Full text of
Emotional Intelligence Meets Traditional Standards for an Intelligence
Emotional Intelligence Meets Traditional Standards for an Intelligence. JOHN D. MAYER; DAVID R. CARUSO; PETER SALOVEY.
Full Text: COPYRIGHT 1999 Ablex Publishing Corporation
Emotions are internal events that coordinate many psychological
subsystems including physiological responses, cognitions, and
conscious awareness. Emotions typically arise in response to a
person's changing relationships. When a person's relationship to
a memory, to his family, or to all of humanity changes, that
person's emotions will change as well. For example, a person who
recalls a happy childhood memory may find that the world appears
brighter and more joyous (e.g., Bower, 1981). Because emotions
track relationships in this sense, they convey meaning about
relationships (Schwarz & Clore, 1983). Emotional intelligence
refers to an ability to recognize the meanings of emotions and
their relationships, and to reason and problem-solve on the basis
of them. Emotional intelligence is involved in the capacity to
perceive emotions, assimilate emotion-related feelings,
understand the information of those emotions, and manage them
(Mayer & Salovey, 1997; Salovey & Mayer, 1990).
Emotional intelligence can be assessed most directly by asking a
person to solve emotional problems, such as identifying the
emotion in a story or painting, and then evaluating the person's
answer against criteria of accuracy (Mayer, DiPaolo, &
Salovey, 1990; Mayer & Geher, 1996). It is worth noting,
however, that emotional intelligence, as an ability, is often
measured in other ways. Some approaches have asked people their
personal, self-reported beliefs about their emotional
intelligence. Test items such as, "I'm in touch with my
emotions," or "I am a sensitive person," assess
such self-understanding (e.g., Mayer & Stevens, 1994;
Salovey, Mayer, Goldman, Turvey, & Palfai, 1995).
Self-reports of ability and actual ability, however, are only
minimally correlated in the realm of intelligence research (e.g.,
r = 0.20; Paulhus, Lysy, & Yik, 1998) and that appears to
hold in the area of emotional intelligence as well (Davies,
Stankov, & Roberts, 1998).(1) Self-concept is important, of
course, because people often act on their beliefs about their
abilities as opposed to their actual abilities (Bandura, 1977).
Emotional intelligence as a domain of human performance, however,
is best studied with ability measures.
Emotional intelligence has often been conceptualized
(particularly in popular literature) as involving much more than
ability at perceiving, assimilating, understanding, and managing
emotions. These alternative conceptions include not only emotion
and intelligence per se, but also motivation, non-ability
dispositions and traits, and global personal and social
functioning (e.g., Bar-On, 1997; Goleman, 1995). Such broadening
seems to undercut the utility of the terms under consideration.
We call these mixed conceptions because they combine together so
many diverse ideas. For example, the Bar-On Emotional Quotient
Inventory (E[Q.sub.i]) includes 15 self-report scales that
measure a person's self-regard, independence, problem solving,
reality-testing, and other attributes (Bar-On, 1997). Such
qualities as problem solving and reality testing seem more
closely related to ego strength or social competence than to
emotional intelligence. Mixed models must be analyzed carefully
so as to distinguish the concepts that are a part of emotional
intelligence from the concepts that are mixed in, or confounded,
with it.
General intelligence serves as an umbrella concept that includes
dozens of related groups of mental abilities. Most of the smaller
subskills studied in this century are related to verbal, spatial,
and related logical information processing (see Carroll, 1993,
for an authoritative review). Such processing is sometimes
referred to as "cold" to denote that its ego- or
self-involvement is minimal (Abelson, 1963; Mayer & Mitchell,
1998; Zajonc, 1980). Information processing, however, also deals
with "hot," self-related, emotional processing.
Emotional intelligence is a hot intelligence. It can be thought
of as one member of an emerging group of potential hot
intelligences that include social intelligence (Sternberg &
Smith, 1985; Thorndike, 1920), practical intelligence (Sternberg
& Caruso, 1985; Wagner & Sternberg, 1985), personal
intelligence (Gardner, 1993), non-verbal perception skills (Buck,
1984; Rosenthal, Hall, DiMatteo, Rogers, & Archer, 1979), and
emotional creativity (Averill & Nunley, 1992). Each of these
forgoing concepts forms coherent domains that partly overlap with
emotional intelligence, but that divide human abilities in
somewhat different ways.
The ability conception of emotional intelligence was developed in
a series of articles in the early 1990s (Mayer et al., 1990;
Mayer & Salovey, 1993; Salovey & Mayer, 1990). For
example, the first empirical study in the area demonstrated that
people's abilities to identify emotion in three types of stimuli:
colors, faces, and designs, could be accounted for by a single
ability factor--which we supposed was emotional intelligence
(Mayer et al., 1990). Another study examined the understanding of
emotion in stories (Mayer & Geher, 1996); this latter study
provided further indications that the underlying factor
"looked like" an intelligence. Simultaneous with this
empirical work, we have honed our definition of emotional
intelligence and the abilities involved (e.g., Mayer &
Salovey, 1997). The present article represents a culmination of
this work, testing our most highly developed conception of
emotional intelligence by operationalizing it according to 12
ability tests of emotional intelligence. The present study can
help answer important questions about emotional intelligence,
among them: whether emotional intelligence is a single ability or
many, and how it relates to traditional measures of general
intelligence and other criteria.
STANDARD CRITERIA FOR AN INTELLIGENCE
Three Criteria for an Intelligence
An intelligence such as emotional intelligence must meet
stringent criteria in order to be judged as a true intelligence.
For the purposes here, these criteria can be divided into three
fairly distinct groups: conceptual, correlational, and
developmental. The first, conceptual criteria, includes that
intelligence must reflect mental performance rather than simply
preferred ways of behaving, or a person's self-esteem, or
non-intellectual attainments (Carroll, 1993; Mayer & Salovey,
1993; Scarr, 1989); moreover, mental performance should plainly
measure the concept in question, i.e., emotion-related abilities.
The second, correlational criteria, describe empirical standards:
specifically, that an intelligence should describe a set of
closely related abilities that are similar to, but distinct from,
mental abilities described by already-established intelligences
(Carroll, 1993; Neisser et al., 1996).(2) The third,
developmental criterion, states that intelligence develops with
age and experience, and is based on the groundbreaking work by
Binet and Simon at the beginning of century (as reviewed in
Fancher, 1985, p. 71; see also, Brown, 1997). These three
criteria will be next examined in greater detail.
Conceptual Criteria for an Intelligence
We have argued elsewhere that emotional intelligence does indeed
describe actual abilities rather than preferred courses of
behavior. These four broad classes of abilities can be arranged
from lower, more molecular, skills to higher, more molar, skills,
as is done in Fig. 1 (Mayer & Salovey, 1993, 1997). The
lowest level skills involve the perception and appraisal of
emotion, e.g., in a facial expression or artwork. The next level
up involves assimilating basic emotional experiences into mental
life, including weighing emotions against one another and against
other sensations and thoughts, and allowing emotions to direct
attention. An example includes holding an emotional state in
consciousness long enough to compare its correspondences to
similar sensations in sound, color, and taste. The third level
involves understanding and reasoning about emotions. Each
emotion-happiness, anger, fear, and the like--follows its own
specific rules. Anger rises when justice is denied; fear often
changes to relief; sadness separates us from others. Each emotion
moves according to its own characteristic rules, like the
different pieces on a chessboard. Emotional intelligence involves
the ability to see the pieces, know how they move, and reason
about emotions accordingly. The fourth, highest level, involves
the management and regulation of emotion, such as knowing how to
calm down after feeling angry or being able to alleviate the
anxiety of another person. Tasks defining these four levels or
branches are described in greater detail in the section
concerning scale development below.
[Figure 1 ]
In considering tasks for an emotional intelligence test, how are
we to discriminate right from wrong answers? One common approach
drawn from emotions research has been to look for group consensus
as to the emotional content of stimuli (e.g., Mayer et al., 1990;
Wagner, MacDonald, & Manstead, 1986). If the group agrees
that a face is happy, say, then that becomes the correct answer.
A second possibility is to use expert criteria for emotional
meanings. An expert could bring a history of philosophy and
empirical psychology to bear on judgments about emotional
meanings (e.g., Darwin, 1872/1965; Ortony, Clore, & Collins,
1988; Plutchik, 1984; Spinoza, 1675/1984), and this might provide
answers similar to, or different from, a consensus criterion. On
the other hand, it has been argued that experts simply provide
estimates of group consensus, and those estimates are fallible
(Legree, 1995). Finally, a target criterion is applicable in
selected circumstances in which a target individual's emotions or
emotional creations are being judged. In such cases, the target
can report the emotion he or she was feeling or expressing at the
time. The group's consensus, the expert, and the target criteria,
represent somewhat different perspectives, and it is therefore
unlikely that they would be in complete agreement. For example,
target individuals sometimes report pleasant feelings, perhaps to
be socially conforming, when in fact they are perceived by a
group as experiencing less pleasant feelings (Mayer & Geher,
1996). Such differences in perspective do not necessarily rule
out a general convergence toward a criterion. Such a rough
convergence would substantiate the view that emotions convey
information, and that emotional intelligence is, in fact, an
intelligence.
Correlational Criteria for an Intelligence
The Logic of Correlational Criteria for Intelligence
Emotional intelligence should define a set of abilities that are
moderately intercorrelated with one another. There are many
excellent overviews of mental abilities and the criteria for
defining their class (e.g., Carroll, 1993; Flanagan, Genshaft,
& Harrison, 1997). This logic can be illustrated with an
example drawn from the clinical assessment of intelligence. The
original Wechsler Adult Intelligence Scales (i.e., WAIS, WAIS-R,
WAIS-III; Wechsler, 1958; see Anastasi & Urbina, 1997, for a
review of later tests) contained a set of verbal intelligence
scales. These consisted of many related mental tests including
identifying similarities among concepts, recognizing word
meanings (vocabulary), general information, comprehension, and
arithmetic. The abilities measured, e.g., vocabulary and
information, are moderately intercorrelated--they rise and fall
across people at about the r = 0.40 level. The tasks can be
summarized by a verbal IQ, where the IQ is based on a person's
overall performance on those tasks compared to the performance of
other people their age (because ability levels change with age).
The Wechsler tests from mid-century to 1998 typically paired
verbal intelligence with performance intelligence. Performance
abilities, such as assembling puzzles, identifying missing
elements in visual depictions, and ordering picture sequences,
also correlate highly with each other. These can be summarized by
a performance IQ, similarly based on the person's overall
performance on the tasks. The verbal and performance tasks
correlate less highly with each other; i.e., the verbal and
performance tasks are related to each other, but not quite as
closely as skills within each group.(3) They are also related,
however, and can be combined to form an overall IQ, which
represents the individual's average performance on a broader
range of mental tasks.
The Establishment of New Intelligences
The possibility that there exists one or more additional classes
of intelligence, beyond verbal and performance intelligence, has
long intrigued researchers. The identification of a new class of
intelligence would broaden our contemporary concepts of
intelligences. Moreover, adding missing intelligences to an
omnibus IQ test can increase the test's fairness by more
accurately representing individuals whose abilities were higher
on unknowingly omitted tests than on the tests that were present.
The identification of a class of intelligence, such as verbal or
performance, however, does not occur all at once. Usually, there
proceeds a painstaking process of developing candidate tasks for
the intelligence, finding a rationale for correct answers (if not
obvious), and then examining their intercorrelations with
existing measures of intelligences. For example, social
intelligence was proposed as a third member of the
verbal/performance grouping earlier in the century; it was
defined as "the ability to understand men and women, boys
and girls, to act wisely in human relations" (Thorndike,
1920). Measures of verbal intelligence, however, already
incorporate much social thinking; in fact, normal verbal
communication is so social that it is difficult to come up with
vocabulary ("What is democracy?") or general knowledge
questions ("Who was John F. Kennedy?") that do not
contain social information. In part, for such reasons, Cronbach
(1960) concluded that social intelligence could not be
distinguished from verbal intelligence. The search for a third
broad intelligence abated for the next several decades, although
a number of alternative intelligences have been discussed as
possible candidates.
Research on social intelligence has continued, with important
work by Sternberg and Smith (1985), Cantor and Kihlstrom (1987)
Legree (1995) and others. Much of that work represented important
conceptual development of social intelligence; little of that
work, however, concerned itself with actual ability measurement
in relation to other intelligences (some exceptions are Legree,
1995; Wagner & Sternberg, 1985). In addition, other
intelligences have been proposed, e.g., the multiple
intelligences of Gardner (1993) which included personal, musical,
and other intelligences. Here, too, research on individual
differences and their relations to already-existing intelligences
was de-emphasized (Sternberg, 1994).
Emotional intelligence represents an alternative grouping of
tasks to social intelligence. On one hand, emotional intelligence
is broader than social intelligence, including not only reasoning
about the emotions in social relationships, but also reasoning
about internal emotions that are important for personal (as
opposed to social) growth. On the other hand, emotional
intelligence is more focused than social intelligence in that it
pertains primarily to the emotional (but not necessarily verbal)
problems embedded in personal and social problems. For example,
reasoning about a sequence of internal feelings, or about the
feelings in a relationship, can be readily distinguished from
general questions about democracy, or John F. Kennedy, as
described above. This increased focus means that emotional
intelligence may be more distinct from traditional verbal
intelligence than is social intelligence.
The Developmental Criterion for an Intelligence
There remains a third criterion an intelligence must meet: that
it develops with age and experience, from childhood to adulthood.
That third criterion will be discussed at the outset of Study 2,
which is focused on studying developmental issues in emotional
intelligence.
INTRODUCTION TO THE PRESENT STUDIES
Widely accepted intelligences share certain features in common:
they are abilities, they manifest specific correlational patterns
among themselves and in relation to other intelligences, and they
develop with age and experience. The two studies described here
operationalize emotional intelligence as a set of abilities,
study the intercorrelational pattern among those abilities, and
examine evidence for their growth between adolescence and early
adulthood.
In Study 1, we constructed a set of 12 ability measures drawn
from each of the four defined areas of emotional intelligence
including perceiving, assimilating, understanding, and managing
emotion (Mayer, Salovey, & Caruso, 1997). The test was
administered to a large group of adults. We predicted moderate
correlations among the 12 tasks, and that a group factor, i.e.,
one that loads all 12 tasks, can be derived. As in our earlier
work, we predicted that a combination of these tasks correlates
with traditional forms of intelligence such as verbal
intelligence at such a level as to be distinct from such
traditional intelligences. Study 1 also examines evidence of
whether this emotional intelligence predicts empathy, parental
warmth, and cultural pursuits.
Study 2 focused more specifically on whether emotional
intelligence meets the developmental criterion for an
intelligence. An adolescent sample was given a reduced set of the
same group of tasks. The adolescent data are then compared to a
subset of the adult data from Study 1 so as to test the
hypothesis that adults outperform adolescents on the tasks.
STUDY 1
Method
Participants
Participants were 503 adults (164 men and 333 women, six
unreported) with a mean age of 23 years (range: 17-70), drawn
from several sources. One group of individuals (47%, N = 235) was
comprised of full-time college students who participated to
fulfill an introductory psychology course research requirement,
or who were paid (US$ 15) for their participation. The remainder
(53%, 268) were part-time college students, corporate employees,
career workshop attendees, and executives in an outplacement
setting who volunteered. The full sample was roughly
representative of the ethnic composition of the United States
census (Self-identified ethnicity/race: African-American, 12%
(58); Asian or Asian-American, 6% (31); Hispanic, 6% (32); Native
American, 1% (4); White: 68% (340); Other/Not Reported: 7% (38)).
The sample was above-average in education: less than 1% (2) had
no college; 80% (401) was in college or had been; 12% (59) was
college graduates; 7% (34) had advanced degrees; information on
the remainder 1% (7) was unreported.
The Multifactor Emotional Intelligence Scale (MEIS)
Overview of Test Organization. The MEIS consists of 12 tasks,
divided into four classes or "branches" of abilities
including (a) perceiving, (b) assimilating, (c) understanding,
and (d) managing emotion (Mayer & Salovey, 1997; Mayer et
al., 1997). Branch 1's four tests measured emotional perception
in Faces, Music, Designs, and Stories. Branch 2's two tests
measured Synesthesia Judgments and Feeling Biases. Branch 3's
four tests examined the understanding of emotion, including in
Blends, Progressions, and Transitions between and among emotions,
and Relativity in emotional perception. Branch 4's two tests
examined Emotion Management in Self and Others. The content of
the subtests and their scoring is described below, as are the
three scoring methods employed: consensus, expert, and target.
Branch 1: Perceiving Emotion
Branch 1 tasks concerned the ability to perceive and identify the
emotional content of a variety of stimuli.
Faces (Eight Stimuli; 48 Items). The first Branch 1 task, Faces,
used as stimuli eight faces from a CD-ROM photographic library
and from personal photos, chosen to represent a variety of
emotions, and for their authenticity in representing those
emotions. Each face was followed by six emotions: happiness,
anger, fear, sadness, disgust, and surprise. The test-taker was
to answer on a five-point scale whether a given emotion (e.g.,
anger) was "Definitely Not Present" (1) or
"Definitely Present" (5). The responses were scored
according to two criteria: consensus and expert.
Consensus Scoring. The group consensus served as the criterion
for this scoring approach. Each participant response was scored
according to its agreement with the proportion of the participant
group who endorsed the same alternative. For example, if 0.51 of
the participant group reported that anger was somewhat present
("4" on the scale), then a participant who chose
"4" would receive 0.51 for the item. If the participant
believed anger was definitely not present ("1" on the
scale), and only 0.06 of the sample agreed, then the individual
would receive a 0.06 for the item.
Expert Scoring. The first two authors served as experts for the
tasks, and went through the test answering questions by bringing
to bear, as much as possible, their reading of Western
philosophical treatments of emotion, and their reading of
contemporary psychological models of emotion. For example, in
deciding questions about emotional blends, reference was made to
the theory of emotional blends by Plutchik (1984). For each item,
the authors identified the best alternative (from 1 to 5) for
each response; general agreement with this best response
(choosing the selected value, or the integer on either side of
it) was scored "1"; otherwise, the individual received
a "0."(4)
Music (Eight Stimuli; 48 Items). The second Branch 1 task, Music,
was similar to the Faces task. The stimuli consisted of eight
brief (5-10 s) original pieces of music composed for this
project. Participants heard each piece of music and then rated
each one as to its emotional content on a series of mood
adjective scales. Each mood adjective was rated from 1
("Definitely Not Present") to 5 ("Definitely
Present"). The same six mood adjectives were employed as in
Faces.
Target Scoring. The music test was scored according to the
consensus and expert methods used above. In addition, the target
scoring method was employed here. Target scoring made use of an
additional data set. As the composer-musician worked, he was
requested to think about his feelings and the feelings his music
conveyed, which he then recorded on a mood scale. Target scoring
was scored for agreement with the target's feelings (in this
case, the composer-musician). It was scored as the expert scoring
was, with a "1" for a match (give or take 1) and
"0" for a non-match. Indeed, the target can be thought
of as a second type of expert.
Designs (Eight Stimuli; 48 Items). The third Branch 1 task,
Designs, was identical to the above except that eight original
computer-generated graphic designs served as the stimuli. The
designer was requested to create graphics that portrayed a
variety of feelings. As the designer worked, he recorded his
feelings on the six-adjective mood scale about what he expressed
in the design. Consensus, expert, and target scoring were
employed for this task.
Stories (Six Stimuli; 42 Items). The fourth Branch 1 task,
Stories, was identical to the above tasks except that six stories
were employed. The stories were obtained as in Mayer and Geher
(1996). Fifteen adult acquaintances of the authors were asked to
report on situations or thoughts affecting their moods, including
(a) "What led up to the situation?"; (b) "What is
the situation, or what you are thinking about?"; and (c)
"What happened in this situation which made you feel the way
you do?" Immediately thereafter, these 15 supplemental
participants recorded their moods on a 30-item mood-adjective
checklist, using the five-point rating scale described above (see
Faces). The passages were then edited lightly. The six passages
were then presented to participants in the main study. An example
was as follows.
This story comes from a middle-aged man. Everything
has been piling up at
work and I am falling behind. I have been working
late many nights and as a
result, my wife and daughter are feeling left out.
My relationship with
them is being stressed. I feel that I am letting
them down emotionally. I
feel guilty not spending time with them. At the same
time, a close family
member moved in with us after his divorce and job
loss. We have no privacy
and I finally told him he has to move out. It was
very difficult for me,
especially since in the way I was raised, you don't
treat a guest this way.
Each story was followed by a seven-adjective mood scale; the
adjectives varied from story to story. They were selected so as
to balance adjectives that were applicable to the story and those
that were not, as well as to balance positive- and negative-toned
adjectives. For the above story, the seven adjectives were,
"depressed, frustrated, guilty, energetic, liking, joyous,
and happy." The participant's job was to identify the
emotion in the story. The responses were scored by consensus,
expert, and target criteria.
Branch 2: Assimilating Emotions
Branch 2 tasks concerned the ability to assimilate emotions into
perceptual and cognitive processes.
Synesthesia (Six Stimuli; 60 Items). The first Branch 2 task,
Emotional Synesthesia, measured people's ability to describe
emotional sensations and their parallels to other sensory
modalities. The analysis of emotions often involves describing
their composition in regard to other sense modalities, including
movement, touch, pace, and color (Clynes, 1977; de Rivera, 1977).
In this task, people imagined an event that could make them feel
a particular feeling, which they then described on 10 semantic
differential scales. For example, one item asked, "Imagine
an event that could make you feel both somewhat surprised and
somewhat displeased ... Now describe your feelings on," each
of 10 five-point semantic differential scales, including
"warm 1 2 3 4 5 cold," and other scales involving color
(yellow or purple) touch (sharp or dull) and so forth; the scales
were invariant across stimuli. This task was scored by consensus
and expert criteria.
Feeling Biases (Four Stimuli; 28 Items). The second Branch 2
task, Feeling Biases, asked people to assimilate their present
mood into their judgments of how they felt toward a [fictional]
person at the moment. Thus, one task instructed participants to:
Imagine that Jonathan is one of your relatives. He
is a tall, muscular
person. Jonathan said something to you that made you
feel both guilty and
afraid. Feeling both guilty and afraid about
Jonathan, how does he seem?
The seven traits following each passage varied so as to be
relevant to each passage; in the above example, traits included
"sad, trusting, tense, cynical, aggressive, controlling, and
hasty." The traits were rated on a five-point scale
("Definitely Does Not Describe" (1) to "Definitely
Does Describe" (5)). The rationale for this task was that
people who use their emotions in thinking do so, in part, by
analyzing judgmental transformations that occur with mood. This
task was scored according to consensus and expert criteria.
Branch 3: Understanding Emotions
Branch 3's tasks concerned reasoning about and understanding
emotions.
Blends (Eight Stimuli; Eight Items). The first Branch 3 task,
Blends, concerned the ability to analyze blended or complex
emotions. Items were of the following form.
Optimism most closely combines which two emotions?
(a) pleasure and anticipation
(b) acceptance and joy
(c) surprise and joy
(d) pleasure and joy.
Participants were instructed to select the single best answer.
The eight items covered blends of two emotions (four items),
blends of three emotions (two items), and blends of four emotions
(two items). Scoring was by consensus and expert criteria.
Progressions (Eight Stimuli; Eight Items). The second Branch 3
task, Progressions, concerned people's understanding of how
emotional reactions proceed over time, with a special focus on
the intensification of feelings. A sample item read:
If you feel angrier and angrier toward someone so that you are
losing control, it would result in (choose one):
(a) gloating
(b) resentment
(c) hate
(d) rage.
Participants were instructed to identify the single best answer.
Items were scored according to consensus and expert criteria.
Transitions (Four Stimuli; 24 Items). The third Branch 3 task,
Transitions, concerned people's understanding of how emotions
(and implicitly, the situations eliciting them) follow upon one
another. Items were of the following form:
A person is afraid and later is calm. In between,
what are the likely ways
the person might feel?
Each item was followed by six alternative feelings. Alternatives
for the above item were acceptance, fear, anger, anticipation,
surprise, and disappointment. The participant rated each item as
"Extremely Unlikely" (1) to have occurred, or as
"Extremely Likely" (5). The remaining three items
followed the same form.
Relativity (Four Stimuli; 40 Items). The fourth Branch 3 task,
Relativity, was composed of items depicting conflictual social
encounters between two characters. The participant's task was to
estimate the feelings of both those characters. One item read:
A dog is chasing sticks outside when he runs out in
the street and gets hit
by a car. The driver stops when the dog's owner
dashes over to check on the
dog.
The first items concern the dog-owner's feelings. Participants
must decide to what extent the dog owner feels each of five ways,
including, "ashamed about not being able to have better
trained the dog," or "challenged to protect other dogs
from mishaps." Each alternative was rated according to how
likely a feeling-reaction was, from "Extremely
Unlikely" (1) to "Extremely Likely" (5). Next, the
participant made similar judgments as to the second character
(the driver, above). In the above example, participants judged
whether the driver felt "relief that it was only a
dog," or "guilty for not being a more cautious
driver," and so on, on the same response scale.
Branch 4: Managing Emotions
Branch 4 concerns the ability to manage emotions.
Managing Feelings of Others (Six Stimuli; 24 Items). The first
Branch 4 task, Managing Feelings of Others, examines how
participants manage the emotions of others. Participants were
asked to evaluate plans of action in response to fictional
people, described in brief vignettes, who needed assistance. The
task consisted of six vignettes, each followed by four possible
courses of action. For example:
One of your colleagues at work looks upset and asks
if you will eat lunch
with him. At the cafeteria, he motions for you to
sit away from the other
diners. After a few minutes of slow conversation, he
says that he wants to
talk to you about what's on his mind. He tells you
that he lied on his
resume about having a college degree. Without the
degree, he wouldn't have
gotten the job.
Participants were to rate alternatives such as (for the above
vignette):
Ask him how he feels about it so you can understand
what's going on. Offer
to help him, but don't push yourself on him if he
really doesn't want any
of your help.
Participants rated responses from "Extremely Ineffective
(1)" to "Extremely Effective (5)." Tasks were
scored according to consensus and expert criteria.
Managing Feelings of the Self (Six Stimuli; 24 Items). The second
Branch 4 task, Managing Feelings of the Self, concerns how a
person would regulate his own emotions. This task consisted of
six vignettes, each one describing a particular emotional
problem. For example:
You have been dating the same person for several
months and feel very
comfortable. Lately, you are thinking that this
relationship may be the one
and although marriage hasn't been discussed, you are
assuming that it is a
real possibility. The last thing you expected was
the phone call you
received saying that the relationship is over. You
have lost the love of
your life.
Participants were instructed that not every situation is equally
applicable to everyone but to imagine, if in that situation, the
effectiveness of given responses. One such response to the above
situation was:
The best way to cope with this terrible blow is to
do whatever you can to
block it out and not let it get to you any more than
it has. You would
throw yourself into your work or some activity and
then try to put it
behind you.
Participants rated each response from "Extremely Ineffective
(1)" to "Extremely Effective (5)." Tasks were
scored according to consensus and expert criteria.
Criterion Scales
Two classes of criterion scales were employed along with the
MEIS. Primary criteria included measures of intelligence and
self-reported empathic feeling, both of which have been predicted
to correlate with emotional intelligence in the past (Mayer et
al., 1990; Salovey & Mayer, 1990). Secondary criteria
included measures of several areas in which emotionally
intelligent individuals are thought to differ from others. These
include higher life satisfaction, a family environment that
encourages learning about feelings, and aesthetic perception and
participation (Mayer & Salovey, 1990; 1995; Salovey &
Mayer, 1990).
Primary Criteria
Intelligence Measure. The intelligence criterion was adapted from
the Army Alpha test of intelligence (Yerkes, 1921). The Army
Alpha was employed because its validity is well-established and
its form is ideal for group testing of the sort carried out here.
The vocabulary scale was used because that subtest is the
strongest component of verbal intelligence (e.g., Wechsler, 1958;
Morrison, 1976, pp. 318-325). Thirty of the more difficult
vocabulary items from the 50 were selected; more difficult items
were favored so as to tailor the test to the participant
population, which included mostly college-educated individuals.
The Army Alpha vocabulary scale employs four response options for
each word to be defined (e.g., "Reply: (1) make, (2) do, (3)
answer, (4) come"). Participants were instructed to select
the alternative from the list that most nearly meant the same as
the target word. The scale had an alpha reliability of [Alpha] =
0.88 in this data set.
Empathy Measure. A 30-item empathy scale (Caruso & Mayer,
1999) was developed with content coverage similar to the
Epstein-Mehrabian scale (Mehrabian & Epstein, 1972), but with
identifiable factor-based subscales. This newer scale was
employed so that overall self-reported empathy and also its
subcomponents could be compared to emotional intelligence. The
scale's overall self-reported empathy score has an alpha
reliability of [Alpha] = 0.86. Because of content overlap with
the Epstein-Mehrabian scale, it is likely to perform similarly to
it. In contrast to the Epstein-Mehrabian, however, the present
scale can be divided into five more specific factor-based scales.
The five subscales, their reliabilities, and a sample item from
each are: (a) Empathic Suffering, [Alpha] = 0.79, "The
suffering of others deeply disturbs me"; (b) Positive
Sharing, [Alpha] = 0.72, "Seeing other people smile makes me
smile"; (c) Responsive Crying, [Alpha] = 0.74, "I cry
easily when seeing a sad movie"; (d) Avoidance [reversed],
[Alpha] = 0.72, "I find it annoying when other people cry in
public"; and (e) Feeling for Others, [Alpha] = 0.61,
"If someone is upset, I get upset too."
Secondary Criteria
Life Satisfaction. Each person was asked about his satisfaction
with his Relationships, Academic Status, and Career and Work
Situation, to be reported on a five-point rating scale (from
"Not at All Satisfied" to "Extremely
Satisfied"). A factor analysis indicated the items were
unifactorial although they were only moderately intercorrelated.
A single life satisfaction score ([Alpha] = 0.59) was employed,
representing the sum of each person's responses.
Artistic Skills. Participants also reported their degree of
artistic skill in eight areas (from "1" no or little
talent to "3" very talented). A unifactorial Artistic
Skill score ([Alpha] = 0.71) indicated overall self-reported
artistic skill in those areas, which included sculpture, music,
and writing.
Parental Warmth. Participants also described their parents'
behaviors on a seven-item scale. A unifactorial Parental Warmth
factor ([Alpha] = 0.81) included items reporting that parents
were warm, listened, were non-abusive, and (reversed) yelled and
were strict.
Psychotherapy. Psychotherapy was scored as the number of months a
person had psychotherapy (which for some people was zero)
multiplied by the number of sessions of psychotherapy per month.
Life Space Leisure. Life space scales consist of items that
record a person's environment in terms of discrete, externally
verifiable, responses (e.g., "How many pairs of shoes do you
own?" "How many times have you attended the theater in
the last year?"; Mayer, 1998; Mayer, Carlsmith, &
Chabot, 1998). Certain life activities, particularly those
involving aesthetic appreciation, have been predicted to involve
more emotional intelligence than others (Mayer et al., 1990).
Thirty-three items concerning leisure activities were
administered to participants covering books read, television
watched, and cultural events observed. These items yielded three
factor-based scales of leisure activities, based on an unrotated,
principal components analysis, using all items loading on a given
factor r [is greater than] [+ or -] 0.45. The first,
Culture-Seeking, factor scale ([Alpha] = 0.78) loaded the
following items: listening to classical music, attending
concerts, listening to soul, listening to gospel, listening to
country, listening to rap, listening to new-age music, listening
to bluegrass, listening to rock, and attending museums. The
second, Improvement-Seeking, scale ([Alpha] = 0.60), loaded
reading self-help books, how-to books, medical books, business
books, and short-stories. The third, Entertainment-Seeking,
factor scale ([Alpha] = 0.67), loaded watching action television
programs, watching comedy programs, listening to punk music,
listening to blues music, and watching televised sports.
Procedure
Participants completed the study in small groups or individually.
Each participant received an item and answer booklet that
contained all necessary instructions, test items and responses.
The test was not timed and the test materials were
self-administered, with the exception of the music task, for
which a tape of instructions and music was played by the
experimenter in group settings.
Results
This section is divided into three parts. First, scoring methods
for emotional intelligence are compared. Second, the emotional
intelligence tasks are intercorrelated and factor analyzed.
Third, emotional intelligence is correlated with various external
criteria.
Scoring for Emotional Intelligence
Consensus, Expert, and Target Criteria for Correct Answers
Emotional intelligence depends on the idea that certain emotional
problems have answers that can be judged correct and incorrect.
Convergence among different scoring criteria provides a
foundation for such assumptions. The data analysis began by
comparing the three different methods for identifying a correct
answer: according to (a) the group consensus, (b) expert's
identification, and (c) a target's assessment (for three tasks
only). We began by examining the degree to which these three
methods converged toward a correct response. To the extent that
the group consensus (as identified by the modal response) and
experts agree as to the best answer, their selections should
intercorrelate over the items of a given test. For example, if
both the group consensus and experts agree that anger is high in
one story ("4" or "5"), but low in another
("1" or "2"), then the correlations should be
high.
To test the relation between consensus and expert ratings, we
selected four tasks, each drawn randomly from one of the four
branches, and calculated the intercorrelation between ratings.
The four tasks collectively contain 127 items, representing each
branch, and provide a good estimate of the test's overall
pattern. For each item, we paired the modal consensus choice with
the specific expert selection. In fact, the consensus and expert
ratings were fairly highly intercorrelated across tasks: Stories
(Branch 1) r = 0.70; Feeling Bias (Branch 2) r = 0.64; Relativity
(Branch 3) r = 0.61; and Managing Feelings of Others (Branch 4) r
= 0.80. (All rs were significant, p [is less than] 0.0001 level).
This suggests that the two criteria are closely related.
The third, Target criterion, was available only for three Branch
1 tasks. This criterion involves reports by the Targets of their
actual feelings as they were creating their artistry (Music and
Designs) or telling how they felt (Stories). In general,
Consensus correlated a bit more highly with the Target criteria
than did the Expert criterion (Music task: r = 0.61 for
consensus, r = 0.52 for expert; Designs: r = 0.70 and 0.60;
Stories, r = 0.80 and 0.69).
Generally speaking, the three criteria appeared to correlate
moderately highly, indicating that some answers were "more
correct" than others, according; to any and all of the
scoring methods used: consensus, expert, and target.
Agreement Scoring for Consensus, Expert, and Target Criteria
A given participant's performance can be assessed in relation to
each of the above three scores: Consensus, Expert, and Target.
These agreement scores represent the degree to which a given
participant's responses coincided with those of the criteria. The
means, standard deviations, and reliabilities of the
participants' performance, broken down by the three scoring
methods, can be seen in Table 1. The means are not directly
comparable across consensus, expert, and target because of their
substantially different scoring approaches (see above). The
figures do indicate, however, the average performance level of
the sample, and also that there were no problems of floor or
ceiling effects in any of the three scoring methods.
Table 1. Means, Standard Deviations, and Reliabilities
(Coefficient Alpha) of the Agreement with Consensus, Expert, and
Target Criteria
Scoring Method
Consensus
Branch and
Task
M
S [Alpha]
Emotional Identification
1:
Faces
0.40
0.08 0.89
1:
Music
0.44
0.11 0.94
1:
Designs
0.36
0.08 0.90
1:
Stories
0.38
0.07 0.85
Assimilating Emotions
2:
Synesthesia
0.31
0.04 0.86
2: Feeling
biases
0.30
0.05 0.70
Understanding Emotions
3:
Blends
0.49
0.10 0.49
3:
Progressions
0.58
0.10 0.51
3:
Transitions
0.30
0.04 0.94
3:
Relativity
0.30
0.04 0.78
Managing Emotions
4: Managing
others
0.28
0.04 0.72
4: Managing
self
0.27
0.04 0.70
Scoring Method
Expert
Branch and
Task
M
S [Alpha]
Emotional Identification
1:
Faces
0.64
0.11 0.74
1:
Music
0.73
0.10 0.86
1:
Designs
0.69
0.11 0.74
1:
Stories
0.72
0.11 0.72
Assimilating Emotions
2:
Synesthesia
0.69
0.09 0.66
2: Feeling
biases
0.72
0.12 0.60
Understanding Emotions
3:
Blends
0.60
0.19 0.35
3:
Progressions
0.83
0.16 0.50
3:
Transitions
0.56
0.11 0.85
3:
Relativity
0.56
0.11 0.63
Managing Emotions
4: Managing
others
0.60
0.12 0.42
4: Managing
self
0.55
0.12 0.40
Scoring Method
Target
Branch and
Task
M
S [Alpha]
Emotional Identification
1:
Faces
--
-- --
1:
Music
0.75
0.12 0.88
1:
Designs
0.65
0.14 0.81
1:
Stories
0.66
0.10 0.61
Assimilating Emotions
2:
Synesthesia
--
-- --
2: Feeling
biases
--
-- --
Understanding Emotions
3:
Blends
--
-- --
3:
Progressions
--
-- --
3:
Transitions
--
-- --
3:
Relativity
--
-- --
Managing Emotions
4: Managing
others
--
-- --
4: Managing
self
--
-- --
The reliabilities of the agreement scores are also promising,
with individual tasks having reliabilities most often between
[Alpha] = 0.70 and 0.94 for consensus, and a bit lower for expert
agreement. The first two tasks of Branch 3, which were also the
shortest, had lower reliabilities, [Alpha] = 0.35-0.51; the
Branch 4 management tasks were also low, but for expert scoring
only. All the reliabilities are satisfactory for this exploratory
study concerning the factorial structure of emotional
intelligence and what it predicts.
Sex Differences in Performance
Women performed somewhat higher than men on the 12 tasks,
according to all the scoring procedures. The difference was 0.5
standard deviation for consensus agreement ([M.sub.women] =
0.376; [SD.sub.women] = 0.029; [M.sub.men] = 0.358; [SD.sub.men]
= 0.036; Hotelling's F(12, 409) = 4.0, p [is less than] 0.001 .),
and about 0.1 standard deviation for each of expert agreement
([M.sub.women] = 0.664; [SD.sub.women] = 0.048; [M.sub.men]=
0.657; [SD.sub.men] = 0.061; Hotelling's F(12, 408) = 4.7, p [is
less than] 0.001), and target agreement ([M.sub.women] = 0.689;
[SD.sub.women] = 0.093; [M.sub.men] = 0.676; [SD.sub.men] =
0.079; Hotelling's F(3,482) = 1.34, n.s.). This replicates
earlier similar findings (cf. Buck, 1984; Mayer & Geher,
1996). We endeavored to understand more about this difference by
focusing on the Story task in particular, which was
representative of the full test according to subsequent factor
analyses (see below). The Story task also showed the greatest sex
differences, and contained all three scoring criteria. It is
possible that women outperformed men using consensus scoring
because the women were using a women's criterion which was
different than the men, and the larger number of women in the
sample (N = 333 vs. 164) meant that the women's choices were
scored with higher values than the men's. This, however, did not
account for the women's slightly better performance. Women and
men seemed to be employing close to the same criterion. The
correlation between women's and men's choices for the emotional
content across the 42 story items (six stories, seven items each)
was r(42) = 0.993, indicating a high level of agreement (nor was
there any difference in the average emotion-level perceived on an
item: [M.sub.women] = 2.67; [SD.sub.women] = 1.19; [M.sub.men] =
2.69; [SD.sub.men] = 1.04; t(41): 0.77, n.s.).
We further examined women's and men's performance by employing a
two (maleparticipant/female participant) by two (male story
character/female story character) by two (male-selected
consensus/female-selected consensus) MANOVA on the story data.
The MANOVA yielded a main effect representing the women's better
consensual accuracy (F(1,495) = 20.08, p [is less than] 0.001).
Women outperformed men under all conditions, even using
male-chosen consensus across stories ([M.sub.women] = 0.37;
[SD.sub.women] = 0.056; [M.sub.men] = 0.35; [SD.sub.men] = 0.059;
t(495) = 3.68, p [is less than] 0.001). A second main effect
indicated that the participants, as a whole, were more accurate
when using women's consensus criteria over men's (F(1,495) =
928.7, p [is less than] 0.001). A sex by consensus interaction
indicated that women did slightly better using their own
consensus criterion (F(1,495) = 67.3, p [is less than] 0.001).
There was also a sex-of-target effect that favored judgments
concerning male targets (F(1,495) = 696.3, p [is less than]
0.001). Collectively, these results indicate that women generally
do better than men on these tasks and that the results are not
caused by any simple bias in the test materials or how they are
scored. Moreover, if one judges by the consensus scoring (which
may be fairest, as the expert's criteria were developed by the
male authors), the difference between women and men's performance
is a moderate 0.5 standard deviation in size.
Correlations among Consensus, Expert, and Target-scored Tasks
Consensus and Expert Scoring Considered Individually. One
correlational standard for an intelligence is that it defines a
cluster of interrelated abilities (Guttman & Levy, 1991). The
following analyses examine the intercorrelations among the 12
tasks to see if they show a "positive manifold"; i.e.,
a correlation matrix in which most tasks correlate positively
with one another. Correlations among the 12 emotional
intelligence tasks were calculated using all three scoring
methods. In each case, a positive manifold was evident. Scored by
the consensus method, the tasks mostly correlated with one
another between r = 0.20 and 0.50, with the full range spanning r
= 0.07-0.68. Scored by the expert method, the tasks mostly
correlated with one another r = 0.10-0.40, with a full range from
r = 0.00 to 0.54. In either case, the matrix possesses a positive
manifold; almost all the tasks are positively intercorrelated, as
expected in regard to a unified intelligence. The
consensus-scored tasks (with alpha reliabilities on the diagonal)
can be seen in Table 2.
Table 2. Intercorrelations of the Consensus Scored Tasks with
Reliabilities (Coefficient Alpha) on the Diagonal(*)
1
Branch and
Task
Fa Mu
De St
Emotional Identification
1:
Faces
0.89
1:
Music
0.61 0.94
1:
Designs
0.68 0.60 0.90
1:
Stories
0.54 0.47 0.54 0.85
Assimilating Emotions
2:
Synesthesia
0.24 0.24 0.26 0.38
2: Feeling
biases
0.30 0.24 0.35 0.47
Understanding Emotions
3:
Blends
0.07 0.13 0.09 0.24
3:
Progressions
0.10 0.15 0.14 0.25
3:
Transitions
0.25 0.29 0.29 0.37
3:
Relativity
0.30 0.35 0.32 0.41
Managing Emotions
4: Managing
others
0.20 0.21 0.20 0.28
4: Managing
self
0.19 0.15 0.14 0.30
2
3
Branch and
Task
Sy Fe
Bl Pr Tr
Emotional Identification
1: Faces
1: Music
1: Designs
1: Stories
Assimilating Emotions
2:
Synesthesia
0.86
2: Feeling
biases
0.39 0.71
Understanding Emotions
3:
Blends
0.22 0.26 0.49
3:
Progressions
0.34 0.35 0.41 0.59
3:
Transitions
0.26 0.34 0.19
0.17 0.94
3:
Relativity
0.32 0.38 0.30
0.34 0.43
Managing Emotions
4: Managing
others
0.25 0.24 0.16
0.22 0.18
4: Managing
self
0.27 0.22 0.20
0.23 0.17
3 4
Branch and
Task
Re Mo Ms
Emotional Identification
1: Faces
1: Music
1: Designs
1: Stories
Assimilating Emotions
2: Synesthesia
2: Feeling biases
Understanding Emotions
3: Blends
3: Progressions
3: Transitions
3:
Relativity
0.78
Managing Emotions
4: Managing
others
0.37 0.72
4: Managing
self
0.25 0.54 0.70
(*) N = 500. Note that correlations above r [approximately
equals] 0.08 are significant at beyond the p < 0.01 level.
Comparisons among Consensus, Expert, and Target Scoring. To
further compare scoring methods, we examined participants'
performance on each of the 12 tasks, scored according to a
consensus, expert-scoring, or target criterion. For consensus and
expert scoring (which were available for all 12 tasks),
participants' performance, scored each way, correlated between r=
-0.16 and 0.95, with half the tasks above r = 0.52. The only
negative correlation (r = -0.16), which occurred for faces, and
other low correlations for the Designs task (r = 0.24) may have
been a consequence of different color photocopying employed to
reproduce the stimuli for the groups and the experts.
The convergence for participant's consensus and target scores for
the Music, Designs, and Stories tasks (where target scoring was
available) were r = 0.81, 0.22, and 0.43, respectively; the same
values for expert and target scoring were r = 0.67, 0.46, and
0.16. Subsequent analyses indicated the general superiority of
the consensus scoring method in relation to the other
alternatives. It yielded higher alpha test reliabilities for
every task without exception, clearer factor result, (which were,
nonetheless, highly similar to expert scoring), and higher
correlations with criteria. The superiority of consensus scoring
has been argued persuasively elsewhere (e.g., Legree, 1995). For
that reason, the subsequent analyses focus on the consensus
scoring.
The Structure of Emotional Intelligence
Factor Structure of the MEIS
Our next question was whether emotional intelligence is best
characterized as one or many abilities. Although a highly
developed theory of emotional intelligence motivates this
article, this represented our own first empirical examination of
so many tasks. For that reason, we employed exploratory factor
analysis at the outset. We therefore applied principal axis
factoring (with communalities on the matrix diagonal) to scores
on the 12 MEIS subscales. A joint scree/meaningfulness criterion
yielded a three-factor solution (first six eigenvalues: 4.3, 1.6,
1.1, 0.9, 0.8, 0.6). Table 3 (left columns) show the
three-factor, unrotated solution for the 12 consensus-scored
subscales. We then further analyzed this three-factor solution by
rotating it according to an oblique criterion (using an oblimin
procedure). The right columns of Table 3 show this result.
Table 3. Three-factor Solutions for the Emotional Intelligence
Test Scored According to Consensus and According to Expert
Criteria, in Unrotated and Rotated Solutions: Principal
Components Factoring(a)
Unrotated
Solution
Branch/Task
I
II III
Unrotated Solution
Emotional Identification
1:
Faces
0.67 -0.48
-0.11
1:
Music
0.63 -0.34
-0.04
1:
Design
0.69 -0.44
-0.02
1:
Stories
0.73
-0.09 0.05
Assimilating Emotions
2:
Synesthesia
0.51
0.19 0.10
2: Feeling
biases
0.59
0.13 0.21
Understanding Emotions
3:
Blends
0.35
0.32 0.24
3:
Progressions
0.43
0.38 0.25
3:
Transitions
0.48
0.04 0.12
3:
Relativity
0.61
0.18 0.09
Managing Emotions
4: Managing
others
0.49
0.36 -0.49
4: Managing
self
0.44
0.36 -0.38
Oblique Rotated
(Pattern Matrix)(b)
Solution
Branch/Task
I
II III
Unrotated Solution
Emotional Identification
1:
Faces
-0.10 0.86 0.04
1:
Music
0.02 0.70 0.02
1:
Design
0.01 0.82 -0.03
1:
Stories
0.30 0.52 0.08
Assimilating Emotions
2:
Synesthesia
0.43 -0.12 0.10
2: Feeling
biases
0.53 -0.20 0.00
Understanding Emotions
3:
Blends
0.57 -0.10 -0.01
3:
Progressions
0.64 -0.11 0.02
3:
Transitions
0.35 0.23 0.00
3:
Relativity
0.45 0.20 0.14
Managing Emotions
4: Managing
others
-0.05 0.00 0.81
4: Managing
self
0.03 -0.03 0.68
(a) Loadings above [+ or -] 0.25 are in bold typeface for
clarity.
(b) Loadings indicated that all three factors were unipolar
(i.e., loadings oil a factor above [+ or -] 0.25 all shared the
same sign). Rotated factors II and III, however, were negative.
To clarify results and facilitate discussion, loadings on rotated
Factors II and III were reversed in sign here and in subsequent
analyses.
In the unrotated solution, the first factor may be interpreted as
a general emotional intelligence (gel) because it loads all the
tasks without exception. This [g.sub.ei] apparently represents a
group factor of emotional intelligence tasks, suggesting their
interrelatedness (below, we explore this question further). The
second factor, Managing vs. Perceiving Emotions, discriminates
tasks high in reasoning from those high in simple emotional
perception. And the third factor, Managing Emotions, describes
the two Branch 4 tasks concerning regulating emotions in oneself
and others.
The rotated version of this three-factor solution tells the same
story from a different angle. The first factor, Emotional
Understanding, loads most of the tasks on Branch 3
(Understanding), along with tasks on Branch 2 (Assimilation). The
second factor, Emotional Perception, loads most of the tasks on
Branch 1 (Perception). The third, Managing Emotion factor, loads
the two Branch 4 (Regulation) tasks, as in the unrotated
solution. In this analysis, oblimin factors 2 and 3 had uniformly
negative loadings. We reversed the loadings in sign so that a
higher score indicated a higher level of ability across tasks. We
similarly changed the sign of factor scores and scales based on
these two factors. This procedure simplifies the presentation and
discussion of results while remaining consistent with the
substantive findings.
As a pattern matrix should do, this solution "turns up the
contrast" on the loadings, separating the test into three
portions: perception, understanding, and managing. This is done,
in part, by transferring the common variance shared among the
individual tasks to the three factors underlying them. As a
consequence, the three factors intercorrelate fairly
substantially. Perception correlated r = 0.39 with Understanding
and r = 0.49 with Management; the latter two intercorrelated, r=
0.33.
The above results provide strong empirical support for a
three-factor model of the MEIS. Recall that our theoretical model
involves a four-branch model. We wondered whether there was also
evidence for a four-factor model. To fully investigate this
possibility, we modeled the data as a four-factor solution using
covariance structural modeling. We used a stringent model in
which each task was forced to load only on its hypothesized
factor and no other (e.g., Arbuckle, 1997, p. 396). The factors
themselves, however, were allowed to intercorrelate as above. The
model fit was sufficiently good to be informative, with a Root
Mean Square Error of Approximation (RMSEA) of 0.09 with no
relaxation of parameters(5) (one rule of thumb is that a RMSEA
0.05 indicates a close fit; Browne & Cudeck, 1993). As
appealing as this four-factor model is to us, the drawback is
that the model estimates two of the factors, Assimilation and
Understanding, to intercorrelate r = 0.87, which makes them
difficult to distinguish from one another. For that reason, we
continue to focus on the three-factor model in our analyses,
while acknowledging that the four-factor model remains viable.
Hierarchical Relations among Factors and the Creation of MEIS
Scales
The first unrotated factor of the MEIS was earlier said to
represent a [g.sub.ei], or general factor of the test. Such
general factors sometimes can arise spuriously due to the nature
of principal axis factoring. For that reason, it is often
recommended that a hierarchical factor analysis be employed as a
secondary check of the existence of a hierarchical factor (e.g.,
Carroll, 1993; Jenson & Weng, 1994). Obtaining a hierarchical
(second-order) factor that loads all the primary factors is
generally considered stronger evidence for a general factor
because it is based solely on the covariances among the primary
factors. A new factor analysis was therefore conducted on the
Perception, Understanding, and Managing factor scores. A single
hierarchical factor was extracted that loaded Perception,
Understanding, and Management at substantial levels; (r = 0.50,
0.86, and 0.75, respectively).(6) This hierarchical factor
correlated with the unrotated first factor of the principal axis
factoring at r = 0.94. This final result indicates that general
emotional intelligence can be reasonably represented by the first
unrotated principal axis factor, and that it loads all the scales
studied here.
The Construction of Factor-based Scales
For our further analyses, we first constructed factor scales for
Perception, Understanding, and Managing Emotions factors (and for
General Emotional Intelligence, [g.sub.ei], based on the first
unrotated factor). The scales were constructed by summing
z-scored subscale scores from tasks that loaded on the factors
above r = [+ or -]0.35. The resulting factor-based scales were
then correlated with the original factor scales (based on a
weighted sum of all 12 scales) to ensure that they represented
the original scales adequately. The three factor-based scales
representing perception, understanding, and managing, correlated
very highly with their respective factor scales (r = 0.98, 0.97,
and 0.98, respectively), and were highly reliable ([Alpha] =
0.96, 0.92, and 0.81). The three factor-based scales were
moderately intercorrelated (Perception with Understanding, r =
0.44; Perception with Managing, r = 0.29; Understanding with
Managing, r = 0.43). The overall General Emotional Intelligence
factor-based scale also correlated with its original factor scale
r = 0.97, and had a reliability of([Alpha] = 0.96. These are the
scales reported in the rest of the article.
Researchers wishing to retain the four-branch theoretical model
(modestly supported by covariance structural modeling above) may
wish to employ four, rather than three, factor-based scales. The
above three scales may be transformed into four by (a) retaining
the Perception and Managing scales as calculated above, and (b)
splitting the Understanding scale, above, into two scales. The
first of these two scales, the revised Understanding scale, is
calculated as the sum of the z-scores of the Blends,
Progressions, Transitions, and Relativity tasks. The second of
these two scales, the new Assimilation scale, is calculated as
the sum of the z-scores of the Synesthesia and Feeling Biases
tasks.[7] The [Alpha] reliabilities of the (unchanged)
Perception, (new) Assimilation, (revised) Understanding, and
(unchanged) Management factor-based scales are, respectively,
[Alpha] = 0.96, 0.86, 0.89, and 0.81. The Understanding
factorbased scale still correlates with the original factor scale
r = 0.89. The new, Assimilation factor-based scale, correlates
with Understanding, r = 0.65.
Relation of the Emotional Intelligence Factors to Criterion
Measures
The final correlational criterion for an intelligence is that it
correlates moderately with intelligences in other domains. The
correlation should be high enough to indicate that the new skill
is an intelligence, but low enough to illustrate that it says
something new about human abilities. Aside from emotional
intelligence's correlation with verbal intelligence, emotional
intelligence will be important to the degree that it predicts
other criteria as well.
Table 4 shows the correlation of the emotional intelligence
factors with various criteria. The central correlations to
examine are those with the [g.sub.ei] factor (first column).
General emotional intelligence is then divided into subfactors of
perception, understanding, and management; correlations with
those subfactors are shown in the next three columns.
Table 4. Correlations Between Individual Tasks and Selected
Criterion Variables
Overall Score Subfactor Scores
Criterion Variables
[g.sub.ei] Perception
Primary Criteria
Ability
Verbal
IQ
0.36(**)
0.16(**)
Empathy
Overall
0.33(**)
0.20(**)
Suffering
0.35(*)
0.18(**)
Positive
Sharing
0.26(**)
0.12(**)
Crying
0.14(**)
0.10(*)
Avoidance
-0.2(**)
-0.20(**)
Feeling for
others
0.16(**)
0.08
Secondary Criteria
Life
satisfaction
0.11(*)
0.01
Artistic
skills
0.05
0.03
Parental
warmth
0.23(**)
0.20(**)
Psychotherapy
0.03
0.04
Leisure (life space)
Culture-seeking
0.00
-0.07
Self-improvement
-0.16(**) -0.07
Entertainment
-0.02
0.09(*)
Subfactor Scores
Criterion Variables
Understanding Management
Primary Criteria
Ability
Verbal
IQ
0.40(**) 0.20(**)
Empathy
Overall
0.25(**) 0.34(**)
Suffering
0.28(**) 0.37(**)
Positive
Sharing
0.16(*) 0.36(**)
Crying
0.10(*) 0.13(**)
Avoidance
-0.23(**) -0.15(**)
Feeling for
others
0.09(*) 0.24(**)
Secondary Criteria
Life
satisfaction
0.11(*) 0.13(**)
Artistic
skills
0.07
0.00
Parental
warmth
0.18(**) 0.15(**)
Psychotherapy
0.14(*) 0.02
Leisure (life space)
Culture-seeking
0.01
0.03
Self-improvement
-0.22(**) -0.05
Entertainment
-0.04
0.05
(*) p<0.05 level.
(**) p<0.01 level, two-tailed tests.
The correlation between the General Emotional Intelligence
factor-based scale and verbal intelligence is r = 0.36, p [is
less than] 0.001. This is the moderate level at which one would
hope that a new domain of intelligence would be correlated with
existing domains. In addition, emotional intelligence has a
number of interesting correlations with other variables. The gel
factor-based scale correlates r = 0.33, p [is less than] 0.001
with overall empathy, also as expected (Salovey & Mayer,
1990; Mayer et al., 1990; Mayer & Geher, 1996), and possesses
a number of significant correlations with subtypes of empathy as
well, correlating positively and at similar levels with
Suffering, Positive Sharing, and negatively with Avoidance.
Emotional intelligence had a positive correlation with parental
warmth, r = 0.23, p [is less than] 0.01, and a negative
correlation with pragmatic attempts at self-improvement r =
-0.16, p [is less than] 0.01, including reading self-help books,
books on business methods, and the like. The subfactor scales
further qualify the relations, suggesting that Understanding is
most closely related to verbal intelligence among the three
subfactors, and that Management most accounts for empathy; all
three subfactors are related to Parental Warmth.
An extremely stringent test would partial verbal IQ and
self-reported empathy out of the correlation between emotional
intelligence and the six secondary criteria. Doing this may
remove variance that legitimately belongs to emotional
intelligence, but it also ensures that emotional intelligence
contributes unique variance in predicting criteria. Partialing
out the influence of intelligence and empathy yielded a
[g.sub.ei] that maintained its significant negative correlation
with attempted self-improvement (r = -0.10, p [is less than]
0.05), and added a negative relation to culture-seeking (r =
-0.09, p [is less than] 0.05), although it no longer correlated
with life satisfaction or parenting.
Although the statistical relations between emotional intelligence
and the life space criteria may seem low, two things are worth
noting about them. First, our central focus has been on
understanding the structure of emotional intelligence. The few
secondary criterion scales included here were exploratory and
brief. Even these crude measures, however, demonstrate that
emotional intelligence predicts criteria independent of the
influence of both verbal intelligence and empathy. Second, it is
worth recalling that personality relations tend to be small but
consistent over the years. This small but consistent influence
can substantially change a person's position in life, just like a
slow but steady current can move a boat a considerable distance
across a lake over time.
Summary and Discussion of Study 1
The results from Study I indicate that emotional intelligence
shows a pattern that is consistent with a new domain of
intelligence. Emotional intelligence can be operationalized as
sets of abilities, and better answers can be distinguished from
worse answers, as indicated by the convergence of three scoring
methods. The 12 tasks also intercorrelate with one another,
independent of which scoring method is employed. The scale yields
four scores: A first, superordinate factor of general emotional
intelligence that provides one excellent and economical method
for representing the concept. The General Emotional Intelligence
factor can be divided in turn into three subscales: Perception,
Understanding, and Managing (thus reducing our four-branch model
to a three-branch model). Finally, emotional intelligence
correlates moderately with a measure of verbal intelligence,
indicating that it is related to other intelligences without
being the same as them. Emotional intelligence shows promise as a
predictor of other qualities such as empathy, (retrospective)
parenting style, and life activities.
STUDY 2
Thus far, emotional intelligence has met two of three important
criteria of a traditional intelligence. First, it has been
operationalized as a set of abilities. Second, it has shown a
pattern of correlations consistent with the existence of such an
intelligence. The third criterion is that intellectual capacities
grow with age and experience from childhood to early adulthood
(Brown, 1997; Fancher, 1985). The importance of age to
intelligence was first recognized by Binet. As Fancher (1985, p.
71) describes it:
Gradually ... a key insight developed--one which
seemed perfectly obvious
once recognized, but which nevertheless had
previously eluded Binet and
other investigators of intelligence. Age was a
crucial factor to be
considered: both subnormal and normal children might
learn to pass the same
tests, but normal children did so at a younger age.
Fancher attributes Binet's success in measuring intelligence, in
comparison to the failures of his contemporaries, to the
realization that mental abilities grow with age and experience.
For emotional intelligence to behave as does a standard
intelligence, it should be shown to increase with age. To test
whether this actually occurs, several portions of the scale
employed in Study 1 were administered to a young adolescent
sample (ages 12-16) in Study 2. The performance of the
adolescents was then compared to the performance of an adult
subsample drawn from Study 1. The use of two samples close in age
ensures that the same test items can be used and understood by
both groups. It also provides a challenging test of the
developmental hypothesis because proximity in age should yield
only small differences in performance between the two groups. We
hypothesized that the adult sample would significantly outperform
the adolescents on the scale.
Method
Adolescent Sample
Participants were 229 adolescents (125 young men, 101 young
women; 3 unidentified) with a mean age of 13.4 (range 12-16) who
were recruited from two independent secondary schools and a
religious youth group. These were split among 35% (81) 7th
graders, 36% (83) 8th graders, 9% (20) 9th graders, 12% (27) 10th
graders, 6% (13) 11th graders, and 1% (2) 12th graders;
(percentages add to 99% due to rounding error). The sample
deviated somewhat from the ethnic composition of the United
States census in under-representing minority groups
(Self-identified ethnicity/race: African-American, 5% (12); Asian
or Asian-American, 3% (6); Hispanic, 3% (7); Native American, 0%
(0); White: 79% (177); Other/Not Reported: 9% (27).
Adult Sample
The adult sample from Study 1 was again used in Study 2. Here,
however, the adult sample was divided on the basis of subject
number into two equal-sized samples: the "Independent Adult
Sample" and the "Consensus Sample." The
Independent Adult Sample served as the comparison group for the
adolescent group. The Consensus Sample was used to calculate a
consensus score to which the first, "Independent
Sample" had not contributed.
Materials
For reasons of time and age-appropriateness, only a subset of the
scales administered to adults was administered to the
developmental sample. These included Faces, Music, Designs, and
(age-appropriate portions of) Stories from Branch 1,(8)
Synesthesia from Branch 2, and Blends and Relativity from Branch
3. In addition, the Army Alpha Vocabulary scale and the Empathy
scale were administered as criteria.(9)
Procedure
Parental consent was first obtained for each participant in the
adolescent group, and then informed consent obtained from each
subject. All data were collected anonymously; no names were
requested. Furthermore, subjects were explicitly instructed not
to answer any questions that made them uncomfortable.
Participants in the developmental sample were tested in a similar
manner to the adults. They completed the materials in small
groups. Each participant received an item and answer booklet that
contained all necessary instructions, test items and responses.
For the music task, a researcher (or a classroom teacher) played
the cassette tape that included all necessary instructions as
well as the musical selections. Students required 45-75 min to
complete the test booklet.
Results
Scoring
Three scoring procedures were employed as in Study 1: agreement
with consensus, expert ratings, and target reports. Some
modifications in the consensus scoring were necessary for this
study. Using the adult consensus as in Study 1 would plainly
favor adults because each adult's score contributed to the
consensus. To control for this, the adult sample was divided in
half (on the basis of odd/even subject number). Next, new adult
consensus scores were calculated for the even half of the sample
only (the consensus sample). This left the odd half of the adult
sample with responses that were independent of the adult
consensus (the independent sample). It was this
"independent" adult sample whose consensus scores were
compared to the adolescent's consensus scores. Expert-scoring and
target-scoring were the same as in Study 1.
Adult-Adolescent Comparisons
The central purpose of Study 2 was to examine whether adults
functioned at a higher level of emotional intelligence than
adolescents. This hypothesis was tested via a two (Age-Group) by
seven (Task) ANOVA, where the seven tasks were within-subjects
variables. As the developmental hypothesis predicted, scores were
higher for adults than for adolescents for consensus agreement
(Grand Mean = 0.38 vs. 0.36; F(1,713) = 23.8, p [is less than]
0.001), for expert agreement (Grand Mean = 0.66 vs. 0.64;
F(1,709) = 22.3, p [is less than] 0.001), and for target
agreement (Grand Mean = 0.69 vs. 0.67; Hotelling's F(1,718) =
8.0, p [is less than] 0.01). Significant Task and Age x Task
effects were also present for all three scoring methods. Focusing
on consensus scoring, there was a significant Age-Group x Task
interaction for consensus (F(6,708) = 12.5, p [is less than]
0.01). Table 5 shows a more detailed comparison between the adult
and adolescent groups for consensus scoring on the individual
tasks they both received, and which tasks showed significant
differences in the predicted direction on their own. We did not
examine age-performance correlations beyond demonstrating these
average differences. First, the two samples were not strictly
comparable, as the adolescents were of slightly higher social
class (and therefore would be expected to perform more highly
than average). More seriously, the restriction of age-range in
both samples would render the correlation impossible to assess.
We did, however, determine that the adolescents' scores showed
the same pattern of correlations with verbal intelligence (r(220)
= 0.45, p [is less than] 0.001) and empathy (r(227) = 0.37, p [is
less than] 0.001) as did the adults.
Table 5. A Test of the Developmental Hypothesis: Means (and
Standard Deviations) of Adult vs. Adolescent Performance on
Selected Consensus-scored Scales of Emotional Intelligence
Adult
Adolescent
Branch/Task
M
SD
M
SD F
Emotional Identification
1:
Faces
0.400 0.078 0.384
0.075 5.2(*)
1:
Music
0.445 0.092 0.438
0.074 0.5
1:
Design
0.359 0.086 0.353
0.077 0.7
1:
Stories
0.328 0.069 0.323
0.061 1.5
Assimilating Emotions
2:
Synesthesia
0.306 0.045 0.295
0.047 7.8(**)
Understanding Emotions
3:
Blends
0.491 0.087 0.424
0.105 52.2(**)
3:
Relativity
0.307 0.053 0.304
0.058 0.2
Combined
tests
0.378 0.046 0.359
0.048 25.6(**)
(*) p < 0.05.
(**) p < 0.01.
Discussion of Study 2
Study 2 tested whether emotional intelligence met the third of
three criteria for a standard, conventional intelligence: whether
ability levels increase with age. As predicted, adults performed
at higher ability levels than do adolescents. In addition,
emotional intelligence in adolescence shows the same relation s
to verbal intelligence and empathy as with adults.
GENERAL DISCUSSION
Three major criteria for a standard intelligence are that it
consists of mental abilities, that those abilities meet certain
correlational criteria, and that the abilities develop with age.
In the tests conducted here, emotional intelligence met all three
criteria. First, emotional intelligence could be operationalized
as a set of ability tests. Second, performance on those ability
tests was intercorrelated and partly distinct from verbal
intelligence, against which they were compared. Third, emotional
intelligence was shown to grow from early adolescence to young
adulthood. Collectively, these findings bring us a major step
forward toward demonstrating a plausible case for the existence
of this intelligence. The data also tell us about the structure
of' emotional intelligence, and what it might predict.
The Nature of Emotional Intelligence and Its Measurement
Our factor analyses of the 12 MEIS tasks suggest that one can
best conceptualize emotional intelligence as involving three
primary factors, and a higher order, General Emotional
Intelligence factor that combines the three. The three primary
factors involve Perception, Understanding, and Managing of
emotion. Perception skills include those drawn from the first
branch of the model, including recognizing emotions in Faces,
Music, Designs, and Stories. Understanding skills include those
drawn from the Assimilation and Understanding branches of the
model, including Synesthesia, Feeling Biases, Blends,
Progressions, Transitions, and Relativity. Finally, Managing
emotions represent skills drawn from the fourth branch of the
model, including Managing Others and Managing the Self. The three
primary factors, in other words, could be said to capture the
four branches of our most recent model of emotional intelligence
(Mayer & Salovey, 1997): The Perception branch was captured
by the Perception factor scale, the Assimilation and
Understanding branches were combined into a single Understanding
factor scale, and the Managing Branch was captured by the
Managing factor scale. This three-branch measurement approach is
also broader than our original 1990 model (which omitted the
Understanding branch). The three primary facets of Perception,
Understanding, and Management clearly emerged from the data, and
although one still might possibly develop a four-branch measure,
it would apparently require developing substantially different
Branch 2 tasks than the ones employed here, so as to better
distinguish them from the Understanding branch.
The three primary abilities appear to be differentially related
to traditional intelligence, with Perception least related (r =
0.16), Management moderately related, and Understanding most
related (r = 0.40). This is consistent with other findings that
scales of nonverbal perception, such as the PONS (Profile of
Nonverbal States; Rosenthal et al., 1979) which appear to be
loaded on emotional perception, are relatively unrelated to
intelligence, whereas problem solving of the sort covered on the
Understanding branch plainly resembles traditional test items for
intelligence more closely. Thus, skills representing emotional
intelligence can be ordered along a continuum from those least to
those most related to general intelligence. At the same time, the
three tasks apparently share a common core of emotionally
intelligent processing, as indicated by a more general, overall
emotional intelligence factor.
As just noted, a single factor of emotional intelligence
incorporates all the tasks studied here. This factor arises as a
hierarchical factor obtained from factor-analyzing the three
primary factor-based scales of Perception, Understanding, and
Management (which are obtained by an oblimin rotation of the 12
tasks). Those three primary scales are fairly intercorrelated and
factor-analyzing them yields a single overall factor that
summarizes performance across them all. This hierarchical factor
is essentially identical to the first, unrotated principal factor
of the 12 scales (their r = 0.94). The global factor indicates
that it makes sense to talk about a single, unified emotional
intelligence and a single emotional intelligence score. Such a
score provides a reasonable first approximation of a person's
ability level in the domain of emotional intelligence. As with
any generalization, however, this overall score neglects
variations in three subsidiary aspects of emotional intelligence,
which can provide further clarification of any overall score.
Alternative Representations
It should be noted that the 12 tasks employed here do not exhaust
the universe of emotionally intelligent abilities. As other tasks
are developed, it is possible that more factors will be
identified. One sort of task, in particular, that does not lend
itself to group testing but that may form a separate factor, is
ability at expressing emotion (Branch 1 skills). It may also be
that a factor better encompassing assimilating emotions (Branch 2
of our model, which merged into Branch 3) might emerge as a more
independent factor were it operationalized in tasks different
than the ones used here.
Sex Differences
The identification of a new intelligence should increase the
fairness of mental ability tests on average. That is because
measures of the new intelligence help assess more of the total
domain of intelligence, thereby giving any previously neglected
capacities their fair consideration. Women and men appear to
perform about the same on most intelligence-related mental tests,
with most mean differences between 0.15 and 0.30 of an estimated
population standard deviation (Hedges & Nowell, 1995). There
are, however, some regular differences in the profiles of the two
groups. Women are somewhat better on tests of reading
comprehension, perceptual speed, associative memory, and
composition. Men are somewhat better in mathematics, social
studies, and in scientific knowledge.
To the list of tasks at which women are somewhat better may be
added emotional intelligence. Women performed about 0.5 standard
deviation higher than men in the present study. The fact that
women are slightly superior to men in perceiving emotion has been
known for some time, through tests of nonverbal perception (that
include emotion) such as the PONS (Rosenthal et al., 1979), as
well as through earlier-developed tests of emotional intelligence
(Mayer & Geher, 1996). One possible explanation for this is
that women must read emotions more carefully because they possess
less power in society than do men (LaFrance & Hecht, in
press), lit is women in more powerful positions rather than less,
however, who exhibit the greater emotional accuracy (Hall &
Halberstadt, 1994). Such findings suggest that emotional
intelligence operates like other areas of intelligence,
potentially raising the occupational status of an individual.
Issues of power and status aside, women may be socialized to pal
more attention to emotions, or they may be better biologically
prepared to perform at such tasks; our research does not address
the relative contributions of the two (cf., LaFrance, &
Banaji, 1992).
Emotional Intelligence, Intelligence, and Empathy
The findings here also concern what emotional intelligence
predicts. From the outset, emotional intelligence has been
hypothesized to correlate with both intelligence and
self-reported empathy (Mayer et al., 1990; Salovey & Mayer,
1990). Overall emotional intelligence, gel, correlated with
verbal intelligence at a low-to-moderate level, as predicted.
This replicates some of our earlier work as well (Mayer &
Geher, 1996).
Overall emotional intelligence, [g.sub.ei], also correlates with
self-reported empathy. This, too, replicates earlier studies
(Mayer & Geher, 1996; Mayer et al., 1990). Emotional
intelligence appears to correlate reliably with self-report
empathy scales that share content overlap with the
Epstein-Mehrabian scale (Mehrabian & Epstein, 1972). Such
scales, including the one used here and the: Davis (1983) empathy
subscales of "empathic concern" and
"emotion-related fantasy," involve a view of oneself as
emotionally responsive and concerned about the feelings of
others. The new scale employed here divides that same content
domain into a variety of subfactors including Empathic Suffering,
Positive Sharing, Responsive Crying, (reversed) Avoidance, and
Feeling For Others. Emotional Intelligence correlated with each
of these criteria in the expected direction.
Emotional Intelligence and Other Intelligences
The above demonstrations indicate that Emotional Intelligence, as
measured by the MEIS, meets the most essential criteria for a
standard intelligence. Our results illustrated that emotional
intelligence does relate to general intelligence (via its proxy,
verbal intelligence). The results, however, provide only the
roughest idea of the relation between emotional intelligence and
other intelligences. For example, traditional, academic
intelligences can be divided into fluid and crystallized
intelligences, or verbal and performance intelligences, or
divided in many other ways (e.g., Carroll, 1993; Flanagan et al.,
1997; Horn & Noll, 1994). Intelligence researchers will want
to examine emotional intelligence and those various breakdowns in
greater detail. The relation between emotional intelligence and
other potentially similar intelligences such as social
intelligence and personal intelligence, and the like, are
similarly yet-to-be explored. As stated at the outset, any final
choice between emotional intelligence and such alternatives as
social intelligence, will depend upon the relative clarity of
their operationalizations, their relative relations to general
intelligence, and what criteria they predict. It is too early to
make this comparison as of yet. Only one of the competing
intelligences (social intelligence) has been operationalized well
enough (e.g., a minimum of three or four ability tasks) to
compare to emotional intelligence. Other alternative
intelligences, however, such as personal intelligence, could move
in that direction in the future. As alternative intelligences
become operationalized, it will be of interest to see how they
compare. Finally, emotional creativity (Averill & Nunley,
1992) emphasizes generative, divergent thinking rather than the
reasoning and problem solving of emotional intelligence.
Emotional intelligence can be thought of as bearing the same
relation to emotional creativity as general intelligence bears to
general creativity. The intelligence-creativity relations are
likely to be complex, but the retention of both concepts likely
will be useful.
Emotional Intelligence and Other Criteria
A crucial job of the field is to relate internal characteristics
of personality--including abilities such as emotional
intelligence--to other psychological tests, and ultimately, to
criteria in the life space (Mayer, 1998; Mayer et al., 1998). The
test developed here has not yet been correlated with other
personality scales such as the Big Five (McCrae & Costa,
1997), and that would be a desirable future direction. Instead,
we moved modestly into comparing these internal abilities with
actual life criteria: parental warmth, life satisfaction,
psychotherapy, artistic ability, and leisure activities related
to culture. The findings indicate that emotional intelligence is
related to (self-reported) parental warmth and support, and, to a
lesser extent, to life satisfaction. Emotional intelligence was
also related to leisure pursuits including, negatively, to
reading a large number of self-help books. Although these
findings are preliminary, and better criteria are desirable, they
are suggestive of the fact that emotional intelligence will be of
use in predicting particular life criteria.
Future Research
We are presently at the beginning of the learning curve about
emotional intelligence. Many questions remain unanswered. Some
still concern the factorial structure of emotional intelligence:
With the development of more tasks, will there be an additional
factor of emotional expressiveness, or of assimilating emotion?
Are there nonverbal tests that should be developed? Other
questions concern the relation between emotional intelligence and
other intelligences: How highly does emotional intelligence
correlate with social intelligence, or with performance
intelligence, or with spatial intelligence? More generally, how
will it relate to the multitude of traditional cognitive
abilities reviewed by Carroll (1993) and Horn & Noll (1994)?
Many of the questions of greatest interest to people, however,
are those raised (as claims, rather than questions) by members of
the press (e.g., Gibbs, 1995; Goleman, 1995). Specifically, these
claims included that emotional intelligence accounts in some
large part for an individual's success, perhaps more so than
conventional analytic intelligence (IQ). Despite the fact that
certain among these claims appeared in reputable magazines and
newspapers, there has been little or no direct evidence to
support them (Mayer & Salovey, 1997; Mayer, Salovey, &
Caruso, in press). Until the present article, in fact, there has
been no widespread, systematic attempt to understand the
measurement of emotional intelligence as an ability, although
self-report mixed-model scales are proliferating (e.g., Bar-On,
1997). The present results indicate that emotional intelligence
does play some role in everyday life. It is our hope that the
field can move forward employing measures such as the MEIS.
Measures such as the MEIS can provide serious answers to the
questions above, as well as those that will arise in the future.
There are some matters that are clearly important about emotional
intelligence already. Although emotions often have been regarded
with respect in the West, there also exists a widespread negative
view of people who think emotionally (Payne,
1986). Emotional thinkers have been referred to over the
centuries variously as "overly emotional," romantics
(or hopeless romantics), people who think with their hearts
(instead of their heads), people swayed by emotions, or
"biased" by emotions. Such labeling does accurately
capture a kind of person who is overwrought with unthinking
emotionality. What the existence of emotional intelligence tells
us, however, is that there exists another type as well: the
emotional, romantic, thinker-with-a-heart, who is engaged in
sophisticated information processing, and who. in such a manner,
contributes importantly to our lives and culture.
Conclusion
Measures of intelligence focused on verbal and performance
intelligence have been developed over the century. Although
verbal, performance, and other similar intelligences have taken
us far (cf., Ree & Earles, 1992), there has also been a
dissatisfaction with such limited conceptions of mental
abilities. Over the century, many have sought out broader sets of
mental capacities (e.g., Gardner, 1993; Guilford, 1967;
Steinberg, 1988; Thorndike, 1920), or depicted a system of mental
abilities (Detterman, 1986). Emotional intelligence represents,
to us, an important candidate, to enlarge the group on which
general intelligence is based. Perhaps a general intelligence
that includes emotional intelligence will be a more powerful
predictor of important life outcomes than one that does not.
Acknowledgements: The research reported here was supported, in
part, by the University of New Hampshire. We are grateful for the
assistance we received from a number of individuals. Peter Legree
read and commented on this manuscript several times and
contributed substantially to its quality. Scott Formica was also
instrumental in identifying several ambiguities in the near-final
manuscript that we were able to correct. In respect to developing
the MEIS test itself, the music selections used in the test were
composed and recorded by Richard Viard. Graphic designs used in
the test were created by David Silverman and Jeremiah Washburn.
Finally, Amy Van Buren and Heather Chabot conducted a portion of
the data collection. To these and all others who contributed to
this work, we extend our heartfelt thanks.
NOTES
(1.) The Davies et al. (1998) article critiques early scales in
the emotional intelligence literature. The present article was
essentially completed before the Davies et al. work was
published, and so we do not comment specifically on those
authors' criticisms of emotional intelligence scales developed
before this one. Nonetheless, it is our hope that the test
results here will put to rest certain of the Davies et al.
concerns, such as those related to the reliability of emotional
intelligence tests.
(2.) One very different set of criteria, suggested by Howard
Gardner, includes requirements that an intelligence be identified
with a specific brain region or structure and be a culturally
valued mental characteristic. Intelligences that are valid
according to Gardner's criteria alone are definitely worth
studying and may provide information for a next generation of
intelligence tests. Still, intelligences that fit his criteria
but that are indistinguishable from general intelligence at a
behavioral level plainly cannot assist in predicting criteria
such as academic success. For that reason, correlational
approaches remain of the greatest pragmatic concerns for now.
(3.) If two intelligences are entirely unrelated, however, we may
want to raise the question as to whether one of them is a real
intelligence, because mental abilities are generally related to
one another. In fact, the "First Law of Intelligence"
of Guttman and Levy (1991) states that all mental ability
measures are positively correlated.
(4.) If the expert-selected value was "3" on the
five-point scale, responses from 2 to 4 were assigned the value
of 1 (correct). If the expert-selected value was "1,"
then 1-2 would be correct; if the expert value was "5,"
then 4-5 would be correct, etc.
(5.) Simply allowing the Stories task to load on the
Understanding (as well as Perception) moves the RMSEA index to
0.077.
(6.) As with Oblique factors II and III, we reversed the sign of
the hierarchical factor so that a higher score reflected better
ability.
(7.) These two tasks had estimated loadings of 0.51 and 0.59,
respectively, on the assimilation factor, of the oblique
four-factor model.
(8.) Adults and adolescents were compared on two of the eight
stories as six stories were deemed potentially unsuitable to
adolescents, using extremely cautious criteria, due to their
content.
(9.) Several additional scales were administered that had been
rewritten for a younger age group. Reports on the downward
extension of the emotional intelligence test can be found
elsewhere (see Caruso, Van Buren, Mayer & Salovey 1998). Only
those tests that were identical across groups are examined here
because only those are relevant to the developmental hypothesis
examined here.
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Direct all correspondence to: Dr. John (Jack) D. Mayer,
Department of Psychology, Conant Hall, 10 Library Way, University
of New Hampshire, Durham, NH 03824-3567, USA. E-mail: jack.mayer@unh.edu
David R. Caruso Work Life Strategies, New Canaan, CT, USA
Peter Salovey Yale University, New Haven, CT, USA
Article A61231760
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