouellette et al.
Journal of Psychiatric Research 156 (2022) 690–697
Table 1
Demographics.
Table 1 (continued )
Non-Use
(n =
135)
Infrequent
Use (n = 45)
Frequent
Use (n =
73)
Variable
Age (years)
Mean (SD)
Gender
36.56
(12.71)
32.49
(12.22)
35.42
(9.41)
Male
Female
Transgender
Relationship status
22.2%
76.3%
1.5%
26.7%
71.1%
2.2%
30.1%
67.1%
2.7%
Single
In a relationship
Education
41.5%
57.8%
33.3%
62.2%
42.5%
57.5%
Some or completed
high school
Some or completed
post-secondary
education
Some or completed
graduate school
Ethnicity
18.5%
White
Indigenous
Black/AfroCaribbean/African
Asian
Biracial/Multiracial
Other
Principal Diagnosis
84.4%
0.7%
0.0%
88.9%
2.2%
0.0%
84.9%
1.4%
1.4%
3.0%
3.7%
0.7%
2.2%
2.2%
0.0%
0.0%
0.0%
1.4%
Generalized Anxiety
Disorder
Social Anxiety
Disorder
Posttraumatic Stress
Disorder
Panic Disorder/
Agoraphobia
Other (e.g., anxiety
and related
disorders, mood
disorders,
personality
disorders)
Additional Diagnosis
Major Depressive
Disorder
Persistent
Depressive Disorder
Generalized Anxiety
Disorder
Social Anxiety
Disorder
Panic Disorder/
Agoraphobia
Cannabis Use
Disorder
Other (e.g., anxiety
and related
disorders, mood
disorders,
personality
disorders)
28.9% n
= 39
17.8% n
= 24
13.3% n
= 18
8.9% n
= 12
8.9% n
= 12
8.9%
23.3%
65.9%
73.3%
65.8%
8.9%
13.3%
6.9%
Non-Use
(n =
135)
Comparisons
20.0% n = 9
6.7% n = 3
4.4% n = 2
17.8% n
= 13
21.9% n
= 16
16.4% n
= 12
4.1% n =
3
12.3% n
=9
24.4%
17.8%
28.77%
8.15%
11.1%
23.29%
19.26%
15.6%
20.55%
18.52%
17.8%
20.55%
13.3%
6.7%
20.55%
0.0%
4.44%
10.96%
29.6%
40.0%
52.1%
Frequent
Use (n =
73)
Number of additional
diagnoses
H(2) = 4.94 p
= .085, ε2 =
.020
Mean (SD)
Baseline CUDIT-R scores
Mean (SD)
χ2(4) = 2.18,
2.01
(1.04)
Range
p = .70, V =
.07
2.04 (1.20)
2.52
(1.64)
3.71 (2.96)
11.03
(5.69)
3 to 27
1 to 12
Comparisons
H(2) = 1.89, p
= .388, ε2 =
.013
Note. Principal diagnosis = A mental health condition that is the patient’s most
pressing concern; Additional diagnosis = Mental health conditions secondary to
the principal diagnosis; Diagnostic data for principal diagnoses were available
for 74% (n = 188) of individuals.
χ2(2) = .76, p
= .68, V = .06
Table 2
Baseline means (SD) for symptom-specific measures matching participants’ CBT
group.
χ2(4) = 4.70,
p = .32, V =
.10
OCI-R
PCL-5
PDSS
PSWQ
SPIN
30.00 (8.63)
55.47 (10.81)
15.30 (4.37)
67.54 (8.42)
46.27 (8.45)
sample of individuals who use cannabis only (b = − 0.09, SE = 0.00, t =
0.15, df = 115, p = .879, d = 0.02). Cannabis-related problems did not
appear to have a significant effect on the trajectory of change in anxiety
and related disorder symptom severity throughout CBT.
χ2(10) = 8.73,
22.2% n =
10
13.3% n = 6
Infrequent
Use (n = 45)
p = .56, V =
.14
3.3. Changes in illness intrusiveness across frequency of
cannabis use groups
Complete pre- and post-treatment data for the IIRS were only
available for 126 participants (see Table 5). We assessed whether the
IIRS total score improved significantly from pre-to post-treatment across
the non-use, infrequent use, and frequent use groups. There was a sig­
nificant main effect of Time [F(1,123) = 27.20, p < .001, η2p = .18], but
the main effect of Group [F(2,123) = 0.72, p = .488, η2p = .01] and the
Group X Time interaction [F(2,123) = 2.00, p = .140, η2p = .03] were
non-significant. These results indicate that changes in anxiety-related
illness intrusiveness from pre-to post-treatment were unrelated to
cannabis use frequency. Differences in IIRS at pre- [F(2,250) = 1.61, p =
.201, η2 = 0.01] and post-treatment F(2,123) = 1.72, p = .183, η2 =
0.03] were non-significant.
χ2(8) = 7.78,
p = .456, V =
.144
4. Discussion
This study adds to the sparse literature examining cannabis use’s
impact on CBT outcomes for anxiety and related disorders. Consistent
with our first hypothesis, frequent cannabis use (2–3 times per week or
more) was associated with less anxiety and related disorder symptom
reduction from pre-to post-CBT compared to non-use. This is inconsis­
tent with results using brief CBT where cannabis use did not impact
outcomes (Bricker et al., 2007; Ruglass et al., 2017), however, the cur­
rent study used a standard 12-session CBT protocol for anxiety and
related disorders and did not exclude severe cannabis use presentations,
which may partially explain the contrasting findings. On the other hand,
this finding is consistent with research suggesting that cannabis use
moderates treatment outcomes. Buckner et al. (2021) compared
MET-CBT and integrated cannabis and anxiety reduction treatment
(ICART). They found that ICART led to better outcomes than MET-CBT
for those who used more baseline cannabis use while MET-CBT led to
better outcomes than ICART for those with low levels of baseline
cannabis use (Buckner et al., 2021). Although our study and Buckner
et al.‘s study differed in type of treatment offered, both suggest that
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M.J. Ouellette et al.
Journal of Psychiatric Research 156 (2022) 690–697
Fig. 1. Participant CBT group allocation, completion, and early termination.
impact on treatment outcomes. This is consistent with research on
combined CBT and pharmacotherapy for anxiety and depressive symp­
toms where low cannabis use frequency did not impact outcomes
(Bricker et al., 2007).
Inconsistent with our hypothesis, cannabis-related problem severity
was not associated with dampened CBT outcomes for anxiety and
related disorders, adding to the nuances of investigating the potential
impact of cannabis use and misuse within CBT. It is possible that our
sample did not present with a broad enough severity range to see
meaningful relationships between cannabis-related problems and CBT
outcomes, as most participants did not have a CUD diagnosis and the
mean CUDIT-R score for the frequent use group was below the CUDIT-R
total cut off score (Adamson et al., 2010). Higher CUD rates might reveal
a relationship between cannabis-related problem severity and CBT
outcomes, however the current study’s CUD rates are representative of a
naturalistic sample of individuals seeking anxiety treatment. It may be
that cannabis-related problems are less important than cannabis use
frequency in affecting CBT outcomes in this population.
There are multiple ways that frequent cannabis use might interfere
with CBT outcomes for anxiety and related disorders. For example,
negative cognitive impacts of cannabis use (e.g., memory, attention;
Broyd et al., 2016) or associated amotivation (e.g., Meier and White,
2018) may make it more difficult for participants to engage in CBT, and
thus affect outcomes. In fact, some research suggests that there are
biological changes involved in the cognitive and amotivation effects of
Table 3
Results of hierarchical linear modelling assessing the effect of cannabis use
status (non-use, infrequent use and frequent use) and cannabis-related problem
severity (CUDIT-R) on trajectory of change in symptom severity (z-score) over
the course of treatment.
Full Sample z-score
Effect
df
p
d
Initial z-score (Intercept)
1.47
0.09
15.83
Infrequent Use
− 0.03
0.19
− 0.14
Frequent Use
0.24
0.16
1.49
z-score Over Time (Slope)
− 0.13
0.01
− 14.74
Infrequent Use
0.02
0.02
1.31
Frequent Use
0.04
0.02
2.68
CUDIT-R in Individuals Who Use Cannabis Only (n = 118)
b
SE
t
250
250
250
250
250
250
<.001
.886
.137
<.001
.190
.008
− 0.01
0.09
− 0.93
0.08
0.17
Effect
b
SE
t
df
p
d
Initial z-score (Intercept)
CUDIT-R
z-score Over Time (Slope)
CUDIT-R
1.60
0.02
− 0.09
0.00
0.10
0.02
0.01
0.00
16.15
1.43
− 10.86
.15
116
116
116
116
<.001
.157
<.001
.879
0.13
− 1.00
0.01
cannabis use may be associated with poorer outcomes with certain
treatments. Additionally, the present findings indicate that cannabis use
frequency appears to impact treatment outcomes, as unlike frequent
cannabis use, infrequent cannabis use was not found to have a negative
Fig. 2. Change in symptom severity (z-score) across
levels of cannabis use (non-use, infrequent use, and
frequent use).
Note. Individuals who used frequently experienced a
statistically significant slower reduction in anxiety
symptoms throughout CBT compared to the non-use
group. The unit of time is coded as one week, and
treatment occurs over the course of 12 weeks, adding
pre- and post-treatment for a total of 14 time points.
See data analysis section for detail on how z-scores
were calculated for each diagnostic measure.
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M.J. Ouellette et al.
Journal of Psychiatric Research 156 (2022) 690–697
Table 4
Mean z scores throughout CBT with ANOVA and Tuckey HSD comparisons between cannabis use groups.
Week
Mean Z score
Non-use
Infrequent use
Frequent use
F
df
p
η2
Tuckey HSD
Comparisons
PreCBT
1
2
3
4
5
6
1.72
1.72
1.9
.96
2,
250
ns
.008
1.21
1.26
1.63
2.07
2,
156
ns
.026
1.18
1.00
1.30
.79
2,
195
ns
.008
.99
1.10
1.32
1.47
2,
198
ns
.015
.97
.95
1.35
2.00
2,
196
ns
.020
.75
.87
1.35
3.89
2, 182
.022
.041
Frequent
use >
Non-use
7
8
9
10
11
12
PostCBT
.65
.64
1.22
3.67
2, 184
.41
.66
1.30
7.08
2, 171
.26
.38
.87
3.24
2, 163
.23
.13
1.00
5.17
2, 153
.001
.076
Frequent
use > Nonuse
.042
.038
Frequent
use > Nonuse
.007
.063
Frequent use
> Non-use &
Infrequent
use
.11
− .29
.55
2.67
2,
135
ns
.038
− .04
− .15
1.11
7.65
2, 96
.027
.038
Frequent
use > Nonuse
.14
.30
.69
2.10
2,
148
ns
.028
.53
.39
.77
.82
2,
125
ns
.013
outcomes, however this is an important area of future research. The
current sample was predominantly White and cis-gender and therefore
the results may not generalize to diverse groups who report differences
in motives and cannabis use patterns (Buckner et al., 2016; Wu et al.,
2016). This is an area for future research. Finally, the current study
relied on self-report measures which are subjective and thus, may lead to
biased reporting.
The current results are preliminary and require replication with
consideration for the limitations. With this in mind, our findings suggest
that cannabis use is not necessarily detrimental to CBT outcomes given
that all groups, including the frequent use group, experienced significant
improvement in anxiety and related disorder symptoms from pre-to
post-treatment. However, it may be worth screening for cannabis use
frequency in patients seeking CBT for anxiety and related disorders.
Clinicians may recommend that individuals who use cannabis frequently
attempt to reduce their use prior to CBT to maximize outcomes. It may
also be helpful for clinicians to closely monitor the timing of use for
individuals who use cannabis frequently throughout CBT and help pa­
tients experiment with small shifts in when and how they use rather than
how much they use. For example, avoiding cannabis use right before a
therapy session may increase the patient’s ability to focus and retain
information learned in CBT. However, the current results suggest that
frequent cannabis use should not warrant unilateral exclusion from CBT
for anxiety and related disorders as patients generally benefit from CBT
despite their cannabis use. In fact, successful CBT may have helpful
downstream effects on cannabis use for those who use as a form of
avoidance.
In summary, this study is one of the first to examine the relationship
between cannabis use and CBT outcomes for anxiety and related disor­
ders. Results indicated that individuals who use cannabis frequently
experienced significant symptom improvement, but dampened CBT
outcomes compared to non-use. Future research should attempt to
replicate the findings and continue to consider the most impactful ways
of measuring and understanding cannabis use and disuse.
Table 5
Means and standard deviations of IIRS from pre-to post-treatment across groups.
Variable
IIRS Total Score
Non-Use
Infrequent Use
Frequent Use
IIRS Total Score
Non/Infrequent Use
Use
N
98
28
Pre-Treatment
Post-Treatment
Mean
SD
Mean
SD
57.30
56.71
57.25
15.35
12.56
11.82
48.99
45.29
53.82
16.83
15.18
17.75
57.15
57.25
14.66
11.81
48.08
53.82
16.45
17.75
<.001
.137
Frequent use
> Non-use &
Infrequent
use
Note. IIRS = Illness Intrusiveness Rating Scale.
cannabis, such as reduced dopamine associated with heavy cannabis use
(Ferland and Hurd, 2020). If participants who use cannabis frequently
are experiencing these negative effects of cannabis use, they may
struggle to learn or practice the CBT skills more than individuals who
use cannabis infrequently or do not use. Engaging in homework (i.e.,
practicing CBT skills outside of the therapy context) enhances CBT
outcomes (Kazantzis et al., 2010) and therefore if individuals who use
cannabis frequently struggle to engage in homework, it is plausible that
they would experience dampened outcomes. Research is needed to
specifically investigate these hypotheses. High cannabis use frequency
may also serve as a subtle avoidance strategy, which may be harder to
target in CBT protocols where overt avoidance is a core treatment target.
Future studies should measure cannabis use throughout treatment to
investigate the temporal relationship between fluctuations in cannabis
use and symptom change in CBT.
There are several limitations to consider when interpreting the cur­
rent results. First, there is no standardized method of categorizing
cannabis use patterns. Differing cannabis use definitions across studies
complicates comparisons of results between them. The current study
used cannabis use frequency and cannabis-related problem severity to
attempt to gain a more specific understanding of the impact of cannabis
use on treatment outcomes. Ideally, the field would standardize frequent
vs. infrequent use and studies would further capture various factors
involved in cannabis use (e.g., product, amount consumed) to identify
variables that contribute most of the variance in CBT outcomes, and
which are negligible. Given the lack of comprehensive cannabis use
measures, future studies should attempt to develop improved cannabis
use measures to examine the effects of these variables on treatment
outcomes. Additionally, the impact of cannabis on CBT outcomes was
not compared between diagnostic groups due to small sub-sample sizes.
Given differing reported frequencies of use across anxiety disorder
groups in the current study (e.g., higher use in SAD), the impact of use
on CBT outcomes may be more or less prominent with different pre­
senting concerns. Further, there were too few individuals with likely
CUD as per the CUDIT-R or diagnosed CUD to examine the effect on CBT
Role of funding source
The study has received funding from the Michael G. DeGroote Centre
for Medicinal Cannabis Research but the sponsors had no other role in
the study.
Grant reference: McCabe, R.E., Rowa, K., Pawluk, E., Phung, N., &
Soreni, N. Cannabis Use and Anxiety Disorders. Seed grant received
October 2018 from the Michael G. DeGroote Centre for Medicinal
Cannabis Research.
CRediT authorship contribution statement
Mélise J. Ouellette: Conceptualization, Methodology, Formal
analysis, Writing – original draft, Writing – review & editing. Karen
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M.J. Ouellette et al.
Journal of Psychiatric Research 156 (2022) 690–697
Rowa: Conceptualization, Methodology, Supervision, Writing – review
& editing. Duncan H. Cameron: Conceptualization, Formal analysis,
Writing – original draft, Writing – review & editing. Ashleigh Elcock:
Data curation. Noam Soreni: Conceptualization, Writing – review &
editing. Elizabeth J. Pawluk: Conceptualization, Methodology, Writing
– review & editing. Randi E. McCabe: Conceptualization, Methodology,
Supervision, Writing – review & editing, Resources.
Ferland, J.N., Hurd, Y.L., 2020. Deconstructing the neurobiology of cannabis use
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Declaration of competing interest
No conflicts of interests to declare.
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