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Frontiers in Psychology | www.frontiersin.org 1 December 2019 | Volume 10 | Article 2621
HYPOTHESIS AND THEORY
published: 12 December 2019
doi: 10.3389/fpsyg.2019.02621
Edited by:
Changiz Mohiyeddini,
Northeastern University,
UnitedStates
Reviewed by:
Giancarlo Dimaggio,
Centro di Terapia Metacognitiva
Interpersonale (CTMI), Italy
Gabriele Caselli,
Sigmund Freud University
Vienna, Austria
*Correspondence:
Adrian Wells
adrian.wells@manchester.ac.uk
Specialty section:
This article was submitted to
Psychology for Clinical Settings,
a section of the journal
Frontiers in Psychology
Received: 21 June 2019
Accepted: 06 November 2019
Published: 12 December 2019
Citation:
Wells A (2019) Breaking the
Cybernetic Code: Understanding
and Treating the Human
Metacognitive Control System to
Enhance Mental Health.
Front. Psychol. 10:2621.
doi: 10.3389/fpsyg.2019.02621
Breaking the Cybernetic Code:
Understanding and Treating the
Human Metacognitive Control
System to Enhance Mental Health
AdrianWells1,2*
1 School of Psychological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester,
United Kingdom, 2 Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom
The self-regulatory executive function (S-REF) model explains the role of strategic
processes and metacognition in psychological disorder and was a major inuence on the
development of metacognitive therapy. The model identies a universal style of perseverative
negative processing termed the cognitive attentional syndrome (CAS), comprised of worry,
rumination, and threat monitoring in the development of disorder. The CAS is linked to
dysfunctional metacognitions that include beliefs and plans for regulating cognition. In
this paper, Iextend the theoretical foundations necessary to support further research on
mechanisms linking metacognition to cognitive regulation and effective treatment. Ipropose
a metacognitive control system (MCS) of the S-REF that can beusefully distinguished
from cognition and is comprised of multiple structures, information, and processes. The
MCS monitors and controls activity of the cognitive system and regulates the behavior of
neural networks whose activities bias the way cognition is experienced. Metacognitive
information involved in the regulation of on-line processing includes metacognitive beliefs,
metacognitive procedural commands, and more transient cybernetic code. Separation
of the cognitive and metacognitive systems and modeling their relationship presents major
implications concerning what should bedone in therapy and how it should bedone. The
paper concludes with an in-depth consideration of methods that strengthen the
psychological basis of psychotherapy and aid in understanding and applying metacognitive
therapy in particular. Finally, limitations of the model and implications for future research
on self-awareness, self-regulation, and metacognition are discussed.
Keywords: metacognitive therapy, metacognition, self-awareness, transdiagnostic mechanisms, cognitive behavior
therapy, neural networks, embodiment, attention
INTRODUCTION
roughout the last 25 years, the Self-Regulatory Executive Function (S-REF) model (Wel ls
and Matthews, 1994, 1996) has stimulated a large volume of research on cognitive control
processes in psychological disorder and is the grounding of an eective psychological treatment:
metacognitive therapy (MCT: Wells, 1995, 2009). In this paper, Iconsider the central principles
of the model in light of recent evidence and expand on the functional components of its
metacognitive control system. e aim is to provide a theoretical framework to stimulate and
Wells Metacognitive Control System
Frontiers in Psychology | www.frontiersin.org 2 December 2019 | Volume 10 | Article 2621
advance future research on varieties of metacognitive information,
processes, and structures in psychological disorder, self-awareness,
and treatment.
HISTORICAL CONTEXT OF THE
SELF-REGULATORY EXECUTIVE
FUNCTION MODEL
Our initial aim in the work leading to the S-REF was to take
a robust scientic approach that was deeply rooted in cognitive
psychology to develop an explanation of the mechanisms behind
psychological disorder. at aim culminated in our book,
Attention and Emotion: A Clinical Perspective; rst published
in 1994 and since re-published (Wells and Matthews, 1994,
2015). Our goal was to generate testable theory-based predictions
that would lead to clinical innovation.
e S-REF model aimed to explain laboratory-based data
on attention bias, individual dierences in stress responses,
and the cause of psychological disorder. is did not turn out
to bea simple task, but it was a controversial one. e prevailing
view at the time was that psychological disorder was largely
an eect of bottom-up (automatic) stimulus-driven biases in
processing resulting from schemas or associative networks.
Wequestioned this view, setting out a model based on alternative
mechanisms, involving maladaptation in top-down volitional
cognitive control, arguing that clinical disorder is associated
with a reduction in dynamic control and adaptability.
e application of cognitive psychology principles in the
eld of psychopathology and treatment was limited when
webegan. Innovative research on attention in anxiety (Mathews
and MacLeod, 1985, 1986; Williams etal., 1988; Mathews etal.,
1990; MacLeod, 1991) demonstrated that patients are
characterized by a bias toward information with negative content.
Our initial goal was to attempt to explain such selective
processing. What might lead the emotional disordered patient
to focus on negative information? Webegan by evaluating the
success of existing theory in accounting for biased attention
and its success in accommodating important attention factors;
capacity limitation and distinctions between voluntary and
involuntary (automatic) processes.
Inuential models of psychological disorders centered on
memory structures (e.g. schemas or associative networks) as
key causes of disorder and the major treatment approaches
focused primarily on the content of these structures and related
cognitions. For example, Beck’s cognitive theory (Beck, 1976;
Beck et al., 1985) of emotional disorders assigned a prominent
role to the content of beliefs and interpretations in disorder,
identifying the negative triad in depression and a preponderance
of thoughts about danger in anxiety (e.g. “I’m going to physically
collapse”). In contrast, we argued that maladaptation occurs
principally due to volitional biases in executive control, in the
selection of self-regulation strategies; the emotionally vulnerable
person selecting those strategies that prolonged rather than
terminated negative processing. Increasingly, we became aware
of limitations of the schema and “automaticity” concepts as an
explanation of these features of processing. In particular, they
failed to account for the individuals inuence over whether or
not to continue with current processing. For instance, the content
of self-knowledge or schemas (e.g. “I’m a failure as a mother”)
does not explain bias in attention or cognitive regulation because
the individual retains choice in whether or not to continue
analyzing their failures. In eect, the role of top-down or executive
processes in the regulation of processing necessitated elaboration.
erefore, our model aimed to explain how voluntary (executive
processes) and involuntary processes interacted with stored
knowledge, especially metacognition in the regulation of processing.
Metacognition refers to the structures, content, and processes
involved in the monitoring, appraisal, and control of cognition.
Sometimes loosely dened as that part of cognition that is
turned onto itself, this simple denition may be misleading,
because it suggests a single structure of cognition responsible
for cognition and metacognition. Seminal work on metacognition
prior to the S-REF model was predominantly in developmental,
educational, and memory psychology with dening contributions
of Flavell (1979), Nelson and Narens (1990), and colleagues.
In order to develop a comprehensive model of cognitive
control and the prioritizing of negative processing, wepredicted
a central contribution of dysfunctional metacognition and
attentional control plans stored in long term memory.
Subsequently, the metacognitive component of the model was
elaborated as the basis for metacognitive therapy (Wells, 1995,
2000, 2009), and the model was extended with greater detail
of features of its architecture and metacognitive components
(especially metacognitive beliefs). However, the central tenets
of the theory and its implications, emphasizing universal
top-down inuences, remain the same.
e S-REF model has inuenced the development of other
treatment approaches. For example, Clark and Wells (1995)
advanced a model and treatment of social phobia that has
proven eective (Clark et al., 2006; Nordahl et al., 2016) and
is a recommended intervention in health guidelines (NCCMH,
2013). Wider inuences of the S-REF on psychotherapy are
apparent as extensions of CBT, for example, “emotional schema”
theory and treatment (Leahy, 2015). While in a separate line
of work, metacognition has been formulated dierently by
Dimaggio et al. (2015) in their therapeutic approach of
interpersonal therapy in personality disorder and by Moritz
and Woodward (2007) in metacognitive training for schizophrenia.
OUTLINE OF THE SELF-REGULATORY
EXECUTIVE FUNCTION MODEL
e S-REF model is based on the principle that most psychological
disorders are the result of a universal style of cognition and
behavior termed the Cognitive Attentional Syndrome (CAS).
e CAS is a state of processing where negative self-relevant
information is prioritized and becomes perseverative (i.e.
extended and repetitive). e most common types of
perseveration include worrying or ruminating (brooding) on
negative and threatening events such as how to deal with
future threats or trying to understand past events and feelings.
In addition to worry and ruminations, the CAS is also comprised
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Frontiers in Psychology | www.frontiersin.org 3 December 2019 | Volume 10 | Article 2621
of attentional strategies of “threat-monitoring” such as checking
for symptoms or thoughts or scanning the environment for
specic signs of danger (e.g. contamination or personal rejection).
Added to these elements are other forms of problematic behavior
such as avoidance, inactivity, thought suppression, or substance
use. ese strategies intensify and extend negative processing.
ey also reduce direct experiences of discontinuation of
processing by the mind itself.
An illustration of the CAS and its eects can be seen in
a depressed patient who when questioned about feelings of
lethargy reported: “I don’t have the strength to cope” and
described how subsequently he responded to this cognition
by analyzing why he lacked energy, compared himself with
other people, repeatedly questioned why he felt depressed,
closely monitored his feelings of fatigue, engaged in self-criticism
in an attempt to increase motivation, and reduced activity
levels in order to conserve strength. is constellation of
responses prolonged negative self-focused processing and
undermined his subjective ability to deal with situations.
In the S-REF model, the CAS is caused by the individual’s
metacognitive knowledge (Wells and Matthews, 1994, 1996),
and such knowledge is formulated as a major target in
metacognitive therapy (Wells, 1995, 2000). A distinction is
made between declarative and procedural metacognitive
knowledge. e declarative can beexpressed verbally as beliefs
about thinking (e.g. “worrying is harmful”), whilst procedural
knowledge exists as implicit instructional information (i.e.
commands or “plans”) that inform the cognitive system how
to operate (e.g. the instructions behind generating worry
or rumination).
e declarative metacognitive beliefs in psychopathology can
be further divided into those that are positive or negative.
e positives concern the usefulness of CAS strategies such
as worry, rumination, and attending to threat (e.g. “Worrying
means I’m always prepared”), while the negatives concern the
uncontrollability and harmfulness of cognition (e.g. “I have
lost control of my thinking” and “Some thoughts can harm
me”). e latter are considered of greater causal signicance
in disorder because beliefs concerning the uncontrollability
and danger of cognition interfere with eective control and
lead to omnipresent threat from an internal process; cognition
itself (Wells, 1995).
It is evident in the S-REF analysis that the cognitive and
neural architecture accommodates strategic processes such as
worry, rumination, and threat monitoring that are conceptualized
as serving personal self-regulatory goals and are linked to
metacognition. However, many of the constructs in our model
were new and therefore a research program was needed to
develop tools for measuring metacognitive beliefs (Cartwright-
Hatton and Wells, 1997), thought control strategies (Wells and
Davies, 1994), and types of worry (Wells, 1994, 2005a) to
facilitate model testing.
A signicant proportion of work in this domain was enabled
by developing the metacognitions questionnaire (MCQ;
Cartwright-Hatton and Wells, 1997, Wells and Cartwright-
Hatton, 2004), a measure of beliefs about thinking. e MCQ
measures ve domains of metacognitive knowledge each on
a separate subscale: negative beliefs about thoughts concerning
uncontrollability and danger (e.g. “When I start worrying
Icannot stop”); positive beliefs about worrying (e.g. “Worrying
helps me to avoid problems in the future”); cognitive condence
(e.g. “I have a poor memory”); need for mental control (e.g.
It is bad to think certain thoughts”); and cognitive self-
consciousness (e.g. “I constantly examine my thoughts”). ese
domains represent the declarative knowledge or information
that individuals hold about thinking and are considered linked
to the procedural knowledge or the commands of the S-REF
that inuence processing.
SCIENTIFIC STATUS OF THE
SELF-REGULATORY EXECUTIVE
FUNCTION MODEL
e S-REF model emphasized common processes in psychological
disorder, predicting universal, or transdiagnostic abnormalities
in attention (e.g. threat monitoring), metacognition and
perseveration. Consistent with this prediction, attentional bias
has been demonstrated across dierent traits and disorders
(Bar-Haim et al., 2007; Cisler and Koster, 2010; Staugaard,
2010; Techmann et al., 2010; Epp et al., 2012), and universal
dysfunction in metacognitive beliefs has been shown across
pathologies (e.g. Sun et al., 2017). In the next section, data
on metacognitions and the CAS will be considered. Several
extensive reviews of biased attention can be found in the
literature elsewhere (e.g. Bar-Haim et al., 2007; Cisler and
Koster, 2010; Epp et al., 2012).
Metacognitive Beliefs
It is now reliably established that metacognitions are elevated
across psychological disorders and are associated meaningfully
with perseverative styles of negative thinking (e.g. worry,
rumination) and emotional vulnerability as our model predicted
(Cartwright-Hatton and Wells, 1997; Wells and Cartwright-
Hatton, 2004; Spada et al., 2008; Nordahl et al., 2019). In a
meta-analysis of 45 studies including 3,772 patients and 3,376
healthy individuals, Sun etal. (2017) showed elevated dysfunctional
metacognitions across patients, with large and robust eects
for beliefs concerning the uncontrollability and danger of worry
and beliefs about the need to control thoughts. Of particular
note, researchers have demonstrated that the metacognitions
of the S-REF model appear to be stronger and more reliable
predictors of psychological vulnerability and symptoms of disorder
than the content of cognition (Gwilliam et al., 2004; Myers
and Wells, 2005; Spada et al., 2007; Myers etal., 2009; Bennett
and Wells, 2010; Bailey and Wells, 2016; Nordahl and Wells,
2017). Furthermore, change in metacognitions during treatment
appears to predict positive outcome better than change in
cognition (Solem et al., 2009; Nordahl et al., 2017), while
pre-treatment metacognition may also impact on outcomes (e.g.
Spada etal., 2009). Development of more specic metacognitive
belief measures for depressive rumination, alcohol use, and
health anxiety add further evidence of positive relationships
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between metacognitive knowledge, problematic aect, and
behaviors (Papageorgiou and Wells, 2003, 2009; Spada and Wells,
2008; Bailey and Wells, 2015a). In addition, prospective studies
support the role of elevated metacognition as a precedent to
elevated emotion disorder symptoms (Myers etal., 2009; Yilmaz
et al., 2011; Capobianco et al., 2019) and as a moderator of
the eects of cognition on anxiety (Bailey and Wells, 2015b).
Experimental studies have sought to manipulate metacognitive
beliefs directly to test their causal impact on symptoms. Rassin
et al. (1999) tested the eect on obsessional thoughts in a
non-clinical sample. Participants were led to believe that an
EEG apparatus to which they were connected would detect
the occurrence of the thought: “apple” and on doing so would
deliver an electric shock to another participant they had just
met. e participants were informed that they could interrupt
the electric shock by pressing a button within 2 s aer the
word “apple” had surfaced in their consciousness. In a comparison
condition, participants were told that the EEG could detect
the thought “apple,” but no information about shocks was given.
us, the experimental condition can beinterpreted as inducing
metacognitive beliefs about the power of the thought “apple”
to cause an electric shock unless the participant acts to prevent
it. e experimental condition resulted in more intrusive
thoughts, greater discomfort, more internally directed anger,
and greater eort to avoid thinking.
In an extension and modication of this paradigm, Myers
and Wells (2013) selected non-patients who scored high and
low on a measure of obsessional symptoms and randomly
allocated them to a metacognitive belief induction or control
condition. All participants were connected to a fake EEG
apparatus and asked to watch a video about drinking water.
Following the video, participants in the experimental group
were led to believe that having thoughts about drinking would
be detected by the EEG apparatus and if so a burst of white
noise sucient to startle them might be generated through
headphones. e control group were informed that the EEG
apparatus could detect thoughts about drinking, and they may
receive a random burst of white noise sucient to startle them.
erefore, only the experimental group were led to believe
the aversive loud noise could be caused by their thoughts.
Consistent with study hypotheses, participants high in obsessions
in the experimental group reported signicantly more intrusions
about drinking, more time thinking about them and greater
discomfort than high obsession participants in the control group.
Capobianco et al. (2018b) used the fake EEG paradigm to
induce negative metacognitive beliefs about the importance
of thoughts and explore their eects on stress responses.
Participants were led to believe that an EEG device could
detect negative thoughts and in the experimental condition
this might lead to a burst of white noise. In the control
condition, the noise was introduced as possibly occurring at
random (there was no actual noise exposure in any condition).
All subjects underwent the Trier Social Stress Test to induce
stress symptoms that were measured across the study and
during a 10-min recovery period. On physiological measures
(skin conductance), no dierences were observed between
groups. But on self-report outcomes, participants in the
experimental condition reported greater negative aect and
lower positive aect in response to the stressor and maintained
lower positive aect at recovery than control participants.
The Cognitive Attentional Syndrome
Turning to data on the CAS, a substantial body of research
supports negative eects of worry (see Davey and Wells, 2006)
and rumination (see Papageorgiou and Wells, 2004) on stress
responses, emotion recovery, and psychological vulnerability.
Matthews et al. (1999) showed that test-anxiety measured at
a trait level was positively related to maladaptive metacognition
and worry (which together loaded on a general factor) and
to style of coping. Furthermore, the eects of worrying appear
to be inuenced by metacognition in some contexts. In a
study of performance under evaluative stress, the eects of
high worry states on performance and psychophysiological
outcomes were moderated by metacognition (i.e. meta-worry),
perhaps reecting the impact of metacognition on compensatory
eort or resource allocation (Matthews etal., 2019). e impact
of the CAS on symptoms of psychopathology has additional
metacognitive moderators; high perceived attention control
appears to reduce the strength of association between the CAS
and disorder symptoms (Fergus et al., 2012).
Studies of individual dierences in the control of distressing
thoughts provide reliable support for the predicted negative
eects of using CAS-related strategies and the ubiquity of
strategies such as worry across dierent disorders and symptoms.
A large number of studies have used the thought control
questionnaire (TCQ: Wells and Davies, 1994). e TCQ separately
assesses the use of worry and self-punishment, and other
occasionally more adaptive strategies of distraction, social
control, and reappraisal. As predicted, worry, and self-punishment
are positively associated with psychological disorder symptoms
(Amir et al., 1997; Warda and Bryant, 1998; Morrison et al.,
2000; Roussis and Wells, 2006). e results of longitudinal
analyses of traumatic stress symptoms suggest that they may
have a causal role (Holeva et al., 2001; Roussis and Wells,
2008). While these data show that CAS is reliably correlated
with symptoms of psychological disorder, the CAS is also
distinguishable from other constructs such as psychological
exibility that are emphasized in other approaches such as
relational frame theory (Fergus etal., 2013). Symptom correlates
of the CAS observed in stress and emotional disorder generalize
to psychosis conrming the universality of these relationships.
In their systematic review, Sellers et al. (2017) identied 51
eligible studies among which ndings conrmed specic positive
relationships between central elements of the CAS and experiences
of psychosis and psychological distress.
Experimental manipulations of CAS processes demonstrate
eects on emotional outcomes and recovery from stress that
are consistent with the S-REF. e induction of worry or
rumination under laboratory settings maintains cognitive and
emotional symptoms following stress exposure. In early work,
pre-dating the S-REF model, Borkovec etal. (1983) showed
that a brief period of induced worry led to greater intrusive
thoughts during a subsequent non-worry task. Subsequently,
Wells and Papagerogiou (1995) and Butler etal. (1995) studied
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the eects of induced brief worry and other forms of mentation
aer exposure to a stressful lm and showed that worry
increased the frequency of intrusive images most over a
subsequent 3-day period. Reviews by Nolen-Hoeksema (1991,
2000) and Lyubomirsky and Tkach (2004) describe experimental
and correlational studies demonstrating that ruminative
thinking about the implications of depressive symptoms
maintains those symptoms, impairs problem solving, and is
associated with worse emotional outcomes aer stressful life
events. Capobianco etal. (2018a) tested whether specic CAS
responses delayed recovery from stress. Participants were
randomly assigned to CAS conditions or a distraction control
condition and exposed to the Trier social stress test. e
rate of recovery from self-report negative aect and
physiological stress (Galvanic Skin Conductance) was
monitored. Compared to a distraction condition, rumination
appeared to impact on skin conductance indicating a prolonged
recovery on this index, while worry subjects reported more
immediate delayed recovery marked by an initial elevation
in self-reported negative aect scores.
REVISITING THE CONTROL
OF COGNITION
Schneider and Shirin (1977) contrast automatic processing
that is fast and reexively triggered by inputs and runs with
little or no conscious involvement with controlled or “strategic”
processing, which requires varying quantities of attention
resources, is partially accessible to consciousness and malleable.
e cognitive system is congured such that stimuli continually
trigger o circuits of automatic processing, but controlled
processing is called when the system indicates a failure of
performance or a situation involving novelty or personal
importance. It is conceivable that abnormality in automatic
or controlled processing could contribute to dierent degrees
to the CAS such as selective focusing on threat or the
persistence of worrying. For example, exposure to repeated
traumas might sensitize processing assemblies for the initial
detection of threat giving it an automatic nature. However,
it seems this in itself would not explain the failure to disengage
negative processing which is identied in the S-REF model
as central to disorder. In the S-REF model sustained processing
such as worry, rumination and threat monitoring is attributed
to executive or strategic factors with metacognitions playing
a key role.
Although both controlled and automatic processing are
likely to operate in disorder (Matthews and Wells, 2000),
evidence supporting the S-REF emphasis on strategic factors
has grown. For example, Phaf and Kan’s (2007) review concluded:
“the emotional Stroop eect seems to rely more on a slow
disengagement process than on a fast, automatic bias” (p.184).
is conclusion ts neatly with a central hypothesis of the
S-REF that psychological disorder is linked with strategic
factors that are the cause of perseverative or extended negative
processing. It also ts with the impact of eective treatment
strategies derived from the S-REF, such as the attention
training technique(Wells, 1990), which demonstrably enhance
self-reported attention exibility (Nassif and Wells, 2014),
objectively measured attention disengagement (Callinan etal.,
2015), and neurophysiological markers of executive control
(Knowles and Wells, 2018; Rosenbaum et al., 2018).
e S-REF model elucidates an advanced “architecture” of
control that involves two sets of distinctions; one between
automatic and controlled processing and the other between
cognitive and metacognitive systems. e distinction between
cognitive and metacognitive systems is supported not only by
self-report as reviewed above but also by neuro-imaging data.
In particular, a meta-analysis of 193 functional neuroimaging
studies of executive functioning tasks (i.e. exibility, inhibition,
working memory, initiation, planning, vigilance) in 2,832 healthy
individuals demonstrated that these tasks share a super-ordinate
network involving the pre-frontal, dorsal anterior cingulate,
and parietal cortices (Niendam et al., 2012). Additionally,
imaging of neural activity during cognitive tasks such as decision
making suggests a neural system located in the pre-frontal
cortex mainly involved in metacognition and independent of
a cognitive system (Qiu et al., 2018).
It is evident from these parallel developments in metacognitive
and neuropsychological research that a more detailed modeling
of the metacognitive and cognitive architectures supporting
self-regulatory processing is needed to advance the eld. Such
a model must explain the dynamic relationship between
metacognition and cognition and the nature of the structures,
circuits, and information involved in the perseveration or
disengagement of negative processing.
In the remaining sections of this paper, I outline a model
of a metacognitive control system of the S-REF specifying the
nature and inuences of metacognitive processes that contribute
to the CAS and maladaptation. Ithen explore the implications
of the model for metacognitive therapy and for future theory
and research in the area.
THE METACOGNITIVE CONTROL
SYSTEM
e Metacognitive Control System Model (MCS) introduces
novel concepts* alongside those that already feature in the
S-REF. In Tab l e 1 they are dened, and their functional
characteristics are summarized to aid understanding.
A simplied schematic of the metacognitive control system
(MCS) and its relationship with the cognitive system (CS) is
depicted in Figure 1. ree overall sets of components are
dierentiated in the gure: (1) cognitive system (where automatic
and on-line strategic processing are further distinguished), (2)
metacognitive system, and (3) neural networks. It should
benoted that this tri-partite separation simplies the architecture
and overlap and sharing of some structures and processes is
expected. In particular, both cognitive and metacognitive
processing are likely to consist of automatic and strategic
processes but for simplicity this is not shown. e model is
intended to represent features of standard architecture and
processes for cognitive control, but as depicted the cognitive
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system (CS) is populated with the type of on-line processing
(i.e. the CAS) that gives rise to psychological disorder.
e MCS is comprised of a comparator mechanism,
metacognitive information in the form of declarative knowledge
(D), procedural knowledge (P), and cybernetic code. ere
are also temporary memory registers. Dierent types of on-line
processing are directed by the MCS, not just the style of
extended negative processing that constitutes the CAS.
e function of the MCS is to monitor (M) and control
(C) the activities of the cognitive system in pursuit of processing
goals. It achieves this through direct and indirect eects involving
the ow of information via the circuits depicted.
e cognitive system, shown in the le-hand side of
Figure 1, is comprised of low-level automatic processing and
on-line (strategic) processing that includes the limited capacity
“thinking space.” e output illustrated is labeled “psychological
disorder” and is considered the consequence of the cognitive
attentional syndrome (CAS) dominating on-line processing as
depicted. Under dierent on-line processing congurations,
where, for example, inhibition of worry under control of the
MCS is specied, internal psychological events will betransitory
and therefore not constitute “disorder.”
Some features of metacognitive control are attentionally
demanding and require conscious involvement and therefore
draw on limited capacity processing which may compete with
CS on-line processing. e operations of the MCS depend on
temporary and longer-term memory stores, with some specialized
memory structures (i.e. memory registers) among other
dimensions (e.g. those involved in comparator function) likely
to be specic to the MCS.
Centrally, the MCS continuously monitors and tests through
the comparator mechanism the current state of processing in
the CS against an internal model. e model represents a
reference standard for the present and future/expected state
of cognition. Aer a discrepancy or mismatch (error) is
detected, instructions are issued to control mechanisms to
bring CS processing in-line with goals. To accomplish this
control function, it is hypothesized that the MCS has a
capability to translate the current status (e.g. a discrepancy)
into information; a cybernetic code that can beused to inuence
the behavior of cognitive and neural systems, biasing activity
toward, for example, discrepancy reduction. It is therefore
hypothesized that an important function of the MCS is
generating, storing and using cybernetic information in the
control of processing.
Code can inuence processing across dierent neural networks
that are recruited to bias the CS. For example, the code may
be used to send commands to interoceptive networks leading
to a “felt-sense” or “gut-feeling” that is recruited to bias or
maintain a particular processing routine. As a means of
illustration, consider an experience familiar to most people;
the “tip-of the tongue” eect. When an item cannot currently
beretrieved from memory (a discrepancy), this is accompanied
by a strong somatic feeling and repetitive and sustained retrieval
attempts that are oen strategic but can also continue
autonomously long aer the individual has given up trying
to remember. us, in this example, production of interoceptive
responses and changes in arousal linked to receiving a signal
of discrepancy (code), bias retrieval (perhaps a type of state-
dependency eect), maintain implementation of retrieval
instructions and increase motivation for sustained strategic
memory search.
Because the comparator is consistently transitioning to the
next set of processes, the system must protect against the loss
of earlier code when the goal of processing remains unmet.
A solution is for code to be stored temporarily in memory
registers. It is then available to the system for repeating processing
sequences – cybernetic looping – in pursuit of goals. Cybernetic
looping, or repetition of a set of processes, like in the example
TABLE 1 | Denitions and functional characteristics of constructs in the MCS
model.
Construct Denition Function
Cybernetic code* Internal code generated
by the MCS representing
the status of cognition in
relation to a reference
Can beused to regulate
networks, support
repetition of processing
and bias the way
cognition is experienced
Cybernetic looping* Repetition of a
processing operation
Maintains processing in
pursuit of system goals
and discrepancy
resolution
Memory registers* Temporary means of
storing cybernetic code
A temporary buffer
protecting against
cybernetic code loss
since the comparator is
constantly transitioning to
the next sequence of
processing
Meta-representation* Pattern of activation (e.g.
sensory) in the neural net
in response to cybernetic
code
Provides a context for
cognition that can
beprocessed according
to various goals (e.g. to
bemeta-aware, have an
objective stance, or sense
of self)
D-knowledge Declarative knowledge
about cognition usually
represented as
metacognitive beliefs
(e.g., “Bad thoughts will
make me bad”)
Provides a library of data
about thinking stored in
long-term memory for use
in self-regulation
P-knowledge Procedural knowledge or
commands that instruct
processing operations
Provides general purpose
orders or “programs” to
control the MCS, CS and
modulate the networks
Comparator A mechanism of the
MCS that compares the
current status of CS
processing against a
reference (e.g. goal)
Enables cognitive
processing to remain
on-track and errors/
discrepancies to
bedetected
Mental Model Active representation of
current processing that
contains the desired goal
Provides a benchmark for
the comparator
Monitoring Flow of information from
the CS to the MCS
Updates the MCS
concerning the real-time
status of on-line
processing
Control Flow of information from
the MCS to the CS
Biases the activity of
on-line processing
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of sustained memory search in the “tip-of-the tongue” experience
is usually adaptive. Looping increases the probability of goal
attainment (e.g. memory retrieval).
An important question relating to self-regulation concerns
the determinant of number of repetitions of a cognitive
process (i.e. adaptive perseveration) in an attempt to reach
processing goals, especially when goals are unattainable.
Several possible solutions to this issue need to be explored.
It seems most probable that there are in-built system limits
to iterations of processing, which may continue until neuronal
or biological states (e.g. level of arousal) change. Plausibly,
the memory registers holding cybernetic code may
be temporary with decay being the norm. ese proposed
characteristics may bean important feature of psychological
recovery or adaptation that naturally ensues over time.
Nevertheless, this process could be adversely aected by
dysfunctional metacognitive knowledge (e.g. “I must worry
about all negative possibilities” or “I have lost control over
thinking”). Under these inuences choice of self-regulation
strategy is dominated by the CAS (e.g. worry), which
perpetuates processing and contributes to discrepancies (e.g.
a sustained sense of threat).
is and other important implications emerge from the
cybernetic code hypothesis. Under the direction of commands
presented in procedural knowledge, cybernetic code could be
used to control processing at dierent destinations in the
neural network. For example, when specic commands activate
or bias interoceptive processors it becomes viable to “somatize”
or feel the status of cognition. Feasibly, through this function
the “sensing” of discrepancies and perhaps other mental
processes can beimplemented by the procedures of the MCS.
In consequence, this allows for more complex internal
representation and communication of the events occurring
within the CS. A “sensing” of cognition may be a building
block of the embodiment of thinking and a process likely to
be important in the construction of self-awareness, to which
I will return later.
As Ihave already proposed a range of memory structures
are required to make internal cybernetic communication
possible and are depicted as part of the MCS in Figure 1.
There must be temporary storage (i.e. memory registers),
long-term stores of metacognitive declarative (D-knowledge),
and procedural (P-knowledge). While the memory registers
act as a temporary buffer to protect against cybernetic code
loss, the long-term memory stores provide metacognitive
information and the instructions or commands for the
model, the comparator process, and control of other
neural systems.
FIGURE 1 | A model of the metacognitive control system and relationships with cognition. Schematic shows main components not a denitive architecture.
D-Knowledge, declarative knowledge (e.g. beliefs: “Worrying is dangerous”); P-Knowledge, procedural knowledge (i.e. processing commands); C, control;
M, monitoring; D, data.
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Embodiment and Self-Awareness
e theoretical structures and inter-relationships described
above provide an architecture, set of functions, and feedback
systems that could have several useful properties. ey enable
real-time information about cognitive activity to pass via
monitoring into the MCS. In turn, under the commands of
procedural knowledge, cybernetic code about cognition can
be generated and inuence processing in specic networks.
Depending on the networks involved a combination of
interoceptive (arousal), visual, or auditory processing activity
linked to the code can arise. is raises the possibility that
metacognitive commands (procedural knowledge) could specify
that processing activity in particular networks is used as data
(D in Figure 1) to create a context or meta-representation for
the events in on-line processing. A system of such conguration
could be directed by its procedural knowledge to compute in
on-line processing a particular meta-representation consisting
of a subjective stance in relation to cognition as objectiable,
separate from external events and within (i.e. tangible, felt, or
embodied). Such a mechanism might provide a basis for states
of objective meta-awareness (i.e. a “sense of cognition” e.g. a
feeling that an item of knowledge is stored in memory).
Furthermore, if procedural knowledge or system commands
specify that objective meta-awareness (i.e. the “sense-of-
cognition”) is processed symbolically as “I” or “me” within
on-line processing, objective meta-awareness is transformed
into self-awareness. us, self-awareness as conceived may
require as a building block a basic metacognitive system
conguration within which the commands generate a sensorial
response to cybernetic information which is subject to “on-line”
(i.e. conscious) symbolic processing.
A propensity to experience meta-awareness, to objectify
thoughts and memory and label the observer as “self” creates
enablers and barriers to cognitive control. Self as a construction
or context for cognition provides for greater exibility and
development of control because it permits cognition to become
the object of focal attention and the subject of an individual’s
motivations and goals. For example, a person’s explicit goals
can be to improve problem solving, concentration or memory
ability, or to become more optimistic. What is more, it means
that the private content of cognition can beshared and modied
through language or other forms of expression. Ironically, it
also means that private cognition can behijacked and underlying
metacognitions corrupted by, for example religious and social
systems that sanctify or punish the possession of certain thoughts
and beliefs.
TREATMENT IMPLICATIONS
e ideas developed in this paper are the basis of metacognitive
therapy (MCT), which focuses on reducing the CAS and
modifying metacognition so that recovery can occur. Full MCT
treatment was rst developed for generalized anxiety disorder
(Wells, 1995, 1997) and subsequently other disorders (Wells,
2000, 2009). In meta-analyses, MCT demonstrates large treatment
eects and appears potentially more eective or more ecient
than cognitive behavioral approaches (Normann et al., 2014;
Normann and Morina, 2018). In a direct test of transdiagnostic
MCT against disorder-specic CBT across anxiety disorders,
outcomes favoring MCT were reported (Johnson et al., 2017)
and potential mechanisms of change could be distinguished
(Johnson and Hoart, 2018). Several trials have evaluated the
eects of MCT against CBT for generalized anxiety. In each
case MCT was superior (Van der Heiden et al., 2010; Well s
et al., 2010; Nordahl et al., 2018). More naturalistic studies
of less highly selected patients also support positive treatment
eects of the full MCT package (e.g. Hagen et al., 2017;
Papageorgiou etal., 2018; Callesen etal., 2019) and of individual
treatment techniques (e.g. Knowles et al., 2016). e majority
of treatment outcome studies have been conducted in anxiety
and depression, but preliminary feasibility data suggest that
the treatment can be implemented in psychosis (Morrison
et al., 2014; Carter and Wells, 2018), transdiagnostic group
settings (Capobianco etal., 2018c), comorbidity (Hjemdal etal.,
2017), treatment resistant cases (Wells et al., 2012; Winter
etal., 2019), alcohol abuse (Caselli etal., 2018), and traumatized
borderline personality (Nordhal and Wells, 2019).
Advanced Treatment Considerations
What is the impact of the MCS model for clinicians and
researchers aiming to develop a better understanding of the
mechanisms and processes of MCT and its eective practise?
A consequence of separating the cognitive system from the
MCS in conceptualizing information processing is the following:
worry, rumination, appraisals, and the execution of behaviors
are all processes occurring within the cognitive system (CS).
However, control, executive processes, knowledge supporting
control and information on the current status of cognition
are properties of the MCS. In psychological disorder it is chiey
the MCS that is the cause of bias observed in the cognitive
system (CS). Maladaptation in the MCS is the major internal
source of extended negative processing (the CAS) occurring
in the CS. An implication of the distinction is that treatment
should focus on formulating and modifying the content, strategies,
and regulatory inuence of the MCS as the most important
source of disorder. us, treatment does not as a matter of
emphasis focus on changing the properties of the CS such as
the content of thoughts, general beliefs, memories or images
or aim to change reexive (automatic) networks of the CS
through prolonged exposure techniques.
e conceptualization of procedural metacognition located
in the MCS and its separation from cognition (the CS) presents
an important implication concerning how treatment is conducted.
It means that MCS knowledge; not only declarative but also
the procedural commands that direct the comparator and bias
the activities of CS must be extracted from the MCS and
processed (e.g. modied) in the CS on-line before being returned
to the MCS or sent to another location in the network. Crucially,
this means that the appropriate parcel of procedural knowledge
must be extracted; that which is the source of the CAS. Since
the CAS can take a variety of forms the therapist must accurately
identify it on a case by case basis. Furthermore, excessive CAS
activity in the CS must bemoderated early in therapy, so that
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the limited capacity “thinking space” can beliberated and used
for MCS modication.
Metacognitive therapy contains techniques designed for the
above purpose that explicitly induce and “hold” the patient in
a “metacognitive mode” of processing during sessions with the
aim to modify both declarative and procedural meta-knowledge
while governing CS processing load. ese techniques include
among others: meta-level discourse, the attention training
technique, the free-association and tiger tasks, rumination
postponement, metacognitive focused exposure, metacognitive
experiments, and worry-modulation procedures. e therapist
must use direct metacognitive experiences and a discourse that
transforms processing styles in the CS before reassigning the
knowledge supporting them to the MCS. In this manner, the
techniques used increase the range, choices, and exibility with
which the individual controls and can relate to their CS. ese
techniques are described in detail elsewhere (Wells, 2005b, 2009).
e model highlights clear dierences between metacognitive
therapy and other treatment approaches in the intended target
of change. In MCT, the therapist retrieves and modies the
validity of declarative metacognitions and also retrieves and
re-writes the commands (procedures) for regulating processing
with the purpose of modifying those involved in the CAS. In
contrast, other treatments either do not aim to work on
metacognitions or they do so without maintaining a clear
structural and functional distinction between systems. But such
a distinction could befacilitative in the design of more advanced
theory-grounded treatment techniques. For example, if
we consider the treatment of low self-esteem, a cognitive
therapist will aim to identify and challenge negative beliefs
about the self by asking questions such as: “What is the evidence
you are a failure, is there another way to view the situation?”
but the metacognitive therapist would ask: “What’s the point
in analyzing your failures?” and follows with techniques that
allow the individual to directly step-back and abandon the
perseverative thought processes that extend the idea. Of particular
importance, in MCT, the client discovers that processing remains
malleable and subject to control in spite of the dominant
cognition (belief) “I’m a failure,” thus creating an alternative
model of processing rather than an alternative model of the
social self (the latter considered a secondary topographic event).
Good metacognitive therapy, the model suggests, is that which
modies the procedural knowledge base. It should enable the
individual to: (1) directly alter the relationship or “stance” they
have with products of cognition; (2) directly manipulate the
control of cognition (e.g. delay worry and inhibit perseverative
thinking); and (3) separate metacognition (i.e. mechanisms of
control) from the strong inuence of internal (e.g. thoughts
and feelings) and external events (as per Attention Training
Technique protocol). e systematic regulation of attention using
a framework of discovery that shows attention remains exible
irrespective of mental events supports the development of general-
purpose strong metacognitive control procedures of this kind.
An implication of the MCS as described is that it can
(under commands of procedural knowledge) initiate and hold
in the moment dierent meta-representations of internal cognition.
A meta-representation is inuenced by the eect of the current
cybernetic code on other processors that provide input to
on-line processing. is creates exibility and the possibility
of choosing how to relate spatially and sensorially (or emotionally)
to inner thoughts, memories and mental events. In object mode,
thoughts are experienced as direct perceptions and treated as
facts (the individual is in the thought), but in metacognitive
mode, they are experienced as events or stimuli in the mind
and the individual steps outside of them (Wells and Matthews,
1994). e model directs us toward developing techniques that
change the meta-representational state. For example practise
of “ipping” between modes or of co-joint experiencing of
incongruent thoughts (e.g. negative thought plus positive
memory) or of experiencing a negative thought and coupling
it with a positive feeling. In each case the meta-representation
might be changed by shiing “stance” or coupling cybernetic
code with new and incongruous bodily and aective states.
Since a goal of MCT is to reduce over-reliance on thinking,
it is usually better to shi into a metacognitive mode and
disengage further conceptual processing rather than analyze
and interrogate negative thoughts as a means of change. However,
the model suggests that an exception must occur when a
negative metacognitive appraisal or meta-belief is present (e.g.
“Worrying will cause cancer”). Since this is primarily a property
of the MCS (it reects maladaptive metacognitive knowledge),
it should be evaluated and replaced with more adaptive
information because it will continue to impact on cognitive
control and the stance in relation to cognition. To summarize,
in metacognitive therapy challenging of the validity of
metacognitions is supported, but challenging the validity of
cognitions is not.
Metacognitive Focused Exposure
Simply engaging the CS in activities of cognitive-behavior
therapy such as evaluating the validity of thoughts or repeated
exposure to fear stimuli present imprecise and coincidental
ways of modifying the control system. Exposure is considered
to facilitate habituation or “emotional processing,” which is
dened as: “a process whereby emotional disturbances are
absorbed and decline to the extent that other experiences and
behavior can proceed without disruption” (Rachman, 1980,
p.51). is has typically been viewed as a mechanism whereby
information about declining arousal is automatically incorporated
in fear networks (e.g. Foa and Kozak, 1986) such that pre-existing
links between stimulus-response nodes and negative meanings
attached to anxiety are weakened. is conception of emotional
processing relates most closely to automatic processing and
neglects the involvement of upper-level cognitive structures,
including the metacognitive control system. For example, it is
possible to think about an emotional event in an unemotional
way. Furthermore, the network approach does not address
questions concerning the factors that determine the cessation
of emotional processing or how the goals of emotional processing
are represented and monitored?
e MCS model invites the clinician to concentrate treatment
on top-down inuences on extended processing such as the
use of worry, over-analysis of memory or threat-monitoring
that lead to repeated or sustained activation of fear networks.
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e MCS model also implies that emotion networks may
respond to cybernetic code and the impact of code on the
network may be moderated by metacognitive knowledge. For
instance, the ability to think about an emotional event in an
un-emotive way is resolved, because the MCS can change the
nature of the relationship (meta-representation) with thoughts.
In addition, theoretical questions about the cessation and
representation of the goals of emotional processing are dealt
with by hypothesizing that the MCS can monitor and control
emotional networks partly through its comparator and cybernetic
code functions. Emotional processing stops when the goal of
processing is met or when the cybernetic code decays. e
ability to achieve such exit signals is potentially reduced by
the CAS and dysfunctional metacognitions, leading to
psychological maladaption.
ere are implications of the model for developing more
ecient and eective exposure therapy techniques. is can
be achieved by inhibiting the CAS during exposure and by
conguring exposure to explicitly modify maladaptive
metacognitive knowledge; both declarative and procedural. Such
an approach of metacognitively focused exposure has been
previously introduced (Wells, 2000).
In a simple form, the combination of exposure with attention
instructions designed to reduce threat monitoring and increase
access to non-threat related information will be helpful. But
more unexpected applications are indicated. For instance, the
MCS model presents an idea that runs counter to the traditional
approach to exposure treatments that emphasize the need to
eliminate avoidance. If we take as an example the treatment
of obsessive-compulsive disorder, exposure and prevention of
covert and overt rituals (forms of avoidance) such as repeated
washing is an eective and recommended treatment. In contrast
to this approach, in MCT, the patient can be permitted to
use rituals in response to thoughts provided they hold the
thought in mind, because the goal is to change the meta-
representation of the thought in the MCS and not the associative
links at a fear network level through habituation. e aim in
MCT is to change the nature of the person’s relationship with
negative cognitions so that thoughts are experienced as
unimportant and transient events in the mind.
A small number of pilot studies have experimented with
forms of metacognitive focused exposure. Fisher and Wells
(2005) examined the eects of brief exposure when it was
presented as an experiment to explicitly test metacognitive
beliefs in OCD. In this study, patients with OCD were asked
to listen for 5 min to their obsessional thoughts recorded on
a loop-tape under two contrasting conditions. In one condition,
a habituation instruction was used with the goal of staying
with the feelings of anxiety and stopping any rituals. In the
metacognitive condition, the instruction was also to stop any
rituals but with the goal of discovering that the thoughts were
unimportant. While both rationales were seen as equally credible
by participants, the metacognitive condition was associated
with signicantly greater reductions in anxiety, metacognitive
beliefs and urge to neutralize. In another study, Wells and
Papageorgiou (1998) exposed social phobia patients to feared
social situations under a habituation rationale or external
attention focusing rational that counteracted threat monitoring.
e latter condition produced superior eects aer a single
brief exposure.
Resistance to Change
e present model oers a means of understanding and dealing
with resistance to change in psychotherapy. It implies that
metacognition can act against a person “changing their mind.”
e model draws the clinician to the paradoxes in cognitive
control such as holding both positive and negative metacognitive
beliefs concerning sustained processing. In generalized anxiety
disorder (GAD), the client believes that worrying will help
anticipate and avoid threat but in conjunction with this there
is the belief that worrying is uncontrollable and harmful (We lls
and Carter, 2001). In health anxiety, there is a belief that
negative misinterpretation of symptoms will facilitate illness
detection and also that thoughts can cause illness (Bailey and
Wells, 2015a). In depression that analyzing why one feels
depressed will lead to feeling better but might also cause self-
harm (Papageorgiou and Wells, 2001, 2003). Each of these
examples presents potential ambivalence, uncertainty, or vacillation
in abandoning the CAS. A belief in the uncontrollability or
pure “biological basis” of negative cognition contributes to a
sense of hopelessness, reduced eort invested in control or a
reliance on extraneous forms of control. is acts against the
client using their own internal control, which might otherwise
enhance MCS capacity to create change.
We have seen how a proposed normal in-built mechanism;
cybernetic looping, contributes to perseveration of processing.
is could explain persistent but relatively normal aective
and motivational states such as longing, desire, grief, craving,
anger, regret, shame, and remorse among others. In these
instances and in stress and adjustment reactions, we would
expect spontaneous recovery over time. However, when an
individual uses the CAS as a coping strategy it maintains the
sense of threat and disrupts the normal exit conditions for
the cybernetic loop, leading the individual to become “gripped”
by their feelings. Furthermore, worrying and ruminating consume
processing resources that are required for metacognitive control
such as switching between goals for processing, consequently
negative processing is less exible and persists. In each of
these cases, the treatment aim should beto remove the barriers
(i.e. CAS) to exit and eective internal control conditions.
Usually, perseverative processes appear to have an in-built
limited and system determined repetition that we might
conceptualize as a normal psychological recovery period. is
concept is used in treating post-traumatic stress disorder, where
the explicit goal shared with clients in MCT is to remove the
CAS so that in-built reexive adaptation processes run their
natural course (Wells, 2009; Wells and Colbear, 2012; Wells
et al., 2015). An important implication is that restructuring
thoughts about trauma, modifying trauma memory and reliving
methods are not necessary for eective treatment. Treatment
should only be introduced aer recovery processes have been
given an opportunity to run naturally.
Cognition is not supplied with a user manual or a schematic
that allows the owner to understand how it works or how best
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to operate it. However, werely on information and procedures
(knowledge) of how our memory and attention works, welearn
to compensate for tiredness or a noisy environment by increasing
eort or concentration, we learn what a thought is, what a
dream is, that we have a good memory for places, and that
cognition is harmless and not prone to loss of control. Wemight
reasonably assume that metacognitive knowledge about cognitive
control has a special place and powerful inuence on how
we construe our own experiences and how much we allow
our own mental events to impact and shape our lives. e
impact can be profound. For instance, consider how some
approaches to mental illness might contribute to a disabling
and unhelpful knowledge of metacognitive control that solidies
a sense of helplessness and mental brokenness. is is not very
useful to the individual, but the discovery of control and a
belief that recovery is a matter of letting some thoughts go is
likely to be more benecial. More broadly, the MCS model
encourages us to examine the messages carried by existing
approaches to mental health diagnosis and treatment. Treatment
delivery programs should ensure that unhelpful metacognitions
are not created but those that already exist are modied.
The Process of Recovery
Implicit in all that I have described above is a fundamental
idea. e MCS is involved in the perpetuation of negative
psychological experiences, and it is also involved in their
cessation; it plays a role in recovery. Under typical circumstances,
we might consider the cybernetic code functions as a “code
for recovery” because it supports continued processing toward
goal attainment and any repetition of processing is usually
limited. However, when metacognitions specify the CAS and
when they give rise to a sense of uncontrollability and threat
from cognition itself, errors or deviations from reference internal
states persist and the code is constantly refreshed. e process
of recovery in psychological therapies is one in which decay
of the code and exit conditions for cybernetic looping are
made accessible. In MCT, this is achieved through modifying
maladaptive metacognitive knowledge, by enhancing exible
control and by disengaging the coping strategies that depend
on extended processing.
LIMITATIONS AND FUTURE RESEARCH
It must be borne in mind that the model is rudimentary and
a project in development. For example, in the interests of
simplicity I have shown “automatic processing” as a separate
cell in Figure 1. However, a dichotomy between automatic and
controlled processing is simplistic, and it may bebetter to view
processing along a continuum of automaticity across multiple
systems. Some automatic processes in the CS may prime specic
procedural knowledge within the MCS, so the CS has some
limited inuence over the MCS, which is not explored. e
CS is controlled by its own “hard-wiring” and in a more exible
and extended way by the procedural knowledge and codes of
the MCS. e processes of the MCS, such as activities of the
comparator and the priming of procedural knowledge are
unconscious and the processes reexively “run-o” in response
to stimuli.
Unanswered questions surface concerning the reliance of
both metacognition and cognition on shared and domain-
specic structures and processes, among them memory. In
particular, depiction of the memory registers is not intended
to imply that these are structurally equivalent to long-term
memory or working memory. Instead, the model points to
the importance of exploring and separating multiple
components of memory including the hypothesized memory
registers and processes that temporarily represent discrepancies
in processing. e prediction that activity in such structures
and related processes is moderated by cybernetic code oers
a potential means to distinguish them from other memory
processes using paradigms that induce code (i.e. cause
discrepancies such as violations of expectancy and induction
of performance errors).
ere are clear limitations in the current database, including
a paucity of information concerning the antecedents of
dysfunctional metacognitive knowledge, such as the possible
role of stressful early life experiences (e.g. Myers and Wells,
2015). Furthermore, while preliminary evidence suggests that
dierent components of metacognitive knowledge may interact
in explaining distress, this remains to be explored in detail.
For instance, interaction between knowledge about attention
and beliefs about uncontrollability of thoughts appears to provide
additional nuanced eects (at least in children) that may prove
important (e.g. Reinholdt-Dunne et al., 2019).
So far in this account I have intentionally avoided any
detailed consideration of the detrimental eects of metacognition
on performance of cognitive tasks. e detrimental eects of
anxiety on performance are well established (e.g. Eysenck,
1992). Anxious mood appears to be a stronger determinant
of impaired performance than trait-anxiety, with worry predicting
poorer performance better than emotional and physiological
aspects of anxiety (e.g. Morris etal., 1981). Eysenck and Calvo
(1992) proposed that anxiety impairs the eciency of the
central executive which appears much like working memory
as proposed by Baddeley (1986). eir theory assumed that
task-irrelevant processing such as worry does not always have
a negative impact on the eectiveness of performance. Finding
oneself worrying may in fact enhance motivation to overcome
the negative performance eects by using additional processing
resources. is appears to beat odds with the idea of a CAS
that causes problems. However, it remains consistent with the
MCS model because the ability to compensate will depend on
characteristics of the MCS. In particular, metacognitive beliefs
of lack of control should negatively inuence the level of
compensatory resources used. For example, in a study by
Matthews etal. (2019), the eects of high worry on performance
and neurophysiology under social-evaluative stress was dependent
on the level of meta-worry (i.e. negative appraisals of the
uncontrollability and danger of worrying).
It remains to bedetermined how the MCS might relate to
a wider range of executive functions, to concepts such as
working memory (Baddeley, 1986, 1996) and inhibition and
attention shiing functions hypothesized by Eysenck et al.
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(2007) in attention control theory. But the model points to
the importance of examining the inuence of metacognitions
on these dimensions.
While there is strong evidence of dysfunctional metacognitive
knowledge across psychopathologies, most of the evidence is
at the level of self-report. Self-report can be criticized, but
it is a mistake to dismiss it as it provides important clues
to the consciously accessible aspects of information processing
such as goals and choice of strategy. But this area of research
needs to be strengthened by investigating further the eect
of self-report metacognitions on attentional responses at a
performance and neural level. Such eorts should seek to
explore the cybernetic code hypothesis and map the neural
structures, circuits and dynamic eects involved. Usefully, the
MCS model suggests the development of laboratory paradigms
to probe and isolate such eects by using the induction of
discrepancies between actual and desired processing states,
such as violating cognitive expectancies. If a trace of the
cybernetic code in such paradigms can be detected in the
form of activity or temporary change at a cellular or network
level this might be used as proof. It may bepossible to adapt
this, using speed of decay of such activity produced in
discrepancy induction paradigms to measure inherent
psychological resilience. For example, greater resilience might
be associated with faster loss of the cybernetic code from
memory registers.
Finally, the model presents important questions and research
directions concerning childhood development of the MCS;
when and what are the inuences on the development of beliefs
about inner-thought? Is there a sequence of development of
attention control skills and is there an optimal set pattern?
We might hypothesize that it is possible to identify proto-
metacognitive states and stages that track the transition from
early attention xation and limited control through to acquired
attention exibility and the later development of higher-order
knowledge of control necessary in consolidating a MCS.
Exploration of levels of complexity and degree of inter-
connectedness of the CS and MCS presents major trajectories
for future cognitive and neuropsychological research.
CONCLUSION
e S-REF model has inuenced research on cognitive control
in psychological disorder, placed top-down processes and
metacognition in a prominent role and informed the development
of metacognitive and other therapies. But an important challenge
remains: to strengthen the theoretical foundations necessary to
advance the study of metacognition in self-awareness and mental
health. One means is by exploring and describing in detail the
components, architecture and functions of the metacognitive
control system of the S-REF and how it relates to disorder; my
goal in this paper. In particular, the eld can benet from
consideration of the types and eects of metacognitive information
generated and used by the system in pursuit of cognitive regulation.
is has become more justied as evidence from neuropsychological
and S-REF based research supports a neural system separate
from cognition and involved in metacognition as the
S-REF predicted.
Psychological disorder from the position of the S-REF model
is conceptualized as a state of persistence of negative processing
that is dicult to control. In most cases, negative ideas and
feelings are transitory but in psychologically vulnerable
individuals they become extended and “xed” due to a
transdiagnostic style of thinking: Cognitive Attentional Syndrome
(CAS). e CAS is largely a consequence of the impact of
biased metacognitions on cognitive regulation. Persistence of
processing is inuenced by dierent features of the MCS;
repetition of processing is normally a feature of cybernetic
looping when discrepancies or errors are detected. But in
psychological disorder this eect is disrupted by choice of
strategies linked to metacognitive knowledge that interfere with
exit conditions for looping, diminish inhibitory control attempts
(e.g. “I have lost control of my thoughts”) or sanction extended
processing (e.g. “I must analyze all my failures until Ibecome
a success”).
An architecture replete with metacognitive information (i.e.
declarative and procedural knowledge, mental models, cybernetic
code and metacognitive experiences) has emergent properties
that contribute to cognitive control. It is a framework for the
development through meta-representational states of within-ness
(embodiment), self-awareness, and a subjective ownership of
cognition. Such eects normally increase exibility, a sense of
stability, and self-control of thoughts. ey also facilitate the
social communication of thought, but they can as described
present a wider range of potential loci for bias that contributes
to disorder. At the most basic of applied levels, health systems
and clinicians working with service users must begin to consider
the potential negative eects on metacognition of the information
and treatment techniques they provide.
In the future, it may be possible to describe the proposed
psychological structures and processes with greater precision.
But for now the model points to the potential in isolating a
discrete metacognitive control system that is separate from
cognition, studying the impact of its components and content
on psychopathology, self-awareness, and self-regulation. I have
described how strengthening this separation can continue to
provide a basis for theoretically derived treatment techniques
in MCT that target specic causal mechanisms in a particular
way. e MCS model opens up a substantial set of new avenues
for research addressing issues that include: mapping the role of
dierent neural systems in cognitive control; testing the eects
of discrepancies or violations of expectancies (i.e. production
of cybernetic code) on interactions between systems; testing the
co-dependence of metacognitive and cognitive operations on
limited capacity; examining the multiple memory requirements
and processes of metacognition; testing the interactive eects
of metacognitive knowledge and attention control on symptoms;
exploring the relationship between metacognition and self-
awareness; and in a broad context examining untoward eects
of healthcare delivery and social systems on metacognitive
functioning. It provides a framework for a more unied cognitive,
Wells Metacognitive Control System
Frontiers in Psychology | www.frontiersin.org 13 December 2019 | Volume 10 | Article 2621
social and neurobiological theory of awareness, self-regulation
and mental wellbeing.
Advances in psychotherapy require a paradigm shi; stronger
information processing theory that can successfully explain
the control of cognition and the negative subjective changes
in perceived control and sense of self that are central features
of disorder. Psychological wellbeing is not a matter of what
we think. It is an issue of how we regulate the cognitive
processes that prioritize and extend thoughts. It is the stance
taken in relation to the content of the limited capacity “thinking
space.” It is above all, the nature and eect of metacognitive
information generated, held and used by processing systems.
AUTHOR CONTRIBUTIONS
e author conrms being the sole contributor of this work
and has approved it for publication.
REFERENCES
Amir, N., Cashman, L., and Foa, E. B. (1997). Strategies of thought control
in obsessive-compulsive disorder. Behav. Res. er. 35, 775–777. doi: 10.1016/
S0005-7967(97)00030-2
Baddeley, A. D. (1986). Working memory. Oxford: Oxford University Press.
Baddeley, A. D. (1996). Exploring the central executive. Q. J. Exp. Psychol. 49A, 5–28.
Bailey, R., and Wells, A. (2015a). Development and initial validation of a
measure of metacognitive beliefs in health anxiety: the MCQ-HA. Psychiatry
Res. 230, 871–877. doi: 10.1016/j.psychres.2015.11.035
Bailey, R., and Wells, A. (2015b). Metacognitive beliefs moderate the relationship
between catastrophic misinterpretation and health anxiety. J. Anxiety Disord.
34, 8–14. doi: 10.1016/j.janxdis.2015.05.005
Bailey, R., and Wells, A. (2016). e contribution of metacognitive beliefs and
dysfunctional illness beliefs in predicting health anxiety: an evaluation of
the metacognitive versus the cognitive models. Clin. Psychol. 20, 129–137.
doi: 10.1111/cp.12078
Bar-Haim, Y., Lamy, D., Pergamin, L., Bakermans-Kranenburg, M. J., and van
IJzendoorn, M. H. (2007). reat related attentional bias in anxious and
nonanxious individuals: a meta-analytic study. Psychol. Bull. 133, 1–24. doi:
10.1037/0033-2909.133.1.1
Beck, A. T. (1976). Cognitive therapy and the emotional disorders. New York:
International Universities Press.
Beck, A. T., Emery, G., and Greenberg, R. L. (1985). Anxiety disorders and
phobias: A cognitive perspective. New York: Basic Books.
Bennett, H., and Wells, A. (2010). Metacognition, memory disorganization and
rumination in posttraumatic stress symptoms. J. Anxiety Disord. 24, 318–325.
doi: 10.1016/j.janxdis.2010.01.004
Borkovec, T. D., Robinson, E., Pruzinsky, T., and DePree, J. A. (1983). Preliminary
exploration of worry: some characteristics and processes. Behav. Res. er.
21, 9–16. doi: 10.1016/0005-7967(83)90121-3
Butler, G., Wells, A., and Dewick, H. (1995). Dierential eects of worry and
imagery aer exposure to a stressful stimulus: a pilot study. Behav. Cogn.
Psychother. 23, 45–56. doi: 10.1017/S1352465800017628
Callesen, P., Capobianco, L., Heal, C., Juul, C., Nielsen, S. F., and Wells, A.
(2019). A preliminary evaluation of transdiagnostic group metacognitive
therapy in a mixed psychological disorder sample. Front. Psychol. 10:1341.
doi: 10.3389/fpsyg.2019.01341
Callinan, S., Johnson, D., and Wells, A. (2015). A randomised controlled study
of the eects of the attention training technique on traumatic stress symptoms,
emotional attention set shiing and exibility. Cogn. er. Res. 39, 4–13.
doi: 10.1007/s10608-014-9634-8
Capobianco, L., Heal, C., Bright, M., and Wells, A. (2019). What comes rst,
metacognition or negative emotion: a test of temporal precedence. Front.
Psychol. 10:2507. doi: 10.3389/fpsyg.2019.02507
Capobianco, L., Morris, J., and Wells, A. (2018a). Worry and rumination: do
they prolong physiological and aective recovery from stress? Anxiety Stress
Coping 31, 291–303. doi: 10.1080/10615806.2018.1438723
Capobianco, L., Morrison, A. P., and Wells, A. (2018b). e eect of thought
importance on stress responses: a test of the metacognitive model. Stress
21, 128–135. doi: 10.1080/10253890.2017.1417378
Capobianco, L., Reeves, D., Morrison, A. P., and Wells, A. (2018c). Group
metacognitive therapy vs mindfulness meditation therapy in a transdiagnostic
patient sample: a randomised feasibility trial. Psychiatry Res. 259, 554–561.
doi: 10.1016/j.psychres.2017.11.045
Carter, K., and Wells, A. (2018). Eects of the attention training technique
on auditory hallucinations in schizo-aective disorder: a single case study.
Case Rep. Psychiatry 2018:1537237. doi: 10.1155/2018/1537237
Cartwright-Hatton, S., and Wells, A. (1997). Beliefs about worry and intrusions:
the metacognitions questionnaire and its correlates. J. Anxiety Disord. 11,
279–296. doi: 10.1016/S0887-6185(97)00011-X
Caselli, G., Martino, F., Spada, M. M., and Wells, A. (2018). Metacognitive
therapy for alcohol use disorder: a systematic case series. Front. Psychol.
9:2619. doi: 10.3389/fpsyg.2018.02619
Cisler, J. M., and Koster, E. H. (2010). Mechanisms of attentional bias towards
threat in anxiety disorders: an integrative review. Clin. Psychol. Rev. 30,
203–216. doi: 10.1016/j.cpr.2009.11.003
Clark, D. M., Ehlers, A., Hackmann, A., Mcmanus, F., Fennell, M., Grey, N.,
et al. (2006). Cognitive therapy versus exposure and applied relaxation in
social phobia: a randomized controlled trial. J. Consult. Clin. Psychol. 74,
568–578. doi: 10.1037/0022-006X.74.3.568
Clark, D. M., and Wells, A. (1995). “A cognitive model of social phobia” in Social
phobia: Diagnosis, assessment and treatment. eds. R. G. Heimberg, M. R.
Liebowitz, D. A. Hope, and F. R. Schneier (New York: Guilford Press), 69–93.
Davey, G. C. L., and Wells, A. (Eds.) (2006). Worry and its psychological
disorders: eory, assessment and treatment. Chichester, UK: Wiley.
Dimaggio, G., Montano, A., Popolo, R., and Salvatore, G. (2015). Metacognitive
interpersonal therapy for personality disorders. London: Taylor & Francis.
Epp, A. M., Dobson, K. S., Dozois, D. J., and Frewen, P. A. (2012). A systematic
meta-analysis of the Stroop task in depression. Clin. Psychol. Rev. 32,
316–328. doi: 10.1016/j.cpr.2012.02.005
Eysenck, M. W. (1992). Anxiety: e cognitive perspective. Hillsdale, NJ: Lawrence
Erlbaum Associates, Inc.
Eysenck, M. W., and Calvo, M. G. (1992). Anxiety and performance: the processing
eciency theory. Cognit. Emot. 6, 409–434. doi: 10.1080/02699939208409696
Eysenck, M. W., Derakshan, N., Santos, R., and Calvo, M. G. (2007). Anxiety
and cognitive performance: attentional control theory. Emotion 7, 336–353.
doi: 10.1037/1528-3542.7.2.336
Fergus, T. A., Bardeen, J. R., and Orcutt, H. K. (2012). Attentional control
moderates the relationship between activation of the cognitive attentional
syndrome and symptoms of psychopathology. Personal. Individ. Dier. 53,
213–217. doi: 10.1016/j.paid.2012.03.017
Fergus, T. A., Valentiner, D. P., McGrath, P. B., Gier-Lonswat, S., and Jencius, S.
(2013). e cognitive attentional syndrome: examining the relations with mood
and anxiety symptoms and distinctiveness from psychological inexibility in
a clinical sample. Psychiatry Res. 210, 215–219. doi: 10.1016/j.psychres.2013.04.020
Fisher, P. L., and Wells, A. (2005). Experimental modication of beliefs in
obsessive-compulsive disorder: a test of the metacognitive model. Behav.
Res. er. 43, 821–829. doi: 10.1016/j.brat.2004.09.002
Flavell, J. H. (1979). Metacognition and metacognitive monitoring: a new area
of cognitive-developmental inquiry. Am. Psychol. 34, 906–911. doi: 10.1037/
0003-066X.34.10.906
Foa, E. B., and Kozak, M. J. (1986). Emotional processing and fear: exposure
to corrective information. Psychol. Bull. 99, 20–35. doi: 10.1037/
0033-2909.99.1.20
Gwilliam, P., Wells, A., and Cartwright-Hatton, S. (2004). Does meta-cognition
or responsibility predict obsessive-compulsive symptoms: a test of the
Wells Metacognitive Control System
Frontiers in Psychology | www.frontiersin.org 14 December 2019 | Volume 10 | Article 2621
meta-cognitive model. Clin. Psychol. Psychother. 11, 137–144. doi: 10.1002/
cpp.402
Hagen, R., Hjemdal, O., Solem, S., Kennair, L. E. O., Nordhal, H. M., Fisher,
P., et al. (2017). Metacognitive therapy for depression in adults: a waiting
list randomized controlled trail with six month follow-up. Front. Psychol.
8:31. doi: 10.3389/fpsyg.2017.00031
Hjemdal, O., Hagen, R., Solem, S., Nordhal, H., Kennair, L. E. O., Ryum, T.,
et al. (2017). Metacognitive therapy in major depression: an open trial of
comorbid cases. Cogn. Behav. Pract. 24, 312–318. doi: 10.1016/j.cbpra.2016.06.006
Holeva, K., Tarrier, N., and Wells, A. (2001). Prevalence and predictors of
acute stress disorder and PTSD following road trac accidents: thought
control strategies and social support. Behav. er. 32, 65–83. doi: 10.1016/
S0005-7894(01)80044-7
Johnson, S. U., and Hoart, A. (2018). Metacognitive therapy versus cognitive
behavioural therapy: a network approach. Front. Psychol. 9:2382. doi: 10.3389/
fpsyg.2018.02382
Johnson, S. U., Hoart, A., Nordhal, H. M., and Wampold, B. E. (2017).
Metacognitive therapy versus disorder-specic CBT for comorbid anxiety
disorders: a randomized controlled trial. J. Anxiety Disord. 50, 103–112.
doi: 10.1016/j.janxdis.2017.06.004
Knowles, M. M., Foder, F., El-Deredy, W., and Wells, A. (2016). A systematic
review of the ecacy of the attention training technique in clinical and
nonclinical samples. J. Clin. Psychol. 72, 999–1025. doi: 10.1002/jclp.22312
Knowles, M. M., and Wells, A. (2018). Single dose of the attention training
technique increases resting alpha and beta oscillations in frontoparietal brain
networks: a randomized controlled comparison. Front. Psychol. 9:1768. doi:
10.3389/fpsyg.2018.01768
Leahy, R. L. (2015). Emotional schema therapy. New York: Guilford Press.
Lyubomirsky, S., and Tkach, C. (2004). “e consequences of dysphoric rumination”
in Depressive rumination: Nature, theory and treatment. eds. C. Papageorgiou
and A. Wells (Chichester, UK: Wiley), 21–41.
MacLeod, C. (1991). Half a century of research on the Stroop eect: an
integrative review. Psychol. Bull. 109, 163–203. doi: 10.1037/0033-2909.109.2.163
Mathews, A., and MacLeod, C. (1985). Selective processing of threat cues in
anxiety states. Behav. Res. er. 23, 563–569. doi: 10.1016/0005-7967(85)90104-4
Mathews, A., and MacLeod, C. (1986). Discrimination of threat cues without
awareness in anxiety states. J. Abnorm. Psychol. 95, 131–138. doi:
10.1037/0021-843X.95.2.131
Mathews, A., May, J., Mogg, K., and Eysenck, M. W. (1990). Attentional bias
in anxiety: selective search or defective ltering? J. Abnorm. Psychol. 99,
166–173. doi: 10.1037/0021-843X.99.2.166
Matthews, G., Hillyard, E. J., and Campbell, S. E. (1999). Metacognition
and maladaptove coping as components of test anxiety. Clin. Psychol.
Psychother. 6, 111–125. doi: 10.1002/(SICI)1099-0879(199905)6:2<111::A
ID-CPP192>3.0.CO;2-4
Matthews, G., Panganiban, A. R., Wells, A., Wohleber, R. W., and Reinerman-
Jones, L. E. (2019). Metacognition, hardiness, and grit as resilience factors
in unmanned aerial systems (UAS) operations: a simulation study. Front.
Psychol. 10:640. doi: 10.3389/fpsyg.2019.00640
Matthews, G., and Wells, A. (2000). Attention, automaticity and aective disorder.
Behav. Modif. 24, 69–93. doi: 10.1177/0145445500241004
Moritz, S., and Woodward, T. S. (2007). Metacognitive training in schizophrenia:
from basic research to knowledge translation and intervention. Curr. Opin.
Psychiatry 20, 619–625. doi: 10.1097/YCO.0b013e3282f0b8ed
Morris, L. W., Davis, M. A., and Hutchings, C. H. (1981). Cognitive and
emotional components of anxiety: literature review and a revised worry-
emotionality scale. J. Educ. Psychol. 73, 541–555. doi: 10.1037/0022-
0663.73.4.541
Morrison, A. P., Pyle, M., Chapman, N., French, P., Parker, S. K., and Wells, A.
(2014). Metacognitive therapy in people with a schizophrenia spectrum diagnosis
and medication resistant symptoms: a feasibility study. J. Behav. er. Exp.
Psychiatry 45, 280–284. doi: 10.1016/j.jbtep.2013.11.003
Morrison, A. P., Wells, A., and Nothard, S. (2000). Cognitive factors in
predisposition to auditory and visual hallucinations. Br. J. Clin. Psychol. 39,
67–78. doi: 10.1348/014466500163112
Myers, S., Fisher, P., and Wells, A. (2009). Metacognition and cognition as
predictors of obsessive-compulsive symptoms: a prospective study. Int. J.
Cogn. er. 2, 132–142. doi: 10.1521/ijct.2009.2.2.132
Myers, S., and Wells, A. (2005). Obsessive-compulsive symptoms: the contribution
of metacognitions and responsibility. J. Anxiety Disord. 189, 806–817. doi:
10.1016/j.janxdis.2004.09.004
Myers, S., and Wells, A. (2013). An experimental manipulation of metacognition:
a test of the metacognitive model of obsessive-compulsive symptoms. Beh av.
Res. er. 51, 177–184. doi: 10.1016/j.brat.2013.01.007
Myers, S. G., and Wells, A. (2015). Early trauma, negative aect, and anxious
attachment: the role of metacognition. Anxiety Stress Coping 28, 634–649.
doi: 10.1080/10615806.2015.1009832
Nassif, Y., and Wells, A. (2014). Attention training reduces intrusive thoughts
cued by a narrative of stressful life events: a controlled study. J. Clin. Psychol.
70, 510–517. doi: 10.1002/jclp.22047
NCCMH (2013). Social anxiety disorder: the NICE guideline on recognition,
assessment and treatment. Leicester & London: e British Psychologcial
Society and the Royal College of Psychiatrists (Full Guideline).
Nelson, T. O., and Narens, L. (1990). “Metamemory: a theoretical framework
and some new ndings” in e psychology of learning and motivation. ed.
G. H. Bower (New York: Academic Press), 125–173.
Niendam, T. A., Laird, A. R., Ray, K. L., Dean, Y. M., Glahn, D. C., and
Carter, C. S. (2012). Meta-analytic evidence for a superordinate cognitive
control network subserving diverse executive functions. Cogn. Aect. Behav.
Neurosci. 12, 241–268. doi: 10.3758/s13415-011-0083-5
Nolen-Hoeksema, S. (1991). Responses to depression and their eects on the
duration of depressive episodes. J. Abnorm. Psychol. 100, 569–582. doi:
10.1037/0021-843X.100.4.569
Nolen-Hoeksema, S. (2000). e role of rumination in depressive disorders
and mixed anxiety/depressive symptoms. J. Abnorm. Psychol. 109, 504–511.
doi: 10.1037/0021-843X.109.3.504
Nordahl, H. M., Borkovec, T. D., Hagen, R., Kennair, L. E. O., Hjemdal, O.,
Solem, S., et al. (2018). Metacognitive therapy versus cognitive-behavioural
therapy in adults with generalised anxiety disorder. Br. J. Psychiatry Open
4, 393–400. doi: 10.1192/bjo.2018.54
Nordahl, H., Hjemdal, O., Hagen, R., Nordahl, H. M., and Wells, A. (2019).
What lies beneath trait-anxiety? Testing the self-regulatory executive
function model of vulnerability. Front. Psychol. 10:122. doi: 10.3389/
fpsyg.2019.00122
Nordahl, H., Nordahl, H. M., Hjemdal, O., and Wells, A. (2017). Cognitive
and metacognitive predictors of symptom improvement following treatment
for social anxiety disorder: a secondary analysis from a randomized
controlled trial. Clin. Psychol. Psychother. 24, 1221–1227. doi: 10.1002/
cpp.2083
Nordahl, H. M., Vogel, P. A., Morken, G., Stiles, T. C., Sandvik, P., and Wells, A.
(2016). Paroxetine, cognitive therapy or their combination in the treatment of
social anxiety disorder with and without avoidant personality disorder: a
randomized clinical trial. Psychother. Psychosom. 85, 346–356. doi:
10.1159/000447013
Nordahl, H., and Wells, A. (2017). Testing the metacognitive model against
the benchmark CBT model of social anxiety disorder: is it time to
move beyond cognition? PLoS One 12:e0177109. doi: 10.1371/journal.
pone.0177109
Nordhal, H. M., and Wells, A. (2019). Metacognitive therapy of early traumatized
patients with borderline personality disorder: a phase-II baseline controlled
trial. Front. Psychol. 10:1694. doi: 10.3389/fpsyg.2019.01694
Normann, N., and Morina, N. (2018). e ecacy of metacognitive therapy:
a systematic review and meta-analysis. Front. Psychol. 9:2211. doi: 10.3389/
fpsyg.2018.02211
Normann, N., Van Emmerik, A. A. P., and Morina, N. (2014). e ecacy
of metacognitive therapy for anxiety and depression: a meta-analytic review.
Depress. Anxiety 31, 402–411. doi: 10.1002/da.22273
Papageorgiou, C., Carlile, K., orgaard, S., Waring, H., Haslam, J., Horne, L.,
et al. (2018). Group cognitive-behavior therapy or group metacognitive
therapy for obsessive-compulsive disorder? Benchmarking and comparative
eectiveness in a routine clinical service. Front. Psychol. 9:2551. doi: 10.3389/
fpsyg.2018.02551
Papageorgiou, C., and Wells, A. (2001). Positive beliefs about depressive rumination:
development and preliminary validation of a self-report scale. Behav. er.
32, 13–26. doi: 10.1016/S0005-7894(01)80041-1
Wells Metacognitive Control System
Frontiers in Psychology | www.frontiersin.org 15 December 2019 | Volume 10 | Article 2621
Papageorgiou, C., and Wells, A. (2003). An empirical test of a clinical metacognitive
model of rumination and depression. Cogn. er. Res. 27, 261–273. doi:
10.1023/A:1023962332399
Papageorgiou, C., and Wells, A. (Eds.) (2004). Depressive rumination: Nature,
theory and treatment. Chichester, UK: Wiley.
Papageorgiou, C., and Wells, A. (2009). A prospective test of the clinical
metacognitive model of rumination and depression. Int. J. Cogn. er. 2,
123–131. doi: 10.1521/ijct.2009.2.2.123
Phaf, R. H., and Kan, K. (2007). e automaticity of emotional Stroop: a meta-
analysis. J. Behav. er. Exp. Psychiatry 38, 184–199. doi: 10.1016/j.
jbtep.2006.10.008
Qiu, L., Su, J., Ni, Y., Bai, Y., Zhang, X., Li, X., et al. (2018). e neural
system of metacognition accompanying decision-making in the prefrontal
cortex. PLoS Biol. 16:e.2004037. doi: 10.1371/journal.pbio.2004037
Rachman, S. (1980). Emotional processing. Behav. Res. er. 18, 51–60. doi:
10.1016/0005-7967(80)90069-8
Rassin, E., Merckelbach, H., Muris, P., and Spaan, V. (1999). ought-action
fusion as a causal factor in the development of intrusions. Behav. Res. er.
37, 231–237. doi: 10.1016/S0005-7967(98)00140-5
Reinholdt-Dunne, M. L., Blicher, A., Nordhal, H., Normann, N., Esbjorn, B.
H., and Wells, A. (2019). Modelling the relationships between metacognitive
beliefs, attention control and symptoms in children with and without anxiety
disorders: a test of the S-REF model. Front. Psychol. 10:1205. doi: 10.3389/
fpsyg.2019.01205
Rosenbaum, D., Mair, J. M., Hudak, J., Metzger, F. G., and Wells, A. (2018).
Neurophysiological correlates of the attention training technique: a component
study. NeuroImage 19, 1018–1024. doi: 10.1016/j.nicl.2018.06.021
Roussis, P., and Wells, A. (2006). Post-traumatic stress symptoms: tests of
relationships with thought control strategies and beliefs as predicted by the
metacognitive model. Personal. Individ. Dier. 40, 111–122. doi: 10.1016/j.
paid.2005.06.019
Roussis, P., and Wells, A. (2008). Psycholocial factors predicting stress symptoms:
metacognition, thought control and varieties of worry. Anxiety Stress Coping
21, 213–225. doi: 10.1080/10615800801889600
Schneider, E., and Shirin, R. M. (1977). Controlled and automatic human
information processing: I. Detection, search and attention. Psychol. Rev. 84,
1–66. doi: 10.1037/0033-295X.84.1.1
Sellers, R., Varese, F., Wells, A., and Morrison, A. (2017). A meta-analysis of
metacognitive beliefs as implicated in the self-regulatory executive function
model in clinical psychosis. Schizophr. Res. 179, 75–84. doi: 10.1016/j.
schres.2016.09.032
Solem, S., Haland, A. T., Vogel, P. A., Hansen, B., and Wells, A. (2009). Change
in metacognitions predicts outcome in obsessive-compulsive disorder patients
undergoing treatment with exposure and response prevention. Behav. Res.
e r. 47, 301–307. doi: 10.1016/j.brat.2009.01.003
Spada, M. M., Caselli, G., and Wells, A. (2009). Metacognitions as a predictor
of drinking status and level of alcohol use following CBT in problem
drinkers: a prospective study. Behav. Res. er. 47, 882–886. doi: 10.1016/j.
brat.2009.06.010
Spada, M. M., Mohiyeddini, C., and Wells, A. (2008). Measuring metacognitions
associated with emotional distress: factor structure and predictive validity
of the metacognitions questionnaire 30. Personal. Individ. Dier. 45, 238–242.
doi: 10.1016/j.paid.2008.04.005
Spada, M. M., Moneta, G. B., and Wells, A. (2007). e relative contribution
of metacognitive beliefs and alcohol expectancies to drinking behaviour.
Alcohol Alcohol. 42, 567–574. doi: 10.1093/alcalc/agm055
Spada, M. M., and Wells, A. (2008). Metacognitive beliefs about alcohol use:
development and validation of two self-report scales. Addict. Behav. 33,
515–527. doi: 10.1016/j.addbeh.2007.10.011
Staugaard, S. R. (2010). reatening faces and social anxiety: a literature review.
Clin. Psychol. Rev. 30, 669–690. doi: 10.1016/j.cpr.2010.05.001
Sun, X., Zhu, C., and So, S. H. W. (2017). Dysfunctional metacognition across
psychopathologies: a meta-analytic review. Eur. Psychiatry 45, 139–153. doi:
10.1016/j.eurpsy.2017.05.029
Techmann, B. A., Joormann, J., Steinman, S. A., and Gotlib, I. H. (2010).
Automaticity in anxiety disorders and major depressive disorder. Clin. Psychol.
Re v. 32, 575–603. doi: 10.1016/j.cpr.2012.06.004
Van der Heiden, C., Muris, P., and van der Molen, H. T. (2010). Randomized
controlled trial on the eectiveness of metacognitive therapy and intolerance-
of-uncertainty therapy for generalized anxiety disorder. Behav. Res. er.
50, 100–109. doi: 10.1016/j.brat.2011.12.005
Warda, G., and Bryant, R. A. (1998). ought control strategies in acute
stress disorder. Behav. Res. er. 36, 1171–1175. doi: 10.1016/S0005-
7967(98)00082-5
Wells, A. (1990). Panic disorder in association with relaxation induced anxiety:
an attentional training approach to treatment. Behav. er. 21, 273–280.
doi: 10.1016/S0005-7894(05)80330-2
Wells, A. (1994). A multidimensional measure of worry: development and
preliminary validation of the anxious thoughts inventory. Anxiety Stress
Coping 6, 289–299. doi: 10.1080/10615809408248803
Wells, A. (1995). Meta-cognition and worry: a cognitive model of generalized
anxiety disorder. Behav. Cognit. Psychother. 23, 301–320.
Wells, A. (1997). Cognitive therapy of anxiety disorders: A practice manual and
conceptual guide. Chichester, UK: Wiley.
Wells, A. (2000). Emotional disorders and metacognition: Innovative cognitive
therapy. Chichester, UK: Wiley.
Wells, A. (2005a). e metacognitive model of GAD: assessment of meta-worry
and relationship with DSM-IV generalized anxiety disorder. Cogn. er.
Res. 29, 107–121. doi: 10.1007/s10608-005-1652-0
Wells, A. (2005b). Detached mindfulness in cognitive therapy: a metacognitive
analysis and ten techniques. J. Ration. Emot. Cogn. Behav. er. 23, 337–355.
doi: 10.1007/s10942-005-0018-6
Wells, A. (2009). Metacognitive therapy for anxiety and depression. New York:
Guilford Press.
Wells, A., and Carter, K. (2001). Further tests of a cognitive model of generalized
anxiety disorder: metacognitions and worry in gad, panic disorder, social phobia,
depression and nonpatients. Behav. er. 32, 85–102. doi: 10.1016/
S0005-7894(01)80045-9
Wells, A., and Cartwright-Hatton, S. (2004). A short form of the metacognitions
questionnaire: properties of the MCQ-30. Behav. Res. er. 42, 385–396.
doi: 10.1016/S0005-7967(03)00147-5
Wells, A., and Colbear, J. (2012). Treating post-traumatic stress disorder with
metacognitive therapy: a preliminary controlled trial. J. Clin. Psychol. 68,
373–381. doi: 10.1002/jclp.20871
Wells, A., and Davies, M. (1994). e thought control questionnaire: a measure
of individual dierences in the control of unwanted thought. Behav. Res.
e r. 32, 871–878. doi: 10.1016/0005-7967(94)90168-6
Wells, A., Fisher, P., Myers, S., Wheatlet, J., Patel, T., and Brewin, C. R. (2012).
Metacognitive therapy in treatment resistant depression: a platform trial.
Behav. Res. er. 50, 367–373. doi: 10.1016/j.brat.2012.02.004
Wells, A., and Matthews, G. (1994). Attention and emotion: A clinical perspective.
Hove, UK: Erlbaum.
Wells, A., and Matthews, G. (1996). Modelling cognition in emotional
disorder: the S-REF model. Behav. Res. er. 34, 881–888. doi: 10.1016/
S0005-7967(96)00050-2
Wells, A., and Matthews, G. (2015). Attention and emotion: A clinical perspective
(classic edition). Hove, UK: Psychology Press.
Wells, A., and Papageorgiou, C. (1995). Worry and the incubation of intrusive
images following stress. Behav. Res. er. 33, 579–583. doi: 10.1016/0005-
7967(94)00087-Z
Wells, A., and Papageorgiou, C. (1998). Social phobia: eects of external attention
instructions on anxiety, negative beliefs and perspective taking. Behav. er.
29, 357–370. doi: 10.1016/S0005-7894(98)80037-3
Wells, A., Walton, D., Lovell, K., and Proctor, D. (2015). Metacognitive therapy
versus prolonged exposure in adults with chronic post-traumatic stress
disorder: a parallel randomized controlled trial. Cogn. er. Res. 39, 70–80.
doi: 10.1007/s10608-014-9636-6
Wells, A., Welford, M., King, P., Papageorgiou, C., Wisely, J., and Mendel, E.
(2010). A pilot randomized trial of metacognitive therapy vs applied relaxation
in the treatment of adults with generalized anxiety disorder. Behav. Res.
e r. 48, 429–434. doi: 10.1016/j.brat.2009.11.013
Williams, J. M. G., Watts, F. N., MacLeod, C., and Mathews, A. (1988). Cognitive
psychology and emotional disorders. Chichester, UK: Wiley.
Winter, L., Gottschalk, J., Nielsen, J., Wells, A., Schweiger, U., and Kahl, K.
(2019). A comparison of metacognitive therapy in current versus persistent
Wells Metacognitive Control System
Frontiers in Psychology | www.frontiersin.org 16 December 2019 | Volume 10 | Article 2621
depressive disorder: a pilot outpatient study. Front. Psychol. 10:1714. doi:
10.3389/fpsyg.2019.01714
Yilmaz, A. E., Gencoz, T., and Wells, A. (2011). e temporal precedence of
metacognitions in the development of anxiety and depression symptoms in
the context of life-stress: a prospective study. J. Anxiety Disord. 25, 389–396.
doi: 10.1016/j.janxdis.2010.11.001
Conflict of Interest: e author declares that the research was conducted in
the absence of any commercial or nancial relationships that could beconstrued
as a potential conict of interest.
e reviewer GC declared a past co-authorship with the author AW to the
handling editor.
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