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THE ROLE OF CULTURE AND AGE IN THE IDENTIFICATION
AND PROCESSING OF NONVERBAL FACIAL EXPRESSIONS OF
EMOTION

presented by

Adrienne Ratliff Herron

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MA. degree in Department of Family and Child
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THE ROLE OF CULTURE AND AGE IN THE IDENTIFICATION AND
PROCESSING OF NON VERBAL FACIAL EXPRESSIONS OF EMOTION

By

Adrienne Ratliff Herron

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements .
for the degree of

MASTER OF ARTS
Department of Family and Child Ecology

2006

ABSTRACT

IDENTIFICATION AND PROCESSING OF NONVERBAL FACIAL
EXPRESSIONS OF EMOTION

By
Adrienne Ratliff Herron

Recently, emotion recognition studies have suggested that anger, disgust,
fear, happiness, sadness and surprise are universally recognized (Hejmadi, 2000).
However, research has demonstrated that individuals perceive nonverbal
communication from members of their own ethnic group more accurately than
they do from members of another ethnic group (Weathers et al., 2002).

This study examines the effect of cultural differences on the ability to
process facial expressions of emotions in children will also be addressed in this
study. Furthermore, the study will consider how accurate emotion identification
of children’s faces is related to internalizing and externalizing behaviors of
children and adults.

For both the child and adult participants the study found that Caucasian
participants were significantly more accurate than African American participants
at the identification of emotions.

When examining the issue of emotional competence, for the child
participants, the correct identification of emotions does not appear to be related to
internalizing or externalizing behaviors. For the adult participants, when happy is

identified correctly the participants reporting aggressive behavior decreases.

DEDICATION

I would like to dedicate this thesis to my parents, Robert and Gloria Herron, who
have scarified so much so that I could have the best. Making you proud is very important
to me!

To Geania Lee’Ann Capler and Talia Harlem Mims, my two intelligent, caring
and beautiful nieces who think that “Te-Te can do anything”. I pray that I am not just
your aunt, but an inspiration and friend as well.

I would like to thank all of my family and friends for supporting me and believing
in me, even when I did not believe in myself. You gave me strength, confidence,
shoulders to cry on, and ears to which I could vent.

Finally, I would also like to dedicate this work in loving memory of my
grandfathers Rev. George Edward Sanders and Chester Arthur Jones In, my grandmother
Essie Mae Herron-J ones, and my friend-guru L. Annette Abrams.

I love you all more than words can say!
“And one standing alone can be attacked and defeated, but two can stand back-to-

back and conquer!” Ecclesiastes 4:12

iii

ACKNOWLEDGMENTS

I would like to thank my committee members Deborah J. Johnson, Ph.D., Jessica
V. Barnes, Ph.D., Thomas J. Luster, Ph.D., and Francisco A. Villarruel, Ph.D. for
mentoring me and helping me to complete this Thesis. The guidance and support that I

received from you all is so greatly appreciated.

iv

Table of Contents

LIST OF TABLES ............................................................................................................ vi
LIST OF FIGURES ......................................................................................................... vii
INTRODUCTION ............................................................................................................. 1
CHAPTER 1

LITERATURE REVIEW .................................................................................................. 4
CHAPTER 2

METHODOLOGY. . . . . .. ................................................................................................. 14
CHAPTER 3

RESULTS ........................................................................................................................ 23
CHAPTER 4

DISCUSSION .................................................................................................................. 39
CHAPTER 5

CONCLUSION ................................................................................................................ 41
APPENDICES

Appendix A: Child Interview: DANVA and CBCL ........................................................ 44
Appendix B: Online Experiment Survey ......................................................................... 55
Appendix C: Production of Emotions Identification and Rating Scale ........................... 72
Appendix D: DANVA Code Sheet: African American Faces ......................................... 73
Appendix E: DANVA Code Sheet: Caucasian Faces ...................................................... 74
REFERENCES ................................................................................................................ 75

List of Tables

1.Sample Characteristics of Child Participants ................................................................ 15
2.8ample Characteristics of Adult Participants ... ............................................................ 16
3.Analysis of Variance for Child Sample: DANVA All Photos ...................................... 28
4.Analysis of Variance for Child Sample: DANVA African American Faces ................ 29
5.Analysis of Variance for Child Sample: DANVA Caucasian Faces ............................ 30
6.Analysis of Variance for Adult Sample: DANVA All Photos ..................................... 31
7.Analysis of Variance for Adult Sample: DANVA African American Faces ............... 32
8.Analysis of Variance for Adult Sample: DANVA Caucasian Faces ............................ 33
9.Hierarchical Regression Analysis for Child Sample: Anxious/Depression .................. 35
10.Hierarchical Regression Analysis for Child Sample: Aggression .............................. 36
“Hierarchical Regression Analysis for Adult Sample: Anxious/Depression ............... 37
12.Hierarchical Regression Analysis for Adult Sample: Aggression .............................. 38

vi

List of Figures

1.Model of Emotional Identification ................................................................................ 13
2.Average Correct Identification of Emotion: Child Sample Graph ............................... 24
3.Correct Identification of Black Faces by Race: Child Sample Graph .......................... 25
4.Correct Identification of White Faces by Race: Child Sample Graph .......................... 25
5.Average Correct Identification of Emotion: Adult Sample Graph .............................. 26
6.Correct Identification of Black Faces by Race: Adult Sample Graph .......................... 27
7. Correct Identification of White Faces by Race: Adult Sample Graph ......................... 27

vii

Introduction

Human beings make extensive use of vocal information to describe the emotional
state of others. When a person conveys an emotion, he/she begin an exchange of ideas,
which are based solely on nonverbal communicative intent. In spite of our ability as
humans to develop an increasingly complex verbal language, nonverbal communication
remains important because of its power to convey unique and valid information about
emotional states (Nowicki and Duke, 1992).

Ninety-three percent of communication is nonverbal. Nonverbal communication
refers to information that is transmitted from one person to another through a means other
than words (Nowicki and Duke, 1992). In the face-to-face encounters of everyday life,
each person monitors the emotional reactions of others. When one person observes the
emotional reaction of another, a variety of sources of information are available (Carroll
and Russell, 1996). There are various types of nonverbal expressions of emotion (tone of
voice (prosody), postures, gestures. emotion eliciting situations (contextual cues and
facial expressions) and they combine to express emotions in very complex and
complicated ways. Fifty-five percent of nonverbal communication is through facial
expression, posture, and gesture; thirty—eight percent is through prosody; and the other
seven percent consists of contextual cues and various combinations.

Everyday, individuals make a variety of complex conclusions about others based
on physical characteristics. For social interactions, faces are probably the most important
visual stimulus to humans, but understanding the development of the ability to readily
recognize and interpret faces remains limited (Taylor, Batty, and Itier, 2004). The face is

a rich source of affective information that can be communicated in a brief amount of time

(Nowicki and DiGirolamo, 1989). There have been studies that explored competence of
facial processing in adults versus the incompetence of facial processing in children.
These studies have shown that there is a gradual increase in facial recognition task
performance with age. Children and adults use configural and featural information, and
the age differences in performance are likely due in large part to children’s gradual,
quantitative improvement in general perceptual and cognitive skills (Baenniger, 1994).

Facial expressions allow a group to easily understand the opinions and attitudes of
others, thus constituting a powerful tool in social coordination (Batty and Taylor, 2003).
Over the past several years, emotion recognition studies have suggested that anger,
disgust, fear, happiness, sadness, and surprise are universally recognized (Hejmadi,
2000). Expressions of emotion were thought of as a God given, universal language that
revealed passions such as love and hate, virtues (courage), and vices (sloth) (Russell,
Bachorowski, and Fernandez Dols, 2003). Universal and cultural dissimilarity in
expression of emotion have been and more than likely will continue to be fervently
argued. The scientific study of how people express emotion has been intertwined with
the question of whether or not emotions are universal across cultures and species
(Elfenbein, 2003).

In today’s society we encounter individuals from other cultures frequently. Our
ability to understand others, and the responses that we make to them, are based largely on
our ability to effectively use the nonverbal behavior that is displayed in any interpersonal
interaction (Nowicki and Mitchell, 1998). Effective interpersonal relationships and social
performance require that individuals accurately receive, process, and decode nonverbal

expressions of emotion in others (Baum and Nowicki, 1998). The ability to interpret

emotional communications has an important influence on how we perceive and interact
with others (Buck, 1984).

This study will examine the level of competency in children and adults regarding
their ability to process facial expressions of emotions in children. The effect of cultural
differences on the ability to process facial expressions of emotions in children will be
addressed in this study as well. The study will also consider how accurate emotion
identification of children’s faces is related to internalizing and externalizing behaviors of

children and adults.

Chapter 1
Literature Review

The findings of several researchers now support the view that, with age, emotions
become increasingly important features of people’s cognitive appraisals of interpersonal
events (Thompson, Aidinejad, and Ponte, 2001). The ability to interpret features in
individuals develops early in life and continues to advance and increase as we grow.
Along with age, culture plays a powerful role in determining the perception and
interpretation of interpersonal events.

Development of Perceptions of Facial Expression of Emotions

Processing nonlinguistic vocalizations plays an essential role in maintaining
successful relationships and healthy psychological functioning. Nonlinguistic
vocalizations are a primary means of communication, as they appear early in ontogenesis;
newborns express and understand emotions vocally long before learning language
(Fecteau, Arrnony, Joanette, and Belin, 2005).

Children as young as a few months old have been shown to be able to
discriminate happy and sad faces from surprised faces, and also to discriminate between
different intensities (Herba and Phillips, 2004). The recognition of facial expressions
develops slowly over the first 2 years of life, and the infant’s understanding of facial
expressions is still quite rudimentary (Nelson, 1987). The preschool age appears to be an
important time during which many emotional skills develop, such as identification and
labeling of emotions (Smith and Walden, 1998).

Young children’s understanding of emotion constitutes a key early component of
their social cognition, because they so frequently draw on this understanding in the

course of social interaction (Denham, Zoller, and Couchoud, 1994). The difficulty that

young children experience in producing and judging some of the more basic facial
expressions may be due to the child’s inability to comprehend the full social meaning of
the facial expression and its corresponding label (Shields and Padawer, 1983).
Nevertheless, children are not as proficient as adults at processing faces (Mondlock,
Geldart, Maurer, and Le Grand, 2003).

Sociocognitive theories propose that with age there is an increased ability to
understand and regulate emotions, because of increasing optimization of positive mood
states and increased skill at understanding cues to emotional meaning (Phillips, MacLean,
and Allen, 2002). Adults are experts in face processing; they can recognize thousands of
individual faces rapidly and accurately, they can easily decipher various cues, such as
emotional expression and direction of gaze (Mondlock, Geldart, Maurer, and Le Grand,
2003). Research on adults suggests that misinterpretation of nonverbal cues such as
facial expression may contribute to such social impairments in patients with mood
anxiety disorders (McClure, Pope, Hoberman, Pine and Leibenluft, 2003).
Discrimination of Facial Expressions and Social Interactions

Behavior Regulation

Emotions play a central role in the organization of individual behavior and social
interaction because emotions expressed by a partner suggest the need to alter, maintain,
or terminate a particular behavior (Garner, 1997). When individuals interact with one
another, it is vital that they are able to accurately interpret other people’s nonverbal cues.
Nonverbal behavior is essential to social interaction because it offers dependable
information about how individuals are feeling (Collins and Nowicki, 2001). A person

who experiences difficulties in processing nonverbal cues increases the chances of

consistently experiencing negative social interactions. Learning to affectively read the
nonverbal expression of others will help to facilitate more positive interactions.

Facial expressions provide important clues about emotions in the absence of
information about the situation, or in the case of (display rules, when the actual meaning
of the emotion is disguised by verbal content (Garner, 1999). The ability to read
emotions in facial expressions and tones of voice are skills necessary for children to
develop “healthy” interactions and successful relationships (Nowicki and Mitchell,
1998). The importance of accurately identifying facial expressions of emotion begins
early in life. The identification of emotion in facial expressions and tones of voice has
been found to be associated with social competence in children from 2 to 12 years of age
(Collins and Nowicki, 2001 ). Emotion knowledge may influence behavior, especially in
emotionally arousing situations that require behavioral regulation (Smith and Walden,
2001).

Some children, adolescents, and adults with various psychological and psychiatric
disorders recognize facial expressions less proficiently than their peers in the general
population (Ellis, 1997). Studies have found that higher rates of social anxiety were
predictors of diminished accuracy in children’s classifications of images of other
children’s expressions of emotions (Battaglia, 2004). Other studies with adults also have
found that adults with anxiety disorders or depression exhibit deficits in identification of
facial expressions.

Some researchers have found that there are no significant differences between the
capability of children with externalizing disorders versus internalizing disorders in

correctly identifying the emotions anger, fear, surprise and happiness in facial displays

(Ellis, 1997). Children with externalizing disorders were more accurate in the
identification of sadness and disgust (Ellis, 1997). Overall, research has found that
children with mood disorders are more accurate at identifying sadness and anger than
children with no mood disorders.

Interpreting and responding appropriately to facial expressions of emotion are
important aspects of social skills (Ellis, 1997). There are several constructs (e.g.,
temperament, emotion knowledge, social problem-solving skills, and emotion
socialization) that are linked conceptually and empirically to behavioral regulation (Smith
and Walden, 2001). Behavior regulation has been shown to involve the aptitude to act in
response to the constant demands of the circumstance in a socially acceptable way.
Consequently, behavior regulation could be related to the development of social problem-
solving skills. If children are better equipped to decipher others’ nonverbal cues, they
will be more able to respond to peers and engage in social interaction in an appropriate
manner (Grinspan, Hemphill and Nowicki, 2003).

Social problem solving

Individuals who are deficient in emotional understanding are deprived of
important social information which makes it difficult for them to respond to others and
less likely that others will respond to them in a positive way (Garner, 1997). Children’s
social problem-solving skills appear to be related to their general level of emotional
competence as well as to more specific intrapersonal factors (Smith and Walden, 1998).
Children who do not interpret nonverbal information accurately must handle accumulated
negative reactions that may predispose them to develop personal and interpersonal

difficulties (Nowicki and Duke. 1992).

The control that children gradually gain over their emotional expression has
important consequences for communication between children (Gosselin, 2002).
Understanding emotion allows children to state their own feelings, to understand
feedback on these feelings, and to more completely process causal associations between
events and emotions (Hesse, 1982). Difficulties decoding emotional facial expressions
and vocal prosody have been shown, for instance, to relate positively to low peer-rated
sociemetric status among preschoolers (McClure, 2001). Children who have learned to
process nonverbal information have an advantage over less nonverbally adept peers in
beginning and maintaining relationships (Nowicki and Mitchell, 1998).

Measures of social information processing have been developed and found to
correlate with antisocial behavior both at the level of the single aggressive act as well as
at the level of enduring individual differences (Dodge, 1997). Students who have
difficulty with social skills because they do not understand nonverbal communication
tend to have family relationship problems, trouble with teacher interactions, fewer
friends, and low self-esteem (Sprouse, Hall, Webster, and Bolen, 1998). Nonverbal
processing difficulties increase the likelihood that children’s social interactions will fail
and will produce negative self-evaluation and feelings (Nowicki and Carton, 1997).

Age will affect the ability to understand emotions; however, the direction of the
predicted age effect is different depending on which theoretical stance is adopted.
Sociocognitive approaches suggest that there should be age-related improvement in the
ability to understand others’ emotions. The ability to decode facial expressions is an
important component of social interaction because of the significant role of facial

information in the appropriate modification of social behaviors (Herba and Phillips,

2004). The ability to interpret emotional cues has been argued to play an important role
in maintaining successful relationships and healthy psychological functioning (Phillips et
al., 2002).

Cultural Characteristics

Early pioneers focused on documenting aspects of universality in emotional
judgments rather than on exploring the cultural differences that emerge in these same
data. Rather than arguing for universality or cultural specificity in the communication of
emotions, to the exclusion of the other, recent work has incorporated some elements of
both into an interactionist perspective (Elfenbein and Ambady, 2003). When looking at
the expression and recognition of emotion, there may be aspects of universality as well as
cultural differences. Just as emotional expression may be a universal “language,”
different “accents” or “dialects” may vary in subtle ways across cultures (Elfenbein and
Ambady, 2003).

Researchers studying emotion recognition have extensively documented both
cultural similarities and differences (Elfenbein, 2002). Although cultural differences may
be described in terms of forms of expression, they also may be described in terms of
accuracy with which such expressions are interpreted (Weathers, Frank, and Spell, 2002).
Therefore, it is not a contradiction to say that the expression of emotion is largely
universal but there are subtle differences across cultures that can create a challenge for
effective communication (Elfenbein, 2003).

Cultural variations

It seems that emotions are recognizable at above-chance levels across cultures,

but there also are cultural variations in emotion recognition accuracy (Elfenbein and

Ambady, 2003). There are a number of reasons why individuals may generally be more
accurate at recognizing expressions by members of their own ethnic group (Beaupre and
Hess, 2005). According to dialect theory, there are cultural differences in the appearance
of emotional expressions resulting from the specific affect (Elfenbein, 2003). Similarly,
other research also has demonstrated that individuals perceive communication of affect
from members of their own ethnic group more accurately than they do from members of
another ethnic group (Weathers et al., 2002). Individuals tend to interpret another
individuals’ behavior in terms of what they would have intended if they had used the
same expression (Elfenbein, 2003).

ln-group advantage

The definition of the in-group advantage is that perceivers’ emotion judgments
are more accurate with culturally matched than culturally mismatched materials
(Elfenbein, 2003). Members of the same race (i.e., Caucasians) accurately interpreted the
affective expressions of members of their own race, whereas the members of another
racial group (i.e., African Americans) did not interpret the same stimuli with the same
degree of accuracy (Weathers et al., 2002). This in-group advantage has been seen across
a range of experimental methods and nonverbal channels of communication, as well as
across each of the basic emotions, both positive and negative (Mandal and Ambady,
2004).

Just as there is an in-group advantage for understanding speech, cultural
differences could lead to an in-group advantage in emotion recognition. Specific
appearances of facial expressions may differ among cultures, as is the case for other

forms of nonverbal behavior (Marsh, 2003). There may be subtle differences in

10

expressive style between members of different cultural groups that make it more difficult
to decode expressions by cultural out-group members (Beaupre and Hess, 2005). Subtle
differences in expressive behavior across cultures can lead to greater ability in
understanding emotions expressed in a familiar style (Elfenbein and Ambady, 2003).
Certain components of emotion identification and recognition are universal; however
some expressions of emotion may lose their meaning across cultural boundaries.
Individuals generally pay attention to the cues that are particularly diagnostic for
members of their own ethnic group. However, these same cues may not assist as clearly
in distinguishing among faces of out-group members (Elfenbein and Ambady, 2003).
Some researchers have found evidence that emotions may be more accurately
understood when they are judged by members of the same national, ethnic, or regional
group that had expressed the emotion. This in-group advantage indicates that culture can
have an important role in shaping our emotional communication (Elfenbein and Ambady,
2002). The in-group advantage is lower when groups are nearer geographically or have
greater cross-cultural contact with each other, and over time participants appear to learn
how to understand the emotions of people from foreign cultures (Elfenbein, 2003).
Culture plays a role in understanding expression of facial emotion and
expressions of emotion are a natural outgrowth of cultural learning (Mandal and
Ambady, 2004). There is a relationship between how culture influences a person’s
capacity to identify emotion. Stevens, Charrnan and Blair (2001) found that children
with psychopathic tendencies showed impaired ability to recognize sad and fearful facial
expressions. MacLeod and Matthews (1988) found that social anxious adults had

problems in decoding facial expressions of emotions.

11

Research Hypotheses

This study utilizes the Diagnostic Analysis of Nonverbal Accuracy (DANVA) in
order to attempt to answer two research objectives. As a part of the DANV A, there are a
set of African American faces and Caucasian faces. The African American faces portion
of the DANVA does not have an answer key. Therefore, in order to utilize both portions
of the DANV A, this study must first create an accurate answer key for the African
American faces portion of the DANVA.

Based on the literature, researchers now believe that there may be aspects of
universality as well as cultural differences in emotion recognition. We also know that the
identification of sadness and fear develOp later than happiness and anger. This study
would first like to explore if there are cultural differences and/or an in-group advantage in
the perception of emotions. Hypothesis 1a; among adults and children no differences in
identification by ethnicity were expected for the emotions, happiness and anger.
Hypothesis lb; Adult and child identification of the emotions sadness and fear will vary
by ethnicity, such that in-group accuracy will be greater. Hypothesis 1c; Adult
identification of emotions will demonstrate greater accuracy than child identification of
emotions irrespective of ethnicity.

Furthermore the literature tells us that a number of children, adolescents, and
adults with an assortment of psychological and psychiatric disorders identify facial
expressions less skillfully than their peers. Hypothesis 2; among both children and
adults, poor performance in identifying emotions will be positively related to disruptive

and/or impaired behavior

12

Based the literature, the model that I propose for this study looks at the
relationship between culture and emotion identification and how internalizing and
externalizing behavior (i.e. anxious/depressed behavior and aggressive behavior) are
affected by emotion identification. This relationship is illustrated in figure 1.

Figure l Emotion Identification Model

 
     
   
   
 

Intemalizing
Behavior
(Anxious!

Depressed)

Emotion

Identification

 

Extemalizing
Behavior

(Aggression)

 

Chapter 2
Methodology

Data Sources

This study uses two separate data sets; one data set contains preschool aged
children involved in a program called Passport. The second data set contains college
aged students who participated in an online study. The preschool aged data source for
this study comes from evaluation research of the Ready, Set, Grow, Passport program in
Flint, Michigan (Barnes, 2003). The primary caregiver (usually the mother) and their 3-4
year old children were interviewed at their home by Michigan State University graduate
and undergraduate students (see Appendix A).

In the online dataset, adult participants signed up by going to the “Human
participants in research” web page for the Department of Psychology at Michigan State
University (MSU). In undergraduate psychology classes, research participation is
required and/or an opportunity for extra class credit. Once participants enter the
Department of Psychology research website, they sign up to complete an online study
(see Appendix B).

Participants

In the Passport dataset, participants were 105 three to five year-old children 53
(51%) boys, 52 (49%) girls) and their caregivers. The child participants’ ages ranged
from 43 to 64 months. The average age was 52.6 months. Eight children were excluded
from the analyses because of prior brain injury, clinical psychiatric disorder, language

difficulty, and refusal to complete tasks.

l4

Table 1

gamble Characteristics of Child Participants (Passport Datiset)

 

 

N = 97 %
Ethnicity .
Caucasian/non-Hispanic 44 45.4
Black/non-Hispanic 50 51 .5
Other 3 3.1
Gender
Male 47 48.5
Female 50 51.5
Age
43-47 months 18 18.5
48-52 months 31 32
53—64 months 48 49.5

 

The adult participants in the online sample consisted of undergraduate students at
Michigan State University, who were enrolled in various undergraduate level psychology
classes. Data were collected from 1,312 students ranging in age from 18 to 31. There
were 336 (26%) males and 976 (74%) female participants. With one participant not
reporting there age, the average age was 20.4 years old. The students who participated in
the study were asked to select the race that best fit them. The racial breakdown consisted
of 1,083 Caucasian/non-Hispanic, 111 Black/non-Hispanic, 73 Asian, 41 Hispanic or
Latino, 13 Native Hawaiian or Pacific Islander, 27 Native American, 16 Indian, and 21
Middle Eastern. For this project, analyses were only run on the Caucasian/non—Hispanic
and Black/non-Hispanic groups, due to low number of participants in the other racial

groups.

15

Table 2

Sample Characteristics of Adult Participants (Online study Dgset)

 

 

 

N = 1312 %
Ethnicity
Caucasian/non-Hispanic 1082 82.5
Black/non-Hispanic 1 1 1 8.5
Asian 73 5.6
Hispanic or Latino 41 3.1
Native Hawaiian or Pacific 13 1.0
Islander
Native American 27 2.]
Indian 16 1.2
Middle Eastern 21 1.6
Gender
Male 336 25.5
Female 976 74.4
Age
18-21 1215 92.7
22-25 84 6.4
26—31+ 12 0.9
Procedures

Passport interviews were conducted in the homes of families with young children.
One graduate student and one undergraduate student worked simultaneously with the
mother and child. Passport interviewers explained the content of the interview and the
research objectives to the mother. Mothers were informed of the voluntary nature of
participation and the confidentiality of data. Informed consent was obtained from all
participants prior to interviewing. The interviewers completed multiple training sessions
(a total of 10 hours) to ensure consistent administration of the interview.

The online study could be completed from the students’ personal computer or on

the MSU campus. They were asked to identify emotions from photographs of children

16

producing facial expressions of happy, sad, mad, and scared. They were asked questions
concerning adaptive functioning, substance use, internalizing behavior problems, and
externalizing behavior problems. Students participated in this study in order to fulfill
research requirements or to receive extra credit for class.

Measures

The primary purpose of this study is to construct an accurate answer key for the
African American faces portion of the DANVA. The study also seeks to examine if an
individuals’ behavior related to their ability to correctly identify expressions of emotion.
The study also seeks to gain knowledge of cultural variations in the ability to understand
the adult and child responses to facial expressions.

The Diagnostic Analysis of Nonverbal Accuracy (DANVA) is a screening tool for
determining nonverbal processing capability. A unique feature of the DAN VA is that it
presents stimuli that can be recognized by most as communicating a particular emotion.
Scores are calculated according to the accurate or inaccurate recognition of the emotion
presented. A low score indicates less frequent accurate identification of emotions and
reduced nonverbal processing ability. The DANVA consists of receptive and expressive
subtests that measure nonverbal processing in children. There are four receptive sections:
facial expressions, postures, gestures and tones of voice. There are three expressive
sections: facial expressions, gestures and tones of voice. The subtests sample emotions
(happiness, sadness, anger, and fear) necessary for daily interpersonal functioning.

In this study, the Child Faces portion of the DANVA was used; this consists of 48
(24 Caucasian and 24 African American) color photographs of children displaying four

emotions: happiness, sadness. anger, and fear. Each emotion grouping encompasses six

17

photographs (for each individual race), with three photographs showing high intensity
expressions and three showing low intensity expressions. In order to make sure that
items worked across age groups, an 80% agreement rate for older and younger
participants was required.

The Child Behavior Checklist (CBCL) (Achenbach and Edelbrock, 1981) was
generated from the Revised Behavior Problem Checklist (Quay and Peterson, 1987) and
other behavior checklists. It is composed of 112 items that each significantly
differentiates clinically-referred from non-referred children.

The CBCUIVz-S assesses parents’ perceptions of 99 problem items plus
descriptions of problems, disabilities, what concerns parents most about their child, and
the best things about the child. In this study, the internalizing sub-scale and the
externalizing sub-scale were used. For the Intemalizing group, this study focused on the
Anxious/Depressed sub-scale. For the Extemalizing group. this study focused on the
Aggressive Behavior sub-scale.

Individual item intraclass correlations (ICC) of greater than .90 were obtained
“between item scores obtained from mothers filling out the CBCL at 1-week intervals,
mothers and fathers filling out the CBCL on their clinically-referred children, and three
different interviewers obtaining CBCLs from parents of demographically matched triads
of children.” Stability of ICCs over a 3-month period was .84 for behavior problems and
.97 for social competencies. Test-retest reliability of mothers’ ratings was .89. Several
studies have supported the construct validity of the instrument. Tests of criterion-related

validity using clinical status as the criterion (referred/non-referred) also support the

18

validity of the instrument. Importantly, demographic variables such as race and SES
accounted for a relatively small proportion of score variance.

The Adult Behavior Checklist (ABCL) has 127 items that describe specific
behavioral and emotional problems. The profiles for scoring the ABCL include normed
scales for adaptive functioning, empirically based syndromes, substance use,
Intemalizing, Extemalizing, and Total Problems. The Intemalizing group problems
include those within the individual, such as anxiety, depression, somatic complaints
(without medical cause) and social withdrawal. The Extemalizing group includes
problems that arise between the individual and others, such as aggression, rule-breaking,
and intrusive behavior.

In this study, the internalizing sub-scale and the externalizing sub-scale were
used. In the Intemalizing group, this study focused on the Anxious/Depressed sub-scale.
This sub-scale consists of eighteen items that ask questions about feelings of loneliness,
nervousness and thoughts of suicide. The total possible scores for this scale range from
18 to 36. For participants who are 18-35 years of age, the clinical range begins with a
score of 20. For participants who are 36-59 years of age, the clinical range begins with a
score of 19. For the Extemalizing group, this study focused on the sub-scale Aggressive
Behavior. This sub-scale consists of fifteen items that ask questions about behavior
changes, temper and impatience. The total possible scores for this scale range from 15
being the lowest possible score to 30 being the highest possible score. For participants
who are 18-35 years of age, the clinical range begins with a score of 18. For participants

who are 36—59 years of age, the clinical range begins with a score of 14.

19

The test-retest reliability for the adult forms was between .80 and .90 for most
scales, with none less than .71. Good internal consistency was found for most scales,
with the average alpha coefficients on the ABCL of .83 and .85 for empirically based
problems scales and .78 and .79 for the DSM-oriented scales. The mean Q correlation
between ABCL problem items was .30. Substantial long-terrn stability of scores was
indicated by rs ranging from .69 over a 2-year interval, to .58-.60 over 39-44 months, and
43-53 over 10 years.

Analysis Strategy

In order to create an accurate answer key for the African American faces portion
of the DANVA, the construct validity process used by the creators of the DANV A was
used. The photos also were coded using Izard’s AFFEX system (Izard, Huebner, Risser,
and Dougherty, 1980) in order to identify and rate intensity for the twenty-four African
American photos (see Appendix C for the rating sheet).

For the identification of happy (Enjoyment-Joy in AFFEX), the experimenter
looked for eyebrows in a normal or resting position, raised cheeks, and a mouth drawn up
and back. If the child displayed three of the three facial movements, the expression was
rated as very detectable. If the child produced two of the three facial movements, the
expression was rated as somewhat detectable. If the child produces only one of the facial
movements, the expression was rated as barely detectable.

For the identification of angry/mad (Anger-Rage in AFFEX), the experimenter
looked for eyebrows that were drawn down and together, broadened nasal root, narrow or
squinted eyes, raised cheeks, and a closed mouth with lips pressed tightly together or

clenched teeth. If the child displayed all of these facial movements, the expression was

20

rated as very detectable. If the child produced three or four of the five facial movements,
the expression was rated as somewhat detectable. If the child produced only one or two
of the facial movements, the expression was rated as barely detectable.

For the identification of sad (Sadness-Dejection in AFFEX), the experimenter
looked for inner comers of the eyebrows that were raised and eyebrows triangular,
narrowed nasal root, upper eyelid pulled up at the inner comers with narrowed/squinted
eyes, open or closed mouth with lips drawn downward and outward, upper lip pushed
upward. If the child displayed all of these facial movements, the expression was rated as
very detectable. If the child produced three or four of the five facial movements, the
expression was rated as somewhat detectable. If the child produced only one or two of
the facial movements, the expression was rated as barely detectable.

For the identification of afraid/scared (Fear-Terror in AFFEX), the experimenter
looked for straight or normally shaped eyebrows that were slightly raised and together,
narrowed nasal root, raised eyelids with eyes wide open, and an open mouth with the
comers of the lips retracted straight back. If the child displayed all of these facial
movements, the expression was rated as very detectable. If the child produced three of
the four facial movements, the expression was rated as somewhat detectable. If the child
produced only one or two of the facial movements, the expression was rated as barely
detectable.

Although judgments based on AFFEX are not completely free of subjective
factors, careful training in applying AFFEX allows the researcher to apply a systematic
method of identifying emotion. Once the rating sheet was created, three AFFEX trained

researchers individually rated each photo using the form. The three researchers then

21

came together and reevaluated any photos that did not have complete agreement. The
next chapter will contain the results of the analysis for both the child and adult data
relative to the DANVA. The individual results for the participants will be divided by

race and each of my hypotheses will be tested.

22

Chapter 3
Results

In this chapter, I will present analyses of my research objectives as described in the
previous chapter. For the first research objective: identifying and possible cultural
differences and/or an in-group advantage in the perception of emotions. There was a
comparison done between the African American and Caucasian students’ ability to
correctly identify the emotions happy, sad, mad and scared. Because of their small
sample sizes, other ethnicities were not a part of the data analyses. Using the African
American code sheet that was created as well as the Caucasian Code sheet, that was
provided; the students’ answers were recoded as correct or incorrect for the forty-eight
DANVA photos. Then a total score for each emotion category was computed and put
into two groups of pictures. Finally, in order to compare the sample means a One-way
ANOVA was used for each set of photos.

Regression analyses were run for identifying if emotion is related to internalizing
(anxiety/depression) and externalizing (aggression) behaviors in young adults. First, the
student’s internalizing (anxiety/depression) scale and externalizing (aggression) scale
sores were totaled. Next, a regression analysis was run for the African American faces,
which included race and the total score for each emotion scale score. Then the regression
analysis was then run a second time, using the Caucasian faces.

African American Faces Code Sheet

An answer key for the African American faces portion of the DANVA was
created using Izard’s AFFEX system. Based on the AFFEX system ratings, there were
three photos that were identified as sad/mad ambiguous photos. Due to the ambiguity of

these the three photos, they were not computed in the total score. Also, one happy face

photo was not computed in the total scores, in order to balance the instrument (see
Appendix D). For the Caucasian faces, there is one photo that used an Asian child for the
happy face. This photo was not used in order to not bias the results of the sample (see
Appendix E).

The following three figures will show a graphical representation of the average
correct identification of emotion percentages for the child sample. The first graph for
will look at how Caucasian and African American participants did overall for all of the
DANVA photos. The second and third graph for each sample compares how Caucasian
and African American participants scored on Caucasian only and African American only
photos. When looking at both figure 2 (black/white children viewing entire DANVA)
and figure 4 (black/white children viewing only Caucasian photos) there appears to be a
large difference between the correct identification of the sad emotion.

Figure 2 Average Correct Identification of Emotion by Race: Child Sample

 

 

 

 

 

 

 

 

Happy Sad Mad Scared

 

L I African American Participants El Caucasian Participants

 

24

Figure 3 Correct Identification of Black Faces by Race: Child Sample

 

100-.

 
   
  
  
  
 

 

801

 

60-...
40
20- ~ f

 

 

0.

Happy Sad Mad Scared

 

l I African American Participants El Caucasian Participants ]

 

Figure 4 Correct Identification of White Faces by Race: Child Sample

 

100-,
80-

60-!

 

 

 

Happy Sad Mad Scared

 

I African American Participants El Caucasian Participants

 

25

The next three figures will show a graphical representation of the average correct

identification of emotion percentages for the adult sample. The first graph for will look

at how Caucasian and African American participants did overall for all of the DANVA

photos. The second and third graph for each sample compares how Caucasian and

African American participants scored on Caucasian only and African American only

photos. When looking at figure 6 (black/white children viewing only African American

photos), there appears to be a large difference in the identification of the scared emotion.

When looking at figure 7 (black/white children viewing only Caucasian photos), there

appears to be a large difference in the identification of the mad emotion.

Figure 5 Average Correct Identification of Emotion by Race: Adult Sample

100

80

60

 

Happy Sad Mad Scared

 

I African American Participants El Caucasian Participants

 

26

Figure 6 Correct Identification of Black Faces by Race: Adult Sample

 

Happy Sad Mad Scared

 

I 3 African American Participants D Caucasian Participants I

 

Figure 7 Correct Identification of White Faces by Race: Adult Sample

 

Happy Sad Mad Scared

 

I African American Participants 13 Caucasian Participants I

 

27

Cultural dtfi‘erences and in-group advantages

Child Sample

For the overall DANVA, there was a significant difference between the African
American and Caucasian children participants for the identification of sadness. The
Caucasian participants were significantly more accurate than African American
participants at the identification of sadness in the DANVA (see table 3).

For all of the DAN VA photos, the sad emotion total had a medium effect size
(Cohen’s d). Cohen’s d is the difference between the means, Ml — M2, divided by
standard deviation, 3, of either group. Cohen defined effect sizes as “small, d = .2,”
“medium, d = .5,” and “large, d = .8” (Cohen, 1988).

Table 3

Analysis of Variance of Child Sample by Race: DANVA All Photos

 

 

 

 

 

Source Df SS F Effect Size
Happy
Between Groups 1 4.87
Within Groups 77 251.73 1'49 '27
Sad
Between Groups 1 64.57 *
Within Groups 81 617.10 8'48 '64
Mad
Between Groups 1 1.40 16 09
Within Groups 73 628.28 ' '
Scared
Between Groups 1 .17
Within Groups 73 773.11 '02 '03
All Emotions
Between Groups 1 126.08
Within Groups 61 2688.15 2'86 '43

 

Note. *p < .05, Effect size used was Cohen’s d

28

In the results from the One-Way ANOVA for the African American faces, there
were no significant differences found between the African American and Caucasian
participants for any of the emotion totals (see table 4).

Table 4

Analysis of Variance of Child Sample by Race: DANVA African American Faces

 

 

 

 

 

Source Df SS F Effect Size
Happy
Between Groups 1 .19 21 11
Within Groups 81 73.33 ° °
Sad
Between Groups 1 2.63 95 21
Within Groups 82 227.51 ' '
Mad
Between Groups 1 3.61 1 15 23
Within Groups 83 260.08 ' '
Scared
Between Groups 1 .04 01 03
Within Groups 78 209.95 ' '
All Emotions
Between Groups 1 13.04
Within Groups 71 889.49 1'04 24

 

Note. *p < .05, Effect size used was Cohen’s d

For the Caucasian faces portion of the DAN VA, there were significant differences
between the African American and Caucasian participants for the identification of the
emotions happy, sad and the overall emotion total. The Caucasian participants were
significantly more accurate than African American participants at the identification of
these three emotion totals in the Caucasian faces (see table 5).

Both the happy emotion total and the overall emotion total have medium effect

sizes (Cohen’s d). For the sad emotion total, there is a large effect size.

29

Table 5

Analysis of Variance of Child Sample by Race: DANV A Caucasian Faces

 

 

 

 

 

Source Df SS F Efiect Size
Happy
Between Groups 1 5.34 *
Within Groups 80 81.05 5'28 '52
Sad
Between Groups 1 42.41 *
Within Groups 82 174.58 19°92 '97
Mad
Between Groups 1 .95 33 13
Within Groups 74 213.30 ' '
Scared
Between Groups 1 .27
Within Groups 76 287.02 '07 '06
All Emotions
Between Groups 1 68.24 *
Within Groups 66 944.63 4'77 '53

 

Note. *p < .05, Effect size used was Cohen’s d

Adult sample

For the overall DANVA, there was a significant difference between the African

American and Caucasian adult participants for the identification of the sad, scared and

overall emotion totals. The Caucasian participants were significantly more accurate than

African American participants at the identification of the sad, scared and overall emotion

totals in the DANVA (see table 6). For all of the DANVA photos, the small effect size

(Cohen’s (1) indicates that the significant difference in this group is due primarily to the

large sample size.

30

Table 6

Analysis of Variance of Adult Sample by Race: DANV A All Photos

 

 

 

 

 

Source Df SS F Effect Size

Happy
Between Groups 1 .186 .38 .07
Wrthrn Groups 1176 572.23

Sad

TREES? 11177 2195334 509* 23

Mad
Between Groups 1 6.92 3.10 .15
Wrthm Groups 1176 2624.95

Scared
Between Groups 1 5.74 3.89* .17
Within Groups 1173 1732.59

All Emotions

Bfliiifiéi‘gf “‘73 107552.563 848* 27

 

Note. *p < .05, Effect size used was Cohen’s d

In the results from the One-Way ANOVA for the African American faces, there

was a significant difference between the African American and Caucasian participants for

both the sad and scared emotion totals. The Caucasian participants were significantly

more accurate than African American participants at the identification of sad and soared

in the African American faces (see table 7). There are no other significant differences in

emotion identification for any of the other three emotions totals (happy, mad and overall)

for the African American faces.

This significant difference is due primarily to the large sample size. There is a

significant difference, but it is not a practical difference.

31

Table 7

Analysis of Variance of Adult Sagple by Race: DANVA African American Faces

 

 

 

 

 

Source Df SS F Efi’ect Size
Happy
Between Groups 1 .003
Within Groups 1176 369.86 '008 '00
Sad
Between Groups 1 5.204 425* .21
Within Groups 1177 1442.78
Mad
Between Groups 1 3.13 2 46 15
Within Groups 1176 1499.38 ' '
Scared
Between Groups 1 8.329 *
Within Groups 1176 685.79 1428 '33
All Emotions
Between Groups 1 12.13
Within Groups 1175 4234.46 3365 17

 

Note. *p < .05, Effect size used was Cohen’s d

For the Caucasian faces portion of the DAN VA, there was a significant difference
between the African American and Caucasian participants for the identification of both
the mad and overall emotion totals. The Caucasian participants were significantly more

accurate than African American participants at the identification of the mad and overall

emotion totals in the Caucasian faces (see table 8). The significant differences in this

group can also be explained by the large sample size.

32

Table 8

Analysis of Variance of Adult Sample by Race: DANV A Caucasian Faces

 

 

 

 

 

Source Df SS F Effect Size
Happy
Bvi/tirviiiiinccibiiiigs 1 1176 165341 4 1'64 '08
Sad
Between Groups 1 .595 1.68 .13
Wrthrn Groups 1177 416.199
Mad
BfiiivhiinGfibilpis l 1176 . 81496355299 2589* '46
Scared
Between Groups 1 .321 .51 .07
Wrthrn Groups 1174 733.910
All Emotions
Between Groups 1 26.034 9.16* .28
Wrthrn Groups 1174 3337.659

 

Note. *p < .05, Effect size used was Cohen’s d

When examining the data from the child participants, the only significant

differences that were found, were for the Caucasian faces and the overall DANVA.

Caucasian participants were significantly more accurate than African American

participants at the identification of the emotions sad, scared and the overall emotions.

When examining the data for the adult participants Caucasian participants were

significantly more accurate than African American participants at the identification of

various emotions. However, after reviewing the effect size, it was found that these

differences were primarily an artifact of sample size.

33

Emotional Competence

Multiple regression was performed for both the internalizing scale
(anxiety/depression) and the externalizing scale (aggression). The independent variable
race was placed alone, in the first block of the model. The independent variables (happy
total, sad total, and mad total) were placed together in the second block of the model,
because these are the first emotions that children become proficient in. Finally, the
independent variable scared total was placed alone in the third block, because this is one
of the more difficult emotions for children to learn. Each model was tested to see which
would contribute to a significant change in R2.

Child sample

In the child sample, the correct identification of emotions does not appear to be
related to either the internalizing scale: anxious/depressed (see table 9) or the

externalizing scale: aggression (see table 10).

34

Table 9

Hierarchical Regression Analysis for Child Sample: Anxious/Depression

 

 

Variable R2 R2 Change Beta
Block 1
Race .007 .007 -.086
Block 2
Race -.077
Happy Total -.054
.042 .035
Sad Total .001
Mad Total .201
Block 3
Race -.069
Happy Total -.063
Sad Total .045 .003 .023
Mad Total .215
Scared Total -.057
Note. *p < .05

35

Table 10

Hierarchical Regression Analysis for Child Sample: Aggression

 

 

Variable R2 R2 Change Beta
Block 1

Race .007 .007 -.081
Block 2

Race -.113

Happy Total -.215

.063 .056

Sad Total -.064

Mad Total .170
Block 3

Race -.105

Happy Total -.225

Sad Total .066 .003 -.041

Mad Total .184

Scared Total -.060

Note. *p < .05
Adult sample

For the internalizing scale (anxious/depressed), when controlling for ethnicity,
there is no significant change. The only factor that has any significance is race. On the
race variable, there is a significant Beta value of .064 (see table 11). For the adult
sample, the participant’s race is related to how they will score on the anxious/depression

subscale of the ABCL.

36

Table 1 1

Hierarchical Regression Analysis for Adult Sample: Anxious/Depression

 

 

Variable R2 R2 Change Beta
Block 1

Race .004 .004* .064*
Block 2

Race .065

Happy Total -,045

.009 .005

Sad Total -.041

Mad Total .036
Block 3

Race .066

Happy Total -.042

Sad Total .009 .000 -.038

Mad Total .039

Scared Total -.016

Note. *p < .05

For the externalizing scale (aggressive behavior) the correct identification of the
happy emotion was significant, when controlling for ethnicity. For the model with happy
there is a significant change in the Beta value of -.097. As the correct identification of

happy increases, the probability of reporting aggressive issues decreases (see table 12).

37

Table 12

Hierarchical Regression Analysis for Adult Sample: Aggression

 

 

Variable R2 R2 Change Beta
Block 1
Race .001 .001 -.035
Block 2
Race -.031
Happy Total -.097*
.014 .013*
Sad Total -.050
Mad Total .025
Block 3
Race -.030
Happy Total -.089
Sad Total .016 .002 -.041
Mad Total .035
Scared Total -.048
Note. *p < .05
Summary

In the children who participated in this study, the correct identification of
emotions was not related anxious/depression behaviors and/or aggressive behavior. For
the adults who participated in this study, the correct identification of emotions was not
related to anxious/depression behaviors. The race of the participant does appear to be a
significant factor to the internalizing scale (anxious/depression). For aggressive
behavior, the correct identification of happiness was related to a decrease in aggressive

behavior.

38

Chapter 4
Discussion

In this Chapter I will discuss the findings of the results of my study that were
shown in the previous chapter.
African American Faces Code Sheet

The objective to complete a code sheet for the African American Faces portion of
the DAN VA was successful. Using the AFFEX system, an answer key was developed
for the African American Faces portion of the DANVA. The degree to which each of the
individual affects were expressed based on the presence or absence of appearance
changes in the faces. Each face was given an intensity level rating of high, moderate or
low. After identification of each photo was completed, four photos were removed from
the African American Faces scale.
Cultural differences and in-group advantages

When examining the data from the child participants, there were no significant
differences found in the rate of accurate identification of emotion for the African
American faces portion of the DANVA. For the Caucasian faces and the overall
DANVA, there were significant cultural differences identified. In all of the differences
found, Caucasian participants were significantly more accurate than African American
participants at the identification of the emotions sad, scared and the overall emotions.

When examining the data for the adult participants there were several significant
cultural differences identified. In all of the differences found, Caucasian participants
were significantly more accurate than African American participants at the identification
of various emotions. After calculating the effect size using Cohen’s d, it was found that

these differences were primarily an artifact of sample size.

These findings suggest that the there are some variations between ethnic groups in
relations to the correct identification of some emotions. This study has brought
additional reservations to the idea that the “basic emotions” are completely universal.
Emotional Competence

For the child participants, the correct identification of emotions does not appear to
be related to either the internalizing scale (anxious/depression) or the externalizing scale
(aggressive behavior). There were no significant changes found for any of the models
that were run. This lack of significance could be due to the sample size or the young age
of the children.

For the adult participants, the correct identification of emotions does not appear to
be related to the internalizing scale (anxious/depression). The race of the participant does
appear to be a significant factor related to the internalizing scale (anxious/depression).
Regardless of the correct or incorrect identification of any of the four emotions does not
determine the participants reporting of anxious/depression behavior. The correct
identification of happiness does appear to be related to the externalizing scale (aggressive
behavior). When the happy emotion is identified correctly the participants reporting

aggressive behavior decreases.

4O

Chapter 5
Conclusion

A number of personal and social factors combine to shape an individual’s
perceptions and actions during the nonverbal interaction process; Patterson (1995) terms
these factors determinants (e. g., the individual’s biology, culture, gender, personality),
social environment (e. g., the setting, partner characteristics), and cognitive affective
(mediators goals, affect, expectancies, cognitive resources) (McClure, 2001). Emotion
expressions may not be expressions and may not be related to emotions in any simple
way (Russell et al., 2003).

From a deveIOpmental standpoint this study has found agreement with the current
literature. The children in this study were not as proficient as the adults in correctly
identifying emotions. This finding supports work of researchers such as (Phillips,
MacLean, and Allen, 2002) and (Mondlock, Geldart, Maurer, and Le Grand, 2003).
Their work found that with age comes an increased skill at understanding cues to
emotional meaning; therefore, the ability to understand and regulate emotions improves.
In short, adults are better equipped than children to recognize individual faces quickly,
decode an assortment of cues, and correctly identify emotional expressions. This
understanding may allow preschool teachers to better facilitate positive interactions when
children have conflict or problems with peers.

From a cultural perspective, in both the child and adult samples, it was found that
Caucasian participants were significantly more accurate than their African American
counterparts at the identification of various emotions. This finding contributes to the

theory that identification of emotion is not completely universal. Beaupre and Hess’s

41

(2005) theory that there may be subtle differences between groups is relevant. The issue
of universal emotion identification is complex and needs further exploration.

Overall, the research on nonverbal behavior proposes that the perceived accuracy
of a person’s behavior will persuade the decisions of other individuals towards that
person. In order to contribute to a greater understanding of the bases of normal and
abnormal social deve10pment, future studies will need to consider confounding factors
and sex differences (Herba and Phillips, 2004).

In this study I was able to successfully develop an answer key was developed for
the African American Faces portion of the DANVA. The answer key developed for the
African American Faces portion of the DANVA will contribute to the literature and
future research. Because this study was able to successfully develop a coding system for
this measure, it can now be used in future work with children and adults. This also will
extend the entire DANVA measure, by allowing all of the child photos to be utilized.

Several limitations were identified in this study. Given the secondary data
analysis approach, modification to questions were not possible. In addition, participants
were forced to choose emotions from a predetermined list (happy, sad, mad, or scared);
as a consequence, the participant was not allowed to judge the photos for any other
possible emotion. Another limitation for the adult sample, is the racial breakdown; there
are substantially more Caucasian/non-Hispanics than any other ethnicity. Also, there are
significantly more female subjects than male subjects. Furthermore, because the adult
sample contains only college students, the study may not be generalizable to a diverse

adult p0pulation.

42

There are several modifications that could have been useful to this study. First, it
may have been useful to also add adults outside of the Michigan State University
community. This would have allowed for a sample that could be generalized to the entire
population. Also, the use of families (children and parents) would have allowed us to
look more intensely at how a child’s ability to identify emotion is related to their parent’s
ability.

Furthermore working with young children and their parents could give us an
insight into the development and learning process of emotion identification. For future
research on cultural differences and similarities issues, research should account for
observed differences in emotional communication across cultures. Also, using a
longitudinal design rather than cross-sectional one may possibly shed additional light on

these findings.

Appendix A
Child Interview: DANV A and CBCL

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1. Aches or pains (without medical cause; do not include 0 O O
stomach or headaches)
2. Acts too young for age 0 O O
3. Afraid to try new things 0 O O
4. Avoids looking others in the eye 0 O O
5. Can’t concentrate, can’t pay attention for long 0 O O
6. Can’t sit still. restless, or hyperactive O O O
7. Can’t stand having things out of place 0 0 O
8. Can’t stand waiting; wants everything now 0 O O
9. Chews on things that aren’t edible O 0 O
10. Clings to adults or too dependent O O O
11. Constantly seeks help 0 O 0
12. Constipated, doesn‘t move bowels (when not sick) 0 O O
13. Cries a lot 0 O O
14. Cruel to animals 0 O O
1 5. Defiant O O O
16. Demands must be met immediately 0 O O
17. Destroys his/her own things 0 O O
18. Destroys things belonging to his/her family or other 0 O 0
chrldren
19. Diarrhea or loose bowels (when not sick) 0 O O
20. Disobedient O O O
21 Disturbed by any change in routine 0 O O
22. Doesn’t want to sleep alone 0 O O
23. Doesn’t answer when people talk to him/her 0 O O
24. Doesn’t eat well (please describe on attached
supplemental O O 0
form)
25. Doesn’t get along with other children 0 O O
26. Doesn’t know how to have fun; acts like a little adult 0 O O

 

 

44

 

27.

Doesn’t seem to feel guilty after misbehaving

 

 

 

 

 

28. Doesn’t want to go out of home

29. Easily frustrated

30. Easily jealous

31. Eats or drinks things that are not food—don’t include
sweets (please describe on attached supplemental form)

32. Fears certain animals, situations, or places (please
describe

on attached supplemental form)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

33. Feelings are easily hurt

34. Gets hurt a lot. accident-prone

35. Gets in many fights

36. Gets into everything

37. Gets too upset when separated from parents
38. Has trouble getting to sleep

39. Headaches (without medical cause)

40. Hits others

41. Holds his/her breath

42. Hurts animals or pe0ple without meaning to
43. Looks unhappy without good reason

44. Angry moods

45. Nausea, feels sick (without medical cause)
46. Nervous movements or twitching (please describe on

attached supplemental form)

 

 

 

 

 

 

 

 

47. Nervous, hi gh-strung, or tense

48. Nightmares

49. Overeating

50. Overtired

51. Shows panic for no good reason

52. Painful bowel movements (without medical cause)

53. Physically attacks people

54. Picks nose, skin, or other parts of body (please describe
on

attached supplemental form)

 

55.

Plays with own sex parts too much

 

 

Poorly coordinated or clumsy

 

45

00000

00000000000000

00000000

0

00000

00000000000000

00000000

0

00000

00000000000000

00000000

0

 

57.

Problems with eyes (without medical cause; please
describe

on attached supplemental form)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

58. Punishment doesn’t change his/her behavior

59. Quickly shifts from one activity to another

60. Rashes or other skin problems (without medical cause)

61. Refuses to eat A

62. Refuses to play active games

63. Repeatedly rocks head or body

64. Resists going to bed at night

65. Resists toilet training (please describe on attached
supplemental form)

66. Screams a lot

67. Seems unresponsive to affection

68. Self-conscious or easily embarrassed

69. Selfish or won’t share

70. Shows little affection toward people

71. Shows little interest in things around him/her

72. Shows too little fear of getting hurt

73. Too shy or timid

74. Sleeps less than most children during day and/or night
(please describe on attached supplemental form)

75. Smears or plays with bowel movements

76. Speech problem (please describe on attached
supplemental
form)

77. Stares into space or seems preoccupied

78. Stomachaches or cramps (without medical cause)

79. Rapid shifts between sadness and excitement

80. Strange behavior (please describe on attached
supplemental
form)

81. Stubborn, sullen, or irritable

82. Sudden changes in mood or feelings

83. Sulks a lot

84. Talks or cries out in sleep

85. Temper tantrums or hot temper

86. Too concerned with neatness or cleanliness

 

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87. Too fearful or anxious

 

88. Uncooperative

 

89. Under active, slow moving, or lacks energy

 

90. Unhappy, sad, or depressed

 

91. Unusually loud

 

describe on
attached supplemental form)

92. _ Upset by new people or situations (please

 

93. Vomiting, throwing up (without medical cause)

 

94. Wakes up often at night

 

95. Wanders away

 

96. Wants a lot of attention

 

97. Whining

 

98. Withdrawn, doesn’t get involved with others

 

99. Worries

 

 

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54

Appendix B
DANV A Online Experiment Survey

 

 

1. I am too forgetful.

 

I make good use of my opportunities.

 

I argue a lot.

 

I work up to my ability.

 

I blame others for my problems.

 

1 brag.

 

NP’V‘PWP

l have trouble concentrating or paying attention
for long.

 

9°

I have trouble sitting still.

 

1 am too dependent on others.

 

10. I feel lonely.

 

11. I feel confused or in a fog.

 

12. lcrya lot.

 

13. I am pretty honest.

 

14. I am mean to others.

 

15. l daydream a lot.

 

16. I deliberately try to hurt or kill myself.

 

17. I try to get a lot of attention.

 

18. l damage or destroy my things.

 

19. I worry about my future.

 

20. I break rules at work or elsewhere

 

I'D
—L

. I don’t eat as well as 1 should.

 

22. I don’t get along with other people.

 

23. I don’t feel guilty after doing something I
shouldn‘t

 

24. I am jealous of others.
2 .
26. My relations with opposite sex are poor.

 

O1

1 get along badly with my family.

 

 

27. I am afraid I might think or do something bad.

 

 

OOOOOOOOOOOOOOOOOOOOOOOOOOOO
OOOOOOOOOOOOOOOOOOOOOOOOOOOO
OOOOOOOOOOOOOOOOOOOOOOOOOOOO

28. I feel that l have to be perfect.

 

55

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

29 I feel that no one loves me.

30. I feel that others are out to get me.

31. I feel worthless or inferior.

32. I accidentally get hurt a lot.

33. I get in many fights.

34. My relations with neighbors are poor.
35. I hang around people who get in trouble.
36. I am impulsive or act without thinking.
37. I would rather be alone than with others
38. I lie or cheat.

39. I feel overwhelmed by my responsibilities.
40. lam nervous or tense.

41. I lack self-confidence.

42. I am not liked by others

43 I can do certain things better than other people.
44. I am too fearful or anxious.

45. I feel dizzy or Iightheaded.

46. I feel too guilty.

47. I have trouble planning for the future.
48. I feel tired without good reason.

49. My moods swing between elation and

depression.

 

50.

I have aches or pains (not stomach or
headaches) without known medical cause

 

 

 

 

 

 

 

 

 

51. l have headaches without known medical
cause.

52. I experience nausea or feel sick without known
medical cause.

53. l have rashes or other skin problems without
known medical causes.

54. I have stomach aches without known medical
cause.

55. I experience vomiting, throwing up without
known medical cause.

56. I experience numbness or tingling in body parts
without known medical cause.

57. I physically attack people.

58. I fail to finish things I should do.

 

56

OOOOOOOOOOOOOOOOOOOOOO

O

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O

O OOOOOOOOOOOOOOOOOOOO

O

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O

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

59. There is very little that I enjoy.

60. My work performance is poor.

61. I am poorly coordinated or clumsy.

62. I would rather be with older people than with
people of my own age.

63. I have trouble setting priorities.

64. I refuse to talk.

65. I have trouble making or keeping friends.

66. I scream or yell a lot.

67. I am secretive or keep things myself.

68. I am self-conscious or easily embarrassed.

69. I worry about my family.

70. I meet my own responsibilities to my family.

71. I show off or clown.

72. My behavior is irresponsable.

73. I have trouble making decisions.

74. I stand up for my rights.

75. My behavior is very changeable.

76. I steal.

77. I am easily bored.

78. I am stubborn, sullen or irritable.

79. My moods or feelings change suddenly.

80. I enjoy being with people.

81. I rush into things without considering the risks.

82. I drink too much alcohol or get drunk.

83. I think about killing myself.

84. I talk too much.

85. l tease others a lot.

86. I have a hot temper.

87. I think about sex too much.

88. I threaten to hurt people.

89. I like to help others.

90. I dislike staying in one place for very long.

91. | stay away from my job even when I’m not sick
and not on vacation.

92. I don’t have energy.

 

57

O O OOOOOOOOOOOOOOOOOOOOOOOOOOOO 0 000

O O OOOOOOOOOOOOOOOOOOOOOOOOOOOO 0 000

O O OOOOOOOOOOOOOOOOOOOOOOOOOOOO 0 OOO

 

93. I am unhappy, sad, or depressed.

 

94. I am louder than others.

 

95. People think I am disorganized.

 

96. I try to be fair to others.

 

97. I feel that I can't succeed.

 

98. I tend to lose things.

 

99. I like to try new things.

 

100. I wish I were the opposite sex.

 

101. I keep from getting involved with others.

 

102. I worry 3 lot.

 

103. I worry about my relations with the opposite
sex.

00000000000
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104. I fail to pay my debts or meet other financial
responsibilities.

 

105. I feel restless or fidgety.

 

106. I get upset too easily.

 

107. I have trouble managing money or credit cards.

 

108. I am too impatient.

 

109. I am good at details.

 

110. I drive too fast.

 

111. I tend to be late for appointments.

 

112. I have trouble keeping a job.

 

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113. I am a happy person.

 

0 000000000 0
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114. I hang out with people from different

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193 Isthis chifd.‘

0000

Happy
Mad

Sad
. , ’ Afraid ‘
1 94.. , is irrigcijiiai; "

0000

Happy
Mad

Sad
Afraid

OOOO

. 195.?)‘in1me past 67189711113; 99-811.77.698...116.17.969.51Qéia‘yeeyaaMQMAQeaaay " . ,

None

Once a month

Once every other week
1-2 days a week

3-5 days a week

6-7 days a week

More than once a day
196 in the 35331 6 months, on average, hoiiir afien Elia 'yéu use inhalants (311an you" '
sniff, hug or: breathe to 991 high)? ' , . .. .1 . , .

OOOOOOO

None

Once a month

Once every other week
1-2 days a week

3-5 days a week

6-7 days a week

More than once a day

0000000

70

In the pest 6 months on average, how Efren d‘d you use ofiter drugs (such as
éjcocaine, Meth, PCP)? ,

vvvvvv

m3, ' L.“ r~ a: r-.-- n—I—El-Iu.‘ ~14: vw-I. Ins-Hun. .u-Z u-Wr ”NV-“1.: SAP: Vi“..- xv“! l-‘M’ (ET... ‘4‘? 1'11“..- 211-“ r".'-'L.. J_‘L..-?"-¢,;" .

None

Once a month

Once every other week
1-2 days a week

3-5 days a week

6-7 days a week

More than once a day

0000000

71

Appendix C
Production of Emotions Identification and Rating Scale

#
0

Fill in number of picture (located on back of photo): G or W #
2. Circle the emotion that this picture displays.
3. Mark an (x) next to each expression(s) displayed in the emotion.

Ha

E brows in a normal or restin ition

Raised cheeks

 

Mouth drawn u and back

Very Detectable (high intensity): 3 of 3
Somewhat detectable (moderate intensity): 2 of 3
Barely detectable (low intensity): 1 of 3

 

Sad

lnner corners of the eyebrows that were raised and eyebrows triangular

 

 

Narrowed nasal root

 

Upper eyelid pulled up at the inner corners with narrowed/squinted eyes

 

Open or closed mouth with lips drawn downward and outward

 

 

 

 

Upper lip pushed upward

Very Detectable (high intensity): 5 of 5

Somewhat detectable (moderate intensity): 3 or 4 of 5
Barely detectable (low intensity): 1 or 2 of 5

 

 

Angry/Mad

Eyebrows that were drawn down and together

 

 

Broadened nasal root

 

Narrow or squinted eyes

 

Raised cheeks

 

 

 

 

Closed mouth with lipsjressedghtly together or clenched teeth
Very Detectable (high intensity): 5 of 5

Somewhat detectable (moderate intensity): 3 or 4 oi~ 5

Barely detectable (low intensity): I or 2 of 5

 

 

Afraid/Scared

Straight or normally shaped eyebrows that were slightly raised and together

 

 

Narrowed nasal root

 

Raised eyelids with eyes wide open

 

 

 

 

Open mouth with the corners of the lips retracted straight back.
Very Detectable (high intensity): 4 of 4

Somewhat detectable (moderate intensity): 2 or 3 of 4

Barely detectable (low intensity): 1 of 4

 

72

G01
G02
G03
G04
G05
GOG
G07
G08
G09
G10
G1 1
G12
G13

G14
615
G16
G17
G18
G19
(320
G21
G22
G23
G24

Emotion
Mad
Sad/Mad
Scared
Scared
Happy
Mad
Mad
Scared
Sad
Sad/Mad
Sad

Sad
Sad/Mad

Happy
Happy
Sad
Happy
Scared
Scared
Sad
Mad
Mad

Happy
Happy

Appendix D

DANVA Code Sheet: African American Faces

Intensity
Low
Low
Moderate
Moderate
High
Moderate
Moderate
Moderate
Moderate
Low
Moderate
Moderate
Low

High
High
Moderate
High
High
Moderate
Moderate
Moderate
Moderate
Moderate
High

Comments

Photo is ambiguous and will not be used in analyses

Photo is ambiguous and will not be used in analyses

Photo is ambiguous and will not be used in analyses
Will not use this photo in the analyses, in order to have an equal
number of photos for each emotion in the scale

W01
W02
W03
W04
W05
W06
W07
W08
W09
W10
W1 1

W12
W13
W14
W15
W16
W17
W18
W19
W20
W21
W22
W23
W24

Emotion
Mad

Happy
Happy
Scared
Sad
Sad
Mad
Happy
Mad
Sad
Scared

Happy
Sad

Mad
Scared
Happy
Sad
Scared
Scared
Mad
Sad
Scared

Happy
Mad

Appendix E
DANVA Code Sheet: Caucasian Faces

Intensity (as
provided by Intensity (as rated by

DANVA manual) AFFEX system) Comments
Low High
High High
Low High
Low High
High Moderate
High Moderate
High Moderate
High High
Low Moderate
Low Low
Low Moderate

Low
High
Low
Low
High
Low
High
High
High
Low
High
Low
High

This photo contains the only

Asian child in the 24

photos. It will not be used
Moderate in the analyses

Moderate
Low
Moderate
High
Moderate
High
High
Moderate
Low
Moderate
Moderate
High

74

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