Journal of Personality and Social Psychology2000, Vol. 79, No. 4, 644-655

Copyright 2000 by the American Psychological Association, Inc.0022-351

EMOTION AND AGE 645

tual performance occurs in middle age. According to this theory,children must suppress idiosyncratic affective judgments aboutcollectively 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). Adultintellectual development, in contrast, involves the reintegration ofsubjective information into existing knowledge structures. Theo-retically, this increased complexity in cognitive operations is as-sociated with increasingly more complex and adaptive emotionalresponses and perhaps with greater flexibility in coping with newlife events (Diehl, Coyle, & Labouvie-Vief, 1996).

A second theory relevant to emotional functioning in adulthoodis 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 focuseson perceived time left in life rather than past experience. Thetheory contends that the distinctly human ability to consciouslyand subconsciously monitor time plays a fundamental role inmotivation and emotion, providing the structure within whichgoals are set, pursued, and evaluated. Because mortality places theultimate constraint on time, chronological age is associated withchanges in goals. Essentially, the theory contends that two primarytrajectories of social motives operate throughout life: the emotiontrajectory and the knowledge trajectory. The former is character-ized by motives to achieve emotional satisfaction and meaning, thelatter by motives to acquire new information and to achieve indomains that are relevant to successful adaptation in the future(e.g., educational and occupational domains). The central changein adulthood is a shift in the salience of social goals. Youngeradults, having much to learn and relatively long futures for whichto prepare, are motivated by the pursuit of knowledgeeven whenthis requires that emotional well-being be suppressed. For olderadults, the reverse trend appears. Facing relatively shorter futuresand having already accrued considerable knowledge about others,older adults prioritize emotional goals because they are realized inthe moment of contact rather than banked for some nebulous futuretime.

The theory stresses that age does not entail the relentless pursuitof happiness but rather the satisfaction of emotionally meaningfulgoals, which entails far more than simply feeling good. Findingmeaning in existing relationships, even conflictual ones, emergesas a central task in later life. Emotional experience is subsequentlyexpected to be more complex, and the experience of mixed emo-tions, more frequent. In short, socioemotional selectivity theorysuggests that constraints on time directly influence emotionalexperience such that emotional states are increasingly mixed.Whether pleasure or joy, sadness or pain, knowledge that anexperience 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 theyare and for their temporal fleetingness.

Despite these relatively optimistic empirical and theoreticalpictures, well-documented declines in later life leave an uneasinessthat positive portrayals of emotion in later life may be overblown.First, much of the literature on emotion, and to the best of ourknowledge all of the literature on emotion regulation, has beenbased on global self-reports, a practice that may be particularlyprecarious 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 saythat they do so. Moreover, global evaluations of life are highlycognitive and involve comparisons with the past and the present, aswell as with idiosyncratic standards (Schwarz, Park, Knaueper, &Sudman, 1999). Subsequently, such evaluations are susceptible toinfluence 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 thougholder people may be able to respond well to emotional tasks inlaboratory settings, emotional dysregulation may be evident in lessstructured settings.

The purpose of the present study was to assess the frequency,intensity, and the complexity of emotional experiences as theyoccur in everyday life. Our general hypothesis was that relative toyounger people, older people would show evidence of improvedemotion 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 toexamine the frequency and intensity with which positive andnegative emotions are experienced, as well as the stability ofnegative and positive states over time and the complexity ofemotional 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 asfrequently as younger adults. According to socioemotional selectivitytheory, increasing age is associated with greater appreciation of lifeand greater investment in emotionally meaningful social relationships.The theory predicts that this emphasis on emotionally meaningfulgoals improves emotional experience in everyday life.

Hypothesis 2. The intensity of positive and negative emotional expe-rience is comparable across age groups. Socioemotional selectivitytheory 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 noclaim 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 aremaintained longer and negative states are terminated more quickly.Surveys that ask people how well they regulate their emotions suggestthat where there are differences, older people report greater control. Inthis study, we obviate global judgments about emotion control byexamining whether positive states last longer and negative statespersist for shorter periods in older adults.

Hypothesis 4. Emotional experience is more complex in older ascompared with younger adults. Because the pursuit of emotionallymeaningful goals often entails mixed emotions, we anticipate a morecomplex dimensional structure to the emotional experience of olderadults.

Method

Sample

One hundred eighty-four African American and European Americanresearch 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

646 CARSTENSEN, PASUPATHI, MAYR, AND NESSELROADE

Francisco Bay area to participate in an experience-sampling study ofemotional experience. Ethnic composition of the sample was restricted tothese two ethnic groups rather than sampling the ethnic diversity of the Bayarea so that sufficient numbers of participants in subsamples would allowfor statistically meaningful analyses. Thirty-one percent of the sample wereAfrican American; the remaining 69% were European American. Forty-one percent of the sample comprised blue-collar workers, and 59% werewhite-collar workers; 54% of the participants were women, and 46% weremen. 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. Asshown in Table 1, the sample was diverse along many dimensions.

Measures

Although our principal aim was to sample emotional experiences ineveryday life, we also assessed health, personality, and verbal fluencybecause each of these factors may influence at least some features ofemotional 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 (notat all) to 7 (extremely), participants indicated the degree to which they werefeeling each of 19 emotions or feeling states. Ratings greater than 1, thus,indicated that the emotion was present and, consequently, both frequencyand intensity are captured in a single rating. The list of emotions includedanger, guilt, pride, sadness, happiness, fear, accomplishment, shame,amusement, anxiety/worry, joy, contentment, irritation, frustration, disgust,interest, embarrassment, boredom, and excitement. An other blank wasalso provided on the response sheet to allow participants to record addi-tional emotions not included on the sampler. A week's supply of emotionresponse sheets were bound in a 5 in. by 5 in. pad for easy transport duringthe 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 physicaland mental health problems that allows the computation of a general healthindex as well as subscales that represent functioning in specific organsubsystems and symptoms associated with specific psychological syn-dromes. Participants report whether they experience each of the 195symptoms. We computed two broad indexes from the CMI, one represent-ing the total number of recent symptoms of physical illness and the otherrepresenting the total number of recent symptoms of mental illness. Anexample of a physical illness symptom item is "Are you troubled byconstant coughing?" A sample mental illness symptom item is "Do youhave to be on your guard even with your friends?"

Category instance fluency (Undenberger, Mayr, & Kliegl, 1993). As ameasure of verbal fluency, participants were asked to name as manydifferent kinds of animals as possible in 90 s. This test shows a strongrelationship to general intellectual ability and has been extensively usedwith older adults.

Adjective checklist (John, Donahue, & Kentle, 1991). This is a listof 54 adjectives presented in the form of self-descriptive sentences. Ad-

Table 1Demographic Characteristics of the Sample

Characteristic Sample description

Age (in years)Education (in years)SexEthnicitySocioeconomic statusMarital status

Number of children

M = 55.0, SD = 20.4, range = 18.0-94.0M = 15.0, SD = 2.7, range - 5.0-22.054% women, 46% men31% African American, 69% European American41% blue-collar, 59% white-collar26% single, 43% married, 19% widowed, 13%

divorcedM = 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 byplacing a check next to it. Example items include "I am talkative" and "Ican be somewhat careless." We computed summary scores for each of theBig Five factors: Neuroticism, Extraversion, Openness to Experience,Agreeableness, and Conscientiousness.

ProcedureFollowing initial screening by the survey research firm to ensure that

participants met recruitment criteria for the project, participants werescheduled at their convenience for an initial interview at Stanford Univer-sity or at the offices of the San Francisco-based survey research firm thatdid the initial recruiting. Participants were informed that the purpose of thestudy was to examine feelings in everyday life. After obtaining informedconsent and obtaining background information, such as education level, thefollowing measures were administered: Category Instance Fluency, CMI,and the Adjective Checklist.

At this point, participants were provided with detailed instructions aboutthe experimental procedures, familiarized with the operations of the elec-tronic pager (e.g., how to set it for motion or sound, how to indicate thatthey received the page by pushing a button, etc.), and instructed tocomplete the emotion response sheets each time they were signaled. Next,two practice trials were administered while participants were still in thelaboratory so that responses could be reviewed with the experimenter priorto beginning the study. The participant was left alone; the intervieweractivated the pager from another room; the participant completed thequestionnaire; and, on returning to die room, the interviewer reviewed theparticipant's responses, clarified any apparent mistakes, and answeredquestions.

During the ensuing week, participants were paged five times each day.Paging times were determined by random selections from all possible10-min intervals between 9 a.m. and 9 p.m. The only constraint onsampling times was that participants were not sampled more than oncewithin a single 20-min period. At the end of each day, participants returnedthe day's completed response sheets by mail in pre-addressed, stampedenvelopes, allowing us to monitor responses during the data collectionperiod and assuring at least rough adherence to the experimental protocol.Participants were encouraged to telephone the laboratory if proceduralquestions or problems arose and periodic calls were made to participants aswell to ensure that the highest quality data were obtained.

After participants completed the week-long experience-sampling datacollection, they returned to the laboratory for a follow-up interview, atwhich time they returned the pagers and were debriefed. Participants werepaid $125 for their participation.

Results

We organize our results into four sections. The first sectiondescribes data reduction and preliminary analyses. The secondsection of the results reports findings from analyses that examineage differences in the frequency and intensity of emotional expe-rience, controlling for individual differences that may influenceemotional experience (Hypotheses 1 and 2). In this section we alsoexamine 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 ofemotional experience (Hypothesis 4). In these latter two sections,hypotheses are tested on the basis of within-individual variabilitythat allowed us to examine emotional complexity and the temporalexperience of emotional experiences. Here, too, we examined theconsistency of effects across ethnicity, gender, and class. Because

EMOTION AND AGE 647

our measure of differentiation was novel, we explored its relation-ship to other measures, such as personality, mental health, andintelligence.

Data Reduction and Preliminary AnalysesRatings of 19 emotions were obtained on 35 separate occasions,

generating a total of 665 experience sampler data points perparticipant. Data were reduced in the following way. Frequencywas represented as the proportion of times across the 35 samplingpoints that a participant acknowledged that he or she experiencedthe emotion to some degree, namely, ratings were greater than 1.Intensity of emotional experience was calculated by computing theaverage rating for each felt emotion (see Schimmack & Diener,1997, for a discussion of this kind of decomposition). Table 2presents the average frequencies and intensities for specific emo-tions across the entire sample. As can be seen, people endorsednegative emotions relatively infrequently and positive emotionsrelatively frequently, a finding consistent with earlier experiencesampling studies (Diener & Diener, 1996). For each specificnegative 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 allduring the experience-sampling period.1

The above procedure resulted in each participant having 38scores indicating the frequency and intensity with which he or shereported 19 emotions over the sampling period. To reduce thenumber of statistical tests in our analyses and to increase thereliability of our measures, we collapsed these 38 scores into four

Table 2Means and Standard Deviations of Frequency and intensityof Experiencing Specific Emotions for the Entire Sample

Emotion

AngerSadnessFearDisgustGuiltEmbarrassmentShameAnxietyIrritationFrustrationBoredom

HappinessJoyContentmentExcitementPrideAccomplishInterestAmusement

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

3.313.313.133.462.993.232.933.283.393.403.38

4.354.104.403.984.094.404.553.95

Intensity

SD

0.911.051.041.090.901.090.930.930.900.860.95

0.971.021.000.941.101.000.990.86

n

147159138157128131112176177176149

1841811S4181180184184182

indicators of emotional experience: average frequency of negativeemotions, 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 personexperiences each of the positive emotions. Because there is somedebate about the dimensionality of emotional experience and be-cause the 38 scores were derived from only 19 ratings, thisaggregation was verified by factor analysis.

We conducted a descriptive factor analysis using varimax rota-tion with mean substitution for missing values. This revealed thatfrequency and intensity scores for the emotions were reasonablywell-characterized by a four-factor solution (69% of the totalvariance was accounted for by this solution). Although six factorswith eigenvalues above 1 could be extracted, Factor 5 had highloadings only for the intensity of Fear (.60) and of Shame (.80),whereas only the intensity of Boredom loaded significantly onFactor 6 (.80). Together Factors 5 and 6 accounted for only anadditional 5% of variance in the data. Inspection of the scree plotshowed a clear dissociation of the latter two from the first fourfactors. Thus, a four-factor solution was used (as per Tabachnik &Fidell, 1989). This solution clearly reflects the frequency andintensity with which positive and negative emotions were experi-enced and was reliable both when cases with missing values weredeleted and when oblique rotation was used. Table 3 presents thevarimax rotated factor loadings of frequency and intensity vari-ables on the four factors as well as eigenvalues and varianceaccounted for by each factor. As shown in Table 3, Factors 1 and 2reflect the frequency and intensity of negative affect, respectively.Factors 3 and 4, respectively, represent the frequency and intensityof positive affect.2

Hypotheses 1 and 2: Age Is Related to the Frequency butnot the Intensity of Emotional Experience

We hypothesized that the frequency of negative, but not posi-tive, emotional experience decreases across age cohorts, and wehypothesized 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 emotionscorrelated at .34, and the factors for intensity and frequency of positiveemotions also correlated (r = .30). Frequency of experiencing negativeemotions and frequency of experiencing positive emotions were alsocorrelated, though less strongly (r = .21). No other interfactor correlationswere above .17. Relationships between the aggregate scores (not factorscores) used in our analyses mirrored these oblique factor correlations, andwere somewhat stronger. Intensity of negative emotion and intensity ofpositive 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 (maximumabsolute value r = .16). Both interfactor correlations and correlationsbetween our variables imply the existence of individual differences inemotional intensity and in the general frequency with which emotions areexperienced. These relationships (between the frequency and intensity ofpositive and negative emotion) did not vary as a function of age at this, thebetween-subjects, level.

648 CARSTENSEN, PASUPATHI, MAYR, AND NESSELROADE

Table 3Varimax Rotated Factor Loadings for Frequency and Intensityof Positive and Negative Affect

Emotion

AngerSadnessFearDisgustGuiltEmbarassmentShameIrritationFrustrationAnxietyBoredomHappinessJoyContentmentExcitementPrideAccomplishmentAmusementInterest

Eigenvalues% of Variance

AngerSadnessFearDisgustGuiltEmbarassmentShameAnxietyIrritationFrustrationBoredomHappinessJoyContentmentExcitementPrideAccomplishmentAmusementInterest

Eigenvalues% of Variance

NEfrequency

PEintensity

Frequencies

.86

.85

.87

.88

.90

.88

.92

.86

.85

.78

.65

.06

.13

.02

.27

.24

.14

.19

.09

9.3425

- .04- .04- .01

.02- .04

.14

.06- .09- .14- .14-.17

.16

.32

.02

.30

.22

.16

.26

.07

8.3522

Intensities

- .09.03

-.05- .15-.01- .11-.07

.17

.06

.14- .04-.07

.03- .24-.01- .02- .07- .05- .07

9.3425

.18

.20

.07

.08

.12

.12

.07

.19

.10

.03

.15

.84

.92

.76

.84

.75

.78

.81

.72

8,3522

PEfrequency

.09

.11

.08

.01

.11

.09

.10

.06

.09

.13

.22

.85

.79

.79

.77

.76,85.80.79

5.6015

-.05- .02- .13-.08- .15- .02

.01-.07- .07- .03-.08

.34

.04

.21

.07

.18

.33

.14

.32

5.6015

NEintensity

.03- .03

.03

.03

.00- .08

.01- .04- .03- .05-.17-.12- .02

.00- .11- .13-.11- .18- .14

2.005

.66

.67

.66

.64

.56

.64

.53

.72

.83

.84

.45

.18

.16

.15

.22

.16

.27

.30

.22

2.005

Note. NE = negative emotions; PE - positive emotions. Boldface indi-cates factor loadings above .40.

with the exception of excitement. Four regression analyses werecomputed to explore relationships between the frequency andintensity of experiencing positive and negative affect and age.Both linear and quadratic age trends were explored. No significantage effects were obtained for the frequency or the intensity ofpositive affect, nor were there age effects for the intensity withwhich negative affect was experienced, all Fs(l, 181) < 1.0, ps >3. However, as predicted, age was associated with the frequencyof experiencing negative affect F(2, 182) - 6.0, p < .01. This

effect has both a linear and a nonlinear component, as shown bythe 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 moreintuitive way, simple correlations between age and frequency ofnegative emotion before and after age 60 were computed. Thesecorrelations reveal a decrease in the frequency of negative emo-tions from 18 to 60 years (simple r = .29, p < .01). After 60years, the decrease ceases (r = .14, ns) and characterizes thepattern from age 60 onward.3 This effect is shown in Figure 1.

Our next step was to explore the robustness of age as a predictorof emotional experience in conjunction with factors known toinfluence emotions. We added the following predictors to theregression 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 weremaintained even with these additional variables included. Con-cerning the frequency of negative emotions, more mental healthsymptoms and higher neuroticism were additionally associatedwith higher frequencies of negative emotion. For the frequency ofpositive emotions, African Americans and those who were moreopen and agreeable reported experiencing positive emotions morefrequently.

Concerning the intensity of emotions, negative affect was pre-dicted by gender and socioeconomic status as well as by mentalhealth symptoms, with women, blue-collar workers, and individ-uals who were more extraverted endorsing more intense negativeaffect. Intensity of positive affect was associated with ethnicity andextraversion, with African Americans and more extraverted indi-viduals endorsing more intense positive affect. We also exploredthe consistency of the pattern of age effects and noneffects inpredicting affective experience across gender, race, and socioeco-nomic status by looking for interactions between age and thesedemographic 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 emotionalexperience.

3 We chose 60 as an illustrative point because it represents approxi-

mately the bottom of the line depicted in Figure 1. Choosing other agecutoffs, such as 40,50, or 65, results in differences in the magnitude but notthe pattern of relationships. To be concrete, the correlations for the youngerportion of the sample are .46, .24, .29, and .24, respectively, forages 40, 50, 60, and 65 years. The same correlations for the older portionof the sample are .04, .17, .14, and .19. In no case is the age relationshipnear zero for the younger portion of the samplea decline is always seen.What happens after the selected cutoff is somewhat more variable, rangingfrom zero relationships to small positive correlations with negative emo-tion. However, again, these are meant only to illustrate the pattern detectedin the regression analyses.

EMOTION AND AGE 649

Table 4Emotional Experience, Age, and Other Variables

Predictors

Demographic variablesRaceSexSocio-economic status

HealthPhysicalMental

PersonalityNeuroticismExtraversionOpennessAgreeablenessConscientiousness

Verbal intelligenceLinear ageQuadratic ageOverall K2Regression, F(13, 129)

r

.07- .04

.03

.11

.28**

.20**

.01

.03- .11- .18*- .02-.08- .04

.202.50**

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

-.1122**.12.16*.17*

- .04.07.06.14

1.60t

PA Frequency

.21*- .13

.02

- .06.06

.08

.1115t.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

.172.00*

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 intensityof excitement. Contrary to our hypothesis of reduced intensity ofexcitement given the literature reviewed above, once again wefailed to reveal a significant relationship between age and theintensity with which excitement was experienced, B = .001 J3 =.08,1(182) = 1.1, p > .25.

Hypothesis 3: Compared With Younger People, OlderPeople Better Regulate Emotional Experience

We operationalized emotion regulation as the maintenance ofdesirable emotional states (defined as those where the individual

.341

.32

ftM .30

S-28"8g .26

u.

feels more positive or less negative affect than usual) and thecessation of undesirable emotional states (defined as states wherethe person is feeling less positive or more negative than usual). Theformer reflect adaptive aspects of emotional stability, and the latterreflect adaptive aspects of emotional lability. To test Hypothesis 3,we computed four scores that reflect these four aspects of emotionregulation.

For each sampling occasion, participants were classified as highon positive affect relative to their own idiosyncratic ally calculatedmean across all sampled situations or as below or equivalent totheir own idiosyncratically calculated mean across situations. A

I18-34 35-64

Age in Years65-94

Figure 1, Frequency of negative affect across the life span.

650 CARSTENSEN, PASUPATHI, MAYR, AND NESSELROADE

similar split was made for negative emotional states. We thencomputed four conditional probabilities: (a) maintaining high pos-itive states: the probability that, given participants were morepositive than average on Occasion 1, they would be more positivethan 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: theprobability that, given participants were less positive than averageat Occasion 1, they would be more positive than average atOccasion 2; and (d) moving from highly negative states to lownegative states: the probability that, given participants were morenegative than average at Occasion 1, they would be less negativethan average on the following occasion. Note that these scores arenot necessarily related to the overall frequencies of experiencingpositive or negative emotions, because these scores reflect some-thing about the temporal distribution of positive and negativestates. Also, note that these scores do not simply reflect stability ofpositive or negative states, but rather, adaptive features of stabilityand adaptive features of lability.

Age-related patterns were reasonably positive. Older men andwomen 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 withstability of low negative states (r .20, p < .001). Age wasnegatively, though not significantly, correlated with moving froma low positive to a high positive state (r = .13, p < .11). Therewere no quadratic trends for age and these effects were constantacross genders, ethnicities, and socioeconomic status groups. Fi-nally, age was uncorrelated with the likelihood of moving from ahighly 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 (LinearAge X Gender interaction: A*2 = .03, &F = 6.7, p < .02).Examining the regression equation separately for men and womenrevealed that the pattern of age effects (linear and quadratic) wasidentiqal 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 geta 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 someage, were less likely to remain in a highly negative state overoccasions 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 maintainhighly positive states and were more likely to maintain the absenceof negative emotional states. Thus, the stability indicators suggestgreater stability of emotional experience in older adults for theadaptive portions of emotional stability (i.e., one could also bevery stable by being continuously very angry). This raises thequestion 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 orbelow one's idiosyncratic mean) that we defined for this analysis.These correlations arc instructive. For positive emotions, smallage-associated increases in stability (whether of low or high pos-itive states) are evident (r = .17, p < .02). This is not the case fornegative emotions (r = .11, p > .15).

Finally, the curvilinear pattern of results obtained for lability inhighly negative states with age raises the possibility that this kindof lability accounts for the age differences observed in the fre-quency of negative emotions. Note that this is not necessarily thecase. Older and younger adults could have different frequencies ofnegative emotions without those emotions occurring in temporallylinked ways. However, if older adults are moving out of negativestates more quickly than young adults (at least up to some point inadulthood), this might mean that older adults' better emotionregulation, as assessed here, accounts for age differences in thefrequency of negative emotions. We examined this by computinga hierarchical regression predicting the frequency of negativeemotion (from Hypothesis 1 above). The probability of movingfrom highly negative to low-negative states was entered as the firstpredictor, 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 negativestates was entered, age (both linear and quadratic) contributed anadditional 2% of the variance to predicting the frequency ofnegative emotion F(2, 179) = 2.3, p = .10. Thus, changes in thefrequency of negative emotion with age may be interpreted asstemming from changes in the lability of highly negative states.

Hypothesis 4: Age Is Associated With the Complexity ofEmotional Experience

To test Hypothesis 4, we computed the eigenvalues of eachindividual's 19 X 19 emotion ratings correlation matrix on thebasis of his or her 35 occasions of measurement. We took as anindex of differentiation the number of eigenvalues greater than 1.Across the whole sample, the average number of eigenvaluesexceeding 1.0 was 5.8 (SD = 1.1, range = 2 to 9). The corre-sponding principal components accounted for, on average, 77% ofthe total variance in emotional ratings across time (SD ~ 3.9). Theamount of variance accounted for by the principal componentswith eigenvalues larger than unity was uncorrelated with age (r =.09). The correlation between age and the number of eigenvalueslarger than 1.0 was, as predicted, positive and significant (r = .28,p < .01) and is shown in Figure 2. This evidence of age-relateddifferentiation held across all levels of ethnicity, gender, andsocioeconomic class. There was no quadratic trend for age. Therelationship between differentiation and age was not accounted forby individual difference variables of personality, health, or verbalfluency.

4 Again, if these correlations are computed for cutoff points of 40,

50, 60, and 65, the respective correlations in the younger portion of thesample are .23, .31, .30, and .26. The respective correlations in the oldersample are .14, .15, .15, and .17. Once again, the pattern is clear:Highly negative states are increasingly labile across adulthood, but at somepoint, this increase levels off or becomes negative.

EMOTION AND AGE 651

18-34 35-64Age in Years

Figure 2. Differentiation of emotional experience over time.

65-94

Because our operational measure of differentiation represented anovel way of thinking about qualitative aspects of emotionalexperience, it was unclear how greater differentiation was associ-ated with mental health. For this reason, we conducted exploratorycorrelation analyses about the relation of our complexity measureswith other variables. We focused on three questions. First, isdifferentiation associated with better mental health? In otherwords, is it meaningfully related to indicators aside from theemotion sampling data on which complexity scores were derived?Second, how does complexity relate to the emotional experiencemeasures (frequency and intensity of negative and positive affect)?Third, is complexity meaningfully related to other conceptuallyrelevant measures, specifically, verbal fluency and neuroticism?Verbal fluency especially may be related to individuals' capacityto represent situations in complex ways. Neuroticism, on the otherhand, 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 notassociated with the intensity of positive affect (r = .06) but wasnegatively correlated with the intensity of negative affect (r =- .16, p < .05). It was unrelated to verbal fluency (r = -.03) butwas negatively associated with neuroticism (r = .19, p < .05).In sum, differentiation appears to be a positive feature of emotionalexperience, as it is associated with greater emotional control andless 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 whichindividuals experienced both positive and negative emotions onthe same sampling occasion. We refer to this feature of emotionalexperience 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, thiscorrelation was - .35 (SD = .33), suggesting that positive andnegative affect tended not to be present on the same occasion. Alinear-age effect emerged, with older age associated with thegreater potential for co-occurrence of positive and negative emo-tions, (r = .26; p < .01). This effect is shown in Figure 3. Forpeople under age 60, the average correlation between positive andnegative emotion within occasions was - .42 (SD = .28), whereasfor those above age 60, that correlation was - .25 (SD = .36). Justas in the above analyses, these age differences remained aftercontrolling 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 individualswho 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