Can the Magnitude of Mood Congruent Effects Be Predicted by Personality?
Dawn Macaulay & Eric Eich, University of British Columbia
Abstract
Method
Materials that match current mood in emotional valence tend to
receive enhanced processing. Though there is agreement that these
mood congruent (MC) effects are robust, little attention has been paid
to differences between tasks or individuals. Prior research points to
some variability in MC effects across subjects; variability that we
suspected might be accounted for by personality differences.
One hundred participants completed personality questionnaires and
performed a battery of four tasks designed to elicit MC effects.
Subjects performed the tasks on two occasions a few days apart after
experiencing mood manipulations to produce pleasant or unpleasant
moods.
Within subject comparisons revealed significant MC effects for each
task, but little correlation across tasks. Regression analyses showed
different relationships across tasks. Discussion centers on the
importance of these results for understanding mood and memory
relations and suggestions for future research.
Background
Interest in the interplay between emotion and cognition had its
experimental awakenings in the early 1980s (Bower, 1980). Since that
time, there have been a multitude of articles demonstrating that materials
which match one’s current mood in valence receive enhanced processing.
Mood congruent effects may range from enhanced memory for items to
over-reliance on mood matching materials in judgment and decision making
tasks (Forgas & Bower, 2000).
Although MC effects are generally reliable, certain circumstances, such as
use of recognition memory tests, will decrease the likelihood of occurrence.
Current research has focused on specifying these boundary conditions.
One approach has been to examine the role of personality. Typically,
researchers sample a limited range of personality variables and examine
those variables effects in between-subjects designs.
Rusting (1999) and others have demonstrated that personality factors like
neuroticism may interact with mood to influence cognition. Specifically,
researchers have shown that the cognitive performance of those high on a
particular dimension (like neuroticism) seem especially sensitive to one
mood (like sadness) but relatively unmoved by another (like happiness).
Given that mood and personality factors do interact, is there a group whose
cognitive performance is especially influenced by current mood, regardless
of its hedonic value?
 Mood congruent effects imply that some aspect of processing is changed
by an alteration in mood, yet within-subject comparisons are almost nonexistent.
By sampling a wider range of personality factors related to emotional
responsiveness and by use of within-subject comparisons, we set out to
determine whether such a mood sensitive group could be identified and,
more generally, to determine whether personality could predict MC effects.
Genuineness:
Participants:
On average, subjects rated both their moods as more than moderately
genuine. However, pleasant moods were perceived as somewhat more
realistic than unpleasant moods (7.8 vs 7.3, t(98) =2.3, p < .05).
100 individuals (66 women and 34 men, average age 23.3 years)
participated.
Personality Questionnaires:
Subjects completed a battery of personality questionnaires in an individual
session. These questionnaires included the NEO-FFI (Costa & Macrae, 1988)
as a general description of basic personality structure. The remaining scales
were related to some aspect of emotional reactivity [e.g., self-esteem
(Rosenberg, 1965), private and public self-consciousness (Fenigstein,
Scheier, & Buss, 1975), self-concept confusion (Campbell, Trapnell, Heine,
Katz, Lavallee & Lehman, 1996), rumination, reflectiveness, and social
anxiety (Trapnell & Campbell, 1996)] and thus were potentially important to
MC effects.
Mood Manipulations:
Subjects completed a battery of personality questionnaires.
Subjects completed four tasks sensitive to mood in two separate sessions,
once after exposure to a pleasant mood manipulation and once after an
unpleasant mood manipulation.
Every subject was introduced to the matrix in Figure 1, an adaptation of the
Affect Grid (Russell, Weiss, & Mendelsohn, 1989). After reporting baseline
mood, the subject then listened to appropriate selections of classical music
and contemplated a real or imagined personal experience which he or she
had selected to help evoke the desired mood state. Every 5 minutes the
experimenter came into the room and the subject marked a new affect grid.
Once a grid was marked, the experimenter used it to determine readiness to
continue with the rest of the experiment. The tasks were started when a
pleasant mood subject marked any of the squares in the two right-most
columns of the mood matrix, when an unpleasant mood subject checked any
of the squares in the two left-most columns, or when any subject had
attempted the mood induction for 40 minutes.
Upon completion of the last task every subject was completely debriefed
both orally and in writing. As part of this debriefing, they were asked to
provide ratings of the genuineness of both moods, with responses ranging
from 0 (extremely artificial) to 5 (moderately genuine) to 10 (extremely
genuine).
Extremely High Arousal
Event Generation task (EG): Subjects recounted specific personal
past events that were related to each of 12 common concrete neutral
nouns such as CITY and KEY. After generating the 12 events in the final
session, subjects rated the original emotionality of all 24 events on a
scale from -4 (extremely negative) to +4 (extremely positive).
Person Perception task (PP): Subjects read 10 sentence descriptions
of 4 fictional characters with the instructions to form an overall impression
of each character. Subjects rated the characters on 8-point bipolar scales
on dimensions such as shy--self-confident, and dislikable—likable.
Subjective Probabilities task (SP): Subjects made personal
judgments of the future likelihood of positive and negative events by
providing an approximate percentage from 0 to 100 (e.g. The chances
that a person will win a substantial amount of money in a lottery are
about ______).
Mood Ratings:
The average of pre- and post-task Affect Grid ratings are
presented in Figure 2. Subject ratings of current mood differ
significantly and substantially between the pleasant and unpleasant
occasions. On average, the moods instilled by the manipulation
techniques were sustained for each of the four tasks.
Extremely Pleasant
Extremely Unpleasant
Figure 2: Pleasure and Arousal Ratings
Average Pleasure Ratings
4
3
3
2
2
1
1
0
0
-1
-1
-2
-2
-3
-3
-4
-4
EG
Pleasant Mood
Extremely Low Arousal
Average Arousal Ratings
4
BSL
PP
Neuroticism
Repress/Sensitize
Self-Concept Confusion
Negative Affect
Social Desirability
Manifest Anxiety
Self-Esteem*
Agreeableness
Conscientiousness
Rumination*
Social Anxiety*
Factor 1
Factor 2
Factor 3
Factor 4
.82
.82
.76
.75
-.75
.72
-.69
-.66
-.61
.50
.47
-
.46
-
.48
.47
-
-.90
-.82
-.71
-
-
-
-
.81
.73
.69
-
-
-
Factor 2: Closed Mindedness
Reflectiveness
Openness
Private Self-Consciousness
Factor 3: Positive Emotional Reactivity
Affect Intensity
Positive Affect
Extraversion
see also Self-Esteem
Factor 4: Social Self-Consciousness
TAT
SP
Unpleasant Mood
BSL
EG
Pleasant Mood
PP
TAT
SP
Unpleasant Mood
.82
see also Rumination, Social Anxiety
Factor loadings of less than .45 are replaced with a dash.
* denotes multiple loadings of greater than .45 (complex factor).
Table 1. Task Performance
TASK
Pleasant
Unpleasant
Difference
(MC index)
t (df)
p
5.8
-4.3
-7.6
6.8
13.4
11.1
5.39 (99)
4.85 (99)
<.001
<.001
5.8
5.5
0.30
4.42 (91)
<.001
0.4
-0.4
0.8
5.52 (99)
<.001
1.5
-2.2
-1.6
1.5
3.2
3.7
2.55 (97)
2.81 (97)
<.05
<.05
Event Generation vs mean
Positive Events
Negative Events
Person Perception
TAT vs mean
Subjective Probabilities vs mean
Table 2. Correlations among Mood Congruence Indices
TASK
Event Generation
EG Neg
PP
TAT
SP Pos
SP Neg
Positive Events
Negative Events
.85*
-
.08
.13
.00
-.04
.15
.10
-.01
-.06
-
-.03
.16
.06
-
.18^
.00
-
-.02
-
Person Perception
TAT
Subjective Probabilities
Table 4. Regression Equations
Beta
Positive Items
Negative Items
Positive Items
Negative Items
Tasks:
Results
Figure 1: The Mood Grid
Analyses revealed significant MC processing for each task as shown
in Table 1. Subjects tended to recount more pleasant events, evaluate
others more favorably, interpret ambiguous scenes more positively, and
see positive outcomes as more likely when they experienced the
pleasant mood and to do just the opposite under an unpleasant mood.
Although there was clear evidence of mood congruence across tasks,
there was little evidence that the MC effect on one task was related to
the effect on any other. That is, the MC indices were uncorrelated (see
Table 2).
Subjects reported their current mood on the affect grid immediately prior to
and following performance of each task in both sessions.
Effects were calculated within-subjects.
Multiple regression was used to predict the degree of MC effects from
variables such as personality, gender, age and mood.
Mood Congruent Effects:
Factor 1: Negative Emotional Reactivity
Public Self-Consciousness
Thematic Apperception Task (TAT): Subjects viewed four cards from
the TAT and provided a verbal description of each depicted event.
Design Summary
Table 3. Principal Component Analysis of Personality Questionnaires
Mood
Index
Average
Genuineness
Gender
Age
Factor 1
Factor 2
Factor 3
Factor 4
R
R
F
df
p
Event Generation
Positive Event
Negative Event
.18^
.11
.20^
.22*
.17^
.17^
-.01
-.07
.02
-.04
.07
.09
-.07
-.10
-.18^
-.20*
.41
.40
.17
.16
2.26
2.13
(8, 91)
(8, 91)
< .05
< .05
PP
-.03
.10
.02
-.05
.18
.05
.13
-.16
.27
.07
<1
(8, 83)
n.s.
TAT
.17
-.17
.02
.02
-.01
.13
.12
.24*
.34
.11
1.45
(8, 90)
n.s.
-.02
.04
.01
-.15
.05
.05
.08
-.25*
.15
.13
.02
.06
.04
.00
-.03
.08
.17
.37
.03
.14
<1
1.76
(8, 89)
(8, 89)
n.s.
<.10
Task
Subjective
Probabilities
Positive Item
Negative Item
^ p < .10 * p < .05
2
Discussion
^ p < .10, * p<.05
Regression Analyses:
The personality measures were reduced to four factors via principal
components analysis with varimax rotation. The four factor solution is reported
in Table 3.
As performance on the mood congruence tasks was uncorrelated, we
undertook separate regression analyses for each task. We combined an index
of mood, average genuineness ratings, gender, age and the four personality
factors to predict the MC index for each task (see Table 4).
Stronger mood effects on the generation of both positive and negative events
(EG) were predicted by being low in social self-consciousness, by high ratings
of mood genuineness, and by being female.
Mood effects on providing the subjective probability of negative events (SP)
were marginally predicted by age. Younger subjects interpreted these events as
more likely when they experienced unpleasant feelings while older subjects
saw these events as unlikely regardless of their mood.
Large mood differences in the interpretation of TAT cards was most strongly
associated with higher social self-consciousness. Persons who report that they
are concerned about the way others perceive them were likely to show larger
mood effects on the TAT.
Within-subject comparisons revealed significant mood effects on all four tasks.
However, the degree that mood influenced performance on one task was nearly
independent of the effect on any other.
Regression analyses examining personality factors, mood intensity and
genuineness, gender and age produced significant prediction equations for only the
Event Generation task.
Mood congruent memory effects in Event Generation were larger for subjects who
reported highly genuine mood experiences, who were women and who scored low
on social self-consciousness. People who reported that they were less concerned
about the way others evaluate them were likely to show the largest difference in their
performance between the pleasant and unpleasant moods. If we consider that
subjects described events aloud to an experimenter, it becomes clear that the Event
Generation task does involve a social element in its performance. Furthermore, this
pattern runs counter to what we would expect if demand characteristics are
responsible for producing these differences.
In contrast, larger mood differences in the interpretation of TAT cards was most
strongly associated with higher social self-consciousness. This suggests that these
apparent mood effects may actually be response to experimental demand.
Younger subjects tended to show MC effects when estimating the likelihood of
negative items on the Subjective Probabilities task whereas older subjects viewed
negative events as unlikely regardless of mood.
Our research suggests that, though MC effects have been consistently
demonstrated across tasks, the underlying phenomenon may vary widely. Future
research into personality, mood, and cognition will need to focus more directly on
task variables, which should allow greater specification of the mechanisms producing
MC effects.