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Journal of Personality and Social Psychology
2000,
Vol. 79, No. 4, 644-655Copyright 2000 by the American Psychological Association, Inc.
0022-351<M»/$5.00 DOI: I O.1037//O022-3 514.79.4.644
Emotional Experience in Everyday Life Across the Adult Life Span
Laura L. Carstensen
Stanford UniversityMonisha Pasupathi
University of Utah
Ulrich Mayr
University of OregonJohn R. Nesselroade
University of Virginia
Age differences in emotional experience over the adult life span were explored, focusing on the
frequency, intensity, complexity, and consistency of emotional experience in everyday life. One hundred
eighty-four people, age 18 to 94 years, participated in an experience-sampling procedure in which
emotions were recorded across a
1-week
period. Age was unrelated to frequency of positive emotional
experience. A curvilinear relationship best characterized negative emotional experience. Negative emo-
tions declined in frequency until approximately age 60, at which point the decline ceased. Individual
factor analyses computed for each participant revealed thai age was associated with more differentiated
emotional experience. In addition, periods of highly positive emotional experience were more likely to
endure among older people and periods of highly negative emotional experience were less stable.
Findings are interpreted within the theoretical framework of socioemotional selectivity theory.
Emotions are central to human functioning, guiding thought and
action from the earliest days of life (Frijda, 1988). In recent years,
research has revealed much about the astonishing developmental
gains made early in life concerning emotional differentiation (e.g.,
Camras, Sullivan, & Michel, 1993) and regulation (e.g., Rothbart
& Ahadi, 1994). The social nature of emotion is evident through-
out this literature. It appears that early on, regulation of emotion is
situated outside of the individual, with caregivers playing a pri-
mary role in soothing, exciting, comforting, and otherwise influ-
encing infants' emotions. Gradually, however, regulatory pro-
cesses are internalized; cognitive appraisals of the emotional
significance of environmental stimuli begin to influence emotional
responses (Lazarus, 1991). Although far less is known about the
developmental course of emotional experience and regulation in
adulthood, it is clear that successful regulation of emotion is
central to functioning in interpersonal relationships, coping with
life's hardships, and optimizing mental health.
We expect that part of the reason emotional development was
not studied in adulthood until relatively recently relates to long-
held presumptions that emotional functioning in later life parallels
biological and cognitive functioning in adulthood and old age,
namely leveling in late adolescence and early adulthood, remain-
Laura L. Carstensen, Department of Psychology, Stanford University;
Monisha Pasupathi, Department of Psychology, University of
Utah;
Ulrich
Mayr, Department of Psychology, University of Potsdam, Potsdam, Ger-
many; John R. Nesselroade, Department of Psychology, University of
Virginia.
This research was funded by National Institute on Aging Grant
RO1AG08816. We thank Susan T. Charles and Helene Fung for their
criticisms of earlier versions of this article.
Correspondence concerning this article should be addressed to Laura L.
Carstensen, Department of Psychology, Jordan Hall, Stanford University,
Stanford, California 94305-2130. Electronic mail may be sent to
Uc@psych.stanford.edu.
ing reasonably stable in midlife, and becoming dysregulated and
rigid in old age (cf. Bromley, 1990). Yet, evidence for emotional
degradation in adulthood is hard to come by. On the contrary, a
small but growing literature on the adulthood course of emotion
paints a distinctly positive picture and suggests that improvements
in emotional functioning may continue well into middle-age and
perhaps old age (Carstensen & Charles, 1999). Older as compared
with younger adults, for example, display increasing complexity
in mental representations, infused by affect and subjectivity
(Labouvie-Vief, DeVoe, & Bulka, 1989; see also Isaacowitz,
Charles, & Carstensen, 1999); report better emotional regulation
(Gross et al., 1997; Labouvie-Vief, Hakim-Larson, DeVoe, &
Schoeberlein, 1989; Lawton, Kleban, & Dean, 1993); display
well-preserved expressive systems (Levenson, Carstensen, Friesen, &
Ekman,
1991;
Tsai, Levenson, & Carstensen, in press; Malatesta &
Kalnok, 1984); and are relatively happy (Diener & Diener, 1996)
and satisfied with life (Herzog & Rodgers, 1981). In a recent
survey, Mroczek and Kolarz (1998) found that age was associated
with a self-reported increase in positive affect and a decrease in
negative affect. Studies also suggest that the salience of emotion
may increase with age, such that emotional material is better
remembered (Carstensen & Turk-Charles, 1994), is more central in
cognitive representations of other people (Carstensen & Fredrick-
son, 1998; Fredrickson & Carstensen, 1990), and is more centrally
involved in problem solving about interpersonal matters
(Blanchard-Fields, 1997).
Two life span developmental theories, which have instigated
much of the empirical work described above, suggest that emo-
tional development continues in adulthood. Both theories draw
heavily on the idea that because age and experience are inextrica-
bly intertwined and because experience and knowledge about
emotions play an important role in emotion regulation, aging may
be associated with emotional maturation. Labouvie-Vief and her
colleagues have contended that cognitive functioning becomes
infused with affectivity in later adulthood such that peak intellec-
644
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EMOTION AND AGE645
tual performance occurs in middle age. According to this theory,
children must suppress idiosyncratic affective judgments about
collectively shared, symbol systems so that they acquire uniform,
culturally consistent representations of the world (Labouvie-Vief
& DeVoe,
1991;
Labouvie-Vief, Hakim-Larson, et
al.
1989). Adult
intellectual development, in contrast, involves the reintegration of
subjective information into existing knowledge structures. Theo-
retically, this increased complexity in cognitive operations is as-
sociated with increasingly more complex and adaptive emotional
responses and perhaps with greater flexibility in coping with new
life events (Diehl, Coyle, & Labouvie-Vief, 1996).
A second theory relevant to emotional functioning in adulthood
is socioemotional selectivity theory (Carstensen, 1993, 1995;
Carstensen, Gross, & Fung, 1997; Carstensen, Isaacowitz, &
Charles, 1999). Although this theory also acknowledges experi-
ence as an important factor in emotional development, it focuses
on perceived time left in life rather than past experience. The
theory contends that the distinctly human ability to consciously
and subconsciously monitor time plays a fundamental role in
motivation and emotion, providing the structure within which
goals are set, pursued, and evaluated. Because mortality places the
ultimate constraint on time, chronological age is associated with
changes in goals. Essentially, the theory contends that two primary
trajectories of social motives operate throughout life: the emotion
trajectory and the knowledge trajectory. The former is character-
ized by motives to achieve emotional satisfaction and meaning, the
latter by motives to acquire new information and to achieve in
domains that are relevant to successful adaptation in the future
(e.g., educational and occupational domains). The central change
in adulthood is a shift in the salience of social goals. Younger
adults, having much to learn and relatively long futures for which
to prepare, are motivated by the pursuit of knowledge—even when
this requires that emotional well-being be suppressed. For older
adults, the reverse trend appears. Facing relatively shorter futures
and having already accrued considerable knowledge about others,
older adults prioritize emotional goals because they are realized in
the moment of contact rather than banked for some nebulous future
time.
The theory stresses that age does not entail the relentless pursuit
of happiness but rather the satisfaction of emotionally meaningful
goals,
which entails far more than simply feeling good. Finding
meaning in existing relationships, even conflictual ones, emerges
as a central task in later life. Emotional experience is subsequently
expected to be more complex, and the experience of mixed emo-
tions,
more frequent. In short, socioemotional selectivity theory
suggests that constraints on time directly influence emotional
experience such that emotional states are increasingly mixed.
Whether pleasure or joy, sadness or pain, knowledge that an
experience will soon end changes the emotional experience
itself.
Rather than simply prompting negative emotions related to antic-
ipated loss, moments are savored, appreciated both for what they
are and for their temporal fleetingness.
Despite these relatively optimistic empirical and theoretical
pictures, well-documented declines in later life leave an uneasiness
that positive portrayals of emotion in later life may be overblown.
First, much of the literature on emotion, and to the best of our
knowledge all of the literature on emotion regulation, has been
based on global self-reports, a practice that may be particularly
precarious when questions elicit older adults* implicit theories
about their own maturation (McFarland, Ross, & Giltrow, 1992).
That is, if research participants believe that people "should" con-
trol their emotions better as they get older, they are likely to say
that they do so. Moreover, global evaluations of life are highly
cognitive and involve comparisons with the past and the present, as
well as with idiosyncratic standards (Schwarz, Park, Knaueper, &
Sudman, 1999). Subsequently, such evaluations are susceptible to
influence by cohort-specific experiences and mores (Elder, Odum,
& Hareven, 1994), as well as by memory of past events (Levine &
Bluck, 1997). A second important concern is that even though
older people may be able to respond well to emotional tasks in
laboratory settings, emotional dysregulation may be evident in less
structured settings.
The purpose of the present study was to assess the frequency,
intensity, and the complexity of emotional experiences as they
occur in everyday life. Our general hypothesis was that relative to
younger people, older people would show evidence of improved
emotion functioning, including more differentiated emotional ex-
periences and better regulation of their emotional states. By re-
peatedly sampling the same participants over time, we were able to
examine the frequency and intensity with which positive and
negative emotions are experienced, as well as the stability of
negative and positive states over time and the complexity of
emotional experience. Below we elaborate four experimental hy-
potheses about age differences in emotional experience.
Hypothesis 1. Older people experience negative emotions less fre-
quently than younger adults and experience positive emotions just as
frequently as younger adults. According to socioemotional selectivity
theory, increasing age is associated with greater appreciation of life
and greater investment in emotionally meaningful social relationships.
The theory predicts that this emphasis on emotionally meaningful
goals improves emotional experience in everyday life.
Hypothesis 2. The intensity of positive and negative emotional expe-
rience is comparable across age groups. Socioemotional selectivity
theory predicts that goal-directed behavior aimed at obtaining emo-
tionally meaningful goals results in less frequent negative emotions.
However, once negative emotions are elicited, the theory makes no
claim about the intensity of the experience.
Hypothesis 3. Older as compared with younger adults show differen-
tial stability of emotional experience such that positive states are
maintained longer and negative states are terminated more quickly.
Surveys that ask people how well they regulate their emotions suggest
that where there are differences, older people report greater control. In
this study, we obviate global judgments about emotion control by
examining whether positive states last longer and negative states
persist for shorter periods in older adults.
Hypothesis 4. Emotional experience is more complex in older as
compared with younger adults. Because the pursuit of emotionally
meaningful goals often entails mixed emotions, we anticipate a more
complex dimensional structure to the emotional experience of older
adults.
Method
Sample
One hundred eighty-four African American and European American
research participants, ranging in age from 18 to 94 years of age, (M
—
55,
SD = 20.4), were recruited by a survey research firm from the San
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646CARSTENSEN, PASUPATHI, MAYR, AND NESSELROADE
Francisco Bay area to participate in an experience-sampling study of
emotional experience. Ethnic composition of the sample was restricted to
these two ethnic groups rather than sampling the ethnic diversity of the Bay
area so that sufficient numbers of participants in subsamples would allow
for statistically meaningful analyses. Thirty-one percent of the sample were
African American; the remaining 69% were European American. Forty-
one percent of the sample comprised blue-collar workers, and 59% were
white-collar workers; 54% of the participants were women, and 46% were
men. Education ranged from 5 to 22 years (M = 15.0, SD = 2.7). Gender,
blue-
or white-collar status, and race were distributed evenly across age. As
shown in Table 1, the sample was diverse along many dimensions.
Measures
Although our principal aim was to sample emotional experiences in
everyday life, we also assessed health, personality, and verbal fluency
because each of these factors may influence at least some features of
emotional experience or performance on the sampling task (see, e.g.,
McCrae & Costa, 1991; Watson & Pennebaker, 1989).
Emotion sampling booklet. On a 7-point scale that ranged from 1 (not
at all) to 7 (extremely), participants indicated the degree to which they were
feeling each of 19 emotions or feeling states. Ratings greater than 1, thus,
indicated that the emotion was present and, consequently, both frequency
and intensity are captured in a single rating. The list of emotions included
anger, guilt, pride, sadness, happiness, fear, accomplishment, shame,
amusement, anxiety/worry, joy, contentment, irritation, frustration, disgust,
interest, embarrassment, boredom, and excitement. An other blank was
also provided on the response sheet to allow participants to record addi-
tional emotions not included on the sampler. A week's supply of emotion
response sheets were bound in a 5 in. by 5 in. pad for easy transport during
the week of data collection.
Cornell Medical Index Health Questionnaire (CMI). The CMI (Brod-
man, Erdmann, &
Wolff,
1949) is a widely used 195-item index of physical
and mental health problems that allows the computation of a general health
index as well as subscales that represent functioning in specific organ
subsystems and symptoms associated with specific psychological syn-
dromes. Participants report whether they experience each of the 195
symptoms. We computed two broad indexes from the CMI, one represent-
ing the total number of recent symptoms of physical illness and the other
representing the total number of recent symptoms of mental illness. An
example of a physical illness symptom item is "Are you troubled by
constant coughing?" A sample mental illness symptom item is "Do you
have to be on your guard even with your friends?"
Category instance fluency (Undenberger, Mayr, & Kliegl, 1993). As a
measure of verbal fluency, participants were asked to name as many
different kinds of animals as possible in 90 s. This test shows a strong
relationship to general intellectual ability and has been extensively used
with older adults.
Adjective checklist (John, Donahue, & Kentle, 1991). This is a list
of 54 adjectives presented in the form of self-descriptive sentences. Ad-
Table 1
Demographic Characteristics of the Sample
CharacteristicSample description
Age (in years)
Education (in years)
Sex
Ethnicity
Socioeconomic status
Marital status
Number of children
M = 55.0, SD = 20.4, range = 18.0-94.0
M = 15.0, SD = 2.7, range - 5.0-22.0
54%
women, 46% men
31%
African American, 69% European American
41%
blue-collar, 59% white-collar
26%
single, 43% married, 19% widowed, 13%
divorced
M = 1.6, SD = 1.6, range = O-9
jectives representing all of the Big Five factors of personality are repre-
sented. Participants indicate whether a given statement describes them by
placing a check next to it. Example items include "I am talkative" and "I
can be somewhat careless." We computed summary scores for each of the
Big Five factors: Neuroticism, Extraversion, Openness to Experience,
Agreeableness, and Conscientiousness.
Procedure
Following initial screening by the survey research firm to ensure that
participants met recruitment criteria for the project, participants were
scheduled at their convenience for an initial interview at Stanford Univer-
sity or at the offices of the San Francisco-based survey research firm that
did the initial recruiting. Participants were informed that the purpose of the
study was to examine feelings in everyday life. After obtaining informed
consent and obtaining background information, such as education level, the
following measures were administered: Category Instance Fluency, CMI,
and the Adjective Checklist.
At this point, participants were provided with detailed instructions about
the experimental procedures, familiarized with the operations of the elec-
tronic pager (e.g., how to set it for motion or sound, how to indicate that
they received the page by pushing a button, etc.), and instructed to
complete the emotion response sheets each time they were signaled. Next,
two practice trials were administered while participants were still in the
laboratory so that responses could be reviewed with the experimenter prior
to beginning the study. The participant was left alone; the interviewer
activated the pager from another room; the participant completed the
questionnaire; and, on returning to die room, the interviewer reviewed the
participant's responses, clarified any apparent mistakes, and answered
questions.
During the ensuing week, participants were paged five times each day.
Paging times were determined by random selections from all possible
10-min intervals between 9 a.m. and 9 p.m. The only constraint on
sampling times was that participants were not sampled more than once
within a single 20-min period. At the end of each day, participants returned
the day's completed response sheets by mail in pre-addressed, stamped
envelopes, allowing us to monitor responses during the data collection
period and assuring at least rough adherence to the experimental protocol.
Participants were encouraged to telephone the laboratory if procedural
questions or problems arose and periodic calls were made to participants as
well to ensure that the highest quality data were obtained.
After participants completed the week-long experience-sampling data
collection, they returned to the laboratory for a follow-up interview, at
which time they returned the pagers and were debriefed. Participants were
paid $125 for their participation.
Results
We organize our results into four sections. The first section
describes data reduction and preliminary analyses. The second
section of the results reports findings from analyses that examine
age differences in the frequency and intensity of emotional expe-
rience, controlling for individual differences that may influence
emotional experience (Hypotheses 1 and
2).
In this section we also
examine the consistency of age differences across ethnic, gender,
and socioeconomic lines.
The third section of the results addresses emotion regulation
(Hypothesis 3), and the fourth section concerns the complexity of
emotional experience (Hypothesis 4). In these latter two sections,
hypotheses are tested on the basis of within-individual variability
that allowed us to examine emotional complexity and the temporal
experience of emotional experiences. Here, too, we examined the
consistency of effects across ethnicity, gender, and class. Because
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EMOTION AND AGE647
our measure of differentiation was novel, we explored its relation-
ship to other measures, such as personality, mental health, and
intelligence.
Data Reduction and Preliminary Analyses
Ratings of 19 emotions were obtained on 35 separate occasions,
generating a total of 665 experience sampler data points per
participant. Data were reduced in the following way. Frequency
was represented as the proportion of times across the 35 sampling
points that a participant acknowledged that he or she experienced
the emotion to some degree, namely, ratings were greater than 1.
Intensity of emotional experience was calculated by computing the
average rating for each felt emotion (see Schimmack & Diener,
1997,
for a discussion of this kind of decomposition). Table 2
presents the average frequencies and intensities for specific emo-
tions across the entire sample. As can be seen, people endorsed
negative emotions relatively infrequently and positive emotions
relatively frequently, a finding consistent with earlier experience
sampling studies (Diener & Diener, 1996). For each specific
negative emotion, some people indicated that they did not expe-
rience the emotion on any of the sampled occasions; however,
only 2 individuals failed to endorse any negative emotions at all
during the experience-sampling period.1
The above procedure resulted in each participant having 38
scores indicating the frequency and intensity with which he or she
reported 19 emotions over the sampling period. To reduce the
number of statistical tests in our analyses and to increase the
reliability of our measures, we collapsed these 38 scores into four
Table 2
Means and Standard Deviations of Frequency and intensity
of Experiencing Specific Emotions for the Entire Sample
Emotion
Anger
Sadness
Fear
Disgust
Guilt
Embarrassment
Shame
Anxiety
Irritation
Frustration
Boredom
Happiness
Joy
Contentment
Excitement
Pride
Accomplish
Interest
Amusement
Frequency"
M
.20
.28
.20
.21
.17
.17
.14
.44
.39
.39
.30
.89
.78
.90
.69
.70
.74
.88
.73
SD
Negative
.24
.30
.28
.25
.27
.27
.25
.32
.28
.28
.32
Positive
.17
.27
.16
.32
.34
.27
.19
.27
M
3.31
3.31
3.13
3.46
2.99
3.23
2.93
3.28
3.39
3.40
3.38
4.35
4.10
4.40
3.98
4.09
4.40
4.55
3.95
Intensity
SD
0.91
1.05
1.04
1.09
0.90
1.09
0.93
0.93
0.90
0.86
0.95
0.97
1.02
1.00
0.94
1.10
1.00
0.99
0.86
n
147
159
138
157
128
131
112
176
177
176
149
184
181
1S4
181
180
184
184
182
indicators of emotional experience: average frequency of negative
emotions, average frequency of positive emotions, average inten-
sity of negative emotions, and average intensity of positive emo-
tions.
Thus, the average frequency of experiencing positive emo-
tions reflects the average of the proportion of times a person
experiences each of the positive emotions. Because there is some
debate about the dimensionality of emotional experience and be-
cause the 38 scores were derived from only 19 ratings, this
aggregation was verified by factor analysis.
We conducted a descriptive factor analysis using varimax rota-
tion with mean substitution for missing values. This revealed that
frequency and intensity scores for the emotions were reasonably
well-characterized by a four-factor solution (69% of the total
variance was accounted for by this solution). Although six factors
with eigenvalues above 1 could be extracted, Factor 5 had high
loadings only for the intensity of Fear (.60) and of Shame (.80),
whereas only the intensity of Boredom loaded significantly on
Factor 6 (.80). Together Factors 5 and 6 accounted for only an
additional 5% of variance in the data. Inspection of the scree plot
showed a clear dissociation of the latter two from the first four
factors. Thus, a four-factor solution was used (as per Tabachnik &
Fidell, 1989). This solution clearly reflects the frequency and
intensity with which positive and negative emotions were experi-
enced and was reliable both when cases with missing values were
deleted and when oblique rotation was used. Table 3 presents the
varimax rotated factor loadings of frequency and intensity vari-
ables on the four factors as well as eigenvalues and variance
accounted for by each factor. As shown in Table 3, Factors
1
and 2
reflect the frequency and intensity of negative affect, respectively.
Factors 3 and 4, respectively, represent the frequency and intensity
of positive affect.2
Hypotheses 1 and 2: Age Is Related to the Frequency but
not the Intensity of Emotional Experience
We hypothesized that the frequency of negative, but not posi-
tive, emotional experience decreases across age cohorts, and we
hypothesized that intensity of emotion would not distinguish age,
*n = 184.
1 Findings remain essentially unchanged when very high and very low
scorers are eliminated.
2 Oblique rotations suggested some relationships between the factors,
with the factors for intensity of positive and intensity of negative emotions
correlated at .34, and the factors for intensity and frequency of positive
emotions also correlated (r = .30). Frequency of experiencing negative
emotions and frequency of experiencing positive emotions were also
correlated, though less strongly (r = .21). No other interfactor correlations
were above .17. Relationships between the aggregate scores (not factor
scores) used in our analyses mirrored these oblique factor correlations, and
were somewhat stronger. Intensity of negative emotion and intensity of
positive emotion showed a moderate relationship (r = .40, p < .01).
Frequency and intensity of positive emotion were also correlated (r
—
.42,
p < .01), as were frequency of positive and frequency of negative emotions
(r — .29, p < .01). All other correlations were much lower (maximum
absolute value r = .16). Both interfactor correlations and correlations
between our variables imply the existence of individual differences in
emotional intensity and in the general frequency with which emotions are
experienced. These relationships (between the frequency and intensity of
positive and negative emotion) did not vary as a function of age at this, the
between-subjects, level.
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648CARSTENSEN, PASUPATHI, MAYR, AND NESSELROADE
Table 3
Varimax Rotated Factor Loadings for Frequency and Intensity
of
Positive
and Negative Affect
Emotion
Anger
Sadness
Fear
Disgust
Guilt
Embarassment
Shame
Irritation
Frustration
Anxiety
Boredom
Happiness
Joy
Contentment
Excitement
Pride
Accomplishment
Amusement
Interest
Eigenvalues
% of Variance
Anger
Sadness
Fear
Disgust
Guilt
Embarassment
Shame
Anxiety
Irritation
Frustration
Boredom
Happiness
Joy
Contentment
Excitement
Pride
Accomplishment
Amusement
Interest
Eigenvalues
% of Variance
NE
frequency
PE
intensity
Frequencies
.86
.85
.87
.88
.90
.88
.92
.86
.85
.78
.65
.06
.13
.02
.27
.24
.14
.19
.09
9.34
25
-.04
-.04
-.01
.02
-.04
.14
.06
-.09
-.14
-.14
-.17
.16
.32
.02
.30
.22
.16
.26
.07
8.35
22
Intensities
-.09
.03
-.05
-.15
-.01
-.11
-.07
.17
.06
.14
-.04
-.07
.03
-.24
-.01
-.02
-.07
-.05
-.07
9.34
25
.18
.20
.07
.08
.12
.12
.07
.19
.10
.03
.15
.84
.92
.76
.84
.75
.78
.81
.72
8,35
22
PE
frequency
.09
.11
.08
.01
.11
.09
.10
.06
.09
.13
.22
.85
.79
.79
.77
.76
,85
.80
.79
5.60
15
-.05
-.02
-.13
-.08
-.15
-.02
.01
-.07
-.07
-.03
-.08
.34
.04
.21
.07
.18
.33
.14
.32
5.60
15
NE
intensity
.03
-.03
.03
.03
.00
-.08
.01
-.04
-.03
-.05
-.17
-.12
-.02
.00
-.11
-.13
-.11
-.18
-.14
2.00
5
.66
.67
.66
.64
.56
.64
.53
.72
.83
.84
.45
.18
.16
.15
.22
.16
.27
.30
.22
2.00
5
Note. NE = negative emotions; PE - positive emotions. Boldface indi-
cates factor loadings above .40.
with the exception of excitement. Four regression analyses were
computed to explore relationships between the frequency and
intensity of experiencing positive and negative affect and age.
Both linear and quadratic age trends were explored. No significant
age effects were obtained for the frequency or the intensity of
positive affect, nor were there age effects for the intensity with
which negative affect was experienced, all Fs(l, 181) < 1.0, ps >
3.
However, as predicted, age was associated with the frequency
of experiencing negative affect F(2, 182) - 6.0, p < .01. This
effect has both a linear and a nonlinear component, as shown by
the joint effects of linear age, B = -.02, 0 = -1.47, z(157) =
-3.42,
p < .01, and age squared, B = .0001 £ = 1.41,
r(157) = 3.30, p < .01. Just to illustrate these effects in a more
intuitive way, simple correlations between age and frequency of
negative emotion before and after age 60 were computed. These
correlations reveal a decrease in the frequency of negative emo-
tions from 18 to 60 years (simple r = —.29, p < .01). After 60
years,
the decrease ceases (r = .14, ns) and characterizes the
pattern from age 60 onward.3 This effect is shown in Figure 1.
Our next step was to explore the robustness of age as a predictor
of emotional experience in conjunction with factors known to
influence emotions. We added the following predictors to the
regression equations described above: personality (Neuroticism,
Extraversion, Openness to Experience, Agreeableness, and Con-
scientiousness), health (self-reported mental health and
self-
reported physical health), and demographic variables (ethnicity,
gender, and socioeconomic status). In addition, because intellec-
tual functioning reliably declines with age, we included the mea-
sure of general intellectual ability (i.e.. Category Instance Flu-
ency).
All variables were entered simultaneously.
The results, displayed in Table 4, show that age findings were
maintained even with these additional variables included. Con-
cerning the frequency of negative emotions, more mental health
symptoms and higher neuroticism were additionally associated
with higher frequencies of negative emotion. For the frequency of
positive emotions, African Americans and those who were more
open and agreeable reported experiencing positive emotions more
frequently.
Concerning the intensity of emotions, negative affect was pre-
dicted by gender and socioeconomic status as well as by mental
health symptoms, with women, blue-collar workers, and individ-
uals who were more extraverted endorsing more intense negative
affect. Intensity of positive affect was associated with ethnicity and
extraversion, with African Americans and more extraverted indi-
viduals endorsing more intense positive affect. We also explored
the consistency of the pattern of age effects and noneffects in
predicting affective experience across gender, race, and socioeco-
nomic status by looking for interactions between age and these
demographic factors in predicting our emotional experience vari-
ables.
There were no interactions for age and gender, socioeco-
nomic status, or race in predicting any of these facets of emotional
experience.
3 We chose 60 as an illustrative point because it represents approxi-
mately the bottom of the line depicted in Figure 1. Choosing other age
cutoffs, such as 40,50, or
65,
results in differences in the magnitude but not
the pattern of relationships. To be concrete, the correlations for the younger
portion of the sample are —.46, —.24, —.29, and —.24, respectively, for
ages 40, 50, 60, and 65 years. The same correlations for the older portion
of the sample are .04, .17, .14, and .19. In no case is the age relationship
near zero for the younger portion of the sample—a decline is always seen.
What happens after the selected cutoff
is
somewhat more variable, ranging
from zero relationships to small positive correlations with negative emo-
tion. However, again, these are meant only to illustrate the pattern detected
in the regression analyses.
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EMOTION AND AGE649
Table 4
Emotional Experience, Age, and Other Variables
Predictors
Demographic variables
Race
Sex
Socio-economic status
Health
Physical
Mental
Personality
Neuroticism
Extraversion
Openness
Agreeableness
Conscientiousness
Verbal intelligence
Linear age
Quadratic age
Overall K2
Regression, F(13, 129)
r
.07
-.04
.03
.11
.28**
.20**
.01
.03
-.11
-.18*
-.02
-.08
-.04
.20
2.50**
NA Frequency
P
.11
-.01
-.07
.00
.17t
-20t
-.01
-.07
.05
-.09
-.03
-1.30*
1.25*
B
.06
-.01
-.03
.0001
.01
.17
-.01
.09
.05
-.10
.0004
-.01
.0001
r
.17*
-.13t
.03
.01
.06
-.11
22**
.12
.16*
.17*
-.04
.07
.06
.14
1.60t
PA Frequency
.21*
-.13
.02
-.06
.06
.08
.11
•15t
.17f
.05
.04
.39
-.38
B
.10
-.05
.00
-.001
.002
.70
.90
.18
.19
.05
.001
.004
.00
r
.16*
.18*
.25**
.16*
.22**
.03
.11
.00
.01
-.02
-.02
-.06
-.06
.17
2.00*
NA Intensity
IS
.12
.18*
.15
.02
.17f
.04
.17*
-.06 -
.04
.02
-.02 -
.37
-.47 -
8
.19
.27
.23
.002
.02
.10
.50
.24
.15
.06
.001
.01
.0001
r
.37**
.07
.15*
.04
.03
-.24**
.29**
.14t
.24**
27**
-.10
.06
.05
.28
4.00**
PA Intensity
.32**
.05
.12
-.04
.04
-.09
.20*
.11
.11
.09
-.02
.17
-.21
B
.62
.09
.22
-.003
.005
-.29
.69
.51
.53
.38
-.002
.007
.00
Note. NA = negative affect; PA = positive affect. Being female, being blue-collar, and being African American are represented by larger values.
tp < .10 (marginally significant). *p < .05. ** p < .01.
Finally, we looked specifically at age differences in the intensity
of excitement. Contrary to our hypothesis of reduced intensity of
excitement given the literature reviewed above, once again we
failed to reveal a significant relationship between age and the
intensity with which excitement was experienced, B =
— .001 J3
=
.08,1(182) = 1.1, p > .25.
Hypothesis 3: Compared With Younger People, Older
People Better Regulate Emotional Experience
We operationalized emotion regulation as the maintenance of
desirable emotional states (defined as those where the individual
.341
£ .32
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M .30
S-28
"8
g .26
u.
feels more positive or less negative affect than usual) and the
cessation of undesirable emotional states (defined as states where
the person is feeling less positive or more negative than
usual).
The
former reflect adaptive aspects of emotional stability, and the latter
reflect adaptive aspects of emotional lability. To test Hypothesis 3,
we computed four scores that reflect these four aspects of emotion
regulation.
For each sampling occasion, participants were classified as high
on positive affect relative to their own idiosyncratic ally calculated
mean across all sampled situations or as below or equivalent to
their own idiosyncratically calculated mean across situations. A
I18-3435-64
Age in Years65-94
Figure 1, Frequency of negative affect across the life span.
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650CARSTENSEN, PASUPATHI, MAYR, AND NESSELROADE
similar split was made for negative emotional states. We then
computed four conditional probabilities: (a) maintaining high pos-
itive states: the probability that, given participants were more
positive than average on Occasion 1, they would be more positive
than average on the subsequent sampling occasion; (b) maintain-
ing the absence of highly negative states: the probability that,
given participants were less negative than average on Occasion 1,
they would be less negative than average on the subsequent occa-
sion; (c) moving from
low
positive states to
high
positive states: the
probability that, given participants were less positive than average
at Occasion 1, they would be more positive than average at
Occasion 2; and (d) moving from highly negative states to low
negative states: the probability that, given participants were more
negative than average at Occasion 1, they would be less negative
than average on the following occasion. Note that these scores are
not necessarily related to the overall frequencies of experiencing
positive or negative emotions, because these scores reflect some-
thing about the temporal distribution of positive and negative
states.
Also, note that these scores do not simply reflect stability of
positive or negative states, but rather, adaptive features of stability
and adaptive features of lability.
Age-related patterns were reasonably positive. Older men and
women showed greater stability of highly positive states (r = .17,
p < .05), and this pattern was consistent across all gender, eth-
nicity, and socioeconoraic groups. Age was also correlated with
stability of low negative states (r — .20, p < .001). Age was
negatively, though not significantly, correlated with moving from
a low positive to a high positive state (r =
—.13,
p < .11). There
were no quadratic trends for age and these effects were constant
across genders, ethnicities, and socioeconomic status groups. Fi-
nally, age was uncorrelated with the likelihood of moving from a
highly negative state to a low negative state (r = .04, ns). How-
ever, here a quadratic trend was present. Together, linear age (B =
.014,
0 = 1.47, p < .002) and quadratic age (B -
-.0001,
/3 =
—1.44,
p < .002) accounted for 6% of the variance in the likeli-
hood of moving from high negative states to low negative states.
This pattern was consistent across both ethnicities and socioeco-
nomic status groups, but did appear to vary by gender (Linear
Age X Gender interaction: A*2 = .03, &F = 6.7, p < .02).
Examining the regression equation separately for men and women
revealed that the pattern of age effects (linear and quadratic) was
identiqal for both genders, but the magnitude was lower for women
(overall R2 = .0(5) than for men (overall J?2 = .13). In both cases,
however, the age regression attained statistical significance. To get
a feel for what these results suggest, we again computed correla-
tions between age and the lability of highly negative states sepa-
rately for those under 60 (r = .30, p < .002) and those over 60
(r =
—
.15,
p > .19). Thus, older adults in our sample, up to some
age,
were less likely to remain in a highly negative state over
occasions than were younger adults. At some point in adulthood,
this trend reverses, although perhaps not significantly,4
To summarize, then, older adults were more likely to maintain
highly positive states and were more likely to maintain the absence
of negative emotional states. Thus, the stability indicators suggest
greater stability of emotional experience in older adults for the
adaptive portions of emotional stability (i.e., one could also be
very stable by being continuously very angry). This raises the
question of whether older adults are simply more stable in general.
This can be examined by computing a phi correlation for positive
emotion and for negative emotion. This is equivalent to a cross-
lagged correlation but applied to the categorical states (above or
below one's idiosyncratic mean) that we defined for this analysis.
These correlations arc instructive. For positive emotions, small
age-associated increases in stability (whether of low or high pos-
itive states) are evident (r =
.17,
p < .02). This is not the case for
negative emotions (r =
.11,
p > .15).
Finally, the curvilinear pattern of results obtained for lability in
highly negative states with age raises the possibility that this kind
of lability accounts for the age differences observed in the fre-
quency of negative emotions. Note that this is not necessarily the
case.
Older and younger adults could have different frequencies of
negative emotions without those emotions occurring in temporally
linked ways. However, if older adults are moving out of negative
states more quickly than young adults (at least up to some point in
adulthood), this might mean that older adults' better emotion
regulation, as assessed here, accounts for age differences in the
frequency of negative emotions. We examined this by computing
a hierarchical regression predicting the frequency of negative
emotion (from Hypothesis 1 above). The probability of moving
from highly negative to low-negative states was entered as the first
predictor, after which we examined whether age (linear and qua-
dratic) made any additional significant contribution to the equa-
tion. This analysis showed that once lability of highly negative
states was entered, age (both linear and quadratic) contributed an
additional 2% of the variance to predicting the frequency of
negative emotion F(2, 179) = 2.3, p = .10. Thus, changes in the
frequency of negative emotion with age may be interpreted as
stemming from changes in the lability of highly negative states.
Hypothesis 4: Age Is Associated With the Complexity of
Emotional Experience
To test Hypothesis 4, we computed the eigenvalues of each
individual's 19 X 19 emotion ratings correlation matrix on the
basis of his or her 35 occasions of measurement. We took as an
index of differentiation the number of eigenvalues greater than 1.
Across the whole sample, the average number of eigenvalues
exceeding 1.0 was 5.8 (SD = 1.1, range = 2 to 9). The corre-
sponding principal components accounted for, on average, 77% of
the total variance in emotional ratings across time (SD ~ 3.9). The
amount of variance accounted for by the principal components
with eigenvalues larger than unity was uncorrelated with age (r =
.09).
The correlation between age and the number of eigenvalues
larger than 1.0 was, as predicted, positive and significant (r = .28,
p < .01) and is shown in Figure 2. This evidence of age-related
differentiation held across all levels of ethnicity, gender, and
socioeconomic class. There was no quadratic trend for age. The
relationship between differentiation and age was not accounted for
by individual difference variables of personality, health, or verbal
fluency.
4 Again, if these correlations are computed for cutoff points of 40,
50,
60, and 65, the respective correlations in the younger portion of the
sample are .23, .31, .30, and .26. The respective correlations in the older
sample are —.14, —.15, —.15, and —.17. Once again, the pattern is clear:
Highly negative states are increasingly labile across adulthood, but at some
point, this increase levels off or becomes negative.
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EMOTION AND AGE651
18-34 35-64
Age in Years
Figure
2.
Differentiation of emotional experience over time.
65-94
Because our operational measure of differentiation represented a
novel way of thinking about qualitative aspects of emotional
experience, it was unclear how greater differentiation was associ-
ated with mental health. For this reason, we conducted exploratory
correlation analyses about the relation of our complexity measures
with other variables. We focused on three questions. First, is
differentiation associated with better mental health? In other
words, is it meaningfully related to indicators aside from the
emotion sampling data on which complexity scores were derived?
Second, how does complexity relate to the emotional experience
measures (frequency and intensity of negative and positive affect)?
Third, is complexity meaningfully related to other conceptually
relevant measures, specifically, verbal fluency and neuroticism?
Verbal fluency especially may be related to individuals' capacity
to represent situations in complex ways. Neuroticism, on the other
hand, is a diffuse tendency to perceive life negatively.
Differentiation was uncorrelated with overall mental health (r =
-.07).
Differentiation was negatively associated with the fre-
quency of experiencing both negative affect (r = —.30, p < .01)
and positive affect (r —
—.22,
p < .01). Differentiation was not
associated with the intensity of positive affect (r = —.06) but was
negatively correlated with the intensity of negative affect (r =
-.16,
p < .05). It was unrelated to verbal fluency (r = -.03) but
was negatively associated with neuroticism (r =
—
.19,
p < .05).
In sum, differentiation appears to be a positive feature of emotional
experience, as it is associated with greater emotional control and
less intense negative affect and with less neuroticism.
In addition to this factor-based indicator of emotional complex-
ity, we computed a second analysis to examine the degree to which
individuals experienced both positive and negative emotions on
the same sampling occasion. We refer to this feature of emotional
experience as "poignancy." Poignancy was computed by calculat-
ing, for each participant, a correlation between positive and neg-
ative affect across the 35 sampling occasions. On average, this
correlation was -.35 (SD = .33), suggesting that positive and
negative affect tended not to be present on the same occasion. A
linear-age effect emerged, with older age associated with the
greater potential for co-occurrence of positive and negative emo-
tions, (r = .26; p < .01). This effect is shown in Figure 3. For
people under age 60, the average correlation between positive and
negative emotion within occasions was -.42 (SD = .28), whereas
for those above age 60, that correlation was -
.25
(SD = .36). Just
as in the above analyses, these age differences remained after
controlling for personality, health, and verbal fluency. Age differ-
ences in poignancy also held within race, gender, and socioeco-
nomic classes. Poignancy was unrelated to the frequency of expe-
riencing positive or negative affect, suggesting that individuals
who frequently endorse all emotions are not more likely to expe-
rience negative and positive emotions in the same moment. Fi-
nally, differentiation and poignancy were correlated, (r =
.23,
p <
.01),
but differentiation did not account for the age and poignancy
relationship, nor did poignancy account for the age and differen-
tiation relationship, suggesting these are separate aspects of emo-
tional complexity.
Discussion
To the best of our knowledge, this project represents the first
experience-sampling study of emotion based on a cross-sectional
sample that spans most of the adult age range. Across a 76-year
span, encompassing participants between the ages of 18 and 94, a
pattern of age differences emerged that is notably consistent with
positive reports based on survey data. Older people experience
positive emotions just as often as their younger counterparts and—
until the age of roughly 60 years—experience fewer negative
emotions in their everyday lives. Of considerable importance is the
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652CARSTENSEN, PASUPATHI, MAYR, AND NESSELROADE
00
•a -.3"
13
4>
SP
I-.5)
18-3435-64
Age in Years65-94
Figure
3.
Poignancy with age: The correlation between positive and negative affect across the life span.
finding that age does not diminish the subjective intensity of
positive or negative emotions in everyday life. In other words,
when older people experience emotions, they are felt just as
intensely as in younger people, addressing an important piece of
the descriptive puzzle representing emotion in the second half of
life.
Findings from this study are especially compelling in that emo-
tions were sampled over an entire week while participants went
about their daily lives. Whereas most previous reports about age
differences in emotion—including one's own—were based on
global judgments about emotional functioning or, alternatively,
were obtained under tighly controlled laboratory conditions, the
experience sampling procedure represents emotional experience in
everyday life. Furthermore, our sample was diverse, and with few
exceptions, the pattern of results held for both African and Euro-
pean Americans, men and women, and blue- and white-collar
workers. The consistency of findings obtained in this project thus
relieves the persistent concern that the rosy picture of emotional
aging is simply the product of cognitive distortions or implicit
theories about emotional aging held by a select group of middle-
class adults.
The primary theoretical basis for the research was socioemo-
tional selectivity theory, the fundamental tenet of which is that
boundaries on time lead to the prioritizing of emotional goals
(Carstensen, 1993, 1995, 1998). Because chronological age is
related to time left in life, as people move through adulthood, they
grow keenly aware of the fragility of the human circumstance.
When they do, the pursuit of emotionally satisfying goals takes
precedence over the pursuit of other goals. Most of the research
testing postulates from socioemotional selectivity theory has ex-
amined goal selection. Over the years, this line of research has
generated considerable evidence that people prefer emotionally
meaningful goals in the face of limited time (Fredrickson &
Carstensen, 1990; Fung, Carstensen, & Lutz, 1999). The theoret-
ical assertion that the pursuit of such goals results in a richer, more
complex, and overall deeply satisfying emotional experience has
not been tested previously.
The first two hypotheses we tested concerned the intensity and
frequency of positive and negative emotional experiences in sub-
jects of different ages. We postulated that the intensity of felt
emotions would be comparable for young and old adults but that
older adults would experience negative emotions less frequently
than their younger counterparts. Our prediction about the fre-
quency of positive emotional experience was more tentative.
Changes in the frequency of positive emotions are not necessarily
predicted by our theoretical model and the literature is equivocal
on this point. Survey studies have found both greater (Mroczek &
Kolarz, 1998) and lesser (Rossi & Rossi, 1990) happiness among
older adults. Our experience-sampling findings reveal no age dif-
ferences in positive emotional experience. We point out, however,
that the nonsignificant correlation between positive affect and age
in our data set (r = .07) is not meaningfully different from the
significant correlation (r = .10), based on a much larger sample,
reported by Mroczek and Kolarz (1998). Both studies find very
slight increases in positive emotion in older people. Thus, our
findings weigh in on the side of very small but reliable increase in
the frequency of positive emotional experience among older
adults. Moreover, our findings certainly speak against a diminish-
ment in positive emotional experience found in some studies.
Measurement instruments may account for discrepancies in the
literature. Age-related reductions in positive affect tend to be
found when positive emotions are operationalized in terms of
surgency and excitability. Four out of the five questions tapping
positive emotions included on the Bradburn Affect Balance Scale
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EMOTION AND AGE653
(Bradburn, 1969), for example, ask about high energy emotions
(e.g., feeling "on top of the world" or excited). None of the items
tap happiness, contentment, or joy. Because of this, we predicted
excitement would be less frequent in older adults. Although we did
not find support for this hypothesis, that is, frequency of excite-
ment did not distinguish older and younger adults, we suspect that
it may have been due to the relatively infrequent endorsement of
excitement in the sample. Thus, interesting questions about the
frequency and the character of positive emotional experience in
old age remain.
The hypothesis that negative emotional experience is less fre-
quent among older people was strongly supported. Our findings,
along with previous reports in the literature, clearly show that early
adulthood is the life stage in which negative affect is most fre-
quent. In this adulthood sample, both linear and quadratic func-
tions were revealed. There was a steady decrease in the frequency
of negative emotion from 18 to roughly 60 years, at which point
the linear decline stopped and a very slight nonsignificant upward
trend appeared. Although, on the one hand, we do not want to
overinterpret a nonsignificant trend, on the other hand, our rela-
tively small sample size may not have allowed detection of a
significant trend. In any event, the correlation of negative emotions
and age in people over 60 was slight (r = .12). Not even at the
oldest ages did the frequency of negative emotions approach that
observed in younger adults. A quadratic function observed in a
sample spanning adulthood may help to reconcile differences in
published reports. The sample studied in Mroczek and Kolarz's
(1998) report, for example, included people only up to 74 years of
age.
Smith and Baltes (1997), in contrast, found increasingly
negative affective status with age, but their sample consisted
entirely of older people and encompassed participants between the
ages of 64 and 103 years. By focusing on different periods in
adulthood, researchers may be tapping different parts of a non-
linear course (Baltes, 1998).
The pattern of findings about the temporal stability of emotion
is consistent with reports of improved emotion regulation with age,
and interestingly these findings are linear, suggesting increasingly
better emotion regulation into the oldest ages we studied. To the
best of our knowledge, these data are the first to address emotion
regulation without asking participants for judgments about their
ability to control their emotions. Thus, circumventing the potential
subjective bias in global reports, the experience sampling data
provide support for self-reported improvement in emotion regula-
tion with age. Older adults were not simply more emotionally
stable in day-to-day life. Rather, highly positive emotions were
stable, whereas highly negative emotions were unstable. Although
these data cannot address questions about the mechanisms used to
influence stability, they strongly suggest that investigation into
potential age differences in regulatory processes is an important
direction for future research.
To the best of our knowledge, our tests of emotional complex-
ity—namely, differentiation and poignancy—are entirely new and,
as such, must be interpreted conservatively. In some ways, how-
ever, they provide the most original contribution of the research
and the theoretical model. Two findings emerge: (a) More dimen-
sions are required to reflect the structure of older as compared with
younger individuals' emotions, and (b) although the average cor-
relation between positive and negative affect within a sampled
moment is negative at all ages, the negative correlation is increas-
ingly smaller at older ages. Although very preliminary, such find-
ings support the utility of applying intraindividual approaches to
the study of emotion.
Regarding the differentiation findings, there are many possible
interpretations of increased factorial complexity in individuals'
emotional experiences. Among Ihem is the idea that older adults'
emotional experience is less coherent, thereby producing more
factors that are essentially meaningless. There are several reasons
that we believe the findings reflect greater differentiation rather
than incoherence. First, the solutions accounted for approximately
the same reasonably high amount of variance across all ages.
Second, the variability in older adults' emotions was, in general,
lesser than younger people, making it doubtful that the amount of
error in the reports somehow increased over the week. For exam-
ple,
if one calculates standard deviations across time for each
emotion, within individuals (since this is the thing at stake for the
within-person factor analyses), and then averages to obtain the
average variability for negative and positive emotions, the result-
ing variabilities for negative emotion correlated at -.26 with age,
and positive emotions correlated at —.29 with age (ps < .01).
These age decreases in variability hold even when controlling for
the average level of endorsement of positive and negative emo-
tions.
Third, the negative correlations between the number of
factors obtained and the frequency of endorsing positive emotions
or negative emotions imply a more differentiated and specific
endorsement of emotions on any given occasion.
The overall profile of findings generated in this study are
consistent with the most classic of developmental hypotheses:
Development brings increasing differentiation. We found greater
differentiation in emotional experience in older as compared with
younger people, and we found that emotional differentiation is
related to a positive profile of characteristics, including less neu-
roticism and better emotional control. Such findings about emotion
are especially important given widely documented decrements
in cognitive and biological aging and conclusions that de-
differentiation better characterizes development in adulthood
(Salthouse, Hancock, Meinz, & Hambrick, 1996). Findings from
this study stand in stark contrast. At the same time in life when
cognitive speed and biological hardiness are on the decline, emo-
tional functioning may continue to improve.
To recapitulate, socioemotional selectivity theory maintains that
boundaries on time imposed by human mortality elicit complex
emotional reactions in later life that are better characterized by
poignancy than happiness. People realize not only what they have
but also that what they have cannot last forever. A good-bye kiss
to a spouse at the age of 85, for example, may elicit far more
differentiated and complex emotional responses than a similar kiss
to a spouse at the age of
20.
The theory maintains that emotions are
deeper and more complex as the end of life nears because life's
fragility comes fully into awareness. Some forms of positive
emotions may decline, yet emotional satisfaction does not, nor
does negative affect become predominant. If, as socioemotional
selectivity theory asserts, such effects are related to approaching
the end of life more than chronological age per
se,
the theory offers
an explanation for the apparent paradox that people suffering from
terminal diseases often describe life as better than ever before
(Taylor & Brown, 1988; Taylor et al., 1992).
Although any and all claims about age change based on cross-
sectional designs must be tempered accordingly, our findings
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654CARSTENSEN, PASUPATHI, MAYR, AND NESSELROADE
contribute to a remarkably reliable pattern of findings in the
literature that suggest that emotional functioning remains vital in
the second half of life. The entire array of emotions are experi-
enced in the later
years,
but negative emotions are experienced less
frequently and are better controlled, and emotional experience is
more complex. More so than younger adults, older adults also
appear to experience complex mixes of emotions, and positive and
negative experiences are less independent in older adults.
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Received March 15, 1999
Revision received February 2, 2000
Accepted February 18, 2000
Call for Nominations
The Publications and Communications Board has opened nominations for the
editorships of Journal of Applied Psychology, Journal of Consulting and Clinical
Psychology, Journal of Educational Psychology, Psychological Bulletin, and Journal
of Personality and Social Psychology: Interpersonal Relations and Group Processes
for the years 2003-2008. Kevin R. Murphy, PhD, Philip C. Kendall, PhD, Michael
Pressley,
PhD,
Nancy Eisenberg, PhD, and Chester A. Insko, PhD, respectively, are the
incumbent editors.
Candidates should be members of APA and should be available to start receiving
manuscripts in early 2002 to prepare for issues published in
2003.
Please note that the
P&C Board encourages participation by members of underrepresented groups in the
publication process and would particularly welcome such nominees. Self-nominations
are also encouraged.
To nominate candidates, prepare a statement of one page or less in support of
each candidate and send to
• Margaret B. Spencer, PhD, for the Journal of Applied Psychology
• Donna M. Gelfand, PhD, and Lucia Albino Gilbert, PhD, for the Journal of
Con-
sulting and Clinical Psychology
• Lauren B. Resnick, PhD, for the Journal of Educational Psychology
• Janet Shibley Hyde, PhD, and Randi C. Martin, PhD, for Psychological Bulletin
• Sara
B.
Kiesler, PhD, for JPSP: Interpersonal Relations and Group Processes
Address all nominations to the appropriate search committee at the following
address:
[Name of journal] Search Committee
c/o Karen Sellman, P&C Board Search Liaison
Room 2004
American Psychological Association
750 First Street, NE
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The first review of nominations will begin December 11,2000.
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
