emotion recognition in children with anxiety disorders ......vi recognition in young children with...
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Emotion Recognition in Children with Anxiety Disorders:
Effects of Age, Subtype, and Gender
By
Trevor Changgun Lee
A thesis submitted in conformity with the requirements
for the degree of Master of Science
Graduate Department of Medical Sciences
University of Toronto
© Copyright by Trevor Changgun Lee, 2013
ii
EMOTION RECOGNITION IN CHILDREN
WITH ANXIETY DISORDERS:
EFFECTS OF AGE, SUBTYPE, AND GENDER
Master of Science, 2013
Trevor Changgun Lee
Institute of Medical Science
University of Toronto
Abstract
Objectives: It is unclear whether anxiety disorders are associated with children’s ability to
recognize emotions. To elucidate this relationship, the effects of age, subtype, and gender
were examined, which have been neglected in past studies. Methods: Sixty-three anxious
children and 59 non-anxious children identified various emotions displayed by an animated
character. Children also completed questionnaires measuring state anxiety and
depressive/anxiety symptoms. Results: Anxious children generally did not have difficulty
identifying emotions compared with non-anxious children. However, children with
separation anxiety disorder (SAD) and young children with generalized anxiety disorder
(GAD) showed difficulty. Gender played a minimal role in emotion recognition, but anxious
girls were less accurate in recognizing disgust when compared with anxious boys and non-
anxious girls. Conclusion: Anxious children as a group may not exhibit difficulty in
emotion recognition. When age and subtype factors are considered, however, children with
SAD and young children with GAD exhibit some deficits.
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Acknowledgments
First of all, I would like to express my deepest appreciation to my thesis supervisor,
Dr. Katharina Manassis, for providing me an opportunity to conduct my first graduate
research at Sick Kids. Without her masterly guidance, time, and patience, my thesis and
publication would have been impossible. Katharina’s words of support and wisdom, during
our Tuesday meetings, helped me stay motivated in my project, and fostered my passion for
research. I sincerely thank her for everything for the last two years of my life, one of the
happiest moments in my life. My marvelous experience as her student will be forever
unforgettable.
I am indebted to Dr. Rosemary Tannock and Dr. Paul Arnold who gave me
constructive advice and suggestions throughout my project. I am absolutely convinced that
taking every piece of their valuable advice has led to timely dissemination of my research.
To Rosemary, I am grateful for being my committee member despite her scheduled
retirement this year. Also, I wish to greatly thank Paul for letting me observe his full-day of
assessments and follow-ups for my graduate module and for my better understanding of
childhood OCD. It was a very fascinating and eye-opening experience for me.
Words fail me to express my appreciation to Dr. Judy Wiener for her insightful
advice for my project and for her continual support throughout my undergraduate and
graduate years. She was always beside me during happy and difficult times to push me and
motivate me. Her compassion for students and teachings will always stay with me.
This study would not have been successful without the help of Mr. David Avery, Ms.
Emily Jones, Dr. Monique Herbert, Dr. Annie Dupuis, and Ms. Carly Guberman. I also
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thank the Social Sciences and Humanities Research Council of Canada and The Hospital for
Sick Children Research Institute for financial support.
I wish to share the credit of my work with my family and friends, who I love from my
heart. With their emotional support and encouragement, I have been able to effectively
manage my stress at times of difficulty. Lastly, I wish to thank my grandparents, who are no
longer among us, for their love and discipline during my childhood in Korea. I wish that, if
they can look down from the above, they would be proud of me thriving to live my dreams.
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Table of Contents
Page
Abstract ii
Acknowledgements iii
Table of Contents v
List of Tables viii
List of Figures ix
Chapter 1 General Introduction 1
General Organization of Thesis
Introduction
Non-pathological Anxiety in Children
Pathological Anxiety in Children
Types of Childhood Anxiety Disorders
o Separation Anxiety Disorder (SAD)
o Generalized Anxiety Disorder (GAD)
o Social Phobia (SP)
o Obsessive-compulsive Disorder (OCD)
o Post-traumatic Stress Disorder (PTSD)
o Specific Phobia
o Panic Disorder (PD)
Changes in Classification and Diagnostic Criteria for
Childhood Anxiety Disorders in DSM-5
Consequences of Childhood Anxiety Disorders
Evidence-based Treatments for Childhood Anxiety
Disorders
o What is Cognitive Behavioural Therapy?
o Cognitive Behavioural Therapy for Childhood
Anxiety Disorders and Its Efficacy
o Emotion-focused Cognitive Behavioural
Therapy
Emotion Understanding
Emotion Recognition
o Neural Mechanisms of Emotion Recognition
o Social Correlates and Psychopathologies Linked
to Emotion Recognition
o Previous Findings on Emotion Recognition in
Children with Anxiety Disorders
What Are the Factors Potentially Contributing to
Inconsistent Results of Past Studies?
o Measurement Limitations in Assessing Emotion
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4
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7
8
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10
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Recognition in Young Children with Anxiety
Disorders
o Other Limitations of Previous Studies
Merits of the Present Study and General Aims
Hypotheses
o Objective #1: Emotion Recognition Accuracy in
Children with and without Anxiety Disorder
o Objective #2: Effect of Age on Emotion
Recognition Accuracy in Children with and
without Anxiety Disorder
o Objective #3: Effects of Anxiety Subtype on
Emotion Recognition Accuracy in Children with
Anxiety Disorders
o Objective #4: Effect of Gender on Emotion
Recognition Accuracy in Children with and
without Anxiety Disorder
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Chapter 2 The Effects of Age and Subtype on Emotion Recognition in
Children with Anxiety Disorders
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Abstract
Introduction
Methods
Results
Discussion
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38
44
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Chapter 3 The Effect of Gender on Emotion Recognition in Children
with and without Anxiety Disorders
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Abstract
Introduction
Methods
Results
Discussion
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64
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Chapter 4 Additional Analysis: The Effects of State Anxiety, Task
Completion Time, Depressive Symptoms, and Anxiety
Symptoms on Emotion Recognition in Children with and
without Anxiety Disorders
Abstract
Introduction
Methods
Results
Discussion
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Chapter 5 General Discussion 91
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Chapter 6 Future Directions
References
Appendix A
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108
134
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List of Tables
Page
Chapter 2
1. Characteristics of the anxiety group and the control group
2. Ordinal regression analyses of anxiety diagnosis and separation and anxiety
disorder predicting emotion recognition accuracy in comparison with the
control group
3. Ordinal regression analyses of age predicting emotion recognition accuracy for
children with and without anxiety disorder
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53
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Chapter 3
1. Ordinal regression analyses of gender and clinical status predicting emotion
recognition accuracy on specific emotions
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Chapter 4
1. Ordinal regression analyses of state anxiety predicting recognition accuracy on
specific emotions in children with and without anxiety disorder
2. Ordinal regression analyses of CDI-T score predicting recognition accuracy on
specific emotions in children with and without anxiety disorder
3. Ordinal regression analyses of SCARED T-score predicting recognition
accuracy on specific emotions in children with and without anxiety disorder
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87
89
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List of Figures
Page
Chapter 2
1. Total accuracy score on MAAC by subtypes: SAD, GAD, SP, and control
groups
2. Regression liens for age and total accuracy score on MAAC in the SAD and
GAD groups, comparison with the control group
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1
Chapter One
General Introduction
2
General Organization of Thesis
My thesis begins with a chapter of general introduction (Chapter 1). In this chapter,
published scholarly articles and textbook chapters are reviewed to frame my thesis with
reference to the history of the present research questions, while explaining important
terminology, concepts, and gaps in knowledge in this area of research. This chapter further
describes the importance of investigating the ability to correctly recognize others’ emotional
states in children with anxiety disorders, and addresses some of the methodological issues in
measuring emotion recognition skill in young children. Lastly, the chapter ends with the
main study aims and hypotheses.
Chapters 2 and 3 are the main studies of my thesis, and are presented as scientific
journal manuscripts for submission. Chapter 2 is based on my first journal manuscript
“Effects of Age and Subtype on Emotional Recognition in Children with Anxiety Disorders”,
which was accepted in November of 2012 for publication in Canadian Journal of Psychiatry.
This chapter examines if children with anxiety disorders are impaired in their ability to
identify others’ emotional states, and if children with certain types of primary anxiety
disorder are more impaired than children with other types of anxiety disorder or without
anxiety disorder.
Chapter 3 is my second journal manuscript “Effect of Gender on Emotion
Recognition Accuracy in Children with Anxiety Disorders: Disgust Recognition Implicated”,
which was prepared as a brief report. This chapter examines if gender significantly predicts
emotion recognition accuracy in children with anxiety disorders.
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Chapter 4 contains additional exploratory analyses that delve into the potential effects
of state anxiety, task completion time, depressive symptoms, and anxiety symptoms on
emotion recognition accuracy in children with and without anxiety disorders.
Chapter 5 is a general discussion section that summarizes significant findings of the
present study, while comparing them to the original hypotheses. Then, the chapter discusses
clinical implications and the limitations of the present study. A general conclusion is briefly
stated, and finally, my thesis ends with Chapter 6, a description of future directions for this
research.
Because my thesis work is organized as a set of self-contained chapters that all
examine emotion recognition accuracy in children with anxiety disorders using common
methods, some degree of repetition was inevitable. Tables and figures are displayed at the
end of each chapter, and all references are placed at the end of this thesis.
4
Introduction
The ability to correctly identify the emotional states of others plays a pivotal role in
interpersonal relationships. Proficiency in this emotional skill may have also served as an
adaptive trait in human evolution. For example, accurate recognition of others’ anger or
disgust would allow the observer to avoid confrontation or poisons/contaminants, leading to
better chance of survival. On the other hand, impairment in this skill may diminish
experiences in everyday lives. Not surprisingly, impaired recognition of emotions is reported
in various mental disorders.
Children with anxiety disorders have difficulties in social and emotional functioning.
These observations raise the question of whether these children are impaired in the ability to
recognize the emotional states of others. However, there is a paucity of research on this
issue, and the available past studies have shown inconsistent results. Answering this
question may allow scientists to better understand the nature of anxious children’s emotional
development and social difficulties.
Further, investigating emotion recognition in anxious children may have implications
for current psychotherapies for childhood anxiety disorders. For example, the traditional
anxiety-focused psychotherapy focuses on the reduction of anxiety symptoms via changing
thinking and behavioural patterns, and regulation of emotions. However, efficacy of the
psychotherapy might improve if equal emphasis were placed on improving emotion-related
skills in children with anxiety disorders. For this reason, researchers developed a new
emotion-focused psychotherapy which involves more sessions to discuss emotions that
anxious children may have difficulty understanding and regulating. Examining emotion
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recognition in anxious children would inform psychotherapy and elucidate when and whether
emotion-focused psychotherapy may be more beneficial.
The present study aims to elucidate the relationship between anxiety disorders and
children’s ability to recognize others’ emotions. In this thesis, I highlight the effects of age,
subtype, and gender on emotion recognition in anxious children. Paying attention to these
factors may lead to novel findings in this field of research, relevant to better understanding
and treating anxious children’s emotional development.
Non-pathological Anxiety in Children
Anxiety or worry is characterized by a diffuse sense of apprehension and unpleasant
thoughts (e.g. anticipation of harm) that are accompanied by autonomic symptoms (e.g. heart
palpitations, muscle tension, stomach pain) and avoidance behaviour (Barlow, 1988; Lang,
1968). Transient anxiety is a normal response to threats or dangerous situations, and this
fleeting condition effectively triggers defensive fight-or-flight responses (Ohman, 1993).
These defensive reactions help individuals protect themselves from the negative emotional
states or physical dangers associated with the acute stressors (Ohman, 1993). Further, this
passing, non-pathological anxiety also motivates individuals to be vigilant about potential
threats and to avoid confrontation of these aversive stimuli by anticipating them (Barlow,
2000).
According to social-cognitive theory, the state of anxiety transpires when a person’s
perception of threat or danger outweighs self-efficacy of coping such that lower perceived
self-efficacy compared with harmful aspects of an aversive event will result in anxiety
arousal (Barlow, 2000; Bandura, 1986; 1988, Marks, 1977). In this sense, the same
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potentially harmful stimulus or event may cause anxiety arousal in some individuals, but may
not in others based on their perception of self-efficacy of coping.
Non-pathological anxiety or worry is very common in school-age children. For
example, about 70% of school-age children are mildly anxious or worried about everyday
life (Muris, Meesters, Merckelbach, Sermon, & Zwakhalen, 1998; Silverman et al., 1995).
Mothers of approximately 43% of school-age children report that their children undergo
seven or more mild worries and fears, often including separation concerns (Bell-Dolan, Last,
& Strauss, 1990; Lapouse & Monk, 1964).
Although the theme of anxiety or worry in school-age children often changes during
the course of development (Albano, Chorpita, & Barlow, 2003; Bauer, 1976), the most
common themes of anxiety in children relate to academic performance, physical health,
dying, and interpersonal relationships (Muris et al., 1998). Such anxiety-generating thoughts
can occur as early as five years, and these thoughts tend to be more frequent and more
complex in content at 8 years or above (Vasey, 1993). The age-related increase in the
frequency and complexity of anxious thoughts in school-age children may reflect their
development in cognitive skills, such as their ability to anticipate threatening outcomes and
to elaborate negative implications from these outcomes (Magnusson, 1985; Vasey, Crnic, &
Carter, 1994). In most cases, anxiety or worry in children is seen as non-pathological
because their anxious feelings do not lead to significant impairment and distress and subside
when the anxiety-provoking stimulus is no longer present or out of sight. Further, the
amount of anxiety children experience is reasonable to the circumstances and in proportion
to the actual threat (Wagner, 2002, pp. 22).
Pathological Anxiety in Children
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Non-pathological anxiety or worry can become pathological and maladaptive when a
child’s anxiety or worry is excessive (i.e. out of proportion to the actual threats), pervasive,
recurrent or chronic, and if anxiety interferes with normal functioning, learning and
concentration. In such case, a child may be diagnosed with an anxiety disorder (American
Psychiatric Association, 2000). The onset of anxiety disorder may be sudden, sometimes
within a few hours, or gradual, often taking weeks, months, or years (Angst & Vollrath,
1991).
Anxiety disorders are among the most prevalent psychiatric disorders of childhood
and adolescence (Anderson, 1994; Bernstein & Borchardt, 1991). However, the exact
prevalence rate of childhood anxiety disorders is unclear as the number varies significantly
across different epidemiologic studies (Cartwright-Hatton, McNicol, & Doubleday, 2006). It
is estimated that approximately 5-15% of the general population has some type of anxiety
disorder during childhood (Klein & Pine, 2002). The most conservative point prevalence in
the literature indicates that at least 3% of children and adolescents are affected (Ford,
Goodman, & Meltzer, 2003), attesting to the high prevalence of childhood anxiety disorders.
Pathological symptoms of anxiety disorders can be a salient feature in a multitude of
psychiatric and mood disorders in children. For example, about 16% to 62% of children and
adolescents with depression have comorbid anxiety disorders (Brady & Kendall, 1992).
Anxiety disorders in children and adolescents also tend to be highly comorbid with each
other (Craske & Waters, 2005), implying that a child diagnosed with one type of anxiety
disorder is at increased risk for another type of anxiety disorder.
Types of Childhood Anxiety Disorders
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Anxiety disorder in children and adolescents, similar to those in adults, may manifest
in a number of distinct forms, including separation anxiety disorder (SAD), generalized
anxiety disorder (GAD), social phobia (SP), specific phobia, obsessive-compulsive disorder
(OCD), post-traumatic stress disorder (PTSD), and panic disorder (PD) (American
Psychiatric Association, 2000). Among these different types of anxiety disorders in children,
SAD is the only type that is specific to childhood (Ollendick & Schroeder, 2003, pp. 34).
Separation anxiety disorder (SAD).
SAD is among the most common types of anxiety disorders of childhood, affecting
approximately 4.1% of school-age children (Shear, Jin, Ruscio, Walters, & Kessler, 2006).
Children diagnosed with SAD are abnormally reactive to real or imagined separation from
their parents or other attachment figures, and their distress is severe enough to interfere with
normal functioning and development (Masi, Mucci, & Millepied, 2001). Childhood SAD is
strongly associated with school-refusal behavior (Last & Strauss, 1990), which in turn
significantly predicts inadequate relationships with peers and poor academic performance
(Berg, Marks, McGuire & Lipsedge, 1974; Hersov, 1972). The onset of school-refusal in
children diagnosed with SAD can begin as early as 8-9 years, and their age at psychiatric
assessment is around 11-12 years (Last & Strauss, 1990).
Childhood SAD has been proposed as a major risk factor for the development of
major depression (Lewinsohn et al., 2008) and certain types of anxiety disorders in adults,
such as panic disorder (Battaglia et al., 1995; Lewinsohn et al., 2008) and agoraphobia in
women (Zitrin & Ross, 1988). However, some recent longitudinal studies have argued
against the link between childhood SAD and panic disorder in adults (Aschenbrand, Kendall,
Webb, Safford, & Flannery-Schroeder, 2003), warranting further investigation in this regard.
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Generalized anxiety disorder (GAD).
According to DSM-IV, a diagnosis of GAD can be made when a child is excessively
anxious for more than six months, but the focus of anxiety is not on a specific event or
stimulus (2000). These children tend to worry about a variety of issues (e.g. relationships,
physical health, keeping schedules), and often exaggerate their concerns and the risks of
situations (Hudson, Deveney, & Taylor, 2005). Symptomatology of GAD in children
includes feelings of tension, apprehension, need for reassurance, irritability, negative self-
perception (Masi, Mucci, Favilla, Romano, & Poli, 1999), and one or more chronic
physiological symptoms (e.g. stomach ache, sleep disturbance, restless, impaired
concentration on tasks) (Kendall & Pimentel, 2003). Children with GAD present a more
frequent need for reassurance than adolescents with GAD, whereas adolescents with GAD
tend to brood more frequently than children with GAD (Masi et al., 1999). The prevalence
rate of GAD in school-age children is estimated to be 5% (Shear et al., 2006), and the onset
is about 9 to 10 years (Last, Perrin, Hersen, & Kazdin, 1992). GAD in children is usually
comorbid with other type(s) of anxiety disorders or mood disorders, and this comorbidity
often limits our understanding of pure childhood GAD (Hudson et al., 2005).
Social phobia (SP).
Children living with SP (or social anxiety disorder) experience persistent and extreme
fear of being judged negatively in social situations, and are often concerned that others will
notice their anxiety symptoms in social settings (American Psychiatric Assocation, 2000;
Heckelman & Schneier, 1995, pp. 3). As a result, SP presents as the second most frequent
anxiety subtype in children and adolescents who refuse to go to school (Last & Strauss,
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1990), and is also often comorbid with other types of anxiety disorder, such as GAD
(Francis, Last, & Strauss, 1992).
The SP syndrome can be diagnosed in school-age children (Biedel & Turner, 1998),
and symptoms resemble those in adults (e.g. fear of speaking/reading/writing in public,
informal social activities) (Beidel, Turner, & Morris, 1999). Psychopathologies of SP in
children manifest as heightened emotional responsiveness, social inhibition or shyness,
dysphoria, loneliness, distress, and maladaptive coping (Beidel et al., 1999).
Obsessive-compulsive disorder (OCD).
The concept of OCD involves both the cognitive feature of obsessions and the
behavioural feature of compulsions. An obsession is “an intrusive, repetitive thought, image,
or impulse that is unacceptable or unwanted and gives rise to subjective resistance”
(Rachman & Shafran, 1998, pp. 51), whereas a compulsion is “a repetitive, stereotyped,
intentional act” with an “experienced sense of pressure to act, and the attribution of this
pressure to internal sources” (Rachman & Shafran, 1998, pp. 53-54). Compulsive
behaviours and cognition are thought to help temporarily relieve or suppress obsessions, and
these behaviours can be either overt (e.g. washing) or covert (e.g. counting, praying,
neutralizing) in nature (March & Friesen, 1998, pp. 5).
The diagnostic criteria for OCD include obsessions or compulsions that cause
significant distress, time consumption (spending more than an hour per day), or marked
interference with the individual’s functioning (American Psychiatric Association, 2000).
The most common themes of obsessions in children are fear of contamination, fear of
harming self or others, and an excessive urge for symmetry or exactness, whereas the most
common compulsions are excessive washing, checking, counting, repeating, touching and
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straightening (March & Friesen, 1998, pp. 6; Swedo et al., 1989). The prevalence rates of
OCD in children and adolescents have been found to be approximately 2-3% (Valleni-Basile,
Garrison, Jackson, & Waller, 1994). About a half of adult OCD patients acquired their OCD
during childhood (Rasmussen & Eisen, 1990)
Post-traumatic stress disorder (PTSD).
When a child directly experiences or observes a catastrophic event, which is life-
threatening or involves serious injury, he/she may develop ongoing emotional and physical
difficulties known as PTSD (American Academy of Child and Adolescent Psychiatry, 2010).
Children experience PTSD through (1) repeated, persistent re-experiencing of the traumatic
event (e.g. distressing memories, dreams, flashbacks), (2) emotional numbing and
detachment (e.g. avoidance of thoughts and feelings about the traumatic event), and (3)
hypervigilance and/or chronic arousal (e.g. always being on guard for the event to recur)
(American Psychiatric Association, 2000). Additionally, children may express post-
traumatic stress through hyperactivity, excessive fear, helplessness, horror, disorganized or
agitated behaviour for more than one month (Fletcher, 2003, pp. 332; Kaminer, Seedat, &
Stein, 2005). If these symptoms last for less than four weeks in duration, however, the child
may be diagnosed with acute stress disorder instead of PTSD (Nolen-Hoeksema, 2007, pp.
193).
Due to the unpredictability of catastrophic or traumatic events, it is difficult to
determine the range of prevalence of PTSD. In Canada, the lifetime prevalence of PTSD and
current (one month) PTSD are estimated to be about 9.2% and 2.4%, respectively (Van
Ameringen, Mancini, Patterson, & Boyle, 2008); however, there is a lack of systematic
epidemiologic review in childhood PTSD. It is generally agreed that school-age children are
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more susceptible to PTSD than adults exposed to a traumatic event as about 36% of
traumatized children are diagnosed with PTSD, whereas about 24% of adults are diagnosed
with PTSD following such events (Fletcher, 2003, pp. 332). Also, it seems evident that
certain familial factors contribute to the risk of developing PTSD in children. For example,
there is a strong correlation between parental PTSD and the likelihood of PTSD in offspring
(Yehuda, Halligan, & Bierer, 2001).
Specific phobia.
Specific phobia refers to a pathological fear of specific objects or situations that are
unrelated to social phobia or panic disorder (Albano et al., 2003, pp. 289-290). The DSM-IV
lists four distinct subtypes of specific phobia: blood-injection-injury type (e.g. seeing blood),
animal type (e.g. spiders), natural environmental type (e.g. heights), and situational type (e.g.
closed spaces) (American Psychiatric Association, 2000). In childhood specific phobia,
children’s anxiety symptoms are present for at least six months, and their phobic reactions
are expressed as tantrums, crying, freezing, and clinging (Muris, Schmidt, & Merckelbach,
1999). Specific phobias in children are as common as 5% (lifetime prevalence), making
them the most prevalent type of anxiety disorders in children (Costello & Angold, 1995, pp.
115).
Panic disorder (PD).
It is highly controversial whether panic attacks or panic disorder (PD) exist in
children (Nelles & Barlow, 1988). One study used retrospective reports of adults diagnosed
with panic disorder, and found a few cases of childhood PD (Klein, Mannuzza, Chapman, &
Fyer, 1992). However, Abelson and Alessi (1992) questioned whether retrospectively
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reviewed psychiatric status should be regarded as valid evidence for childhood PD (Abelson
& Alessi, 1992), and the controversy seems to continue in the literature.
PD becomes more common during adolescence. According to a longitudinal
epidemiologic study of psychiatric disorders within a representative sample of children and
adolescents (Costello, Mustillo, Erkanli, Keeler, & Angold, 2003), prevalence of PD begins
to increase at a moderate rate during adolescence and the disorder eventually becomes one of
the most prevalent anxiety problems by middle adolescence.
Changes in Classification and Diagnostic Criteria for Childhood Anxiety Disorders in
DSM-5
According to recent revisions in DSM-5 (American Psychiatric Association, 2012),
one of the major changes in the classification of anxiety disorders is that OCD has been
removed from the anxiety disorders category because the key feature of OCD is not often
anxiety but rather the repertoire of intrusive obsessions and compulsive rituals (Stein et al.,
2010). Alternatively, it is unknown to what extent anxiety is linked to obsessions and
compulsions, and some researchers therefore argue that OCD should be included in a new
category of OC-spectrum disorders or obsessive-compulsive-related disorders (OCRD),
consistent with the classification system of the International Classification of Mental
Disorders (ICD) (Hollander, Kim, & Zohar, 2007). It is expected that the new specification
may allow clinicians to make more targeted diagnoses and screening.
There are also other minor changes within the category of anxiety disorders in DSM-
5. First, the age of onset requirement has been dropped for the diagnosis of SAD,
recognizing that SAD may occur in adulthood (American Psychiatric Association, 2013) and
making the disorder no longer specific to childhood. In fact, an epidemiologic study (Shear,
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Jin, Ruscio, Walters, & Kessler, 2006) showed that SAD in adults is very common condition,
and that the majority of them have their first onsets in adulthood. Second, the ‘generalized’
specifier for social anxiety disorder (or SP) has disappeared, whereas the ‘performance only’
specifier has remained (American Psychiatric Association, 2013). Third selective mutism
has been included in the anxiety disorders category because “a large majority of children
with selective mutism are anxious” (American Psychiatric Association, 2013).
Scrutiny is mandated in the future for the effects of revised diagnostic criteria of
GAD in DSM-5. For example, the test-retest reliability (i.e. extent to which clinicians agree
on the same diagnosis) of the GAD diagnosis in DSM-5 is in the questionable range. This
reliability has not improved from the field trial results based on the DSM-IV criteria for
GAD (Regier et al., 2013).
Consequences of Childhood Anxiety Disorders
Anxiety disorders of childhood can cause various debilitating social and academic
problems for affected children and their families (Donovan & Spence, 2000). Evidence
shows that children with anxiety disorders have difficulty with social adjustment (Wood,
2006), peer relationships (Ginsberg, La Greca, & Silverman, 1998), academic performance
(Van Ameringen, Mancini, & Farvolden, 2003; Wood, 2006), and school attendance (i.e.
school refusal) (Atkinson, Quarrington, Cyr, & Atkinson, 1989; Last & Strauss, 1990).
These mental disorders of childhood often persist into later life, resulting in adult
diagnoses of anxiety disorder (Last, Philips, & Statfield, 1987; Shear et al., 2006). The
persistent pathological symptoms of anxiety disorders in adolescence or adulthood
significantly predict a range of social and psychological/psychiatric long-term complications,
including comorbid depression (Kovacs, Gatsonis, Paulauskas, & Richards, 1989),
15
vocational impairment (Koran, 2000), marital problems (McLeod, 1994), and substance
abuse (Kushner, Sher, & Beitman, 1990; Woodward & Fergusson, 2001).
Given the high prevalence, a significantly increased risk for comorbid psychiatric
disorders or conditions, and their emergence as a significant public health concern, early
intervention for anxiety disorders in children is essential.
Evidence-based Treatments for Childhood Anxiety Disorders
Cognitive behavioral therapy (CBT) and serotonin-specific medication are the
evidence- based treatment options for anxiety disorders in children. In terms of clinical
outcomes, a combination of CBT with medication therapy is significantly superior to CBT or
medication alone; however, each type of monotherapy is significantly more effective than
placebo (Walkup et al., 2008). CBT is equally effective as medication therapy for reducing
the anxiety symptoms, but generally causes significantly fewer adverse side effects than
medication therapy in clinically anxious school-age children (Walkup et al., 2008).
Consequently, many clinicians prefer CBT to medication as the first-line treatment in
children with anxiety disorders.
What is cognitive behavioural therapy?.
CBT is an evidence-informed psychotherapeutic approach that is used to treat
symptoms of a range of mental health disorders by reducing dysfunctional emotions and
behaviour through modifying cognitive patterns and contents (Sheldon, 1995, pp. 3). The
primary goals of CBT for anxiety disorders in children are suppression and management of
anxiety symptoms. However, recent clinical applications have broadened, emphasizing the
need of improving their social and emotional skills (Mash, 2006, pp. 12).
16
The systematic procedures implicated in CBT integrate two distinct models of
psychological/psychiatric disorders: the cognitive model and the behavioural model. These
models are based on the shared assumption that prior learning may cause maladaptive
consequences, and that intervention reduces dysfunctional emotions and behaviour by
reversing the prior learning (Brewin, 1996). The cognitive model assumes that we react to
life events via a combination of cognitive, emotional, motivational, and behavioural
responses (Brewin, 1996; Corsini & Wedding, 2000, pp. 276), and a cognitive therapist
would evaluate an individual’s irrational thinking patterns of causal attribution and treat them
as the main target of treatment (Beck, 1976). On the other hand, behavioural modification
focuses on extinguishing an undesirable behaviour by replacing with a desirable behaviour
through contingency learning (Brewin, 1996), visualized or real exposure to anxiety-
generating objects or situations (i.e. gradual desensitization), and relaxation training (Suveg,
Kendall, Comer, & Robin, 2006).
Cognitive behavioural therapy for childhood anxiety disorders and its efficacy.
CBT is effective in the treatment of all types of anxiety disorders in adults (Hoffman
& Smits, 2008). Although CBT is also effective for anxiety disorders in children aged 6
years and older when compared with wait-list controls, reviews of CBT for specific anxiety
disorders in children (e.g. SAD, SP) are absent in the literature (Cartwright-Hatton, Roberts,
Chitsabesan, Fothergill, & Harrington, 2004). Most trials grouped children with specific
anxiety disorders into a unitary anxiety group due to high comorbidity, without assessing the
relative effect of CBT on each type of anxiety disorders. Such specification in research,
however, may help optimize clinical outcomes of CBT for anxious children, as evident in the
17
treatment of specific anxiety disorders in adults that benefit from different approaches
(Cartwright-Hatton et al., 2004).
Kendall’s ‘Coping Cat’ (2006) is unquestionably among the most-widely-used,
evidence-based CBT protocols for treating anxiety disorders of childhood, especially for
SAD, GAD or SP (Macklem, 2011, pp. 34). Some strategies applied in Coping Cat, however,
can also be applied in the treatment of childhood PTSD, OCD, and specific phobia (Kendall,
Furr, & Podell, 2003, pp. 45). This manualized CBT program was first developed at the
Child and Adolescent Anxiety Disorders Clinic at Temple University (Philadelphia, USA).
The program requires the therapist to follow the therapist’s treatment manual (Kendall &
Hedtke, 2006a) and child to use his or her workbook during treatment (Kendall & Hedtke,
2006b). The Coping Cat protocol has been adapted internationally and modified for
populations in different countries: Coping Bear in Canada (Scapillato & Mendlowitz, 1993)
and Coping Koala in Australia (Barrett, Dadds, & Rapee, 1991).
The main goal of the Coping Cat CBT is to help children with anxiety disorders
recognize their anxiety-related physiological, cognitive, and behavioural symptoms in order
to effectively apply coping strategies in anxiety-generating situations (Velting et al., 2004;
Wood, 2006). This protocol is composed of sixteen sessions in which the first eight sessions
are devoted to psychoeducation (e.g. learning how to recognize cues for their anxiety, cues
for feelings of one’s own or others, coping skills), and the second eight sessions focus on
behavioural desensitization and modification (e.g. facing their fears in a graded hierarchy)
(Beidas, Benjamin, Puleo, Edmunds, & Kendall, 2010). During the psychoeducation period,
emotion-related concepts are addressed to some extent with more emphasis on emotion
18
regulation than emotion understanding. However, the largest focus of this traditional CBT is
on anxiety symptoms (Suveg, et al., 2006).
In the first randomized controlled trial (RCT) by the developer of Coping Cat, the
anxiety symptoms were markedly reduced at post-treatment in about two thirds of anxious
children with primary diagnoses of SAD, GAD, and SP; however, the remaining one third
still met the full criteria for anxiety disorders following the treatment (Kendall, 1994). The
second RCT also replicated the initial findings of Kendall (1994), and nearly half of treated
children with anxiety disorders no longer met the diagnostic criteria for any anxiety disorder
at post-treatment (Kendall et al., 1997). Many further RCT’s of Coping Cat or programs
very similar to it have been done internationally with similar results. Finally, a recent meta-
analysis on the efficacy of CBT on anxiety disorders in children and adolescents strongly
supported the effectiveness of anxiety-focused CBT and suggested that its effects could be
maintained for up to two years (Ishikawa, Okajima, Matsuoka, & Sakano, 2007).
Despite the evidence for short-term and long-term efficacy of CBT for children with
anxiety disorders, at least one third of treated children remain unresponsive to CBT, thereby
categorizing the treatment as a “probably efficacious” (Silverman, Pina, & Viswesvaran,
2008). Given this clinical limitation of anxiety-focused CBT, researchers must further
examine potential areas of difficulty beyond cognitive or behavioral domains in children with
anxiety disorders. One promising area of research is emotion.
Emotion-focused cognitive behavioural therapy.
There has been growing emphasis in CBT on assessing emotion-related difficulties
that children with anxiety disorders may experience, especially in those unresponsive to
traditional CBT. One example of such an effort is emotion-focused CBT (ECBT), which
19
closely follows the standard procedures of traditional anxiety-focused CBT. Although ECBT
is consistent with anxiety-focused CBT, it places equal weight on ameliorating emotional
deficits and anxiety symptoms (Jablonka, Sarubbi, Rapp, & Albano, 2012, pp. 546; Suveg et
al., 2006). Specifically, whereas the traditional anxiety-focused CBT spends only 1-2
session(s) on emotion recognition or understanding, ECBT integrates the same emotional
content throughout the entire eight sessions of psychoeducation (Suveg et al., 2006). In each
session of ECBT, both clinician and child work as a team to identify emotion(s) that the child
has difficulty regulating and understanding (Suveg et al., 2006). However, the emotion
understanding component in ECBT focuses on understanding or recognizing one’s own
emotional experiences, with less emphasis on others’ emotional states (Beidas et al., 2010;
Suveg, Sood, Comer, & Kendall, 2009; Rynn, Vidair, & Blackford, 2012, pp. 546).
Emotion Understanding
Emotion understanding refers to the “conscious knowledge about emotion” and
related processes (Southam-Gerow & Kendall, 2002, pp. 200; Thompson, 1990). In
research, the construct of emotion understanding comprises emotion recognition and other
emotional knowledge (e.g. causes of emotion, multiple emotions, emotion display or hiding,
knowledge about emotion regulation) (Southam-Gerow & Kendall, 2002). Emotion
understanding facilitates a child’s social functioning, (Hubbard & Coie, 1994), and
impairment in this conscious knowledge is associated with some types of psychopathologies
of childhood. For example, impaired emotion understanding is reported in school-age
children with attention-deficit hyperactivity disorder (ADHD) (Da Fonseca, Seguier, Santos,
Poinso, & Deruelle, 2009).
20
Research on emotion understanding in children with anxiety disorders is very scant in
the literature. Only one study by Southam-Gerow and Kendall (2000) examined four distinct
facets of the emotion understanding construct in anxious children: knowledge about
emotional cues, multiple or simultaneous emotions, changing or hiding emotions, and
knowledge about emotion regulation and coping. The study found that children with anxiety
disorders are less able to hide or change their emotions than non-anxious children; however,
the study did not assess the children’s ability to recognize emotions, although emotion
recognition is another crucial element of emotion understanding.
Emotion Recognition
Emotion recognition refers to the perceptual and cognitive capacity to identify others’
or one’s own emotional states through facial, postural, and contextual cues (Buitelaar, Van
der Wees, Swaab-Barnesveld, & Van der Gaag, 1999). The ability to recognize others’
emotions may manifest as early as in newborns and infants, albeit in immature form, and
infants begin to heed facial expressions for appraisal of emotions (Field, Woodson,
Greenberg, & Cohen, 1983). According to the theory of natural selection by Darwin (1898),
this biological predisposition in humans to pay attention to facial expressions and to correctly
discriminate emotions may have been a favoured trait for survival (Fridlund, 1997, pp. 109-
111). More specifically, accurate recognition of others’ emotional states allows receivers to
appropriately change their behaviour based on the sender’s emotional expressions (e.g.
acting submissively after seeing an angry face), and such adaptive behaviour may facilitate
cooperation and prevent aggression and energy expenditure (Elfenbein, March, & Ambady,
2002, pp. 38-39). Furthermore, proficiency in emotion recognition may allow individuals to
21
effectively manage their emotional states (e.g. hiding their feelings or deceiving others) in
the presence of others (Ekman, 1973).
There is another theory relating to emotion recognition and its potential importance
for survival, the ‘subordination hypothesis’ (Henley, 1973). According to this hypothesis,
women are generally more accurate than men in emotion recognition based on the
historically lower social status of women relative to men. This subordinate or oppressed
status made emotion recognition an important skill for women’s survival. However, some
researchers have opposed this view with empirical evidence that men can recognize certain
emotions, such as anger, more accurately than women (Elfenbein et al., 2002; Mandal &
Palchoudhury, 1985; Wagner, MacDonald, & Manstead, 1986).
Neural mechanisms of emotion recognition.
In terms of neuroanatomical correlates of emotion recognition, the process takes
place predominantly in the right hemisphere in most people when judging negative or
positive emotions (DeKosky, Heilman, Bowers, & Valenstein, 1990; Ley & Bryden, 1979).
However, this tendency seems less apparent when judging neutral or mild emotions (Ley &
Bryden, 1979). Further, some lesion studies (Blonder, Bowers, & Heilman, 1991) also
provide evidence for the right hemisphere playing a major role in emotion recognition,
especially when appraising emotions through facial and bodily expressions. On the other
hand, some variations seem to exist across studies in locating discrete sectors for processing
emotions. For example, one study (Adolphs, Damasio, Tranel, & Damasio, 1996) found that
the right inferior parietal cortex and mesial anterior infracalcarine cortex are the main
cortical systems for the processes involved in emotion recognition, whereas other studies
22
have located this function in the right inferior frontal cortex (Nakamura et al., 2000) or
exclusively in the right temporoparietal cortex (Bowers, Bauer, Coslett, & Heilman, 1985).
There is converging evidence, however, that such differential activation of the
discrete cortical areas may reflect emotion-specific processes during emotion recognition
(Adolphs et al., 1996). For example, although perceiving some negative basic emotions
(anger, disgust, and fear) all equally activates Brodmann area 47 in the left inferior-frontal
cortex, ‘anger’ seems to distinctively activate right gyrus cinguli, whereas ‘disgust’ and ‘fear’
may predominantly activate right putamen and amygdala, respectively (Adolphs et al., 1996).
Following this perceptual processing, amygdala and orbitofrontal cortices communicate with
other parts of the neocortex and hippocampal formation in order to retrieve emotional
knowledge. Then, the conscious recognition of the emotional states of others ensues
(Adolphs, 2002).
Social correlates and psychopathologies.
The ability to correctly recognize others’ emotional states is an important emotional
skill in social communication and interpersonal relationships. For example, emotion
recognition is significantly associated with children’s social competence (Mueser et al.,
1996), which helps children to adapt successfully in various social settings (Semrud-
Clikeman, 2007). Further, emotion recognition is one of the most reliably validated elements
of emotional intelligence (Elfenbein et al., 2002, pp. 45), which in turn predicts leadership
competencies (George, 2000) as well as satisfaction with interpersonal relationships (Lopes,
Salovey, & Straus, 2003). By the same logic, however, any deficit in emotion recognition
may presage social difficulties in everyday life. In fact, impairment in emotion recognition
23
seems to be significantly related to various types of psychopathologies (Collin, Bindra, Raju,
Gillberg, & Minnis, 2013) that cause social and behavioural problems in affected individuals
Impaired ability to recognize others’ emotional states has been reported in adults and
children suffering from a wide range of mental health disorders. For example, a deficit in
this ability is seen in adults with alexithymia (Lane, Sechrest, Reidel, Weldon, Kaszniak, &
Schwartz, 1996), dementia (Keane, Calder, Hodges, & Young, 2002), bipolar disorder (Getz,
Shear, & Strakowski, 2003), depression (Demenescu, Kortekaas, Den Boer, & Aleman,
2010), eating disorders (Kucharska-Pietura, Nikolaou, Masiak, & Treasure, 2003), mania
(Lembke & Ketter, 2002), panic disorder (Kessler, Roth, von Wietersheim, Deighton, &
Traue, 2006), and schizophrenia (Johnston, Stojanov, Devir, & Schall, 2005; Kohler et al,
2003; Mandal, Jain, Haque-Nizamie, Weiss, & Schneider, 1999; Namiki et al., 2007; Sachs,
Steger-Wuchse, Kryspin-Exner, Gur, & Katsching, 2004). Impaired emotion recognition has
also been found in children and adolescents with autism spectrum disorders (Kuusikko et al.,
2009), ADHD (Singh, Ellis, Winton, Singh, Leung, & Oswald, 1998), bipolar disorder
(McClure, Pope, Hoberman, Pine, & Leibenluft, 2003), and abuse and neglect (Camras,
Grow, & Ribordy, 1983; Pollak, Cicchetti, Hornung, & Reed, 2000).
Despite the strong evidence that children with anxiety disorders have a broad range of
social deficits (e.g. social shyness/withdrawal, inappropriate social skills, social
maladjustment) (Strauss, Lease, Kazdin, Dulcan, & Last, 1989), current treatments, including
both CBT and ECBT, for anxiety disorders of childhood are mostly focused on the child’s
ability to recognize his/her own emotions. They do not carefully address and treat the child’s
potential difficulty in recognizing others’ emotions. This is unfortunate because a deficit in
decoding others’ emotional information is an important correlate of interpersonal problems
24
(Kornreich et al., 2002), and such a deficit, if it exists, could potentially contribute to
exacerbation of anxiety symptoms during social interactions in children with anxiety
disorders.
Previous findings on emotion recognition in children with anxiety disorders.
Research on the relationship between anxiety disorders and emotion recognition in
children is scarce and inconsistent. One study by Easter et al. (2005) found that children
with anxiety disorders are more impaired in recognizing emotions than children without
anxiety disorder. In this study, researchers compared emotion recognition accuracy in a
relatively small number of child participants, 15 clinically anxious children and adolescents
and 11 non-anxious controls, using a set of posed pictures of facial expressions. By
convention, SAD, GAD, and SP types of anxiety disorders were considered as a single
experimental group in this study. This is commonly done because these types are highly
comorbid, but neglects the distinct clinical features associated with each of the anxiety types.
Furthermore, the effect of other highly comorbid conditions, such as conduct or oppositional
disorder, has not been examined in children with anxiety disorders.
With the same conventional research design and with the same set of facial emotion
cues, however, other studies produced results that are different from the finding by Easter et
al. (2005). For example, Manassis and Young (2000) found that children with anxiety
disorders can identify others’ facial emotions as accurately as children without anxiety
disorder. Only children with learning disabilities without anxiety were significantly impaired
in this study. Similarly, McClure et al. (2003) found that children and adolescents with
anxiety disorders could recognize others’ emotional states as accurately as their non-anxious
counterparts, but only children and adolescents with bipolar disorder showed a deficit in
25
emotion recognition. Lastly, Guyer et al. (2007) compared emotion recognition accuracy
among children and adolescents from various clinical groups, and reported that children with
anxiety disorders and children with depression as a group were not impaired in emotion
recognition. In this particular study, however, different pediatric mood and psychiatric
disorders were arbitrarily combined into single groups (e.g. combining the depression group
with the anxiety group. Thus, their findings may be limited in telling a clear story about
anxious children’s ability to recognize emotions. As illustrated above, there seems to be
little agreement on emotion recognition in children with anxiety disorders.
What Are the Factors Potentially Contributing to Inconsistent Results of Past Studies?
Measurement limitations in assessing emotion recognition in young children
with anxiety disorders.
Previous studies relied on static pictures of adult and child facial emotions for
assessing emotion recognition in children with anxiety disorders. However, there may be
some measurement issues in using these pictorial cues for measuring young children’s ability
to recognize emotions. First, the use of static photographs of facial expressions in traditional
lab settings may not adequately capture the emotional tenor in real social interactions
because emotional messages in real-life settings are often conveyed via a combination of
different types of emotional cues (e.g. facial cues, bodily cues, contextual/situational cues).
Contextual cues in particular are known to provide additional crucial information when
appraising others’ emotional states (Carroll & Russell, 1996). In other words, if past studies
had provided more emotional information, while making the lab settings more generalizable,
findings might have been more consistent.
26
Second, most of these instruments require verbal labelling of emotions based on
choices for each item, and responses are scored as dichotomous outcomes (i.e. right or
wrong). This dichotomous scoring method may cause statistical distortions, especially with
small sample sizes (Comrey, 1988), and can skew the interpretation of the results. Because
previous studies typically involved small sample sizes, this type of forced-choice format and
dichotomous scoring may have contributed to inconsistent past results.
Third, some of these instruments, such the Diagnostic Analysis of Nonverbal
Accuracy (DANVA), do not assess recognition accuracy for some basic and complex
emotions that young children may gradually learn to understand during the course of
development. Examples include some neutral emotions (relaxed, tired, exhausted) as well as
disgust, guilt, pride, and jealousy. Of particular interest, assessing the recognition of ‘disgust’
seems to have some clinical implications in CBT for certain types of anxiety disorders, such
as OCD (Rector, Daros, Bradbury, & Richter, 2012). Failing to provide a wider array of
complex and clinically relevant emotions may have hindered attainment of developmentally
meaningful and reliable outcome data, potentially leading to the mixed findings in this area
of research.
Lastly, emotional cues used in previous studies are motionless. During social
interactions, however, we perceive emotional expressions as dynamic and spontaneous
processes rather than perceiving them as static or motionless in time. Research suggests that
providing even a little dynamic information when presenting emotional cues allows more
accurate emotion recognition compared to using exclusively static information (Elfenbein &
Ambady, 2002; Wehrle, Kaiser, Schmidt, & Scherer, 2000). Although a very recent study
argues that young children may not have any significant advantage in emotion recognition
27
using dynamic expressions than using static expressions (Nelson & Russell, 2012), the
children in this study were limited to 4-7 years of age. Participants in past studies in this area
of research ranged from 7 to 17.
New research, therefore, needs to assess emotion recognition ability in children with
anxiety disorders using a developmentally sensitive tool that is well-validated in children of
varying ages, while addressing the above shortcomings of traditional experimental designs.
Other limitations of previous studies.
There are other limitations within the experimental design of previous studies. First,
sample sizes were generally small in previous studies. Only two previous studies are
exceptions to this observation; however, even these studies had some flaws in sampling. For
example, one study (Manassis & Young, 2000) had an anxiety group size similar to the
present study, but this study included preschool children with limited emotional vocabulary,
which may have affected results. The other one, by Guyer et al. (2007), had a much larger
total number of child and adolescent participants than the present study, involving various
clinical groups. However, there were only 14 children diagnosed with anxiety disorders, and
these children were mixed with children with depression to form a single experimental
group. Thus, results could not be clearly attributed to the presence of anxiety disorders.
Second, the effect of age on emotion recognition accuracy has not been examined in
children with anxiety disorders. However, age seems to have major impacts on emotion
recognition accuracy in children without anxiety disorder (Durand, Gallay, Seigneuric,
Robichon, & Baudouin, 2007; Feldman & Philippot, 1990). Careful control of this variable
in children with anxiety disorders might have yielded more meaningful and reliable outcome
data in past studies. For example, in some past studies, the age range was large despite a
28
small number of participants, so results may have been largely due to age effects. Therefore,
it may be important to scrutinize the effect of this developmental proxy in order to explain
the inconsistent results of past studies.
Third, diverse types of anxiety disorders of childhood were often combined into one
experimental group without assessing the relative impact of distinct primary diagnoses on
emotion recognition accuracy. This conventional design is often used because anxiety
disorder types are highly comorbid with each other. However, since each anxiety disorder
has unique clinical features and symptoms, this variability in characteristics may have
differentially influenced emotion recognition accuracy in child participants of past studies.
Therefore, it is imperative to examine the effect of anxiety type on emotion recognition in
children.
Lastly, previous studies neglected to carefully assess gender effects on emotion
recognition accuracy in children with anxiety disorders. It is well-established, however, that
gender effects on emotion recognition accuracy exist in non-anxious individuals. Women
are generally more accurate than men in recognizing emotions (Hall, 1978; Kirouac & Dore,
1985; Rotter & Rotter, 1988). Therefore, gender difference may have interacted with clinical
status, affecting the results of previous studies.
Merits of the Present Study and General Aims
In contrast to previous studies bearing the limitations above, the present study
examines a substantial sample of child participants who are old enough to verbally express a
range of simple and complex emotions.
Age effects on emotion recognition accuracy are also scrutinized and controlled for
when comparing anxiety diagnoses for accurate statistical analyses. The present research is
29
the first study to assess the effect of different types, comparing SAD, GAD, and SP types, on
children’s ability to recognize emotions. Furthermore, the present study aims to examine the
effect of gender on emotion recognition accuracy in children with and without anxiety
disorders.
Lastly, the present study utilizes Mood Assessment via Animated Characters
(MAAC; Manassis et al., 2009) a computerized instrument that displays an animated
character’s dynamic facial, bodily, and situational cues in order to measure sixteen specific
feelings in young children with anxiety disorders (Appendix A). There are some key
advantages of using MAAC over static facial photographs for young anxious children’s
ability to recognize emotions. First, MAAC was specifically designed for and validated in
young children with anxiety disorders. Second, MAAC displays dynamic and subtle types of
emotional cues (facial, bodily, and situational cues) using an animated character. These
animations may provide more accurate and clear emotional messages to the child for
appraisal than do still facial photographs removed from context. Third, MAAC’s displays of
a child-friendly animated character may help reduce participants’ anxiety during assessment,
minimizing the effect of confounding factors such as state anxiety. Fourth, the standard
scoring of responses on MAAC introduces three-level ordinal scores (incorrect, close to
correct, correct), allowing researchers to capture the developmental patterns or ‘growth’ of
emotion recognition ability in children with anxiety disorders, while mitigating the statistical
bias associated with dichotomous scoring. All of these advantages justify the use of MAAC
in the present study. More details on this instrument are explained in Chapter 2.
This thesis has four main aims: (a) to compare children with anxiety disorders and
children without anxiety disorder in their accuracy of recognizing the emotional states
30
expressed by an animated character on MAAC, (b) to examine age-related changes in
emotion recognition accuracy in children with anxiety disorders in comparison with that in
children without any anxiety disorder, (c) to determine how the most documented types of
anxiety disorders for anxious youth, namely SAD, GAD, and SP, are related to children’s
ability to recognize emotions, and (d) to assess any gender effect on emotion recognition
accuracy in children with anxiety disorders.
In addition to these main research questions, this thesis also reports secondary
analyses in a separate chapter (Chapter 4) that explores the effects of other potential
confounding factors (e.g. state anxiety, task completion time, depressive/anxiety symptoms)
on emotion recognition accuracy in children with and without anxiety disorders.
Hypotheses
Objective #1: to determine emotion recognition accuracy in children with and
without anxiety disorder (examined in Chapter 2).
For this objective, I predict that children with anxiety disorders will show lower
emotion recognition accuracy than non-anxious children. A recent meta-analysis
(Demenescu et al., 2010) on emotion recognition accuracy in children with anxiety disorders
has suggested that presence of anxiety disorders is not associated with children’s ability to
recognize various emotions. In this review, however, the sampling criterion was based on
the presence of any type of anxiety disorder, without specifying types of anxiety disorders.
Some included studies only contained children with SP, excluding children with SAD or
GAD as primary diagnosis. Such sampling design may not accurately represent the
proportion of different anxiety groups in a treatment setting or in the general population, and
fails to consider unique clinical features of each type of anxiety disorders. By studying a
31
diverse anxiety group in a treatment setting with careful attention to anxiety types,
differences between anxious and non-anxious children may be elucidated.
Objective #2: to determine the effect of age on emotion recognition accuracy in
children with and without anxiety disorder (examined in Chapter 2).
This second objective examines the effect of age on emotion recognition accuracy in
children with and without anxiety disorders. It is predicted that there will be a positive
correlation between age and overall emotion recognition accuracy in both children with and
without anxiety disorders because age represents a conventional proxy for development.
This prediction is based on the previous literature on the effect of age on emotion recognition
in children without anxiety disorder. In previous studies, age had a positive correlation with
emotion recognition accuracy in children and adolescents (Durand et al., 2007; Feldman &
Philippot, 1990). Furthermore, it is predicted that the rate of age-related improvement in
emotion recognition accuracy will be significantly lower in children with anxiety disorders
than in children without anxiety disorder because clinically anxious children tend to have
more problems in social and emotional domains than non-anxious children. However, this
particular prediction has not been previously tested, so the results will be preliminary.
Objective #3: to determine the effects of anxiety subtypes on emotion recognition
accuracy in children with anxiety disorders (examined in Chapter 2).
The third objective examines the effect of primary type of anxiety disorders on
emotion recognition accuracy in children. It is hypothesized that children with SP will be
significantly more impaired in recognizing others’ emotional states than children with other
types of anxiety disorder or children without anxiety disorder because the primary symptoms
of SP pertain to social features. However, there has been no study that evaluates the relative
32
effects of anxiety subtype on children’s emotion recognition accuracy, so the findings of this
objective will be preliminary.
Objective #4: to determine effect of gender on emotion recognition accuracy in
children with and without anxiety disorders (examined in Chapter 3).
For the fourth objective, examining the effect of gender on emotion recognition
accuracy in children with and without anxiety disorder, it is predicted that girls, regardless of
clinical status, will be significantly more accurate in recognizing emotions than boys. This
prediction is based on the finding of a systematic review on emotion recognition accuracy in
children and adolescents (McClure, 2000). This systematic review indicates that girls
without any clinical diagnosis are more accurate than boys without a clinical diagnosis in
recognizing basic emotions when facial emotion cues are presented (McClure, 2000).
As these gender differences exist in predicting emotion recognition accuracy in
children without anxiety disorder (McClure, 2000), the gender factor may also influence
emotion recognition accuracy in children with anxiety disorders. Therefore, it is predicted in
this study that girls with anxiety disorders will be more accurate than boys with anxiety
disorders in emotion recognition. Further, non-anxious girls will be more accurate in
emotion recognition than non-anxious boys. The present study is the first attempt to
comprehensively examine potential gender effects on emotion recognition accuracy in
children with anxiety disorders, so findings will be preliminary.
33
Chapter Two
Effects of Age and Subtype on Emotion Recognition in Children with Anxiety Disorders
Contents of this chapter have been published in Canadian Journal of Psychiatry:
Lee T. C., Dupuis, A., Jones, E., Guberman, C., Herbert, M., & Manassis, K. (2013). Effects
of age and subtype on emotional recognition in children with anxiety disorders: Implications
for cognitive-behavioural therapy. Canadian Journal of Psychiatry [In Press].
34
Abstract
This study examined whether an anxiety diagnosis, age, and subtype are associated
with emotion recognition accuracy in school-age children. Children with anxiety disorders
performed comparably with children without anxiety disorder in emotion identification. In
both groups, accuracy for disgust increased significantly each year of age. When age and
primary anxiety types were considered, however, children with separation anxiety disorder
(SAD) showed a deficit in overall emotion recognition, compared with children with other
subtypes or without anxiety disorder. Further regression analyses showed that children with
generalized anxiety disorder (GAD) presented significantly lower accuracy than control
children at a young age, but this deficit disappeared with increased age. Children with
anxiety disorders as a group may not appear to be impaired in emotion recognition. However,
when age and subtypes are considered, children with SAD and young children with GAD
appear to have difficulty, compared with children without anxiety disorder.
35
Introduction
Childhood anxiety disorders, especially separation anxiety disorder (SAD),
generalized anxiety disorder (GAD), and social phobia (SP), are most effectively treated with
a combination of medication and cognitive behavioural therapy (CBT) (Walkup et al., 2008).
CBT or medication (for example, sertraline) alone is more effective than placebo, however,
CBT tends to cause fewer side effects than medication (Walkup et al., 2008).
For some clinicians, therefore, CBT may be preferred as a first-line treatment for
anxiety disorders in children. In an evidence-based, manualized CBT for anxiety disorders
in children (such as, Coping Cat CBT; Kendall & Hedtke, 2006), clinicians include activities
that may help clinically anxious children facilitate emotion recognition (for example,
discussion of nonverbal cues for feelings or pictorial representations of feelings) (Kendall &
Hedtke, 2006). However, there is a lack of consistent empirical evidence for these children’s
deficits in recognizing others’ emotions (Easter et al., 2005; Manassis & Young, 2000;
McClure et al., 2003; Guyer et al., 2007; Melfsen & Florin, 2002; Simonian et al., 2001).
Rather, recent research has identified deficits in other emotional domains in children with
anxiety disorders, such as emotion regulation skills (Suveg & Zeman, 2004) and identifying
their own emotional states (Zeman, Shipman, & Suveg, 2002).
Therefore, a new emotion-focused CBT for children with anxiety disorders has been
developed. This program adds sessions to existing CBT protocols (Suveg et al., 2006)
focusing on improving emotion regulation and identifying one’s own emotional states. The
emphasis is less clearly placed on training children with anxiety disorders to identify others’
emotions. As the ability to recognize others’ emotions is crucial for social interactions
(Ciarrochi, Heaven, & Supavadeeprasit, 2008), and is postulated to help children with
36
anxiety disorders adaptively regulate their emotional experiences (Suveg et al., 2009),
scrutinizing the developmental trajectory of this conscious ability informs both anxiety- and
emotion-focused CBT for children with anxiety disorders.
Emotion Recognition in Children with Anxiety Disorders
It remains unclear whether children with anxiety disorders are impaired in
identifying the emotional states of others (Easter et al., 2005; Manassis & Young, 2000;
McClure et al., 2003; Guyer et al., 2007; Melfsen & Florin, 2002; Simonian et al., 2001).
Findings for children with SP are particularly inconsistent (Melfsen & Florin, 2002;
Simonian et al., 2001), and emotion recognition accuracy in children with SAD or GAD
(commonly treated with CBT) has not been examined to date.
Conflicting results may relate to study limitations. First, previous studies generally
had small sample sizes. Only one study (Manassis & Young, 2000) had an anxiety group
size comparable to that of the present study, but this study contained few control subjects
without anxiety disorders and included preschool children whose emotional vocabulary is
generally limited (Aldridge & Wood, 1997). Another study (Guyer et al., 2007) included a
much larger total number of participants aged between 7 and 18 years, but there were only 14
children with anxiety disorders, and they were mixed with children with depression into a
single experimental group. Second, there was a lack of well-validated, developmentally
sensitive tools to measure the ability to identify both simple and complex emotions in young
children with anxiety disorders. Past research relied on facial pictures, which have not been
well-validated for use with children younger than 8 years. Also, greyscale facial pictures
may be unappealing to children. Further, these stimuli cannot provide some types of
emotional cues that children often use. For example, preschool children with anxiety
37
disorders can use both facial and bodily cues for identifying emotions (Nelson & Russell,
2011), and with increased age, school-age children rely more on situational cues than facial
cues (Hoffner & Badzinski, 1989). Third, age effects on emotion recognition ability have
not been examined in children with anxiety disorders, although age significantly predicts the
ability to recognize emotions in children without anxiety disorders (Durand et al., 2007;
Feldman & Philippot, 1990). The effect of this developmental proxy may explain the
inconsistent results of past studies. Finally, past studies have lumped diverse anxiety
disorders into one proband group without assessing the relative impact of distinct anxiety
types on emotion recognition.
By contrast, our study examines a large sample of children old enough to express a
range of feelings using a developmentally sensitive tool that displays facial, bodily, and
situational cues. We pursued three main objectives: to compare the accuracy in identifying
others’ emotions in children with and without anxiety disorders, to examine age effects on
the emotion recognition accuracy in children with anxiety disorders, and to determine how
the anxiety disorders commonly treated with CBT in youth with anxiety disorders (SAD,
GAD, and SP) are related to children’s emotion recognition accuracy.
38
Methods
Participants
A total of 130 participants between 6 and 11 years of age were initially recruited,
including 65 referred patients with anxiety from an outpatient anxiety clinic in the Hospital
for Sick Children in Toronto and 65 volunteer control participants via community
advertisement in the Toronto area. In terms of demographics, children in both case and
control groups were predominantly from well-educated Caucasian families. The institutional
review board (IRB) of the hospital reviewed the research protocols and approved this study.
Children were excluded from the sampling if they were: (a) taking psychoactive medication
(e.g. selective serotonin reuptake inhibitor) or receiving any type of psychological treatment
(e.g. CBT); (b) suffering from any psychosis or intellectual disability; or (c) presenting with
the primary diagnosis of a mood disorder or developmental disorder. All the included
participants and their parents completed informed assent and consent, respectively.
All participants completed a semi-structured diagnostic interview (Anxiety Disorders
Interview Schedule or ‘ADIS’) (Silverman & Albano, 1996) as part of clinical assessment,
administered by trained psychiatrists with at least three years of experience using this
instrument. After this screening process, the sample was reduced to 122 participants because
six children from the control group had marked difficulties understanding instructions in
English, and two children from the anxiety group had only subclinical levels of anxiety.
The anxiety group of 63 children mainly had primary diagnoses of SAD (n = 13),
GAD (n = 35), and SP (n = 10), and a few children had specific phobia (n = 3), and post-
traumatic stress disorder (PTSD; n = 2). Among the 63 clinically anxious children in the
final sample, 38.1% had a secondary comorbid anxiety diagnosis, and 8.0% had a comorbid
39
non-anxiety diagnosis (e.g. attention-deficit hyperactivity disorder). The control group of 59
children in the final sample was screened for psychopathology and did not meet full criteria
for any non-anxiety DSM diagnosis (e.g. attention-deficit hyperactivity disorder, major
depressive disorder, oppositional defiant disorder, learning disability).
Instruments
Mood Assessment via Animated Characters (MAAC).
The Manassis Lab developed and validated a computer-based self-report instrument,
MAAC, which was specifically designed for young anxious children to elicit feeling states
associated with their psychopathology. MAAC displays a female teenage animated character
(“Teena”) expressing 16 different types of feeling states (relaxed, bored, exhausted,
surprised, sad, guilty, ashamed, angry, irritable, jealous, scared, nervous, disgusted, happy,
elated, and pleased) in animation for about three to four seconds (Manassis et al., 2009).
Using the child-friendly animated character, instead of plain text and scale, MAAC measures
a young child’s ability to recognize feelings of others (i.e. emotion of Teena) and self (by
comparing himself/herself to animated emotions expressed by Teena). The interface of
MAAC displays a tableau of sixteen still facial expressions of Teena’s simple and complex
emotions. If a child presses the emotion representation on the tablet screen with a PC stylus
pen, the selected emotion picture becomes a short animated cartoon. These animations show
Teena’s dynamic and engaging facial, bodily, and situational cues that capture the character’s
current emotional state. The child can play and/or replay the emotion-related clips in any
order of his or her preference.
State-trait Anxiety Inventory for Children (STAIC).
40
The STAIC contains two sets of 20 items using a 3-point scale that measures the
intensity of both long-term trait anxiety (i.e. how children usually feel or their general
tendency to be anxious) and transitory state anxiety (i.e. how children feel right now or a
temporary state of anxiety specific to situations) (Spielberger, Edwards, Lushene, Montuori,
& Platzak, 1973). Therefore, the STAIC state anxiety scores represent changes in transient
anxiety that children experience during psychological testing or treatment, whereas the
STAIC trait anxiety scores are used to identify children with “high levels of neurotic anxiety”
(Spielberger et al., 1973). The STAIC can be administered to children between the ages of 6
and 14. Participants in this study completed the STAIC at the time of MAAC administration
to determine if the children were feeling anxious during the testing, which could potentially
be a confounding variable in the relation between a diagnosis of anxiety disorder and
emotion recognition.
Procedures
A graduate student with a master’s degree introduced MAAC to a child based on
standardized protocols (“On this computer is a cartoon character named Teena who has a
number of different feelings.”). The child was first allowed to freely explore pictorial
representations of the animated character, selecting any picture(s) to view the emotion-
specific animations and gaining familiarity with MAAC (“Right now, she is just sort of
hanging out. If you press a button at the bottom of the screen, she will act out one of her
feelings”). Following the introduction, the child was asked to pick the emotion(s) that he/she
was feeling at the moment and rate intensity (“Pick the button where Teena seems to feel the
way you’re feeling right now. How can you tell? If 5 checkmarks is a perfect match between
how you feel right now and how Teena feels and “X” means you don’t feel that way at all
41
right now, show how much you feel like Teena right now on the scale”). Then, the graduate
student and child visited each animated emotion together in order from top to bottom, left to
right, asking the child to identify the emotional state of Teena (“Tell me how Teena is
feeling”). The same instruction was repeated until all sixteen emotions on MAAC were
viewed (“Let’s have a look at Teena’s other feelings.”), selecting all the buttons not
previously selected. All verbal responses of the child were tape-recorded for scoring of
his/her emotion identification accuracy.
For scoring, each response was converted to a numerical score based on how
accurately the child identified the emotion: 0 (incorrect), 1 (close but not exactly correct),
and 2 (correct). The child’s overall or general ability to identify the emotional states of
others was defined by a total accuracy score, obtained by adding the individual scores across
the sixteen emotions presented on MAAC. Therefore, the maximum total score is 32 points
(2 points multiplied by 16 items). To establish inter-rater reliability, two graduate students
blindly and independently scored the responses endorsed by participants, and the Kappa
statistic was computed.
Statistical Analyses
For the first main analysis, comparing the emotion recognition accuracy between
clinically anxious children and non-anxious children, both a Wilcoxon Rank Sum test and an
independent t-test were used to compare total accuracy scores between the two groups. The
parametric t-test was conducted because the residual distributions of the total accuracy scores
were normally distributed for both anxiety and control groups (the findings on the normality
assumption will be reported in the results section). However, the dependent variable (total
accuracy score) was defined as the sum of sixteen ordinal scores in this study, and such
42
restricted ordinal score range could also justify the use of the non-parametric rank sum
comparison. Therefore, the present study reported both parametric and non-parametric
results. Further, ordinal regression analyses were conducted to compare these two groups’
ability to identify each of sixteen specific emotions.
For the second main analysis, examining age effects on emotion recognition, linear
regression analyses were conducted in the anxiety and control groups for modeling the
relationship between age (predictor) and total accuracy score (outcome). Then, ANCOVA
was conducted for comparing the slopes and intercepts of these two regression lines in order
to determine if the general ability to identify emotions in anxious children differentially
correlates with age in comparison with that of non-anxious children. Additionally, ordinal
logistic regression analyses were conducted to determine if clinically anxious children’s and
non-anxious children’s ability to identify specific types of emotions differentially changes
with age.
For the third main analysis, comparing the emotion recognition accuracy as a
function of the primary anxiety diagnosis, children with specific phobia or PTSD were
dropped because these samples were too small for this analysis. An ANCOVA was
conducted to contrast differences in mean total accuracy scores among the anxiety groups of
SAD, GAD, and SP, while age was controlled for. Then, Bonferroni-adjusted pairwise
comparisons were conducted with the two-tailed alpha level set at 0.05 for statistical
significance. Furthermore, linear regression analyses were used to model the association
between age and total accuracy score in each primary anxiety diagnosis group to examine the
developmental trajectory of the general ability to recognize others’ emotions in these groups.
Using ANCOVA, the slopes and intercepts of these regression lines were compared with
43
those of the non-anxious control group by checking for the presence of any interaction
between the lines.
44
Results
Mean ages of the anxiety group (M = 8.7, SD = 1.2) and non-anxious control group
(M = 8.3, SD = 1.4) were similar, t (120) = - 1.60, p = 0.11. A one-way ANOVA indicated
that SAD (M = 8.5, SD = 1.3), GAD (M = 8.8, SD = 1.1), SP (M = 8.4, SD = 1.3), and
control groups were also comparable in mean age, F (3, 113) = 1.18, p = 0.32. The normality
assumption was tested for age and total accuracy score variables and found that the data of
these variables were normally distributed within each comparison group. The state anxiety
scores did not differ among the SAD, GAD, SP, and control groups, F (3, 86) = 0.79, p =
0.50.
Objective #1: Emotion Recognition Accuracy in Children with and without Anxiety
Disorder
Total accuracy score in anxious children was not significantly different from non-
anxious children when a t-test was conducted, t (120) = 0.73, p = 0.68. The restricted,
ordinal total accuracy score range could also justify the use of the nonparametric test.
However, the result was unchanged when a non-parametric test of a Wilcoxon Rank Sum test
was conducted, z = - 0.72, p = 0.47, as the mean of the ranks of total accuracy score in the
anxiety group was 59.27 and that of the control group was 63.88.
Ordinal logistic regression analyses failed to reveal any significant difference in
recognition accuracy for any specific types of emotions on MAAC between children with
anxiety disorders and children without anxiety disorder (Table 2). It is noteworthy that
children with anxiety disorders as a group performed exceptionally well on correctly
identifying certain basic emotions, such as happy, angry, and scared
45
Objective #2: Effect of Age on Emotion Recognition Accuracy in Children with and
without Anxiety Disorder
Age was positively correlated with total accuracy score received on MAAC (i.e. age
was correlated with the general ability to identify emotions) for both anxious children (r =
0.52, p = 0.001) and non-anxious children (r = 0.36, p = 0.005). Linear regression analyses
were conducted to model the linear relationship between age (predictor) for total accuracy
score (outcome) in both anxiety and control groups: (1) Predicted total accuracy score in the
anxiety group = 7.79 + 1.49 Age (years); (2) Predicted total accuracy score in the control
group = 14.35 + 0.81 Age (years). An ANCOVA indicated that these slopes were similar,
Delta B1 (ANX-CONT) = 0.68, 95% CI -0.13 to 1.52, p = 0.10, and their intercepts were also
comparable, Delta B0 (ANX-CONT), = -6.56, 95% CI -13.87 to 0.39, p = 0.06.
Ordinal logistic regression analyses revealed that non-anxious children‘s recognition
accuracy for ‘disgusted’, ‘jealous’, and ‘proud’ emotions increased significantly each year
(Table 3). Similarly, clinically anxious children’s recognition for ‘disgusted’ and ‘jealous’
emotions also increased significantly during this period; however, their identification
accuracy for ‘tired’ and ‘nervous’ emotions was also found to increase significantly.
Objective #3: Effects of Anxiety Subtypes on Emotion Recognition Accuracy in
Children with Anxiety Disorders
A Kruskal-Wallis test was initially conducted to examine the effect of subtypes on
anxious children’s emotion recognition accuracy, due to the small SP group size with a bi-
modal data distribution. This non-parametric test did not take into account age effect on
emotion recognition, and the results revealed that there was a significant group difference in
emotion recognition accuracy, X2 (3) = 9.49, p = 0.02. A post-hoc test using a series of
46
Mann-Whitney tests with Bonferroni adjustment and the alpha level set at 0.008 (0.05 / 6)
showed significant differences in total accuracy score received on MAAC between the SAD
and control groups (U = 191.50, Z = - 2.83, p = 0.005, r = 0.33) and between the SAD and
GAD groups (U = 104.50, Z = - 2.87, p = 0.004, r = 0.41).
A parametric test of ANCOVA was also conducted to compare the mean total
accuracy scores across different anxiety disorder groups, while controlling for possible age
effects. In this type of analysis, the assumption of homogeneity of regression slopes must be
met as it relates to how the covariate and the dependent variable are associated with each
other for every comparison group (Field, Miles, & Field, 2012, pp. 466). If this assumption
is violated, the results and conclusions will be misleading.
The assumption of homogeneity of regression slopes was met for the ANCOVA, F (3,
109) = 2.28, p = 0.08. The result of ANCOVA indicated that group differences by primary
anxiety diagnosis (covarying for age) were significant, F (3, 112) = 4.47, p = 0.004, eta-
squared = 0.11 (Figure 1). Pairwise comparisons between SAD (M = 18.27, SD = 0.75) and
all other groups were significant with Bonferroni corrections (GAD [M = 21.05, SD = 0.46, p
= 0.01]; SP [M = 21.42, SD = 0.86, p = 0.04]; control [M = 21.28, SD = 0.35, p = 0.003]),
but those among GAD, SP, and control groups were not. However, interpreting this result
required caution because age was significantly correlated only with the total accuracy score
in the SAD (r = 0.60, p = 0.03) and GAD groups (r = 0.68, p < 0.001), but not in the SP
group (r = 0.20, p = 0.59).
Therefore, we repeated an ANCOVA without the SP group, while age was controlled
for. The ANCOVA for group differences by primary diagnosis was still significant, F (2,
103) = 7.06, p = 0.001, eta-squared = 0.12, but very close to violating the homogeneity of
47
regression slopes assumption, F (2, 101) = 2.90, p = 0.05. Bonferroni-corrected pairwise
comparisons showed that the SAD group was still significantly lower on total accuracy score
than the GAD (p = 0.001) and control groups (p = 0.006). However, the GAD and control
groups were not significantly different from each other (p > 0.99).
Linear regression equations of age predicting total accuracy score in both SAD and
GAD groups were: (1) Predicted total accuracy score in the SAD group = 6.64 + 1.36 Age
(years); (2) Predicted total accuracy score in the GAD group = 3.90 + 1.99 Age (years).
Both of these regression lines had an intercept lower than that for the control group, but only
one for the GAD group was statistically significant (SAD [Delta B0 (SAD-CONT) = -7.71, 95%
CI - 19.19 to - 3.77, p = 0.18; GAD [Delta B0 (GAD-CONT) = -10.45, 95% CI - 19.04 to - 1.87, p
= 0.02). The slope of the SAD group line was not significantly different from that for the
control group, Delta B1 (SAD-CONT) = 0.55, 95% CI - 0.79 to 1.89, p = 0.42, whereas the slope
of the GAD group line was significantly steeper than that for the control group, Delta B1 (GAD-
CONT) = 1.18, 95% CI 0.20 to 2.16, p = 0.02 (Figure 2).
To compare emotion recognition accuracy of specific emotions between the SAD
group and the control group, an ordinal regression analysis was performed for each of sixteen
specific emotions. However, the analyses did not detect any deficit in recognition of a
specific type of emotion (Table 2).
48
Discussion
The present study was the first to examine age effects on anxious children’s emotion
recognition and the first to examine how some of the most documented anxiety disorders for
anxious children, SAD and GAD, are related to the ability to recognize others’ emotions.
Children in our study ranged from 6 to 11 years, when children’s verbal skills are not
correlated with the ability to identify emotions (Steele, Steele, & Croft, 2008). With these
considerations, we revisited the question of whether anxiety diagnosis is associated with
children’s ability to recognize the emotional states of others, illuminating explanations for
contradictory findings in the past.
Emotion Recognition Accuracy in Children with and without Anxiety Disorder
Because the prevalence of specific anxiety disorders in children varies across
epidemiologic studies (Cartwright-Hatton et al., 2006), our anxiety group may not show the
same diagnostic distributions as children with anxiety disorders in the general population.
Initially, we placed different anxiety types into one proband group to replicate conventional
research designs that neglected to examine various types of primary diagnosis.
When children with and without anxiety disorders are compared with non-anxious
children on emotion recognition abilities, our results show that children with anxiety
disorders can identify the emotional states of others as accurately as children without anxiety
disorder. This finding is consistent with a recent meta-analysis of emotion recognition in
children with anxiety disorders (Demenescu et al., 2010) and with the findings of McClure et
al., (2003) Manassis and Young (2000), and Guyer et al. (2007). Moreover, we failed to
detect any difficulty in children with anxiety disorders in recognizing any specific type of
emotion compared with children without any anxiety disorder. Rather, children with anxiety
49
disorders seem proficient in recognizing basic emotions when various types of emotion-
related cues are available.
Effects of Age and Anxiety Subtypes on Emotion Recognition Accuracy
Our findings indicate that, as in children without anxiety disorder, the general ability
to recognize others’ emotions in children with anxiety disorders increases significantly with
age, and the rate of improvement is comparable with that of children without anxiety
disorder. In both children with and without anxiety disorders, recognition of ‘disgust’
improves significantly between 6 and 11 years of age. Furthermore, in both groups,
identification accuracy of some complex emotions increases significantly each year,
especially emotions conveyed via bodily or contextual cues (e.g. ‘jealous’, ‘pleased/proud’,
‘tired’ and ‘nervous’). On the other hand, the recognition of ‘nervous’ appears to improve
significantly each year during the elementary years in children with anxiety disorders,
whereas the recognition of ‘proud’ improves significantly each year in children without
anxiety disorders.
When age effects were controlled, children with SAD demonstrated a significantly
lower overall ability to recognize the emotional states of others, compared with children
without anxiety disorder and children with the primary diagnosis GAD or SP. Like children
with GAD or children without anxiety disorder, children with SAD demonstrated age-
dependent improvement in emotion recognition accuracy. On the other hand, children with
GAD also showed difficulty at a young age, but their ability to identify others’ emotions
improved with age at a faster rate to catch up with that of children without anxiety disorder
during school years.
Limitations and Clinical Implications
50
Our study has limitations. First, the present findings are limited to children ages 6
through 11 years. Second, our findings do not address whether children with anxiety
disorders have problems recognizing their own emotional states, but the scope of our
research is limited to recognizing others’ emotional states through a female animated
character. Third, including more participants with SAD or SP would have much improved
statistical confidence/power, especially regarding age effects on emotion recognition
accuracy in these subgroups. Fourth, we did not measure general intelligence or verbal skills
of our participants as a covariate. Fifth, children with anxiety disorders in our study were not
more state anxious than their non-anxious counterparts at the time of testing. Therefore, our
findings do not capture these children’s ability to recognize emotions during anxiety-
provoking situations (for example, social activities for children with SP). Sixth, there may
have been ceiling effects in the measure as participants generally made few errors on
recognizing basic emotions. Lastly, MAAC does not measure processing time for emotion
recognition.
Our findings suggest that augmenting emotion recognition skills may help children
with SAD and early school-age children with GAD, as they appear to have difficulty
identifying various emotions, compared with their non-anxious counterparts. However, the
treatment may be more effective if clinicians discuss various types of cues for both basic and
complex feelings, not limited to facial cues for basic emotions only, with these children.
Finally, our findings support the flexible use of anxiety-focused CBT, allowing for increased
emphasis on understanding emotions in children with anxiety disorders with deficits in social
or emotional understanding. However, such flexibility may be less crucial in children with
GAD, whose impaired emotion recognition seems transitory at a young age.
51
Future Directions
First, future directions include a comparison of emotion recognition deficits with
other clinical groups using a developmentally sensitive tool in school-age children with
SAD. Second, as the ability to identify others’ emotions in children with SP was not linearly
commensurate with age, this clinical subgroup needs to be re-examined with a larger sample
size of varying ages. Third, emotion recognition ability of children with anxiety disorders
needs to be measured during anxious states to determine if their recognition is distorted in
such situations, and in relation to gender. Lastly, longitudinal studies will be required to
confirm the developmental trajectory of emotion recognition ability in children with anxiety
disorders.
52
Tables
Table 1. Characteristics of the Anxiety Group and the Control Group
Anxiety (n=63)
N %
Primary Anxiety Diagnosis
SAD 13 20.6
GAD 35 55.6
SP 10 15.9
Specific Phobia 3 4.8
PTSD 2 3.2
Secondary Anxiety Diagnosis
None 34 54.0
SAD 3 4.8
GAD 13 20.6
Social Phobia 5 7.9
Specific Phobia 3 4.8
Secondary Non-anxiety Diagnosis
ADHD 1 1.6
ODD 1 1.6
LD 3 4.8
Boys 28 44.4
Age <8 19 30.2
Age – mean (SD) 8.7 1.2
Control (N=59)
N %
Boys 29 49.2
Age <8 28 47.5
Age – mean (SD) 8.3 1.4
53
Table 2. Ordinal Regression Analyses of Anxiety Diagnosis and Separation Anxiety Disorder Predicting Emotion Recognition
Accuracy in Comparison with the Control Group
Anxiety, Compared with Control Group SAD, Compared with Control Group
Emotion Odds Ratio (95% CI) P Odds Ratio (95% CI) P
Relaxed 1.0 (0.5, 2.0) >0.9 1.5 (0.5, 4.8) 0.5
Bored 1.2 (0.6, 2.5) 0.7 0.6 (0.2, 2.0) 0.4
Tired 0.7 (0.3, 1.4) 0.3 0.4 (0.1, 1.2) 0.1
Surprised 0.6 (0.2, 1.3) 0.2 0.3 (0.06, 1.9) 0.2
Sad 0.9 (0.4, 1.8) 0.7 0.3 (0.09, 1.0) 0.05
Guilty 0.9 (0.5, 1.9) 0.8 0.3 (0.06, 1.3) 0.1
Ashamed 0.7 (0.3, 1.5) 0.4 0.5 (0.1, 1.6) 0.2
Angry 1.5 (0.3, 6.9) 0.6 0.8 (0.09, 8.0) 0.9
Irritable 0.9 (0.5, 1.8) 0.8 0.4 (0.1, 1.2) 0.1
Jealous 1.2 (0.6, 2.3) 0.7 1.3 (0.3, 2.5) 0.7
Scared 1.0 (0.4, 2.5) 0.9 2.5 (0.3, 22.2) 0.4
Nervous 1.5 (0.8, 3.0) 0.2 1.1 (0.3, 2.9) 0.9
Disgusted 0.9 (0.4, 1.7) 0.7 0.4 (0.1, 1.3) 0.1
54
Table 2. Ordinal Regression Analyses of Anxiety Diagnosis and Separation Anxiety Disorder Predicting Emotion Recognition
Accuracy in Comparison with the Control Group (Continued)
Anxiety, Compared with Control Group SAD, Compared with Control Group
Emotion Odds Ratio (95% CI) P Odds Ratio (95% CI) P
Happy 1.6 (0.5, 4.9) 0.4 2.0 (0.2, 16.2) 0.5
Elated 1.1 (0.5, 2.1) 0.9 0.6 (0.2, 2.3) 0.5
Proud 1.1 (0.5, 2.5) 0.7 0.4 (0.09, 1.9) 0.3
55
Table 3. Ordinal Regression Analyses of Age Predicting Emotion Recognition Accuracy for Children with and without Anxiety
Disorder
Control Anxiety
Emotion Odds Ratio (95% CI) P Emotion Odds Ratio (95% CI) P
Disgusted 2.1 (1.3, 3.3) 0.002 Disgusted 2.6 (1.6, 4.3) <0.001
Jealous 1.8 (1.2, 2.7) 0.003 Tired 2.1 (1.3, 3.3) 0.003
Proud 2.0 (1.2, 3.3) 0.004 Nervous 1.7 (1.1, 2.7) 0.02
Jealous 1.7 (1.1, 2.7) 0.02
Bored 1.5 (1.0, 2.5) 0.05
Ashamed 1.4 (1.0, 2.2) 0.06 Surprised 1.7 (1.0, 3.0) 0.06
Relaxed 1.4 (1.0, 2.0) 0.09 Bored 1.5 (0.9, 2.4) 0.1
Happy 1.6 (0.9, 3.0) 0.1 Irritable 1.4 (0.9, 2.2) 0.1
Guilty 0.8 (0.5, 1.1) 0.1 Happy 1.6 (0.7, 3.3) 0.2
Nervous 1.3 (0.9, 1.8) 0.2 Sad 1.3 (0.8, 2.0) 0.3
Irritable 1.2 (0.8, 1.8) 0.3 Scared 0.7 (0.4, 1.3) 0.3
Angry 0.7 (0.3, 1.5) 0.3 Ashamed 1.3 (0.8, 2.0) 0.3
Surprised 1.2 (0.8, 1.8) 0.4 Guilty 0.8 (0.5, 1.2) 0.3
56
Table 3. Ordinal Regression Analyses of Age Predicting Emotion Recognition Accuracy for Children with and without Anxiety
Disorder (continued)
Control Anxiety
Emotion Odds Ratio (95% CI) P Emotion Odds Ratio (95% CI) P
Sad 0.9 (0.6, 1.3) 0.6 Relaxed 0.8 (0.5, 1.2) 0.4
Elated 1.1 (0.7, 1.6) 0.7 Angry 1.5 (0.5, 4.0) 0.5
Tired 0.9 (0.6, 1.3) 0.7 Proud 1.2 (0.7, 2.0) 0.5
Scared 1.0 (0.6, 1.6) 0.9 Elated 1.0 (0.7, 1.6) 0.8
57
57
Figures
Figure 1. Total Accuracy Score by Anxiety Types: SAD, GAD, SP, and Control Groups
- Significant difference among test groups, F(3,112)=4.47, p=0.004, eta-squared=0.11
58
58
Figure 2. Regression Lines for Age and Total Accuracy Score on MAAC in the SAD and GAD
Groups, Comparison with the Control Group
- Compared to the control group, the y-intercept of the SAD group was not significantly
lower (p = 0.18), and the slope was not significantly different (p = 0.4).
- Compared to the control group, the y-intercept of the GAD group was significantly lower
(p=0.02), and its slope was significantly steeper (p=0.02)
59
59
Chapter Three
Effect of Gender on Emotion Recognition Accuracy in Children with Anxiety Disorders
This chapter was prepared as a brief report for journal submission
60
60
Abstract
The present study examined the link between gender and emotion recognition accuracy in
school-age children with and without anxiety disorders. Gender failed to predict overall emotion
recognition accuracy. However, disgust recognition was significantly less accurate in clinically
anxious girls than in clinically anxious boys, and was also less accurate, albeit not significantly
so, than in age-matched non-anxious girls.
.
61
61
Introduction
The ability to accurately recognize emotions through nonverbal cues mediates children’s
social and academic outcomes (Izard et al., 2001). This ability may be associated with anxious
children’s social difficulties and hence requires scrutiny. There is a lack of theoretical model
that explains for gender differences in emotion recognition patterns. Nevertheless, in non-
anxious children, girls are significantly more accurate than boys in recognition of emotions via
facial cues (McClure, 2000), and this female advantage is also consistent across different
cultures (Elfenbein et al., 2002).
In children with anxiety disorders, gender differences have not been extensively
examined in relation to emotion recognition accuracy. To elucidate the nature of their emotional
difficulties, however, it may be important to characterize gender differences in emotion
recognition accuracy in this clinical population. More specifically, gender-specific patterns of
emotion recognition accuracy in anxious children may reveal a novel biobehavioral marker for
anxiety disorders of childhood. Therefore, we examined gender effects on emotion recognition
accuracy in clinically anxious children, using developmentally sensitive, dynamic displays of
emotions. Then, we compared the result with that for non-anxious, age-matched counterparts.
62
62
Methods
Data were obtained from a previous study by Lee et al. (2013), which included 122
school-aged children (57 boys and 65 girls) 6-11 years of age, consisting of 63 clinic-referred
children with an anxiety disorder at the Hospital for Sick Children in Toronto and 59 non-
anxious volunteers. Diagnostic interviews were conducted by experienced clinicians, using the
Anxiety Disorders Interview Schedule. Any child with ongoing treatments or with a presentation
of psychosis or intellectual disability was not included in this study. The anxiety group mainly
consisted of children with separation anxiety disorder (n=13), generalized anxiety disorder
(n=35), and social phobia (n=10), with a few participants with specific phobia (n=3) and post-
traumatic stress disorder (n=2). The control group did not contain any anxiety or non-anxiety
DSM diagnoses.
Emotion recognition accuracy was measured with Mood Assessment via Animated
Characters (MAAC), a computerized self-report instrument, specifically designed for anxious
children (Manassis et al., 2013). MAAC presents a child-friendly character expressing sixteen
types of emotions (relaxed, bored, tired, surprised, sad, guilty, ashamed, angry, irritable, jealous,
scared, nervous, disgusted, happy, elated, and proud) via facial, bodily, and contextual cues in
dynamic motion.
All children viewed each of sixteen emotion-specific animations, and were asked to
identify the character’s emotional state. The child’s response for each emotion was scored for
accuracy (0=incorrect, 1=close to correct, 2=correct), and individual scores were summed for the
total accuracy score. Inter-rater agreement on scoring was previously computed (Lee, Dupuis,
Jones, Guberman, Herbert, & Manassis, 2013), and was excellent (kappa=0.92, p < 0.001).
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Statistical Analysis
The total accuracy score was compared between anxious boys and anxious girls using an
independent t-test. Then, ordinal regression analyses were used to compare emotion recognition
accuracy between the gender groups on each of sixteen emotions. Using the same method,
accuracy was also compared between genders in non-anxious children and between anxious girls
and non-anxious girls. Further, we measured state anxiety (T-score on the State-Trait Anxiety
Inventory for Children) and depressive symptoms (T-score on the Children’s Depression
Inventory) to control for potential confounding factors.
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Results
Boys with Anxiety Disorders vs. Girls with Anxiety Disorders
Boys with anxiety disorders (n = 28, M = 8.83, SD = 0.97) and girls with anxiety
disorders (n = 35, M = 8.51, SD = 1.25) were matched for age, t (61) = 1.09, p = 0.28, state
anxiety (p = 0.67), and depressive symptoms (p = 0.06). The normality assumption was satisfied
for total accuracy score within both groups.
When an independent t-test was conducted, there was no significant difference between
boys with anxiety disorders (M = 21.46, SD = 2.50) and girls with anxiety disorders (M = 19.94,
SD = 3.54) in the overall recognition accuracy (i.e. total score), t (61) = 1.89, p = 0.06. Ordinal
regression analyses revealed that clinically anxious boys and clinically anxious girls were not
significantly different in recognition accuracy on most of the specific emotions (Table 1).
However, girls with anxiety disorders performed significantly worse than boys with anxiety
disorders on recognition of disgust (p = 0.03), boredom (p = 0.02), and surprise (p = 0.02).
Boys without Anxiety Disorder vs. Girls without Anxiety Disorder
Boys without anxiety disorder (n = 29, M = 8.25, SD = 1.36) and girls without anxiety
disorder (n = 30, M = 8.34, SD = 1.38) were comparable for mean age, t (57) = - 0.25, p = 0.80,
state anxiety (p = 0.59), and depressive symptoms (p = 0.53). The normality assumption was
satisfied within both non-anxiety groups.
Gender did not have any significant effect on the outcome of the overall emotion
recognition accuracy, t (57) = - 1.07, p = 0.29. The results of ordinal regression analyses
indicated that there was no significant gender effect on recognition accuracy for most specific
emotions; however, girls without anxiety disorder recognized the ‘relaxed/calm’ emotion more
accurately than boys without anxiety disorder (p = 0.02).
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Girls with Anxiety Disorders vs. Girls without Anxiety Disorder
Girls with anxiety disorders and girls without anxiety disorders were matched for age, t
(63) = - 0.55, p = 0.59, and state anxiety (p = 0.14), but depressive symptoms were significantly
higher in clinically anxious girls (p=0.006). However, depressive symptoms did not significantly
predict total accuracy score in clinically anxious girls (r = 0.09, p = 0.64) or non-anxious girls (r
= 0.21, p = 0.34). The result indicated that clinically anxious girls (M = 19.94, SD = 3.54) and
non-anxious girls (M = 21.08, SD = 3.02) did not differ in recognition accuracy for overall, t (63)
= 1.87, p = 0.07), and specific emotions (Table 1). Accuracy in disgust recognition between
groups did not differ significantly , but came close to significance level with ordinal regression
analysis (p = 0.06) in which misidentifying disgust as anger was given the score of one (i.e. close
to correct). The partial score for the response of anger for disgust is justified by the fact that
anger and disgust share the same emotional valence (negative) and that in the disgust animation
the character looks somewhat angry when she throws down her lunch bag after sticking out her
tongue. However, one may also argue that previous studies in this field consistently used a
dichotomous scoring method (correct vs. incorrect), and that the response of anger should not be
given a partial credit. Therefore, a 2x2 contingency table was also generated in which
misidentifying disgust as anger was not given a score, and in this analysis girls with anxiety
disorders showed significantly lower accuracy in recognition of disgust than girls with anxiety
disorders (p = 0.04). However, no significant difference was detected on all other specific
emotions with the 2x2 contingency table.
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Discussion
Although limited by modest sample size, our findings suggest that gender plays a
minimal role in overall emotion recognition accuracy in children with anxiety disorders. The
finding regarding children without anxiety disorder in this study is inconsistent with the result of
a meta-analysis by McClure (2002), and suggests that school-age girls are not more proficient
than boys in emotion recognition when a combination of various dynamic, non-verbal cues for
emotion are available. This inconsistency may suggest that non-anxious boys make effective use
of contextual cues to compensate their difficulty with facial emotion recognition compared with
girls. If so, the present results may be generalizable to real world social settings where various
non-verbal channels of expression and contextual cues are available to children.
Interestingly, girls with anxiety disorders in our study are particularly less accurate in
disgust recognition, often misidentifying disgust as anger. In children without anxiety disorder,
however, boys and girls can recognize disgust at a comparable level when dynamic facial, bodily,
and contextual cues are presented. Based on this evidence, inaccurate disgust recognition in girls
with anxiety disorder may be a characteristic of anxiety disorders of childhood. Impaired disgust
recognition has also been reported in individuals with certain types of OCD (Sprengelmeyer et
al., 1997; Rector et al., 2012) or with severe OCD (Parker, McNally, Nakayama, & Wilhelm,
2004). Thus, the present finding on disgust recognition may be implicated in identifying a shared
characteristic of anxiety disorders and OCD.
Due to sample size constraints, it was not possible to examine gender effects on emotion
recognition in children with each specific type of anxiety disorders. Because types of anxiety
disorders may have an effect on emotion recognition accuracy (Lee et al., 2013), future study of
this issue is indicated. Further, a deficit in disgust recognition in girls with anxiety disorders in
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comparison with girls without anxiety disorder was only apparent when one type of
scoring/analysis was used. Therefore, replication of our study is required. Including OCD
participants in future studies may clarify if deficit is a potential marker for childhood anxiety.
Lastly, use of vocal cues as well as visual emotion cues in future studies may further increase
generalizability of the findings of this study.
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Tables
Table 1 Ordinal Regression Analyses of Gender and Clinical Status Predicting Emotion Recognition Accuracy on Specific Emotions
Anxious Girls vs. Anxious Boys Anxious Girls vs. Non-anxious Girls
Emotion Odds Ratio (95% CI) P Odds Ratio (95% CI) P
Relaxed 1.1 (0.4, 2.7) 0.9 0.9 (0.4, 2.2) 0.8
Bored 0.2* (0.07, 0.7) 0.02 0.4 (0.1, 1.3) 0.1
Tired 0.8 (0.3, 2.2) 0.7 0.5 (0.2, 1.5) 0.2
Surprised 0.2* (0.07, 0.9) 0.02 0.4 (0.1, 1.3) 0.1
Sad 0.6 (0.2, 1.6) 0.3 0.5 (0.2, 1.5) 0.2
Guilty 1.4 (0.5, 3.7) 0.5 0.9 (0.3, 2.2) 0.8
Ashamed 0.8 (0.3, 2.5) 0.7 0.7 (0.2, 1.6) 0.4
Angry - - - 1.2 (0.2, 6.7) 0.8
Irritable 1.0 (0.4, 2.5) >0.9 0.7 (0.3, 1.8) 0.5
Jealous 1.1 (0.4, 2.7) 0.9 1.2 (0.5, 3.0) 0.7
Scared 0.7 (0.2, 2.5) 0.5 1.3 (0.4, 4.1) 0.7
Nervous 0.7 (0.2, 1.8) 0.4 1.4 (0.5, 3.7) 0.5
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Table 1 Ordinal Regression Analyses of Gender and Clinical Status Predicting Emotion Recognition Accuracy on Specific Emotions
(Continued)
Anxious Girls vs. Anxious Boys Anxious Girls vs. Non-anxious Girls
Emotion Odds Ratio (95% CI) P Odds Ratio (95% CI) P
Disgusted 0.3* (0.1, 0.9) 0.03 0.4 (0.1, 1.6) 0.06
Happy 0.6 (0.09, 3.3) 0.5 1.4 (0.3, 6.0) 0.6
Elated 1.8 (0.7, 5.0) 0.2 0.9 (0.4, 2.5) 0.9
Proud 1.7 (0.5, 5.0) 0.4 1.2 (0.4, 3.3) 0.7
- The asterisk (*) represents a significant result
- None of the anxious boys misidentified ‘angry’, resulting in an empty cell
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Chapter Four
Additional Analyses: Effects of State Anxiety, Depressive Symptoms, and Anxiety
Symptoms on Emotion Recognition Accuracy in Children with Anxiety Disorders
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Abstract
This additional analysis examined the effects of state anxiety, severity of depressive
symptoms and anxiety symptoms on emotion recognition accuracy in children with and
without anxiety disorders. We found that state anxiety, task completion time, and
depressive/anxiety symptoms do not significantly predict overall emotion recognition
accuracy in children with and without anxiety disorders. Thus, these factors may not play a
decisive role in emotion recognition in children with anxiety and without anxiety disorders.
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Introduction
The secondary analyses investigated possible effects of state anxiety, depressive
symptoms, anxiety symptoms, and time elapsed for MAAC completion on emotion
recognition accuracy in children with and without anxiety disorders. Based on previous
research, state anxiety does not seem to be associated with emotion recognition accuracy in
children without anxiety disorders. For example, Surcinelli et al. (2006) reports that state
anxiety generally failed to predict emotion recognition accuracy. On the other hand, the
effect of state anxiety on emotion recognition accuracy is still unknown for children with
anxiety disorders, and this study is the first attempt to examine the link between state anxiety
and emotion recognition accuracy in clinically anxious children. Moreover, the effects of
task completion time, depressive symptoms, and anxiety symptoms on emotion recognition
accuracy have not been reported for this clinical population. Therefore, this chapter
examines the effects of these variables, and any finding will be preliminary to the literature.
Aims and Hypotheses
Objective #1: to determine the effect of state anxiety on emotion recognition
accuracy in children with and without anxiety disorders.
According to previous research, state anxiety seems to have a significant effect on
recognition accuracy in fear-related emotions in children without anxiety disorder (Surcinelli
et al., 2006). It is therefore predicted that state anxiety will significantly affect recognition
accuracy on fear-related emotions in children with anxiety disorders in this study.
Objective #2: to investigate the effect of depressive symptoms on emotion
recognition accuracy in children with and without anxiety disorders.
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Since the literature suggests that anxiety disorders often lead to depression in children
and adolescents (Cole, Peeke, Martin, Truglio, & Seroczynski, 1998), it is predicted that
depressive symptoms indicated by the CDI total T-score will be higher in children with
anxiety disorders compared with children without anxiety disorder. It is also predicted that
depressive symptoms will be negatively correlated with the overall total accuracy score
received on MAAC regardless of the clinical status since adults with depression have a
deficit in recognizing emotional expressions (Demenescu et al., 2010).
Objective #3: to characterize the effect of anxiety symptoms on emotion
recognition accuracy in children with and without anxiety disorders.
Since the anxiety group in the present study consists of children characterized by
clinically high levels of anxiety diagnosed by experienced clinicians, it is predicted that
anxiety symptoms will be significantly more elevated (indicated by T-score on MASC and
SCARED) in clinically anxious children than in non-anxious children.
We have further predicted that anxiety symptoms in children with and without
anxiety disorders will be negatively correlated with total accuracy score on MAAC (i.e. the
overall emotion recognition accuracy), but will be positively related to recognition accuracy
for fear related emotions (e.g. scared, nervous).
Objective #4: to determine the effect of time elapsed for completing MAAC on
emotion recognition accuracy in children with and without anxiety disorders.
For examining the effect of time elapsed for MAAC completion on emotion
recognition accuracy, there is no specific hypothesis as children with anxiety disorders might
make hasty and biased judgment on identifying the emotional states of others, or might work
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more slowly as a result of excessive worry about answering correctly or worrying about what
the examiner might think.
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Methods
Participants, procedures, and statistical analysis are consistent with those described in
the Methods section in Chapter 2. Additional instruments used are described in this section.
These additional surveys were completed either before or after the MAAC assessment to
measure their level of state anxiety, depressive symptoms, and anxiety symptoms since such
factors may cause confounding effects on research outcomes. Administration of measures
was counterbalanced to minimize order effects.
Additional Instruments Used
Children’s Depression Inventory (CDI).
The Children’s Depression Inventory (CDI) is a paper-and-pencil self-report survey
that measures the presence and severity of depression in children and adolescents (Kovacs &
Beck, 1977). It is used as a screening instrument and to monitor changes in depressive
symptoms over the course of treatment (Kovacs & Beck, 1977). The long form of the CDI
consists of 27 questions, whereas the short form consists of 10 questions, each with a 3-point
scale indicating severity of the symptoms (0 = symptoms absent, 1 = symptoms mild, 2 =
symptoms definite). The present study used the long form of the CDI. The subscales include
negative mood, interpersonal problems, ineffectiveness, anhedonia, and negative self-esteem,
and the sum of these subscale scores yield the CDI total score whose T-score of 65 is
interpreted as clinically significant. Reliability of the CDI in children and adolescents
computed by coefficient alpha, item-total score product-moment correlation, and test-retest
coefficients has been proven acceptable (Smucker, Craighead, Craighead, & Green, 1986).
Multidimensional Anxiety Scale for Children (MASC).
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The Multidimensional Anxiety Scale for Children (MASC) instrument is a self-report
questionnaire targeted for children and youth from the ages of 8 to 19 years. The measure
contains 39 items, and addresses four distinct dimensions of children’s anxiety, including
physical symptoms (tense/restless and somatic/autonomic), harm avoidance (perfectionism
and anxious coping), social anxiety (humiliation/rejection and public performance fears), and
separation anxiety/panic (March, Parker, Sullivan, Stallings, & Conners, 1997). The
administration time of MASC is about 5-15 minutes, and the measure has an inconsistency
index that detects the presence of reckless responses. MASC is equipped with Profile Sheets
which allow the conversion of raw scores to standardized T-scores. Test-retest reliability
ranges from satisfactory to excellent, whereas the parent-child agreement on ratings of
anxiety is poor to moderate (March et al., 1997).
The Screen for Child Anxiety Related Emotional Disorders (SCARED).
The Screen for Child Anxiety Related Emotional Disorders (SCARED) consists of
parent and self-report versions for screening anxiety disorders in children (Birmaher et al.,
1997). This instrument provides information regarding children’s symptoms of
somatic/panic disorder, general anxiety, separation anxiety, social phobia, and school phobia
(Birmaher et al., 1997), and contains 41 items pertinent to these symptoms, each with a
three-point scale (0 = not true, 1 = somewhat true, 2 = often true) (Birmaher et al., 1999).
Both the child and parent versions of SCARED show good internal consistency (alpha = .74
to .93), test-retest reliability (intraclass correlation coefficients = .70 to .90), and
discriminative validity (from other non-anxiety disorders as well as within anxiety disorders)
(Birmaher et al., 1997).
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Results
Objective #1: To determine the Effect of State Anxiety on Emotion Recognition
Accuracy in Children with and without Anxiety Disorders
The normality assumption was checked to determine if the dependent variable (i.e.
total accuracy score) were normally distributed for each level of the independent variable.
The histograms showed normally distributed data in the total sample, in the anxiety group,
and in the control group; however, Kolmogorov-Smirnov (KS) and Shapiro-Wilk (SW) tests
of normality assumed a normal distribution only for the control group.
When a one-way ANOVA was conducted, there was no significant group difference
among the SAD, GAD, SP, and control groups, F (3, 86) = 0.79, p = 0.50.
A correlation analysis revealed that state anxiety was not significantly correlated with
the average total accuracy score received in the total sample (p = 0.64). The correlation
analysis was also conducted in the anxiety group and the control group, but no significant
correlation was detected between state anxiety and total accuracy score in either anxious
children (p = 0.81) or non-anxious controls (p = 0.84). Therefore, the ANCOVA analysis for
the objective #3 of the present study excluded state anxiety as a covariate since the variable
failed to show any significant association with the total accuracy score.
Ordinal regression analyses were performed to predict a relationship between state
anxiety and recognition accuracy for specific emotions in both the anxiety and control groups.
The result revealed that in clinically anxious children, an increase in state anxiety
significantly decreased the accuracy for recognizing ‘surprised’, while significantly
increasing the recognition accuracy for ‘irritable’ emotion (Table 1). However, in non-
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anxious controls there was no significant association between state anxiety and recognition
accuracy for any specific emotions (Table 1).
Objective #2: The Effect of Depressive Symptoms on Emotion Recognition Accuracy in
Children with and without Anxiety Disorders.
The normality assumption for the CDI T-score was satisfied within the anxiety and
control groups, but the GAD group showed a positively skewed distribution shown by a
histogram and tests of normality: KS (p = 0.03) and SW (p = 0.03). However, the ratios of
skewness and kurtosis statistics by standard error for the GAD group were both below the
value of 2, thus correlation analyses were pursued.
The average T-score for the total score on CDI was compared between the anxiety
and control groups using an independent t-test. The Levine’s test showed that the variances
were unequal between the two groups (p = 0.02). The t-test result indicated that the t-scores
were significantly different between the anxiety group (M = 48.57, SD = 7.50) and the
control group (M = 44.63, SD = 5.82), t (95.87) = - 3.94, p = 0.005. A one-way ANOVA
detected a significant difference among the groups of SAD, GAD, SP, and control groups, F
(3, 90) = 3.42, p = 0.02). A post-hoc test revealed that the GAD group and the control group
were significantly different, such that CDI total t-score was higher in the GAD group (M =
49.66, SD = 8.16) than the control group (M = 44.63, SD = 5.82). However, no significant
difference was detected between the SAD (M = 47.60, SD = 7.53) and control groups or
between the SP (M = 45.22, SD = 5.93) and control groups.
Correlation analyses indicated that the T-score for the total CDI score was not
significantly correlated with total accuracy score either in the anxiety group (r = - 0.07, p =
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0.61) or in the control group (r = - 0.10, p = 0.50). Further, no significant correlation
between the variable and total accuracy score was reported within any of the subtype groups.
Ordinal logistic regression analyses in the anxiety group revealed that the T-score for
the total CDI score was not significantly associated with accurate recognition of any specific
type of emotions (p > 0.05) (Table 2). The variable was also not significantly associated
with any of the specific emotions in the control group (Table 2).
Objective #3: The Effect of Anxiety Symptoms on Emotion Recognition Accuracy in
Children with and without Anxiety Disorders.
The normality assumption for both the SCARED and MASC t-scores was satisfied
within the anxiety and control groups. The same assumption was met for both t-scores
within all of the different groups of anxiety disorders indicated by non-significant KS and
SW test results (p > 0.05). Correlation analyses showed that T-score for the SCARED and
MASC total score was not significantly related to total accuracy score in anxious children
([SCARED] r = - 0.06, p = 0.65; [MASC] r = 0.06, p = 0.73) and in non-anxious children
([SCARED] r = - 0.25, p = 0.06; [MASC] r = 0.10, p = 0.59).
The average T-scores for SCARED total score (M = 33.28, SD = 11.28), t (115) = -
5.16, p < 0.001, and MASC total score (M = 59.54, SD = 8.42), t (70) = - 4.23, p < 0.001,
were significantly higher in the anxiety group than the T-scores for SCARED (M = 22.46,
SD = 11.38) and MASC (M = 50.65, SD = 9.37) of the control group.
A one-way ANOVA was conducted to examine the presence of any group difference
in T-score for SCARED among the different types of anxiety disorders, and detected a
significant difference, F (3, 108) = 10.60, p < 0.001). A post-hoc test revealed that the SAD
(M = 38.83, SD = 10.58) and GAD (M = 32.53, SD = 10.81) groups, but not the SP group
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(M = 25.60, SD = 9.98), had significantly higher T-scores than the control group (M = 22.46,
SD = 11.38). On the other hand, the same type of parametric analysis was not recommended
for MASC T-scores because the SP group only had five scored MASC questionnaires. A
non-nonparametric Kruskal-Wallis test was conducted instead, and found a significant group
difference, chi square = 10.77, p = 0.01 with df = 3). Mann-Whitney tests using the Holm-
Bonferroni adjustment indicated that only the GAD group was significantly lower on the T-
score for the total MASC score (p = 0.005 with alpha level at 0.008) than the control group,
but there was no significant difference among the anxiety subtypes on this measure.
Ordinal logistic regression analyses in the anxiety group showed that the T-score for
the total SCARED score did not significantly predict the recognition accuracy for specific
types of emotions. The ‘disgusted’ emotion was close to the significance level (chi square =
3.69, df = 1), but it was not statistically significant (p = 0.06) (Table 3). In the control group,
the variable failed to significantly predict the accuracy outcome for any specific type of
emotions (Table 3).
In the anxiety group, the T-score for the total MASC score also did not significantly
predict the recognition accuracy for specific types of emotions. In the control group, the
MASC T-score was a significant predictor for recognizing the ‘sad’ emotion (chi square =
7.75, p = 0.005, df = 1) with Cox and Snell and Nagelkerke values of 0.22 and 0.27,
respectively. However, the MASC T-score failed to predict for other types of specific
emotions.
Objective #4: The Effect of Time Elapsed for Completing MAAC on Emotion
Recognition Accuracy in Children with and without Anxiety Disorders.
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The normality assumption for the variable of the MAAC completion time in minutes
was satisfied within the anxiety and control groups as well as within each anxiety disorder
group, indicated by the ratios of skewness and kurtosis statistics / standard error, histograms,
and KS and SW statistics (p > 0.05).
The average time elapsed for the completion of MAAC was not significantly different
between clinically anxious children (M = 14.05, SD = 2.36) and non-anxious controls (M =
13.62, SD = 2.32), t (120) = -1.03, p = 0.31. A one-way ANOVA was performed to detect
any significant difference among the different anxiety groups of SAD, GAD, SP, and control
groups, but no significant difference was detected, F (3, 113) = 1.43, p = 0.24.
Correlation analyses showed that the elapsed time for completing MAAC was not
significantly correlated with the average total accuracy score in the total sample (r = 0.06, p
= 0.50), the anxiety group (r = 0.04, p = 0.97), or the control group (r = 0.15, p = 0.28). The
effect of the time needed to complete MAAC on recognition accuracy for specific emotions
was not examined due to missing data.
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Discussion
Effects of State Anxiety and Time Elapsed for MAAC Completion on Emotion
Recognition Accuracy in Children with and without Anxiety Disorder
The findings of the present study imply that state anxiety is not an important factor
for emotion recognition accuracy in either children with anxiety disorders or children without
anxiety disorder. In particular, the present result regarding the effect of state anxiety on
emotion recognition accuracy supports the findings of previous studies. For instance, Cooper
et al. (2008) found that state anxiety does not significantly influence the recognition accuracy
for facial expressions of seven different types of emotions: anger, sadness, happiness, fear,
surprise, disgust, and neutral. Further, the same result is also consistent with the finding of
Surcinelli et al. (2006) that there is no association between state anxiety and recognition
accuracy for anger, sadness, happiness, surprise, disgust, and neutral emotions. However,
this previous study reported a significant association between state anxiety and recognition of
fearful facial emotion, whereas state anxiety failed to predict fear recognition accuracy in the
present study. Differences between this previous study and the present study may also relate
to the enrollment of non-clinical participants with high- and low- state anxiety in the
previous study versus our enrollment of clinical participants.
Clinically anxious children did not complete the MAAC tasks in haste or exhibited
excessive worry about selecting ‘correct’ answers when compared with non-anxious children.
Furthermore, task completion time (in minutes) does not seem to play a significant role in
predicting emotion recognition accuracy in children with or without anxiety disorders. This
finding may have some implications for MAAC administration in the future. For example, it
may not be crucial to record time taken in MAAC administrations for school-aged children,
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whether clinically anxious or not, since elapsed time for MAAC task completion does not
predict the child’s performance on emotion recognition tasks
Effects of Depressive Symptoms and Anxiety Symptoms on Emotion Recognition
Accuracy in Children with and without Anxiety Disorder
Findings of this study suggest that children with anxiety disorders are significantly
more depressed and anxious than children without anxiety disorder. Higher or more severe
anxiety symptoms in children with anxiety disorders than without are expected. Further, the
present findings are consistent with previous comorbidity research on anxiety disorders,
showing that depressive symptoms are very common in this population (Anderson, Williams,
McGee, & Silva, 1987; McGee et al., 1990; Seligman & Ollendick, 1998).
The findings of the present study suggest that the severity of anxiety symptoms or
depressive symptoms does not seem to directly influence children’s overall emotion
recognition accuracy. These findings, in conjunction with results of the main objectives in
this thesis, suggest that clinical status and type of anxiety disorder in children predict their
overall emotion recognition accuracy, but severity of anxiety symptoms does not.
Similarly, the severity of depressive symptoms may not play an important role in
predicting emotion recognition accuracy in either clinically anxious children or non-anxious
children. According to previous research, however, adult patients diagnosed with depression
are significantly more impaired in emotion recognition than their non-depressed counterparts
(Demenescu et al., 2010; Feinberg, Rifkin, Schaffer, & Walker, 1986; George, Huggins,
McDermut, Parekh, Rubinow, & Post, 1998; Leppanen, Milders, Bell, Terriere, & Hietanen,
2004). Therefore, it may be the case that clinical status of depression, reflecting clinicians’
judgment in the diagnosis of depression, may be more important in predicting emotion
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recognition accuracy than depressive symptoms in individuals measured by the CDI T-score.
Another possible explanation for the non-significant effect of depressive symptoms on
emotion recognition accuracy is that the effect may be gender-specific. For example, there is
a report discussing the significant association between depressive feelings and impaired
emotion recognition in non-anxious boys but not in non-anxious girls. Investigating this
gender-specific effect of depressive symptoms on emotion recognition accuracy goes beyond
the scope of the present study, but it may merit further research in the future.
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Tables
Table 1. Ordinal Regression Analyses of State Anxiety Predicting Recognition Accuracy for Specific Emotions in Children with and
without Anxiety Disorder
Control Anxiety
Emotion Odds
Ratio
(95% CI) p-value Emotion Odds
Ratio
(95% CI) p-value
Relaxed 1.0 (0.9, 1.2) 0.9 Relaxed 1.0 (0.8, 1.1) 0.6
Bored 0.9 (0.8, 1.1) 0.9 Bored 1.1 (1.0, 1.3) 0.1
Tired 1.2 (1.0, 1.3) 0.06 Tired 1.0 (0.8, 1.1) 0.5
Surprised 0.9 (0.8, 1.1) 0.2 Surprised 0.8* (0.7, 1.0) 0.04
Sad 1.0 (0.9, 1.2) 0.6 Sad 1.0 (0.9, 1.2) 0.9
Guilty 1.0 (0.9, 1.2) 0.6 Guilty 0.9 (0.8, 1.0) 0.07
Ashamed 1.0 (0.9, 1.2) 0.5 Ashamed 1.0 (0.8, 1.2) 0.9
Angry 1.0 (0.8, 1.3) 0.7 Angry 1.0 (0.7, 1.5) 0.9
Irritable 1.0 (0.9, 1.2) 0.7 Irritable 1.2* (1.0, 1.3) 0.04
Jealous 1.0 (0.9, 1.1) 0.9 Jealous 0.9 (0.8, 1.1) 0.3
Scared 0.9 (0.7, 1.1) 0.3 Scared 0.9 (0.7, 1.1) 0.3
Nervous 1.0 (0.8, 1.1) 0.5 Nervous 1.0 (0.9, 1.1) 0.8
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Table 1. Ordinal Regression Analyses of State Anxiety Predicting Recognition Accuracy for Specific Emotions in Children with and
without Anxiety Disorder (Continued)
Control Anxiety
Emotion Odds
Ratio
(95% CI) p-value Emotion Odds
Ratio
(95% CI) p-value
Disgusted 1.0 (0.9, 1.2) 0.8 Disgusted 1.2 (1.0, 1.4) 0.05
Happy 1.0 (0.8, 1.2) 0.7 Happy 1.1 (0.9, 1.4) 0.4
Elated 1.0 (0.9, 1.1) 0.8 Elated 1.1 (0.9, 1.2) 0.3
Proud 1.0 (0.9, 1.1) 0.9 Proud 1.1 (0.9, 1.3) 0.4
- The asterisk (*) denotes statistically significant result
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Table 2. Ordinal Regression Analyses of CDI T-Score Predicting Recognition Accuracy for Specific Emotions in Children with and
without Anxiety Disorder
Control Anxiety
Emotion Odds
Ratio
(95% CI) p-value Emotion Odds
Ratio
(95% CI) p-value
Relaxed 1.0 (0.9, 1.1) 0.5 Relaxed 1.0 (0.9, 1.1) 0.4
Bored 0.9 (0.8, 1.1) 0.3 Bored 1.0 (0.9, 1.1) 0.6
Tired 1.1 (1.0, 1.2) 0.06 Tired 1.0 (0.9, 1.1) 0.5
Surprised 1.0 (0.9, 1.1) 0.9 Surprised 1.0 (0.9, 1.1) 0.6
Sad 1.0 (0.9, 1.1) 0.5 Sad 1.0 (1.0, 1.1) 0.5
Guilty 1.1 (1.0, 1.2) 0.1 Guilty 0.9 (0.9, 1.1) 0.8
Ashamed 1.0 (0.9, 1.1) 0.7 Ashamed 1.0 (0.9, 1.0) 0.4
Angry 1.0 (0.8, 1.2) 0.6 Angry 1.0 (0.9, 1.2) 0.7
Irritable 1.1 (1.0, 1.2) 0.2 Irritable 1.0 (1.0, 1.1) 0.4
Jealous 1.0 (0.9, 1.1) 0.6 Jealous 0.9 (0.9, 1.0) 0.08
Scared 1.0 (0.9, 1.2) 0.8 Scared 1.0 (0.9, 1.1) 0.7
Nervous 1.1 (1.0, 1.2) 0.2 Nervous 1.0 (0.9, 1.1) 0.7
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Table 2. Ordinal Regression Analyses of CDI T-Score Predicting Recognition Accuracy for Specific Emotions in Children with and
without Anxiety Disorder (Continued)
Control Anxiety
Emotion Odds
Ratio
(95% CI) p-value Emotion Odds
Ratio
(95% CI) p-value
Disgusted 1.0 (0.9, 1.1) 0.9 Disgusted 1.1 (1.0, 1.2) 0.05
Happy 1.1 (0.9, 1.2) 0.3 Happy 1.0 (0.9, 1.1) 0.9
Elated 0.9 (0.8, 1.0) 0.1 Elated 1.0 (0.9, 1.1) 0.6
Proud 1.0 (0.9, 1.1) 0.8 Proud 1.0 (0.9, 1.0) 0.3
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Table 3. Ordinal Regression Analyses of SCARED T-Score Predicting Recognition Accuracy for Specific Emotions in Children with
and without Anxiety Disorder
Control Anxiety
Emotion Odds
Ratio
(95% CI) p-value Emotion Odds
Ratio
(95% CI) p-value
Relaxed 1.0 (1.0, 1.1) 0.6 Relaxed 1.0 (1.0, 1.1) 0.8
Bored 1.0 (1.0, 1.1) 0.4 Bored 1.0 (0.9, 1.0) 0.8
Tired 1.0 (1.0, 1.1) 0.5 Tired 1.0 (0.9, 1.2) 0.4
Surprised 1.0 (1.0, 1.1) 0.7 Surprised 1.0 (1.0, 1.1) 0.2
Sad 1.0 (0.9, 1.0) 0.9 Sad 1.0 (1.0, 1.1) 0.5
Guilty 1.0 (1.0, 1.1) 0.2 Guilty 1.0 (1.0, 1.1) 0.2
Ashamed 1.0 (1.0, 1.1) 0.6 Ashamed 1.0 (1.0, 1.1) 0.5
Angry 1.0 (0.9, 1.1) 0.8 Angry 1.1 (1.0, 1.2) 0.3
Irritable 1.1 (1.0, 1.1) 0.05 Irritable 1.0 (0.9, 1.0) 0.07
Jealous 1.0 (0.9, 1.1) 0.3 Jealous 1.0 (0.9, 1.1) 0.5
Scared 1.1 (1.0, 1.1) 0.06 Scared 1.0 (1.0, 1.1) 0.2
Nervous 1.0 (1.0, 1.1) 0.8 Nervous 1.0 (0.9, 1.0) 0.2
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Table 3. Ordinal Regression Analyses of SCARED T-Score Predicting Recognition Accuracy for Specific Emotions in Children with
and without Anxiety Disorder (Continued)
Control Anxiety
Emotion Odds
Ratio
(95% CI) p-value Emotion Odds
Ratio
(95% CI) p-value
Disgusted 1.0 (1.0, 1.1) 0.6 Disgusted 1.0 (1.0, 1.1) 0.07
Happy 1.0 (0.9, 1.1) 0.8 Happy 1.0 (0.9, 1.1) 0.9
Elated 1.0 (1.0, 1.1) 0.9 Elated 1.0 (0.9, 1.0) 0.9
Proud 1.0 (1.0, 1.1) 0.2 Proud 1.0 (1.0, 1.1) 0.3
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Chapter Five
General Discussion
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General Discussion
To the author’s knowledge, the present study was the first to examine age effects on
emotion recognition in children with anxiety disorders, and was the first to examine how
some of the most documented types of anxiety disorders for anxious children, SAD and
GAD, are related to the ability to recognize the emotional states of others. Furthermore, the
study explored gender effects on emotion recognition in children with anxiety disorders,
which had not been extensively studied in the past. Additionally, although not included as
one of the main research manuscripts, the present study conducted secondary analyses to
investigate potential impacts of state anxiety, task completion time, and depression/anxiety
symptoms on emotion recognition accuracy in children with anxiety disorders, all of which
had not been reported in the past. The fact that children’s age was carefully controlled to
range from 6 to 11 years was a strength because at this age children’s verbal skills do not
seem to be correlated with the ability to identify emotions (Steele et al., 2008). Thus, the
study minimized the possible cofounding effect of individual verbal ability on emotion
recognition accuracy. Each of the study’s key findings will now be discussed in greater detail.
Emotion Recognition Accuracy in Children with and without Anxiety Disorder
The prevalence of specific anxiety disorders in children varies across epidemiologic
studies (Cartwright-Hatton et al., 2006), and due to the high rate of comorbidity among
specific disorders (Last, Strauss, & Francis, 1987) conventional research designs usually
study children with anxiety disorders as a single group. Therefore, in the first objective of
this study all the anxiety types of SAD, GAD, and SP (and a few children with PTSD or
specific phobia) were combined into a single experimental group to explore findings of these
past studies.
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The result for this first objective suggested that children with anxiety disorders do not
have difficulty identifying emotions accurately compared with children without anxiety
disorder. Using the same conventional designs of past studies, combining various types of
anxiety disorders into a single experimental group, the present study therefore produced
results similar to those of previous studies of emotion recognition in children with anxiety
disorders (Demenescu et al., 2010). Further, children with anxiety disorders did not seem to
have any difficulty recognizing any specific type of emotions in comparison with children
without anxiety disorder.
Effects of Age on Emotion Recognition Accuracy in Children with and without Anxiety
Disorders
The result of the second objective indicated that emotion recognition accuracy
linearly increases with age in children with and without anxiety disorders. Unlike the initial
prediction of this study, however, the rate of improvement seemed to be comparable in the
two groups. It was also suggested that the recognition accuracy for the basic emotion of
disgust improves during the elementary school years in both children with and without
anxiety disorders. Improvement in recognition of disgust may be a common feature of
emotional development in children between 6 and 11 years of age. On the other hand, the
same children did not show age-related improvement in recognition accuracy for other basic
emotions (happy, sad, angry, and scared). This was the case because children with and
without anxiety disorder were highly accurate in recognizing these emotions at 6 years of age,
and statistical analyses could not detect any significant improvement beyond this age.
In both groups of children, recognition accuracy for some complex emotions
increased significantly each year, especially those that were conveyed via bodily or
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contextual cues (e.g. ‘jealous’, ‘proud/pleased’, ‘tired/exhausted’, ‘nervous’). This finding
seems to be consistent with the trend shown in children without anxiety disorder that with
increased age, representing wider social experiences and improved verbal ability to express
complex emotions, they can recognize others’ complex feelings more accurately (Gross &
Ballif, 1991).
Effects of Age and Anxiety Subtypes on Emotion Recognition Accuracy in Children
with Anxiety Disorders
When the age effects were included as a covariate, the present study indicated that
children with SAD have significantly lower overall emotion recognition accuracy, compared
with non-anxious children and children with the primary diagnosis GAD or SP.
Although children with SAD demonstrated age-dependent improvement in emotion
recognition accuracy in the present study, their recognition accuracy seems to be
significantly lower than that of children without anxiety disorder at an early school age, and
this deficit seems to continue throughout 6 to 11 years of age. By contrast, children with
GAD also showed a deficit in emotion recognition accuracy at a young school age, but
accuracy improved at a faster rate than that of SAD children to catch up with the accuracy of
children without anxiety disorder at later school years. These findings are only discernible
when age and different types of anxiety disorders are considered together. Conclusions for
the SP group are limited by small sample size, but children with SP failed to display
significant age effects on their overall emotion recognition accuracy.
The developmental delay in emotion recognition ability shown in children with SAD
may relate to the observation that children with SAD tend to lack early social experiences
due to their reluctance to leave their parents or attachment figures (Ollendick, King, & Yule,
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1994, pp. 146). The rationale for this hypothesis is based on evidence that recognition of
facial emotions can be influenced by children’s early social experiences (Pollak, Messner,
Kistler, & Cohn, 2008). Learning or expertise in emotion recognition seems to develop with
practice. On the other hand, children with GAD or SP may be more concerned than children
with SAD about others’ perceptions, as (in GAD) they may worry about being bullied or
scapegoated by peers and (in SP) they may worry about embarrassment and negative
evaluation by others (Albano et al., 2003, pp. 285-292). These concerns all involve the
children’s learning and inspection of others’ thoughts and feelings, potentially fostering
development of emotion recognition skills.
Effects of Gender on Emotion Recognition Accuracy in Children with and without
Anxiety Disorder
The findings on gender effects on emotion recognition accuracy in the present study
imply that gender plays a minimal role in emotion recognition accuracy children with and
without anxiety disorders. However, the present study found that gender is significantly
related to disgust recognition accuracy such that girls with anxiety disorders are more
impaired in recognizing disgust than boys with anxiety disorders or their non-anxious
counterparts.
It is noteworthy that gender was not associated with emotion recognition accuracy in
children without anxiety disorder in the present study. This is inconsistent with a previous
meta-analysis on gender effects in emotion recognition accuracy, which suggested that non-
anxious girls are more accurate than non-anxious boys on emotion recognition tasks
(McClure, 2000). One possible explanation relates to the fact that children in the present
study were shown various types of cues in dynamic motion. It is possible that boys in this
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study may have effectively used contextual cues or dynamic bodily motion of the character
to compensate for their delay, compared with girls, in facial emotion recognition. In real-life
social settings, however, children assess others’ emotional states based on a combination of
facial expressions, bodily gestures, and situational contexts. Therefore, findings of the
present study (which used all of these cues) may be more generalizable than previous studies
in the anxiety literature.
Limitations
The present study has a number of limitations. First, although participants were
mainly from well-educated Caucasian families, detailed data for children’s cultural or ethnic
background were not available for statistical analyses in this study. However, evidence
suggests that cultural background may modulate amygdala activation during emotion
processing, influencing emotion recognition accuracy. For instance, Asians tend to exhibit a
significantly more robust amygdala response upon perceiving angry faces in comparison
with Europeans, paralleled by decreased recognition accuracy (Durntl et al., 2012). Another
example of culture-specificity is provided by a meta-analysis on cross-cultural universality
and cultural specificity of emotion recognition. This study revealed that emotion recognition
accuracy tends to increase when emotions are expressed and identified by individuals of the
same national or ethnic group, reflecting in-group familiarity (Elfenbein & Ambady, 2002).
In the present study, however, the main animated character of MAAC (Teena) is a white
teenage girl. Although this character captures the local majority group status in terms of
culture and ethnic background, her ethnicity may place children with minority status at a
disadvantage with respect to emotion recognition.
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Second, the analyses did not determine if the overall emotion recognition accuracy in
children with anxiety disorders continues to linearly increase in relation to age after the age
of eleven. Because the present research may have implications for child-focused CBT for
anxiety disorders which targets children of ages up to 13 (Kendall, Gosch, Furr, & Sood,
2008), the ideal experiment would therefore have included children older than 11 (i.e. 12 and
13 year-old children) with anxiety disorders. Replication involving the full age range up to
13 years is warranted in order to better understand the development of emotion recognition
accuracy in anxious children.
Third, the present findings are limited to recognition of the emotional states of a
female animated character, which may or may not be generalizable to other children or other
adults. Nevertheless, MAAC was used to ensure the validity of findings in young children
who may have difficulty labelling emotions based on facial expressions. This limitation may
be improved if both male and female characters, of varying ages, are presented in the future.
Fourth, the ability to recognize one’s own emotions or to recognize emotions using
verbal cues has not been addressed in this thesis. However, a study of the roles of verbal and
non-verbal cues in emotion recognition in persons with and without autism spectrum disorder
(ASD) shows that individuals with ASD can use both verbal and non-verbal cues for
emotions in the same way as individuals without ASD. High-functioning individuals with
ASD rely more on non-verbal cues than verbal cues to recognize a speaker’s emotional states
(Loveland et al., 1997). Based on this evidence from the literature of ASDs, the present
study may be limited in the sense that it fails to assess if clinically anxious children rely more
on non-verbal cues than verbal cues, or use both types of cues in the same manner as non-
anxious children. Further, although clinically anxious children show proficiency in
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recognizing basic emotions (e.g. happy, sad, angry) in the present study, it may be
worthwhile investigating to what extent verbal cues contribute to these children’s recognition
of complex emotions (e.g. jealous, irritable, proud). Such investigation would be relevant to
the generalizability of our findings, as it is a common sense that we perceive both verbal and
non-verbal cues in everyday situations.
Fifth, the present study contained moderately unequal group sizes, and increasing the
sample size of certain comparison group(s) would have improved statistical confidence. For
example, the numbers of participants in the SAD group and in the SP group were only 10 and
13, respectively, whereas the numbers in the GAD group and in the control group were 35
and 59, respectively. A mild to moderate degree of unequal group sizes can be expected and
can sometimes reflect randomness (Schulz & Grimes, 2002). However, because all members
in the present study are assumed to be equally influential, unequal sample group sizes that do
not reflect the population distribution may cause a bias in the estimation of effect sizes
(Kenny, Mannetti, Pierro, Livi, & Kashy, 2002). Therefore, an increase in sample size for
both the SAD and SP groups could have improved the power of our analyses, especially
regarding age effects on emotion recognition accuracy in these groups. This is especially
true for the SP group, the only diagnostic group that failed to exhibit a significant correlation
between age and emotion recognition accuracy. To resolve this limitation, the proband
group in future studies must include a larger number of children with SAD or SP.
Sixth, the present study failed to investigate the effect of socioeconomic status (SES)
of participating children’s families. In fact, SES appears to significantly affect emotion
recognition accuracy such that persons with a higher SES tend to recognize others’ emotions
better compared with those with a lower SES (Edwards, Manstead, & Macdonald, 1984; Hall
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& Halberstadt, 1994). Thus, SES may have played a role in predicting emotion recognition
accuracy in children with anxiety disorders in the present study, although the range of SES is
generally narrow in this clinic (middle and upper middle class). Therefore, it may be more
informative if future research includes children from various SES backgrounds and then
examine the effects of various SES levels on emotion recognition accuracy.
Seventh, the present study did measure general intelligence of the child participants.
Such information was not collected because the present study was a secondary analysis to the
validation of MAAC (Manassis et al., 2013). However, the link between general intelligence
and emotion recognition accuracy in anxious children is still unknown, and this may be an
important factor in this analysis – ergo, this factor must be addressed in the future.
Eighth, children with anxiety disorders in the present study did not show higher state
anxiety than their non-anxious counterparts at the time of the MAAC assessment. Therefore,
our findings do not capture these children’s ability to recognize emotions during anxiety-
provoking situations (e.g. social activities for children with SP). In the future, therefore, the
present study may be repeated in anxious children when their state-anxiety is high (e.g.
children with SP in anticipation of social activities or public performance).
Lastly, attentional and motivational factors may have caused a bias in the results of
the present study as some scientists have argued that individual variance in emotion
recognition accuracy is simply a reflection of individual differences in attention or
motivation to decode emotional information from emotion-related stimuli (Buck, 1988).
However, none of the existing research has assessed the effect of individual differences in
attention and motivation on emotion recognition accuracy. The present study also did not
assess the potential interaction between the effect of anxiety diagnosis and the effect of
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attention and motivation on emotion recognition accuracy. These issues may also be
addressed in later studies.
Implications
The present study may have some implications for CBT in the treatment of childhood
anxiety disorders (e.g. Coping Cat program) as a part of the protocol guides clinicians and
children with anxiety disorders to discuss cues for the emotional states of others. However,
greater emphasis is still placed on recognition of one’s own emotions in these CBT programs.
Findings of the present study suggest, albeit within the limitations inherent to a cross-
sectional research design, that expanded emotion recognition training may be helpful for
children with anxiety disorders, especially children with the primary diagnosis of SAD.
Increased emotion recognition training, however, may be more essential for younger anxious
children (early school-age children) than older ones as the deficit in emotion recognition
skills seems to be more prominent in the younger anxiety group in the present study. For
example, both early school-age children with SAD and early school-age children with GAD
appear to have difficulty identifying various emotions compared with their non-anxious
counterparts in the present study. However, the deficit in emotion recognition ability
remains constant throughout the elementary school years in children with the primary
diagnosis of SAD, whereas the deficit seems to diminish with time in children with the
primary diagnosis of GAD. Therefore, early intervention involving additional training in
emotion recognition skills may lead to better social experiences for young anxious children
than improving these skills during late childhood, especially in children with a primary
diagnosis of GAD.
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The present findings also demonstrate that children with anxiety disorders tend to be
accurate in judging basic emotions (e.g. happy, sad, angry) of others (as displayed by the
animated character) that can be conveyed via simple facial cues. Such findings are
consistent with a meta-analysis of previous research that utilized static facial cues
(Demenescu et al., 2010). In the present study, however, the deficit in emotion recognition
ability in children with SAD becomes evident only when these children are tested on a range
of both simple and complex emotions that are dynamically expressed via all facial, bodily,
and situational cues. This observation suggests that emotion recognition training in CBT for
anxious children may be more effective if clinicians facilitate discussions of various types of
cues expressing a wide range of basic and complex emotions, not limited to facial cues for
basic emotions only.
Another intriguing finding involves the decreased recognition accuracy for disgust in
clinically anxious girls in comparison with clinically anxious boys and non-anxious girls. If
replicated, it is possible that this finding may represent a marker for the presence of anxiety
disorder since school-age girls without any anxiety diagnosis are not impaired in the ability
recognize disgust in others in the present study. Although this idea may seem very
speculative, due to the lack of supporting theoretical framework in the literature, it is not
unique in the field as some reports claim that disgust recognition is impaired in individuals
with OCD (Sprengelmeyer et al., 1997), and this association seems to depend on symptom
severity and general functioning (Corcoran, Woody, & Tolin, 2008).
Overall, the present findings support the flexible use of anxiety-focused CBT,
allowing for increased emphasis on emotion recognition in clinically anxious children with
deficits in social or emotional understanding (Beidas et al., 2010). Such flexibility may be
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less important, however, in children with the primary diagnosis of GAD whose impaired
emotion recognition may be transitory at a young age.
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Conclusion
Although the author must interpret the present findings in the context of study
limitations, children with SAD showed a deficit in the recognition of others’ emotions
relative to children without anxiety disorder. Young school-aged children with GAD also
showed difficulty in this emotional domain. These underlying associations can be masked,
however, if age and specific diagnosis factors are neglected. Lack of attention to these
details in past studies may help explain their inconsistent results. Moreover, although gender
plays a minimal role in emotion recognition accuracy in children with anxiety disorders,
anxiety diagnosis may be related to impairment in disgust recognition in girls. This finding
merits further study with the inclusion of other clinical groups. Clinically, facilitating
emotion recognition skills may be a useful component of CBT for school-aged children with
SAD and for younger children with GAD.
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Chapter Six
Future Directions
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Future Directions
First school-aged children with SAD (the group that showed emotion recognition
deficits in this study) must be compared with other clinical groups using a developmentally
sensitive tool (e.g. MAAC) to accurately assess the severity of this impairment. Although
statistically significant, the difference in emotion recognition accuracy between the SAD
group and the control group seems rather mild in this study, as children with SAD do not
appear to have any difficulty recognizing any specific emotion in comparison to their non-
anxious counterparts. Previously, McClure et al. (2003) found that children and adolescents
with bipolar disorder are more severely impaired in facial emotion recognition than those
with anxiety disorders or those without any psychiatric diagnosis. Therefore, comparing
children with SAD with other clinical groups, such as children with bipolar disorder, may
yield meaningful outcome data.
Second, emotion recognition accuracy in children with SP will need to be reassessed
with a larger sample size of varying ages because the size of the SP group was small in the
present study. Emotion recognition accuracy of children in this clinical group does not seem
to linearly commensurate with age. With a significantly higher number of child participants
with SP, however, future studies could assess the potential relationship between age and
emotion recognition accuracy in this clinical subgroup. Such studies could also examine if
other factors, such as certain demographic attributes (e.g. SES, ethnic/cultural background),
are significantly associated with emotion recognition accuracy in this group.
Third, additional neuropsychological tests could be used in future studies to measure
clinically anxious children’s general intelligence or IQ, verbal ability to express various
emotions, and personality traits. Potential interactions between these neuropsychological
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factors and age in predicting emotion recognition accuracy could then be investigated.
Personality traits are considered in this future direction because certain personality traits
seem to predict emotion recognition accuracy in non-anxious persons. ‘Openness to
experience’, for instance, is positively correlated with emotion recognition accuracy, whereas
‘neuroticism’ is negatively associated (Matsumoto et al., 2000). The latter finding is
particularly relevant to anxiety disorders because ‘neuroticism’ is highly correlated with the
presence of anxiety disorders in adults (Kotov, Gamez, Schmidt, & Watson, 2010).
Fourth, emotion recognition accuracy of clinically anxious children needs to be
measured during anxious states to determine if their recognition is distorted in anxiety-
generating situations. Reliable methods of inducing particular moods include the use of
imagination, expressive behaviour, scripted/unscripted social situations, and music (Coan &
Allan, 2007, pp. 9), but films or film fragments are the most conventionally and reliably used
for inducing fearful mood or state anxiety in experimental conditions (Tovilovic, Novovic,
Mihic, & Jovanovic, 2009). Therefore, in future research, clinically anxious children and
non-anxious children could be shown film fragments validated in school-age children to
increase their state anxiety, and both child groups’ emotion recognition ability could then be
measured using MAAC. In the specific case of children with SP, an alternative method of
inducing state anxiety might be to have them engage in public speaking (Martin, 1990).
Such a method would be especially effective for inducing fear in children with SP whose
primary anxiety pertains to public performance, presumably yielding results that are highly
generalizable to real-life settings. Of course, anxiety induction would have to be time limited
and relatively mild to ensure ethical treatment of child research subjects.
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Fifth, the analysis of age effects on emotion recognition in the present study
represents an exploratory analysis since a cross-sectional research design was used.
Longitudinal studies will be required to confirm the developmental trajectory of emotion
recognition accuracy in anxious children. This method is more suitable than the cross-
sectional method for isolating the relationship between two variables without the interference
of third variables based on individual differences, allowing researchers to comprehensively
examine changes over time. Even with this method, however, some degree of sampling bias
and inconsistency is unavoidable (Bayley, 1965; Rajulton, 2001).
Lastly, there have been recent proposed revisions in the diagnostic criteria of GAD
for DSM 5 (i.e. removing the symptoms of fatigue, difficulty concentrating, irritability, and
sleep disturbance). Therefore, children diagnosed with GAD based on these new diagnostic
criteria must be re-examined in future studies.
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Appendix A
Mood Assessment via Animated Characters (MAAC)
Mood Assessment via Animated Characters (MAAC) is a computerized self-report
instrument designed for clinicians and researchers to effectively communicate about emotion
in young children with anxiety disorders. MAAC provides various types of dynamic
emotion cues (facial cues, bodily cues, and situational cues) through a teenage female
animated character (“Teena”) in order to facilitate young children’s discussion of 16 types of
feeling states (calm/relaxed, bored, tired, surprised, sad, guilty, ashamed, angry, irritable,
jealous, scared, nervous, disgusted, happy, elated, and proud/pleased). This instrument was
created by a team of clinicians who are experienced in the assessment and treatment of
childhood anxiety disorders and researchers who have expertise in the clinical application of
computer devices and computer animation (Manassis et al., 2009).
MAAC assesses young children’s ability to express and identify a range of both
simple and complex (social) emotions of positive, negative, fearful and neutral valence. This
instrument has been validated in children, 4-10 years of age, with and without anxiety
disorders. The initial validation of MAAC included children younger than 8 because well-
validated assessment instruments had been largely missing in this age group.
In terms of context in which MAAC is designed to be used, this instrument may be
used in the clinic for screening for internalizing symptoms or anxious feelings in young
anxious children who may not have fully developed the cognitive ability to verbally describe
or label their feelings. However, the instrument can also be used in non-clinical settings (e.g.
home, school) to discuss everyday feelings of young children.
Administration, coding and scoring.
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The administration of MAAC takes about on average of 15 minutes. During the
procedure, children are asked to express their current feelings by comparing them to those
expressed by Teena, and asked to rate the intensity of these feelings on the Likert scale
between 0 (not at all) and 5 (being an exact match) by selecting/tapping on the screen.
Then, the child and the interviewer together visit each of 16 emotions in order on
MAAC screen, top to bottom and left to right, to view each of these emotion-specific
animations. Upon viewing each clip, the child is asked to identify Teena’s feeling.
Responses may be tape-recorded and scored based on how accurately the child identified
each feeling state of Teena: 0 (incorrect), 1 (close to correct), 2 (correct).
To minimize the effect of verbal ability on emotion identification accuracy, any
immature form of verbal responses, but with the correct emotional tenor, ought to be
carefully considered. For example, young children without the verbal ability to label
‘disgusted’ may identify the emotion in a simpler term, such as ‘yucky’, and such response
may be given a score of two. For this reason, it is highly recommended that multiple raters
blindly score responses on MAAC and report the inter-rater agreement on scoring.
Psychometric properties.
Face validity: Factors on MAAC (positive, negative, fearful, and neutral groups)
contain emotions of similar valence, suggesting face validity (Manassis et al., 2013).
Content validity: The content validity of each item has not been evaluated in relation
to the symptoms content of anxiety disorders.
Construct validity (convergent validity, discriminant validity): The convergent
validity has shown that children’s ratings of current feelings show a significant correlation
with scores on the STAIC, whereas ratings of feelings for the past two weeks significantly
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correlate with some of the measures of trait anxiety, such as KFQ, MASC, and SCARED.
These correlations were reported in the expected direction such that ratings on negative
emotions on MAAC predicted higher ratings on the anxiety measures of STAIC and
SCARED, whereas those on positive emotions predicted lower ratings on STAIC and MASC.
In terms of the discriminant validity for differentiating the anxiety and non-anxiety groups
based on MAAC ratings, clinically anxious children identified themselves to be significantly
less positive and less calm than non-anxious children (Manassis et al., 2013).
Internal consistency: Cronbach’s alpha values have been reported in four emotion
factors of positive, negative, fearful, and neutral emotions. These values were 0.83, 0.76,
0.71, and 0.55, respectively.
Inter-rater reliability: Inter-rater reliability is excellent (kappa = 0.92).
Test-retest reliability and criterion validity await further investigation.