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Rieffe, C., Oosterveld, P. and Meerum Terwogt, M., Novin, S., Nasiri, H. & Latifian, M. (2010). Relationship
between alexithymia, mood and internalizing symptoms in children and young adolescents: Evidence from an
Iranian sample. Personality and Individual Differences, 48, 425 /C0430.
Results and Comments
There are indications for reliability, sufficient factor-structure, and convergent validity, indicating that the
TAS12 could be used for alexithymia measurement in children, especially if the items are rephrased in children’s
language. However, the scale does not cover all alexithymia facets as described by Nemiah and Sifneos (1970),
and more research is warranted.
TAS-12 Sample Items
1.It is difficult for me to find the right words for my feelings (TAS-12).
2.I find it difficult to say how I feel inside (TAS-12 Rieffe).
3.I have feelings that I can’t quite identify (TAS-12).
4.Sometimes I can’t find the words to say how I feel inside (TAS-12 Rieffe).
5.I find it hard to describe how I feel about people (TAS-12).
6.I find it hard to say how I feel about people (TAS-12 Rieffe).
7.I often don’t know why I am angry (TAS-12).
8.I often don’t know why I am angry (TAS-12 Rieffe).
Emotional Awareness Questionnaire (EAQ-30)
(Rieffe et al., 2008 ).
Variable
Rieffe et al. (2007) broadened the alexithymia construct by adding three facets (assumed to be related to alex-
ithymia) to three already accepted alexithymia facets, and developed a children’s self-rating scale: ‘The Emotional
Awareness Questionnaire (EAQ)’ for these six facets, and revised the scale a year later ( Rieffe et al., 2008 ),
resulting in the EAQ-30.
Description
The 30-item EAQ-30 comprises six subscales, three of which are related to facets of the TAS-20 and BVAQ:
‘Differentiating emotions’ (DIF, 7 items); ‘Verbal sharing emotions’ (VERB, 3 items); and ‘Analyzing emotions’
(ANA, 5 items). The other subscales refer to constructs, assumed to be related to alexithymia: ‘Not hiding emo-
tion’ (NHE, 5 items); ‘Bodily awareness’ (BA, 5 items); and ‘Attending to others emotions’ (AOE, 5 items). Items
are written in children’s language, and most have face validity for their facet. However, two items of the DIF sub-
scale refer to the cause of an emotional reaction, and, not to the capacity to differentiate between various emo-
tions. Although 17 of the 30 items are negatively keyed, these contra-indicative items are unequally distributed
over the subscales. Finally the subscale VERB contains only three items.
Sample
The initial sample in the Rieffe et al. (2008) study comprised 403 primary school children ( M510 years,
8 months; SD5.93 months) and 303 secondary school children ( M514 years, 3 months; SD514 months). Data
for 41 participants (with more than 6 missing values) were excluded. The final sample comprised 297 boys and
368 girls.
Reliability
Internal Consistency
Rieffe et al. (2008) reported Cronbach alpha coefficients for the EAQ-30 subscales in the elementary school
sample #.7 (range .64 to .68), and in the high school sample $.7 (range .74 to .77). Lahaye et al. (2011) , as well
as Camodeca and Rieffe (2012) reported comparable alpha coefficients for five different samples.250 9. MEASURES OF ALEXITHYMIA
III. EMOTION REGULATION |
Test/C0Retest
The reported test /C0retest correlations, for the subscales, are low (mean value .48, range .45 /C0.52). However the
interval was in this study one year (Camodeca & Rieffe, 2012).
Validity
Construct/Factor Analytic
A principal components analysis with oblimin rotation produced factor loadings on facets varying between .45
and .72; DIF mean .58, VERB .71, ANA .67, NHE .66, BA .64, AEO .62. No significant cross-loadings were
reported ( Rieffe et al., 2008 ).Lahaye et al. (2011) reported comparable findings. Confirmatory factor analyses
showed adequate fit to the data ( χ2/df51.72 to 2.33, CFI 5.87 to .89, RMSEA 5.04 to .05) for the six-factor
model. Moreover, a multigroup CFA (samples from The Netherlands [ N5665], Belgium [ N5707], and Spain
[N5464]) indicated measurement invariance for the three language versions ( χ2/df51.80, CFI 5.91, RMSEA
5.02) ( Lahaye et al., 2011 ).
Rieffe et al. (2008) present correlations between subscales as found in two samples (primary school N5403,
mean age 10 year 8 month, SD .93 month and secondary school, N5303 mean age 14 year 3 month, SD 14
month). Values ranged between /C0.31 (BA/ANA) to 1.42 (VERB/NHE), mean absolute correlation .19.
Camodeca and Rieffe (2012) found in two samples comparable low to moderate correlations; mean absolute
values .18 & .22, rages /C0.36 (VER/DIF) to 1.36 (VER/NHE) & /C0.37 (ANA/AOE) to 1.48 (VER/DIF).
Criterion/Predictive
Rieffe et al. (2008) presents correlations between the Emotion Awareness Questionnaire subscales. Although
most correlations reached significance (26 out of 30 calculated), many of these were rather low. The results were
satisfactory for the subscale ‘Differentiating emotions’ (all correlations $.3, (range .52 TEIQ to /C0.34 SCL), and
Subscale ‘Bodily awareness’ which produced three correlations $.3 out of the 5 calculated, subscale ‘Verbal
sharing emotions’ produced just one and the other subscales none.
Location
Rieffe, C., Oosterveld, P., Miers, A.C., Meerum Terwogt, M. & Ly, V. (2008). Emotion awareness and internalis-
ing symptoms in children and adolescents: The Emotion Awareness Questionnaire revised. Personality and
Individual Differences, 45, 756 /C0761.
Results and Comments
Internal Consistencies vary, depending on the age groups, from marginal to very acceptable. Factor structure
is adequate. Test /C0retest data are low, but the long interval used could be a factor in these statistics. There are,
further, indications for convergent validity for two subscales. Finally, the low correlations between subscales,
indicating that they measure different domains. However, three subscales do not measure alexithymia directly.
Still, all in all, the EAQ-30 seems a promising instrument for measuring alexithymia in children, but more
research is warranted.
EAQ Sample Items
I am often confused or puzzled about what I am feeling (DIF).
I find it difficult to explain to a friend how I feel. (VERB).
When I am upset about something, I often keep it to myself (NHE).
When I am scared or nervous, I feel something in my tummy (BA).
It is important to know how my friends are feeling (AOE).
When I am angry or upset, I try to understand why (ANA).
FUTURE RESEARCH DIRECTIONS
We have reviewed all scales/measures that were specifically intended to measure alexithymia. The main result
from this review is that concurrent validity is problematic with the exception for that between the TAS-20 and
BVAQ-COG, leaving no other conclusion than that the various scales measure different domains, indicating that
there are various definitions of the alexithymia construct.251 FUTURE RESEARCH DIRECTIONS
III. EMOTION REGULATION |
Although authors slavishly include references to Marty and de M’Uzan (1963) , Nemiah and Sifneos (1970a),
and Sifneos (1973) , almost no-one takes the trouble to read these classics, as is indicated by the fact that for more
than 30 years, references contained the wrong page numbers for Marty and de M’Uzan’s (1963) publication.
Furthermore, while referring to Sifneos (1973) , all authors present either one of two translations for alexithymia
from the Greek: alexis 5not reading, thymos 5mood/emotion, or a 5lack, lexis 5word, thymos 5mood/
emotion). However, the translation Sifneos (1973) gave is: ‘from the Greek alexi 5not working, thymos 5mood/
emotion’.8
The high number of alexithymia scales, with low concurrent validities, have robbed the construct of its import.
Although this is mainly due to ignoring the founding fathers of the construct, it is also the result of the idea that
the content of a construct can change in response to the research results ( Taylor et al., 1997 , p.58), or can be
extended by incorporating other constructs (e.g., Rieffe et al., 2007 ). Although there is something to say for these
views, it results in a Babylonian confusion of tongues. Furthermore, a redefinition of a construct on basis of
research results can only be made if the results are obtained by a scale that measures the original construct reli-
ably and fully. Since there is debate about the measurement, all changes in the definition of the construct are
premature.
Another source of confusion can be found in the history of alexithymia measures that reveals two very differ-
ent approaches. The early measures were made by clinical professionals, and the items were directly related to
the original descriptions of the construct (e.g., Sifneos, 1973 ; Apfel & Sifneos, 1979). However, these authors did
not bother much about the psychometric properties of their scales. Subsequently, measures have been developed
by laying too much trust on psychometric analyses, and not enough on content validity. Items sets were formed,
analyzed with advanced statistical methods, and only those items fulfilling pre-established psychometric require-
ments were selected for the final scale. However, initial sets often contained items referring to constructs
assumed to be related to alexithymia that were sometimes simply taken from scales measuring such other con-
structs (for instance, Taylor et al., 1985 ). Since many of these proxy items survived the selection procedure, the
final measure contained items, and/or factors that were not part of the original descriptions of the alexithymia
construct, resulting in re-descriptions, sometimes even redefinitions of alexithymia, and, thus, in a watering
down of the construct.
There is only one-way to solve these problems: we need general agreement about the alexithymia construct,
only then will it survive and have a future. This means acceptance of the description as presented by Nemiah
and Sifneos, not because these authors introduced the term alexithymia, but since they based their construct on
clinical observations, and the facets distracted out of these observations, should be the starting point of all alex-
ithymia scales. Moreover, it is, for the time being, the only thing we can agree on. Measurement scales should,
thus, cover all facets as mentioned by these authors, nothing less and nothing more. In short, the future of the
alexithymia construct lies in the past.
Acknowledgement
The authors are indebted to Merel Agenant, Lily Menco, Charlotte Ornstein, and Linde van Vlijmen for ordering the literature data, and to
various members of the alexithymia network, who sent us suggestions and information.
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III. EMOTION REGULATION |
CHAPTER
10
Measures of Empathy: Self-Report, Behavioral,
and Neuroscientific Approaches
David. L. Neumann1, Raymond C.K. Chan2, Gregory. J. Boyle3,
Yi Wang2and H. Rae Westbury1
1Griffith University, Gold Coast, Queensland, Australia;2Chinese Academy of Sciences, Beijing, China;3University of
Melbourne, Parkville, Victoria, Australia
The measurement of empathy presents a serious challenge for researchers in disciplines ranging from social
psychology, individual differences, and clinical psychology. Part of this challenge stems from the lack of a clear,
universal definition for empathy. Titchener (1909) used the term to describe how people may objectively enter
into the experience of another to gain a deeper appreciation and understanding of their experiences. However,
contemporary definitions are much more complex and highlight a range of cognitive, affective, and physiological
mechanisms. For example, Batson (2009) noted eight conceptualizations: (a) knowing another’s emotional and
cognitive state; (b) matching the posture or neural response of another; (c) feeling the same as another; (d) pro-
jecting oneself into another’s situation; (e) imagining how another is feeling and thinking; (f) imagining how one
would think and feel in another’s situation; (g) feeling distress for the suffering of another; and (h) feeling for
another person who is suffering. Furthermore, empathy overlaps with related, although distinct, constructs such
as compassion and sympathy ( Decety & Lamm, 2009; Hoffman, 2007; Preston & de Waal, 2002 ).
A review of the major definitions of empathy over the past 20 years reveals that there is no single definition
that is consistently cited; indeed, the multitude of definitions is often cited as a distinct feature of the field (e.g.,
Batson, 2009; Gerdes, Segal, & Lietz, 2010 ). Despite this disparity, some commonality can be seen across defini-
tions, and comprehensive theoretical conceptualizations have been provided (e.g., Preston & de Waal, 2002 ). At a
broad level empathy involves an inductive affective ( feeling ) and cognitive evaluative ( knowing ) process that
allows the individual to vicariously experience the feelings and understand the given situation of another
(Hoffman, 2007 ). Its presence or absence is related to autonomic nervous system activity ( Bradley, Codispoti,
Cuthbert, & Lang, 2001; Levenson & Ruef, 1992 ) and overt behaviors that are augmented by affective intensity
and cognitive accuracy ( Ickes, Stinson, Bissonette, & Garcia, 1990; Plutchik, 1990 ). Further, empathy is a funda-
mental emotional and motivational component that facilitates sympathy and prosocial behavior ( responding com-
passionately )(Thompson & Gullone, 2003 ).
Researchers have used various approaches to measure empathy with instruments dating back to the 1940s
(e.g., Dymond, 1949 ). Largely, as a consequence of the cognitively oriented psychological zeitgeist of the mid-
20th century, empathy measurement was heavily influenced by cognitive approaches, although there were some
notable emotion-based measures (e.g., the Emotional Empathic Tendency Scale; Mehrabian, & Epstein, 1972 ).
Prominent examples of such measures from the mid-20th century include the Diplomacy Test of Empathic
Ability ( Kerr, 1960 ) and Hogan’s (1969) Empathy Scale. In the 1980s to 1990s, social and developmental psycholo-
gists emphasized the multiplicity of empathy in terms of physiologically linked affective states ( Batson, 1987 ),
cognitive processing, or a self-awareness of these feelings ( Batson et al., 1997 ), and emotion regulation ( Eisenberg
257Measures of Personality and Social Psychological Constructs.
DOI: http://dx.doi.org/10.1016/B978-0-12-386915-9.00010-3 ©2015 Elsevier Inc. All rights reserved. |
et al. 1994; Gross, 1998 ). Furthermore, throughout this period physiological measurements, such as skin conduc-
tance and heart rate (e.g., Levenson & Ruef, 1992 ) were increasingly being used. From the 1990’s through to the
present day empathy measurement has been influenced by the development of social-cognitive neuroscience,
although self-report approaches have continued to be developed and extensively used.
Reviews of empathy measures have been provided in the past (e.g., Chlopan, McCain, Carbonell, & Hagen,
1985; Eisenberg & Fabes, 1990 ; Wispe, 1986). The present aim is to provide brief, succinct psychometric reviews
of contemporary empathy measures, and also to expand upon recent reviews on empathy measures constructed
for specific research audiences, such as the measurement of empathy in social work ( Gerdes et al., 2010 ) and
medicine ( Hemmerdinger, Stoddart, & Lilford, 2007; Pedersen, 2009 ). Hopefully, the present chapter will enable
researchers interested in measuring empathy to gain an appreciation of what approaches are available and an
understanding of the benefits and challenges that each of the reviewed measures present. Using a combination of
measures may also counter the criticism that some measurement approaches are narrow in scope ( Levenson &
Ruef, 1992 ).
MEASURES REVIEWED HERE
An extensive search of literature databases (PsycINFO, Social Sciences Citation Index, and Google Scholar),
test manuals and related publications, citation searches of original scale descriptions, and inspection of the refer-
ence lists of relevant reports was carried out. Only measures that were constructed or extensively revised follow-
ing the first edition of this handbook were selected for review (i.e., post-1991). For this reason, questionnaires
that were constructed earlier have not been included even though they have been frequently used in research.
Examples include the Hogan Empathy Scale ( Hogan, 1969 ), the Emotional Empathic Tendency Scale ( Mehrabian
& Epstein, 1972 ), and the Interpersonal Reactivity Index ( Davis, 1983 ). In addition, due to space limitations,
empathy measures designed for specific applications were excluded. Examples of such questionnaires include
the Consultation and Relational Empathy measure ( Mercer, Maxwell, Heaney, & Watt, 2004 ), the Jefferson Scale
of Physician Empathy ( Hojat et al. 2001 ), the Nursing Empathy Scale ( Reynolds, 2000 ), the Autism Quotient
(Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001 ), the Japanese Adolescent Empathy Scale
(Hashimoto & Shiomi, 2002 ), the Scale of Ethnocultural Empathy ( Wang et al. 2003 ), and the Emotional Empathy
Scale ( Ashraf, 2004 ). The measures reviewed here were grouped into three categories: self-report instruments,
behavioral observational methods, and neuroscientific approaches.
Self-Report Measures
1.Balanced Emotional Empathy Scale ( Mehrabian, 1996 )
2.Multidimensional Emotional Empathy Scale ( Caruso & Mayer, 1998 )
3.Empathy Quotient ( Baron-Cohen & Wheelwright, 2004 )
4.Feeling and Thinking Scale ( Garton & Gringart, 2005 )
5.Basic Empathy Scale (Joliffe & Farrington, 2006a)
6.Griffith Empathy Measure ( Dadds et al., 2008 )
7.Toronto Empathy Questionnaire ( Spreng, McKinnon, Mar, & Levine, 2009 )
8.Questionnaire of Cognitive and Affective Empathy ( Reniers et al. 2011 )
Behavioral Measures
1.Picture Viewing Paradigm
2.Comic Strip Task ( Vo¨llm et al. 2006 )
3.Picture Stories ( Nummenmaa, Hirvonen, Parkkola, & Hietanen, 2008 )
4.Kids Empathetic Development Scale ( Reid et al. 2011 )
Neuroscientific Measures
1.Magnetic Resonance Imaging
2.Functional Magnetic Resonance Imaging
3.Facial Electromyography
4.Electroencephalogram
5.Event-Related Potentials258 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
OVER VIEW OF THE MEASURES
Self-report questionnaires include paper-and-pencil measures. Behavioral methods include evaluations of
experimental stimuli and performance on tests. Neuroscientific approaches include brain imaging techniques
(e.g., fMRI) and other measures of central nervous system activity (e.g., electroencephalography, EEG), measure
of facial electromyography (EMG), and autonomic nervous system measures (e.g., skin conductance, heart rate).
Space restrictions limited an extensive discussion of all neuroscientific measures and only some of the more
recent techniques are reviewed. Studies that have used more than one type of measure (e.g., fMRI and self-report
scales; Mathur, Harada, Lipke, & Chiao, 2010; Singer et al. 2004 ) generally show that the different measurement
approaches correlate well with each other.
Balanced Emotional Empathy Scale (BEES)
(Mehrabian, 1996 ).
Variable
The BEES is a unidimensional measure that conceptualizes empathy as an increased responsiveness to
another’s emotional experience. The measure assesses the degree to which the respondent can vicariously experi-
ence another’s happiness or suffering.
Description
‘The Balanced Emotional Empathy Scale (BEES) measures both of the aforementioned components of
Emotional Empathy (i.e., vicarious experience of others’ feelings; interpersonal positiveness) in a balanced way’
(Mehrabian, 1995 /C02010). The 30 items of the BEES are rated on a 9-point Likert-type response scale. The scale
yields a single score with higher scores representing greater levels of emotional empathy. A 7-item Likert-type
abbreviated scale and a French adaptation of the full scale also exist.
Sample
Separate samples of male and female college students were used in the initial construction of the BEES
(Mehrabian, 1996 ).
Reliability
Internal Consistency
Cronbach alpha coefficients for the BEES have been reported as follows: .87 ( Mehrabian, 1997 ), .81 ( Macaskill,
Maltby, & Day, 2002; Shapiro et al., 2004 ), .83 ( Toussaint & Webb, 2005 ), .90 ( Courtright, Mackey, & Packard,
2005 ), .85 ( Smith, Lindsey, & Hansen, 2006 ), and .82 ( Albiero, Matricardi, Speltri, & Toso, 2009 ).
Test/C0Retest
At e s t/C0retest reliability coefficient ( r5.79) was reported by Bergemann (2009) over a six-week interval.
Validity
Convergent/Concurrent
The BEES correlates positively with the Emotional Empathetic Tendency Scale ( r5.77) and with helping
behavior ( r5.31;Smith et al., 2006 ). It correlates positively with the Basic Empathy Scale ( Jolliffe & Farrington,
2006a ) for both males ( r5.59) and females ( r5.70) in an Italian sample ( Albiero et al., 2009 ).LeSure-Lester (2000)
reported that the BEES correlates positively with compliance with house rules ( r5.67) and chores completed
(r5.57). Scores on the BEES are also positively associated with forgiveness of others ( Macaskill et al., 2002 ) and
in a sample of FBI agents, negotiation skills ( Van Hasselt et al., 2005 ). In an fMRI study, BEES scores were posi-
tively correlated with activation of neurons that compose the pain matrix (anterior insula and rostral anterior cin-
gulate cortex, r5.52 and, r5.72 respectively) when participants viewed significant others subjected to pain
(Singer et al., 2004 ).259 OVERVIEW OF THE MEASURES
III. EMOTION REGULATION |
Divergent/Discriminant
Smith et al. (2006) found that the BEES correlates negatively with aggression ( r52.21). Similarly, in a sample
of adolescents, negative correlations were reported between aggression towards peers ( r52.57) and aggression
towards staff ( r52.59) ( LeSure-Lester, 2000 ).Mehrabian (1997) also reported that BEES scores correlated nega-
tively with aggression ( r52.31) and risk of eruptive violence ( r52.50).
Construct/Factor Analytic
A principal components analysis based on the item intercorrelations investigated the structure of the BEES
(see Mehrabian, 1997 ). Although three components had eigenvalues greater than one, it was concluded that a uni-
dimensional structure reflecting emotional empathy provided the most parsimonious interpretation.
Criterion/Predictive
Scores on the BEES increased significantly from pretest to posttest in educational programs designed to
increase empathy towards patients ( Shapiro et al., 2004 ) and towards Holocaust victims ( Farkas, 2002 ).
Location
Mehrabian, A. (1996). Manual for the Balanced Emotional Empathy Scale (BEES) . Monterey, CA: Albert
Mehrabian.
Details available at: www.kaaj.com/psych/scales/emp.html (Retrieved December 30, 2013).
Results and Comments
Gender differences have been reported with females tending to obtain higher scores than males on the full
BEES ( Marzoli et al., 2011; Schulte-Ru ¨ther, Markowitsch, Shah, Fink, & Piefke, 2008; Toussaint & Webb, 2005 )a s
well as on an abbreviated version ( Mehrabian, 2000 ). Although the BEES has been widely adopted by researchers,
empathy is commonly regarded as a multidimensional construct. The BEES is limited in its focus on emotional
empathy. The extent to which the single score on the measure is independent of cognitive empathy remains to be
determined.
BEES SAMPLE ITEMS
‘I cannot feel much sorrow for those who are
responsible for their own misery.’
‘Unhappy movie endings haunt me for hours
afterwards.’Notes : Items are rated on a 9-point Likert-type
scale ranging from 145‘Very strong agreement’ to
245‘Very strong disagreement’.
Copyright r1995/C02010 Albert Mehrabian.
Multidimensional Emotional Empathy Scale (MDEES)
(Caruso & Mayer, 1998 ).
Variable
The MDEES focuses on the affective component of empathy and is intended for use with adolescents and
adults.
Description
Thirty items describing positive and negative emotional situations are responded to on a 5-point Likert-type
scale. The MDEES is proposed to consist of six subscales labeled: Empathic Suffering, Positive Sharing,
Responsive Crying, Emotional Attention, Feeling for Others, and Emotional Contagion. The total scale score is
obtained by summing across all the items (six negatively worded items are reverse scored), although reverse-
worded items may measure a rather different construct (Boyle et al., 2008).260 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Sample
The samples used in validating the MDEES included 503 adults (164 men and 333 women) whose mean age
was 23 years (ranging from 17 to 70 years) and 290 adolescents (115 male and 140 female; 35 no gender indicated)
whose mean age was 14 years (ranging from 11 to 18 years). ( Caruso & Mayer, 1998 ).
Reliability
Internal Consistency
The Cronbach alpha coefficient for the entire scale of 30 items was found to be .88 ( Caruso & Mayer, 1998 ).
Using the 26 items that formed six factors in the scale (see below) yielded an alpha coefficient of .86. The alpha
coefficients for the six subscales varied from .44 to .80 (Empathic Suffering 5.80; Positive Sharing 5.71;
Responsive Crying 5.72; Emotional Attention 5.63; Feeling for Others 5.59; Emotional Contagion 5.44). Using
the same items from the subscales described by Caruso and Mayer (1998) ,Olckers, Buys, and Grobler (2010)
reported alpha coefficients ranging from .32 to .82 (Empathic Suffering 5.79; Positive Sharing 5.85; Responsive
Crying 5.69; Emotional Attention 5.51; Feeling for Others 5.61; Emotional Contagion 5.32).
Test/C0Retest
Test/C0retest reliability of the MDEES is not currently available.
Validity
Convergent/Concurrent
In the sample of adolescents, there was a positive correlation ( r5.63) with an adaptation of the Emotional
Empathetic Tendency Scale ( Mehrabian & Epstein, 1972 ). Also, for the adult subsample, Emotional Attention cor-
related positively (.34) with Eisenberg’s Parenting Style scale ( Eisenberg, Fabes, & Losoya, 1997 ).
Divergent/Discriminant
Caruso and Mayer (1998, p. 14) reported that, ‘The new scale did not, generally, correlate with a measure of
social loneliness, with one exception: the correlation between the Responsive Crying scale and social loneliness
was2.13 ( p,.05). However, the scores share less than 2% of the variance ( r25.016).’ Also, higher scores for
women than men have been shown for the overall scale score and on all subscale scores (all p,.001; Caruso &
Mayer, 1998 ), although this gender difference has not always been observed ( Faye et al. 2011 ). Studies have also
shown significantly higher scores for older individuals ( Caruso & Mayer, 1998; Faye et al., 2011 ).
Construct/Factor Analytic
Caruso and Mayer (1998) undertook a principal components analysis to examine the structure of the MDEES
in the sample of 793 adults and adolescents described above. The PCA yielded six components (with eigenvalues
greater than one) labeled: Empathic Suffering (8 items), Positive Sharing (5 items), Responsive Crying (3 items),
Emotional Attention (4 items), Feeling for Others (3 items), and Emotional Contagion (2 items). However, in a
confirmatory factor analysis using a sample of 212 adults, Olckers et al. (2010) were unable to verify the six-
dimensional structure claimed for the MDEES. Individual factor loadings were low for variables associated with
Emotional Attention, Feel for Others, and Emotional Contagion.
Criterion/Predictive
The MDEES was found to predict a number of behavioral criteria. Caruso and Mayer (1998) examined the rela-
tionship between MDEES scores and various lifespace scales. ‘Lifespace scales are self-report scales, similar to
bio-data scales, which record information on the types and frequency of behavior a subject engages in’ (Caruso &
Mayer, 1988, p. 8). The MDEES scores correlated with artistic skills ( r5.12), satisfaction with one’s career, social
and personal life ( r5.23), a warm, supportive upbringing ( r5.20), and attendance at cultural events in the sam-
ple of adults ( r5.18) ( Caruso & Mayer, 1998 ). Scores on the MDEES also predicted ( r5.30) preferences fo rper-
sonal, non-erotic touch in a sample ( N5129) of university students ( Draper & Elmer, 2008 ). Also, in an Iranian
sample of 70 undergraduates, a cognitive-affective reading-based course that aids in emotion regulation signifi-
cantly predicted MDEES scores ( Rouhani, 2008 ).261 OVERVIEW OF THE MEASURES
III. EMOTION REGULATION |
Location
Caruso, D. R., & Mayer, J. D. (1998). A measure of emotional empathy for adolescents and adults . Unpublished
Manuscript. Available online at:
www.google.com.au/url?sa 5t&rct5j&q5&esrc5s&source 5web&cd 51&ved50CCkQFjAA&url 5http%3A%
2%2Fwww.unh.edu%2Femotional_intel ligence%2FEI%2520Assets%2FEma pthy%2520Scale%2FEmpathy%2520
Article%25202000.doc&ei 510G-UsL9GK-0iQea3IDIDA&usg 5AFQjCNHbIUirDCZr0fhyG3vTMsCfjecUYw&bvm 5
bv.58187178,d.dGI (Retrieved December 28, 2013).
Results and Comments
The MDEES aims to measure different components of affective empathy. However, Caruso and Mayer (1998)
cautioned against using the Emotional Contagion subscale given that it contains only two items. In addition,
Olckers et al. (2010) carried out a CFA that was unable to verify the purported MDEES structure. Test /C0retest reli-
ability of the MDEES also remains to be determined.
MDEES SAMPLE ITEMS
Circle the response which best indicates how much
you agree or disagree with each item.
The suffering of others deeply disturbs me.
I rarely take notice when other people treat each
other warmly.
Being around happy people makes me feel
happy, too.I feel like crying when watching a sad movie.
Too much is made of the suffering of pets or animals.
I feel others’ pain.
My feelings are my own and don’t reflect how
others feel.
Note: Items are rated on a 5-point Likert-type scale rang-
ing from 1 5‘Strongly disagree ’t o55‘Strongly agree ’.
Empathy Quotient (EQ)
(Baron-Cohen & Wheelwright, 2004 ).
Variable
Baron-Cohen & Wheelwright (2004) defined empathy as, ‘the drive to identify another person’s emotions and
thoughts, and to respond to these with an appropriate emotion’ (p. 361). In line with this definition, the EQ was
designed to be a short, easy to use scale that measures both cognitive and affective components of empathy.
Description
The 60-item EQ comprises 40 empathy items and 20 filler/control items. Respondents score one a 4-point
forced-choice scale from ‘strongly agree’, ‘agree slightly’, ‘disagree slightly’ and ‘disagree strongly’ with higher
scores reflecting higher empathic capacity. The EQ contains 20-control items, included to provide some distrac-
tion to minimize the ‘relentless focus on empathy’ while responding to the EQ measure ( Baron-Cohen &
Wheelwright, 2004 , p. 166). The control items can be used to check for response bias. Furthermore, approximately
half the items in the EQ are reverse worded, although reverse-worded items tend to measure a somewhat differ-
ent construct (Boyle et al., 2008).
Sample
Initial pilot testing of the EQ was undertaken on a small sample of 20 normal individuals ( Baron-Cohen &
Wheelwright, 2004 ). Subsequent validation samples included 90 adults with Asperger syndrome or high-
functioning autism who were compared on the EQ with 90 age-matched controls, and 197 adults from the general
population (71 males whose mean age was 38.8 years; and 136 females whose mean age was 39.5 years) ( Baron-
Cohen & Wheelwright, 2004 ).262 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Reliability
Internal Consistency
Baron-Cohen and Wheelwright (2004) reported a Cronbach alpha coefficient of .92. Other researchers have
also reported alpha coefficients of .87 ( Hambrook, Tchanturia, Schmidt, Russell, & Treasure, 2008 ), .78 ( Kim &
Lee, 2010 ), and .85 ( Muncer & Ling, 2006 ). For a child-adapted version of the EQ (EQ-C), an alpha coefficient of
.93 was reported ( Auyeung et al., 2009 ).
Test/C0Retest
Baron-Cohen and Wheelwright (2004) also reported a 12-month interval test /C0retest reliability coefficient of .97
for the EQ. In an independent study, the 12-month test /C0retest reliability coefficient was found to be .84
(Lawrence, Shaw, Baker, Baron-Cohen, & David, 2004 ). The test /C0retest reliability coefficient for the EQ in both
Korean and Italian adaptations over a four-week period was r5.84 ( Kim & Lee, 2010 ) and r5.85 ( Preti et al.,
2011 ).
Validity
Convergent/Concurrent
In the Korean adaptation of the EQ, positive correlations were obtained between the EQ and the Interpersonal
Reactivity Index (IRI) subscales: Perspective Taking ( r5.33), Empathetic Concern ( r5.25), and Fantasy ( r5.20)
(r5.17) ( Kim & Lee, 2010 ).Lawrence et al. (2004, p. 917) reported ( N552) that the Emotional Reactivity compo-
nent of the EQ correlated positively (.31) with Beck Anxiety Inventory (BAI) scores.
Divergent/Discriminant
The EQ score correlated negatively with the IRI Personal Distress subscale ( r52.17) ( Kim & Lee, 2010 ). The
EQ also exhibits significant sex differences with women scoring more highly than men ( Lawrence et al., 2004;
Muncer & Ling, 2006 ). Individuals with either Asperger’s syndrome or high-functioning autism obtained signifi-
cantly lower scores on the EQ than did normals ( Baron-Cohen & Wheelwright, 2004; Kim & Lee, 2010 ).Lawrence
et al. (2004, p. 917) reported ( N545) that the Social Skills component of the EQ correlated negatively (.35) with
Beck Depression Inventory (BDI) scores. In a French study, Berthoz, Wessa, Kedia, Wicker, and Gre `zes (2008)
reported that the EQ correlated with the BDI ( 2.13), with Spielberger’s State STAI ( 2.08), and with the Trait
STAI (2.11). With regard to the three EQ components, only Social Skills correlated significantly with the BDI
(2.36), State STAI ( 2.34), and Trait STAI ( 2.37).
Construct/Factor Analytic
Lawrence et al. (2004) carried out a principal components analysis of the item intercorrelations and suggested
that the EQ could be better regarded as a 28-item scale with three related components of empathy (labeled: cogni-
tive empathy, emotional reactivity, and social skills), rather than a 40-item unifactorial scale. Muncer and Ling
(2006) conducted a confirmatory factor analysis that provided some support the proposed three factor structure.
Berthoz et al. (2008) undertook a confirmatory factor analysis of the EQ that provided support for the three-
dimensional structure of the measure. Allison, Varon-Cohen, Wheelwright, Stone, and Muncer (2011, p. 829)
investigated the structure of the EQ using both Rasch and CFA analyses, in samples of 658 autism spectrum dis-
order patients, 1375 family members, and 3344 normals. The CFA suggested that a 26-item model exhibited a sat-
isfactory fit to the data (RMSEA 5.05, CFI 5.93), while the Rasch analysis suggested that the EQ provides a valid
measure of empathy.
Criterion/Predictive
The EQ has been shown to exhibit criterion/predictive validity in research pertaining to autism and gender
differences ( Auyeung et al., 2009; Baron-Cohen & Wheelwright, 2004 ), social functioning and aging ( Bailey,
Henry, and Von Hippel, 2008 ), schizophrenia ( Bora, Go ¨kc¸en, and Veznedaroglu. 2007 ), and eating disorders
(Hambrook et al., 2008 ).
Location
Baron-Cohen, S., & Wheelwright, S. (2004). The empathy quotient: An investigation of adults with Asperger
syndrome or high functioning autism, and normal sex differences. Journal of Autism and Developmental Disorders,
34, 163/C0175.263 OVERVIEW OF THE MEASURES
III. EMOTION REGULATION |
Results and Comments
There is some debate with regards to the structure of the EQ. Baron-Cohen and Wheelwright (2004) based the
scale on a model of empathy as having both affective and cognitive components. However, some evidence sug-
gests that the scale may consist of three factors (Lawrence, 2004; Muncer & Ling, 2006 ).Reniers et al. (2012)
pointed out that the EQ items tend to focus more on measuring the empathetic process rather than the empathy
construct itself.
EQ SAMPLE ITEMS
Cognitive empathy questions
I can easily work out what another person might
want to talk about
I am good at predicting how someone will feel
Affective empathy questions
Seeing people cry doesn’t really upset meI usually stay emotionally detached when watching
a film
Notes : Items are rated on a 4-point scale with the
response options of ‘ Strongly agree ’; ‘Slightly agree ’;
‘Slightly disagree ’t o‘ Strongly disagree ’.
Feeling and Thinking Scale (FTS)
(Garton & Gringart, 2005 ).
Variable
The FTS is an adaptation of the Interpersonal Reactivity Index (IRI, Davis, 1980 ) for use with children. The IRI
contains four independent subscales labeled: Empathic Concern, Perspective Taking, Personal Distress, and
Fantasy.
Description
The IRI items were reworded to be more easily understood by children. Item 16 (Fantasy subscale) and all
reverse worded items were removed as they were too difficult for children to comprehend. The final FTS scale
comprised 18 of the IRI items including four Empathetic Concern items, four Perspective-Taking items, six
Personal Distress items, and four Fantasy items (see Garton & Gringart, 2005 ).
Sample
The initial sample used by Garton and Gringart (2005) comprised 413 children (194 girls and 219 boys, aged
from 7.11 to 9.11 years).
Reliability
Internal Consistency
FTS items reflecting affective and cognitive components of empathy exhibited Cronbach alpha coefficients of
.69 and .54 respectively ( Garton & Gringart, 2005 ). Likewise, Kokkino and Kipritsi (2012) reported alpha coeffi-
cients of .53 and.56 (for cognitive and affective components), and .68 for the total scale.
Test/C0Retest
Test/C0retest reliability coefficients for the FTS are not currently available.
Validity
Convergent/Concurrent
The FTS total scale score correlated positively with self-efficacy ( r5.22), social self-efficacy ( r5.27), and aca-
demic self-efficacy ( r5.23) ( Kokkinos & Kipritsi, 2012 ).264 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Divergent/Discriminant
Kokkinos and Kipritsi (2012) found that the FTS total score correlated negatively with their Bullying and
Victimization scale or BVS ( r52.15). Girls scored more highly than boys on both the cognitive and affective
components of empathy ( Garton & Gringart, 2005 ).
Construct/Factor Analytic
A principal components analysis with oblimin rotation using the sample of 413 school children resulted in a
four-component solution ( Garton & Gringart, 2005 ). The resultant 12-item scale comprised a two-dimensional
structure reflecting both affective and cognitive components of empathy. Likewise, Kokkinos and Kipritsi (2012) ,
using a Greek sample of 206 Grade 6 children, conducted an exploratory factor analysis of the item intercorrela-
tions, resulting in separate cognitive and affective empathy factors.
Criterion/Predictive
No criterion/predictive validity evidence is currently available.
Location
Garton, A.F., & Gringart, E. (2005). The development of a scale to measure empathy in 8- and 9-year old chil-
dren. Australian Journal of Education and Developmental Psychology, 5 ,1 7/C025.
Results and Comments
Theory consistent sex differences have been found with the FTS. Girls show significantly higher scores than
boys on both affective ( p,.001) and cognitive ( p,.01) factors ( Garton & Gringart, 2005 ). During construction of
the FTS, Garton and Gringart (2005) proposed a two-factor model reflecting cognitive and affective components
of empathy. However, the FTS was based upon Davis’ (1980) IRI which comprises four subscales. Evidently, the
relationship between the FTS and IRI requires further investigation. Also, the test /C0retest reliability as well as the
criterion/predictive validity remain to be investigated.
FTS SAMPLE ITEMS
Cognitive empathy question
I think people can have different opinions about the same thing.
Affective empathy question
Emergency situations make me feel worried and upset.
Note: Items are rated on a 5-point Likert-type scale ranging from: 1 5‘Not like me at all ’; 25‘Hardly ever like me ’;
35‘Occasionally like me ’; 45‘Fairly like me ’; and 5 5‘Very like me ’.
Basic Empathy Scale (BES)
(Jolliffe & Farrington, 2006a ).
Variable
The BES is based on a definition of empathy proposed by Cohen and Strayer (1996) as the sharing and under-
standing of another’s emotional state or context resulting from experiencing the emotive state (affective) and
understanding another’s (cognitive) emotions.
Description
The BES measures five basic emotions (fear, sadness, anger, and happiness) wherein the measurements relate
more generally to cognitive and affective empathy and not to a non-specific affective state (e.g., anxiety). For the
40-item scale, reverse worded items have been included with 20 items requiring a positive response and 20
requiring a negative response ( Jolliffe & Farrington, 2006a ). A shortened 20-item version is also available, along
with a French version for use with adults ( Carre ´, Stefaniak, D’Ambrosio, Bensalah, & Besche-Richard, 2013 ).265 OVERVIEW OF THE MEASURES
III. EMOTION REGULATION |
Sample
The BES was constructed using a sample of 363 Year 10 adolescents (194 males and 169 females whose mean
age was 14.8 years). A separate validation sample included 357 Year 10 students (182 males and 175 females).
Reliability
Internal Consistency
Jolliffe and Farrington (2006a) reported an overall Cronbach alpha coefficient of .87 (.79 and .85 for cognitive
and affective components). Stavrinides et al. (2010) reported alpha coefficients for cognitive (.80 and .83) and
affective components (.71 and .77), respectively. In an Italian study ( Albiero et al., 2009 ), an alpha coefficient of
.87 for the total scale was reported (.74 for cognitive and .86 for affective empathy). A Chinese study ( Geng, Xia,
& Qin, 2012 ) reported an alpha coefficient of .77 for the total scale (.72 for cognitive, and .73 for affective empa-
thy). In a French study ( N5370), Carre ´et al. (2013) reported alpha coefficients for cognitive (.71), and affective
components (.74), respectively.
Test/C0Retest
Test/C0retest reliability over a 3-week interval for the BES was demonstrated for a French adaptation ( r5.66)
(D’Ambrosia et al., 2009 ) and for the Chinese version over a 4-week interval ( r5.70) ( Geng et al., 2012 ).
D’Ambrosia et al. also reported test /C0retest coefficients for the affective empathy subscale ( r5.70) and for the
cognitive empathy subscale ( r5.54). Likewise, Carre ´et al. (2013) reported a test /C0retest coefficient of .56 for the
BES cognitive empathy component ( N5222) over a 7-week interval.
Validity
Convergent/Concurrent
Jolliffe and Farrington (2006a) reported that total scores on the BES correlate positively with total scores on the
IRI for males ( r5.53) and females ( r5.43), respectively. The BES affective component correlates more strongly
with IRI Perspective Taking ( r5.51) than with Empathic Concern ( r5.33) in males. Likewise, the BES cognitive
component correlates more strongly with IRI Perspective Taking ( r5.44) than with Empathic Concern ( r5.37)
for females. The BES also correlated positively with the earlier constructed BEES for both males ( r5.59) and
females ( r5.70) in an Italian sample ( Albiero et al., 2009 ). Total BES scores correlate positively with agreeable-
ness in males ( r5.30) and females ( r5.24), conscientiousness for males only ( r5.17), openness for males
(r5.34) and females ( r5.15), and neuroticisim for females only ( r5.16) ( Jolliffe & Farrington, 2006a ).
Divergent/Discriminant
Jolliffe and Farrington (2006a) reported that total BES scores correlate negatively with a measure of alexithy-
mia, although this appeared to reflect a significant negative relationship with cognitive empathy only ( r52.21
for males; r52.31 for females). Females obtain significantly higher scores than males on affective empathy, cog-
nitive empathy and total empathy scores ( Jolliffe & Farrington, 2006a ). These sex differences in reported empathy
have been replicated in an Italian study ( Albiero et al., 2009 ).
Construct/Factor Analytic
The BES was constructed using a principal components analysis (plus orthogonal varimax rotation) to reduce
the 40-item scale into affective and cognitive empathy factors ( Jolliffe & Farrington, 2006a ). Confirmatory factor
analysis ( N5720), revealed that a good fit to the data was obtained for the two-factor solution: GFI (.89), the
AGFI (.86), and the RMSR (.06). The affective and cognitive subscales were significantly correlated for males
(r5.41) and females ( r5.43). Subsequently, Carre ´et al. (2013) carried out a CFA ( N5370) which provided sup-
port for both two- and three-dimensional BES structures.
Criterion/Predictive
For both males and females, BES total scores were higher among individuals who reported that they would
help in a real-life incident requiring their assistance, than in those who reported that the incident was none of
their business ( Jolliffe & Farrington, 2006a ).266 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Location
Jolliffe, D., & Farrington D.P. (2006a). Development and validation of the Basic Empathy Scale. Journal of
Adolescence, 29 , 589/C0611.
Results and Comments
The BES has been used in research into bullying (e.g., Jolliffe & Farrington, 2006b; Stavrinides et al., 2010 ) and
offending ( Jolliffe & Farrington, 2007 ). There is a paucity of literature that provides stability coefficients for the
BES over a time interval greater than seven weeks. Despite collection of the BES on two occasions over a 6-month
period, Stavrinides et al. (2010) did not report test /C0retest reliability.
BES SAMPLE ITEMS
Cognitive empathy question
It is hard for me to understand when my friends are sad.
Affective empathy question
I usually feel calm when other people are scared.
Note: Items are rated on a 5-point Likert-type scale ranging from: 1 5‘Strongly disagree ’; 25‘Disagree ’; 35‘Neither
agree nor disagree ’; 45‘Agree ’; 55‘Strongly agree ’.
Griffith Empathy Measure (GEM)
(Dadds et al., 2008 )
Variable
The GEM was constructed due to the shortage of multi-informant assessment of empathy in children and ado-
lescents, deemed important for accurate measurement of empathy in this population group ( Dadds et al., 2008 ,
p. 111). It is an adaption of the Bryant Index of Empathy ( Bryant, 1982 ) used by parents to assess child and ado-
lescent empathy ( Dadds et al., 2008 ).
Description
The GEM contains 23 items that are rated on a 9-point Likert-type response scale to assess parents’ level of
agreement with statements concerning their child. The GEM appears to measure cognitive and affective compo-
nents of empathy ( Dadds et al., 2008 ).
Sample
Construction of the GEM used a sample of 2612 parents of children aged 4 to 16 years (mean age 57.71 years;
SD53.06) from primary and secondary schools in Australia.
Reliability
Internal Consistency
Dadds et al. (2008) reported a Cronbach alpha coefficient of .81 for the overall scale of 23 items, .62 for cogni-
tive empathy (6 items), and .83 for affective empathy (9 items). subsequently, Dadds et al. (2009) reported alpha
coefficients of .62 (cognitive empathy), and .77 (affective empathy).
Test/C0Retest
For a subsample of 31 parents with non-clinic children aged 5 /C012 years, Dadds et al. (2008) reported a
test/C0retest reliability coefficient over a one-week interval of .91 for the GEM (affective subscale: r5.93; cognitive
subscale: r5.89). In a further sub sample of 127 parents with non-clinic children, Dadds et al. (p. 117) reported
an impressive six-month stability coefficient ( r5.69).267 OVERVIEW OF THE MEASURES
III. EMOTION REGULATION |
Inter-Rater
Dadds et al. (2008) reported that inter-parent ratings for total scores were: (boys r5.63, girls r5.69), affective
scores (boys r5.47, girls r5.41), and cognitive scores (boys r5.52, girls r5.47).
Validity
Convergent/Concurrent
Dadds and Hawes (2004) reported that for mothers, correlations between GEM total, cognitive, and affective
empathy scores, and Maximum Distress Allowed (measured via the Interpersonal Response Test) were .38, .56,
and .30, respectively. The GEM cognitive empathy component correlated .30 with verbal IQ scores ( Dadds et al.,
2008 ). Positive correlations were found between the GEM and the Cruelty to Animals Inventory (Dadds et al.,
2004). Observed Pet Nurturance correlated .25 with the total GEM scale, and .34 with the GEM affective
component.
Divergent/Discriminant
Although the GEM did not correlate with verbal IQ ( r5.01), the affective empathy component correlated 2.15
with verbal IQ scores ( Dadds et al., 2008 ). Negative correlations were found between the GEM and the Cruelty to
Animals Inventory (Dadds et al., 2004). Observed Pet Cruelty correlated 2.31 with the total GEM scale, 2.35
with the affective GEM component, and 2.12 with the cognitive GEM component. Dadds et al. (2009) examined
the relationship between parent-rated cognitive and affective empathy (on the GEM) with psychopathic traits.
For males, psychopathic traits correlated negatively with cognitive ( r52.41) and affective ( r52.17) empathy.
For females, psychopathic traits correlated negatively with cognitive ( r52.39) but not affective ( r52.02) empa-
thy. For 155 mother and father ratings on the GEM, mothers tended to rate their children more highly on total,
cognitive, and affective components ( Dadds et al., 2008 ).
Construct/Factor Analytic
GEM item intercorrelations were subjected to a principal components analysis with oblique (direct oblimin)
rotation, revealing separate cognitive and affective components ( Dadds et al., 2008 ). The two components were
found to be independent ( r5.07). A confirmatory factor analysis demonstrated an acceptable fit (CFI 5.90;
RMSEA 5.05), providing support for the proposed two-dimensional structure of the GEM across genders and
age groups.
Criterion/Predictive
Dadds and Hawes (2004) reported that Reaction Time (measured via the Interpersonal Response Test) corre-
lated negatively with total and affective empathy ( r52.56, and r52.57) but not with cognitive empathy scores
(r5.15). Using behavioral measures of children’s’ nurturing behavior as well as cruel behaviors towards pets,
Observed Pet Nurturance correlated .25 with the GEM total score (.34 with the affective component, and .05 with
the cognitive component) ( Dadds et al., 2008 ).
Location
Dadds, M.R. et al. (2008). A measure of cognitive and affective empathy in children using parent ratings. Child
Psychiatry and Human Development, 39 , 111/C0122.
Results and Comments
The cognitive component of the GEM, while seeming stable, does not show high internal consistency.
Furthermore, the principal components analysis extraction employed by Dadds et al. (2008) can increase the risk
of falsely inflating component loadings. It would be recommended for future research using the GEM to re-visit
the scales factor structure. The GEM also does not incorporate a means of systematically reducing response bias.
GEM SAMPLE ITEMS
My child rarely understands why other people cry
My child becomes sad when other children around
him/her are sadNote: Items are rated on a 9-point Likert-type scale
ranging from: 145‘Strongly agree ’t o/C045‘Strongly
disagree’ .268 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Toronto Empathy Questionnaire (TEQ)
(Spreng et al., 2009 ).
Variable
The development of the TEQ did not begin with a conceptual definition of empathy other than to consider it
at the broadest level and derive a measure based on existing empathy scales.
Description
Spreng et al. (2009) factor analyzed responses made on every self-report measure of empathy they could iden-
tify, resulting in 142 items from 11 different empathy and related questionnaires including the IRI ( Davis, 1980,
1983 ), Hogan’s Empathy Scale ( Hogan, 1969 ), Questionnaire Measure of Emotional Empathy ( Mehrabian &
Epstein, 1972 ), BEES ( Mehrabian, 2000 ), Scale of Ethnocultural Empathy ( Wang et al., 2003 ), Jefferson Scale of
Physician Empathy ( Hojat et al., 2001 ), Nursing Empathy Scale ( Reynolds, 2000 ), Japanese Adolescent Empathy
Scale ( Hashimoto & Shiomi, 2002 ), and the Measure of Emotional Intelligence (Schutte et al., 1998). An additional
36 items were composed descriptive of individuals with altered empathic responding due to neurological or psy-
chiatric disease. The resulting TEQ places an emphasis on the emotional component of empathy, and consists of
16 items, with an equal number of positively and reverse worded items. Responses are made using a 5-point
Likert-type scale.
Sample
The initial scale development sample consisted of 200 undergraduates (100 male, 100 female) (mean age 518.8
years, SD51.2). A validation sample comprised 79 undergraduates (24 male, 55 female) of similar age
(mean518.9 years, SD53.0). Another validational sample consisted of 65 undergraduates (mean age 518.6
years, SD52.3).
Reliability
Internal Consistency
The Cronbach alpha coefficient was found to be .85 for both the developmental and validation samples. For
the additional validation sample, the alpha coefficient was found to be .87 ( Spreng et al., 2009 ).
Test/C0Retest
For the subsample of 65 students who completed the TEQ again after a mean interval of 66 days, the stability
coefficient was .81 ( Spreng et al., 2009 ).
Validity
Convergent/Concurrent
The TEQ correlated positively with IRI Empathic Concern ( r5.74) and also after reworded Empathic Concern
items were removed ( r5.71). Total TEQ scores also correlated positively with IRI Perspective Taking ( r5.35).
TEQ scores correlated positively with IRI Empathic Concern ( r5.74), with Perspective Taking ( r5.29), and
Fantasy ( r5.52). TEQ scores also correlated positively with EQ scores ( r5.80) ( Spreng et al., 2009 ).
Divergent/Discriminant
Scores on the TEQ correlated with a behavioral measure of social comprehension (Reading the Mind in the
Eyes Test-Revised: r5.35, Interpersonal Perception Task-15: r5.23) in a sample of 79 undergraduates ( Spreng
et al., 2009 ). In a sample of 200 students, a negative correlation was observed with the Autism Quotient
(r52.30). Males and females did not differ significantly in total TEQ scores in the first sample, although in the
second sample, females scored significantly higher than males.
Construct/Factor Analytic
An iterative maximum-likelihood factor analysis with SMCs as initial communality estimates was undertaken
on the item intercorrelations ( N5200). Spreng et al. (2009) then conducted a further exploratory factor analysis
on the intercorrelations of the final 16 items of the TEQ forcing a single-factor structure.269 OVERVIEW OF THE MEASURES
III. EMOTION REGULATION |
Criterion/Predictive
Criterion/predictive validity coefficients remain to be documented.
Location
Spreng, R.N., McKinnon, M.C., Mar, R.A., & Levine, B. (2009). The Toronto Empathy Questionnaire: Scale
development and initial validation of a factor-analytic solution to multiple empathy measures, Journal of
Personality Assessment, 91 ,6 2/C071.
Results and Comments
The TEQ loads on a single factor representative of ‘the broadest, common construct of empathy’. Spreng et al.
(2009) argued that since the TEQ correlates with IRI components of empathetic concern, perspective taking, and
fantasy, it may not be necessary to use multiple subscales to measure empathy. However, the TEQ does not cor-
relate with the IRI subscale of personal distress, suggesting that it may not encapsulate all facets of empathy.
TEQ SAMPLE ITEMS
I enjoy making other people feel better
I am not really interested in how other people feel
I find it silly for people to cry out of happiness
I can tell when others are sad even when they do not
say anythingNote: Items are rated on a 5-point Likert-type scale
ranging from: 1 5‘Never ’; 25‘Rarely ’; 35‘Sometimes ’;
45‘Often ’; 55‘Always ’.
Questionnaire of Cognitive and Affective Empathy (QCAE)
(Reniers, Corcoran, Drake, Shryane, & Vo ¨llm, 2011 ).
Variable
The QCAE aims to build on earlier measures of empathy in which the constructs were considered to be either
too narrow or inaccurate, inconsistently defined, or psychometric properties were less than optimal ( Reniers
et al., 2011 ). Both cognitive and affective components of empathy are measured.
Description
The QCAE is a 31-item measure with a 4-point forced-choice response scale. To create the QCAE, items were
derived from the EQ ( Baron-Cohen & Wheelwright, 2004 ), Hogan’s Empathy Scale ( Hogan, 1969 ), the Empathy
subscale of the Impulsiveness-Venturesomeness-Empathy Inventory (IVE; Eysenck & Eysenck, 1991 ), and the IRI
(Davis, 1980, 1983 ). Each item was assessed by two raters. If both raters agreed on an item as a measure of cogni-
tive or affective empathy it was included in the measure. The QCAE comprises five subscales (31 items) labeled:
perspective taking, online simulation, emotion contagion, proximal responsivity, and peripheral responsivity,
respectively ( Reniers et al., 2011 ). The first two subscales measure cognitive empathy and the remaining three
subscales measure affective empathy.
Sample
The initial sample comprised 925 participants (284 males; 641 females) whose mean age was 26 years ( SD59).
Some 81% of the participants originated from European decent with the majority specifying the United Kingdom
as their place of origin.
Reliability
Internal Consistency
Cronbach alpha coefficients have been reported as follows: perspective taking (.85), emotional contagion (.72),
online simulation (.83), peripheral responsivity (.65), and proximal responsivity (.70) ( Reniers et al., 2011 ).
Test/C0Retest
Test/C0retest reliability coefficients for the QCAE are not currently available.270 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Validity
Convergent/Concurrent
Reniers et al. (2011) reported that the cognitive and affective subscales of the QCAE share some variance in
common ( r5.31). This suggests that while there is a relationship between the cognitive and affective subscales,
they still represent distinct forms of empathy. The BES correlates positively with the QCAE subscales of cognitive
(r5.62) and affective ( r5.76) empathy ( Reniers et al., 2011 ).
Divergent/Discriminant
Reniers et al. (2011) reported that females scored more highly than males on both the cognitive and affective
subscale. Reniers et al. (2012, p. 205) reported that the QCAE cognitive empathy subscale is negatively correlated
with secondary psychopathy ( r52.64)/C0(as measured via the Levenson Self-Report Psychopathy Scale). No
relationship was observed between empathy scores and moral judgment competence scores (as measured via the
Moral Judgment Task).
Construct/Factor Analytic
A principal components analysis (with direct oblimin rotation) was carried out for the original 65-item scale
(N5640). Both the Scree test ( Cattell, 1978; Cattell & Vogelmann, 1977 ) and a parallel analysis ( Velicer & Jackson,
1990 ) suggested five components, defining the subscales of the QCAE. Although a subsequent confirmatory fac-
tor analysis in an independent sample ( N5318) provided support for the five-component structure, a two-
dimensional structure relating to cognitive and affective empathy ‘provided the best and most parsimonious fit
to the data’ ( Reniers et al., 2011 , p. 84).
Criterion/Predictive
Lang (2013) reported that QCA scores decreased in a sample of 185 participants (82% female) following obser-
vation of chronic pain portrayed in entertainment media. Also, predictive validity of the QCAE has been demon-
strated in studies into prenatal testosterone and the later development of behavioral traits ( Kempe & Heffernan,
2011 ), as well as musical appreciation ( Clemens, 2012 ).
Location
Reniers, R., Corcoran, R., Drake, R., Shryane, N.M., & Vo ¨llm. B.A. (2011). The QCAE: A questionnaire of cogni-
tive and affective empathy. Journal of Personality Assessment, 93 ,8 4/C095.
Results and Comments
The QCAE has been used alongside other empathy measures including the QMEE ( Mehrabian & Epstein,
1972 ) and IRI ( Davis, 1980, 1983 ) in research studies into empathy ( Kempe & Heffernan, 2011 ) or music apprecia-
tion ( Clemens, 2012 ). The QCAE is the first online measure of empathy to date. However, test /C0retest reliability
remains to be determined for the QCAE.
QCAE SAMPLE ITEMS
I can easily work out what another person might
want to talk about.
I am good at predicting what someone will do.
It worries me when others are worrying and panicky.
Friends talk to me about their problems as they say
that I am very understanding.
It is hard for me to see why some things upset people
so much.I try to look at everybody’s side of a disagreement
before I make a decision.
Note: Items are rated on a 4-point scale ranging from:
45‘Strongly agree ;’ 35‘Slightly agree ;’ 25‘Slightly dis-
agree ;’ and 1 5‘Strongly disagree ’.
Picture Viewing Paradigms (PVP)
(Westbury & Neumann, 2008 ).271 OVERVIEW OF THE MEASURES
III. EMOTION REGULATION |
Variable
In the PVP, empathy is conceptualized as an individual’s self-reported response to empathy-eliciting visual
images.
Description
The PVP is a simple task in which images depicting individuals (termed targets ) are depicted in certain situa-
tions. Often these are negative (e.g., confinement, injury, grief), but they may also be positive. Image duration is
typically between 6 and 10 seconds. Participants view the images and make a rating response. Ratings may also
relate to different components (e.g., affective and cognitive) or related constructs (e.g., sympathy, distress).
Physiological recordings may also be taken during the image presentation. Westbury and Neumann (2008)
defined empathy on a 9-point scale as, ‘to what degree you are able to imagine feeling and experiencing what the
target is experiencing, in other words, your ability to put yourself in the others’ situation.’ They also measured
corrugator electromyographic activity and skin conductance responses. Images were sourced from the
International Affective Picture System (IAPS; Lang, Bradley, and Cuthbert, 1999 ) or other media (e.g., Internet).
Variations of the PVP were also used, such as using video clips instead of static images ( Westbury & Neumann,
2008 ). In addition, participants were asked to concentrate on their own feelings while viewing the images or con-
centrate on the feelings of the target /C0a ‘self’ versus ‘other’ distinction (e.g., Schulte-Ru ¨ther et al., 2008 ).
Sample
Westbury and Neumann (2008) used a sample of 73 undergraduates (mean age 522.5 years, SD59.41). A sec-
ond sample comprised 33 undergraduates (mean age 524.6 years). Neumann, Boyle, and Chan (2013) subse-
quently employed a sample of 26 male and 73 female Caucasian participants (mean age 525.44 years, SD59.41)
as well as a sample of 29 male and 70 female Asian participants (mean age 520.89 years, SD51.70).
Reliability
Internal Consistency
Westbury and Neumann (2008) reported Cronbach alpha coefficients for subjective empathy ratings of .91 (first
sample) and .94 (second sample). Subsequently, Neumann et al. (2012) reported high alpha coefficients for
empathy-perspective taking ( α5.98), empathy-affect ( α5.98), and empathy-understanding ( α5.98), suggesting
the possibility of some narrowness of measurement (cf. Boyle, 1991 ).
Test/C0Retest
Test/C0retest reliability has not been reported for empathy-related PVT itself. In research unrelated to empathy
that used the IAPS, Lang et al. (1993) reported stability coefficients (time interval unspecified) for arousal
(r5.93), valence ( r5.99), the corrugator response ( r5.98) and zygomatic response ( r5.84).
Validity
Convergent/Concurrent
Self-reported PVP empathy ratings in Westbury and Neumann (2008) , correlated positively with BEES scores
in the first ( r5.56) and second ( r5.43) samples. In the second sample, empathy ratings correlated positively
with ratings of sympathy ( r5.66) and distress ( r5.59).
Divergent/Discriminant
Kring and Gordon (1998) used videotaped facial expressions that represented the emotions of happiness, sad-
ness, and fear. Participants watched video clips unaware their facial expressions were being recorded during film
presentation. Following each clip, participants were asked to rate the extent to which they experienced sadness,
fear, disgust, and happiness. Females reacted more expressively than males across all film clips.
Criterion/Predictive
No criterion/predictive validity coefficients have been reported to-date.
Location
Westbury, H.R., & Neumann, D.L. (2008). Empathy-related responses to moving film stimuli depicting human
and non-human animal targets in negative circumstances. Biological Psychology, 78 ,6 6/C074.272 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Results and Comments
The picture viewing paradigm is commonly employed in experimental research in which experimental manip-
ulations are used (e.g., empathy towards different animal types; Westbury & Neumann, 2008 ) or in neuroscien-
tific research (e.g., fMRI). Researchers have rarely used the same stimuli across different experiments.
In addition, the results obtained depend on the specific way in which empathy-related responding is quantified
(e.g., self-report versus physiological response). The psychometric properties of the PVP approach require further
investigation.
Comic Strip Task (CST)
(Vo¨llm et al., 2006 ).
Variable
The CST paradigm as an indicator of empathy is based on how well one can correctly assess other individuals’
mental states (desires, intentions, and beliefs).
Description
The CST comes from the original version of attribution of intention by Sarfati et al. (1997) , and Brunet, Sarfati,
Hardy-Bayle, and Decety (2000) . This is a non-verbal task that presents a series of comic strips and asks partici-
pants to choose the best one out of two or three strips on an answer card to finish the story. Vo¨llm et al. (2006)
modified the original paradigm using some of the original comic strips from Brunet et al. (2000) from the ‘attribu-
tion of intention’ condition, but also generated new comic strips for assessing cognitive empathy. In the pilot
study of the empathy stimuli, Vo¨llm et al. (2006) reported that participants ‘rate each cartoon for clarity and
empathic understanding on a scale from 1 /C05 (very poor, poor, average, good and excellent) ...[with] ...the fol-
lowing instruction: “The cartoons that will be presented require you to put yourself in the situation of the main
character”.’ There are four conditions: theory of mind, empathy, physical attribution with one character, and
physical attribution with two characters. In the cognitive empathy condition, participants choose one of two pic-
tures to finish the story that makes the main character in the story feel better.
Sample
Vo¨llm et al. (2006) used a small sample of 13 male participants recruited from the general community and uni-
versity populations whose mean age was 24.9 years (ranging from 19 to 36 years).
Reliability
Internal Consistency
No information is currently available on internal consistency.
Test/C0Retest
Test/C0retest reliability coefficients for the CST are not currently available.
Validity
Convergent/Concurrent
Evidence on convergent/concurrent validity is not currently available.
Divergent/Discriminant
Brunet, Sarfati, Hardy-Bayle, and Decety (2003) showed that performance of schizophrenic patients was signif-
icantly lower than normal control participants on all three conditions measuring successful intention of
attribution.
Construct/Factor Analytic
Using an earlier version of the CST, Brunet et al. (2000) defined four conditions of attribution of intention (AI),
a physical causality with characters (PC-Ch), a physical causality with objects (PC-Ob), and a rest condition.
Brunet et al. (2000) conducted a principal components analysis for all experimental conditions with two main273 OVERVIEW OF THE MEASURES
III. EMOTION REGULATION |
components extracted; the first component loaded positively on AI and PC-Ch and negatively on PC-Ob. The sec-
ond component loaded positively on PC-Ch and negatively on AI.
Criterion/Predictive
Vo¨llm et al. (2006) showed that affective empathy conditions activated the medial prefrontal cortex (mPFC),
temporo-parietal junction (TPj), middle temporal gyrus, middle occipital gyrus, lingualis gyrus, and cerebellum.
Affective empathy was associated with more activations of paracingulate, anterior and posterior cingulate, and
the amygdala, related to emotional processing.
Location
Vo¨llm, B.A. et al. (2006). Neuronal correlates of theory of mind and empathy: A functional magnetic resonance
imaging study in a nonverbal task. NeuroImage, 29 ,9 0/C098.
Results and Comments
The CST may be overly simplistic and unable to appropriately estimate an individual’s cognitive understand-
ing or responsiveness in an empathy inducing situation ( Reid et al., 2012 ). Also, this type of stimulus has been
characterized as not reflecting ‘real-life’ situations which are often more complex and involve multiple persons
(Reid et al., 2012 ). The psychometric properties of the task require further investigation. However, the CST does
provide a performance based measure (i.e., it is an actual test) of empathy, in contrast to the plethora of subjec-
tive self-report measures.
Picture Story Stimuli (PSS)
(Nummenmaa et al., 2008 ).
Variable
In the PSS, empathy is conceptualized as the ability to interpret visual scenes and predict the most likely
behavioral consequence based on cognitive or affective cues.
Description
Nummenmaa et al. (2008) used 60 digitized color pictures. The pictures comprise two categories depicting two
individuals in visually matched aversive (30) and neutral (30) scenes. Aversive pictures depict interpersonal
attack scenes, such as strangling, while neutral pictures present daily (non-emotional) scenes, such as having a
conversation. Participants are required either to ‘watch’ (as though watching TV) the scene or ‘empathize’ (men-
tally simulate how the person in the scene thinks and feels). On corners of the picture yellow arrows instruct par-
ticipants how to respond, for instance, during an ‘empathize’ block, all arrows point towards the area in which
the target of the empathy is depicted in the scene (e.g. an attacker, victim, or a person engaged in a non-
emotional activity). On ‘watch’ blocks, the arrows in the left visual field point left and those in the right visual
field point right. The pictures are matched on visual variables such as luminosity, average contrast density,
global energy, complexity, and pixel area covered by faces in each scene, as well as how often the actors looking
towards the camera.
Reliability
No test /C0retest reliability coefficients for the PSS are currently available.
Validity
Convergent/Concurrent
No convergent/concurrent validity evidence is currently available.
Divergent/Discriminant
No divergent/discriminant validity evidence is currently available.274 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Criterion/Predictive
Nummenmaa et al. (2008) showed that emotional pictures depicting an attack scene increase experience of
fear, anger and disgust while decreasing experience of pleasure in participants. Affective empathy stimuli
resulted in increased activity in the thalamus (involved in emotional processing), left fusiform gyrus (face percep-
tion), right brain stem and networks associated with mirroring (inferior parietal lobule). Furthermore, the thala-
mus, primary somatosensory and motor cortices showed augmented functional coupling in relation to emotional
empathy ( Nummenmaa et al., 2008 ).
Location
Nummenmaa, L., Hirvonen, J., Parkkola, R., & Hietanen, J.K. (2008). Is emotional contagion special? An fMRI
study on neural systems for affective and cognitive empathy. NeuroImage, 43 ,5 7 1/C0580.
Results and Comments
The PSS has not been used extensively in research into empathy. The psychometric properties of the picture
story approach, including test /C0retest reliability, internal consistency, as well as convergent and discriminant
validity remain to be determined.
Kids’ Empathetic Development Scale (KEDS)
(Reid et al., 2012 ).
Variable
Cognitive, affective, and behavioral components of empathy are examined using emotion recognition, picture
based scenarios, and behavioral self-report techniques.
Description
The KEDS is ‘a measure of complex emotion and mental state comprehension as well as a behavioral measure
of empathy’ ( Reid et al., 2012 , p. 11). It is a multidimensional measure of empathy for school-aged children, com-
prising 12 ‘faceless’ pictographic stimuli that are scenarios of events or multiple characters. The figures are ‘face-
less’ to ensure the measurement of affective inference as opposed to emotion recognition. Emotional
identification response cards consist of faces used to match up with the figures in scenes. Faces incorporate both
simple (happy, sad, angry) and complex (relaxed, surprised, afraid) emotions. Prior to administration, children
are shown the emotional identification response cards and identify the sex, mental, and emotional states.
Children ascribe one of six emotions presented to a person/s in each of the scenes by pointing to the picture or
by verbally labeling the emotion. Following each stimulus presentation, children are prompted with questions
pertaining to inferred affective empathy (e.g., ‘How do you think this boy/girl/man feels?’), cognitive empathy
(e.g., ‘Can you tell me why this boy/girl/man feels ...?’ and ‘Please tell me more about what is happening’), as
well as behavioral elements of empathy (‘What would you do, if you were that boy/girl/man?’). In six scenarios,
two characters have blank faces and children are asked the same questions for each. The number of males and
females presented in each scene are counterbalanced.
Sample
The initial developmental sample comprised 220 children, aged from 7 to almost 11 years ( Reid et al., 2012 ).
Reliability
Internal Consistency
Reid et al. (2012) reported a Cronbach alpha coefficient for all 17 character scenarios of .84, for affective (.63),
for cognitive (.82), and for the behavioral scales (.84).
Test/C0Retest
Test/C0retest reliability coefficients are not currently available.275 OVERVIEW OF THE MEASURES
III. EMOTION REGULATION |
Validity
Convergent/Concurrent
There is a positive correlation between the cognitive and behavioral subscales (.42) ( Reid et al., 2012 ). Also, the
KEDS total score and cognitive and behavioral subscales correlate positively with the Bryant Index of Empathy
(.21, .14, and .20, respectively). The total and cognition scores correlate positively with both the Emotion
Vocabulary Test ( Dyck et al., 2001 ) and the Happe Strange Stories test ( Happe, 1994 ). The KEDS total score corre-
lates .21 with the BEQ, emotional vocabulary (.25), while behavior scores correlate .24 with emotional vocabulary.
The Wechsler Intelligence Scale for Children (WISC-IV; Wechsler, 2003 ) Full-Scale IQ, Verbal Comprehension
(VCI) and Perceptual Reasoning (PRI) subtests correlate positively with the KEDS total score, as well as with
affect and behavior subscales. KEDS total and affect scores correlate positively with Working Memory (WMI).
Divergent/Discriminant
The KEDS total and cognition scores do not correlate with the Emotion Recognition Task ( Baron-Cohen et al.,
1997 ). For total scores and for affective, cognitive, and behavioral subscales, older children exhibit significantly
higher mean scores on each scale than younger children. The KEDS total scale correlates negatively ( 2.23) with
the WCST-PE, while subscale correlations with the WCST-PE were as follows: affect ( 2.24), behavior ( 2.18).
Also, females score more highly on total KEDS and the cognition subscale than do males ( Reid et al., 2012 ).
Construct/Factor Analytic
A principal components analysis with varimax rotation produced four components. The first component
exhibited the highest loadings on items with single figures, positive emotions, and unhappy situations where
affect could be inferred without other characters’ mental states; this component was labeled ‘Simple’. The second
component loaded on items of figures experiencing conflicting emotions or where an expectation was violated
(situations which involve reconciling two perspectives); this component was labeled ‘Complex’. The third compo-
nent entailed items where figures were in conflict, attacking, or taking advantage of another figure; this compo-
nent was labeled ‘Aggression’. The fourth component loaded on items from a scenario that reflected a parent/
child interaction and was labeled ‘Authority’.
Criterion/Predictive
No criterion/predictive validity evidence is currently available.
Location
Reid, C., Davis, D., Horlin, C., Anderson, M., Baughman, N., & Campbell, C. (2013). The kids’ empathic devel-
opment scale (KEDS): A multi-dimensional measure of empathy in primary school-aged children. British Journal
of Developmental Psychology, 31 , 231/C0256.
Results and Comments
The KEDS aims to provide a comprehensive measure of empathy that overcomes problems in how an individ-
ual estimates empathy, the simplicity of scenarios in other story based scales, observer and expectancy bias that
transpires from self-report measures, as well as language restraints in young children. It also distinguishes
between empathy, sympathy, and distress. All KEDS scales (except cognitive subscale) display significant correla-
tions with the WISC-IV and the VCI, suggesting that performance on the KEDS depends to some extent on a
child’s general verbal comprehension. The cognitive scale, unlike the affective and behavioral scales, in most
cases does not require the child to go beyond the stimulus picture to infer the answer.
NEUROSCIENTIFIC MEASURES OF EMPATHY
Can neuroscientific measures such as MRI be used to measure empathy? The answer is Yes. To limit our mea-
surements of empathy to self-report or behavioral tasks would not satisfactorily progress research in the field.
We include neuroscientific measures here, highlighting their importance and future use (see Gerdes et al., 2010 ).276 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Magnetic Resonance Imaging (MRI)
(Banissy, Kanai, Walsh, & Rees, 2012 ).
Variable
MRI is a magnetic field neuroimaging technique that produces non-invasive images of the internal structures
of the body, including the central nervous system.
Description
An MRI scanner uses a strong magnetic field that aligns the atomic nuclei and radio frequency fields. The
resulting fields are processed by the scanner to reproduce an image of internal structures. The MRI scanner pro-
duces excellent spatial resolution (approximately 2 mm or better) and high levels of contrast between tissues of
the brain. The MRI technique is essentially a measure of the volume of certain brain regions /C0the dependent var-
iable being a volume measure (e.g., voxtels). The MRI does require compliance on behalf of the participant to
ensure accurate measurement (e.g., minimal movements during the scanning).
Sample
Due to the use of specialized equipment and the time consuming testing protocol, empathy assessment using
MRI has typically used small sample sizes. In addition, it is also necessary that the participants are screened to
rule out the potential influence of a range of other factors on the measurements. Screening is done for history of
psychiatric or neurological disorders, use of medications that affect central nervous system function, head
trauma, substance abuse, and other serious medical conditions.
Reliability
Inter-Rater
Levin et al. (2004) reported that two technicians assessed MRI images on three separate occasions to assess
inter-rater reliability. Both technicians showed good intra-class correlations between trials 1 and 2 (ICC 5.99 and
1.00) and between trials 2 and 3 (ICC 51.00 and 1.00). These findings were replicated by Kumari et al. (2009) .
Validity
Convergent/Concurrent
Certain brain regions subserve empathy (e.g., ACC, IFG) and so these are focused on in MRI (and fMRI)
research into empathy. Correlations between self-report measures such as the Interpersonal Reactivity Index (IRI)
and the Empathy Quotient (EQ) and these brain regions would seem to represent appropriate evidence of con-
vergent validity. Banissy et al. (2012) examined the correlations between grey matter and IRI scores in 118 healthy
adults. They reported that Perspective Taking scores correlated positively with left anterior cingulate volume
(.25). Sassa et al. (2012) examined the neural correlates between grey matter volume and scores on the child ver-
sion of the EQ in 136 boys and 125 girls (aged from 5.6 to 15.9 years). EQ scores correlated significantly (posi-
tively) with the regional grey matter volume of the precentral gyrus, the inferior frontal gyrus, the superior
temporal gyrus, and the insula. Hooker, Bruce, Lincoln, Fisher, and Vinogradov (2011) examined the correlation
between grey matter volume, IRI scores, and Quality of Life Scale (QLS) scores in 21 schizophrenia spectrum dis-
order patients and 17 healthy controls. Brain regions significantly associated with IRI Perspective Taking were
the hippocampus, anterior cingulate cortex (VMPFC), superior temporal gyrus, insula, and precuneus. In addi-
tion, there were also some regions relating to QLS-Empathy, including the insula, precentral gyrus, superior/
middle frontal gyrus, and anterior cingulate cortex.
Divergent/Discriminant
Banissy et al. (2012) also reported evidence of divergent validity, wherein the IRI measure of Empathic
Concern was found to correlate significantly (negatively) with grey matter volume in the left inferior frontal
gyrus ( 2.36). Also, Empathic Concern scores were significantly and negatively associated with left precuneus
(2.27), left anterior cingulate ( 2.25), and left insula volume ( 2.35).277 NEUROSCIENTIFIC MEASURES OF EMPATHY
III. EMOTION REGULATION |
Location
Banissy, M.J., Kanai, R., Walsh, V., & Rees, G. (2012). Inter-individual differences in empathy are reflected in
human brain structure. NeuroImage, 62 , 2034/C02039.
Results and Comments
MRI measures neuroanatomical structures that subserve empathy. Taken together, the cognitive component of
empathy is associated with grey matter volume of the ventral medial Prefrontal Cortex (vmPFC), whereas the
affective component of empathy is associated with grey matter volume of the inferior frontal gyrus, insula and
precuneus. The MRI cannot show the empathic process in action. The extent to which the size of a given brain
structure reflects a particular level of empathy, remains to be determined.
Functional Magnetic Resonance Imaging (fMRI)
(Singer, 2006 ).
Variable
Functional magnetic resonance imaging (fMRI) is an extension of MRI in which high resolution images of
activity levels in neural structures are obtained. Whereas MRI provides images of structural brain anatomy, fMRI
provides real-time images of brain activity by detecting increased blood supply and metabolic function (Blood
Oxygen Level Dependence or BOLD).
Description
A common technique in fMRI is blood oxygen level dependency (BOLD), which measures the hemodynamic
response related to energy use in neurons. Those neurons that are more active will consume more oxygen. fMRI
measures are used with tasks or stimuli that elicit empathy (e.g., PVP) and the corresponding brain activation is
measured. Like the MRI, fMRI has excellent spatial resolution (approximately 2 mm), but has comparatively
poorer temporal resolution (500 to 1000 ms). Another technique that produces spatial representations of active
neurons is positron emission tomography (PET). However, this method has not been used extensively in empa-
thy research (e.g., see Ruby & Decety, 2004; Shamay-Tsoory et al., 2005 ). Research using fMRI reveal the follow-
ing brain regions are associated with the empathic response: medial, dorsal medial, ventromedial and
ventrolateral prefrontal cortex ( Kra¨mer, Mohammadi, Don ˜amayor, Samii, & Mu ¨nte, 2010; Lawrence et al., 2006;
Seitz et al., 2008 ), superior temporal sulcus ( Kra¨mer et al., 2010 ), presupplementary motor area ( Seitz et al., 2008;
Lawrence et al., 2006 ), insula and supramarginal gyrus ( Lawrence et al., 2006; Carr, Iacoboni, Dubeau, Mazziotta,
& Lenzi, 2003 ), and amygdala ( Carr et al., 2003 ). Some of these findings have been extended to children ( Pfeifer,
Iacoboni, Mazziotta, & Dapretto, 2008 ).
Sample
As with MRI, due to the use of specialized equipment and the time consuming testing protocol, empathy
assessment using fMRI has typically used small sample sizes. In addition, it is also necessary that the participants
are screened to rule out the potential influence of a range of other factors on the measurements. Screening is
done for history of psychiatric or neurological disorders, use of medications that affect central nervous system
function, head trauma, substance abuse, and other serious medical conditions. It is also standard practice that
researchers state the number of right handed participants due to the laterality of brain functions. In many fMRI
studies, IQ scores and confirmation of normal or corrected to normal vision is also often stated.
Most research has used healthy adult participants recruited from the university population or local commu-
nity. This has included Carr et al. (2003) who used 7 males and 4 females with a mean age of 29.0 years
(range521 to 39), Lawrence et al. (2006) who used 6 males and 6 females with a mean age of 32.2 years
(SD59.95), Jackson et al. (2005) who used 8 males and 7 females with a mean age of 22.0 years ( SD52.6 years),
Gazzola, Aziz-Zadeh, and Keysers (2006) who used 7 males and 9 females with a mean age of 31 years
(range525 to 45), Seitz et al. (2008) who used 7 males and 7 females with a mean age of 28.6 years ( SD55.5),
Hooker, Verosky, Germine, Knight, and D’Esposito (2010) who used 8 males and 7 females with a mean age of
21.0 years (range 518 to 25), Kra¨mer et al. (2010) who used 11 males and 6 females with a mean age of 27.8 years
(SD54.8). Unlike prior research that has used samples consisting of males and females, Nummenmaa et al.
(2008) used only females ( N510) with a mean age of 26 years ( SD55.6 years). The researchers cited maximizing278 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
statistical power as the reason for the female-only sample because females were argued to experience generally
more intense emotional responsivity. Sex differences in fMRI were specifically examined by Schulte-Ru ¨ther et al.
(2008) who used 12 males with a mean age of 24.4 years ( SD53.0) and 14 females with a mean age of 24.8 years
(SD53.7). Xu et al. (2009) examined ethnic differences with a sample of eight male and nine female Chinese col-
lege students (mean age 523.0 years, SD52.0) and eight male and eight female Caucasian college students
(mean age 523.0 years, SD53.7). Few studies have used adolescent or children samples. Sterzer, Stadler,
Poustka, and Kleinschmidt (2007) used 12 male adolescents with conduct disorder (mean age of 12.75 years,
SEM50.49) recruited from clinics of the Department of Child and Adolescent Psychiatry in Germany and com-
pared this sample with 12 healthy male adolescents (mean age of 12.5 years, SEM50.45). Pfeifer et al. (2008)
used a sample of 16 children (nine boys and seven girls) aged from 9.6 to 10.8 years ( M510.2 years, SD50.4).
Reliability
Activations across the entire brain consistently resulted in positive correlations for lateralized indices of encod-
ing ( r5.82) and recognition ( r5.59)Wagner et al. (2005, p. 126) .
Test/C0Retest
Wagner et al. (2005) investigated test /C0retest reliability of activation patterns elicited in the medial temporal
lobes using fMRI and a verbal episodic memory paradigm over a 7 to 10-month time interval. They reported sig-
nificant test /C0retest coefficients of medial temporal lobe activations for encoding ( r5.41) but not for recognition
(r52.24).
Validity
Convergent/Concurrent
As indicated above in relation to MRI, certain brain regions subserve empathy (e.g., ACC, IFG) and these are
also focused on in fMRI research into empathy. Convergent validity with self-report empathy scales and fMRI
has been obtained. The IRI Perspective Taking subscale correlates positively with activation of a mirror neuron
system for auditory stimuli related to motor execution ( Gazzola et al., 2006 ). Activation in the somatosensory cor-
tex, inferior frontal gyrus, superior temporal sulcus, and middle temporal gyrus were positively correlated with
self-reported cognitive empathy as measured by the IRI Perspective Taking and Fantasy subscales ( Hooker et al.,
2010 ). Activity in the precentral gyrus was also significantly correlated with IRI Empathic Concern and IRI
Personal Distress subscales ( Hooker et al., 2010 ).Sterzer et al. (2007) reported that anterior insula activity was
positively associated with Impulsiveness /C0Venturesomeness /C0Empathy Questionnaire ( Eysenck & Eysenck, 1991 )
scores. Singer et al. (2004) reported that activation in the ACC and left anterior insula was positively correlated
with scores on the BEES (ACC: r5.52; left insula: r5.72) and the IRI Empathic Concern subscale (ACC: r5.62;
left insula: r5.52). A significant correlation ( r5.77) has been found between fMRI medial prefrontal cortex activ-
ity and favorable ingroup biases (ingroup /C0outgroup) in ratings of the amount of empathy felt towards indivi-
duals in pain scenarios (1 5not at all to 45very much ;Mathur et al., 2010 ).Shamay-Tsoory et al. (2005) used
Positrom Emission Tomography (PET) and showed that the cerebellum, thalamus, occipitotemporal cortex, and
frontal gyrus were more strongly activated during an empathy eliciting interview than a neutral interview.
Divergent/Discriminant
Xu et al. (2009) using fMRI showed that Caucasian and Chinese participants who viewed images of faces
receiving a painful injection showed more activity of the ACC and insular cortex if those images depicted people
of their own ethnicity than if they depicted people of another ethnic group. African-American participants have
shown greater activity of the medial prefrontal cortex when viewing members of their same ethnic group than
other ethnic groups ( Mathur et al., 2010 ).
Likewise, sex differences in brain regions activated during fMRI are apparent from various research studies.
For example, Schulte-Ru ¨ther et al. (2008) tested 12 males and 14 females in a picture viewing paradigm.
Participants viewed synthetic fearful or angry faces and were asked to concentrate on their own feelings when
viewing the faces (self-task) or on the emotional state in the target (other-task). Female participants scored more
highly on the BEES and rated the intensity of their own emotions when viewing the stimuli as higher than male
participants. Sex differences in fMRI were found in the comparison of the self-task with a baseline task wherein
females showed stronger activation of the right inferior frontal cortex, right superior temporal sulcus, and right
cerebellum than males. Males showed stronger activation of the left temporoparietal junction than females. In the279 NEUROSCIENTIFIC MEASURES OF EMPATHY
III. EMOTION REGULATION |
comparison of the other-task with the baseline, females showed stronger activation in the inferior frontal cortex
than males.
Criterion/Predictive
Using fMRI, Jackson et al. (2005) asked participants to imagine the feelings of another person and oneself in
painful situations and to rate the pain level from different perspectives. Adopting the perspective of the other
person was found to correlate positively with regional activation in the posterior cingulate/precuneus and right
temporo-parietal junction. Jackson et al. (2006) found in a sample of 15 healthy adults that subjective ratings of
pain of targets in photographic stimuli correlated significantly with activity in the anterior cingulate cortex sug-
gesting predictive validity for the brain region activations, and possibly of empathy for pain in others.
Nummenmaa et al. (2008) compared fMRI scans to images designed to elicit affective or cognitive components of
empathy. The cognitive empathy conditions depicted targets in everyday situations, whereas the affective condi-
tions depicted targets in hard, threat, or suffering situations. The affective condition elicited greater activation of
the thalamus (emotion processing), fusiform gyrus (face and body perception), and inferior parietal lobule and
premotor cortex (mirroring of motor actions) than did the cognitive condition.
Location
Singer, T. (2006). The neuronal basis and ontogeny of empathy and mind reading: Review of literature and
implications for future research. Neuroscience and Biobehavioral Reviews, 30 , 855/C0863.
Results and Comments
Among fMRI and PET research analyzing empathy, most of the studies have investigated empathy for pain
(Jackson et al., 2005 ), disgust ( Wicker et al., 2003; Benuzzi, Lui, Duzzi, Nichelli, & Porro, 2008 ), threat
(Nummenmaa et al., 2008 ) and pleasantness ( Jabbi, Swart, & Keysers, 2007 ). Research that examines empathy
using stimuli depicting facial expressions in different situations or social interactions is at risk of confounding
empathy with emotion perception. In addition, fMRI and PET research is interpreted to reflect the neural
responses related to empathy. However, it might be argued that such responses are actually related to aversive
responses coupled with motor preparation for defensive actions in general ( Yamada & Decety, 2009 ).
Facial Electromyography (EMG)
(Westbury & Neumann, 2008 ).
Variable
Electromyography is the measurement of the electrical potentials produced by skeletal muscles when they con-
tract ( Neumann & Westbury, 2011 ). In contrast to alternative approaches to measuring facial expressions (e.g.,
observer ratings), EMG activity has the advantage of being able to detect muscle activity that occurs below the
visual threshold. It provides a non-verbal index of motor mimicry which many theorists argue underlies
empathic responding (e.g., Preston & de Waal, 2008).
Description
Facial EMG recordings can be obtained by attaching small surface electrodes on the skin over the site of the
muscles that play a role in the facial expression of interest. These muscles are primarily the corrugator supercilli ,
zygmaticus major ,lateral frontalis ,medial frontalis ,levator labii superioris ,orbicularis oculi , and masseter . Inferences
regarding the intensity of the facial expression are gained by measuring the magnitude of the EMG signal.
However, the application of electrodes onto the face may increase awareness of facial expressiveness and lead to
exaggerated facial reactions or more general demand characteristics.
Sample
The four studies that have examined facial EMG measurement of empathy have sampled from healthy adult
university populations. Westbury and Neumann (2008) used 36 male and 37 female university students with a
mean age of 22.5 years ( SD56.9). Similarly, Sonnby-Borgstro ¨m (2002) used 21 male and 22 female university stu-
dents with a median age of 23 years (range 18 to 37) and Sonnby-Borgstro ¨m, Jo¨nsson, and Svensson (2003) used
36 male and 24 female university students with a median age of 22 years (range 19 to 35). Brown, Bradley, and280 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
Lang (2006) recruited two samples from a university population: one consisting of 21 male and 22 female African
Americans and the other 20 male and 20 female European Americans. The ages for each sample were not
described, although it was reported that 98% of the total sample were aged between 17 and 25 years.
Reliability
Internal Consistency
Westbury and Neumann (2008) reported a Cronbach alpha coefficient of .92 over all stimuli used in a picture-
viewing paradigm.
Test/C0Retest
‘Facial EMG shows moderate test /C0retest stability over relatively long intervals ...’(Harrigan, Rosenthal, &
Scherer, 2008 , p. 41).
Validity
Convergent/Concurrent
‘Facial EMG has high concurrent validity with visible intensity changes in onset phase of zygomatic major,
with average correlation above 0.90.’ ( Harrigan et al., 2008 , p. 40). Westbury and Neumann (2008) reported that
ratings on the BEES were significantly correlated with corrugator EMG activity when viewing images of human
and non-human animals in negative circumstances ( r5.35). In addition, subjective ratings of empathy towards
the targets in the images were significantly correlated with corrugator EMG activity ( r5.41). Subjective empathy
ratings and corrugator EMG showed the same pattern across different animal groups (e.g., higher for human tar-
gets than bird targets). Activity of the orbicularis oculi muscle when viewing another person receiving painful
sonar treatment has shown to be significantly correlated with scores on the IRI perspective taking subscale
(r5.39). Facial EMG during pictures of happy and angry facial expressions has been shown to be correlated with
scores on the EETS ( Sonnby-Borgstro ¨m, 2002; Sonnby-Borgstro ¨m et al., 2003 ). In recordings of the orbicularis
occuli, indicative of wincing, participants showed greater activity relative to a pre-stimulus baseline when view-
ing others undergoing painful sonar treatment when taking the perspective of the other person ( Lamm, Porges,
Cacioppo, & Decety, 2008 ).
Divergent/Discriminant
Brown et al. (2006) conducted a study in which African American and European American participants
viewed images depicting pleasant and unpleasant facial expressions. African American participants showed
larger corrugator EMG responses to unpleasant pictures of Black targets than to unpleasant pictures of White tar-
gets. However, the same ethnic difference was not found in the European American participants. Sex differences
may also be observed in facial EMG ( Dimberg & Lundquist, 1990 ).
Location
Westbury, H.R., & Neumann, D.L. (2008). Empathy-related responses to moving film stimuli depicting human
and non-human animal targets in negative circumstances. Biological Psychology, 78 ,6 6/C074.
Results and Comments
EMG activity is advantageous in its ability to detect muscle activity that occurs below the visual threshold.
Although, researchers should take care to ensure that any motor mimicry observed through facial EMG recording
reflect the stimuli the participant is being exposed to and not other stimuli. For example, corrugator EMG can be
elicited by non-facial visual stimuli and even sounds ( Larsen, Norris, & Cacioppo, 2003 ).
Electroencephalogram (EEG) and Event Related Potentials (ERPs)
(Neumann & Westbury, 2011 ).
Variable
The EEG and ERP measure the electrical activity produced by the firing of neurons in the scalp. The firing of
the neurons is presumed to reflect psychological processes, including the empathic response. Short-term changes
in the EEG are termed event-related potentials (ERPs).281 NEUROSCIENTIFIC MEASURES OF EMPATHY
III. EMOTION REGULATION |
Description
The recordings are taken through electrodes placed on the surface of the scalp. Electrode locations are based
on the 10 /C020 System that defines regions as frontal (F), central (C), parietal (P), temporal (T), and occipital (O).
Electrode caps are designed to correspond to these regions and may contain 32, 64, 128, or 256 potential electrode
locations. The EEG signal is characterized according to the pattern of brain waves defined according to the fre-
quency band in which they are found. The frequency bands include alpha (8 to 13 Hz), beta (14 to 30 Hz), gamma
(30 to 100 1Hz), theta (4 to 7 Hz), and delta (0.5 to 3.5 Hz). ERPs are described in terms of whether the potential
is a positive or negative wave and the latency in which the wave occurs. The N100, for example, is a negative
change that occurs approximately 100 ms following stimulus onset. EEG and ERP show excellent temporal reso-
lution by being able to sample brain activity at 2000 Hz or better.
Sample
Light et al. (2009) examined data from children aged 6 years (8 children), 7 years (25 children), 8 years (45 chil-
dren), 9 years (27 children) and 10 years (6 children). The resulting sample had a mean age of 7.92 years
(SD50.98) and consisted of 52 males and 56 females. In their research, Gutsell and Inzlicht (2012) tested 17 male
and 13 female White right-handed university students with a mean age of 18.46 years ( SD53.81). Mu, Fan, Mao,
and Han (2008) recruited 11 male and 4 female adults with a mean age of 20.8 years ( SD51.82) and who were
all right handed and had normal vision. Similarly, Han, Fan, and Mao (2008) recruited 13 males (mean age 520.9
years, SD52.25) and 13 females (mean age 521.0 years, SD51.47) that were screened for normal or corrected to
normal vision and were all right handed.
Reliability
Schmidt et al. (2012) reported evidence of ERP reliability and split-half reliability.
Test/C0Retest
Schmidt, et al. (2012) also reported test /C0retest reliability in absolute frontal ( r5.86 to .87) central ( r5.94), and
parietal ( r5.95 to .96) EEG alpha power for a resting condition over a one-week period. Williams, Simms, Clark,
and Paul (2005) reported that over a 4-week interval, for both eyes open and eyes closed resting periods (of two
minutes duration), that EEG data did not differ across sessions with respect to alpha, beta, theta, and delta
waves. Test /C0retest reliability coefficients ( r5.71 to .95) were reported with larger reliability coefficients for eyes
open as compared with eyes closed conditions. Numerous other studies have also provided evidence for
test/C0retest reliability of up to 1-year ( Cassidy, Robertson, & O’Connell, 2012; Ha ¨mmerer, Li, Vo ¨lkle, Mu ¨ller, &
Lindenberger, 2012; Segalowitz, & Barnes, 2007 ).Williams et al. (2005) revealed that for oddball targets, N100
amplitude and latency (.76 and .72 respectively), P200 amplitude (.68), N200 amplitude and latency (.47 and .71
respectively) and P300 latency (.56) all provided significant partial correlations over a 4-week interval. For odd-
ball non-targets, N100 amplitude and latency (.74 and .63 respectively) and P200 amplitude and latency (.82 and
.62 respectively) also showed moderate test /C0retest reliability. Furthermore, Williams et al. (2005) provided
test/C0retest reliability coefficients for P150 amplitude and latency (.84 and .93) and P300 amplitude and latency
(.55 and .52) on a working memory task.
Validity
Convergent/Concurrent
Using EEG during a pleasurable task in 6 to 10 year old children, self-report measures of empathic concern
and positive empathy were related to increased right frontopolar activation ( Light et al., 2009 ). A second form of
positive empathy was related to increasing left dorsolateral activation ( Light et al., 2009 ) thus highlighting the
role of prefrontal activity in association with empathy. Gutsell and Inzlicht (2012) revealed that higher prefrontal
alpha asymmetry scores to both in-group and out-group members appeared to be associated with higher scores
on the EQ ( Baron-Cohen & Wheelwright, 2004 ).
Divergent/Discriminant
In an analysis of the role of theta and alpha oscillations in empathy for pain, Mu et al. (2008) used wavelet
EEG with healthy adults who judged pain in pictures of hands in painful or neutral contexts. Pain related stimuli
increased theta event-related synchronization at 200 to 500 ms and decreased alpha at 200 to 400 ms. Theta
event-related synchronization was positively correlated with subjective ratings of perceived pain while alpha282 10. MEASURES OF EMPATHY: SELF-REPORT , BEHAVIORAL, AND NEUROSCIENTIFIC APPROACHES
III. EMOTION REGULATION |
event-related desynchronization was negatively correlated suggesting that theta and alpha oscillations are impli-
cated in emotional sharing and regulation for empathy in pain scenarios. Gutsell and Inzlicht (2012) explored
EEG alpha oscillations in observers who viewed stimuli of in-group/out-group members in sad contexts and
showed that participants displayed similar prefrontal alpha asymmetry activation toward in-group members
compared with when the participants felt sad themselves. Participants did not display similarity in prefrontal
alpha asymmetry when viewing pictures of out-group members.
Criterion/Predictive
Han et al. (2008) investigated empathy for pain by measuring ERPs in relation to pictures of hands in painful
or neutral situations and revealed that subjective ratings of perceived pain in others were positively correlated
with ERP amplitudes (at 140 /C0180 ms).
Location
Neumann, D.L., & Westbury, H.R. (2011). The psychophysiological measurement of empathy. In D.J. Scapaletti
(Ed.), Psychology of empathy (pp. 119 /C0142). Hauppauge NY: Nova Science.
Results and Comments
EEG and ERP show relatively poor spatial resolution but provide excellent temporal resolution enabling time
locked stimulus presentations to be matched with neural activity. However, physical movement and eye blinks
can also interfere with EEG and ERP recordings and counter methods (e.g., eye blink recordings) must be taken
to account for such artifacts.
FUTURE RESEARCH DIRECTIONS
The great diversity in approaches to measuring empathy may be interpreted in different ways. It could mean
that researchers have yet to find an adequately reliable and valid means by which to measure empathy. It could
also reflect the highly complex and multifaceted nature of empathy. It could indicate that what empathy is and
how it should be measured is quite different from situation to situation or population to population. Regardless,
the various measurement approaches may present a significant advantage to researchers and practitioners who
wish to measure empathy. Selecting from the different measurement traditions of self-report, behavioral/observa-
tional, and social cognitive is advantageous.
Subjective self-report measures of empathy currently provide the most comprehensive measures to date.
However, uncertainty remains as to whether empathy should be measured as a unidimensional or a multidimen-
sional construct. Current unidimensional measures tend to be biased towards measuring the affective component of
empathy. In contrast, most multidimensional measures consider empathy to consist of at least two components /C0
affective and cognitive empathy. Aside from their subjectivity and susceptibility to motivational distortion and
response bias, another limitation of self-report measures is that each measure has been based on a different defini-
tion of empathy ( Reniers et al., 2012 ).Lovett and Sheffield (2007) argued that due to questionable psychometric
properties and the social desirability of empathy, self-report measures may be unreliable and contaminated with
motivation/response bias. Furthermore, most of the longstanding measures give little consideration to the multi-
dimensional conceptualization of empathy when research findings suggest that empathy is a multidimensional
construct involving at least cognitive and affective processes ( Baron-Cohen & Wheelwright, 2004; Davis, 1983 ).
Another criticism of self-report measures of empathy is that they are prone to presentation bias (e.g.,
Eisenberg & Fabes, 1990 ). Being empathic is likely to be regarded as a socially desirable trait in society, particu-
larly in certain occupational groups including teachers and health care workers. The extent to which response
bias influences responses on self-report measures warrants further consideration. Indeed, in the development of
the BES, Jolliffe and Farrington (2006a) included six items from the Lie Scale of the Eysenck Personality
Questionnaire ( Eysenck & Eysenck, 1991 ) to provide a measure of social desirability. Joliffe and Farrington
reported that scores on the IRI Perspective Taking and Empathic Concern subscales correlated positively with
scores on the Lie Scale ( r..15).
Neuroscientific measures of empathy promise to be an ever expanding field in future research. The increasing
development of technology, combined with cheaper and easier to use equipment, will make neuroscientific mea-
sures more easily available for researchers. However, as a methodology that promises to provide an objective283 FUTURE RESEARCH DIRECTIONS
III. EMOTION REGULATION |
and quantifiable measure of empathy, substantial future work is required. Psychometrically grounded research is
required to develop a standardized testing protocol that includes both the test stimuli and parameters of the mea-
surement approach (e.g., data scoring and quantification). Moreover, the testing protocol is required to undergo
the necessary tests of item homogeneity, reliability, and validity. While current research tends to support the
validity of neuroscientific measures in the form of convergent and discriminative validity, other forms of validity
require further confirmation. Moreover, the reliability of the various measures has yet to be determined in the
context of empathy measurement. In the absence of such information, the promise of the objectivity that neurosci-
entific approaches can bring to empathy measurement will not be fulfilled.
Neuroimaging techniques provide the most direct link between empathy and the activity of the brain regions
that underlie them. However, it is also a technique that is currently expensive, has high technical requirements,
and displays low temporal resolution. Facial EMG provides an objective measurement of motor mimicry and is
linked to the most information rich part of an empathy eliciting situation (i.e., the face). However, it can be lim-
ited by measuring only one muscle group whereas facial expressions reflect the combined action of many and it
appears only validated for the affective component of empathy. The EEG and ERP provide the advantage of high
temporal resolution and link to cognitive and emotional processes that are associated with empathy. However, it
requires technical equipment and is largely limited to recording the action of brain structures near the surface of
the skull. All neuroscientific approaches can suffer from interpretation difficulties if they are not correctly used.
For example, a range of psychological processes and environmental stimuli may influence the physiological pro-
cesses under investigation. Thus, it is important to ensure a strong link between the observed change in the phys-
iological response and the empathic response.
Another limitation of most approaches to empathy measurement is that they do not permit an assessment of
empathy across the entire lifespan. The complex nature of empathy and the type of self-insight that is required
has meant that instruments constructed in adults have not been suitable for empathy assessment in children.
This has resulted in the development of child or adolescent scales through the modification of adult question-
naires. The MDEES ( Caruso & Mayer, 1998 ) represents one exception to this rule due to its construction using
adult and adolescent samples. However, it remains to be validated with young child samples. Future research
might develop an empathy measure applicable across any age group. In self-report measures, the use of ‘plain
language’ worded items may be one means by which this could be done. For example, the item ‘The suffering of
others deeply disturbs me’ from the MDEES may be reworded in plain terms as ‘I get upset when I see someone
in pain’.
Although current empathy measures continue to have several limitations ( Reid et al., 2012 ), a potentially fruit-
ful avenue is to combine measures to provide a comprehensive approach to empathy assessment, drawing on the
diversity of self-report, behavioral, and neuroscientific measurement approaches. Such a battery may best com-
prise a broad self-report measure of empathy administered in conjunction with appropriate behavioral tests or
physiological measures of empathy in specific situations, such as in emotional contagion, motor mimicry, or
empathy for pain.
Acknowledgements
This research received support from a Griffith Health Institute Project Grant, Griffith Health Institute Area of Strategic Investment for Chronic
Disease Project Grant, and Bond University Vice Chancellor’s Research Grant Scheme. The assistance of Kylie Loveday in research assistance
and manuscript preparation is gratefully acknowledged.
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CHAPTER
11
Measures of Resiliency
Sandra Prince-Embury1, Donald H. Saklofske2and Ashley K. V esely2
1Resiliency Institute of Allenhurst LLC, West Allenhurst, NJ, USA;2University of Western Ontario, London,
Ontario, Canada
Resilience, resiliency or the ability to ‘bounce back’ in the face of adversity has been a topic of investigation
by psychology theorists for the past 50 years. Within e veryday lexicon, we see references to ‘she is a strong
woman,’ ‘he is a real survivor,’ or ‘how did they mana ge to overcome such hardships experienced during the
war!’ Researchers had also observed that some youth and adults managed to survive exposure to adversity
and even thrive in later life, while others were less succ essful to the point of developing various physical and
psychological disorders, sometimes leading to death by suicide, personal neglect, or excessive stress on the
physical self.
Interest in this topic has grown as technologically enha nced information access has increased awareness of
the overwhelming physical and psychological events that impact us on a daily basis. This can range from nat-
ural disasters such as the earthquake that struck Japan or the great Indian Ocean Tsunami in recent times, the
horrific list of man-made disasters ranging from terror ist attacks in African and Middle East counties, or the
Holocaust of WWII, to the random killings of civilians in schools and public places in the USA and other
countries. Each day, news reports on the web, televisi on, and radio bring more reports of the ‘inhuman’ civil
wars that have recently engulfed countries such as Syria. The economic instability caused by faltering country
economies in Europe has led to lost jobs and pensions, as well as future job uncertainty amongst youth. The
stresses and strains of everyday life that include caring for an ill child or parent, studying for a difficult
exam, or the threat of job loss are exacerbated as con ditions become more extreme and tax human capacity
and spirit.
This chapter will present a theoretical discussion of resilience/resiliency as well as measurement issues
related to tapping these constructs. One major measurem ent issue is that lack of consensus regarding the pre-
cise definition of resilience. For example, Luthar, Cicchetti, and Becker (2000) have pointed to the distinction
between the terms ‘resiliency’ and ‘resilience.’ ‘Resilien ce’ refers to the interaction between the person and his
or her environment that brings about a ‘resilient’ out come. Resiliency on the other hand refers to personal
qualities that influence the individual’s ability to ex perience a resilient outcome. The majority of the measures
reviewed in this chapter pertain to personal attributes with the exception of the ClassMaps Survey, which tar-
gets the interaction occurring in a particular classroom and the CYRM-28 which look s at the individual within
a cultural context.
DEVELOPMENTAL VIEWS OF RESILIENCY
The study of resilient children and adults has gone t hrough many rich phases of discovery, identifying
aspects of both the person and environment that appear to serve as protective or mitigating factors influencing
the impact of adversity (see Luthar, 2003, 2006; Masten, 2007 ). The particular focus of much of the
290Measures of Personality and Social Psychological Constructs.
DOI: http://dx.doi.org/10.1016/B978-0-12-386915-9.00011-5 ©2015 Elsevier Inc. All rights reserved. |
developmental research has been the identification of f actors that were present in the lives of those who both
survived and thrived in the face of adversity compared to those who did not ( Garmezy, Masten, & Tellegen,
1984; Luthar, 1991, 2003; Masten, 2001; Rutter, Harring ton, Quinton, & Pickles, 1994; Werner & Smith, 1982,
1992, 2001 ).
Examining the evolution of the construct and study of resilience, Masten and Wright (2009) described four
phases of research directed primarily by developmental researchers who approached the study of this construct
from different perspectives across time ( Masten, 2007 ; Wright & Masten, 2005). The first wave focused on
description, with considerable investment in defining and measuring resilience, and in the identification of differ-
ences between those who did well and poorly in the context of adversity or risk of various kinds. This research
revealed consistency in protective factors, such as qualities of people, relationships, and resources that predict
resilience, which were found to be robust in later research.
The second wave of research moved beyond descriptio ns of the factors or variables associated with resil-
ience to a greater focus on processes (i.e., the ‘how’ que stions) aimed at identifying and understanding those
that might lead to resilience. These studies led to new labels for these processes, such as ‘protective,’ ‘moderat-
ing,’ ‘compensatory,’ etc. Two of the most basic model s described compensatory an d moderating influences on
the development of resilience. In compensatory models, f actors that neutralize or cou nterbalance exposure to
risk or stress have direct, independent, and positive effects on the outcome of interest, regardless of risk level.
These compensatory factors have been termed assets ,resources ,a n d protective factors in the literature. Higher
intelligence or an outgoing personality might be considered assets or resources that are helpful regardless of
exposure to adversity. In protective or ‘moderating eff ect’ models, a theoretical factor or process has effects
that vary depending on the level of risk. A classic ‘protec tive factor’ shows stronger effects at higher levels of
risk. Access to a strong support system might be considere d protective in that its protective influence is more
noticeable in the face of adversity.
The third era of research began with efforts to test ideas about resilience processes through interventions
designed to promote resilience such as the promotion of positive parenting (Brooks and Goldstein, 2001). Brooks
and Goldstein translated basic principles of promoting a healthy mindset in children and disseminated this infor-
mation to professionals, teachers, and parents in a variety of venues including books and training workshops for
parents, teachers, and other caregivers. These programs and findings laid the groundwork for many of the
school-based mental health initiatives we see today.
The fourth wave of resilience research includes discu ssion of genes, neurobehavioral development, and sta-
tistics for a better understanding of the c omplex processes that led to resilience ( Masten, 2007 ). These studies
often focus at a more molecular level examining how proc esses may interact at the biological level. Some of
this work has led to the proposal of concepts such as diffe rential susceptibility and sensitivity to context, to
explore the possibility that some individuals are more sus ceptible or sensitive to the influence of positive or
negative contexts.
ADULT VIEWS OF RESILIENCY
Although the study of early childhood development is often viewed as the intellectual home of the construct,
‘resilience’ has also been described as an aspect of adult personality. Block (1989) conceived of ‘Ego-resiliency’ in
adults as a meta-level personality trait associated with the concept of ‘ego’ as a complex integrative mechanism.
Ego-resiliency is defined as the ability to adapt ones level of emotion control temporarily up or down as circum-
stances dictate ( Block, 2002; Block & Block, 1980 ). The related assumption is that this flexibility in controlling
emotion is a relatively enduring trait, which impacts a variety of other abilities including but not limited to sur-
vival in the face of adversity. Furthermore, Block and Kremen (1996) linked positive affect, self-confidence, and
overall psychological adjustment to resiliency.
Other theorists have identified traits in adults that overlap with the notion of ‘resiliency.’ One such construct
is that of ‘hardiness’ described by Kobasa and colleagues. Hardiness is characterized by three general assump-
tions about self and the world ( Kobasa, 1979, 1982 ; Maddi, 2002, 2005). These include (a) a sense of control over
one’s life (e.g., believing that life experiences are predictable and that one has some influence in outcomes
through one’s efforts); (b) commitment and seeing life activities as important (e.g., believing that you can find
meaning in, and learn from, whatever happens, whether events be negative or positive); and (c) viewing change291 ADULT VIEWS OF RESILIENCY
III. EMOTION REGULATION |
as a challenge (e.g., believing that change, positive or negative, is an expected part of life and that stressful life
experiences are opportunities).
Victor Frankl (1959) highlighted the importance of sense of meaning in adult resilience, suggesting that it
can act as a buffer to negative affect in the face of adversity by allowing the individual to find prayer, support
in God, or understanding within the context of a religion or another belief system. The belief that one
still has choice in the face of adversity can provide strength as illustrated in Frankl’s book, Man’s Search for
Meaning (1959).
Findings from earlier phases of developmental research of resilience as well as constructs such as ‘ego-
resiliency’ seem to imply that resilient individuals are ex traordinary and that this quality is not accessible to
everyone. Later research, characteristic of phase two, suggested that resilience was largely a product of a com-
plex interaction of factors in which the individual’s env ironment played a significant part. Along with this shift
in emphasis came questioning of whether ‘resilience’ is ex traordinary. The emergence of resilience as ‘ordinary
magic’ by Masten identified the proce ss as characteristic of normal development and not applicable in adverse
circumstances only ( Masten, 2001; Masten & Powell, 2003 ).Masten (2001) suggested that fundamental systems,
already identified as characteristic of human functionin g, have great adaptive signifi cance across diverse stres-
sors and threatening situations. This shift in emphasis ha d significant implications. The ‘ordinary magic’ frame-
work suggested by Masten extends application of resilien ce theory to a broader range of individuals in varied
contexts.
CONCEPTUAL AND APPLICATION ISSUES
There has been considerable divergence in the literature with regard to the definition, criteria, or standards for
describing and consequently measuring resiliency; whether it is a trait, a learned process or an outcome variable;
whether it is enduring or situation specific; whether survival in the face of adversity is required and the nature
of the adversity required for resiliency to be demonstrated (e.g., what is a sufficient exposure risk factor?). Wald,
Taylor, Asmundson, Jang, and Stapleton (2006) pointed to a lack of consensus on the definition of resilience.
According to them, there are several existing definitions of resilience that share in common a number of features
all relating to human strengths, some type of disruption and growth, adaptive coping, and positive outcomes fol-
lowing exposure to adversity (e.g., Bonanno, 2004 ; Connor et al., 2003; Fredrickson, Tugade, Waugh, & Larkin,
2003; 2005; Masten et al., 1999; Richardson, 2002 ). There are also several distinctions made in attempt to define
this construct. For example, some investigators assume that resilience is located ‘within the person’ (e.g., Block &
Block, 1980; Davidson et al., 2005 ). Other investigators (e.g., Friborg, Hjemdal, Rosenvinge, & Martinussen, 2003;
Luthar, et al., 2000; Masten, 2001 ) propose that there are multiple sources and pathways to resiliency, including
social context (e.g., family, external support systems). Luthar et al. (2000) have provided clarification by distin-
guishing between ‘resilience’ as a dynamic developmental process or phenomenon that involves the interaction
of personal attributes with environmental circumstances, and ‘resiliency’ ( Block & Block, 1980 ) as a personality
characteristic of the individual.
The definition of resilience/resiliency has varied across research focus and population studies, (Prince-Embury &
Saklofske, 2013). Some critics have suggested that this lack of consensus in the definition of resilience makes the use
of the construct questionable ( Kaplan, 2005, 1999 ). However, if these criteria were strictly applied, then the same chal-
lenges could be directed to intelligence, personality, and most other psychological constructs. In contrast, we suggest
that ‘the baby should not be thrown out with the bathwater,’ but that the presence of an operational definition, con-
sistent assessment and utility of the construct should determine the usefulness of the construct as applied in specific
circumstances (Prince-Embury, 2013).
Definition and assessment problems notwithstanding, in the past few years, a plethora of self-help books and
interventions have been published that have not been systematically linked to sound core developmental
constructs and empirical support. These interventions are often not tested for effectiveness. Some interventions
that are found to be effective are explained on the basis that they increase resiliency while this implied mediating
process is not documented. Thus, there is a disconnection between the complex theory and body of research
on resiliency and the abundant self-help techniques and programs employing this term (Prince-Embury, 2013). It
is within this context that a thorough understanding of the resilience/resiliency construct(s) and measures is
needed.292 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
Several researchers and theorists have attempted to integrate the many research findings and their implica-
tions for practical application, including assessment. However, the understanding that resilience is a product of
complex interactions of personal attributes and environmental circumstances, mediated by internal mechanisms,
has presented an assessment challenge to developmental researchers ( Luthar et al., 2000 ). Some longitudinal
studies from a developmental psychopathology perspective have tried to capture contextual aspects of resilience
specific to the group and sets of circumstances ( Masten, 2001, 2006; Werner, 2005 ). These studies have employed
extensive batteries of preexisting tests to assess personal resiliency, but like most research in this area, different
measures have been used across both research studies and populations, making it difficult to compare the results
of these published studies. The research-based tools employed in previous studies have often been impractical
for widespread use in the schools and communities because they are too labor intensive, expensive, or focused
on presence or absence of psychiatric symptoms. Consequently, the lack of a common metric for measuring resil-
iency has resulted in difficulty assessing the need for, choice of, and effectiveness of preventive intervention strat-
egies in a way that allows comparison across methods and populations. Thus it is the purpose of this chapter to
present and review measures of resilience/resiliency that are application friendly and consistent with conceptual
definitions presented by these assessments.
MEASURES REVIEWED HERE
Ten measures are reviewed for their theoretical grounding, psychometric underpinnings, and application.
These scales/measures are presented as examples of operationalized definitions of resiliency/resilience that vary
by the intended purpose of the assessment and age of the intended respondent.
1.Ego-resiliency Scale ( Block, 1989; Block & Block, 1971; Block & Kremen, 1996; Block et al., 1988 )
2.Resilience Scale (Wagnild, 1987)
3.Resilience Scale for Adults ( Friborg et al., 2003 )
4.Connor /C0Davidson Resilience Scale ( Connor & Davidson, 2003 )
5.Brief Resilience Scale ( Smith et al., 2008 )
6.Resiliency Scales for Children and Adolescents ( Connor et al., 1999; Davidson et al., 2006; Prince-Embury,
2006, 2007 )
7.Child and Youth Resilience Measure ( Ungar & Liebenberg, 2009, 2011 )
8.Social/C0Emotional Assets and Resiliency Scales ( Merrell, 2011 )
9.Devereux Student Strengths Assessment (LeBuffe et al., 2009)
10.ClassMaps Survey ( Doll, Zucker, & Brehm, 2004, 2009 )
Instruments selected for this review need to have the intended purpose of assessing strengths, including resil-
ience/resiliency and must have had a least one major favorable review in the published literature and have been
included in several studies supporting their reliability and validity. In addition, the measures selected must dem-
onstrate practical applicability in both applied and research settings. Thus many other measures that may be
more (e.g., hardiness) or less (e.g., psychological flourishing) linked to resiliency have not been included.
However we do acknowledge that there is overlap between many factors that have causal, mediating, moderat-
ing, and outcome relationships with resiliency. Selection of a resiliency measure must also take conceptual issues
into account. The first consideration is whether the assessment is for children, adolescents, or adults. Scales will
vary both in reading level and in the cognitive and developmental complexity of the construct(s) they are asses-
sing. Although protective factors present in childhood may predict better outcome later in life, the actual expres-
sion and experience of resilience may differ across the lifespan.
A second consideration is whether resiliency is considered as a one-dimensional or multidimensional con-
struct. Although much discussion of resilience has referred to it as one-dimensional, most assessment tools
assume multiple dimensions. Some scales have identified the dimensions after the fact by using statistical meth-
ods (exploratory factor analysis) to define the dimensions or subscales. Other tools have selected the theoretical
constructs first and then built the assessment tool around these constructs.
A third consideration is whether resiliency is considered a trait, a state, or a combination of both. Instruments
such as Block and Kremen’s Ego-resiliency Scale consider resiliency as a trait or a relatively enduring characteristic.
Other scales such as the RSCA ( Prince-Embury, 2006 ) consider resiliency as modifiable through appropriate293 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
intervention. The ClassMaps instrument (Doll et al., 2003) considers resilience as a characteristic of a classroom
experience resulting from the interaction between the teacher, teaching method, and the children in the classroom.
The first three instruments presented, the ER89 (Block & Kremen, 1989), the RS (Wagnild, 2003), and the RSA
(Friborg, Hjemdal, Rosenvinge, & Martinussen, 2003 ) represent resiliency scales that are intended for adults,
have strong conceptual underpinnings and may be considered largely assessments of traits or relative enduring
characteristics. Both the ER89 and the RS treat resilience/resiliency as one dimensional in that one total score is
utilized, although both scales conceptualize resilience as consisting of multiple characteristics. The fourth and
fifth scales reviewed represent scales that were initially developed for use in medical settings. The CD-RISC
(Connor & Davidson, 2003 ) was developed to demonstrate change in PTSD symptoms due to medication. The
BRS ( Smith et al., 2008 ) was developed to access the specific aspect of resilience relating to ability to bounce back
from stress. Both of these scales assume that resiliency is modifiable, particularly as mediated by psycho-
pharmaceutical intervention. These two instruments each generate one total score and may also be considered
one-dimensional.
The next five scales described apply to children and adolescents. The RSCA ( Prince-Embury, 2006 ) was
designed to tap core aspects of personal resiliency for the purpose of preventive screening and intervention and
for assessment of change associated with interventions. The CYRM-28 ( Unger & Liebenberg, 2009 ) was developed
to tap resilience as the result of internal and external factors in a way that is sensitive to cultural differences. The
SEARS ( Merrell, 2011 ) and DESSA (LeBuffe et al., 2009) were designed to assess strengths in children and these
include resiliency. The ClassMaps Survey (CMS) was defined as an ecological tool to assess the resilience of class-
rooms based on the assumption that the interaction between the child and the environment defines resilience rel-
evant to school engagement and learning.
Ego-Resiliency Scale (ER89)
(Block & Kremen, 1996 ).
Variable
Ego-resiliency was conceptualized by Block as a component of personality, which served as a ‘structure for
managing emotion’ ( Block, 2002 ). Block and associates developed self-report scales for both ego-control and ego-
resiliency. The ego-resiliency scale (ER89) is intended to assess trait variation in psychological resilience.
Description
The ER89 is a 14 item measure with responses on a 4-point scale ranging from 0 to 4, and a high score indicat-
ing high ego-resiliency. Items were drawn from the Minnesota Multiphasic Personality Inventory (MMPI) and the
California Psychological Inventory (CPI), were written by Block, or came from other sources that are untraceable
(see Block & Kremen, 1996 ). In his book Personality as an Affect Processing System , (2002), Block presented his
model of personality as an adaptive system for taking in, organizing information, and maintaining non-
disruptive levels of anxiety while responding to inner and outer demands. His proposed system consists of a per-
ceptual and control mechanisms operating in delicate balance.
Ego-control (EC) and ego-resiliency (ER) comprise the central mechanisms for understanding Block’s model of
an adaptive personality system ( Block, J., 1950, 2002 ; Block, J.H., 1951; Block & Block, 1980 ). Ego-control refers to
an adaptive system of impulse inhibition/expression and ego-resiliency encompasses an adaptive system for
modifying one’s level of control in response to situational demands. As a personality theorist, Block employed
these mechanisms to explain relatively enduring traits.
Ego-resiliency is the ability to adapt one’s level of control temporarily up or down as circumstances dictate
(Block, 2002; Block & Block, 1980 ). Highly ego-resilient individuals were described as characteristically able
to modify their level of control to suit the situational context. Individuals with a low level of ego-resiliency
were seen as more restricted in their response to the same level of impulse containment or expression regardless
of the situational context. As a result of this adaptive flexibility, individuals with a high level of ego-resiliency
are more likely to experience positive affect, and have higher levels of self confidence and better psychological
adjustment than individuals with a low level of ego-resiliency ( Block & Kremen, 1996 ). It is presumed that when
confronted by stressful circumstances, individuals with a low level of ego-resiliency may act in a stiff and persev-
erative manner or chaotically and diffusely, and in either case, the resulting behavior is likely to be maladaptive
(Block & Kremen, 1996 ). Block’s theoretical conceptualization of ego-resiliency is closely related to conceptions of294 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
‘good psychological functioning’ and appropriate and adaptive behavior across social contexts ( Block & Block,
1980; Klohnen, 1996 ).
Sample
Originally, Block and Kremen (1996) administered the 14-item ER scale to research participants in the Block
and Block (1980) Longitudinal Study of Cognitive and Ego Development ( Block & Block, 1980 ) at age 18
(N51001). Since its origin the ER scale has been employed in a large body of research with diverse samples.
Reliability
Internal Consistency
The Cronbach alpha coefficient for the original sample of over 100 participants was .76 ( Block & Kremen,
1996).
Test/C0Retest
Across the five years between assessments in Block’s original sample (aged 18 to 23 years), the test /C0retest sta-
bilities were .67 and .51 (adjusted for attenuation), for females and males respectively ( Block & Kremen, 1996 ).
Validity
Convergent/Concurrent
Research using the ER89 generally shows moderate correlations with other measures of resiliency. Smith et al.
(2008) reported correlations between the Brief Resilience Scale and the ER-89 of 0.51. The Ego-Resiliency scale
showed moderate positive correlations with the RSCA-A Mastery (.60) and Relatedness (.57) factors ( Saklofske,
Nordstokke, Prince-Embury, Crumpler, & Hinde, 2013 ).
Divergent/Discriminant
A significant negative correlation (-37) was found between the ER89 and the Emotional Reactivity factor of the
RSCA with a sample of university students ( Saklofske et. al., 2013 ).
Construct/Factor Analytic
Factor analyses are not reported for the ER89.
Criterion/Predictive
Fredrickson et al. (2004) reported that trait resilience was associated with a range of psychological benefits,
both in day-to-day life and in coping with crises. Higher scores on the ER89 were found to predict the reporting
of fewer depressive symptoms after the 9/11 terrorist attacks on the World Trade Center in New York
(Fredrickson et al., 2003 ), faster affective and physiological recovery from threat ( Tugade & Fredrickson, 2004;
Waugh, Fredrickson, & Taylor, 2008 ), and more successful adaptation to daily stressors (Ong et al., 2006). The
ER89 scale was employed in a study by Tugade and Fredrickson (2004) , who found that positive emotionality
and appraisal of threat moderate the relationship between resilience and the duration of cardiovascular reactivity
following the induction of a negative emotion.
These studies support the predictive validity of the ER-89 showing the role of trait resilience as a protective
factor against stress. Second, trait resilience /C0which itself can be considered a psychological resource /C0is associ-
ated with a host of other psychological resources, including life satisfaction, optimism, and tranquility. Third,
people with high ER-89 scores were more likely to find positive meaning in the problems they faced following
the September 11 attacks. Fourth, persons with higher ER-89 scores, endured fewer depressive symptoms follow-
ing the 9/11 attacks (Frederickson et al., 2004). Also, those scoring high on the ER-89 experienced more positive
emotions than did their less resilient peers (Fredrickson et al., 2004).
Location
Block, J., & Kremen, A.M. (1996). IQ and ego-resiliency: Conceptual and empirical connections and separate-
ness. Journal of Personality and Social Psychology, 70 , 349/C0361.295 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
Results and Comments
Block and Kremen (1996) noted that the development of the ER89 over the years was empirically driven, but
that conceptual decisions were not fully systematic and changes to the scale have not been recorded properly.
The ER89 is to be distinguished from the Ego-Resiliency Scale developed independently by Klohnen (1996) also
based on the observer rater scale developed by Block, but was different from the ER89 in item content and con-
structs covered. Other scales have been developed building on the ER89 for specific purposes but none have
achieved the prominence of the ER89.
Note: Copyright for the ER89 is owned by the American Psychological Association. Permission to copy should
be obtained from the APA ( www.apa.org ) and the estate of Jack Block.
Resilience Scale (RS)
(Wagnild, 1987).
Variable
The five characteristics of resilience identified by Wagnild were: Purpose, Equanimity, Self-Reliance,
Perseverance, and Existential Aloneness. Wagnild has labeled these five characteristics as the ‘Resilience Core’
and suggests that strengthening the core will enable a person to exhibit a very healthy resilience response to
adversity ( Wagnild, 2009 ). Much like a fitness coach will encourage athletes to strengthen their physical core; the
resilience core can be strengthened and practiced, too. The stronger the core, the healthier is one’s response to
adversity and setbacks.
Description
The 25-item RS is an instrument designed to measure resilience directly ( Wagnild & Young, 1993 ). There are
five items per core characteristic labeled: Purpose, Equanimity, Self-Reliance, Perseverance, and Existential alone-
ness. All items are worded in a positive direction. No items are reverse-worded or otherwise modified prior to
calculating scores. RS scores range from 25 to 175. Responses are made using a 7-point Likert-type scale ranging
from 1 (strongly disagree) to 7 (strongly agree). Total scores are used rather than scores for each of the five sepa-
rate components.
Sample
The samples used in the development of the instrument consisted of 782 seniors between the ages of 53 and
95; 62% were female and 38% males, 79% were retired at the time of testing ( Wagnild & Young, 1993 ).
Reliability
Internal Consistency
The Cronbach alpha coefficient of the RS using the initial sample was 0.91. Additional studies have reported
alpha coefficients ranging from 0.73 to 0.95 ( Wagnild & Young, 1993; Wagnild, 2009 ).
Test/C0Retest
Stability coefficients of .78 for a Swedish sample ( N5422) and .83 for a Thai sample ( N5200) have been
reported ( Choowattanapakorn, Ale ´x, Lundman, Norberg, & Nygren, 2010 ).
Validity
Convergent/Concurrent
Wagnild (2012) has reported that the RS positively related to measures of successful aging including morale,
life satisfaction, optimism, and self-esteem. The RS is also positively related to behaviors associated with healthy
aging such as health promoting behaviors, self-care, and chronic disease management. Correlations showing the
association between the RS and various validity measures appear to range from .25 to .59 (see Wagnild, 2013 ).
Concurrent validity was assessed by correlating the RS score with measures of life satisfaction using the Life
Satisfaction Index A (.37); (Neugarten et al., 1961), morale (.32) using the Philadelphia Geriatric Center Morale
Scale (Lawton, 1975), and self-reported health status ( /C0.30). The RS was significantly correlated to these
measures.296 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
Divergent/Discriminant
Divergent validity was assessed by correlating the RS score with measures of depression ( /C0.41) using the Beck
Depression Inventory. Wagnild (2013) reported that many studies have shown that the RS total score is consis-
tently and inversely related to measures of poor adaptation to adversity and stress including depression, anxiety,
and perceived stress.
Construct/Factor Analytic
Although initially developed to capture three core constructs, a principal components analysis suggested a
two-dimensional solution with 17 items in Component I that suggested self-reliance, independence, determina-
tion, invincibility, mastery, resourcefulness, and perseverance. This component was labeled Personal
Competence. The eight items constituting Component II ‘suggested’ adaptability, balance, flexibility, and a bal-
anced perspective of life. They reflected acceptance and a sense of peace despite adversity. This factor was
labeled Acceptance of Self and Life. The items of the two components (personal competence and acceptance of
self and life) were loaded on more than one factor, thus limiting support for this analysis. Subsequent studies
have not consistently supported two components; instead there is growing support for a one-dimensional scale
(Wagnild, 2012).
Criterion/Predictive
Leppert, Gunzelmann, Schumacher, Strauss, and Bra ¨hler (2005) studied 599 elderly adults in Germany whose
mean age was about 70 years. The mean RS score was 132.6 ( SD522.17). Higher RS scores were predictive of
elders who reported lower subjective body complaints. ES scores was a significant predictor of physical well-
being. Strauss et al. (2007) studied the influence of resilience on fatigue in cancer patients undergoing radiation
therapy. RS scores strongly predicted patients’ fatigue at the beginning of radiation therapy. The authors con-
cluded that resilience is a psychological predictor of quality of life and coping in cancer patients.
Location
Wagnild, G. (2009). The Resilience Scale User’s Guide for the US English version of the Resilience Scale and the 14-
item Resilience Scale (RS-14) . Worden, MT: The Resilience Center.
Wagnild, G., & Young, H.M. (1993). Development and psychometric evaluation of the Resilience Scale. Journal
of Nursing Measurement ,1,1 6 5/C0177.
Results and Comments
The RS was constructed in 1987 and initial psychometric analyses conducted in two studies in 1989 and 1990
(Wagnild & Young, 1993 ). Subsequently, it has been used worldwide and translated into at least 36 languages.
According to the author, there have been more than 5000 requests to use the RS for a variety of purposes includ-
ing research, employment assistance programs, clinical assessment, education, and continuing education confer-
ences and workshops. Although developed initially in association with healthy aging (used with middle and
elderly adults to measure resilience in these populations), it has also been used with other populations including
youth, and young adults. A 14-item short version is also available ( Wagnild, 2009 ).
Notes: Permission to use the Resilience Scale as well as a Resilience Scale User’s Guide may be obtained on the
Resilience Scale websites: www.resiliencescale.com/ (Retrieved January 10, 2014); www.resiliencescale.com/pro-
ducts.html (Retrieved January 6, 2004).
The Resiliency Scale is located at: www.resiliencescale.com/en/rstest/rstest_25_en.html (Retrieved January
6, 2014).
Resilience Scale for Adults (RSA)
(Friborg et al., 2003 ).
Variable
Intrapersonal and interpersonal protective resources may promote resilience in adults, facilitating adaptation,
or regaining and maintaining mental health in the face of stress, adversity, or maltreatment ( Friborg et al., 2003 ).
Resilience is viewed as a multidimensional construct.297 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
Description
The originally validated Norwegian version of the RSA contained 37 items, and covered five dimensions
(Friborg et al., 2003 ). An updated RSA contains 33 items and is based on a 6-dimensional structure ( Friborg,
Barlaug, Martinussen, Rosenvinge, & Hjemdal, 2005 ). A semantic differential response format is currently used
as it effectively reduces acquiescence bias (Friborg et al., 2006). The initial five dimensions of the RSA were
labeled: personal competence, social competence, family coherence, social support, and personal structure (Friborg et al.,
2003). Subsequently, personal competence was broken down into two separate factors, namely perception of self and
planned future and the remaining factors were named social competence, structured style, family cohesion , and social
resources . The content of each factor is: (1) perception of self /C0measures one’s confidence in his/her abilities and
judgment, self-efficacy, and realistic expectations; (2) planned future /C0measures one’s ability to be goal oriented,
have a positive outlook, and plan ahead; (3) social competence /C0measures extraversion, social adeptness/warmth,
cheerful mood, ability to initiate activities and use humor positively, good communication skills, and flexibility
in social matters; (4) structured style /C0measures one’s ability to uphold daily routines, and to plan and organize;
(5)family cohesion /C0measures family conflict/values, cooperation support, loyalty, and stability); and (6) social
resources /C0measures availability of external support from friends and relatives and outside the family, intimacy,
and individual’s ability to provide support ( Friborg et al., 2005; Hjemdal, Friborg, Stiles, Rosenvinge, &
Martinussen, 2006 ). The RSA fits the conceptualization of resilience as characterized by Werner (1989; 1993),
Rutter (1990), and Garmezy (1993), to encompass: (a) personal/dispositional attributes ( personal competence /C0now
perception of self and planned future ,social competence ,personal structure /C0now structured style ); (b) family support
(family coherence /C0now family cohesion ); and (c) external support systems ( social support /C0now social resources )
(Friborg et al., 2003 ).
Thus, the RSA is based on notions of adjustment and coherence and yields 5-6 subscale scores in addition to a
total score. The psychometric properties of the RSA have been explored cross-culturally in countries including
Norway (northernmost Scandinavian culture), Belgium /C0French-speaking version (part of Western European
culture; Hjemdal et al., 2011 ), Turkey ( Basim & Cetin, 2011 ), and in Iran ( Jowkar et al., 2010 ).
Sample
The author’s control sample ( Friborg et al., 2003 ) included 130 women ( M536.0 years, SD57.6) and 97 men
(M537.4 years, SD57.1).
Reliability
Internal Consistency
Cronbach alpha coefficients for the RSA five-factor version were 0.90 for personal competence , 0.83 for social com-
petence , 0.87 for family coherence , 0.83 for social support , and 0.67 for personal structure (Hjemdal et al., 2006 ). The
33-item RSA exhibited alpha coefficients that were greater than .70 for all the subscales, being .74, .73, .83, .80,
.80, and .77 with respect to a 6-factor solution (see Hjemdal et al., 2006 ). Alpha coefficients for the six factors
were .81 for perception of self , .78 for planned future , .75 for social competence , .67 for structured style (personal struc-
ture), .79 for family cohesion (family coherence) , and .77 for social resources (social support).
Test/C0Retest
The four-month stability coefficients for the five dimensions were 0.79, 0.84, 0.77, 0.69 and 0.74, respectively,
based on the control sample ( Friborg et al., 2003 ).
Validity
Convergent/Concurrent
RSA subscales correlate positively (0.29 to 0.75) with the Sense of Coherence Scale (SOC; Antonovsky, 1993,
1998).
Divergent/Discriminant
Negative correlations (ranging from /C00.19 to /C00.61) have been found between the RSA and the Hopkins
Symptom Check List (HSCL; Nettelbladt et al., 1993). The RSA differentiates between patients and healthy con-
trols ( Friborg et al., 2003 ).298 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
Construct/Factor Analytic
Friborg et al. (2003) using a principal components analysis with a varimax rotation ( N5276), extracted five
components labeled: personal competence, social competence, family coherence , and personal structure. They added
locus-of-control items, considered imperative for resilient outcomes, a confirmatory factor analysis ( N5159)
showed that a 6-dimensional structure provided a slightly better fit ( Hjemdal et al., 2006 ). The 6-factor structure
suggested that personal competence might contain two subfactors labeled: perception of self and planned future
(Friborg et al., 2005 ).
Criterion/Predictive
RSA scores were shown to moderate the perception of pain and stress (Friborg et al., 2006). Furthermore, RSA
scores are predictive of a reduced likelihood of developing psychiatric symptoms when individuals are exposed
to stressful life events ( Hjemdal et al., 2006 ).
Location
Friborg, O., Hjemdal, O., Rosenvinge, J. H., & Martinussen, M. (2003). A new rating scale for adult resilience:
what are the central protective resources behind healthy adjustment? International Journal of Methods in Psychiatric
Research, 12 ,6 5/C076.
Friborg, O., Barlaug, D., Martinussen, M., Rosenvinge, J.H., & Hjemdal, O. (2005). Resilience in relation to per-
sonality and intelligence . International Journal of Methods in Psychiatric Research, 14 ,2 9/C040.
Results and Comments
Limitations of the RSA include the inconsistency of use of the 5-dimensional and 6-dimensional versions. Also,
asWindle et al. (2011) pointed out, the reason for the choice of wording of the RSA items, as well as whether the
target population was involved in item selection, remains unclear. Nonetheless, both exploratory and confirma-
tory factor analysis of the RSA item inter-correlations supports the conceptualization of resilience as a multidi-
mensional construct.
Note: Permission to use the RSA scale must be obtained from the author.
Connor /C0Davidson Resilience Scale (CD-RISC)
(Connor & Davidson, 2003 ).
Variable
Resilience is viewed as an individual’s ability to manage and cope successfully with stressful life events
(Connor & Davidson, 2003 ).
Description
The original Connor /C0Davidson Resilience Scale (CD-RISC) is an instrument that consists of 25 self-rated items
(Connor & Davidson, 2003 ). Each item is rated on a 5-point frequency response ranging from 0 (not at all true) to
4 (true nearly all of the time). The total score range is between 0 and 100. Higher scores correspond to greater
resilience. The rating is based on how the subject has felt over the past month. In addition, both a 10-item and
2-item version have been developed for research purposes ( Campbell-Sills & Stein, 2007 ). The 25-item, most com-
monly used version is presented in Connor and Davidson (2003, p. 78, Table 2).
Sample
The original samples in which the CD-RISC was developed/validated included a general non-clinical group
(N5577) and four additional clinical groups; primary care outpatients ( N5139); psychiatric outpatients in pri-
vate practice ( N543); participants in a study of generalized anxiety disorder ( N525); and participants in two
clinical trials of PTSD ( N522, and N522, respectively) ( Connor & Davidson, 2003 ).
Reliability
Internal Consistency
The Cronbach alpha coefficient for the CD-RISC (for the original non-clinical group) was found to be .89
(N5577). The alpha coefficient for the abridged 10-item version was .85 ( N5131) ( Connor & Davidson, 2003 ).299 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
Test/C0Retest
An intra-class coefficient of .87 was reported over a time interval of two weeks or more ( Connor & Davidson,
2003, p. 79).
Validity
Convergent/Concurrent
The CD-RISC correlates positively (.83) with the Kobasa (1979) hardiness measure in psychiatric outpatients
(N530). It also correlates positively (.36) with the Sheehan Social Support Scale ( N5589) ( Connor & Davidson,
2003, pp. 79 /C080).
Divergent/Discriminant
The CD-RISC correlates negatively ( /C0.76) with the Perceived Stress Scale ( N524), (/C0.32) with the
Sheehan Stress Vulnerability Scale ( N5591), and ( /C0.62) with the Sheehan Disability Scale ( N540) ( Connor
& Davidson, 2003 , p. 79). They also reported that the CD-RISC e xhibited differential validity relative to
other measures of stress and hardiness, and reflected different levels of resilience in populations that were
thought to be differentiated by their degree of resilie nce (e.g., general population vs. patients with anxiety
disorders).
Construct/Factor Analytic
Connor and Davidson (2003) identified five factors (labeled: personal competence, trust, tolerance/strengthen-
ing effects of stress, acceptance of change, and secure relationships) that guided initial item selection although
this factor structure has not held up across studies.
Criterion/Predictive
The CD-RISC was developed specifically for assessing treatment effects of pharmacotherapy and it has shown
sensitivity in detecting symptom changes associated with drug treatment. Scores on the CD-RISC have been
shown to be predictive of initial symptom alleviation and subsequent changes in patient well-being ( Connor &
Davidson, 2003 ).
Location
Connor, K.M., Davidson, J.R. (2003). Development of a new resilience scale: The Connor /C0Davidson Resilience
Scale (CD-RISC). Depression & Anxiety, 18, 76 /C082.
Results and Comments
The CD-RISC is an assessment tool developed in a research environment with a specific purpose of assessing
improvements over and above symptom reduction in patients with PTSD associated with drug treatment. Item
selection appears to have had a good theoretical basis. In addition, both a 10-item and 2-item version has been
developed for research purposes, although the 25-item version is the most commonly used. Approved transla-
tions of the CD-RISC currently exist in the following languages: Afrikaans, Bahasa Indonesian (2 and 10 item ver-
sions only), Chinese (both Taiwan and Peoples Republic of China), Dutch, Farsi, Finnish, French (France,
Belgium), German, Hindi, Italian, Japanese, Kiswahili, Korean, Norwegian, Portuguese (Europe, Brazil),
Quechua, Russian, Serbian, Spanish (Europe, Caribbean, South America), Turkish, Urdu. An approved CD-RISC
2 Arabic version also exists.
CD-RISC SAMPLE ITEMS
16. ‘I am not easily discouraged by failure’
25. ‘I take pride in my achievements.’
Notes : Copyright is retained by Kathryn Connor and
Jonathan Davidson (2012). All rights reserved. The items
may not be reproduced, used or transmitted withoutpermission. Permission for use must be obtained from
Jonathan Davidson at: www.connordavidson-resiliences-
cale.com (Retrieved May 31, 2014). Reproduced with
permission.300 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
Brief Resilience Scale (BRS)
(Smith et al., 2008 ).
Variable
Smith et al. (2008) suggested that the original and most basic meaning of resilience is the ability to bounce
back and recover from stress ( Agnes, 2005 ). The authors refer to Carver’s (1998) definition of ‘resilience’ as
returning (i.e., bouncing back or recovery) to the previous level of psychologically healthy functioning.
Description
The BRS includes six questions, with an equal number of positive and negatively worded items to reduce the
effects of response sets. Smith et al. (2008) suggested that a mean BRS score of 3.70 ( SD50.70) provides an index
of typical resilience level. The authors suggested that BRS scores below 3.00 be considered low and that BRS
scores above 4.30 be considered as high in resilience.
Sample
Psychometric characteristics of the BRS were examined in four samples: (1) general college students ( N5259);
(2) healthy adult women ( N551); (3) women with fibromyalgia ( N532); and (4) cardiac patients ( N5228).
There were two healthy samples: college students (Sample 1, N5259) and healthy adult women (Sample 2,
N551). The healthy women had no chronic pain and served as a control group for a study of women with fibro-
myalgia. There were two patient samples: women with fibromyalgia (Sample 3, N532) and cardiac patients
(Sample 4, N5228).
Reliability
Internal Consistency
Cronbach alpha coefficients reported for the BRS in samples 1 to 4 were .84 (undergraduates), .90 (adult
women), .88 (undergraduates), .80 (cardiac rehabilitation patients) /C0(Smith et al., 2008 ).
Test/C0Retest
Test/C0retest reliability using ICCs was .69 for 48 undergraduates after two weeks, .62 after three months and
.61 for fibromyalgia patients after two weeks ( Smith et al., 2008 ).
Validity
Convergent/Concurrent
Concurrent validity evidence includes a correlation of .59 with the CD-RISC assessment of resilience, .51 and
.49 with the ER89 measure of Ego-resiliency. The BRS correlated .45 and .69 with Optimism ( Smith, Epstein,
Ortiz, Christopher, & Tooley, 2013 ).
Divergent/Discriminant
Smith et al. (2008) reported that the BRS correlates negatively with measures of anxiety, depression, negative
affect, and physical symptoms, when other resilience measures and optimism, social support, and Type B person-
ality (high negative affect and high social inhibition) were controlled ( Smith et al., 2013 ). The BRS correlated neg-
atively with anxiety ( /C0.46 to /C0.60), negatively with depression ( /C0.41 to /C0.66), and negatively with perceived
stress ( /C0.60 to/C0.68) ( Smith et al., 2013 ).
Construct/Factor Analytic
No factor analytic findings have been reported as this is a six item scale with a single score.
Criterion/Predictive
Urban firefighters (3.95, N5123), healthy women (3.93, N551), and cardiac patients (3.87, N5228) scored
significantly higher in their mean BRS score than did college students (3.56, N5259) and first-generation stu-
dents (3.54, N5151) who scored significantly higher than did women with fibromyalgia (3.18, N532) ( Smith
et al., 2013 ).301 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
Location
Smith, B.W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P., & Bernard, J. (2008).
The Brief Resilience Scale: Assessing the ability to bounce back. International Journal of Behavioral Medicine, 15 ,
194/C0200.
Results and Comments
The BRS shows the expected correlations with other resiliency scales and discriminates between clinical groups
in the predicted direction. However, limitations of the BRS are related to the very specificity of the scale as
related to the individual’s ability to ‘bounce back’ after experiencing adversity. A second important limitation is
the lack of evidence that the BRS, as a self-report measure of resilience, predicts actual ‘bouncing back’ or recov-
ery as evidenced by independent behavioral and physiological measures ( Smith et al., 2013 ).
BRS SAMPLE ITEMS
Instructions: Please indicate the extent to which you
agree with each of the following statements by using the
following scale: 1 5strongly disagree; 2 5disagree;
35neutral; 4 5agree; 5 5strongly agree.
1.I tend to bounce back quickly after hard times.
2.I have a hard time making it through stressful
events (R).
3.It does not take me long to recover from a stressful
event.
4.It is hard for me to snap back when something bad
happens (R).5.I usually come through difficult times with little
trouble.
6.I tend to take a long time to get over set-backs in my
life (R).
Notes :R/C0Reverse worded item. Scores are the average
of responses on all items after reverse coding items 2, 4,
and 6.
Available from the first author ( [email protected] ).
Reproduced with permission.
Resiliency Scales for Children and Adolescents (RSCA)
(Prince-Embury, 2006, 2007 ).
Variable
Resiliency is viewed by Prince-Embury, 2006, 2007 ) as multidimensional (Sense of Mastery, Sense of
Relatedness and Emotional Reactivity) and is based in ordinary developmental processes as expressed by
Masters (2001). Further, it is assumed that core developmental dimensions of personal resiliency may be ‘protec-
tive’ of ‘risk’ and are best assessed in relation to each other for each individual.
Description
The RSCA, is a 64 item self-report inventory for children and adolescents aged 9 /C018 years, ( Prince-Embury,
2007). The RSCA consists of three global scales designed to reflect the three designated underlying systems of
resiliency listed above. Standardized T-scores on these three global scales comprise a Personal Resilience Profile,
which graphically displays the child’s relative strengths and vulnerabilities. Two composite scores, the Resource
Index and the Vulnerability Index, are summary scores that quantify the child’s relative strength and vulnerabil-
ity for use in preventive screening. The three global scales are comprised of 10 subscales that can be used to
understand the child’s specific strengths and vulnerabilities in more depth. Items were selected to cover theoreti-
cal content areas, were written at a Grade 3 reading level and were modified based on the findings of pilot stud-
ies and statistical analysis. Response options for all items are ordered on a 5-point Likert-type scale. The three
subscales of the RSCA are described below.
The Sense of Mastery S cale (20 items) consists of three conceptually related content areas: optimism about life
and one’s own competence; self-efficacy associated with developing problem-solving attitudes and strategies; and
adaptability , being personally receptive to criticism, and learning from one’s mistakes. Higher scores on this global
scale or subscales suggest higher personal resiliency in this developmental system.302 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
The Sense of Relatedness scale (24 items) consists of four subscales which reflect comfort with others, trust in
others, perceived access to support by others when in need, and tolerance of differences with others. Higher scores
on this global scale or subscales suggest higher personal resiliency in this developmental system.
The Emotional Reactivity scale, a 20-item scale, differs from the Sense of Mastery and Sense of Relatedness scales,
in that lower scores on the Emotional Reactivity scale are indicative of low reactivity and less risk. On the other
hand, high scores suggest higher reactivity, which is associated with more risk and less personal resiliency. This
scale consists of three related content areas: the Sensitivity subscale assesses the child’s threshold for emotional reac-
tion and the intensity of the reaction, the Recovery subscale describes the length of time required for recovering from
emotional upset, and the Impairment subscale describes the child’s experience of disrupted functioning while upset.
The RSCA Summary Index scores combine information into two scores, which may be unfolded to provide
more detailed information at the global and subscale levels; the Resource and Vulnerability Index scores. The
Index scores were developed based on empirical analyses of RSCA scale score profiles, factor analytic studies
and validity studies ( Prince-Embury, 2006, 2007; Prince-Embury & Courville, 2008a,b ). The Resource Index com-
bines the Sense of Mastery and Sense of Relatedness Scale scores estimating protective factors experienced by the
child. A high Resource Index score indicates that the child experiences protective personal resources. The
Vulnerability Index is designed to estimate the discrepancy between an individual’s personal risk and perceived
available personal resources. Personal vulnerability would be indicated by a high Vulnerability Index score indicat-
ing that students’ personal resources were significantly below their level of emotional reactivity.
Sample
All scores are standardized on age and gender based normative samples ( N5641) that are stratified by race/
ethnicity and parent education level to match the US Census for 2003 ( Prince-Embury, 2007, 2008 ).
Child
A total of 450 children, aged 9 years to 14 years 11 months, were selected from the larger pool of the child
community sample. Cases were eliminated when there was an indication that the child was currently receiving
services for a psychiatric disorder. Cases were not excluded for previous psychiatric services, as this did not
meet partial criteria for inclusion in the clinical sample. A stratified sampling plan ensured that the standardiza-
tion samples included representative proportions of children according to each selected demographic variable.
An analysis of data gathered by the U.S. Bureau of the Census (U.S. Bureau of the Census, 2003) provided the
basis for stratification by race/ethnicity and education level within each sex and age group.
Adolescent
A total of 200 children, aged 15 /C018 years, were selected from the larger pool of the adolescent community
sample. Cases were eliminated when there was an indication that the teenager was currently receiving services
for a psychiatric disorder. Cases were not excluded for previous psychiatric service, as this did not meet partial
criteria for inclusion in the clinical sample. A stratified sampling plan ensured that the standardization samples
included representative proportions of children according to each selected demographic variable. An analysis of
data gathered by the U.S. Bureau of the Census (U.S. Bureau of the Census, 2002) provided the basis for stratifica-
tion by race/ethnicity and education level within each sex and age group.
Reliability
Internal Consistency
Sense of Mastery Scale Cronbach alpha coefficients for the Sense of Mastery Scale were .85 for youth aged 9 to
11 years ( N5226), .89 for youth aged 12 to 14 years ( N5224) and .95 for youth aged 15 to 18 years ( N5200).
Sense of Relatedness Scale Cronbach alpha coefficients for the Sense of Relatedness scale were .89 for children
aged 9 to 11 years ( N5226), .91 for children aged 12 to 14 years ( N5224) and .95 for youth aged 15 to 18 years
(N5200).
Emotional Reactivity Scale Cronbach alpha coefficients for the Emotional Reactivity scale were .90 for youth
aged 9 to 11 years ( N5226), .91 for youth aged 12 to 14 years ( N5224) and .94 for youth aged 15 /C018 years
(N5200).303 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
Resource Index Cronbach alpha coefficients for the Resource Index were .93 for youth aged 9 to 11 years
(N5226), .94 for youth aged 12 to 14 years ( N5224), and .97 for youth aged 15 to 18 years ( N5200).
Vulnerability Index Cronbach alpha coefficients for the Vulnerability Index score were .93 for youth aged 9 to 11
years ( N5226). .94 for youth aged 12 to 14 years ( N5224), and .97 for youth aged 15 to 18 years ( N5200).
Cross-cultural studies indicate high levels of item homogeneity for the three global RSCA Scale Scores (see
Table 11.1 below). The RSCA has been employed previously with youth in Canada (Saklofske & Nordstokke,
2011), South African ( VanWyk, 2011 ), Kenya (Tignor & Prince-Embury, 2013), China ( Cui, Teng, Li, & Oei, 2010 ),
Brazil ( Jordani, 2008 ), and Lebanon (Ayyash-Abdo, & Sanchez-Ruiz, 2011).
Test/C0Retest
Sense of Mastery Scale Test/C0retest reliability coefficients for a two week interval, were .79 for youth aged 9 to
14 years ( N549) and .86 for youth aged 15 to 18 years ( N565).
Sense of Relatedness Scale Test/C0retest reliability coefficients for a two week interval were .84 for youth aged
9 to 14 years ( N549) and .86 for youth aged 15 to 18 years ( N565).
Emotional Reactivity Scale The test /C0retest reliability coefficient was .88 for youth aged 9 to 14 years ( N549)
and for youth aged 15 to 18 years ( N565) over a two week interval.
Resource Index The test /C0retest reliability coefficient was .90 for youth aged 9 to 14 years ( N549) and .85 for
youth aged 15 to 18 years ( N565) over a two week interval.
Vulnerability Index
Test/C0retest reliability coefficients for a two week period were .83 for youth aged 9 to 14 years ( N549) and .93
for youth aged 15 to 18 years ( N565).
Validity
Convergent/Concurrent
RSCA protective factors are positively correlated with measures of positive self-esteem. Significant positive
correlations were found for both child and adolescent samples, between a positive BYI Self-Concept score and
the RSCA Resource Index score (.78, .79), the Sense of Mastery Scale score (.74, .80), and the Sense of Relatedness
Scale score (.70, .70), suggesting convergent validity for these scores as reflective of positive self- concept as a pro-
tective factor ( Prince-Embury, 2007, 2013a, 2013b ). Also, positive correlations were found between the Emotional
Reactivity Scale score and all Beck Youth Inventory /C0Second Edition (BYI-II; Beck et al., 2004) scores of negative
emotion in non-clinical samples of children and adolescents; (.43, .65) with Anxiety, (.70, .67) with Disruptive
Behavior, (.44, .74) with Depression and (.59, .76) with Anger. The Vulnerability Index score was also associated
with the BYI-II negative emotion scores; (.36, .65) with Anxiety, (.71, .66) with Disruptive Behavior, (.51, .75) with
Depression and (.59, .77) with Anger (see Prince-Embury, 2013a, 2013b).
Divergent/Discriminant
Discriminant Function analysis using gender, parent education level, Resilience Scale Global and Index scores
and BYI /C0II Negative Affect and Behavior scores to predict membership in the clinical versus non-clinical sample
indicated that the RSCA Vulnerability Index was the best single discriminator. These findings suggest that highTABLE 11.1 Alpha Coefficients for the RSCA Global Scales across Six Countries
Scale Canada 2009
(543)Canada 2010
(390)China
(726)Brazil
(1226)Lebanon
(599)Nairobi, Kenya
(83)South Africa
(487)
Mastery .90 .92 .95 .83 .78 .70 .74
Relatedness .92 .93 .94 .90 .86 .74 .83
Emotional
Reactivity.90 .91 .89 .87 .87 .80 .76304 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
Emotional Reactivity in combination with low personal resources is associated with the development of psycho-
logical symptoms in youth (see Prince-Embury, 2007, 2008 , 2009, 2012; Prince-Embury & Courville, 2008a,b for
additional information).
Construct/Factor Analytic
A three factor structure for the RSCA has been confirmed for the RSCA on the standardization sample, with
measurement invariance across gender and across age band ( Prince-Embury, 2007; Prince-Embury & Courville,
2008a,b ).
Criterion/Predictive
Criterion validity for RSCA global scales, subscales and index scores was provided by comparisons of child
and adolescent clinical samples and demographically matched control groups for Depressive Disorder, Anxiety
Disorder, Conduct Disorder, Bipolar Disorder and ADHD. Effect sizes were generally large. For details see RSCA
Technical Manual ( Prince-Embury, 2007 , pp 110 /C0119).
Location
The RSCA is copyrighted and available commercially from Pearson Assessments. Example items from the
Resiliency Scales for Children & Adolescents /C0A Profile of Personal Strengths (RSCA).
Results and Comments
The RSCA assesses core constructs found to underlie personal resiliency in children and adolescents.
The Global and subscale scores may also be used in men tal health treatment for intake assessment, treat-
ment planning and outcome assessment. The Resourc e and Vulnerability Index scores may be used in
universal screening to identify relat ive strength and vulnerability in youth prior to the development of nega-
tive symptoms for the purpose of preventive interv ention. The RSCA is unique as a measure of personal
resiliency in that it considers the resources and v ulnerability experienced by the child as well as the
discrepancy between these factors . Sample items are listed below for each of three subscales within three
global scales.
RSCA SAMPLE ITEMS
Sense of Mastery
Optimism: ‘No matter what happens, things will be all right.’
Self-efficacy: ‘If I have a problem, I can solve it.’
Adaptability: ‘I can learn from my mistakes.’
Sense of Relatedness
Trust: ‘I can trust others.’
Support: ‘There are people who love and care about me.’
Comfort: ‘I feel calm with people.’
Emotional Reactivity
Sensitivity: ‘It is easy for me to get upset.’
Recovery: ‘When I get upset, I stay upset for several hours.’
Impairment: ‘When I am upset, I make mistakes.’
Notes: Items are rated on a 5-point Likert-type scale ranging from: 0 5‘Never’; 1 5‘Rarely’; 2 5‘Sometimes’;
35‘Often, and 4 5‘Almost Always’.
Copyright r2006 NCS Pearson, Inc. Reproduced with permission. All rights reserved.
A technical manual describing administration, interpretation and application of the scales is available from
Pearson Assessments: www.pearson.com (Retrieved January 6, 2014). Reproduced with permission.305 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
Child and Youth Resilience Measure (CYRM-28)
(Unger & Liebenberg, 2009 , 2011).
Variable
Resilience as reported by the individual child is regarded as covering three core areas: Individual attributes,
relationships with primary care-givers, and the experience of contextual factors that facilitate a sense of belonging
(Unger & Liebenberg, 2009, 2011 ).
Description
The CYRM-28 is a 28 item self-report measure of resilience developed to be a culturally and contextually rele-
vant measure of child and youth resilience across four domains (individual, relational, community and culture).
All items are rated on a 5-point response scale with higher scores indicating increased presence of resilience pro-
cesses. The CYRM-28 has three sub-scales: Individual, relationships with primary care-givers, and contextual fac-
tors that facilitate a sense of belonging. Within each of these sub-scales there are additional clusters of questions
that provide additional insight into these three dimensions. The score for each of the clusters and/or sub-scales
is the sum of responses to the relevant questions. The higher the score, the more these resilience components are
said to be present in the lives of participating youth.
The development of the CYRM is detailed in a number of previous publications by the authors ( Ungar &
Liebenberg, 2005, 2009, 2011; Ungar et al., 2008, Lindenberg, Ungar, & Van de Vijver, 2012 ). The original CYRM
was the result of a 14-site, 11 country pilot study of resilience in which advisory groups from each community
contributed to the development of the questions.
The development of the CYRM and derivative CYRM-28 followed a multi-method model. The original con-
struction was across 14 international research sites, and more recent validation includes studies with Aboriginal
and non-Aboriginal youth in Canada and New Zealand, youth in countries like South Africa, Colombia and
China, as well as youth living in poverty or marginalized by family breakdown, exposure to violence. In order
for young people to have been selected into the validation studies, they had to be judged by their communities to
have been exposed to heightened levels of adversity that distinguished them from other children. Items emerged
from focus group interviews with youth and adults at each site.
Face-to-face meetings of all team members in 2003 helped to identify the most useful 58 items to be piloted
with youth known to be facing significant levels of adversity as defined by members of local advisory commit-
tees. This method helped the research team to identify common aspects of resilience that demonstrated construct
validity across all 14 sites.
Sample
A minimum of 60 youth participated from each of 14 international sites; the total sample included 1451 youth
(aged 13 to 23 years). The measure was translated where necessary before administration (see Ungar &
Liebenberg, 2011).
Reliability
Internal Consistency
Cronbach alpha coefficients (see Table 11.2 ) ranged from .77 to .83 in all cases (Ungar & Liebenberg, 2011).
TABLE 11.2 Cronbach Alpha Coefficients of CYRM-28 Subscales
Individual (11 items) Relational (7 items) Contextual (10 items)
Canada ( N5410) .79 .83 .82
New Zealand ( N5581) .77 .77 .75
South Africa ( N5192) .81 .81 .81306 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
Test/C0Retest
A sample of 53 youths who completed the measure approximately 3 weeks apart provided test /C0retest data.
Interclass Correlation Coefficients (absolute agreement) ranged from .58 to .77. Paired sample t-tests showed nosignificant differences between Times 1 and 2 (Ungar & Lindenberg, 2013).
Validity
Convergent/Concurrent
Convergent validity evidence for the CYRM-28 is currently unavailable.
Divergent/Discriminant
Evidence of divergent/discriminant validity is currently available.
Construct/Factor Analytic
Initial exploratory factor analyses (unrotated) were conducted across four samples to identify initial compo-
nents. A second wave of international research has allowed us to continue validation of the CYRM. Canadian
data on 497 concurrent users of multiple services (aged 12 to 21 years) was subjected to an EFA with obliquerotation (direct oblimin), identifying three subscales of the CYRM: individual, relational, and contextual. Itemsrelated to individual components include personal skills, peer support and social skills; caregiver componentsinclude psychological caregiving and physical caregiving; and contextual components include educational, cul-tural and spiritual components. This structure was then confirmed with an additional sample of 410 multipleservice using youth. The data set was split into visible minority and visible majority youth, accounting for cul-tural variation in the analysis. Multi-group confirmatory factor analysis showed high invariance and model sta-
bility across the two groups ( χ
2
(53, N5410)598.00, p,.001; TLI 5.96; CFI 5.98; RMSEA 5.05) (Ungar &
Liebenberg, 2013).
Criterion/Predictive
No criterion/predictive validity evidence is currently available.
Location
Ungar, M., & Liebenberg, L. (2009). Cross-cultural consultation leading to the development of a valid measure
of youth resilience: The International Resilience Project. Studia Psychologica, 51 , 259/C0268.
Ungar, M., & Liebenberg, L. (2011). Assessing resilience across cultures using mixed-methods: Construction of
the child and youth resilience measure-28. Journal of Mixed-Methods Research, 5 ,1 2 6/C0149.
Results and Comments
In developing the CYRM-28, the authors broke with procedures typically used for instrument design
where validity is sought through validity coefficients (testing a new measure against existing measures) or
group comparisons (comparing the results of youth who are doing well with those youth who are not doingwell). The authors chose to avoid using existing meas ures that might reintroduce biased notions of what
resilience should look like among those at risk. Conven tional practices for scale development would identify
this as a potentially serious shortcoming. However, t he authors report that by engaging with their commu-
nity partners through focus groups and mixed methods d ata collection they compensated for this limitation.
Similar concerns exist regarding measurement of risk and the degree to which their samples were in truth,
at-risk youth. No standardized test of risk was used to se lect youth across all 14 research sites. That said, the
authors report more than 100 researchers are now using the CYRM-28 in studies ranging from investigations
with children with physical disabilities in India, de-institutionalized children in Ethiopia, Aboriginal childrenat risk of suicide in Canada, and Californian youth who are disengaged from their communities. Validation
of the instrument is ongoing and its use to-date ha s been primarily for research as opposed to clinical
application.307 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
CYRM-28 SAMPLE ITEMS
Individual
Individual: Individual personal skills
13. I am able to solve problems without harming
myself or others (for example by using drugs and/or
being violent)
Individual: Individual peer support
18. My friends stand by me during difficult times
Individual: Individual social skills
25. I have opportunities to develop skills that will be
useful later in life (like job skills and skills to care for
others)
Relationship with Primary Caregiver
Caregiver: Physical Care giving
7. If I am hungry, there is enough to eat
Caregiver: Psychological Care giving
17. My caregiver(s) stand(s) by me during difficult timesContext
Context: Spiritual
9. Spiritual beliefs are a source of strength for me
Context: Education
16. I feel I belong at my school
Context: Cultural
19. I am treated fairly in my community
Notes : Items are rated on a 5-point Likert-type scale
ranging from: 1 5‘Does not describe me at all’ to
55‘Describes me a lot’.
The CYRM-28 Manual is available from the authors
who recommend creating a local community focus
group to assure that the assessment is meaningful to
that community.
The CYRM-28 is available from the website: www.
resilienceresearch.org (Retrieved May 31, 2014).
Reproduced with permission.
Social/C0emotional Assets and Resiliency Scales (SEARS)
(Merrell, 2011 ).
Variable
Strength-based social /C0emotional assessments for children and adolescents have been developed as a set of
cross-informant measures in order to incorporate perspectives of the student, teacher, and parent(s) ( Merrell,
2008). As part of the Oregon Resiliency project, a goal of this group of researchers was to move assessment
toward a more strength-based approach, consistent with best practice in school psychology, allowing for smooth
transition from assessment to intervention practices (e.g., Tom et al., 2009 ).
Description
This multi-informant system is comprised of four self-report scales, including the teacher (SEARS-T), parent
(SEARS-P), child (SEARS-C), and adolescent (SEARS-A) versions, of which the SEARS-T has 41-items, the
SEARS-P has 39 items, and both youth versions have 35 items each. Of the youth rating scales, the SEARS-C is
used for grades 3 through 6 and the SEARS-A for grades 7 through 12 ( Merrell, 2011 ). All items are scaled posi-
tively so that a higher score reflects a higher number of assets/greater resilience. Each form uses a 4-point rating
scale. Whereas the SEARS-C has a unitary factor structure, the SEARS-T and SEARS-A both additionally provide
four subscale scores, and the SEARS-P provides three subscale scores, which represent their underlying factor
structures (discussed subsequently). Each version of the SEARS includes items related to the following character-
istics of resilience: Responsibility, Self-Regulation, Social Competence, and Empathy. Though the items for each
are similar (see examples below), they differ according to developmental level, setting for rating, and context of
the rating. The SEARS-T and SEARS-A yield scores that represent this underlying factor structure, whereas the
SEARS-P provides three scores with Responsibility and Self-Regulation collapsed into one factor ( Merrell, 2011 ;
2012).
Sample
The initial sample comprised 903 children in Grades 3 to 6 (49% female, 51% male). The sample for the
SEARS-A consisted of 714 participants in Grades 7 to 12 (equal number of males and females). The SEARS-T308 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
initial sample comprised 418 teachers who rated 1673 K-12 students. The SEARS-P was administered to a sample
of 2,356 parents or guardians of children and adolescents aged 5 to 18 years. Four subsamples were incorporated
into the normative sample as follows: SEARS-C: 1224 children in Grades 3 to 6 (aged 8 to 12 years); SEARS-A:
1,727 adolescents in Grades 7 to 12 (aged 13 to 18 years); SEARS-T: 1400 teachers of children in Grades K to 12
(aged 5 to 18 years); and SEARS-P: 1204 parents of children in Grades K to 12 (aged 5 to 18 years).
SEARS-C and SEARS-A
Reliability
Internal Consistency
For the SEARS-C and SEARS-A, Cronbach alpha coefficients of .95 and .96 were reported ( Cohn, Merrell,
Felver-Gant, Tom, & Endrulat, 2009 ). In a separate study across four administrations of the SEARS-C and SEARS-
A(Romer & Merrell, 2012 ), alpha coefficients ranged from .91 to .94, and from .92 to .95, respectively. Short forms
of the SEARS- C and SEARS-A exhibited alpha coefficients of .85 and .82, respectively.
Test/C0Retest
Stability coefficients for the SEARS-C and SEARS-A over a 2-week interval were .81 and .89, respectively, over
a 4-week interval .79 and .81, respectively, and over a 6-week interval .73 and .78, respectively. The short forms
(SEARS-C-SF and SEARS-A-SF) exhibited stability coefficients over a two-week interval of .74 and .84, respec-
tively, over a 4-week interval .81 and .81, respectively, and over a 6-week interval .67 and .80, respectively.
SEARS-T
Reliability
Internal Consistency
The SEARS-T exhibited Cronbach alpha coefficients of .95, .94, .95, and .92 for Responsibility, Social
Competence, Self-Regulation, Empathy, respectively. All 41 items (total score) exhibited an alpha coefficient of
.98 (Merrell, Felver-Gant, & Tom, 2011 ). In a separate study, an alpha coefficient of .96 was reported for the initial
administration and .97 for the second administration ( Romer & Merrell, 2012 ). An alpha coefficient of .93 was
reported for the SEARS-T-SF ( Merrell, 2011 ).
Test/C0Retest
The SEARS-T total score stability coefficient averaged across varying intervals (initial, Weeks 2, 4, and 6) was
found to be .94, while the subscale score stability coefficients ranged from .84 to .92 ( Romer & Merrell, 2012 ). The
stability coefficient over a two-week interval was found to be .90 for the SEARS-T-SF ( Merrell, 2011 ).
SEARS-P
Reliability
Internal Consistency
For the total scale (39 items), Merrell et al. (2011) reported a Cronbach alpha coefficient of .96, and similar
alpha coefficients were reported for the three factors (labeled: Self-Regulation/Responsibility, α5.95; Social
Competence, α5.89; Empathy, α5.87). An alpha coefficient of .89 was reported for the SEARS-P-SF ( Merrell,
2011).
Inter-Rater
Inter-rater reliability measured using a sample of 319 pairs of mothers and fathers (who rated the same child),
yielded reliability coefficients of .72 for total score, .71 for the Self-Regulation/Responsibility, .68 for Social
Competence factor, and .65 for Empathy.
Test/C0Retest
The stability coefficient for the SEARS-P and for the SEARS-P-SF over a two-week test /C0retest interval was
found to be .93 and .92, respectively ( Merrell, 2011 ).309 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
SEARS-C
Validity
Convergent/Concurrent
The SEARS-C total score correlated positively (.77) with the Social Skills Rating Scale ( Gresham & Elliot, 1990 ;
N5137 Grade 3-6 students) and (.80) with the Behavior and Emotional Rating Scale ( Epstein & Sharma, 1998 )
scale, respectively. The correlations between the four subscales of the SEARS-C and the SSRS ranged from .63 to
.72, and between the SEARS-C and the BERS from .62 to .78, respectively.
Divergent/Discriminant
The SEARS-C total scores correlated negatively ( /C0.53) with the Internalizing Symptom Scale for Children
(Merrell & Walters, 1995), based on data for 153 children in Grades 3 /C06.
Construct/Factor Analytic
Exploratory factor analysis (PAF) with oblique rotation did not produce an interpretable factor structure. Using
clinical judgment and item elimination, 35 items from the original 52 were retained but no meaningful interpretation
could be made except that a single factor emerged as the best description of this scale ( Merrell, 2011 ).
Criterion/Predictive
Merrell (2011) reported use of the SEARS-C and SEARS-A as intervention outcome predictor in studies con-
ducted during their development. For example, Harlacher and Merrell (2010) demonstrated that the SEARS-C
can detect treatment gains when assessing the effectiveness of the Strong Kids Social and Emotional Learning
(SEL) program for elementary aged students ( Merrell, Carrizales, Feuerborn, Gueldner, & Tran, 2007 ).
SEARS-A
Validity
Convergent/Concurrent
Two studies correlating the SEARS-A with the Social Skills Rating System ( Gresham & Elliot, 1990 ) and the
Student Life Satisfaction Scale ( Huebner, 1991 ) with samples of high school students resulted in positive correla-
tions of .49 ( N5259) and .48 ( N5253) respectively.
Divergent/Discriminant
No evidence of divergent/discriminant validity is currently available.
Construct/Factor Analytic
Exploratory principal axis factor analysis with oblique rotation was carried out using a sample of 2356 adoles-
cents. A Scree test ( Cattell, 1978; Cattell & Vogelmann, 1977 ) suggested four factors, resulting in a 35 item scale.
Confirmatory factor analysis supported the four factors (labeled: Self-Regulation, Social Competence, Empathy
and Responsibility) with CFI 5.87, RMSEA 5.05 and SRM R5.06.
Criterion/Predictive
The SEARS-A was found to be predictive of adolescent self-perceptions of social /C0emotional assets after partic-
ipation in a social emotional learning program (for at-risk high school students) (Merrell et al., 2010).
SEARS-T
Validity
Convergent/Concurrent
The SEARS-T correlates positively with two established strength-based teacher /C0informant child behavior rat-
ing scales, namely (.82) with the social skills scale of the parent rating form of the Social Skills Rating Scale
(SSRS; Gresham & Elliot, 1990 ), and (.90) with the peer relations subscale of the School Social Behavior Scales
(SSBS-2; Merrell, 2002; Merrell et al., 2011 ).310 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
Divergent/Discriminant
Significant classification status differences in SEARS-T scores on the basis of gender (girls significantly higher
than boys) and special education (without classification scored more highly) supports the divergent validity of
the SEARS-T ( Merrell et al., 2011 ).
Construct/Factor Analytic
Both exploratory (PAF) analysis with direct oblimin rotation and confirmatory factor analysis revealed a robust
four-factor structure (using a split sample of N5836 and 837), where Factor 1, Responsibility , comprised 10 items,
Factor 2, Social Competence , comprised 12 items, Factor 3, Self-Regulation , comprised 13 items, and Factor 4,
Empathy , comprised six items ( Merrell et al., 2011 ).
Criterion/Predictive
The SEARS-T scores are predictive of academic performance with lower perceived levels of academic perfor-
mance directly associated with lower mean SEARS-T scores and higher academic performance associated with
higher SEARS-T scores. Also, when comparing student scores on the SEARS-T between students receiving special
education services because of disabilities versus those not receiving these services, teachers rated students with-
out these designated disabilities/who were not receiving services significantly higher than their special education
counterparts ( Merrell, 2011 ).
SEARS-P
Validity
Convergent/Concurrent
The SEARS-P correlates positively with two established parent-informant strength-based child behavior rating
scales, the SSRS ( Gresham & Elliot, 1990 ), and the social competence scale of the Home and Community Social
Behavior Scales (HCSBS; Merrell & Caldarella, 2002). For a summary of convergent validity studies on the
SEARS-P, see Merrell et al. (2011) .
Divergent/Discriminant
Significant classification status differences have been observed in SEARS-P scores on the basis of gender (girls
significantly higher than boys) and special education (without classification scored higher), supporting the diver-
gent validity of the SEARS-P, as also found for SEARS-T scores ( Merrell et al., 2011 ).
Construct/Factor Analytic
Principal axis factor analyses with direct oblimin rotation were carried out using a split sample procedure (on over
2000 participants) and revealed a robust and replicable factor structure that contained three factors (vs. four for the
SEARS-A and T). Within this factor structure, Factor 1, Self-Regulation/Responsibility , comprised 22 items, Factor 2,
Social Competence , comprised 10 items, and Factor 3, Empathy , comprised 7 items ( Merrell, Felver-Gant et al., 2011 ).
Criterion/Predictive
Similar to the SEARS-T (same study as above on special education), when comparing students receiving spe-
cial education services because of educational disabilities versus those who were not receiving these services, par-
ents gave significantly lower scores on the SEARS-P to those students receiving these services/designated with
disabilities than their counterparts ( Merrell, 2011 ).
Location
Merrell, K.W. (2011). Social and Emotional Assets and Resilience Scales (SEARS) . Lutz, FL: Psychological
Assessment Resources.
Merrell, K.W., Cohn, B., & Tom, K. M. (2011). Development and validation of a teacher report measure for
assessing social /C0emotional strengths of children and adolescents. School Psychology Review , 40, 226 /C0241.
Comments and Results
The multi-informant SEARS scales appear to be a useful means of obtaining different perspective of child and
adolescent behavior from the viewpoint of strength rather than relying only on information about deficit.311 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
Limitations of these scales include the different factor structure of corresponding scales, restricting certain spe-
cific comparison between scales. Further, although it appears that individuals Grades 6 to 8, in addition to ado-
lescents and teachers, are able to reliably report perception of their social /C0emotional competence (over 2 /C06 week
intervals), significant differences were found between initial and later reports of the SEARS-C with younger chil-
dren, indicating that caution should be taken when interpreting changes in self-reports of children below Grade 6
(seeRomer & Merrell, 2012 ).
SEARS SAMPLE ITEMS
Examples of the SEARS-C, A, T and P items are shown as follows:
SEARS-C
I am good at understanding what other people think (Empathy)
I make friends easily (Social Competence)
I know how to calm down when I am upset (Self-Regulation)
SEARS-A
I am good at understanding the point of view of other people (Empathy)
I make friends easily (Social Competence)
I know how to calm down when I am stressed or upset (Self-Regulation)
SEARS-T
Is good at understanding the point of view of other people (Empathy)
Makes friends easily (Social Competence)
Knows how to calm down when stressed or upset (Self-Regulation)
Examples of the SEARS-P items include the following (see Merrell et al., 2011 )
SEARS-P
Understands how other people feel (Empathy)
Makes friends easily (Social Competence)
Can calm down when upset (Self-Regulation/Responsibility)
Notes : Items are rated on a 4-point scale ranging from: 0 5‘Never’ to 4 5‘Almost always’.
Copyright 2011 by PAR, Inc., 16204 North Florida Avenue, Lutz, Florida, 33549, from the Social Emotional Assets
and Resilience Scales (SEARS) by Kenneth W. Merrell, PhD.
The SEARS scales are commercially distributed by PAR Inc. and are available at: www4.parinc.com/Products/
Product.aspx?ProductID 5SEARS (Retrieved January 10, 2014). Reproduced with permission.
Devereux Student Strengths Assessment (DESSA)
(LeBuffe et al., 2009).
Variable
Social/C0emotional capacities in children are measured wi thin schools, after-school programs, and other
behavioral healthcare provider settings, from a strengt hs-based perspective. Competencies are measured that
act as protective factors in children from kindergarten t hrough Grade 8. Protective factors are viewed as resid-
ing on a continuum on which one may range from incomp etent to proficient. Strengths and weaknesses in
social-learning and behavior are captured based on the c hild’s ability to demonstrate interactions with others
who display appropriate emotion management given t he context and developmental stage of the child
(LeBuffe et al., 2009).312 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
Description
The DESSA comprises 72 items and covers eight dimensions of within-child protective factors labeled: Self-
awareness, Social-Awareness, Self-Management, Goal-Directed Behavior, Relationship Skills, Personal
Responsibility, Decision Making, Optimistic Thinking (Lebuffe et al., 2009). All informants (child, parents, and
teachers) indicate how often the student has engaged in a given behavior over the past four weeks on a 5-point
Likert-type scale. Scores are standardized and norm-referenced and can be categorized (based on T-score /C0higher
scores depicting higher competencies) into those that are strengths, typical, or needs for instruction and thus can
guide strategies to promote these competencies in schools, classrooms, and individuals. The eight dimensions of
the DESSA (Lebuffe et al., 2009) together yield a social emotional composite score.
The DESSA has been used with a variety of prevention and intervention initiatives ( Woodland et al., 2011 ),
emphasizing the importance of social /C0emotional learning in the determination of school-readiness and predic-
tion of academic success ( Denham & Brown, 2010 ), as well as examining social /C0emotional factors related to
resilience and their relation to problem behaviors ( Naglieri, LeBuffe, & Shapiro, 2010 ).
Sample
The standardization sample consisted of 2500 children from the U.S. (representative according to gender, race,
ethnicity, residence, and poverty status) ( Naglieri et al., 2010 ).
Reliability
Internal Consistency
Cronbach alpha coefficients for the DESSA composite strengths score were .98 for parent raters and .99 for
teacher raters. Alpha coefficients for the subscales were as follows (for parent and teacher raters respectively) .82
and .89 for Self-Awareness , .84 and .91 for Social Awareness , .86 and .92 for Self-Management , .88 and .93 for Goal-
Directed Behavior , .89 and .94 for Relationship Skills , .86 and .92 for Personal Responsibility , .85 and .92 for Decision
Making , and .82 and .89 for Optimistic Thinking (Lebuffe et al., 2009).
Test/C0Retest
The DESSA test /C0retest reliability coefficients over the short term ranged from .79 to .90 for parents and from
.86 to .94 for teachers (Lebuffe et al., 2009).
Validity
Convergent/Concurrent
Nickerson and Fishman (2009) using a sample of 227 participants (94 teachers and 133 parents), reported posi-
tive correlations for both parents and teachers between the DESSA and all subscales of the Behavioral and
Emotional Rating Scales-2 (BERS /C02;Epstein, 2004 ) and the adaptive skills subscales of the Behavior Assessment
System for Children-2 (BASC-2; Reynolds & Kamphaus, 2004 ). Correlations ranged from .41 to .77 ( N589) for
the parent DESSA and BERS-2 subscales; from .49 to .78 ( N559) for the teacher DESSA and BERS-2 subscales;
from .42 to .71 ( N575) for the parent DESSA and BASC-2 Adaptive Skills subscale; and from .62 to .85 ( N565)
for the teacher DESSA and BASC-2 Adaptive Skills subscale.
Divergent/Discriminant
The DESSA total protective factor scale and subscales correlated negatively with the BASC-2 behavioral symp-
toms index and clinical subscales (except for the Anxiety, Somatization, and Withdrawal subscales ( Nickerson &
Fishman, 2009 ).
Construct/Factor Analytic
No factor analytic findings have been reported to-date.
Criterion/Predictive
Scores on the DESSA were able to differentiate students who were identified as having social, emotional or
behavioral disorders from their non-identified peers (Lebuffe et al., 2009).313 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
Location
LeBuffe, P.A., Shapiro, V.B ., & Naglieri, J.A. (2009). The Devereux Student Strengths Assessment (DESSA),
Technical Manual, and User’s Guide. Lewisville, NC: Kaplan.
Results and Comments
The DESSA is limited in not identifying risk factors or maladaptive behaviors, although low scores on
strengths do suggest problem areas. Further, because this measure requires time-consuming information from
multiple informants, this may act as a barrier when attempting to gather data from a school or school district.
DESSA SAMPLE ITEMS
Sample items are shown below and are responded to on a 5-point Likert-type scale ranging from ‘ Never toVery
Frequently’ .
During the past 4 weeks, how often did the child ...
give an opinion when asked? (Self-Awareness)
get along with different types of people? (Social-Awareness)
adjust well to changes in plans? (Self-Management)
keep trying when unsuccessful? (Goal-Directed Behavior)
express concern for another person? (Relationship Skills)
remember important information? (Personal Responsibility)
accept responsibility for what he/she did? (Decision Making)
say good things about herself/himself? (Optimistic Thinking)
Notes : Items are rated on a 5-point Likert-type scale ranging from: Never toVery Frequently.
The DESSA may be obtained from the Devereux Foundation at the Devereux Center for Resilient Children www.
centerforresilientchildren.org (Retrieved January 6, 2014).
The DESSA has also been published recently by Kaplan Early Learning Company.
www.kaplanco.com (Retrieved May 31, 2014). Reproduced with permission.
ClassMaps Survey (CMS)
(Doll et al., 2004; Doll et al., 2009 ).
Variable
Doll et al. (2009) ,Doll et al. (2010) , as well as Doll, Spies, LeClair, Kurien, and Foley (2010) using a unique eco-
logical perspective, have aimed to assess the resilience of individual classrooms from the perspective of students
attending a class.
Description
The ClassMaps Survey (Doll et al., 2004, 2009 ) is a 55-item student rating scale that provides a brief, relevant
and conceptually-simple evaluation of important classroom or student characteristics related to students’ aca-
demic engagement. The survey’s originally described the correlates of students’ school success ( Doll et al., 2004 ),
and it was refined in a series of studies with elementary and middle-aged students so that items were written in
clear and straightforward language and scale reliability was strengthened ( Doll et al., 2009 ). Each ClassMaps
Survey item describes a characteristic of the classroom or its students, and students respond using a 4-point scale.
Negatively worded items are reverse coded. There are eight subscales. Five subscales describe relational aspects
of the classroom, including teacher-student relationships (My teacher, 7 items), peer friendships (My classmates,
7 items), peer conflict (Kids in this class, 5 items), worries about peer aggression (I worry that, 8 items), and
home-school relationships (Talking with my parents 7 items.) Three of the subscales describe autonomy charac-
teristics including academic self-efficacy (Believing in me, 8 items), self-determination (Taking charge, 8 items),
and behavioral self-control (Following class rules, 6 items.)314 11. MEASURES OF RESILIENCY
III. EMOTION REGULATION |
Sample
The initial sample included 345 Grades 3, 4 and 5 students drawn from two public schools: School 1 in a
Midwestern plains state, and School 2 in a metropolitan east coast state. The 257 students from School 1 were
Grade 3, 4 and 5 students present on the day that the surveys were collected. They included 84 Grade 3 students,
92 Grade 4 students, and 81 Grade 5 students. From School 2, 88 students included 49 third graders, 29 fourth
graders, and 11 fifth graders, of whom 45% were male and 55% were female.
Reliability
Internal Consistency
Despite the CMS subscales’ brevity (5 to 8 items), they have repeatedly shown item substantial homogeneity.
Cronbach alpha coefficients for the ClassMaps Survey subscales are shown in Table 11.3 .
Test/C0Retest
Test/C0retest reliability evidence is not currently available.
Validity
Convergent/Concurrent
Concurrent validity evidence comparing subscales of the ClassMaps Survey and related measures are summa-
rized here:
1.Parallel scales of ClassMaps and the Yale School Development Program School Climate Survey were positively
correlated (.47 to .80; Paul, 2005 ).
2.Positive correlations between the Friendship Features Scale and the peer relationships subscales of the
ClassMaps Survey were ( r5.81 with My Classmates and .28 with Kids in This Class; Doll et al., 2006).
3.Significant correlations were found between all ClassMaps Survey subscales and the degree to which middle
school science students valued their science instruction, were engaged in science instruction, and expected to
succeed in science inquiry assignments ( Doll, Spies, Champion et al., 2010 ).
Divergent/Discriminant
No evidence of divergent validity has been reported to-date.
Construct/Factor Analytic
Two exploratory factor analyses ( Doll & Spies, 2007; Doll, Spies, LeClair et al., 2010 ) and one confirmatory
factor analysis (Doll, Spies, Championet al., 2010) support the construct validity of the CMS subscales
(Table 11.4 ).
Criterion/Predictive
Significant predictive validity correlations have been reported between all CMS subscales and the degree to
which middle school science students valued their science instruction; between Efficacy for Science and the CMS
Believing In Me subscale ( r5.66) and between Engagement in Science and the CMS Taking Charge subscale
(r5.62;Doll, Spies et al., 2010; Kurien, 2011 ). Also, there is evidence that CMS scores are responsive to classroom
changes ( Murphy, 2002; Nickolite & Doll, 2008 ).
Location
Doll, B., Zucker, S., & Brehm, K. (2004.) Resilient classrooms: Creating healthy environments for learning. New
York: Guilford.
Results and Comments
The CMS presents a unique assessment tool for use in educational settings for enhancing the resiliency pro-
moting features of the classroom environment. The anonymity of students is an advantage in school environ-
ments where parents are sensitive to privacy considerations and increase the likelihood of truthful responding.
A possible disadvantage is that scores are not used for individual assessment.315 MEASURES REVIEWED HERE
III. EMOTION REGULATION |
TABLE 11.3 ClassMaps Survey: Internal Consistency
Reference Sample Academic
EfficacySelf-
DeterminationSelf-
ControlTeacher-
StudentHome
SchoolPeer-
friendshipsPeer-
conflictPeer-I Worry
That
Doll et al., 2004 466 middle school; CO .89 .93 .82 .77 .56
Doll & Siemers, 2004 1615 elementary; NE, IL, NJ .64 .55 .75 .84 .77 .70
Doll & Spies, 2007 420 elementary; NE, NJ .86 .87 .88 .96 .89 .92 .87 .90
Doll et al., 2010 1019 5th/C08thgrade
students; NE.87 .82 .89 .87 .88 .87 .91
Doll et al., 2010 345 elementary students;
NE, NJ.81 .78 .84 .82 .86 .86 .87 .92 |
CMS SAMPLE ITEMS
Believing in Me
I can get good grades when I try hard in this class.
I know that I will learn what is taught in this class.
I expect to do very well when I work hard in this class.
My Teacher
My teacher listens carefully to me when I talk.
My teacher helps me when I need help.
My teacher likes having me in this class.
Taking Charge
I want to know more about things we learn in class.
I work as hard as I can in this class.
I know the things I learn in this class will help me outside of school.
Following the Class Rules
Most kids work quietly and calmly in this class.
Most kids in this class listen carefully when the teacher gives directions.
Most kids follow the rules in this class.
Talking to my Parents
My parents and I talk about my grades in this class.
My parents and I talk about what I am learning in this class.
My parents and I talk about my homework in this class.
Notes : Items are rated on a 4-point scale ranging from: 0 5‘Never’; 1 5‘Sometimes’; 2 5‘Often’; 3 5‘Almost
always’. Reproduced with permission.
FUTURE RESEARCH DIRECTIONS
The positive psychology movement has gained considerable momentum in the past decade resulting in
a plethora of ‘measures’ to assess the various factors and constructs encompassed by this. While certainly not
a new concept to psychology, resilien cy has received particular attention because of its theoretical role as
both a protective factor but also one that underlies the growth of human potential. The definition of resiliency
continues to undergo development and it can be expected that more elaborate models of resiliency, also
showing its position in a description of human behavior, will be forthcoming. Thus we may also expect to seeTABLE 11.4 ClassMaps Survey: Factor Analyses
Reference Sample CFI RMSEA SRMR # Items misloading
CRITERIA - ..95 ,.06 ,.08 0
Doll & Spies, 2007 420 elementary; NE, NJ .91 .05 .05
Doll et al., 2010 1019 5th /C08th Grade students; NE .92 .04 .05 1 MT item
Doll et al., 2010 345 elementary students; NE, NJ Eight factor solution accounted for 58%
of variance.1 MT item; 2 TC items;317 FUTURE RESEARCH DIRECTIONS
III. EMOTION REGULATION |
not only the scales reviewed here undergo change but also new ones to appear in the research and clinical
literature.
While resiliency does not necessarily appear in the titles of all measures reviewed here, these scales share com-
mon features that are generally viewed as defining the construct. At the same time, it must be remembered that,
like ‘intelligence or personality’ instruments, each scale does have both overlapping and unique content and thus
it is important to operationally define how one is assessing and describing resiliency. The scales we have elected
to include in this review are not exhaustive of the literature addressing resiliency but show both the evolution of
the construct and its current measurement. Further, we have included only those scales/measures that have pro-
vided reasonable support for their psychometric integrity and clinical use.
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CHAPTER
12
Measures of Coping for Psychological
Well-Being
Katharine H. Greenaway1, Winnifred R. Louis1, Stacey L. Parker1,
Elise K. Kalokerinos1, Joanne R. Smith2and Deborah J. T erry1
1University of Queensland, St Lucia, Queensland, Australia;2University of Exeter, Exeter, UK
As individuals go through life they face adversity, encounter resistance, experience stress, and meet chal-
lenges. People deal with these threats and challenges in a variety of different ways. They might confront the
problem head on; engage in other activities to distract themselves from the problem; use substances to alter their
senses; or turn to others or religion to help them cope. Researchers have developed instruments designed to dis-
tinguish and measure specific coping strategies in stressful situations. We review six of the most prominent
instruments used in coping research (see below).
Coping can take various forms. Animal models conceptualize coping as acts that resolve aversive environmen-
tal conditions, thereby reducing psychophysiological disturbance ( Miller, 1980; Ursin, 1980 ). Cognitive theories
define coping as ‘constantly changing cognitive and behavioral efforts to manage specific external and/or inter-
nal demands that are appraised as taxing or exceeding the resources of the person’ ( Lazarus & Folkman, 1984 ,
p. 141). These theories typically conceptualize coping as a dynamic interplay of person and environment factors.
That is, people may be exposed to the same environmental stressor but cope in different ways depending on their
personal characteristics. Similarly, the same individual may cope differently from one situation to the next
depending on variation in the specific environmental demands.
This theoretical distinction between a focus on the individual as possessing static versus malleable coping ten-
dencies across situations has led to some confusion in the field. What researchers do agree on is that the process
of coping should be considered as separate from the outcome of coping ( Lazarus & Folkman, 1984; Leventhal,
Suls, & Leventhal, 1993; Schwarzer & Schwarzer, 1996 ). That is, definitions of coping should include efforts to
manage stressful demands, regardless of whether those efforts are successful. An inclusive study of coping
should include assessment of both adaptive and maladaptive coping strategies.
Coping is generally thought of as a reactive process triggered in response to a causal event. It is this element
of an external trigger that distinguishes coping specifically from the related process of self-regulation more gener-
ally ( Folkman & Moskowitz, 2004 ). Most commonly, people encounter a stressful event with which they need to
cope. There are a number of features of the trigger, or stressful event, that influence howpeople cope with that
event. In cognitive theories, the most important factor in determining how people cope is their appraisal of the
situation. Individuals also may identify and utilize resources at their disposal to assist their coping efforts.
People differ widely in their response to stress. Some react strongly to minor stresses while others are not
fazed by even major stresses in life. An event that evokes fear and avoidance in one individual may inspire
energy and approach in another. A main determinant of a person’s coping response is the way they appraise a
stressful situation. Lazarus’ (1966) classic stress and coping theory distinguishes between two types of cognitive
appraisals: primary and secondary appraisals (for a more recent review see Lazarus, 2006 ).
322Measures of Personality and Social Psychological Constructs.
DOI: http://dx.doi.org/10.1016/B978-0-12-386915-9.00012-7 ©2015 Elsevier Inc. All rights reserved. |
Primary appraisals are made when an individual evaluates a situation as having significance for their well-
being. Appraisals of stressful situations fall into three main categories: harm, threat, and challenge ( Lazarus &
Folkman, 1984 ). Harm appraisals are made about situations in which psychological or physical damage has been
sustained. Threat appraisals are made about anticipated negative situations in which psychological or physical
damage could occur. In contrast, challenge appraisals are made about situations that carry the potential for posi-
tive outcomes, improvement, and growth. Whether someone appraises a stressful situation as representing harm,
threat, or a challenge critically impacts on that individual’s orientation towards the stressor, choice of coping
strategies, and his/her emotional experience of stress. Primary appraisals are not static or one-off cognitive repre-
sentations of events, however; individuals engage in a constant process of appraisal and reappraisal until stress
is resolved.
Secondary appraisals concern an individual’s perceived ability to handle a stressful event. These appraisals
are key in identifying what might and can be done to cope with the stressor. An important element that influ-
ences secondary appraisal is the availability of coping resources /C0practical and psychological tools that assist peo-
ple in meeting and overcoming demands in the environment.
Coping resources may be actual features of the environment that enable people to cope with stress (e.g., access
to money, availability of social support; Schwarzer & Leppin, 1991 ) or factors internal to the individual that aid
coping efforts (e.g., optimism, Scheier & Carver, 1992 ; hardiness, Eschleman, Bowling, & Alarcon, 2010 ; self-effi-
cacy; Jerusalem & Schwarzer, 1992 ). These personal resources are distal predictors of coping strategies. For exam-
ple, internal locus of control is associated with greater problem-focused coping strategies ( Parkes, 1994 ). In a
recent meta-analysis, Conner-Smith and Flaschsbart (2007) found that extraversion and conscientiousness pre-
dicted more problem-solving and cognitive restructuring coping strategies. In contrast, neuroticism predicted
maladaptive coping strategies such as wishful thinking, withdrawal, and emotion-focused coping.
Given the wide variety of specific coping strategies available, researchers have found it useful to identify more
parsimonious dimensions by which to distinguish and categorize coping strategies ( Skinner, Edge, Altman, &
Sherwood, 2003 ). A common theoretical distinction in coping research is between approach and avoidance (an
individual’s orientation towards or away from threatening stimuli) /C0(Roth & Cohen, 1986 ).
Several measures reviewed here draw on this distinction. The Miller Behavioral Style Scale (Miller, 1981) dis-
tinguishes between monitors /C0individuals who seek out information about threats in the environment /C0and
blunters /C0individuals who seek to distract themselves from threat. The Mainz Coping Inventory ( Krohne, 1993 )
distinguishes the use of vigilant coping styles from avoidance coping styles. Vigilant coping involves the direction
of attention towards threatening information, and avoidance coping involves the direction of attention away
from threatening information.
Another basic distinction is between assimilation and accommodation (e.g., Brandstadter & Renner, 1990;
Piaget, 1985 ). Assimilative processes involve altering the env ironment or situation to bring it more in line with
one’s desires (e.g., trying to change stressful circumstan ces; exerting primary control). In contrast, accommoda-
tive processes involve adjusting one’s desires to fit with situational constraints (e.g ., accepting the situation
and looking for positives; exerting secondary control; Band & Weisz, 1988; Heckhausen & Schulz, 1995;
Rothbaum, Weisz, & Snyder, 1982; Weisz, McCabe, & Dennig, 1994 ).Lazarus and Folkman’s (1984) classic dis-
tinction between problem-focused coping and emotion-focused coping draws on the assimilation-accommodation
distinction. The Ways of Coping Questionnaire ( Folkman & Lazarus, 1988 ), reviewed in this chapter, measures
coping efforts aimed at altering the s tressful event, and those aimed at reg ulating emotional reactions to the
stressful event.
The dimensions of approach /C0avoidance and assimilation /C0accommodation can provide useful taxonomies for
classifying specific strategies into higher-order coping categories. This theoretical approach has received criticism,
however ( Skinner et al., 2003 ). There is ambiguity regarding the concrete classification of specific coping strate-
gies into either one dimension or another. For example, seeking social support could be considered an approach
coping strategy in that people seek out methods of helping them cope with a stressful event, or it could be con-
sidered an avoidance coping strategy whereby people seek to escape from the stressful event. Information seek-
ing may represent either a method of assimilation (to the extent that people seek to use the information to
change the situation) or accommodation (to the extent that people seek to use the information to accept and
adjust to the situation). Therefore, although broad coping taxonomies are useful theoretically, the multi-faceted
nature of coping necessitates use of specific measures that assess a broad range of coping strategies (e.g., Skinner,
2003). Measurement of specific coping strategies presents its own challenges, however.
The most pervasive debate in the coping literature centers on the measurement of dispositional coping
styles compared with situational coping strategies. Coping styles are dispositional tendencies toward a323 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
particular way of coping that are considered to be relatively stable across different stressful situations (e.g.,
Carver, Scheier, & Weintrab, 1989 ). In comparison, coping strategies are flexible responses to situational
demands ( Lazarus & Folkman, 1984 ). Coping strategies are considered to be dynamic and responsive moment-
by-moment efforts in response to a specific stressful situation.
Conceptualization of coping as a trait (i.e., fixed) or as a state (i.e., flexible) process has its own merits and lim-
itations. There is utility in measuring stable coping styles across individuals ( Carver et al., 1989 ). Such an
approach allows for the identification of consistent ways of coping with stress. Does an individual in general
tend to orient towards or away from threat? Are they more likely to draw on social support rather than other
forms of coping? Answering these questions addresses predictive validity across a range of situations. Indeed,
trait coping measures share variance with personality traits ( Conner-Smith & Flachsbart, 2007 ), indicating that
these types of measures tap stable and predictable differences between individuals.
The study of coping styles has received criticism, however (e.g., Lazarus, 1991 ).Lazarus and Folkman (1984)
argued that an assessment of coping at the trait level stifles predictive validity within specific coping contexts,
because it ignores variation in behavior due to specific situational demands. They claimed that this underesti-
mates the complexity and variability in actual coping efforts and that an analysis of coping styles does not cap-
ture the multidimensional nature of coping processes.
In contrast, situational assessments view coping as a dynamic process that changes within individuals across
situations. State measures of coping assess how an individual reports coping in specific stressful situations, rather
than how they report coping with stress in general. Lazarus and Folkman (1984) claimed that in order to gain a
full understanding of the coping process, one must understand what problem an individual is coping with and
the specific strategies being used to cope in that situation. State coping measures are therefore likely to be more
predictive of coping outcomes within specific situations than trait coping measures.
A situation-specific analysis also allows for assessment of stress and coping as a dynamic feedback process
that unfolds over time. That is, an individual’s coping efforts respond flexibly to changes in the environment
(Daniels & Harris, 2005; Lazarus & Folkman, 1984 ). This conceptualization is distinct from the relatively static
analysis provided by trait measures of coping.
Thus, there is a tension in the coping literature between researchers who propose the use of trait measures of
coping and those who propose the use of state measures of coping. Yet both analyses are important for a full
understanding of the coping process. People are not ‘locked into’ a particular coping style that dictates their
response in every stressful situation. Such an adaptation would be useless and potentially dysfunctional. Nor are
people ‘blank slates’, reacting to every new situation in a completely novel way. Carver et al. (1989) proposed
that after repeated exposure to stress and successful resolution of this stress, some people come to habitually
implement the specific coping strategies that led to the successful outcome. Coping styles then provide the dispo-
sitional scaffolding that predisposes individuals to a particular way of coping. It appears that people engage
actively in the coping process, using tailored coping strategies and reacting dynamically to the demands of the
specific situation.
MEASURES REVIEWED HERE
The measures reviewed in this chapter fall into the two broad categories of dispositional (or trait) coping and
situational (or state) coping. The measures and their subscales are outlined below.
Trait Coping Measures
1.Miller Behavioral Style Scale ( Miller, 1987 )
2.Mainz Coping Inventory ( Krohne, 1993 )
3.Coping Inventory for Stressful Situations ( Endler & Parker, 1990, 1994 )
4.COPE Inventory ( Carver et al., 1989 )
State Coping Measures
1.Coping Strategy Indicator ( Amirkhan, 1990 )
2.Ways of Coping Questionnaire ( Folkman & Lazarus, 1988 )324 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
OVER VIEW OF THE MEASURES
The first four instruments outlined in this chapter measure dispositional coping styles, although they assess
coping in different ways. The Miller Behavioral Style Scale (MBSS; Miller, 1987 ) and the Mainz Coping Inventory
(MCI; Krohne, 1993 ) conceptualize coping style in terms of the direction of attention toward or away from threat-
ening stimuli. Both these measures assess ways of focusing on threatening or stressful stimuli in a process akin to
‘attentional deployment’ in models of emotion regulation ( Gross, 1998 ). This basic distinction between monitoring
and blunting (MBSS) or vigilance and avoidance (MCI) is thought to direct and shape later coping efforts,
although researchers rarely combine these instruments with other measures that assess dispositional coping strat-
egies (e.g., the Coping Inventory for Stressful Situations or CISS; the COPE Inventory).
The CISS ( Endler & Parker, 1990, 1994 ) and the COPE Inventory ( Carver et al., 1989 ) measure a wide range of
dispositional coping styles. Although they assess different content, both measures are psychometrically well vali-
dated and used widely in coping research. Modified versions of both the CISS and the COPE were constructed to
assess specific coping strategies in addition to dispositional coping styles. To distinguish dispositional coping
styles from situational coping strategies, researchers typically alter the frame of reference when measuring coping
responses. When adopting a dispositional perspective, researchers ask about how people respond to stressful
events in general . When adopting a situational perspective, researchers ask about how people respond to a specific
stressful event.
The final two measures, the Coping Strategy Indicator (CSI; Amirkhan, 1990 ) and the Ways of Coping
Questionnaire (WCQ; Folkman & Lazarus, 1988 ) assess situational coping strategies in response to a specific
stressful event. These measures provide a counterpoint to dispositional measures. The WCQ is the most com-
monly used situational measure in coping research, possibly because it assesses a wider range of coping strate-
gies, or because of the seminal impact of Folkman and Lazarus’ work on coping theory.
These measures represent some of the most widely used and psychometrically validated coping scales cur-
rently available. There are many other coping measures available that specifically target particular populations,
such as children and adolescents (e.g., Coping Scale for Children and Youth; Brodzinsky et al., 1992 ; Adolescent
Coping Orientation for Problem Experiences Inventory; Patterson & McCubbin, 1987 ) or employees (e.g., Career
Attitudes and Strategies Inventory; Holland & Gottfredson, 1994 ; Occupational Attributional Styles
Questionnaire; Furnham, Sadka, & Brewin, 1992 ). Similarly, there are coping measures that target particular
domains, such as health and sports (e.g., Health and Daily Living Form; Moos, Cronkite, Billings, & Finney, 1983 ;
Drinking Motives Questionnaire; Cooper, 1994 ) and academic performance (e.g., Academic Coping Strategies
Scale; Sullivan, 2009 ). We focus on measures that are not domain or sample specific, and thus have a broad appli-
cability across a wide range of research and other contexts.
TRAIT COPING MEASURES
Miller Behavioral Style Scale (MBSS)
(Miller, 1987 ).
Variable
The MBSS assesses stable differences in attentional focus during uncontrollable threatening events.
Description
The MBSS distinguishes between two possible ways of dealing with threat: To seek out information about the
threat, or to distract oneself from the threat. The scale categorizes individuals as monitors (information seekers)
or blunters (distractors). One’s preference for seeking threat-related information and the availability of threat-
related information in the environment determines how stressed and anxious individuals become. Accordingly,
monitors prefer high information input during threatening episodes, and show a reduction in stress and arousal
when such information is available. Conversely, blunters prefer low information input during threatening epi-
sodes, and show a reduction in stress and arousal when able to distract themselves from the situation.
The MBSS consists of four hypothetical stressful sc enarios (visiting a dentist, being held hostage by
terrorists, potential job loss, and a turbulent plane ride ) that participants are asked to imagine and respond to.
There is also a brief version of the MBSS (see Steptoe, 1989 ) that uses the two most ecologically valid325 TRAIT COPING MEASURES
III. EMOTION REGULATION |
hypothetical situations: The dentist and job loss scenarios. Each scenario is followed by eight possible ways of
dealing with the situation, four of which represent moni toring or information seeking strategies (e.g., ‘I would
ask the dentist exactly what he was going to do’) and fou r that represent blunting or distraction strategies
(‘I would try to think about pleasant memories’). Indi viduals indicate whether or not they would use each
strategy on a forced-choice yes/no response scale.
The scale yields two scores: A total monitoring score, derived from adding the number of selected ‘monitoring’
options and a total blunting score, derived from adding the number of selected ‘blunting’ options. Individuals
can be categorized as high or low monitors and blunters by employing a median split procedure. Alternatively,
researchers can treat the scales as unipolar constructs by summing the items for each scale and using the result-
ing scores as independent predictors ( Myers & Derakshan, 2000 ). In some instances researchers have created a
summary score by subtracting blunting scores from monitoring scores (e.g., Miller & Mangan, 1983 ).
Sample
The scale was normed in two experiments on American undergraduate students with sample sizes of 30 and
40 respectively (equal gender ratios in both studies; Miller, 1987 ). The means on the monitoring subscale were
9.70 ( SD52.63; Experiment 1) and 11.10 ( SD52.46; Experiment 2) and the means on the blunting subscale were
5.57 ( SD52.86; Experiment 1) and 4.55 ( SD52.09; Experiment 2).
Reliability
Internal Consistency
The MBSS exhibited Cronbach alpha coefficients ranging from .67 (blunting, Miller, 1987 ; Experiment 2) to .79
(monitoring, Miller, 1987 ; Experiment 1). Its use in different populations such as children (e.g., Kliewer, 1991 )
and adults (e.g., Ben-Zur, 2002 ) has yielded similarly varied estimates, with some researchers finding smaller
Cronbach alpha coefficients particularly for the blunting subscale ( α5.41;Rees & Bath, 2000 ).
Test/C0Retest
Test/C0retest reliability over four weeks was adequate for the monitoring subscale (.71) although the test /C0retest
reliability of the blunting subscale was not assessed ( Rees & Bath, 2000 ).Miller (1987) reported test /C0retest reli-
abilities for the monitoring (.72) and blunting (.75) subscales over an interval of four months.
Validity
Convergent/Concurrent
Research has revealed meaningful relationships between the MBSS and situation-specific coping strategies (as
measured by the COPE, reviewed later in this chapter). In a study with 52 university students, Myers and
Derakshan (2000) found that monitoring was positively related to active coping ( r5.26), Similarly, van Zuuren
and Wolfs (1991) found that monitoring was positively related to more problem-focused forms of situation spe-
cific coping ( r5.35).
Divergent/Discriminant
Coping validation studies often do not set out to show evidence of discriminant validity, preferring instead to
focus on demonstrating convergent, construct, and predictive validity. Despite this, some evidence can be found
to show that monitoring and blunting are not associated with constructs to which they should be unrelated. For
example, monitoring and blunting have been found to be unrelated to use of humor as a coping strategy and
negatively related to seeking instrumental social support ( r52 .34) and acceptance ( r52 .28; Myers &
Derakshan, 2000 ). Blunting tends to be unassociated with functional, approach-related forms of coping, such as
problem-focused help-seeking, and adaptive attribution styles that predict lower depression ( van Zuuren &
Wolfs, 1991 ).
Construct/Factor Analytic
The MBSS was originally validated in two experiments by Miller (1987) . Participants were placed in aversive
situations that carried the potential of a physical threat (an electric shock; Experiment 1) or an ego threat (poor
test performance; Experiment 2). In Experiment 1, participants were able to choose between two radio channels
that played information about the electric shock (high monitoring channel) or distracting music (high blunting
channel). In Experiment 2, participants could obtain on-line information about their test performance by326 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
attending to a light (high monitoring behavior). In both experiments, high monitors and low blunters attended
more to the information about the threat than low monitors and high blunters. In Experiment 1, low monitors
and high blunters attended more to the distracting music than did high monitors and low blunters. The factor
structure of the scale holds up in tests conducted by independent researchers ( Muris & Schouten, 1994 ). In this
study, 583 students completed the 5-point version of the MBSS, and an exploratory factor analysis was con-
ducted. Two factors were extracted; monitoring items loaded on to the first factor, blunting items on to the sec-
ond factor.
Criterion/Predictive
In a variety of contexts, monitors have been found to have higher levels of worry and distress than blunters.
For example, more so than blunters, monitors have been found to be particularly prone to anxiety ( Muris, van
Zuuren, & De Vries, 1994 ), depression ( Shiloh, Koehly, Jenkins, Martin, & Hadley, 2008 ), displays of distress dur-
ing invasive screening examinations ( Wardle et al., 1993 ), and anticipation of discomfort and physical pain dur-
ing medical procedures ( Miller, Roussi, Altman, Helm, & Steinberg, 1994 ). Other researchers ( Rees & Bath, 2000;
Wakefield, Homewood, Mahmut, Taylor, & Meiser, 2007 ) have validated the general tendency of monitors to
attend to threatening information among patients with a family history of cancer. High monitors are more likely
than low monitors to seek out information about cancer ( Rees & Bath, 2000 ), and high blunters are more likely
than low blunters to engage in distraction ( Wakefield et al., 2007 ).
Location
Miller, S.M. (1988). The interacting effects of coping styles and situational variables in gynecologic settings:
Implications for research and treatment. Journal of Psychosomatic Obstetrics and Gynaecology ,9,2 3/C034. doi:
10.3109/01674828809030946.
Results and Comments
The MBSS is a measure of the degree to which people seek out or avoid information about threatening events.
These issues of information search and threat are particularly relevant in the context of health ( Miller, 1992 ), and
the measure has been used extensively in this domain. Among other applications, the MBSS has been used to
investigate the experience of chronic pain ( Litt, Shafer, & Kreutzer, 2010 ), physician visits ( Miller, Brody, &
Summerton, 1988 ), dental fear (Muris et al., 1996), HIV testing ( Delaney & O’Brien, 2009; Miller, Rodoletz,
Schroeder, Mangan, & Sedlacek, 1996 ), gynecological surgery ( Steptoe & O’Sullivan, 1986 ), prenatal diagnosis
(van Zuuren, 1993 ), genetic screening (Miller et al., 2007), and cancer chemotherapy ( Gard, Edwards, Harris, &
McCormach, 1988 ).
In addition to being more reliable than the blunting subscale, the monitoring subscale has been shown to be a
more consistent predictor of health-related coping behaviors (Miller et al., 1987). However, this does not mean
that monitoring is a more effective strategy than blunting in coping with health threats. Although high monitors
are more likely than high blunters to take preventative health care actions, they are also more likely to experience
arousal and anxiety about their health, and are more prone to ruminative thoughts about their illness ( Miller
et al., 1988, 1996 ). In clinical samples, efforts to avoid disturbing thoughts require extreme defensive strategies
including denial as well as mental and behavioral disengagement. This suggests there might be costs to a moni-
toring attentional style for patients with severe long-term medical threats.
Treatment of the monitoring and blunting subscales can be critiqued on the grounds that dichotomizing
reduces the variance unnecessarily and introduces error at the category boundaries. In addition, the response
format of the scale requires a forced-choice yes/no response from participants, further reducing potentially
explainable variance. It should be noted that researchers have successfully adapted the response scale to a 5-
point Likert-type, however (see van Zuuren, De Jongh, Beekers, & Swinkels, 1999 ). It is also the case that the sub-
scales are not always equally reliable, valid, or strongly negatively associated with each other. Thus independent
use of the subscales, or sole use of the monitoring subscale, can be considered.
MILLER BEHAVIORAL STYLE SCALE (SAMPLE ITEMS)
1.Vividly imagine that you are on an airplane, 30
minutes from your destination, when the plane
unexpectedly goes into a deep dive and thensuddenly levels off. After a short time the pilot
announces that nothing is wrong, although the rest of
the ride may be rough. You, however, are not327 TRAIT COPING MEASURES
III. EMOTION REGULATION |
convinced that all is well. Tick allof the statements
that might apply to you.
____ I would carefully read the information
provided about safety features in the plane and
make sure that I knew where the exits were. (M)
____ I would make small talk with the passenger
beside me. (B)
____ I would watch the end of the movie, even if I
had seen it before. (B)
____ I would call the flight attendant and ask
him/her exactly what the problem was. (M)
____ I would order a drink from the
stewardess. (B)____ I would listen carefully to the engines for
unusual noises and would watch the crew to see if
their behavior was out of the ordinary. (M)
____ I would talk to the passenger beside me
about what might be wrong. (M)
____ I would settle down and read a book or
magazine or write a letter. (B)
Subscales :M5Monitoring, B 5Blunting.
Source :Miller (1988) . The interacting effects of coping
styles and situational variables in gynecologic set-
tings: Implications for research and treatment. Journal
of Psychosomatic Obstetrics and Gynaecology ,9,2 3/C034.
Reprinted with permission from Informa Healthcare.
Mainz Coping Inventory (MCI)
(Krohne, 1993 ).
Variable
The MCI measures the degree to which individuals adopt a vigilant or avoidant coping style when approach-
ing threatening situations.
Description
The MCI distinguishes between coping strategies that are designed to reduce ambiguity and increase under-
standing (vigilance) and strategies designed to protect the individual from threatening information and manage
emotional distress (cognitive avoidance). Unlike the MBSS, which was originally intended to categorize people as
either high monitors/low blunters or low monitors/high blunters, Krohne’s measure treats vigilance and avoid-
ance as independent from one another. Thus, it is possible for people to score high in both cognitive avoidance
and vigilance at the same time.
Given that the scales are relatively independent, people can be grouped in terms of four coping profiles.
People high in vigilance and low in cognitive avoidance are referred to as sensitizers and adopt a rigid monitoring
style in threatening situations. People low in vigilance and high in cognitive avoidance, however, are known as
repressors and adopt a consistent avoidant style in threatening situations. A high score on both vigilance and cog-
nitive avoidance is thought to be a particularly maladaptive coping profile (indeed, this group is referred to as
unsuccessful copers orhigh anxious ) while a low score on both dimensions is the hallmark of flexible ornon-defensive
coping.
The MCI consists of eight hypothetical threat scenarios, half of which depict a physical threat situation (e.g., a
turbulent plane ride) and the other half an ego threat situation (e.g., making a public speech). The MCI can there-
fore be divided into two subtests of responses to physical and ego threats. Each scenario is followed by 18 possi-
ble responses that are reworded to reflect the content of the particular scenario. These 18 responses comprise
nine vigilant coping strategies and nine avoidance coping strategies. The nine vigilant coping strategies are:
(1) recalling negative events; (2) self-pity; (3) information search; (4) comparison with others; (5) planning; (6)
escape tendency; (7) control via information; (8) anticipation of negative events; and (9) situation control. The
nine cognitive avoidance coping strategies are: (1) minimization; (2) self-enhancement; (3) re-interpretation; (4)
attentional diversion; (5) down playing; (6) denial; (7) emphasizing one’s own efficacy; (8) accentuating positive
aspects; and (9) trust. These 18 coping strategies do not represent independent dimensions or sub-facets of vigi-
lant and avoidance coping; these merely serve as test items to generate scores for the two scales ( Schwarzer &
Schwarzer, 1996 ). Confirmatory factor analysis verified that vigilance and avoidance are distinct and distinguish-
able dimensions of the scale ( Krohne et al., 2000 ).
Participants respond on a true /C0false scale to indicate whether or not they would use each strategy. Scores can
be obtained for each coping style (i.e., vigilance and avoidance) and each type of threat, resulting in four scores328 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
representing vigilant coping in physical threat situations, vigilant coping in ego threat situations, avoidant coping
in physical threat situations, and avoidant coping in ego threat situations.
Sample
The initial test of the MCI was conducted with 426 West German participants ranging in age from 14 to 76
years ( Krohne, Rosch, & Kursten, 1989 ). An English version of the MCI was also created and tested with native
speaking university students in America and Canada ( N5348; Krohne et al., 2000 ). The mean for the vigilance
subscale was 26.26 ( SD56.59) for men and 28.06 ( SD56.35) for women. The mean for the cognitive avoidance
subscale was 22.95 ( SD55.69) for men and 20.33 ( SD56.91) for women.
Reliability
Internal Consistency
The MCI exhibited Cronbach alpha coefficients between .80 and .88 ( Krohne, 1989; Krohne et al., 1989;
Schumacher, Krohne, & Kohlmann, 1989 ). The English version of the scale also exhibited alpha coefficients of .84
for each subscale.
Test/C0Retest
The English version of the scale yielded acceptable test /C0retest reliability over two weeks of .70 for the vigi-
lance subscale and .84 for the cognitive avoidance subscale ( Krohne et al., 2000 ).
Validity
Convergent/Concurrent
The MCI showed convergent validity in tests of associations with other coping-related measures ( Krohne
et al., 2000 ). Vigilance correlated positively with negative affect ( r5.14 to .18), behavioral inhibition ( r5.19 to
.23), and several subscales from the COPE scale ( Carver et al., 1989 , reviewed later in this chapter) including
planning coping ( r5.19 to .23), active coping ( r5.15 to .22), instrumental social support ( r5.20 to .26), venting
emotions ( r5.23 to .26), and restraint coping ( r5.19 to .24).
Consistent with the observation that the MCI assesses attentional deployment in a similar way to the MBSS
(Miller, 1987 ),Muris et al. (1994) found that the monitoring subscale of the MBSS was highly correlated with the
vigilance subscale of the MCI ( rs..40), and that the blunting subscale of the MBSS was similarly correlated with
the avoidance subscale of the MCI ( rs..50). Within the MCI, the vigilance subscales were strongly positively cor-
related across the physical threat and ego threat scenarios (.60), as were the cognitive avoidance subscales (.57)
(Krohne et al., 2000 ). This finding was replicated by Krohne and Egloff (2005) , who also found positive correla-
tions across scenarios within the vigilance ( r5.59) and avoidance scales ( r5.47).
Divergent/Discriminant
Showing evidence of discriminant validity, vigilance was unrelated to meaningful subscales of the COPE,
including acceptance, and various forms of disengagement (behavioral, mental). In contrast, cognitive avoidance
tended to be uncorrelated with more problem-focused forms of coping, such as active coping and planning. This
scale was also uncorrelated with behavioral activation, or approach ( Krohne et al., 2000 ). Cognitive avoidance
was negatively correlated with negative affect, r52.20 to 2.39 and behavioral inhibition, r52.16 to 2.28)
although not always significantly for the coping variables (e.g., active coping and venting emotions). Finally,
Krohne et al (2000) found that vigilance and cognitive avoidance coping strategies were modestly negatively cor-
related with one another ( r52 .23), a finding replicated by Krohne and Egloff (2005) .
Construct/Factor Analytic
To examine the factor structure of the MCI, Krohne et al. (2000) had 169 students complete the MCI, and con-
ducted confirmatory factor analyses separately for the ego threat and physical threat subscales. For the ego threat
subscale, fit indices demonstrated that the two-dimensional model had good fit to the data. For the physical
threat subscale, the two-dimensional model demonstrated good fit once the model was respecified to allow the
residuals associated with vigilance and cognitive avoidance in the ‘visiting the dentist’ and ‘turbulent flight’
situations to covary. This suggests that for these two scenarios, vigilance and cognitive avoidance were not
completely independent of each other. In another study, Krohne, Schmukle, Burns, Egloff, and Spielberger (2001)
had 720 college students (360 North Americans and 360 Germans) complete the MCI and conducted both329 TRAIT COPING MEASURES
III. EMOTION REGULATION |
exploratory and confirmatory factor analyses. The exploratory factor analysis identified two factors with eigenva-
lues over 1, with the vigilance items mapping on to one factor, and the cognitive avoidance items mapping on to
the other factor. The confirmatory factor analyses showed that a two-factor model had good fit for the North
American sample, but failed to meet the criteria for good fit for the German sample. The misfit for the German
sample was rectified by allowing the residuals of ‘dentist’ and ‘flight’ to covary, as in Krohne et al. (2000) .
Criterion/Predictive
The MCI has been found to predict emotion regulation and health outcomes in medical contexts ( Krohne &
Egloff, 2005 ). Vigilance was associated with greater negative affect ( r5.18), lower self-esteem ( r52.19), and
higher neuroticism ( r5.34). On the other hand, avoidance predicted less negative affect ( r52 .41), greater posi-
tive affect ( r5.32), better self-esteem ( r5.26), and lower neuroticism ( r52 .43), marking it as a useful emotion
regulation strategy in these contexts. However, vigilance was positively associated ( r5.27) and avoidance nega-
tively associated ( r52 .25) with symptom reporting. As a result, vigilant individuals may be less happy than
avoidant individuals, but also more likely to receive treatment for potentially life-threatening illnesses.
The MCI also predicted self-reported and physiological stress reactions in a sample of patients awaiting sur-
gery ( Krohne, 1989 ). Individuals high in both vigilance and avoidance (unsuccessful copers) showed the most
subjective and objective levels of stress, while individuals low in both dimensions (flexible copers) showed the
lowest levels of stress.
Location
Krohne, H., Egloff, B., Varner, L., Burns, L., Weidner, G., & Ellis, H. (2000). The assessment of dispositional
vigilance and cognitive avoidance: Factorial structure, psychometric properties, and validity of the Mainz Coping
Inventory. Cognitive Therapy & Research, 24 , 297/C0311. doi: 10.1023/A:1005511320194.
Results and Comments
The MCI has been used to investigate reactions to a number of threatening life events. For example, the mea-
sure has been used to test how people cope with the stress of surgery ( Krohne, Heinz, Kleeman, Hardt, &
Thesen, 1990 ), high-stakes athletic competitions ( Krohne & Hindel, 1988 ), exposure to threatening health commu-
nications ( Nestler & Egloff, 2012 ), reactions to media violence ( Krahe, Moller, Berger, & Felber, 2011 ), and aca-
demic performance ( Krohne, 1993; Krohne & Hock, 1993 ). In general, cognitive avoidance has been found to be a
particularly effective strategy in achievement situations; individuals who scored high in cognitive avoidance
tended to outperform those who scored low on this dimension, or high in vigilance, in the athletic and academic
stress situations. This echoes findings with the conceptually similar monitoring subscale of the MBSS ( Miller,
1987), which suggest that cognitive vigilance may ultimately prove to be a maladaptive and stressful coping strat-
egy in situations of extreme or chronic stress.
Krohne’s theory proposes that the environment plays an important role in successful coping, and the degree to
which people are enabled by the environment to use their coping strategies of choice. For example, in one test of
this logic Krohne (1993) found that repressors and sensitizers performed equally well on an academic test when
provided with structured instructions on the content of the test (‘structured preparation’). However, sensitizers
were impeded and repressors facilitated in their performance when given no information about the content that
would be tested (‘unstructured preparation’). Accordingly, it is important to consider how people’s dispositional
coping styles may result in adaptive or maladaptive coping depending on the situation. This theorizing repre-
sents an example of the kind of attempt to synthesize research on dispositional and situational coping that we
called for in the introduction of this chapter.
The two dimensions of vigilance and cognitive avoidance provide a useful framework with which to catego-
rize reactions to stressful events. However, the MCI as a measure does suffer from some limitations. As with the
MBSS, the instrument relies on hypothetical scenarios to measure dispositional reactions to stress. Some research-
ers have criticized this type of measurement as lacking ecological validity (e.g., Muris & Schouten, 1994; Steptoe,
1989) and as a sub-optimal way of measuring people’s actual coping style.
It can also be noted that within the vigilance subscale there are both measures of rumination (self-pity, recal-
ling negative information) and more problem-focused responses (planning, information search). Similarly, within
the avoidance measure there are measures of self-enhancement and denial as well as reappraisals such as focus-
ing on one’s own efficacy and on the positive aspects of the situation. The dimensions thus reflect considerable
diversity in coping methods. As a broader philosophical point, the measure focuses on the absence of pathologi-
cal coping strategies rather than the presence of functional coping strategies. Other measures of coping take a330 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
more balanced approach to include both adaptive and maladaptive coping strategies (e.g., Ways of Coping
Questionnaire; Folkman & Lazarus, 1988 and the COPE Inventory; Carver et al., 1989 ).
It should be further noted that the MCI until recently had only been validated in German samples (see
Schwarzer & Schwarzer, 1996 ).Krohne et al. (2000) have reported on the construction and validation of an
English version of the MCI, demonstrating it has acceptable reliability and validity in terms of the factorial struc-
ture. To-date, however, limited research has been conducted with the English version of the MCI.
MAINZ COPING INVENTORY
Ego Threat Subtest
1.Speech: Imagine that you have to make a speech to a
group of people (i.e., participants of a course or
seminar, parents at a meeting at their children’s
school) in about 1 hour.
2.Exam: Imagine that you will have an important
examination the next morning.
3.Job interview: Imagine that you applied for a job and
that, in a few minutes, your application interview
will start.
4.Mistake on the job: Imagine that you have made a
mistake on the job which shouldn’t have happened
and that you are to have a talk with your boss.
Physical Threat Subtest
1.Dentist: Imagine that you haven’t been to the dentist
for quite a long time. You are now sitting in his
waiting room because you are having problems with
your teeth.2.Group of people: Imagine that you are walking along
through town in the late evening. A group of
people, who look suspicious, approach you out of
a side street.
3.Inexperienced driver: Imagine that you are a front
seat passenger next to an obviously inexperienced
driver. Road conditions are poor due to snow
and ice.
4.Turbulent flight: Imagine that you are sitting in an
airplane. The flight has been turbulent for quite a
while now, and the ‘No Smoking’ and ‘Fasten Seat
Belts’ signs have lit up.
Source :Krohne et al. (2000) . The assessment of dispo-
sitional vigilance and cognitive avoidance: Factorial
structure, psychometric properties, and validity of
the Mainz Coping Inventory. Cognitive Therapy &
Research, 24 , 297/C0311.
Reprinted with permission from Springer Science and
Business Media.
COPING REACTIONS FOR THE THREAT SCENARIO
‘PUBLIC SPEECH’
Imagine that you have to make a speech to a group
of people (i.e. participants of a course or seminar, par-
ents at a meeting at their children’s school) in about one
hour.
In this situation ...
1.I carefully review the topics I’m going to present.
2.I tell myself: ‘Everything will go well.’
3.I don’t think about the speech any more.
4.I think about what I can do if I lose track of what I
wanted to say.
5.I’m considerably more stressed than most people
I know.
6.I prefer to talk with friends about something other
than the speech.7.I think about what questions might be asked after
the speech.
8.I stay completely calm.
9.I remember the advice of people who already had to
make a similar speech.
10.I tell myself: ‘I’ve been able to cope with situations
that were far more trying.’
Items No. 1, 4, 5, 7, and 9 indicate vigilant coping,
items 2, 3, 6, 8, and 10 indicate cognitive avoidance.
Source : Reprinted from Personality and Individual
Differences ,30(7), Krohne, H.W., Schmukle, S.C.,
Burns, L.R., Egloff, B., & Spielberger, C.D. The mea-
surement of coping in achievement situations: An
international comparison, 1225 /C01243. Copyright
(2001), with permission from Elsevier.331 TRAIT COPING MEASURES
III. EMOTION REGULATION |
COPING REACTIONS FOR THE THREAT SCENARIO
‘INEXPERIENCED DRIVER’
Imagine that you are riding in a car as a front-seat
passenger next to an obviously inexperienced driver.
Road conditions are poor due to snow and ice.
In this situation ...
1.I remember similar dangerous situations that I have
experienced in the past.
2.I tell myself: ‘Nothing terrible is going to happen.’
3.I am glad that I don’t lose my composure as easily
as most others.
4.I think: ‘I’m the one this always happens to.’
5.I tell myself: ‘Thank goodness, he’s not driving that
fast.’
6.I watch the driver carefully and try to tell in
advance when he is going to make a mistake.
7.I think that I don’t cope with this kind of situation
(for instance, by staying calm and relaxed) as well as
most of my acquaintances.
8.I just stop looking at the road and either think about
something else, or look at the scenery.
9.I stay completely calm.
10.I tell myself: ‘In future, I’ll only go on rides like this
if I myself am the driver, never again as a
passenger.’11.I‘d very much like to say: ‘Stop, I want to get out.’
12.I tell myself: ‘As a passenger, one often perceives
the driver’s way of driving as unsteady, whereas in
fact, the driver isn’t driving all that badly.’
13.I tell myself: ‘I’ve been able to cope with situations
that were far more trying than this one.’
14.‘I drive along with the driver’, i.e., I act as if I myself
were driving.
15.I think about everything that could go wrong.
16.I think: ‘Somehow this driver also has to have the
opportunity to practice driving when road
conditions are poor.’
17.I tell myself: ‘When one has fastened one’s seat belt
and is moreover driving so slowly, not too much
can go wrong.’
18.I think about what I should do if the car should start
to skid.
Source : Used with permission from Attention and
Avoidance by Heinz Walter Krohne, ISBN 0-88937-108-
3 and ISBN 3-8017-0664-8, Hogrefe & Huber
Publishers and Hogrefe, 1993. Copyright r1993
Hogrefe & Huber Publishers, Seattle, WA.
Coping Inventory for Stressful Situations (CISS)
(Endler & Parker, 1990, 1994 ).
Variable
The CISS is a dispositional measure of coping style.
Description
The CISS was developed as an alternative to other coping measures that suffered from poor psychometric
properties and consequently underwent rigorous empirical development and testing. The CISS is a 48-item
instrument comprised of three 16-item subscales measuring task-oriented coping, emotion-oriented coping, and
avoidance-oriented coping. Individuals indicate the extent to which they engage in these various coping strate-
gies when encountering a difficult, stressful, or upsetting situation.
Although the CISS was developed as a dispositional measure of coping, a modified situational measure was
developed by Endler and Parker (1994) . The CISS Situation-Specific Coping (CISS-SSC) is a 21-item instrument
with three 7-item subscales measuring task-oriented, emotion-oriented, and avoidance-oriented coping. Instead
of reporting how they normally react in stressful situations, in the CISS-SSC, individuals focus on a particular
stressful event and answer the items as they relate to that particular event.
Sample
The CISS was normed on a sample of 559 undergraduate students (Endler & Parker, 1990). The mean for task-
oriented coping was 3.53 ( SD50.57) for men and 3.54 ( SD50.63) for women; the mean for emotion-oriented cop-
ing was 2.85 ( SD50.65) for men and 3.20 ( SD50.73) for women; and the mean for avoidance-oriented coping
was 2.75 ( SD50.64) for men and 3.08 ( SD50.70) for women. The CISS-SSC was normed on 432 undergraduate
students ( Endler & Parker, 1994 ). Means and standard deviations for the CISS-SSC were omitted from the paper.332 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
Reliability
Internal Consistency
The CISS exhibited Cronbach alpha coefficients for task-oriented coping of .88 for men and .91 for women;
emotion-oriented coping alpha coefficients were .76 for men and .81 for women; and avoidance-oriented coping
alpha coefficients were .77 for men and .83 for women (Endler & Parker, 1990). The CISS-SSC produced similarly
consistent scales, with alpha coefficients of .78 for men and .78 for women on task-oriented coping, .83 for men and
.84 for women on emotion-oriented coping, and .70 for men and .80 for women on avoidance-oriented coping.
Test/C0Retest
Test/C0retest reliability statistics were moderate over eight weeks ( Endler & Parker, 1994 ). The three subscales
yielded test /C0retest reliabilities of .74, .66, and .68 for task-oriented, emotion-oriented, and avoidance-oriented
coping, respectively. Later tests by Endler and Parker (1994) confirmed the consistency of these psychometric
findings in new samples. Test /C0retest reliability over 12 weeks was found to be poor to moderate by other
researchers, however (.58 to .62; Rafnsson, Smari, Windle, Mears, & Endler, 2006 ).
Validity
Convergent/Concurrent
The CISS showed acceptable convergent validity in tests that compared the measure with the Ways of Coping
Questionnaire (WCQ; Folkman & Lazarus, 1988 ) and the Coping Strategy Indicator (CSI; Amirkhan, 1990 , both
measures reviewed later in this chapter). The CISS task-oriented coping subscale correlated strongly and posi-
tively with the WCQ and CSI problem-focused subscales ( r5.67 and .50, respectively; Endler & Parker, 1990;
Endler & Parker, 1994 ).
Subscales in the CISS also correlate in expected ways with relevant personality traits. For example, Cosway,
Endler, Sadler, and Deary (2007) found task-oriented coping was positively associated with extraversion ( r5.24),
while emotion-oriented coping was positively associated with neuroticism ( r5.63). In addition to these patterns,
task-oriented coping was positively associated ( r5.35) with conscientiousness, a personality trait that is associ-
ated with thoroughness, efficiency, and task-focused action.
Divergent/Discriminant
Cosway et al. (2007) found that emotion-oriented and avoidance coping were unrelated to problem-focused
subscales of the WCQ and CSI. They also found that task-oriented coping was negatively associated with neuroti-
cism ( r52.23), and emotion-oriented coping was negatively associated with extraversion ( r52.26) and consci-
entiousness ( r52.32). All three coping subscales tended to be uncorrelated with psychoticism, suggesting good
discriminant validity (Endler & Parker, 1990).
Construct/Factor Analytic
Construct validity of the CISS was established in Endler and Parker’s (1994) original assessment. In this study,
832 college students and 483 adult community members completed the CISS, and a principal components analy-
sis was conducted to determine the CISS structure. In both samples, there was support for a three-component
structure. The task-oriented items loaded uniquely on one component, the emotion-focused items uniquely on
another component, and with the exception of two items in the adult community sample, the avoidance items
loaded uniquely on a third component. This structure has since been replicated in a range of other populations,
including health professionals ( Cosway et al., 2007 ) and patients with major depressive disorder ( McWilliams,
Cox, & Enns, 2003 ).
Criterion/Predictive
In initial tests by Endler and Parker (1990), emotion-oriented coping was found to covary positively with a
number of disorders of emotion regulation, including depression and anxiety in both men ( r5.43 and .49) and
women ( r5.55 and .51). Task-oriented coping was negatively associated with these disorders in women
(r52.34 and 2.45), while avoidance-oriented coping was positively associated with depression and anxiety
among men ( r5.38 and .37).
More recently, Hurt et al. (2011) have found support for the validity of the CISS with patients suffering from
Parkinson’s disease. In support of the construct validity, the authors demonstrated that the use of emotion-
focused coping was positively associated with depression ( r5.45) and anxiety ( r5.65). In addition, avoidance333 TRAIT COPING MEASURES
III. EMOTION REGULATION |
coping was positively correlated with anxiety ( r5.12), replicating the findings among men in Endler and
Parker’s (1990) original analysis. In contrast, task-orientated coping was negatively associated with depression
(r52 .20) and anxiety ( r52 .12), replicating Endler and Parker’s findings among women.
Location
Endler, N., & Parker, J. (1990). Coping Inventory for Stressful Situations (CISS): Manual . Toronto: Multi-Health
Systems.
Results and Comments
Overall, research using the CISS supports the notion that task-oriented coping is associated with greater well-
being and positive adjustment to stress, while emotion-oriented and avoidance-oriented coping tend to be associ-
ated with greater distress and maladaptive adjustment. These associations have been found across a wide variety
of stressful circumstances, including among people coping with academic worries ( Zeidner, 1994 ), eating disor-
ders (Koff & Sangani, 1998), chronic disease (Hurt et al., 2011), desire to quit smoking ( Naquin & Gilbert, 1996 ),
and insomnia ( Morin, Rodrigue, & Ivers, 2003 ).
The main strength of the CISS lies in its robust psychometric properties, rather than its theoretical novelty. The
factor structure has been replicated in an impressive array of populations ( Cosway et al., 2007; Furukawa,
Suzuki-Moor, & Hamanaka, 1993 ; Hurt et al., 2011; McWilliams et al., 2003; Pedrabissi & Santinello, 1994;
Rafnsson et al., 2006 ), yet the instrument is not as widely used as some others in the field. The CISS was devel-
oped mainly from items adopted from previous instruments, and echoes the basic dimensions of other measures
(e.g., Folkman & Lazarus, 1980 ). As a result, the measure has gained less traction in the literature than might
have been expected based on its impressive psychometric pedigree.
COPING INVENTORY FOR STRESSFUL SITUATIONS
(SAMPLE ITEMS)
Task Coping
Schedule my time better
Think about how I solved similar problems
Analyze the problem before reacting
Come up with several different solutions
to the problem
Emotion Coping
Preoccupied with aches and pains
Tell myself that it is not really happening to me
Blame myself for not knowing what to do
Worry about what I am going to doAvoidance Coping
Go out for a snack or meal
Watch TV
Try to be with other people
Phone a friend
Source : Endler, N.S., & Parker, J.D.A. (1994).
Assessment of multidimensional coping: Task, emo-
tion, and avoidance strategies. Psychological
Assessment, 6 ,5 0/C060.
Copyright r1994 by the American Psychological
Association. Reproduced with permission.
COPE Inventory (COPE)
(Carver et al., 1989 ).
Variable
The COPE is a measure of dispositional tendencies to adopt particular coping styles.
Description
Carver et al. (1989) constructed the COPE to assess stable individual differences in coping, partly in reaction to
claims by Folkman and Lazarus (1980, 1985) ;Lazarus & Folkman, 1984 that coping is a dynamic and malleable
process. The authors argued that it was important to consider the personality characteristics that might predis-
pose individuals towards a particular way of coping with stress.334 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
The COPE is a 60-item measure comprising 15 subscales with 4 items each. The subscales are planning, active
coping, suppression of competing activities, restraint, use of instrumental support, use of emotional support, pos-
itive reinterpretation and growth, acceptance, religious coping, focusing on and venting emotions, denial, behav-
ioral disengagement, mental disengagement, substance use, and humor. Individuals are asked to indicate the
extent to which they use these coping strategies when encountering difficult or stressful events in their lives. Like
the CISS, a situational version of the COPE Inventory was developed by rewording the instructions so that parti-
cipants think about a particular event when answering the items. A brief 28-item version of the scale is also avail-
able ( Carver, 1997; Kapsou, Panayiotou, Kokkinos, & Demetriou, 2010 ).
Sample
The COPE Inventory was normed on 978 undergraduate students ( Carver et al., 1989 ). The means and stan-
dard deviations for the subscales are shown below. The brief COPE was assessed using a sample of 168 hurricane
victims ( Carver, 1997 ).
MEANS AND STANDARD DEVIATIONS FOR THE COPE INVENTORY
MS D
1.Active coping 11.89 2.26
2.Planning 12.58 2.66
3.Suppression of competing activities 9.92 2.42
4.Restraint coping 10.28 2.53
5.Instrumental social support 11.50 2.88
6.Emotional social support 11.01 3.46
7.Positive reinterpretation 12.40 2.42
8.Acceptance 11.84 2.56
9.Turning to religion 8.82 4.10
10.Focus on and venting emotions 10.17 3.08
11.Denial 6.07 2.37
12.Behavioral disengagement 6.11 2.07
13.Mental disengagement 9.66 2.46
14.Alcohol disengagement 1.38 0.75
Note: Range of possible values is 4 /C016 (except for alcohol disengagement which ranges from 1 /C04). The humor
subscale is omitted because it was added in a later version of the instrument ( Carver et al., 1989 , p. 280).
Reliability
Internal Consistency
The dispositional COPE Inventory exhibited Cronbach alpha coefficients ranging from .45 (Mental disengage-
ment) to .92 (Turning to religion) in the large sample of 978 undergraduates ( Carver et al., 1989 ).
Test/C0Retest
Test/C0retest reliability over 6- and 8-week intervals yielded correlations higher than .42 (mental disengagement;
Carver et al., 1989 ). Other researchers found acceptable test /C0retest reliability over four weeks (ranging from .60 to .82;
Fillion, Kovacs, Gagnon, & Endler, 2002 ) and one year (ranging from .58 to .72; Cooper, Katona, & Livingston, 2008 ).
Validity
Convergent/Concurrent
Based on their reasoning that the COPE measured stable individual differences in coping, Carver et al. (1989)
tested the associations between COPE subscales and personality traits that they hypothesized would covary. The335 TRAIT COPING MEASURES
III. EMOTION REGULATION |
authors demonstrated predicted positive associations between ‘desirable’ coping strategies and ‘desirable’ per-
sonality traits (e.g., active coping and optimism, r5.32, planning and self-esteem, r5.22, positive reinterpreta-
tion and optimism, r5.41), Clark, Bormann, Cropanzano, and James (1995) provided evidence that the COPE
subscales correlated as expected with corresponding subscales in the CSI ( Amirkhan, 1990 ; e.g. COPE active cop-
ing, planning, and suppression of competing activities and CSI problem-solving, r5.69, COPE mental disengage-
ment and CSI avoidance, r5.89) and WCQ ( Folkman & Lazarus, 1988 ; e.g. WCQ seeking social support and
COPE seeking instrumental and social support, r5.86).
Divergent/Discriminant
As evidence of discriminant validity, many of the COPE subscales were uncorrelated with social desirability
(Carver et al., 1989 ) and the more adaptive coping strategies showed inverse associations with ‘undesirable’ traits
(e.g., active coping and anxiety, r52.25).
Construct/Factor Analytic
Carver et al. (1989) initially found evidence for an 11-factor structure, with the active coping and planning sub-
scales loading on one factor. The authors subsequently separated these scales on theoretical grounds. Cook and
Heppner (1997) found both 12-factor and 14-factor solutions, although the confirmatory factor analysis fit indices
for the 14-factor solution were slightly better. Lyne and Roger (2000) found that 11-, 12-, and 13-factor solutions
fit the data equally well, and reported that a high number of items loaded on more than one factor at over .40.
The most robust subscales in their analysis were seeking social support, personal growth, planning and active
coping, turning to religion, venting, denial, and behavioral disengagement. Based on the observation that the
COPE structure was highly unstable, Lyne and Roger (2000) suggested a new scoring key that reduces the scale
to three factors labeled (1) rational or active coping; (2) emotion coping; and (3) avoidance coping or
helplessness.
Criterion/Predictive
In an analysis that compared the COPE with the CSI ( Amirkhan, 1990 ) and WCQ ( Folkman & Lazarus, 1988 ),
Clark et al. (1995) demonstrated that the COPE Inventory explained the most variance in relevant outcome mea-
sures such as physical stress symptoms (35%, versus 22% for WCQ and 14% for CSI), life satisfaction (30% vs.
26% for WCQ and 15% for CSI), positive affect (41% vs. 28% for WCQ and 15% for CSI) and negative affect (40%
vs. 33% for WCQ and 23% for CSI).
In general, problem-focused coping subscales such as active coping and planning are found to predict positive
social and well-being outcomes, including more functional attachment styles ( Cooper et al., 2008 ), fewer symp-
toms of psychological distress ( Khawaja, 2008 ), more physical and psychological well-being at work ( Muhonen &
Torkelson, 2011 ), and an absence of anxiety and depression ( Fillion et al., 2002 ). The relationship between
emotion-focused subscales such as seeking emotional support from close others, and mental health outcomes is
less clear. Often using emotional support is associated with more problematic mental states, including anxiety
and depression ( Fillion et al., 2002; Khawaja, 2008 ), although this is likely reflective of individuals’ attempts to
improve their mental state, rather than a negative mental health outcome of using emotional support.
Location
Carver, C.S., Scheier, M.F., & Weintraub, J.K. (1989). Assessing coping strategies: A theoretically based
approach. Journal of Personality and Social Psychology, 56 , 267/C0283. doi:10.1037/0022-3514.56.2.267.
Results and Comments
The COPE Inventory is one of the most widely used coping measures in the literature. The instrument has
been used to assess how people cope in a variety of stressful situations, ranging from the health domain (e.g., Antoni,
Esterling, Lutgendorf, Fletcher, & Schneiderman, 1995; Carver et al., 1993; Ironson et al., 1994; Mackay, Charles,
Kemp, & Heckhausen, 2011 ), to sporting activity (e.g., Abrahamsen, Roberts, Pensgaard, & Ronglan, 2008 ;V o i g h t ,
2009), academic achievement (e.g., Carver et al., 1989; Thompson & Gaudreau, 2008 ), work stress (e.g., Muhonen &
Torkelson, 2011 ), and even missile attacks (e.g., Ben-Zur & Zeidner, 1991; Zeidner & Hammer, 1992 ). The COPE
Inventory has proven to be a useful and effective measure of dispositional coping styles.
The COPE taps more fine-grained, or specific forms of coping than other measures of coping styles (e.g., the
CISS), meaning that it may have greater practical utility ( Folkman & Moskowitz, 2004 ). A potential limitation of336 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
this specificity is that the output is 15 subscales, which makes for a somewhat cumbersome instrument. Some
researchers may find that this impedes its practical application in samples that are under time pressure (e.g., con-
venience sampling; some clinical groups). Fortunately, the brief COPE appears to be an adequate substitute for
the full COPE Inventory in such circumstances ( Carver, 1997 ).
BRIEF COPE INVENTORY
Instructions: We are interested in how people
respond when they confront difficult or stressful events
in their lives. There are lots of ways to try to deal with
stress. This questionnaire asks you to indicate what you
generally do and feel, when you experience stressful
events. Obviously, different events bring out somewhat
different responses, but think about what you usually
do when you are under a lot of stress.
15I usually don’t do this at all
25I usually do this a little bit
35I usually do this a medium amount
45I usually do this a lot
Active coping
I take additional action to try to get rid of
the problem.
I concentrate my efforts on doing something
about it.
I do what has to be done, one step at a time.
I take direct action to get around the problem.
Planning
I try to come up with a strategy about what to do.
I make a plan of action.
I think hard about what steps to take.
I think about how I might best handle
the problem.
Suppression of competing activities
I put aside other activities in order to concentrate
on this.
I focus on dealing with this problem, and if
necessary let other things slide a little.
I keep myself from getting distracted by other
thoughts or activities.
I try hard to prevent other things from interfering
with my efforts at dealing with this.
Restraint coping
I force myself to wait for the right time to
do something.
I hold off doing anything about it until the
situation permits.
I make sure not to make matters worse by acting
too soon.
I restrain myself from doing anything too quickly.
Seeking social support for instrumental reasons
I ask people who have had similar experiences
what they did.
I try to get advice from someone about what to do.I talk to someone to find out more about
the situation.
I talk to someone who could do something
concrete about the problem.
Seeking social support for emotional reasons
I talk to someone about how I feel.
I try to get emotional support from friends
or relatives.
I discuss my feelings with someone.
I get sympathy and understanding from someone.
Positive reinterpretation and growth
I look for something good in what is happening.
I try to see it in a different light, to make it seem
more positive.
I learn something from the experience.
I try to grow as a person as a result
of the experience.
Acceptance
I learn to live with it.
I accept that this has happening and that it can’t
be changed.
I get used to the idea that it happened.
I accept the reality of the fact that it happened.
Turning to religion
I seek God’s help.
I put my trust in God.
I try to find comfort in my religion.
I pray more than usual.
Focus on and venting of emotions
I get upset and let my emotions out.
I let my feelings out.
I feel a lot of emotional distress and
I find myself expressing those feelings a lot.
I get upset, and am really aware of it.
Denial
I refuse to believe that it has happened.
I pretend that it hasn’t really happened.
I act as though it hasn’t even happened.
I say to myself ‘this isn’t real.’
Behavioral disengagement
I give up the attempt to get what I want.
I just give up trying to reach my goal.
I admit to myself that I can’t deal with it,
and quit trying.
I reduce the amount of effort I’m putting into
solving the problem.337 TRAIT COPING MEASURES
III. EMOTION REGULATION |
Mental disengagement
I turn to work or other substitute activities to take
my mind off things.
I go to movies or watch TV, to think about it less.
I daydream about things other than this.
I sleep more than usual.
Alcohol /C0drug disengagement
I drink alcohol or take drugs, in order to think
about it less.Source : Carver, C.S., Scheier, M.F., & Weintraub, J.K.
(1989). Assessing coping strategies: A theoretically
based approach. Journal of Personality and Social
Psychology , 56, 267 /C0283.
Copyright r1989 by the American Psychological
Association. Reproduced with permission.
STATE COPING MEASURES
Coping Strategy Indicator (CSI)
(Amirkhan, 1990 ).
Variable
The CSI measures coping responses to a specific stressful event.
Description
Amirkhan (1990) constructed the CSI using a bottom-up method of taking items from previous research and
submitting them to a principal-factor analysis. The CSI is a situational measure of coping because it asks indivi-
duals to recall a problem that was important and caused them to worry. Individuals then indicate the extent to
which they used 33 coping strategies while dealing with the problem. The CSI consists of three subscales of 11
items each: problem-solving, seeking social support, and avoidance.
Sample
The CSI was developed by soliciting responses from 458 community members who were recruited at super-
markets, health clinics, and unemployment agencies. The psychometric properties were tested in a sample of 92
undergraduate student sample ( Amirkhan, 1990 ). Information about means and standard deviations was not
available from the original paper.
Reliability
Internal Consistency
Amirkhan (1990) reported Cronbach alpha coefficients of .93 for seeking support, .89 for problem solving, and
.84 for avoidance.
Test/C0Retest
Amirkhan (1990) also reported that test /C0retest reliability up to four and eight weeks later was .82 for a sample
of 92 community members and .81 among 87 undergraduate students.
Validity
Convergent/Concurrent
Amirkhan (1990) reported that the CSI correlated as expected with counterpart subscales from the WCQ
(Folkman & Lazarus, 1988 ) using revised scales by Vitaliano, Russo, Carr, Maiuro, and Becker (1985) . In particu-
lar, CSI problem solving correlated highly and positively with WCQ problem-focused coping ( r5.56), as did CSI
avoidance and WCQ avoidance ( r5.55), and did CSI social support and WCQ social support ( r5.46). Somewhat
surprisingly, WCQ social support was positively correlated more strongly with CSI problem solving ( r5.55)
than CSI seeking social support. This may have been due to the instrumental nature of the social support items
in the WCQ (e.g., ‘Talked to someone who could do things about the problem’).
Clark et al. (1995) found no correlation between the CSI seeking social support subscale and WCQ social sup-
port. The authors did report high correlations between other corresponding subscales (and null correlations338 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
between non-corresponding subscales) in the CSI, WCQ, and COPE Inventory, however. They concluded that the
scales tap similar constructs and are highly congruent.
Amirkhan (1994) assessed the convergent and discriminant validity of the CSI in three studies. Replicating a
procedure by Miller (1987) , participants who scored high on problem solving were most likely to choose to hear
information about an upcoming electric shock; participants who scored high on avoidance were most likely to
choose to hear distracting music; and participants who scored high on social support and avoidance were likely
to choose to talk to a confederate. In a second study, Amirkhan found that students scored higher in problem
solving after completing a critical thinking course compared with completing an introductory psychology course.
Finally, a substance abuse treatment program was evaluated and found to reduce avoidant coping and increase
seeking of social support.
Divergent/Discriminant
In the study by Amirkhan (1994) outlined above, participants who scored high on problem solving were not
likely to seek distraction or support, participants who scored high on avoidance were not likely to seek informa-
tion, and participants who scored high on social support and avoidance were not likely to seek information or
distraction.
Construct/Factor Analytic
Generally, researchers have replicated the 3-factor structure described by Amirkhan (1990) .Ager and
MacLachlan (1998) had 415 Malawian students complete the CSI, and found, using an exploratory factor analysis,
that a three-factor solution explained the data. Desmond, Shevlin, and MacLachlan (2006) had 618 elderly veter-
ans with acquired limb amputations complete the CSI and using confirmatory factor analysis, showed accepted
fit for a three-factor model. However, these researchers have argued that a 4-factor structure distinguishing
between two types of avoidance coping fits the data best (i.e., support seeking, problem solving, avoidance dis-
traction, and avoidance-withdrawal). Both Ager and MacLachlan (1998) andDesmond et al. (2006) demonstrated
that four-factor model had significantly better fit to the data than a three-factor model. Some researchers have
even suggested that an 8-factor model is the most appropriate based on confirmatory factor analysis goodness-of-
fit indices ( Cook & Heppner, 1997 ).
Criterion/Predictive
In general, avoidance is the subscale most commonly predictive of negative mental health outcomes.
Avoidance coping was associated with general stress in college samples ( Amirkhan, Risinger, & Swickert, 1995 ),
and with depression, anxiety, and poor marital adjustment in at-risk patients suffering from a major depressive
disorder ( Spangenber & Theron, 2010 ). Neither problem solving nor seeking social support were associated with
mental health outcomes in these samples.
Location
Desmond, D., Shevlin, M., & MacLachlan, M. (2006). Dimensional analysis of the coping strategy indicator in a
sample of elderly veterans with acquired limb amputations. Personality and Individual Differences, 40 , 249/C0259.
doi: 10.1016/j.paid.2005.04.015.
Results and Comments
Given that the CSI is a situational measure of coping, it can be applied to assess coping in a wide variety of con-
texts. For example, the CSI has been used to investigate how people cope with physical disability (e.g., Kara &
Acikel, 2011 ), alcohol dependence (Campbell & Spangenberg, 2008), partner violence (e.g., Sullivan,
Ashare, Jaquier, & Tennen, 2012 ), spousal bereavement ( Somhlaba & Wait, 2008 ), and dementia caregiving (e.g.,
Ashley & Kleinpeter, 2002 ). Overall, problem solving and social support are associated with positive outcomes and
increased well-being, while use of avoidance coping strategies tend to be associated with pathology and
dysfunction.
The CSI is a useful tool for assessing specific coping strategies. Yet, the measure has been criticized for com-
paratively poor goodness-of-fit statistics at the development stage, and some questionable correlations with other
established coping measures ( Schwarzer & Schwarzer, 1996 ), as reviewed in the Validity section, above. The
range of coping strategies assessed in the CSI is also less than the other well-known situational coping instru-
ment, the Ways of Coping Questionnaire.339 STATE COPING MEASURES
III. EMOTION REGULATION |
COPING STRATEGY INDICATOR
CSI Item (Subscale)
1.Described your feelings to a friend (SS)
2.Rearranged things so your problem could be
solved (PS)
3.Thought of many ideas before deciding what
to do (PS)
4.Tried to distract yourself from the problem (A)
5.Accepted sympathy and understanding from
someone (SS)
6.Did all you could to keep others from seeing how
bad things really were (A)
7.Talked to people about the situation because talking
about it made you feel better (SS)
8.Set some goals for yourself to deal with the
situation (PS)
9.Weighed up your options carefully (PS)
10.Daydreamed about better times (A)
11.Tried different ways to solve the problem until you
found one that worked (PS)
12.Talked about fears and worries to a relative or
friend (SS)
13.Spent more time than usual alone (A)
14.Told people about the situation because talking
about it helped you come up with solutions (SS)
15.Thought about what needs to be done to straighten
things up (PS)
16.Turned your full attention to solving the
problem (PS)
17.Formed a plan in your mind (PS)
18.Watched television more than usual (A)
19.Went to someone friend or professional to help you
feel better (SS)
20.Stood firm and fought for what you wanted in the
situation (PS)
21.Avoided being with people in general (A)
22.Buried yourself in a hobby or sports activity to
avoid the problem (A)23.Went to a friend to help you feel better about the
problem (SS)
24.Went to a friend for advice about how to change the
situation (SS)
25.Accepted sympathy and understanding from friends
who had the same problem (SS)
26.Slept more than usual (A)
27.Fantasized about how things could have been
different (A)
28.Identified with characters in movies or novels (A)
29.Tried to solve the problem (PS)
30.Wished that people would just leave you alone (A)
31.Accepted help from a friend or relative (SS)
32.Sought reassurance from those who know you
best (SS)
33.Tried to carefully plan a course of action rather than
acting on impulse (PS)
Notes :
SS5Social Support; PS 5Problem Solving;
A5Avoidance.
Source :Desmond et al. (2006) . Reprinted from
Personality and Individual Differences, 40 (2 ), Desmond,
D.M., Shevlin, M., & MacLachlan, M. Dimensional
analysis of the coping strategy indicator in a sample
of elderly veterans with acquired limb amputations,
249/C0259. Copyright (2006), with permission from
Elsevier. Copyright r1990 by the American
Psychological Association.
Adapted with permission. No further reproduction or
distribution is permitted without written permission
from the American Psychological Association.
The official citation for the scale is: Amirkhan, J.H.
(1990) . A factor analytically derived measure of cop-
ing: The Coping Strategy Indicator. Journal of
Personality and Social Psychology, 59 , 1066/C01074.
Ways of Coping Questionnaire (WCQ)
(Folkman & Lazarus, 1988 ).
Variable
The Ways of Coping Questionnaire (WCQ) or Ways of Coping Checklist (WCC) is a situational measure of
coping strategies.
Description
Individuals focus on a real-life stressful situation and respond to the WCQ based on their responses to that
specific situation. The questionnaire consists of 66 items with eight coping scales and 16 filler items. In a student
sample, the subscales were problem-focused coping, wishful thinking, detachment, seeking social support,340 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
focusing on the positive, self-blame, tension reduction, and keep to self ( Folkman & Lazarus, 1985 ). In a commu-
nity sample of married couples, the scales were planful problem solving, positive reappraisal, escape /C0avoidance,
seeking social support, accepting responsibility, self-controlling, distancing, and confrontive coping ( Folkman,
Lazarus, Dunkel-Schetter, Delongis, & Gruen, 1986 ). The latter set is reported as the definitive set of subscales in
the WCQ manual ( Folkman & Lazarus, 1988 ).
Vitaliano et al. (1985) published a shorter, updated version of the scale called the Ways of Coping Checklist /C0
Revised (WCC-R). The scale comprised 42 items with five subscales: Problem-focused, seeks social support,
blamed self, wishful thinking, and avoidance.
Sample
The WCQ was first tested in a sample of 108 undergraduate students about to undergo a college examination
(Folkman & Lazarus, 1985 ). The means and standard deviations for each scale are contained below ( Folkman &
Lazarus, 1988 ).
MEANS AND STANDARD DEVIATIONS FOR WCQ SUBSCALES
MS D
1.Confrontive coping 3.94 2.09
2.Distancing 3.05 1.78
3.Self-controlling 5.77 2.87
4.Seeking social support 5.40 2.40
5.Accepting responsibility 1.87 1.44
6.Escape /C0Avoidance 3.18 2.48
7.Planful problem solving 7.25 2.34
8.Positive reappraisal 3.48 2.96
The WCC-R was first tested among a sample of 425 medical students ( Vitaliano et al., 1985 ). The means and
standard deviations for each scale are shown below.
MEANS AND STANDARD DEVIATIONS FOR WAYS OF COPING
CHECKLIST /C0REVISED SUBSCALES
MS D
1.Problem-focused 24.70 8.37
2.Wishful thinking 12.72 5.92
3.Seeks social support 8.87 3.69
4.Blamed self 4.35 2.48
5.Avoidance 12.82 5.37
Reliability
Internal Consistency
The WCQ coping scales exhibited Cronbach alpha coefficients ranging from .61 (distancing) to .79 (positive
reappraisal). The WCC-R scales overall exhibited slightly higher alpha coefficients ranging from .74 (avoidance)
to .88 (problem-focused).341 STATE COPING MEASURES
III. EMOTION REGULATION |
Test/C0Retest
Test/C0retest reliability of the WCQ was relatively poor over two weeks in surgical patients (ranging from .36 to
.52;Sørlie & Sexton, 2001 ) and over 4 years in parents of children with Down’s syndrome (ranging from .39 to
.89;Hatton, Knussen, Sloper, & Turner, 1995 ). However, it should be noted that Folkman and Lazarus (1988)
argued that it is inappropriate to consider the test /C0retest reliability of the WCQ because of the dynamic process
the measure is designed to capture. Individuals are expected to adjust their coping responses based on the spe-
cific situation, and the success or failure of particular strategies.
Validity
Folkman and Lazarus (1988) claimed evidence for convergent and discriminant validity in the fact that find-
ings with the WCQ were consistent with their theoretical predictions.
Convergent/Concurrent
Clark et al. (1995) provided further evidence for convergent validity by showing generally expected correla-
tions between the WCQ and comparable subscales from the COPE and CSI, reviewed elsewhere in this chapter.
Divergent/Discriminant
Problem-focused coping ( r52 .14) and seeking social support ( r52 .12) were significantly negatively related
to occupational stress while the other coping strategies (i.e., self-blame, wishful thinking, and avoidance) had
smaller relationships with occupational stress ( r52.02 to2.06)/C0(Clark et al., 1995 ).
Construct/Factor Analytic
Using a sample of 306 students and conducting confirmatory factor analysis, Clark et al. (1995) concluded that
the factor structure identified by Folkman et al. (1986) fit the data well. Among 137 employees, Wright (1990) dem-
onstrated support for the 7-factor structure of the measure as well as the Internal Consistency of the seven scales.
Vitaliano et al. (1985) examined the WCC-R, and found that a principal components analysis originally sup-
ported a six-component solution, although loadings on the items suggested that a five-component solution was
more parsimonious. Since the original Vitaliano et al. (1985) validation study, the WCC-R has been validated
using a confirmatory approach rather than an exploratory approach. In a large sample of full-time Asian employ-
ees, Sawang and colleagues (2010) found that a briefer, 5-factor structure model (i.e., problem-focused, seeks
social support, self-blame, wishful thinking, and avoidance) fit the data better.
Criterion/Predictive
The WCC-R subscales have been found to correlate with reports of occupational stress in a meaningful way
(Sawang et al., 2010 ). For instance this pattern of relationships indicates that coping strategies related to self-
blame, wishful thinking, and avoidance might not be as adaptive as problem-focused coping and seeking social
support for the work context.
In terms of mental health, the WCC-R predicted anxiety and depression in spouses of patients with senile
dementia, psychiatric outpatients, and medical students ( Vitaliano et al., 1985 ). Overall, wishful thinking and
seeking social support were the strongest predictors of anxiety, accounting for up to 14% and 15% of the vari-
ance, respectively. Wishful thinking was also a strong positive predictor of depression, accounting for up to 21%
of variance, as was problem-focused coping, which accounted for the same amount of variance (but was linked
with lower depression).
Folkman et al. (1986) found that the WCQ was a good predictor of mental well-being among married couples.
Coping as measured by the WCQ scales was found to be an excellent predictor of psychological health and only
a weak predictor of physical health. In a study with nurses, using the briefer WCC-R, Mark and Smith (2011)
found no relation between problem-focused coping and clinical anxiety scores, while escape/avoidance ( r5.34),
wishful thinking ( r5.34), and self-blame ( r5.48) were all significant predictors. There was a small, but signifi-
cant, negative correlation between problem-focused coping ( r52 .10) and depression scores, while self-blame
(r5.38) and wishful thinking ( r5.28) were significant positive predictors of depression.
Somewhat surprisingly, Bolger (1990) found that the WCQ did not predict concrete academic outcomes among
medical students, although certain subscales like wishful thinking predicted greater anxiety about exam perfor-
mance ( r5.36). In line with this, Wright and Sweeney (1989) found civil service employees experienced higher342 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
diastolic blood pressure when they used the coping strategies of wishful thinking and avoidance. The overall
power of the WCQ and WCC-R in predicting psychological outcomes, but limited evidence in predicting practi-
cal performance outcomes, suggests it is better used as a predictor of physical and psychological health than of
productivity. In addition, these findings indicate less frequent use of maladaptive coping strategies (e.g., wishful
thinking), as opposed to more frequent use of adaptive coping strategies (e.g., problem-focused coping), might
potentially have greater implications for psychological health.
Folkman and Lazarus (1985) found that the WCQ predicted responses to a stressful examination in a theoreti-
cally meaningful way. Students varied their coping style depending on the temporal distance from the exam,
measured two days before the exam, after the exam before the grades were posted, and again after the grades
were posted. Students showed greater use of problem-focused coping before the exam, distancing after the exam,
and wishful thinking, social support, and self-blame depending on the grade received.
Location
Folkman, S., Lazarus, R., Dunkel-Schetter, C., DeLongis, A., & Gruen, R. (1986). Dynamics of a stressful
encounter: Cognitive appraisal, coping, and encounter outcomes. Journal of Personality and Social Psychology, 50 ,
992/C01003. doi: 10.1037/0022-3514.50.5.992.
Vitaliano, P.P., Russo, J., Carr, J.E., Maiuro, R.D., & Becker, J. (1985). The ways of coping checklist: Revision
and psychometric properties. Multivariate Behavioral Research ,20,3/C026, doi: 10.1207/s15327906mbr2001_1.
Results and Comments
The WCQ and briefer WCC-R assesses a larger range of coping strategies than the CSI ( Amirkhan, 1990 ).
Given that both the WCQ and WCC-R measure situation-specific coping, the authors have encouraged research-
ers to adjust the wording of the items to reflect the study context. Consequently, the measures are highly
adaptable and useful to assess coping in a wide range of contexts. As a result, these questionnaires have been
employed to investigate coping with a wide variety of stressful situations in an impressive variety of populations,
including children (e.g., Horowitz, Boardman, & Redlener, 1994; Kuther & Fisher, 1998 ), adolescents (e.g., Chan,
1994; Puskar & Lamb, 1991 ), parents (e.g., Hatton et al., 1995; Murphy, Flowers, McNamara, & Young-Saleme,
2008; Vidyasagar & Koshy, 2010 ), working adults (e.g., Sawang et al., 2010; Scherer & Brodzinski, 1990 ), clinical
samples (e.g., Hamilton, Stewart, Crandell, & Lynn, 2009; Lysaker, Davis, Lightfoot, Hunter, & Stasburger, 2005;
Siegel, Schrimschaw, & Pretter, 2005 ), and older adults (e.g., Drozdick & Edelstein, 2001; Lowis, Jewell, Jackson, &
Merchant, 2011 ).
The WCQ and WCC-R have been translated into other languages and validated. A Farsi version of the WCQ,
tested on Iranian adults, has also been validated finding a similar 7-factor structure to what Folkman et al. origi-
nally identified ( Padyab, Ghazinour, & Richter, 2012 ). The psychometric properties of the WCQ also have been
validated in a Turkish community and student sample (Senol-Durak et al., 2012). In addition, a French validation
has been conducted on the WCC-R, finding some support for the 5-factor structure but also support for a 3-factor
structure of seeking social support, avoidance/self-blame, and problem-solving ( Cousson, Bruchon-Schweitzer,
Quintard, & Nuissier, 1996; Cousson-Gelie et al., 2010 ). More recently, a Spanish validation of the WCC-R was
conducted and also found support for the reliability of the scales as well as the 5-factor structure ( Mayo, Real,
Taboada, Iglesias-Souto, & Dosil, 2012 ).
WAYS OF COPING (SAMPLE ITEMS)
Instruction: To respond to the statements in this ques-
tionnaire, you must have a spec ific stressful situation in
mind. Take a few moments and think about the most stress-
ful situation that you have experienced in the past week.
As you respond to each of the statements, please
keep this stressful situation in mind. Read each state-
ment carefully and indicate, by circling 0, 1, 2 or 3, to
what extent you used it in the situation.05Does not apply or not used
15Used somewhat
25Used quite a bit
35Used a great deal
Planful Problem Solving
Just concentrated on what I had to do next /C0the
next step.
I made a plan of action and followed it.343 STATE COPING MEASURES
III. EMOTION REGULATION |
Confrontive Coping
I did something which I didn’t think would work,
but at least I was doing something.
Tried to get the person responsible to change his
or her mind.
Distancing
Made light of the situation; refused to get too
serious about it.
Went on as if nothing had happened.
Self-Controlling
I tried to keep my feelings to myself.
Kept others from knowing how
bad things were.
Seeking Social Support
Talked to someone to find out more about
the situation.
Talked to someone who could do something
concrete about the problem.Accepting Responsibility
Criticized or lectured myself.
Realized I brought the problem on myself.
Escape /C0Avoidance
Wished that the situation would go away or
somehow be over with.
Hoped a miracle would happen.
Positive Reappraisal
Changed or grew as a person in a good way.
I came out of the experience better than when I
went in.
Source : Folkman, S., Lazarus, R.S., Dunkel-Schetter,
C., DeLongis, A., & Gruen, R.J. (1986). Dynamics of a
stressful encounter: Cognitive appraisal, coping, and
encounter outcomes. Journal of Personality and Social
Psychology ,50, 992/C01003.
Copyright r1986 by the American Psychological
Association. Adapted with permission.
FUTURE RESEARCH DIRECTIONS
The effectiveness of a given coping strategy depends on a complex interplay of people’s appraisals, coping
resources, and specific features of the environment. This complexity makes it difficult to capture the full variation
in coping in one measure, leading some researchers to conclude that, ‘the measurement of coping is probably as
much art as it is science’ ( Folkman & Moskowitz, 2004 , p. 751). The structure of coping has dominated the
approach towards its measurement. It is difficult to establish a consistent structure across the diverse contexts in
which coping occurs (see Folkman & Moskowitz, 2004 ; Skinner, 2003).
Despite the challenges posed by the multidimensional na ture of the coping process, improvements can still be made
in the measurement of coping. Parker and Endler (2006) recently identified two main problems. First, the proliferation
of coping scales has made it difficult to observe meaningful a nd consistent coping patterns across different populations
or stressors. Second, coping research should be limited to usin g only the most psychometrically rigorous scales to pro-
cure valid and generalizable information about coping beh avior. We have attempted to follow these guidelines, and
chose to highlight only a few key coping scales to meet the challenge set out by Parker and Endler (2006) .
Another challenge is the length of coping questionnaires, which has limited published studies where the com-
plete instrument is used (and therefore validated). This is especially the case for some participant groups (e.g.,
employees, some clinical samples). Indeed, most validation studies reported here were conducted using student
samples. The lengthiness of coping instruments has resulted in many researchers only selecting the specific
‘ways of coping’ that interest them, or is relevant to the specific stressor or context under investigation.
Skinner’s (2003) review on coping taxonomies highlighted that specific ‘ways of coping’ are potentially more
relevant and powerful predictors of outcomes, as opposed to broader ‘families of coping’. Skinner concluded that
focusing on the specific coping mechanism is more likely to unravel the complex processes of coping behavior as
these indicators will be more specific predictors of coping outcomes. Researchers should be selective in the
coping instruments they choose to administer and base their decision-making on the content of the measures; i.e.,
ensuring the specific ‘ways of coping’ are included in any measure, which are relevant to the phenomenon, con-
text, or sample under investigation. This might mean researchers select a smaller number of relevant subscales
from the instruments reviewed here.
Criticisms have been leveled at current coping instruments ( Folkman & Moskowitz, 2004; Parker & Endler, 2006 ).
One criticism is that most coping inventories, including the measures reviewed above, involve responding either to
hypothetical scenarios or recalling past coping experiences (Coyne & Gottlieb, 1996; Porter & Stone, 1996; Steptoe, 1989 ).
Both these procedures fail to assess actual ‘in-the-moment ’ coping. An alternative method of measurement is to use
experience sampling to assess ‘real time’ attempts at self-regulation and coping ( Hofmann, Vohs, & Baumeister, 2012 ).344 12. MEASURES OF COPING FOR PSYCHOLOGICAL WELL-BEING
III. EMOTION REGULATION |
Stone and Neal (1984) constructed the Daily Coping Inv entory to reduce recall inaccuracy in coping reports.
The instrument is completed at the same time each day wi th respondents ask ed to report their reactions to the
most bothersome event of the day. This method of assessm ent correlates moderately with recall procedures /C0
between .47 and .58 ( Ptacek, Smith, Espe, & Raffety, 1994 ). Such experience sampling-type measures may
change the way people respond to stressors, alerting them to alternative functional (or dysfunctional) ways of
coping.
Daily measures of coping may also act as self-regulation interventions in addition to measuring coping.
Indeed, counselors, consulting psyc hologists, and coaches have successfully used experience sampling techni-
ques as a tool for self-tracking and guided analysis with clients (see Foster & Lloyd, 2007 ). These techniques
are useful in practice, as the method prompts the respondent to record affect, coping, or any range of prede-
fined behaviors in real time. The technique can then be us ed to track the progress or effectiveness of any inter-
ventions that are implemented. The ma jor challenges of these approaches are (1) keeping measures brief and
easy to complete; and (2) capturing the right informatio n. Because these techniques are emergent, researchers
and practitioners alike should draw on the validity evidence presented here when devising coping items for
experience sampling.
A relatively new development has been an emerging focus on future-oriented proactive coping ( Folkman &
Moskowitz, 2004 ). The majority of coping measures focus on how people coped with past stressful events. This
model considers coping as a process that occurs after the onset of a stressful event, and positions individuals as
reactive rather than proactive agents in crafting their coping response. An alternative model is to consider how
people cope in anticipation of a stressful event to avert or minimize its impact ( Aspinwall & Taylor, 1997;
Greenglass, Schwarzer, & Taubert, 1999; Schwarzer & Knoll, 2003; Sohl & Moyer, 2009 ).
This perspective overlaps with emotion regulation research more generally. Gross’s (1998, 2002) model of emo-
tion regulation views emotion as an unfolding process. Emotion regulation reflects both attempts to avoid or
lessen negative emotions as well as attempts to foster or heighten positive emotions. Stressful events or episodes
may trigger an unfolding emotional experience ( Folkman & Moskowitz, 2004 ), which people can attempt to avoid
or reduce by using antecedent-focused emotion regulation strategies (i.e., situation selection, situation modifica-
tion, attention deployment, cognitive reappraisal). Once the emotional experience is ‘full blown’ individuals can
attempt to regulate emotions via response modulation (i.e., attempts at managing physiological, affective, and
behavioral reactions). Coping research too can benefit from an understanding of the preventive steps people take
to avoid or mitigate the experience of future negative emotions associated with stress, as well as reactive coping
responses after a stressful event has occurred.
Burgeoning research on proactive coping has found that it has considerable power for cultivating and main-
taining psychological well-being. Sohl and Moyer (2009) concluded that proactive coping was particularly protec-
tive/C0resulting in enhanced positive affect and life satisfaction, and fewer stress-related physical symptoms /C0
when conceptualized as a positively-focused striving for goals ( Aspinwall & Taylor, 1997 ) rather than preven-
tion of negative outcomes ( Bode, de Ridder, Kuijer, & Bensing, 2007 ). The results demonstrated that aspiring
for a positive future is distinctly predictive of well-being and suggests that research should focus on accumu-
lating resources and goal setting in designing i nterventions to promote proactive coping. Sohl and Moyer’s
(2009) work further suggests that inter esting overlaps may exist betwee n proactive coping and promotion
regulatory focus ( Higgins, 1997 ) that could combine to predict an optima l level of positive goal engagement in
stressful situations.
Finally, integrating research into the measuremen t of coping with assessments of self-regulation and
emotion-regulation more generally would seem desirable. Just as assessing the interplay between disposi-
tional coping styles and situational coping strategies may provide a more nuanced understanding of coping
behavior, so too may including the asses sment of state or trait regulatory capacities. Specific coping strategies
d i f f e ri nt h ed e g r e et ow h i c ht h e yr e q u i re self-regulatory resources. For example, interacting directly with a
stressor via problem-focused coping strategies may take more willpower than engaging in distraction or
avoidance. People who are dispositionally low in self-regulation ability may therefore be more likely to be
unsuccessful in certain coping efforts, and consequently more predisposed toward using particular coping
strategies over others.
In summary, this chapter provides a theoretical and m ethodological outline of the assessment of coping.
Six widely-used coping measures were reviewed and c r i t i q u e d .W eh o p et oh a v ep rovided a comprehensive
reference for scholars interested in assessing success ful coping and its implications for psychological
well-being.345 FUTURE RESEARCH DIRECTIONS
III. EMOTION REGULATION |
APPENDIX: SUBSCALES FOR THE SIX COPING MEASURES
REVIEWED IN THIS CHAPTER
Miller Behavioral Style Scale ( Miller, 1987 )
1.Monitoring
2.Blunting
Mainz Coping Inventory ( Krohne et al.,
2000 )
1.Vigilance
2.Cognitive avoidance
Coping Inventory for Stressful Situations
(Endler & Parker, 1990)
1.Task-oriented coping
2.Emotion-oriented coping
3.Avoidance-oriented coping
COPE Inventory ( Carver et al., 1989 )
1.Active coping
2.Planning
3.Suppression of competing activities
4.Restraint coping
5.Instrumental social support
6.Emotional social support
7.Positive reinterpretation8.Acceptance
9.Turning to religion
10.Focus on and venting emotions
11.Denial
12.Behavioral disengagement
13.Mental disengagement
14.Alcohol disengagement
15.Humor
Coping Strategy Indicator ( Amirkhan, 1990 )
1.Problem solving
2.Seeking social support
3.Avoidance
Ways of Coping Questionnaire
(Folkman & Lazarus, 1988 )
1.Confrontive coping
2.Distancing
3.Self-controlling
4.Seeking social support
5.Accepting responsibility
6.Escape /C0avoidance
7.Planful problem solving
8.Positive reappraisal
Acknowledgements
Preparation of this paper was facilitated by an award to the lead author from the Canadian Institute for Advanced Research: Social
Interactions, Identity, and Well-being Program.
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Subsets and Splits