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The empirical status of acceptance and commitment therapy: A review of meta-analyses

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The efficacy of Acceptance and Commitment Therapy (ACT) has been evaluated in many randomized controlled trials investigating a broad range of target conditions. This paper reviews the meta-analytic evidence on ACT. The 20 included meta-analyses reported 100 controlled effect sizes across n = 12,477 participants. Controlled effect sizes were grouped by target conditions and comparison group. Results showed that ACT is efficacious for all conditions examined, including anxiety, depression, substance use, pain, and transdiagnostic groups. Results also showed that ACT was generally superior to inactive controls (e.g. waitlist, placebo), treatment as usual, and most active intervention conditions (excluding CBT). Weaknesses and areas for future development are discussed.
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Journal of Contextual Behavioral Science 18 (2020) 181–192
Available online 29 September 2020
2212-1447/© 2020 The Author(s). Published by Elsevier Inc. on behalf of Association for Contextual Behavioral Science. This is an open access article under the
CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Review Articles
The empirical status of acceptance and commitment therapy: A review of
meta-analyses
Andrew T. Gloster
a
,
*
, Noemi Walder
a
, Michael E. Levin
b
, Michael P. Twohig
b
, Maria Karekla
c
a
University of Basel, Division of Clinical Psychology and Intervention Science, Switzerland
b
Utah State University, U.S.A
c
University of Cyprus, Cyprus
ARTICLE INFO
Keywords:
Acceptance and commitment therapy
Review
Meta-analysis
Evidence
ABSTRACT
The efcacy of Acceptance and Commitment Therapy (ACT) has been evaluated in many randomized controlled
trials investigating a broad range of target conditions. This paper reviews the meta-analytic evidence on ACT.
The 20 included meta-analyses reported 100 controlled effect sizes across n =12,477 participants. Controlled
effect sizes were grouped by target conditions and comparison group. Results showed that ACT is efcacious for
all conditions examined, including anxiety, depression, substance use, pain, and transdiagnostic groups. Results
also showed that ACT was generally superior to inactive controls (e.g. waitlist, placebo), treatment as usual, and
most active intervention conditions (excluding CBT). Weaknesses and areas for future development are
discussed.
1. Introduction
Acceptance and Commitment Therapy (ACT) aims to decrease
suffering and increase well-being via six core processes of change
(Hayes, Strosahl, & Wilson, 2012). In the thirty years since the rst study
on ACT was published (Zettle & Hayes, 1986), over 325 randomized
controlled trials have been conducted (Hayes, 2019). From its seeds in
North America, the proliferation of ACT trials has resulted in empirical
studies from South America, Europe, Asia, Africa, and Australia. Such
impressive growth is matched by positive results, with most studies
reporting results that favor ACT. To date, no counterindications or iat-
rogenic effects have been reported to our knowledge, though they have
not been extensively studied in an explicit manner. Nevertheless, some
studies have reported that ACT performed less well compared to a
control group in some comparisons. For example, ve studies found that
outcomes were not signicantly different compared to either treatment
as usual, cognitive behavioral therapy (CBT), befriending, or waitlist
control (Craske et al., 2014; Plumb Vilardaga, 2013; Shawyer et al.,
2012; Wetherell et al., 2011; White et al., 2011). Other studies showed
different change trajectories between ACT and the control condition. In
one study, ACT was superior to CBT at posttreatment but not
signicantly different at a 3-months follow-up timepoint (Avdagic,
Morrissey, & Boschen, 2014) and in another, ACT was inferior at post-
treatment but superior to CBT at 6-months follow-up (Lanza, García,
Lamelas, & Gonz´
alez-Men´
endez, 2014). Furthermore, the quality of
studies within the ACT literature varies greatly, a fact criticized in the
literature (Linardon, Gleeson, Yap, Murphy, & Brennan, 2019; ¨
Ost,
2014). Thus, there is a need to systematically examine the current
literature and, further, to assess the methodological quality of this
evidence.
Matching the development of randomized controlled studies is the
growth of reviews and meta-analyses that have examined ACT. To date,
over 60 such papers have examined ACT within various topics ranging
from clinical psychology to behavioral health. Many of the reviews and
meta-analyses examine ACT in combination with other interventions
such as dialectic behavioral therapy, mindfulness-based cognitive ther-
apy, or behavior activation depending on the purpose of the study. This
fact makes it difcult to determine the efcacy of ACT in isolation.
Furthermore, many reviews and meta-analyses examine the effect of
ACT in a single group of diagnoses (e.g., depression, anxiety, psychosis,
etc.). Whereas this is common in the literature, the theoretical basis of
ACT is transdiagnostic and thus it is important to systematically examine
This research was supported by the Swiss National Science Foundation (SNF Grant # PP00P1_163716/1 & PP00P1_190082).
* Corresponding author. University of Basel Department of Psychology Division of Clinical Psychology and Intervention Science Missionsstrasse, 62 A 4055, Basel,
Switzerland.
E-mail address: andrew.gloster@unibas.ch (A.T. Gloster).
Contents lists available at ScienceDirect
Journal of Contextual Behavioral Science
journal homepage: www.elsevier.com/locate/jcbs
https://doi.org/10.1016/j.jcbs.2020.09.009
Received 13 March 2020; Received in revised form 18 September 2020; Accepted 24 September 2020
Journal of Contextual Behavioral Science 18 (2020) 181–192
182
the full breadth of studies that exist in order to determine if ACT is
equally efcacious across diagnoses or if ACT is less efcacious for some
conditions. Furthermore, the theoretical basis of ACT suggests that
outcomes of interest in intervention studies should not focus (exclu-
sively) on symptoms or diagnoses, as has been done traditionally in the
larger psychotherapy literature, but rather measure the degree to which
ACT improves participantsfunctioning and well-being.
Summary claims of ACTs efcacy as with any intervention are
also relative, in that the reported effect sizes are impacted by the com-
parison group used to determine the effect size. For example, an un-
controlled effect size (i.e., within group, pre-post comparison) will
almost always be larger than controlled effect sizes (i.e., comparison to
changes seen in participants in an alternate condition). Likewise, the
between-group effect sizes differ as a function of the comparison group.
It is therefore necessary to systematically compare ACT across various
diagnostic categories and comparison groups in order to determine their
impact on observed effect sizes.
With these considerations in mind, the aim of the present study was
to answer the question: what are the aggregated effect sizes of ACT vs.
control groups, and by target conditions, across published meta-
analyses. Towards this end, we reviewed the existing meta-analytic
evidence of effect sizes for ACT factoring in control group and target
condition. Specically, we only included meta-analyses reporting
between-condition analyses (controlled effect sizes) and where ACT was
tested in isolation (e.g., not grouped together with other therapies).
2. Method
2.1. Selection of meta-analyses
A systematic literature search was conducted by the second author
on August 30th, 2019 to identify meta-analyses of ACT. In electronic
databases (Ovid Medline®, PsycArticles, PsycInfo, Web of Science, and
the compilation on the webpage of the Association of Contextual
Behavioral Science (ACBS, 2020)) the following search terms were used:
“acceptance, commitment, therapy, meta, and analysis. These
searches yielded 53 results. An additional 14 meta-analyses were iden-
tied in reference lists or via hand search. Overall the literature search
yielded 67 results. Inclusion criteria for this review were: 1) written in
English, 2) included meta-analytic analyses of randomized controlled
trials comparing ACT to active and/or inactive control conditions, and
3) published in a peer-reviewed journal.
During a rst screening process of the 67 initial manuscripts, 44 were
excluded because 2 meta-analyses were not written in English, 3 were
comments on or authors responses to a published meta-analysis, 16
were reviews and did not report any controlled meta-analytic effect
sizes, 16 did not include at least one effect size for ACT compared to
another condition, 2 were not peer-reviewed, 2 meta-analyses investi-
gated psychological exibility processes exclusively in the lab (rather
than RCTs), and 2 only described the protocol of the meta-analysis (for
more details see owchart in Fig. 1). After the extraction (see next
section) three more meta-analyses were excluded because they did not
report effect sizes for ACT alone compared to inactive/active conditions
(instead they combined ACT with other mindfulness-based and modern
cognitive behavioral treatments).
Fig. 1. Flowchart describing literature search and processing.
A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
183
2.2. Extraction and rating
After the rst screening process, the information of each remaining
meta-analysis was extracted. We extracted effect sizes for different
outcome measures, over different control conditions, and the number of
comparisons these effect sizes included. In some cases, different effect
sizes were given for the same comparison (e.g., ACT compared to
waitlist). In these instances, the smallest effect size was chosen. For
example, when outliers were omitted, the effect size without the outliers
was the one extracted if it had a smaller effect size than the one with
outliers.
In a rst step, we grouped the effect sizes according to the investi-
gated target condition. If a meta-analysis combined studies looking at
different target conditions, we classied the reported effect size as
transdiagnostic. This resulted in the following target conditions:
depression (n =15), anxiety (n =11), substance abuse (n =6), chronic
pain (n =8), transdiagnostic combinations of conditions (n =24), all
other conditions (n =10), and other outcomes such as quality of life (n
=26).
In a second step, three independent raters (rst, third and last
author) rated the intervention or control condition ACT was compared
to, for all effect sizes reported within the identied meta-analyses.
Comparison groups were waitlist (WL), cognitive behavior therapy
(CBT), active treatments not including CBT (active), treatment as usual
(TAU), placebo, or a combination of different non-active control groups
that includes WL, TAU, and placebo when they were not analyzed
separately in the meta-analyses (combined control conditions). After
this rating, differences were examined, discussed, and a consensus
grouping was reached. All raters agreed with the nal rating. The aim of
the rating was to cluster the effect sizes based on their comparison group
and to see how ACT performs compared to different control conditions.
Within all included meta-analyses 100 comparisons were identied,
Table 1
Results of the Assessing the Methodological Quality of Systematic Reviews 2 (AMSTAR 2) quality assessment.
Meta-Analysis AMSTAR 2 Items
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
¨
Ost (2008) No No Yes Partial
yes
No No No Partial
Yes
Yes No Yes No Yes Yes Yes No
Powers, Zum V¨
orde Sive V¨
ording, and
Emmelkamp (2009)
No No No Partial
yes
No No No Partial
Yes
Yes No Yes Yes Yes Yes Yes No
Veehof et al. (2011) Yes No No Partial
yes
Yes Yes No Partial
Yes
Yes No Yes No Yes No Yes Yes
(Ruiz (2012)) Yes No Yes Partial
yes
No No Yes Partial
Yes
No No Yes No Yes Yes Yes No
Bluett et al. (2014) No No No Partial
yes
No No No Partial
Yes
No No Yes No Yes No No No
¨
Ost (2014) No No Yes Partial
yes
No No No Partial
Yes
Yes No Yes No Yes No Yes No
A-Tjak et al. (2015) No No No Yes Yes No No Partial
Yes
Yes No Yes Yes Yes Yes Yes No
(Hacker et al. (2016)) Yes No No Partial
yes
Yes Yes No Partial
Yes
Yes No Yes No No No Yes Yes
Lee, An, Levin, and Twohig (2015) Yes No No Partial
yes
No Yes No Partial
Yes
No No Yes No Yes No Yes Yes
Brown, Glendenning, Hoon, and John
(2016)
Yes No No Partial
yes
Yes No No Partial
Yes
Yes No Yes No Yes No No Yes
Spijkerman et al. (2016) Yes No No Partial
yes
Yes Yes No Yes Yes No Yes Yes Yes Yes Yes No
Tonarelli et al. (2016) Yes Partial
yes
No Partial
yes
Yes No No Partial
Yes
No No Yes No Yes No No No
Veehof et al. (2016) No Partial
yes
No Partial
yes
Yes No No Yes Yes No Yes No Yes No Yes Yes
French et al. (2017) Yes No No Yes Yes No No Partial
Yes
Yes No Yes Yes Yes Yes Yes No
Hughes et al. (2017) Yes Yes No Yes No No Yes Yes Yes No Yes No Yes Yes No No
Rogers, Ferrari, Mosely, Lang, and Brennan
(2017)
Yes No No Partial
yes
Yes Yes No Yes No No Yes No Yes Yes Yes Yes
Reeve et al. (2018) Yes No Yes Partial
yes
No No No Partial
Yes
Yes No Yes No Yes Yes Yes No
Howell and Passmore, (2019) Yes No No Partial
yes
No No No Partial
Yes
No No Yes No Yes No Yes No
Ii et al. (2019) Yes Yes No Partial
yes
Yes Yes No Yes Yes No Yes Yes Yes Yes No Yes
Linardon et al. (2019 Yes No No Partial
yes
No No No Partial
Yes
Yes No Yes No Yes No Yes Yes
Notes: Item 1) Did the research questions and inclusion criteria for the review include the components of PICO?; Item 2) Did the meta-analysis contain an explicit
statement that the methods were established prior to the conduct of the meta-analysis and did the meta-analysis justify any signicant deviations from the protocol?;
Item 3) Was an explanation about the selection of the study designs for inclusion included in the meta-analysis?; Item 4) Was a comprehensive literature search strategy
used?; Item 5) Was the study selection performed in duplicate?; Item 6) Was the data extraction performed in duplicate?; Item 7) Was a list of excluded studies with
justication for the exclusions provided?; Item 8) Were the included studies described in adequate detail?; Item 9) Did the authors of the meta-analysis use a satis-
factory technique for assessing the risk of bias (RoB) in individual studies that were included in the review?; Item 10) Did the authors of the meta-analysis report on the
sources of funding for the studies included in the review?; Item 11) Were appropriate methods used for statistical combination of results?; Item 12) Was the potential
impact of RoB in individual studies on the results of the meta-analysis assessed?; Item 13) Did the authors of the meta-analysis account for RoB in individual studies
when interpreting/discussing the results of the review?; Item 14) Was a satisfactory explanation for, and discussion of, any heterogeneity observed in the results of the
review provided?; Item 15) Did the authors of the meta-analysis carry out an adequate investigation of publication bias (small study bias) and discuss its likely impact
on the results of the review?; Item 16) Did the authors of the meta-analysis report any potential sources of conict of interest, including any funding they received for
conducting the review?.
A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
184
which were split as follows: n =12 comparison to CBT, n =22 com-
parisons to another active intervention, n =13 comparisons to TAU, n =
11 comparisons to WL, n =3 comparisons to placebo, and n =39
comparisons to combined control conditions.
For the nal sample of 20 meta-analyses, the third and fourth author
independently performed a quality assessment using the validated
Assessing the Methodological Quality of Systematic Reviews 2
(AMSTAR-2) checklist. The AMSTAR-2 checklist includes 16 items
focusing on the use of PICO as inclusion criteria, the prior registration of
the review designs, how studies were selected and excluded, how the
data was extracted, how the authors accounted for biases in their
selected studies, the statistical analyses and the funding of the review as
well as conicts of interests (Shea et al., 2017). All items can be found in
the notes of Table 1.
Outcomes were determined by means of various standardized in-
terviews, questionnaires, behavioral or biological measurements. A
detailed list of all measures across all comparisons is provided in
Table 2.
All effect sizes in this review are reported in hedges g or are other-
wise indicated. We rst extracted the effect sizes as they were in the
original meta-analyses. Effect sizes originally reported in Cohens d were
transformed into Hedges g using the ‘escpackage in R (Lüdecke, 2018)
to increase comparability between effect sizes from different
meta-analyses. Cohens d and Hedges g are very similar, however, in
small sample sizes Hedges g outperforms Cohens d (Ellis, 2010). To
simplify the interpretation of the results, U
3
scores are also provided. U
scores were introduced by Cohen (1988) as a measure of nonoverlap. A
U
3
score describes the percentage of the control group (e.g., CBT, Active,
TAU, WL) that is exceeded by the upper half of the experimental group
(ACT). Each U
3
score corresponds to a specic effect size. For example,
an effect size of 0 would correspond to a U
3
score of 50% and an effect
size of 1 would correspond to a U
3
score of 84%. To illustrate the
meaning of a U
3
score, a U
3
score of 84% signies that the outcome of an
average ACT patient is superior to the outcome of 84% of the patients in
the control group. In each result section the effect sizes as well as the
range of the U
3
scores are given. Consider also Table 3, to see how a
single effect size is expressed as a U
3
score.
To further illustrate the results, we report an overall mean effect size
of the different effect sizes described within each target condition or
comparison condition. The overall mean effect size was determined by
the arithmetic mean of the individual effect sizes. These numbers should
be read with caution, since they could not be weighted for number of
participants as is done in primary meta-analyses.
3. Results
3.1. Sample
The nal sample consisted of 20 meta-analyses, which were based on
133 studies and 12,477 participants. The individual studies that were
reviewed in the meta-analyses spanned from 1986 (Zettle & Hayes,
1986) to 2018 (Gr´
egoire, Lachance, Bouffard, & Dionne, 2018). Some
studies were used in more than one meta-analysis. In order to under-
stand the extent that individual studies were used in multiple
meta-analyses (double-dipping), we examined all included studies in
each meta-analysis and reviewed how many times each constituent
study was used across all the included meta-analyses. More than half of
the studies were included in only one meta-analysis. A third of the
studies were used in two to four meta-analyses, a few were used ve to
seven times, and one study (Lundgren, Dahl, Melin, & Kies, 2006) was
used ten times. The amount of unique studies in each meta-analysis
varied greatly. Some of the more current meta-analyses report up to
85% unique studies (Reeve, Tickle, & Moghaddam, 2018), though one
reported no unique studies (Ii et al., 2019). Newer meta-analyses have a
greater chance of including unique studies (because new studies are
continually being reported), while some of the older metanalyses no
longer contain any unique studies as a function of their age (Tonarelli,
Pasillas, Alvarado, Dwivedi, & Cancellare, 2016; Veehof, Oskam,
Schreurs, & Bohlmeijer, 2011; ¨
Ost, 2008).
The methodological quality of the included meta-analyses were
assessed using the AMSTAR-2 checklist (Shea et al., 2017). All or nearly
all of the included meta-analyses reported on information assessed in the
checklist with respect to: literature search (item 4), details of the
included studies (item 8), appropriate statistical methods (item 11), and
accounted for risk of bias in interpretation (item 13). None or next to
none of the meta-analyses included information about: details of
excluded studies (item 7) and information on the funding source (item
10). The other information assessed by the checklist was included in
some to most of the included meta-analyses (range 415 of the
meta-analyses) (see Table 1 for details).
Over all comparisons analyzed in this review, only four comparisons
resulted in U
3
scores that were below 50%, meaning that for these four
comparisons the outcome of an average patient in the ACT condition is
superior to the outcome of less than 50% of the patients in the control
condition. In 19 comparisons U
3
scores ranging from 50.0% to 59.9%
were found, 44 comparisons had U
3
scores from 60.0% to 69.9%, 24
comparisons had U
3
scores from 70.0% to 79.9% and 4 comparisons
indicated U
3
scores higher than 80.0%. For the remaining 5 compari-
sons, the effect sizes were given in risk ratios that could not be translated
into U
3
scores from the information provided.
3.2. Outcomes of symptom reduction by target conditions
The ndings are presented for symptom reduction measures by
condition.
Depression (15 effect sizes). Nine meta-analyses were included in
this review that reported on the effects of ACT for depression. Most (6 of
9) presented with signicant effect sizes favoring ACT (range of ES g =
0.24- 0.76; small to medium ES) compared to active (e.g., TAU, all active
psychological interventions except CBT) and inactive (e.g., waitlist,
placebo) conditions. The overall mean ES was small, g =0.33. Two of the
meta-analytic studies favored the control condition, however both were
non-signicantly better than ACT for depression (Reeve et al., 2018
compared to combined control groups; Veehof, Trompetter, Bohlmeijer,
& Schreurs, 2016 compared to CBT). The U
3
scores for depression
ranged from 39.7% to 79.7%.
Anxiety (11 effect sizes). Seven meta-analyses were included that
reported effects of ACT for anxiety spectrum disorders. Six of these
presented with signicant effect sizes favoring ACT with small to me-
dium ES (g =0.18-0.57) compared to comparison conditions. Only one
meta-analysis favored active control conditions (Hacker, Stone, &
Macbeth, 2016), however the effect was negligible and non-signicant
(g =0.04, p >.05). The overall mean ES was small, g =0.24. The U
3
scores for anxiety ranged from 48.4% to 71.6%.
Substance use (6 effect sizes). Only three meta-analyses were
included that reported effects of ACT for substance use. Two of these
signicantly favored ACT with small effect sizes (g =0.40-0.45)
compared to other active interventions. The overall mean ES was small,
g =0.41. None of the studies favored the control conditions. The U
3
scores for substance use ranged from 63.3% to 67.4%.
Chronic Pain (8 effect sizes). Two meta-analyses were included in
this review that evaluated ACT for chronic pain, both of which focused
on studies comparing ACT to active interventions, CBT, and a combi-
nation of inactive control conditions. There was a signicant and large
effect favoring ACT for one meta-analysis (Hughes, Clark, Colclough,
Dale, & McMillan, 2017; g =0.83), whereas for the other meta-analysis
the effects were non-signicant (Veehof et al., 2016). The overall mean
ES was small, g =0.44. The U
3
scores for pain ranged from 49.2% to
82.6%.
Transdiagnostic combinations of conditions (24 effect sizes).
Five meta-analyses were included that examined the effects of ACT
transdiagnostically across a range of conditions compared to active and
A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
185
Table 2
Meta-analyses of acceptance and commitment therapy outcome measures.
Meta-analysis Number of effect
sizes in Comparisons
Outcome cluster Comparison
group
Timepoint Outcome Measures
¨
Ost (2008) 8 Transdiagnostic Active Post Specic measures not listed
5 Transdiagnostic TAU Post Specic measures not listed
2 Transdiagnostic WL Post Specic measures not listed
Powers et al.
(2009)
9 Transdiagnostic TAU Post BEST, CGI, DERS, Delusions, DSHI, Glycated hemoglobin,
Hallucinations, Pain, Rehospitalization, Self-reported diabetes self-
care, Smoking cessation, Stress symptoms hemoglobin
4 Transdiagnostic WL Post BDI, BMI, Hairs pulled, Job satisfaction/motivation, MGH-HS, Weight
Stigma Questionnaire
8 Transdiagnostic Active Post ASI, BAI, BDI, HDRS, Job satisfaction/motivation, MARS, Pain, Self-
reported use, SCL-90, TAI, Urine analysis
2 Depression Combined Post BDI, HDRS
5 Other Conditions: Physical
Health
Combined Post BMI, Glycated hemoglobin, Pain, Self-reported diabetes self-care,
Seizure frequency, Seizure index, Stress symptoms, Weight Stigma
Questionnaire,
7 Transdiagnostic Combined Post ASI, BEST, CGI, DERS, Delusions, DSHI, Hallucinations, Hairs pulled,
MGH-SH, Rehospitalization, Self-reported use, Smoking cessation,
Urinanalysis
4 Transdiagnostic Combined Post BAI, BDI, Job satisfaction/motivation, MARS, SCL-90, TAI
Veehof et al.
(2011)
2 Pain Combined Post HADS, Pain, PDI, SWLS
(Ruiz (2012)) 16 Transdiagnostic CBT Post and
FU
BAI, BDI, CSR, FACT-Breast, FNE, FQ, HRSD, Mood Visual Scale,
QOLI, QOLS, SASS, SIAS, SF-36, SPS, SUD, VSLS, WILL, Y-BOCS
10 Depression CBT Post and
FU
BDI, HRSD, Mood Visual Scale, SASS
9 Anxiety CBT Post and
FU
BAI, CSR, FNE, FQ, HAS, MARS, PSWQ, SIAS, SPS, STAI, SUD, TAI,
WILL, Y-BOCS,
11 Other Outcomes: Quality of
Life
CBT Post and
FU
FACT-Breast, QOLS, QOLI, SF-36, VSLS
Bluett et al.
(2014)
7 Anxiety Active Post BAI, DASS, GAI, HADS, SCL-90-Anxiety, STAI-S
5 Anxiety CBT Post BAI, DASS, GAI, HADS, SCL-90-Anxiety, STAI-S
¨
Ost (2014) 16 Transdiagnostic WL Post Specic measures not listed
4 Transdiagnostic Placebo Post Specic measures not listed
14 Transdiagnostic TAU Post Specic measures not listed
30 Transdiagnostic Active Post Specic measures not listed
22 Transdiagnostic CBT Post Specic measures not listed
7 Transdiagnostic WL FU Follow-up Specic measures not listed
3 Transdiagnostic Placebo Follow-up Specic measures not listed
7 Transdiagnostic TAU Follow-up Specic measures not listed
23 Transdiagnostic Active Follow-up Specic measures not listed
17 Transdiagnostic CBT Follow-up Specic measures not listed
A-Tjak et al.
(2015)
9 Transdiagnostic WL Post and
FU
AAQ, Average hairs pulled per day, BMI, Clinician severity rating,
DASS, GHQ, Hours of viewing pornography, Mental health difculties,
MGH-HS, NIMH-TIS, PDI, Physical activity, PSWQ, Weekly Pain,
Weight Stigma Questionnaire, Stress, THI
5 Transdiagnostic Placebo Post and
FU
Condence in coping with command hallucinations, Condence to
resist command hallucinations, LDQ, OMPQ, PANSS, Seizure
frequency, THI, Y-BOCS
12 Transdiagnostic TAU Post and
FU
ADAMS, BDI, BDI-II, Believability ratings, BEST, BPI, BPRS, BSQ,
DSHI, Drug test, Drug use self-report, EDE-Q, FDI, ISS, GHQ, HbA1C,
Hallucinations, Number of glucose control, MIDAS, MPQ-SF, PAIRS,
Rehospitalization, Smoking Cessation Quit Rate, Self-management,
SBEQ, THI, Understanding, VABS
9 Transdiagnostic CBT Post and
FU
ASI, BAI, BDI, BPI, Drug test, Dysphoria, FQ, HDRS, Negative affect,
Negative self, PSWQ, RADS-2, Somatic, THI
30 Other Outcomes:
Secondary Outcome
CBT Post and
FU
Specic secondary outcome measures not listed
19 Other Outcomes: Quality of
Life
CBT Post and
FU
Specic secondary outcome measures not listed
23 Other Outcomes Process
Measures
Combined Post and
FU
Specic secondary outcome measures not listed
8 Transdiagnostic TAU Post and
FU
Specic secondary outcome measures not listed
8 Substance Abuse TAU Post and
FU
BDI-II, Drug Test, Drug use self-report, ISS, LDQ, Smoking Cessation
Quit Rate
15 Other Conditions: Somatic
Complaints
Combined Post and
FU
BMI, BSQ, CECS, COPE, GHQ, HbA1C, Mental health difculties,
MIDAS, MPQ-SF, Number in glucose control, OMPQ, Physical activity,
POMS, Self-management, Seizure frequency/duration, THI,
Understanding, Weekly pain
(Hacker et al.
(2016))
15 Depression Active Post BDI, CES-DC, DASS-D, HADS-D,
10 Anxiety Active Post ASI, BAI, CSR, DASS-A, HADS-A, PASS, PSWQ, STAI
28 Anxiety WL Post BAI, DASS-A, HADS-A, PAI-A, PSWQ, STAI, STAI-T
39 Depression WL Post BDI, CES-D, DASS-D, GDS-10, HADS-D, PAI-D, PHQ-9, RADS-2
Lee et al. (2015) 10 Substance Abuse Active Follow-up Substance abstinence
(continued on next page)
A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
186
Table 2 (continued )
Meta-analysis Number of effect
sizes in Comparisons
Outcome cluster Comparison
group
Timepoint Outcome Measures
3 Substance Abuse Active (CBT) Follow-up Substance abstinence
5 Substance Abuse: Smoking Active Post Substance abstinence
5 Substance Abuse: Drugs Active Post Substance abstinence
Brown et al.
(2016)
10 Depression Combined Post BDI, CES-D, DASS, HADS, MADRS-S
7 Anxiety Combined Post BAI, DASS, HADS
8 Other Outcomes: Quality of
Life
Combined Post GHQ-12, MHC-SF, QOLI, SCL-90
Spijkerman et al.
(2016)
5 Depression Combined Post BDI-II, CES-D, DASS-D, HADS-D, PHQ-9-D, POMS-D
5 Anxiety Combined Post BAI, DASS-A, HADS-A, POMS-A
2 Other Conditions: Stress Combined Post CSOSI, DASS-S, PSS, PSQ
4 Other Outcomes: Well-
Being
Combined Post MHC-SF, QOLI, SWLS, WHO-5,
2 Other Outcomes:
Mindfulness
Combined Post CAMS-R, FFMQ, FMI, MAAS
Tonarelli et al.
(2016)
2 Other Conditions:
Psychosis (Negative
Symptoms)
TAU Post PANNS +
2 Other Conditions:
Psychosis (Positive
Symptoms)
TAU Post PANNS -
3 Other Conditions:
Schizophrenia
TAU Post Delusions, Emotional dysfunction, Hallucinations
3 Other Conditions: Schizo-
affective
TAU Post Delusions, Emotional dysfunction, Hallucinations
2 Other Outcomes:
Rehospitalization
TAU Post Rehospitalization Rate at 4-month follow-up
Veehof et al.
(2016)
2 Pain CBT Post BPI-SF
2 Depression CBT Post BDI
3 Pain Active Post MPI, NRS, VAS
3 Depression Active Post HADS
2 Other Outcomes: Disability Active Post OMPQ, SF-36 PCS
2 Other Outcomes: Quality of
Life
Active Post QOLI
French et al.
(2017)
9 Depression Combined Post BDI-II, CES-D, DASS-21, CMDI, HADS
8 Depression WL Post BDI-II, CES-D, DASS-21, CMDI, HADS
8 Anxiety Combined Post BAI, DASS-21, HADS
8 Anxiety WL Post BAI, DASS-21, HADS
10 Other Outcomes:
Psychological Flexibility
Combined Post AAQ-II, AFQ-Y, AIS, CPAQ, PIPS, TAQ
8 Other Outcomes:
Psychological Flexibility
WL Post AAQ-II, CPAQ, PIPS
Hughes et al.
(2017)
3 Pain: Acceptance Combined Post BPCI-A, CPAQ
6 Other Outcomes: Quality of
Life
Combined Post LSQ, QOLI, QOLS, SF-36, SWLS
3 Other Outcomes: Quality of
Life
Combined Follow-up LSQ, QOLI, QOLS, SF-36, SWLS
5 Other Outcomes:
Functioning
Combined Post PAIRS, PDI, RMDQ
4 Other Outcomes:
Functioning
Combined Follow-up PAIRS, PDI
4 Anxiety Combined Post HADS, STAI-S
3 Anxiety Combined Follow-up HADS, STAI-S
5 Depression Combined Post BDI, DASS, HADS, PHQ-9
4 Depression Combined Follow-up BDI, DASS, HADS, PHQ-9
2 Other Outcomes:
Psychological Flexibility
Combined Post PIPS
2 Other Outcomes:
Psychological Flexibility
Combined Follow-up PIPS
6 Pain: Intensity Combined Post MPI, NRS, PIR, VAS
4 Pain: Intensity Combined Follow-up MPI, NRS, PIR, VAS
2 Pain Active Post BPI-S, NRS
2 Pain Active Follow-up BPI-S, NRS
2 Other Outcomes: Quality of
Life
Active Post SF-12 PCS, SWLS
2 Other Outcomes: Quality of
Life
Active Follow-up SF-12 PCS, SWLS
2 Other Outcomes:
Functioning
Active Post BPI-I, OMPQ, PDI
2 Other Outcomes:
Functioning
Active Follow-up BPI-I, OMPQ, PDI
2 Depression Active Post BDI-II, HADS
Rogers et al.
(2017)
3 Other Outcomes: Quality of
Life
Combined Post IWQOL-Lite, QOLI, WHOQOL
Reeve et al.
(2018)
3 Depression Combined Post MBI, SSQ
2 Depression Combined Follow-up MBI, SSQ
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A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
187
inactive control groups. All resulted in signicant small to large effect
sizes in favor of ACT (g =0.17-0.96). The overall mean ES was small, g
=0.46. The U
3
scores investigating transdiagnostic conditions ranged
from 51.2% to 83.1%.
Other conditions (10 effect sizes). Individual meta-analyses were
included that reported on other conditions, such as eating disorders (n =
1), psychosis (n =1), stress (n =2), somatic complaints (n =1) and
physical conditions (n =1). Five of these reported signicant small to
medium ES for ACT compared to control conditions (g =0.29- 0.64). In
only one meta-analysis specically for positive psychosis symptom-
atology there was a non-signicant negligible effect in favor of the TAU
control group compared to ACT (Tonarelli et al., 2016). The U
3
scores
investigating other conditions ranged from 44.0% to 73.9%.
Other Outcomes (26 effect sizes). Regarding quality of life as an
outcome of the interventions tested, 6 meta-analyses were found and all
reported effects in favor of ACT compared to active and inactive control
groups. For three of these meta-analyses the effects were signicant and
medium ES (g =0.37-0.45). For the rest (3 studies) there were non-
signicant differences between ACT and control conditions on quality
of life. The overall mean ES was small g =0.48. The U
3
scores range from
52.0% to 94.0%.
Three meta-analyses examined intervention effects on psychological
exibility. Two of the studies signicantly favored ACT compared to
active and inactive control conditions with small to large ES (g =0.32-
0.83). In the (Reeve et al. (2018)) meta-analysis, ACT did not signi-
cantly differ from other control conditions on psychological exibility.
The overall mean ES was small g =0.42. The U
3
scores range from 52.8%
to 79.7%.
Some meta-analyses (total n =7) utilized different outcome mea-
sures (e.g., well-being, rehospitalization, physical health, mindfulness,
functioning, and disability). Five of them presented with signicant
small to medium ES (g =0.29-0.67) in favor of ACT. For the other two
studies, ACT was not found to signicantly differ on these outcomes
(well-being; Spijkerman, Pots, & Bohlmeijer, 2016; and disability;
Veehof et al., 2016). The overall mean ES was medium g =0.57. The U
3
scores range from 56.7% to 99.4%.
3.3. Findings by comparison conditions
WL. Eleven effect sizes from seven meta-analyses compared ACT to
WL. All 11 comparisons favored ACT and all were reported to be sta-
tistically signicant. Effect sizes were calculated for outcomes of
depression, anxiety, eating disorders, transdiagnostic conditions, and
psychological exibility. These outcomes were measured at post and
follow up time points. The 11 meta-analytic effects comparing ACT to
WL reported ESs ranging from small (g =0.35; French,
Golijani-Moghaddam, & Schr¨
oder, 2017) to large (g =0.82; A-Tjak
et al., 2015). The mean overall ES comparing ACT to WL corresponded
to a medium effect (g =0.57). The U
3
scores range from 63.7% to 83.1%.
Placebo. Three effect sizes from two meta-analyses compared ACT
to placebo. Two of the three comparisons were reported to be statisti-
cally signicant. All the effect sizes for comparisons between ACT and
placebo were for transdiagnostic conditions. These outcomes were
measured at post and follow up time points. All three meta-analytic
effects reported for comparisons with placebo were medium effects
sizes ranging from g =.51 (A-Tjak et al., 2015) to g =0.59 (¨
Ost, 2014).
Table 2 (continued )
Meta-analysis Number of effect
sizes in Comparisons
Outcome cluster Comparison
group
Timepoint Outcome Measures
3 Other Conditions: Stress Combined Post DSI, GHQ-12, GHQ-28, PANAS, WEMWBS
2 Other Conditions: Stress Combined Follow-up GHQ-12, GHQ-28, WEMWBS
3 Other Outcomes:
Psychological Flexibility
Combined Post AAQ-II, COPE, SSVQ, VLQ, WBSI
2 Other Outcomes:
Psychological Flexibility
Combined Follow-up AAQ-II, SSVQ, VLQ, WBSI
Howell and
Passmore,
(2019)
5 Other Outcomes: Well-
Being
Combined Post ABS, MHC-SF, WBMMS
Ii et al. (2019) 3 Substance Abuse TAU Post Substance discontinuation
Linardon et al.
(2019)
3 Other Conditions: Eating
Disorders
WL Post Binge eating frequency, BSQ, DEBQ, EAT, EDE, PEWS
Notes: AAQ =Acceptance and Action Questionnaire, ABS =Affect Balance Scales, ADAMS =Anxiety, Depression, and Mood Scale, AFQ =Avoidance and Fusion
Questionnaire for Youth, AIS =Avoidance and Inexibility Scale, ASI =Addiction Severity Index, BAI =Beck Anxiety Inventory, BDI =Becks Depression Inventory,
BEST =Borderline evaluation of severity over time, BMI =Body Mass Index, BPCI =Brief Pain Coping Inventory, BPI =Brief Pain Inventory, BPRS =Brief Psychiatric
Rating Scale, BSQ =Body Shape Questionnaire, CAMS-R =Cognitive and Affective Mindfulness Scale Revised, CECS =Courtland Emotional Control Scale, CES-DC =
Centre for Epidemiological Studies Depression Scale for Children, CGI =Clinical Global Impression, CMDI =Chicago Multi-scale Depression Inventory, COPE =
Assessment of coping, CPAQ =Chronic Pain Acceptance Questionnaire, CSOSI =Calgary Symptoms of Stress Inventory, CSR =Clinical Severity Ratings, DASS =
Depression Anxiety Stress Scales, DEBQ =Dutch Eating Behavior Questionnaire, DERS =Difculties in Emotion Regulation Scale, DSHI =Deliberate Self-harm In-
ventory, DSI =Daily Stress Inventory, EAT =Eating Attitudes Test, EDE-Q =Eating Disorders Examination Questionnaire, FACT =Functional Assessment of Cancer
Therapy, FDI =Functional Disability Inventory, FFMQ =Five Facet Mindfulness Questionnaire, FNE =Fear of Negative Evaluation Scale, FQ=Fear Questionnaire,
GAI =Geriatric Anxiety Inventory, GHQ =General Health Questionnaire, HADS =Hospital Anxiety and Depression Scale, HDRS =Hamilton Depression Rating Scale,
ISS =Internalized Shame Scales, IWQOL =Impact of Weight on Quality of Life, LDQ =Leeds Dependence Questionnaire, LSQ =Life Satisfaction Questionnaire, MAAS
=Mindful Attention Awareness Scale, MARS =Mathematics Anxiety Rating Scale, MBI =Maslach Burnout Inventory, MGH-HS =Massachusetts General Hospital
Hairpulling Scale, MHC =Mental Health Continuum, MIDAS =Migraine Disability Assessment Scale, MPQ =McGill Pain Questionnaire, NIMH-TIS =NIMH-
Trichotillomania Impairment Scale, NRS =Numerical Rating Scale, OMPQ =
¨
Orebro Muscoloskeletal Pain Questionnaire, PAI =Personality Assessment Inventory,
PAIRS =Pain Impairment Relationship Scale, PANAS =Positive and Negative Affect Scale, PANSS =Positive and Negative Symptoms Scale, PASS =Pain Anxiety
Symptom Scale, PCS =Physical Component Summary, PDI =Pain Disability Index, PEWS =Pediatric Early Warning Score, PHQ =Patient Health Questionnaire, PIPS
=Psychological Inexibility in Pain Scale, POMS =Prole of Mood States, PSS =Perceived Stress Scale, PSWQ =Penn State Worry Questionnaire, QOLI =Quality of
Life Inventory, QOLS =Quality of Life Scale, RADS-2 =Reynolds Adolescent Depression Scale, RMDQ =Life Satisfaction Questionnaire, SASS =Social Adaptation Self-
Evaluation Scale, SBEQ =Subjective Binge Eating Questionnaire, SCL-90 =Symptom Checklist-90, SF-36 =Short Form Health Survey, SIAS =Social Interaction
Anxiety Scale, SPS =Social Phobia Scale, SSQ =Staff Stressor Questionnaire, SSVQ =Support Staff Values Questionnaire, STAI =State Trait Anxiety Inventory, SUD =
Subject Units of Discomfort, SWLS =Satisfaction with Life Scale, TAI =Test Anxiety Inventory, TAQ =Tinnitus Acceptance Questionnaire, THI =Tinnitus Handicap
Inventory, VABS =Vineland Adaptive Behaviors Scales, VAS =Visual Analogue Scale, VLQ =Valued Living Questionnaire, VSLS =Visual Scale Life Satisfaction,
WBMMS =Well-Being Manifestations Measure Scale, WBSI =White Bear Suppression Inventory, WEMWBS =Warwick-Edinburgh Mental Well-Being Scale, WHO-5 =
5 Item World Health Organization Well-Being Index, WHOQOL =World Health Organization Quality of Life, WILL =Willingness Scale, Y-BOCS =Yale-Brown
Obsessive-Compulsive Scale.
A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
188
Table 3
Effect sizes of included meta-analyses of Acceptance and Commitment Therapy Outcomes.
Meta-analysis Number of
Comparisons
Outcome cluster Comparison
group
Timepoint of comparison ES Signicance U
3
(%)
¨
Ost (2008) 8 Transdiagnostic Active Post 0.53 Signicant 70.2
5 Transdiagnostic TAU Post 0.79 Signicant 78.5
2 Transdiagnostic WL Post 0.96 Signicant 83.1
Powers et al. (2009) 9 Transdiagnostic TAU Post 0.42 Signicant 66.3
4 Transdiagnostic WL Post 0.68 Signicant 75.2
8 Transdiagnostic Active Post 0.18 Not
signicant
57.1
2 Depression Combined Post 0.76 Signicant 77.6
5 Other Conditions: Physical Health Combined Post 0.39 Signicant 65.2
7 Transdiagnostic Combined Post 0.60 Signicant 72.6
4 Transdiagnostic Combined Post 0.03 Not
signicant
51.2
Veehof et al. (2011) 2 Pain Combined Post 0.28 Not
signicant
61.0
(Ruiz (2012)) 16 Transdiagnostic CBT Timepoints combined
(Post and FU)
0.40 Signicant 65.5
10 Depression CBT Timepoints combined 0.27 Not
signicant
60.6
9 Anxiety CBT Timepoints combined 0.14 Not
signicant
55.6
11 Other Outcomes: Quality of Life CBT Timepoints combined 0.22 Not
signicant
58.7
Bluett et al. (2014) 7 Anxiety Active Post 0.02 Not
signicant
50.8
5 Anxiety CBT Post 0.00 Not
signicant
50.0
¨
Ost (2014) 16 Transdiagnostic WL Post 0.63 Signicant 73.6
4 Transdiagnostic Placebo Post 0.59 Not
signicant
72.2
14 Transdiagnostic TAU Post 0.55 Signicant 70.9
30 Transdiagnostic Active Post 0.22 Signicant 58.7
22 Transdiagnostic CBT Post 0.16 Not
signicant
56.4
7 Transdiagnostic WL Follow-up 0.39 Signicant 65.2
3 Transdiagnostic Placebo Follow-up 0.53 Not
signicant
70.2
7 Transdiagnostic TAU Follow-up 0.48 Signicant 68.4
23 Transdiagnostic Active Follow-up 0.17 Signicant 56.7
17 Transdiagnostic CBT Follow-up 0.06 Not
signicant
52.4
A-Tjak et al. (2015) 9 Transdiagnostic WL Timepoints combined 0.82 Signicant 79.4
5 Transdiagnostic Placebo Timepoints combined 0.51 Signicant 69.5
12 Transdiagnostic TAU Timepoints combined 0.64 Signicant 73.9
9 Transdiagnostic CBT Timepoints combined 0.32 Not
signicant
62.6
30 Other Outcomes: Secondary Outcome CBT Timepoints combined 0.30 Signicant 61.8
19 Other Outcomes: Quality of Life CBT Timepoints combined 0.37 Signicant 64.4
23 Other Outcomes: Process Measures Combined Timepoints combined 0.56 Signicant 71.2
8 Transdiagnostic TAU Timepoints combined 0.37 Signicant 64.4
8 Substance Abuse TAU Timepoints combined 0.40 Signicant 65.5
15 Other Conditions: Somatic
Complaints
Combined Timepoints combined 0.58 Signicant 71.9
(Hacker et al. (2016)) 15 Depression Active Post 0.26 not
signicant
60.3
10 Anxiety Active Post 0.04 not
signicant
48.4
28 Anxiety WL Post 0.45 Signicant 67.4
39 Depression WL Post 0.54 Signicant 70.5
Lee et al. (2015) 10 Substance Abuse Active Follow-up 0.43 Signicant 66.6
3 Substance Abuse CBT Follow-up 0.34 Not
signicant
63.3
5 Substance Abuse: Smoking Active Post 0.42 Signicant 66.3
5 Substance Abuse: Drugs Active Post 0.45 Signicant 67.4
Brown et al. (2016) 10 Depression Combined Post 0.24 Signicant 59.5
7 Anxiety Combined Post 0.18 Signicant 57.1
8 Other Outcomes: Quality of Life Combined Post 0.06 Not
signicant
52.4
Spijkerman et al.
(2016)
5 Depression Combined Post 0.40 Signicant 65.5
5 Anxiety Combined Post 0.37 Signicant 64.4
2 Other Conditions: Stress Combined Post 0.34 not
signicant
63.3
4 Other Outcomes: Well-Being Combined Post 0.17 not
signicant
56.7
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A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
189
Table 3 (continued )
Meta-analysis Number of
Comparisons
Outcome cluster Comparison
group
Timepoint of comparison ES Signicance U
3
(%)
2 Other Outcomes: Mindfulness Combined Post 0.39 Signicant 65.2
Tonarelli et al. (2016) 2 Other Conditions: Psychosis (Positive
Symptoms)
TAU Post 0.15 Not
signicant
44.0
2 Other Conditions: Psychosis
(Negative Symptoms)
TAU Post 0.64 Signicant 73.9
3 Other Conditions: Schizophrenia TAU Post RR =
1.03
Not
signicant
3 Other Conditions: Schizo-affective TAU Post RR =
0.73
Not
signicant
2 Other Outcomes: Rehospitalization TAU Post RR =
0.54
Signicant
Veehof et al. (2016) 2 Pain CBT Post 0.02 Not
signicant
49.2
2 Depression CBT Post 0.25 Not
signicant
40.1
0.1
3 Pain Active Post 0.94 Not
signicant
82.6
3 Depression Active Post 0.83 Not
signicant
79.7
2 Other Outcomes: Disability Active Post 2.52 Not
signicant
99.4
2 Other Outcomes: Quality of Life Active Post 1.55 Not
signicant
93.9
French et al. (2017) 9 Depression Combined Post 0.28 Signicant 61.0
8 Depression WL Post 0.40 Signicant 65.5
8 Anxiety Combined Post 0.30 Signicant 61.8
8 Anxiety WL Post 0.35 Signicant 63.7
12 Other Outcomes: Psychological
Flexibility
Combined Post 0.32 Signicant 62.6
8 Other Outcomes: Psychological
Flexibility
WL Post 0.52 Signicant 69.8
Hughes et al. (2017) 3 Pain: Acceptance Combined Post 0.52 Signicant 69.8
6 Other Outcomes: Quality of Life Combined Post 0.05 Not
signicant
52.0
3 Other Outcomes: Quality of Life Combined Follow-up 0.26 Not
signicant
60.3
5 Other Outcomes: Functioning Combined Post 0.45 Signicant 67.4
4 Other Outcomes: Functioning Combined Follow-up 0.41 Signicant 65.9
4 Anxiety Combined Post 0.57 Signicant 71.6
3 Anxiety Combined Follow-up 0.32 Not
signicant
62.6
5 Depression Combined Post 0.52 Signicant 69.8
4 Depression Combined Follow-up 0.52 Signicant 69.8
2 Other Outcomes: Psychological
Flexibility
Combined Post 0.83 Signicant 79.7
2 Other Outcomes: Psychological
Flexibility
Combined Follow-up 0.64 Signicant 73.9
6 Pain: Intensity Combined Post 0.26 Not
signicant
60.3
4 Pain: Intensity Combined Follow-up 0.29 Not
signicant
61.4
2 Pain Active Post 0.83 Signicant 79.7
2 Pain Active Follow-up 0.42 Signicant 66.3
2 Other Outcomes: Quality of Life Active Post 0.39 Signicant 65.2
2 Other Outcomes: Quality of Life Active Follow-up 0.45 Signicant 67.4
2 Other Outcomes: Functioning Active Post 0.67 Signicant 74.9
2 Other Outcomes: Functioning Active Follow-up 0.35 Signicant 63.7
2 Depression Active Post 0.35 Signicant 63.7
Rogers et al. (2017) 3 Other Outcomes: Quality of Life Combined Post 0.66 Not
signicant
74.5
Reeve et al. (2018) 4 Depression Combined Post 0.26 Not
signicant
39.7
3 Depression Combined Follow-up 0.05 Not
signicant
52.0
4 Other Conditions: Stress Combined Post 0.29 Not
Signicant
61.4
3 Other Conditions: Stress Combined Follow-up 0.09 Not
signicant
53.6
3 Other Outcomes: Psychological
Flexibility
Combined Post 0.07 Not
signicant
52.8
2 Other Outcomes: Psychological
Flexibility
Combined Follow-up 0.16 Not
signicant
56.4
Howell and Passmore,
(2019)
5 Other Outcomes: Well-Being Combined Post 0.29 Signicant 61.4
Li et al. (2019) 3 Substance Abuse TAU Post
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A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
190
The mean overall effect size comparing ACT to placebo corresponded to
a medium effect (g =0.54). The U
3
scores range from 69.5% to 72.2%.
Treatment as Usual (TAU). Thirteen effect sizes from six meta-
analyses compared ACT to TAU. Twelve of the 13 comparisons
favored ACT and 8 of the 13 comparisons were reported to be statisti-
cally signicant. The one comparison that favored TAU was a non-
signicant effect for negative symptomatology in psychosis. Effect
sizes were calculated for outcomes of substance abuse, psychosis (pos-
itive and negative symptoms), re-hospitalization, and quality of life.
These outcomes were measured at post and follow up time points. The
thirteen meta-analytic effects comparing ACT to TAU reported effects
sizes ranging from no effect g = − 0.15 (Tonarelli et al., 2016) to medium
g =0.79 ( ¨
Ost, 2014). The mean overall effect size comparing ACT to
TAU corresponded to a small effect (g =0.46). The U
3
scores range from
44.0% to 78.5%.
Active Interventions (other than CBT). Twenty-two effect sizes
from eight meta-analyses compared ACT to active interventions.
Twenty-one of the 22 comparisons favored ACT and 14 of the 22 com-
parisons were reported to be statistically signicant. The one compari-
son that favored the active condition was a non-signicant effect for
anxiety (Hacker et al., 2016). Effect sizes were calculated for outcomes
of anxiety, depression, chronic pain, substance abuse, transdiagnostic
conditions, functioning, disability, and quality of life. These outcomes
were measured at post and follow up time points. The 22 meta-analytic
effects comparing ACT to active interventions other than CBT reported
effects sizes ranging from no effect in anxiety g = − 0.04 (Hacker et al.,
2016) to large in disability g =2.52 (Veehof et al., 2016). The mean
overall effect size comparing ACT to active interventions corresponded
to a medium effect (g =0.57). The U
3
scores range from 48.4% to 99.4%.
Cognitive Behavioral Therapy (CBT). Twelve effect sizes from ve
meta-analyses compared ACT to CBT. Ten of the 12 comparisons favored
ACT and 3 of the 12 comparisons were reported to be statistically sig-
nicant. The two comparisons that favored CBT were non-signicant
effects for depression and chronic pain (Veehof et al., 2016). Effect
sizes were calculated for outcomes of anxiety, depression, chronic pain,
quality of life and secondary outcomes. These outcomes were measured
at post and follow up time points. The 12 meta-analytic effects
comparing ACT to CBT reported effects sizes ranging from no effect in
anxiety g =0.00 (Bluett, Homan, Morrison, Levin, & Twohig, 2014) to
small in transdiagnostic outcomes g =0.40 (Ruiz, 2012). The mean
overall effect size comparing ACT to active interventions corresponded
to a negligible effect (g =0.16). The U
3
scores range from 40.1% to
65.5%.
Combined Control Conditions. Thirty-nine effect sizes from 10
meta-analyses compared ACT to a combination of control conditions (e.
g. placebo, waitlist, TAU). Thirty-eight of the 39 comparisons favored
ACT and 27 of the 39 comparisons were reported to be statistically
signicant. The one comparison that favored the combined control
conditions was a non-signicant effect for depression (Reeve et al.,
2018). Effect sizes were calculated for outcomes of anxiety, depression,
other mental conditions, chronic pain, somatic complaints, stress,
mindfulness, psychological exibility, quality of life, well-being, func-
tioning, and other process measures. These outcomes were measured at
post and follow up time points. The 39 meta-analytic effects comparing
ACT to combined conditions reported effect sizes ranging from no effect
in depression g = − 0.26 (Reeve et al., 2018) to a large effect for psy-
chological exibility g =0.83 (Hughes et al., 2017). The mean overall
effect size comparing ACT to combined control conditions corresponded
to a small effect (g =0.33). The U
3
scores range from 39.7% to 79.7%.
4. Discussion
As evidenced across 20 meta-analyses, 133 studies, and 12,477
participants, ACT is efcacious. The evidence suggests that ACT is ef-
cacious across a broad range of intervention targets (e.g., diagnoses of
mental disorders and health conditions such as chronic pain), with
largely equivalent results across these areas. As expected, effect sizes
were larger when compared to inactive control groups and smaller when
compared to active control groups. Importantly, in this review we
exclusively extracted and reported on controlled effect sizes (i.e.,
between-condition comparisons in RCTs) because these are the most
conservative estimates. U3 scores, a measure of nonoverlap, were re-
ported as well to illustrate the effect sizes. The scores ranged from 40%
comparing ACT to CBT to over 90% comparing ACT to another active
intervention.
The literature of treatment outcome studies has traditionally been
organized around specic diagnoses, and meta-analyses have followed
suit. In the present review we found multiple meta-analyses showing
that ACT is associated with controlled effect sizes ranging from small to
medium (with mean effect sizes in the small range) for target conditions
of depression, anxiety, substance abuse, and chronic pain. Multiple
meta-analyses also found that ACT is efcacious transdiagnostically for
a range of conditions, again with small controlled effect sizes. Single
meta-analyses further found evidence for eating disorders, stress, so-
matic complaints, and physical conditions, with small to medium
controlled effect sizes. The consistent small to medium sized controlled
effects across all target conditions suggests that ACTs effects are largely
uniform. The results of this review are consistent with the trans-
diagnostic theoretical basis of ACT. Nevertheless, in order to more fully
test the transdiagnostic assumptions of ACT, future studies are needed.
One type of study that is needed are meta-analyses that expand the types
of disorders examined in order to continue to examine whether less
common targets or populations prot as much as the targets examined in
meta-analyses to date. Related, studies are needed that explicitly test
multiple types of diagnoses and targets simultaneously (as opposed to in
isolation and then combining at the meta-analytic level) in order to more
thoroughly test the degree to which ACT can successfully be applied
transdiagnostically. This later point rst needs to be examined in
outcome studies before being examined in meta-analyses.
Given that effects observed in all studies and meta-analyses are
dependent on multiple factors and conditions, we further examined the
controlled effect sizes with respect to functional outcomes and not
simply symptom-based outcomes. From the onset, ACT authors have
stipulated that the goal of ACT is not reduction of internal states
(although that may happen) but promoting functioning and well-being.
This is predicated on the fact that mental health and well-being are not
Table 3 (continued )
Meta-analysis Number of
Comparisons
Outcome cluster Comparison
group
Timepoint of comparison ES Signicance U
3
(%)
RR =
1.34
Not
signicant
Linardon et al. (2019) 3 Other Conditions: Eating Disorders WL Post 0.5 Signicant 69.1
Notes: The table presents the outcome clusters as we reported them in the result section. The category other conditionsincludes all psychological disorders other than
anxiety, depression, substance abuse, and pain. The psychological diagnoses are specied behind the respective colon. The category other outcomes includes
different secondary outcomes such as well-being, psychological exibility, and quality of life. The effect sizes are if not other specied given in hedges g. The sig-
nicance of the effect size was determined by the authors of the original meta-analysis by indicating a p-value below .05, or 0.01 or 0.001, or by reporting the
condence interval. CBT (Cognitive Behavior Therapy), TAU (Treatment as Usual), WL (Waitlist), FU (Follow-up).
A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
191
simply the opposite of symptoms (Keyes, 2005). Thus, while they are
partially related, it is possible that an individual can have a high level of
internal symptoms and high level of well-being just as it is possible that
one can be anxiety-free and have low levels of well-being. Furthermore,
ACT theory explicitly states that successful treatment promotes psy-
chological exibility (Hayes et al., 2012; Hayes, Luoma, Bond, Masuda,
& Lillis, 2006). Based on 20 meta-analyses, this review found that
controlled effect sizes for ACT are small to medium on quality of life,
small to large on psychological exibility (though one meta-analysis did
not report superior meta-analytic effects for psychological exibility),
and small to medium on measures of well-being, functioning, and
disability. The somewhat higher controlled effect sizes observed for
these outcomes in comparison to outcomes of symptoms can be inter-
preted as consistent with theory. It should be noted, however, that
although these are controlled effect sizes, the magnitude of the differ-
ence was signicant in 50% of the comparisons. It remains an open
theoretical and empirical question as to the best way to dene, assess,
and capture successful intervention change. We remain mindful of the
fact that these effects are often based on questionnaires and thus are
subject to various biases. That said, this is common across studies and
meta-analyses and so it can be assumed that these effects are held largely
constant.
We also examined the controlled effect sizes with respect to control
conditions, with the assumption that effect sizes vary as a function of the
comparison condition. When examining this contextual factor, we found
small to large effect sizes for ACT compared to non-active control (e.g.,
waitlist), passive interventions (e.g., placebo), or a combination. With a
few exceptions, ACT was either non-signicantly different to or superior
to other active interventions including treatment as usual, and a com-
bination of various active interventions. ACT was generally not statis-
tically different from CBT, although ACT was found to be more
efcacious than CBT in a minority of meta-analyses (e.g., Ruiz, 2012).
These results are consistent with previous studies (A-Tjak et al., 2015).
Although different types of comparison groups are used for different
purposes, we agree with others that testing and isolating processes of
change (e.g., psychological exibility, etc.) are more pressing research
priorities than comparative trials testing two different treatments to
determine if one is more efcacious. Naturally, these types of studies are
not mutually exclusive, but future studies need to focus on common and
unique processes, contexts, and procedures irrespective of the type of
group design or even single-subject experimental designs (Gloster et al.,
2017; Levin, Hildebrandt, Lillis, & Hayes, 2012; Villanueva et al., 2019;
Villatte et al., 2016).
This review is subject to some important limitations. First, as
aforementioned, there was a double dippingissue, where some studies
were used for several comparisons and in more than one meta-analysis.
Thus, some of the effects from individual studies may factor more than
others. This was more likely to occur with older meta-analyses because
newer ones have a wider range of published ACT trials from which to
include studies. It remains unclear whether this double-dippingresults
in an overestimation, underestimation, or has a negligible effect on
meta-analytic evidence. Future meta-analyses are encouraged to care-
fully consider this issue when selecting studies. A second limitation is
that there were differences in terms of quality between the meta-
analyses included, but we were not able to balance these differences.
Some meta-analyses had inconsistencies regarding how many studies
were included in a comparison. In several, it was unclear which studies
were included, and in some the outcome measures were not listed. As
reected in the AMSTAR-2 assessment, several study details were
missing and, in some case, incomplete. It is possible that some of these
details were implemented in the studies, but not reported. Irrespective,
future meta-analyses are strongly encouraged to be explicit about these
methodological issues. Finally, meta-analyses are not without problems.
Although meta-analyses allow summarization of effects, the observed
effect sizes need to be contextualized. In this study we attempted to do
this by examining the heterogeneity of effects across categories of target
conditions, outcome variable, comparison group, and double dipping.
Other factors impacting the heterogeneity of effect sizes are probable
and future research should try to better capture these. Finally, individual
meta-analyses constituted their groups differently (e.g., what patients
make up transdiagnostic or which treatment is used in TAU) such
that observed differences between meta-analyses within these labels
may differ in part due to these contextual factors.
These limitations notwithstanding, the present review found that
ACT is efcacious for a wide range of intervention targets and outcomes.
Further, ACT can be considered as efcacious as traditional CBT and
more efcacious than other active comparisons. Future studies are
strongly recommended to examine change processes including different
trajectories of change and include (additional) outcomes of functioning
and well-being.
Declaration of competing interest
None.
This research was supported by the Swiss National Science Founda-
tion (SNF Grant # PP00P1_163716/1 & PP00P1_190082). The views
expressed in this paper are those of the authors and not necessarily those
of the funder. The funding body in no way inuenced the authors in
writing the manuscript. The authors declare that they have no
competing interests.
References
A-Tjak, J. G. L., Davis, M. L., Morina, N., Powers, M. B., Smits, J. A. J., et al. (2015).
A meta-analysis of the efcacy of acceptance and commitment therapy for clinically
relevant mental and physical health problems. Psychotherapy and Psychosomatics, 84
(1), 3036. https://doi.org/10.1159/000365764
Association for Contextual Behavioral Science. (2020). ACT randomized controlled trials
since 1986. Retrieved from https://contextualscience.org/ACT_Randomized_Cont
rolled_Trials.
Avdagic, E., Morrissey, S. A., & Boschen, M. J. (2014). A randomised controlled trial of
acceptance and commitment therapy and cognitive-behaviour therapy for
generalised anxiety disorder. Behaviour Change, 31(2), 110130. https://doi.org/
10.1017/bec.2014.5
Bluett, E. J., Homan, K. J., Morrison, K. L., Levin, M. E., & Twohig, M. P. (2014).
Acceptance and commitment therapy for anxiety and OCD spectrum disorders: An
empirical review. Journal of Anxiety Disorders, 28(6), 612624. https://doi.org/
10.1016/j.janxdis.2014.06.008
Brown, M., Glendenning, A., Hoon, A. E., & John, A. (2016). Effectiveness of web-
delivered acceptance and commitment therapy in relation to mental health and well-
being: A systematic review and meta-analysis. Journal of Medical Internet Research, 18
(8), 114. https://doi.org/10.2196/jmir.6200
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York,
NY, US: Lawrence Erlenbaum Associates.
Craske, M. G., Niles, A. N., Burklund, L. J., Wolitzky-Taylor, K. B., Vilardaga, J. C. P.,
Arch, J. J., et al. (2014). Randomized controlled trial of cognitive behavioral therapy
and acceptance and commitment therapy for social phobia: Outcomes and
moderators. Journal of Consulting and Clinical Psychology, 82(6), 10341048. https://
doi.org/10.1037/a0037212
Ellis, P. D. (2010). The essential guide to effect sizes. Statistical power, meta-analysis, and the
interpretation of research results. Cambridge: Cambridge University Press.
French, K., Golijani-Moghaddam, N., & Schr¨
oder, T. (2017). What is the evidence for the
efcacy of self-help acceptance and commitment therapy? A systematic review and
meta-analysis. Journal of Contextual Behavioral Science, 6(4), 360374. https://doi.
org/10.1016/j.jcbs.2017.08.002
Gloster, A. T., Klotsche, J., Ciarrochi, J., Eifert, G., Sonntag, R., Wittchen, H. U., et al.
(2017). Increasing valued behaviors precedes reduction in suffering: Findings from a
randomized controlled trial using ACT. Behaviour Research and Therapy, 91, 6471.
https://doi.org/10.1016/j.brat.2017.01.013
Gr´
egoire, S., Lachance, L., Bouffard, T., & Dionne, F. (2018). The use of acceptance and
commitment therapy to promote mental health and school engagement in university
students: A multisite randomized controlled trial. Behavior Therapy, 49(3), 360372.
https://doi.org/10.1016/j.beth.2017.10.003
Hacker, T., Stone, P., & Macbeth, A. (2016). Acceptance and commitment therapy - do
we know enough? Cumulative and sequential meta-analyses of randomized
controlled trials. Journal of Affective Disorders, 190, 551565. https://doi.org/
10.1016/j.jad.2015.10.053
Hayes, S. C. (2019). State of the ACT evidence | association for contextual behavioral
science. Retrieved http://contextualscience.org/state_of_the_act_evidence. (Accessed
29 January 2020).
Hayes, S. C., Luoma, J. B., Bond, F. W., Masuda, A., & Lillis, J. (2006). Acceptance and
commitment therapy: Model, processes and outcomes. Behaviour Research and
Therapy, 44(1), 125. https://doi.org/10.1016/j.brat.2005.06.006
A.T. Gloster et al.
Journal of Contextual Behavioral Science 18 (2020) 181–192
192
Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2012). Acceptance and commitment
therapy. In The process and practice of mindful change (2nd ed.). New York, NY, US:
The Guilford Press. https://doi.org/10.1017/CBO9781107415324.004.
Howell, A. J., & Passmore, H. A. (2019). Acceptance and commitment training (ACT) as a
positive psychological intervention: A systematic review and initial meta-analysis
regarding ACTs role in well-being promotion among university students. Journal of
Happiness Studies, 20(6), 19952010. https://doi.org/10.1007/s10902-018-0027-7
Hughes, L. S., Clark, J., Colclough, J. A., Dale, E., & McMillan, D. (2017). Acceptance and
commitment therapy (ACT) for chronic pain. The Clinical Journal of Pain, 33(6),
552568. https://doi.org/10.1097/AJP.0000000000000425
Ii, T., Sato, H., Watanabe, N., Kondo, M., Masuda, A., Hayes, S. C., et al. (2019).
Psychological exibility-based interventions versus rst-line psychosocial
interventions for substance use disorders: Systematic review and meta-analyses of
randomized controlled trials. Journal of Contextual Behavioral Science, 13(July),
109120. https://doi.org/10.1016/j.jcbs.2019.07.003
Keyes, C. L. M. (2005). Mental illness and/or mental health? Investigating axioms of the
complete state model of health. Journal of Consulting and Clinical Psychology, 73(3),
539548. https://doi.org/10.1037/0022-006X.73.3.539
Lanza, P. V., García, P. F., Lamelas, F. R., & Gonz´
alez-Men´
endez, A. (2014). Acceptance
and commitment therapy versus cognitive behavioral therapy in the treatment of
substance use disorder with incarcerated women. Journal of Clinical Psychology, 70
(7), 644657. https://doi.org/10.1002/jclp.22060
Lee, E. B., An, W., Levin, M. E., & Twohig, M. P. (2015). An initial meta-analysis of
Acceptance and Commitment Therapy for treating substance use disorders. Drug and
Alcohol Dependence, 155, 17. https://doi.org/10.1016/j.drugalcdep.2015.08.004
Levin, M. E., Hildebrandt, M. J., Lillis, J., & Hayes, S. C. (2012). The impact of treatment
components suggested by the psychological exibility model: A meta-analysis of
laboratory-based component studies. Behavior Therapy, 43(4), 741756. https://doi.
org/10.1016/j.beth.2012.05.003
Linardon, J., Gleeson, J., Yap, K., Murphy, K., & Brennan, L. (2019). Meta-analysis of the
effects of third-wave behavioural interventions on disordered eating and body image
concerns: Implications for eating disorder prevention. Cognitive Behaviour Therapy,
48(1), 1538. https://doi.org/10.1080/16506073.2018.1517389
Lüdecke, D. (2018). Effect size computation for meta analysis. Retrieved from https://cran.
r-project.org/package=esc.
Lundgren, T., Dahl, J., Melin, L., & Kies, B. (2006). Evaluation of acceptance and
commitment therapy for drug refractory epilepsy: A randomized controlled trial in
South Africa - a pilot study. Epilepsia, 47(12), 21732179. https://doi.org/10.1111/
j.1528-1167.2006.00892.x
¨
Ost, L. G. (2008). Efcacy of the third wave of behavioral therapies: A systematic review
and meta-analysis. Behaviour Research and Therapy, 46(3), 296321. https://doi.org/
10.1016/j.brat.2007.12.005
¨
Ost, L. G. (2014). The efcacy of Acceptance and Commitment Therapy: An updated
systematic review and meta-analysis. Behaviour Research and Therapy, 61, 105121.
https://doi.org/10.1016/j.brat.2014.07.018
Plumb Vilardaga, J. C. (2013). Acceptance and commitment therapy for longstanding
chronic pain in a community-based outpatient group setting. Dissertation Abstracts
International: Section B: The Sciences and Engineering, 74 (5-B(E)), No-Specied.
Retrieved from http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_
val_fmt=info:o/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:
3550275%5Cnhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=ps
yc10&NEWS=N&AN=2013-99220-469.
Powers, M. B., Zum V¨
orde Sive V¨
ording, M. B., & Emmelkamp, P. M. G. (2009).
Acceptance and commitment therapy: A meta-analytic review. Psychotherapy and
Psychosomatics, 78(2), 7380. https://doi.org/10.1159/000190790
Reeve, A., Tickle, A., & Moghaddam, N. (2018). Are acceptance and commitment
therapy-based interventions effective for reducing burnout in direct-care staff? A
systematic review and meta-analysis. Mental Health Review Journal, 23(3), 131155.
https://doi.org/10.1108/MHRJ-11-2017-0052
Rogers, J. M., Ferrari, M., Mosely, K., Lang, C. P., & Brennan, L. (2017). Mindfulness-
based interventions for adults who are overweight or obese: A meta-analysis of
physical and psychological health outcomes. Obesity Reviews, 18(1), 5167. https://
doi.org/10.1111/obr.12461
Ruiz, F. J. (2012). Acceptance and commitment therapy versus traditional cognitive
behavioral therapy: A systematic review and meta-analysis of current empirical
evidence. International Journal of Psychology and Psychological Therapy, 12(3),
333357.
Shawyer, F., Farhall, J., Mackinnon, A., Trauer, T., Sims, E., Ratcliff, K., et al. (2012).
A randomised controlled trial of acceptance-based cognitive behavioural therapy for
command hallucinations in psychotic disorders. Behaviour Research and Therapy, 50
(2), 110121. https://doi.org/10.1016/j.brat.2011.11.007
Shea, B. J., Reeves, B. C., Wells, G., Thuku, M., Hamel, C., Moran, J., et al. (2017).
Amstar 2: A critical appraisal tool for systematic reviews that include randomised or
non-randomised studies of healthcare interventions, or both. BMJ, 358, 19. https://
doi.org/10.1136/bmj.j4008
Spijkerman, M. P. J., Pots, W. T. M., & Bohlmeijer, E. T. (2016). Effectiveness of online
mindfulness-based interventions in improving mental health: A review and meta-
analysis of randomised controlled trials. Clinical Psychology Review, 45, 102114.
https://doi.org/10.1016/j.cpr.2016.03.009
Tonarelli, S. B., Pasillas, R., Alvarado, L., Dwivedi, A., & Cancellare, A. (2016).
Acceptance and commitment therapy compared to treatment as usual in psychosis: A
systematic review and meta-analysis. Journal of Psychiatry, 19(3), 25. https://doi.
org/10.4172/2378-5756.1000366
Veehof, M. M., Oskam, M. J., Schreurs, K. M. G., & Bohlmeijer, E. T. (2011). Acceptance-
based interventions for the treatment of chronic pain: A systematic review and meta-
analysis. Pain, 152(3), 533542. https://doi.org/10.1016/j.pain.2010.11.002
Veehof, M. M., Trompetter, H. R., Bohlmeijer, E. T., & Schreurs, K. M. G. (2016).
Acceptance- and mindfulness-based interventions for the treatment of chronic pain:
A meta-analytic review. Cognitive Behaviour Therapy, 45(1), 531. https://doi.org/
10.1080/16506073.2015.1098724
Villanueva, J., Meyer, A. H., Rinner, M. T. B., Firsching, V. J., Benoy, C., Brogli, S., et al.
(2019). Choose change: Design and methods of an acceptance and commitment
therapy effectiveness trial for transdiagnostic treatment-resistant patients. BMC
Psychiatry, 19(1), 173. https://doi.org/10.1186/s12888-019-2109-4
Villatte, J. L., Vilardaga, R., Villatte, M., Plumb Vilardaga, J. C., Atkins, D. C., &
Hayes, S. C. (2016). Acceptance and Commitment Therapy modules: Differential
impact on treatment processes and outcomes. Behaviour Research and Therapy, 77,
5261. https://doi.org/10.1016/j.brat.2015.12.001
Wetherell, J. L., Afari, N., Rutledge, T., Sorrell, J. T., Stoddard, J. A., Petkus, A. J., et al.
(2011). A randomized, controlled trial of acceptance and commitment therapy and
cognitive-behavioral therapy for chronic pain. Pain, 152(9), 20982107. https://doi.
org/10.1016/j.pain.2011.05.016
White, R., Gumley, A., McTaggart, J., Rattrie, L., McConville, D., Cleare, S., et al. (2011).
A feasibility study of Acceptance and Commitment Therapy for emotional
dysfunction following psychosis. Behaviour Research and Therapy, 49(12), 901907.
https://doi.org/10.1016/j.brat.2011.09.003
Zettle, R. D., & Hayes, S. C. (1986). Dysfunctional control by client verbal behavior: The
context of reason-giving. The Analysis of Verbal Behavior, 4(1), 3038. https://doi.
org/10.1007/bf03392813
A.T. Gloster et al.
... However, mounting evidence suggests physical therapy informed by ACT can be effective in addressing psychological distress and improving physical function associated with chronic pain. 13,14,15 ACT is a cognitive behavioral therapy that has shown effectiveness for both physical 16 and mental health conditions. 17 ACT uses acceptance, mindfulness, commitment, and behavior change strategies to increase psychological flexibility. ...
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Purpose: Purpose: Mounting evidence supports the use of cognitive and behavioral techniques as part of physical therapist practice. These methods are used within a physical therapist's multimodal treatment approach for the management of pain and to facilitate health behavior change. There is a multitude of evidence-based cognitive behavioral techniques to choose from including newer approaches based on Acceptance and Commitment Therapy. Yet few studies have examined physical therapists' perceptions to learning and implementing ACT into clinical practice. The purpose of this manuscript is to present a clinical perspective of physical therapists learning about and incorporating Acceptance and Commitment Therapy in clinical practice. Methods: Methods: An 8-week online physical therapist-led ACT for chronic pain training was completed by 65 physical therapists. A post-training evaluation was developed and then scored by 46 participants. The evaluation included 15-questions with regard to the self-reported perceptions of learning foundational ACT skills necessary to implement into physical therapy practice, a deeper understanding of psychological factors involved in musculoskeletal pain, confidence in managing musculoskeletal pain, utility in physical therapist practice, and the recognition of a new or different approach to treating musculoskeletal pain. Results: Results: Participants' self-reported perceptions were highly positive with 73% reporting the training furthered their understanding of psychological factors in chronic musculoskeletal pain and 100% reported learning the foundational ACT skills necessary to implement it into physical therapy practice. In addition, 7 sub-themes regarding the ACT training emerged from a qualitative content analysis and included the following: 1) The training filled a knowledge gap in understanding of how to assess and treat psychological factors related to pain, 2) A mixture of prerecorded video training, reading, experiential exercises, and self-reflection via the ACTPTE were critical to reinforce learning, 3) Coaching and supervision calls were a useful part of the training and helped to translate course knowledge and implement into clinical practice, 4) Having an opportunity to practice in a group setting with like-minded peers was a critical component of confidence building, 5) Ongoing communication, networking, and mentorship via the online forum and coaching calls allowed participants to complete the course material on-time, stay connected, and share stories and experiences about implementing the material in practice, 6) The ACT stance of not changing pain or related psychological content (example: not changing thoughts, pain related beliefs, reconceptualizing pain) may run counter to other psychologically-informed approaches found in physical therapy practice and took some time for practitioners to process and integrate, 7) Some practitioners expressed that ACT helped them cope with work-related stress and burnout and to drop the struggle of fixing or curing every patient with pain. Conclusions: Conclusions: ACT delivered via an online training was acceptable to physical therapists and supervision calls were necessary for confidence building and implementation into practice. The ACT model was perceived as adaptable to the practice of physical therapy as well as the complex clinical and psychosocial presentation of many chronic pain conditions. Future investigations should explore brief training interventions, treatment fidelity, long-term outcomes, the development and validation of a scale to measure knowledge, concepts and skills conceptualizing psychological flexibility within physical therapist practice., PT, DPT is the founder of the Integrative Pain Science Institute, a cutting-edge health company reinventing pain care through evidence-based treatment, research, and professional development. His research and career achievements include scalable practice models centered on health behavior change, integrative medicine, and methods that empower physical therapists to serve at the top of their scope of practice as primary providers of healthcare. He is a speaker, author, hosts a podcast, adjunct professor, and guest lecturer in many DPT programs. ABSTRACT Purpose: Mounting evidence supports the use of cognitive and behavioral techniques as part of physical therapist practice. These methods are used within a physical therapist's multimodal treatment approach for the management of pain and to facilitate health behavior change. There is a multitude of evidence-based cognitive behavioral techniques to choose from including newer approaches based on Acceptance and Commitment Therapy. Yet few studies have examined physical therapists' perceptions to learning and implementing ACT into clinical practice. The purpose of this manuscript is to present a clinical perspective of physical therapists learning about and incorporating Acceptance and Commitment Therapy in clinical practice. Methods: An 8-week online physical therapist-led ACT for chronic pain training was completed by 65 physical therapists. A post-training evaluation was developed and then scored by 46 participants. The evaluation included 15-questions with regard to the self-reported perceptions of learning foundational ACT skills necessary to implement into physical therapy practice, a deeper understanding of psychological factors involved in musculoskeletal pain, confidence in managing musculoskeletal pain, utility in physical therapist practice, and the recognition of a new or different approach to treating musculoskeletal pain. Results: Participants' self-reported perceptions were highly positive with 73% reporting the training furthered their understanding of psychological factors in chronic musculoskeletal pain and 100% reported learning the foundational ACT skills necessary to implement it into physical therapy practice. In addition, 7 sub-themes regarding the ACT training emerged from a qualitative content analysis and included the following: 1) The training filled a knowledge gap in understanding of how to assess and treat psychological factors related to pain, 2) A mixture of prerecorded video training, reading, experiential exercises, and self-reflection via the ACTPTE were critical to reinforce learning, 3) Coaching and supervision calls were a useful part of the training and helped to translate course knowledge and implement into clinical practice, 4) Having an opportunity to practice in a group setting with like-minded peers was a critical component of confidence building, 5) Ongoing communication, networking, and mentorship via the online forum and coaching calls allowed participants to complete the course material on-time, stay connected, and share stories and experiences about implementing the material in practice, 6) The ACT stance of not changing pain or related psychological content (example: not changing thoughts, pain related beliefs, reconceptualizing pain) may run counter to other psychologically-informed approaches found in physical therapy practice and took some time for practitioners to process and integrate, 7) Some practitioners expressed that ACT helped them cope with work-related stress and burnout and to drop the struggle of fixing or curing every patient with pain. Conclusions: ACT delivered via an online training was acceptable to physical therapists and supervision calls were necessary for confidence building and implementation into practice. The ACT model was perceived as adaptable to the practice of physical therapy as well as the complex clinical and psychosocial presentation of many chronic pain conditions. Future investigations should explore brief training interventions, treatment fidelity, long-term outcomes, the development and validation of a scale to measure knowledge, concepts and skills conceptualizing psychological flexibility within physical therapist practice.
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Background There is a growing body of research suggesting that psychological flexibility (PF) is an important psychological construct related to psychological health and human performance. The Psychological Flexibility in Sport Scale (PFSS) is the first general scale to assess sport-related PF. So far, the PFSS has not yet been validated in other contexts than Sweden. Therefore, the current study sought to investigate a Persian version of the PFSS (P-PFSS) and extend the investigation of the psychometric properties of the PFSS in Iranian athletes. Methods A total of 302 athletes from both team and individual sports (average age of 20.7 years, SD ± 7.5, 62.3% were female) were involved in the current study. Statistical analysis was performed on the data to test validity and reliability. The validity of the P-PFSS was tested through face and content validity, construct validity, criterion validity, and known-groups validity. The reliability of P-PFSS was verified through internal consistency and temporal stability of the scale. Results Results revealed that validity of the P-PFSS was satisfactory. The instrument was determined to have strong face and content validity. With modifications, the confirmatory factor analysis confirmed the scale’s unidimensionality. The convergent validity of the P-PFSS was found to be acceptable (average variance extracted = 0.66) and satisfactory results were also found in the correlation matrix for the assessment of construct validity. The P-PFSS showed good criterion validity related to generic psychological flexibility and athletic-related variables. Also, the P-PFSS was able to differentiate PF between known groups. The P-PFSS was found to be reliable, with good internal consistency (Cronbach’s alpha = 0.92; composite reliability = 0.92) and temporal stability on retest (intraclass correlation coefficient = 0.95). Conclusions Overall, the Persian version of the PFSS showed good psychometric qualities in Iranian athletes. The current study provides additional support for the PFSS and extends the context-specific utility for practitioners and researchers in assessing sport-related PF.
... The components for PF include Acceptance, Contact with the Present Moment, Self-as-Context, Defusion, Committed Action, and Values, whereas the components of PI are Experiential Avoidance, Lack of Contact with the Present Moment, Self-as-Content, Fusion, Inaction and Lack of Contact with Values (see Hayes et al., 2006 for more details). An enormous amount of research has shown that ACT is effective in treating a range of diagnoses (Fang & Ding, 2020;Gloster et al., 2020) and that PF/PI is a core mechanism of change (Hayes et al., 2006;Vasiliou et al., 2022). ...
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Third-wave behavioural interventions are increasingly popular for treating and preventing mental health conditions. Recently, researchers have begun testing whether these interventions can effectively targeting eating disorder risk factors (disordered eating, body image concerns). This meta-analysis examined whether third-wave behavioural interventions (acceptance and commitment therapy; dialectical behaviour therapy; mindfulness-based interventions; compassion-focused therapy) show potential for being effective eating disorder prevention programs, by testing their effects on eating disorder risk factors in samples without an eating disorder. Twenty-four studies (13 randomized trials) were included. Most studies delivered selective prevention programs (i.e. participants who reported elevated risk factor). Third-wave interventions led to significant pre–post (g = 0.59; 95% CI = 0.43, 0.75) and follow-up (g = 0.83; 95% CI = 0.38, 1.28) improvements in disordered eating, and significant pre–post improvements in body image (g = 0.35; 95% CI = 0.13, 0.56). DBT-based interventions were associated with the largest effects. Third-wave interventions were also significantly more efficacious than wait-lists (g = 0.39; 95% CI = 0.09, 0.69) in reducing disordered eating, but did not differ to other interventions (g = 0.25; 95% CI = –0.06, 0.57). Preliminary evidence suggests that third-wave interventions may have a beneficial effect in ameliorating eating disorder risk.
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Purpose Work-related stress amongst staff working in direct care roles in mental health and intellectual disability settings is associated with a range of problematic outcomes. There has been a proliferation of research into the use of acceptance and commitment therapy (ACT)-based interventions in this staff population. The purpose of this paper is to review the extant literature. Design/methodology/approach A systematic search of the literature was conducted, and seven studies identified which met the criteria for inclusion in the review, of which four were eligible for meta-analysis. Findings Results of the meta-analysis were most convincing for the effectiveness of ACT-interventions to reduce psychological distress within a subgroup of those with higher distress at baseline. There was no statistically significant effect for the amelioration of burnout, nor for an increase in psychological flexibility (a key ACT construct). Research limitations/implications Conceptual issues are considered including the purpose and treatment targets of ACT interventions, such as supporting valued living rather than diminishing stress per se . Methodological issues are discussed around the measurement of psychological flexibility. Originality/value This review makes recommendations for future research and for the implementation of ACT-interventions for work-related stress in these settings.
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The aim of this multisite randomized controlled trial was to determine whether an intervention based on Acceptance and Commitment Therapy (ACT) was efficacious in improving university students' psychological flexibility, mental health, and school engagement. Students were recruited in four Canadian universities and randomly assigned to an intervention ( n = 72) or a wait-list control group ( n = 72). Students in the intervention group took part in four 2.5-hour workshops during a 4-week period and were asked to do exercises at home (e.g., meditation, observation grids). Wait-list students received the intervention soon after the post measurements. MANCOVAs and ANCOVAs revealed that students in the intervention group showed greater psychological flexibility at postintervention than those in the control group. They also reported greater well-being and school engagement, and lower stress, anxiety, and depression symptoms. Taken together, results of this study suggest that an ACT-based intervention offers a valuable way to promote mental health and school engagement in postsecondary settings.
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Acceptance and Commitment Therapy (ACT) is a form of psychotherapy with growing evidence for its transdiagnostic effects. Traditionally face-to-face, ACT is also delivered in self-help formats. As self-help is becoming more prevalent, the demand for empirical evidence of the efficacy of ACT self-help is increasing, and there are concerns that intervention outcomes are being 'over-sold'. A systematic search of the literature was conducted to find all peer-reviewed randomized controlled trials investigating the efficacy of ACT self-help on depression, anxiety, and/or psychological flexibility (PF). Thirteen studies were identified and reviewed, totaling 2580 participants. A quality appraisal of the papers under review indicated bias in methodology and reporting that may limit the interpretability of existing evidence. Meta-analysis showed significant small effect sizes favoring intervention for depression (g=0.34; 95% CIs [0.07, 0.61]; Z=2.49, p=.01), anxiety (g=0.35; 95% CIs [0.09, 0.60]; Z=2.66, p=.008), and PF (g=0.42; 95% CIs [0.14, 0.70]; Z=2.93, p=.003) outcomes. Results indicate that higher levels of clinician guidance improves outcomes but that intervention format (e.g. book/computer) is unlikely to moderate results. Analysis also showed that increases in PF were associated with reductions in depression (rho=-.70, p=.25, n=10) and anxiety (rho=-.90, p<.001, n=10), giving initial support for the theory that changes in PF mediate distress outcomes. Therefore, ACT self-help may be a suitable intervention, particularly when clinician guidance is given. However, due to the small effect sizes, limited number of studies, and considerable heterogeneity of results, any conclusions made are tentative.
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Background: Psychological flexibility theory (PFT) suggests three key processes of change: increases in value-directed behaviors, reduction in struggle with symptoms, and reduction in suffering. We hypothesized that Acceptance and Commitment Therapy (ACT) would change these processes and that increases in valued action and decreases in struggle would precede change in suffering. Method: Data were derived from a randomized clinical trial testing ACT (vs. waitlist) for treatment-resistant patients with primary panic disorder with/without agoraphobia (n = 41). Valued behavior, struggle, and suffering were assessed at each of eight sessions. Results: Valued actions, struggle, and suffering all changed over the course of therapy. Overall changes in struggle and suffering were interdependent whereas changes in valued behavior were largely independent. Levels of valued behaviors influenced subsequent suffering, but the other two variables did not influence subsequent levels of valued action. Discussion: This finding supports a central tenet of PFT that increased (re-)engagement in valued behaviors precedes reductions in suffering. Possible implications for a better understanding of response and non-response to psychotherapy are discussed.