Full text of DOI:10.1093/geronb/57.3.P246

Journal of Gerontology: PSYCHOLOGICAL SCIENCES
Copyright 2002 by The Gerontological Society of America
2
002, Vol. 57B, No. 3, P246–P255
Anxiety, Cognitive Performance, and Cognitive
Decline in Normal Aging
1
2
1, 3
Julie Loebach Wetherell, Chandra A. Reynolds, Margaret Gatz,
and Nancy L. Pedersen1
, 3
1Department of Psychology, University of Southern California, Los Angeles.
2Department of Psychology, University of California, Riverside.
3Department of Medical Epidemiology, The Karolinska Institute, Stockholm, Sweden.
A sample of 704 cognitively intact individuals (M age ϭ 63.7 years) performed a battery of cognitive tests on as
many as three occasions, at approximately 3-year intervals. The authors used random effects models to analyze
cross-sectional relationships between cognitive performance and state anxiety and longitudinal relationships be-
tween cognitive change and neuroticism, after controlling for gender, age, and education. Cross-sectionally,
higher state anxiety was associated with poorer performance on Wechsler Adult Intelligence Scale Synonyms,
WIT III Analogies, Koh’s Block Design, two measures of visual learning (Names and Faces and Thurstone’s Pic-
ture Memory), and, for men, CVB-Scales Digit Span Test and Card Rotations. In longitudinal models, the main
effects for neuroticism were significant for Block Design, Symbol Digit, and Names and Faces, but there were no
significant interactions among neuroticism, gender, and time. These results provide some support for Eysenck’s
processing efficiency theory but none for neuroticism as a risk factor for cognitive decline in normal aging.
YSENCK’S processing efficiency theory (Eysenck,
1992; Eysenck & Calvo, 1992) holds that anxiety inter-
sual problem-solving tasks such as Block Design, Card Ro-
tations, Figure Logic, and Matrix Reasoning). Other tasks
assessing recall of well-learned verbal information or word
meanings, such as Information, Synonyms, or Vocabulary,
and simple visual pattern matching or perceptual speed
(Figure Identification) are presumed not to rely as heavily
on working memory.
E
feres with cognitive performance by preempting some of the
processing and storage resources of the working memory
system. Working memory is hypothesized to consist of a pho-
nological loop that is responsible for the brief storage and ma-
nipulation of verbal information, a visuospatial sketchpad
that is responsible for manipulating visual images, and a cen-
tral executive that performs attentional tasks and coordi-
nates other subsystems (Baddeley, 1990). Storage and pro-
cessing capacities of the subsystems are presumed to be
limited. Thus, simultaneous performance of tasks that rely
on the same component of working memory tends to result
in greater interference than does performance of tasks that
rely on different working memory components.
Eysenck’s theory posits that anxiety produces worry and
other intrusive thoughts that compete for resources in work-
ing memory (Eysenck, 1992). Because these thoughts are
verbal, they are processed by the phonological loop and the
central executive, but they do not affect the resources of the
visuospatial sketchpad. Thus, the theory predicts that anxi-
ety should interfere with verbal tasks and with tasks requir-
ing complex attention and coordination, but should not in-
terfere with simple visuospatial tasks whose demands on the
central executive are relatively low.
Anxiety is often described as both a state and a trait phe-
nomenon. State anxiety refers to an emotional condition
characterized by feelings of tension, apprehension, nervous-
ness, and worry, along with symptoms of increased physio-
logical arousal (Spielberger, 1983). Trait anxiety, or anxiety
proneness, is the tendency to perceive situations as threaten-
ing and to respond with more frequent and more intense ele-
vations in state anxiety. Trait anxiety is considered a rela-
tively stable variable showing individual differences.
Neuroticism, a personality trait that predisposes individuals
to experience negative affect, is sometimes considered a
proxy for trait anxiety, and correlations between measures
of trait anxiety and neuroticism are typically quite high
(e.g., Harrison & Whissell, 1980; Merckelbach, Muris, Nij-
man, & de Jong, 1996; Watson & Clark, 1984). The effects
described in processing efficiency theory are likely due to
state anxiety, because the proposed mechanism for adverse
effects on working memory is the experience of worry or in-
trusive thoughts, which accompany state anxiety. A relation-
ship between trait anxiety and working memory would be
mediated by state anxiety, which is typically higher in indi-
viduals with high trait anxiety.
Tasks that are heavily influenced by the phonological
loop of working memory include Digit Span (particularly
Digits Backward) and measures of verbal learning. Tasks in-
fluenced by the visuospatial sketchpad include Block De-
sign, Card Rotations, Figure Logic, Matrix Reasoning, and
Symbol Digit, which is also a measure of perceptual speed.
Tasks influenced by the central executive include Analogies,
Similarities, and other problem-solving tasks (including vi-
Relative to younger adults, older adults show deficits in
working memory performance, particularly for processing
rather than storage tasks (Salthouse & Babcock, 1991).
These differences appear to be mediated by perceptual speed
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ANXIETY AND COGNITION
P247
(
Hultsch, Hertzog, & Dixon, 1990). Age-related declines in
To date, the relationship between anxiety and simple
visuospatial tasks that do not rely heavily on the processing
capacity of the central executive (such as pattern matching)
does not appear to have been adequately tested with older
adults. The relationship between anxiety and visual learning
has also not been investigated. The processing efficiency
theory would predict no effect of anxiety on simple visuo-
spatial tasks such as pattern matching, but would predict an
effect on visual learning due to the involvement of the cen-
tral executive.
Furthermore, all reports on anxiety and cognition pub-
lished to date have been limited to cross-sectional data.
There appear to be no published studies on the relationship
between anxiety and normal age-related cognitive decline.
Previous research on longitudinal cognitive change has
found age-related declines in perceptual speed, complex
visuospatial skills, and learning and memory but not in ver-
bal knowledge (Reynolds, Gatz, & Pedersen, 2000; Schaie,
1995). There are clear parallels in lists of tasks that typically
show age-related decline and tasks usually affected by anxi-
ety. Therefore, the question arises of whether general anxi-
ety proneness is related to accelerated rates of decline rela-
tive to those who are less anxious. Specifically, because
anxiety is hypothesized to affect complex visual tasks and
visual learning, but not simple visual tasks involving per-
ceptual speed, it is expected that higher levels of anxiety
will be associated with greater age-related declines in com-
plex visuospatial performance and visual learning but not
with declines in verbal knowledge or simple visual pattern
matching.
Exploring the relationships between anxiety and cogni-
tive performance and decline in older adults is important for
several reasons. First, because neuropsychological tests are
used in diagnosing dementia, there are serious conse-
quences for failing to recognize which tests may be vulnera-
ble to the effects of anxiety in older adults. Additionally,
learning more about the effect of anxiety on cognition
across the life span can lead to a better understanding of
cognitive processes associated with anxiety and aging. To
address these questions and further explore the relationships
between anxiety and cognitive performance, this study
tested the following hypotheses using data from a large, lon-
gitudinal, population-based panel of cognitively intact older
adults: (a) Higher levels of state anxiety will be associated
with poorer performance on tests of verbal reasoning and
working memory, complex visuospatial skills, and visual
learning but will not have an effect on verbal knowledge
or simple visual pattern matching; and (b) Trait anxiety,
assessed with a measure of neuroticism, will be associ-
ated with longitudinal declines in visual learning and
complex visuospatial tasks but not with declines in other
cognitive domains.
perceptual speed may thus be responsible for not only de-
creases in the processing tasks of working memory but also
age-related changes in cognitive performance in general
(Salthouse, 1996).
Because of already-reduced working memory and pro-
cessing resources, older adults may be more vulnerable than
younger adults are to the effects of anxiety across multiple
cognitive domains. In particular, older adults with higher
levels of anxiety may show poorer performance on tasks in-
volving processing of verbal information. Likewise, anxious
older adults may perform less well on complex visuospatial-
processing tasks involving the central executive. However,
less complicated visuospatial tasks without a heavy process-
ing component should be relatively unaffected by anxiety,
although performance on tasks of perceptual speed should
be poorer in older adults, regardless of anxiety. Recall of
well-learned (verbal) knowledge such as general informa-
tion or word meanings is typically preserved in late life.
Empirical data largely support the hypothesis that in-
creased anxiety is associated with poorer performance on
verbal working memory tasks involving the phonological
loop and the central executive in later life. State anxiety has
shown a negative effect on Digit Span (Rankin, Gilner,
Gfeller, & Katz, 1994; West, Boatwright, & Schleser, 1984).
Studies have found state and trait anxiety associated with
significantly poorer performance on Similarities, Analogies,
and practical problem-solving tests (Cohen, Eisdorfer, Vi-
taliano, & Bloom, 1980; LaRue & D’Elia, 1985). There is
also some evidence that both state and trait anxiety are asso-
ciated with poorer verbal learning in late life (Deptula,
Singh, & Pomara, 1993; Paterniti, Dufouil, Bisserbe, &
Alperovitch, 1999; Whitbourne, 1976). Trait anxiety is typi-
cally not associated with tasks such as Information or Vo-
cabulary in older samples (Cohen et al., 1980; Costa,
Fozard, McCrae, & Bossé, 1976; Schultz, Hoyer, & Kaye,
1
980). Hence, the evidence suggests that verbal tasks that
involve the processing capacities of the phonological loop
and the central executive functions of working memory can
be compromised by anxiety in older adults.
Findings for visuospatial tasks are much less consistent
than for verbal tasks. Poorer performance on Digit Symbol
was associated with trait anxiety in one very large investiga-
tion (Paterniti et al., 1999) but not with state anxiety in an-
other (Schultz et al., 1980). The relationship between anxi-
ety and performance on Raven’s matrices has yielded mixed
results for both state and trait anxiety in larger samples
(Ns Ն 100; Cockburn & Smith, 1994; Paterniti et al., 1999;
Schultz et al., 1980). A pattern of less consistent results on
visuospatial tasks than on verbal tasks is generally consis-
tent with the hypothesis that worry and other verbal intru-
sive thoughts are responsible for the effects of anxiety on
working memory. For verbal tasks, anxiety potentially inter-
feres with the processing capacity of both the phonological
loop and the central executive. For visuospatial tasks, anxi-
ety potentially compromises only the efficiency of the cen-
tral executive. Hence, effects of anxiety on visuospatial
tasks may depend on the complexity of the task and the de-
mands it places on the central executive, and results may
therefore be less consistent than for verbal tasks.
METHODS
Sample
Data were collected as part of the Swedish Adoption/
Twin Study of Aging (SATSA), a longitudinal study of per-
sonality, health, and aging among cognitively intact same-
sex twins (Pedersen et al., 1991). SATSA is a subsample of

P248
WETHERELL ET AL.
the Swedish Twin Registry, which includes virtually all
same-sex twin pairs born in Sweden between 1886 and
The sample consisted of 288 men (40.9%) and 416 women
(59.1%). Participants had an average age of 63.7 years
(SD ϭ 8.6) at their initial assessment, 66.5 years (SD ϭ 8.5)
at their second assessment, and 70.3 years (SD ϭ 7.5) at
their third assessment. Education level was assessed in four
categories: elementary (61.0%), vocational (27.2%), aca-
demic secondary school (5.7%), and university (6.1%). The
majority were married (70.8%), with 12.2% widowed, 8.9%
divorced, and 8.1% single. Women were significantly older
than men were at their second assessment, t(252) ϭ Ϫ2.07,
p ϭ .04, but not at the first or third assessment. Men had sig-
nificantly more education than women did, t(317) ϭ 2.72,
p ϭ .007.
1
958 (Cederlöf & Lorich, 1978). Evidence from the Swed-
ish Twin Registry indicates that twins are representative of
the broader Swedish population on environmental and so-
ciological variables, suggesting that findings from this sam-
ple are generalizable (Cederlöf, Friberg, & Lundman, 1977).
The sample was chosen because it is large, population-based,
and longitudinal; the fact that respondents are twins is inci-
dental, and neither family nor genetic similarity is addressed
in these analyses.
SATSA includes all registry twins who were reared apart
and a control sample of twins reared together matched on
the basis of gender, age, and county of birth. Twins were not
excluded from SATSA if their partner had died; thus, the
sample includes both complete pairs and singletons. In gen-
eral, the SATSA twins are representative of twins in the
Swedish Twin Registry, except that they are older, because
most of the reared-apart twins were born during the first 3
decades of the 20th century, when economic depression and
epidemics increased the likelihood of separation. Further-
more, twins reared apart experienced on average a lower
standard of living as children than twins reared together did.
A prior report indicated that twins reared apart do not differ
from registry twins reared together on personality variables,
with the exception of neuroticism, on which twins reared
apart score higher (Pedersen, Friberg, Floderus-Myrhed,
McClearn, & Plomin, 1984).
Measures
The cognitive battery was selected to provide representa-
tion of the domains of verbal reasoning and knowledge,
visuospatial skills, perceptual speed and attention, and vi-
sual memory, but not verbal memory. All tests were taken
from standard batteries, with alpha coefficients ranging
from .82 to .96 in this sample (Pedersen et al., 1992). For
every test except Block Design, answers were reported
orally to the examiner to minimize the effect of motor speed
on performance. All cognitive tests administered were used
in the present analyses.
A Swedish version of the Wechsler Adult Intelligence
Scale (WAIS) Information subtest (Jonsson & Molander,
1964) includes 22 items assessing general knowledge (e.g.,
“What is the population of Sweden?”). Respondents are al-
lowed 20 s to answer each question.
Synonyms is a 30-item forced-choice vocabulary test
(sample item: “Inform: divide, award, expire, distribute, an-
nounce”) from the Swedish Dureman–Sälde Battery (Dure-
man, Kebbon, & Osterberg, 1971). Respondents are allowed
3.5 min to finish each 15-item section.
Analogies is a 27-item Swedish test of verbal reasoning
(sample item: “Pen: Draw; Brush: Painting, Paint, Picture,
Frame”) in which respondents have 3.5 min to finish each of
two sections (Westrin, 1969).
Figure Logic is a 30-item visual reasoning test in which
respondents choose which one of five figures differs from
the other four (Dureman et al., 1971). Respondents have 4
min to complete each 15-item section.
Koh’s Block Design is a visuospatial test, similar to the
WAIS Block Design subtest, in which respondents create
designs using colored blocks (Dureman et al., 1971). Each
of its seven items is scored from 0 to 6 on the basis of the
amount of time the respondent takes to correctly complete
the design.
Card Rotations is a mental rotation task in which respon-
dents report whether each of four items is a rotated form of
a target design (Ekstrom, French, & Harman, 1976). Pos-
sible scores range from 0 to 112, and respondents have 2
min to complete each of two sections.
Figure Identification is a 60-item pattern-matching test
assessing perceptual speed and attention (Dureman et al.,
1971). Respondents report which of five options matches
a target item. They have 2 min to complete each 30-item
section.
The SATSA investigators collected data through surveys
mailed in 1984, 1987, 1990, and 1993. All intact SATSA
twin pairs who were at least 50 years of age or who turned
5
0 over the course of the study were invited to participate in
a supplemental in-person testing program consisting of cog-
nitive and medical assessments (Pedersen, Plomin, Nessel-
roade, & McClearn, 1992). Three waves of in-person testing
were conducted between waves of the mailed surveys. Data
were collected by registered nurses trained specifically to
administer the measures in a standardized fashion. The
twins were tested at locations close to their homes; for the
most part, district nurses’ offices, health care schools, and
long-term care clinics were used. An average testing session
took 4 hr.
A total of 755 individuals provided cognitive data on at
least one occasion. To ensure that the sample was cogni-
tively intact rather than in the early stages of a dementing
process, we retrospectively excluded from the analyses data
from participants who were diagnosed with dementia at any
point (n ϭ 51), yielding a final sample of 704. Of these, 568
completed at least two assessments, and 415 participated in
all three waves of cognitive testing. Not all participants en-
tered the study at the first wave of cognitive testing. Of
those who entered the study at the first or second wave, at-
trition was 24.5%. Previous research with the SATSA data
indicates that attriters score relatively more poorly than non-
attriters on measures of perceptual speed and visuospatial
skills, without controlling for age (Kasl-Godley, Pedersen,
Berg, & Gatz, 1996). In the current sample, older age pre-
dicted attrition, but gender, education, rearing status, state
anxiety, neuroticism, and performance on any cognitive test
did not, after controlling for age.
In Symbol Digit, respondents verbally report digits that

ANXIETY AND COGNITION
P249
correspond to symbols. They have 45 s to complete each of
older (Spielberger, 1979). The correlation between state anx-
iety scores at the second and third waves was .57. Correla-
tions between neuroticism and state anxiety scores were .38
at the second wave and .39 at the third wave. Age showed no
significant correlations with state anxiety but was negatively
correlated with neuroticism, r ϭ Ϫ.08, p ϭ .04. There were
no significant relationships between education and state anx-
iety, but the relationship between education and neuroticism
was significant, r ϭ Ϫ.07, p ϭ .05. Women reported higher
levels of neuroticism and state anxiety at both time periods
than men did, t(318) ϭ Ϫ2.98, p ϭ .003, t(236) ϭ Ϫ3.32,
p ϭ .001, t(203) ϭ Ϫ2.12, p ϭ .04.
Because prior investigations have found an effect of psy-
chotropic medications on cognitive performance in older
adults (e.g., Paterniti et al., 1999), we compared test scores
between those who did and those who did not report use of
such medications, including tranquilizers and sleeping aids,
within 30 days prior to the second and third wave of assess-
ments. Prevalence of medication use was 11% to 12% at
each period. Although medication users scored significantly
higher on state anxiety and neuroticism than nonusers did,
22.7 versus 17.1, t(62.3) ϭ Ϫ4.21, p Ͻ .001 (unequal vari-
ance; first time point), 22.2 versus 16.7, t(74.6) ϭ Ϫ4.92,
p Ͻ .001 (unequal variance; second time point), and 4.6 ver-
sus 2.5, t(65.9) ϭ Ϫ5.69, p Ͻ .001 (unequal variance; first
time point), we found no significant differences between re-
cent medication users and nonusers on any cognitive test at
either time point, so medication use was not included as a
covariate in these analyses.
1
0 groups of 10 items.
CVB-Scales Digit Span was scored as the sum of the
highest number of digits the respondent was able to repeat
correctly in each direction, ranging from 3–9 forward and
2
–8 backward (Jonsson & Molander, 1964). Respondents
were given two trials of different strings of digits for each
length span; correct performance on either string was
counted toward their final score.
In Names and Faces, respondents pair names with 16 pic-
tures of faces after viewing them for 1 min (DeFries, Plomin,
Vandenberg, & Kuse, 1981). Immediate and 30-min delayed
recall performance are summed to create a total score.
Thurstone’s Picture Memory tests recognition memory of
2
8 drawings of common items such as a truck and a table
(Dureman et al., 1971). Respondents are shown each picture
for 5 s; their response is not timed.
Anxiety was assessed using the 10-item State Anxiety
subscale of the State–Trait Personality Inventory (STPI;
Spielberger, 1979). This is a general state anxiety measure
that is not specific to cognitive performance or testing situa-
tions. The STPI contains a subset of the 20 items from the
State–Trait Anxiety Inventory, Form Y-1 (Spielberger,
1
983). In the present study, each item was scored on a 5-
point scale representing how the respondent was feeling “right
now, at this moment” from 1 (fits exactly) to 5 (does not fit
at all); this response format differs slightly from the 4-point
scale usually used with the STPI. The response format was
modified to be consistent with other personality scales ad-
ministered in the same battery.
The STPI was mailed to SATSA participants 10 days be-
fore their appointment for the second and third wave of in-
person testing sessions. The state anxiety questionnaire was
not completed immediately prior to the first wave of assess-
ments, so cross-sectional analyses of state anxiety and cog-
nitive performance could not be performed using the first
wave of cognitive data.
For longitudinal analyses, neuroticism was used as a
proxy for trait anxiety. Participants completed a nine-item
short form of the Eysenck Personality Inventory Neuroti-
cism scale as part of the mailed surveys (Pedersen et al.,
Statistical Analyses
Cognitive performance was analyzed using a random ef-
fects model (SAS PROC MIXED; SAS Institute, 2000). The
random effects model is a multilevel model that allows esti-
mation of overall fixed effects (the average model for the
entire group) and also allows for individual variation from
the group model (i.e., the random effects; Campbell, 1999;
Laird & Ware, 1982; Teri, Hughes, & Larson, 1990). Thus,
there is a model for the group and a model for each individ-
ual. It is possible to explain individual deviations from the
fixed model in terms of other covariates, such as anxiety.
Furthermore, this method of analyzing data allows for de-
pendent observations, such as members of twin pairs in
these analyses. In longitudinal analyses, correlations among
scores across time are accounted for and all available data
can be used, regardless of attrition. The maximum likeli-
hood approach was used to estimate parameters. The esti-
mation of the variances/covariances among the random co-
efficients was set to the unstructured option.
For the cross-sectional analyses, we used data from each
participant at the first measurement period in which the par-
ticipant completed both cognitive testing and a state anxiety
questionnaire (for most participants, this was the second
wave of cognitive testing). Gender, age, education, state
anxiety, and the Gender ϫ State Anxiety interaction were
entered into a PROC MIXED model as predictor variables
for each cognitive test score. Age and education were in-
cluded in the models because they consistently correlated
with most of the cognitive tests in univariate analyses. Gen-
der was included because gender differences are often found
1
984). Neuroticism data from the first measurement occa-
sion, typically the 1984 mailed SATSA survey, were used in
the present analyses.
State anxiety data were considered missing if the partici-
pant failed to answer two or more items; if only one anxiety
item was left blank, it was replaced with the average item
score for the individual. Respondents who answered at least
six of the nine neuroticism items received a valid score on
this measure. Two participants were missing neuroticism
data. Of the 558 who participated in the second wave of cog-
nitive testing, 15 were missing state anxiety data, and of the
5
4
37 who participated in the third wave of cognitive testing,
6 were missing state anxiety data. Average anxiety scores
were 17.7 (SD ϭ 7.3, range ϭ 10–49) at the second wave
and 17.4 (SD ϭ 7.1, range ϭ 10–46) at the third wave; the
average neuroticism score was 2.68 (SD ϭ 2.31, range ϭ 0–
9
6
). State anxiety scores were at approximately the 59th to
5th percentile for women and the 53rd to 58th percentile for
men, compared with a sample of working adults aged 33 or

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WETHERELL ET AL.
in some areas of cognitive performance. Age, education, and
state anxiety were mean-centered for these analyses. A
twin-pair identifier was entered into a random statement to
take into account nonindependence between twin partners.
We tested the significance of model fits by comparing the
difference between the Ϫ2 log likelihood ratio [Ϫ2 Log (L)]
for nested models; this value has a chi-square distribution
and can be evaluated for statistical significance accordingly.
Lastly, we present parameter estimates for each predictor in
the final model.
The longitudinal models contained the variables gender,
education, age, neuroticism, time, and several interactions:
Neuroticism ϫ Gender, Neuroticism ϫ Time, and Neuroti-
cism ϫ Time ϫ Gender. The goal was to analyze the effects
of neuroticism on cognitive change (the Neuroticism ϫ
Time interaction and the Neuroticism ϫ Time ϫ Gender in-
teraction), after controlling for other potentially confound-
ing effects. Age and education were mean-centered for these
analyses. Participants were included regardless of the num-
ber of assessments they completed. A variable denoted time
was created whereby an individual’s age at each time of
measurement was centered on that individual’s first age at
testing so that the individual intercepts reflect the percent
correct for each cognitive test at the first measurement occa-
sion; essentially the group or fixed effect intercept would
then reflect the average intercept at the first occasion. We in-
cluded a random statement for the pair as well as a random
statement for the individual to model correlations between
twin partners and correlations across time for each individ-
ual. The random effect for time tested the significance of in-
dividual variation in change over time. Again, we tested the
significance of model fits by comparing the difference be-
tween the Ϫ2 log likelihood ratio for nested models.
tests, including Information, Figure Logic, Card Rotations,
Figure Identification, Names and Faces, and Thurstone’s
Picture Memory, after controlling for education and age.
Men were advantaged in knowledge, visual reasoning, and
mental rotation; women, in visual memory and perceptual
speed.
Table 2 displays correlations among cognitive tests at
Time 2, between cognitive tests and predictor variables such
as age, education, state anxiety, and neuroticism at Time 2,
and autocorrelations between cognitive tests at different
time points. In general, higher level of education is associ-
ated with better performance on cognitive tests, whereas
older age is associated with poorer performance. State anxi-
ety and neuroticism are generally associated with poorer
performance on cognitive tests, although the magnitude of
the correlations is small and not typically significant.
State Anxiety and Cognitive Performance
Table 3 displays model fitting statistics (⌬␹ between Ϫ2
2
log likelihood values) for cross-sectional nested models and
the intercept and parameter estimates for each cognitive test.
Model 1 includes as fixed effects gender, age, education,
state anxiety, the State Anxiety ϫ Gender interaction, and
an intercept term. Model 2 includes all variables except the
State Anxiety ϫ Gender interaction. Model 3 drops both the
interaction and the main effect of state anxiety. The compar-
ison between Models 1 and 2 tests the significance of the
State Anxiety ϫ Gender interaction. The comparison be-
tween Models 2 and 3 tests the significance of the main ef-
fect of state anxiety. Models 1 and 2 were significantly dif-
ferent for Card Rotations and for Digit Span, indicating that
the State Anxiety ϫ Gender interaction was a significant
predictor of performance on these tests. Models 2 and 3
were significantly different for Synonyms, Analogies, Block
Design, Names and Faces, and Thurstone’s Picture Memory,
indicating that state anxiety was a significant predictor of
performance on these tests. We also tested a quadratic state
anxiety term to explore a curvilinear relationship between
anxiety and cognitive performance; this term was not signif-
icant for any cognitive test (results not shown).
RESULTS
Descriptive Statistics
Mean percent correct on the cognitive tests at each as-
sessment period is presented in Table 1. Gender was a sig-
nificant predictor of performance on a number of cognitive
Table 1. Cognitive Test Performance at Three Measurement Periods: Average Percentage Correct and
Standard Deviations for Men and Women
First
Second
Third
Cognitive Test (Domain)
Men
Women
Men
Women
Men
Women
Information (verbal knowledge)
Synonyms (vocabulary)
Analogies (verbal reasoning)
Figure Logic (visual reasoning)
Block Design (visuospatial)
Card Rotations (visuospatial)
Figure Identification (attention, speed)
Symbol Digit (speed, working memory)
Digit Span (attention, working memory)
Names and Faces (visual memory)
Thurstone’s Picture Memory (visual memory)
77.7 (16.4)
63.3 (19.7)
57.4 (15.9)
63.3 (12.4)
48.2 (18.1)
50.7 (17.8)
48.6 (12.0)
40.2 (11.7)
58.9 (12.9)
10.9 (10.8)
72.6 (16.5)
67.1 (18.0)***
63.0 (18.0)
53.2 (13.9)
58.6 (13.1)**
44.7 (18.0)
41.1 (16.5)***
50.1 (13.3)**
39.9 (11.7)
77.9 (15.8)
64.6 (18.8)
57.9 (14.5)
63.5 (13.4)
46.6 (17.2)
51.7 (17.2)
48.6 (12.5)
38.7 (11.8)
58.9 (12.5)
12.1 (11.9)
72.4 (17.6)
69.0 (17.2)***
64.3 (16.7)
55.2 (13.6)
59.0 (13.1)*
45.0 (17.0)
42.3 (16.0)***
50.9 (13.3)***
38.4 (11.8)
79.4 (15.5)
65.1 (19.0)
57.9 (16.2)
63.6 (14.0)
46.0 (17.7)
48.2 (19.1)
47.1 (13.8)
36.8 (13.0)
58.5 (13.7)
9.9 (10.2)
69.0 (16.9)***
64.2 (17.6)
54.1 (13.7)
58.6 (12.6)**
43.9 (17.2)
39.5 (16.8)***
50.2 (13.5)***
37.9 (12.0)*
57.7 (13.1)
57.4 (12.4)
13.3 (12.1)***
76.6 (15.3)***
58.4 (12.8)
14.3 (11.7)***
77.2 (15.4)***
14.0 (12.3)***
79.0 (15.3)***
72.3 (18.5)
n
288
62.8 (8.0)
416
64.4 (9.0)
238
65.5 (7.7)
330
67.2 (8.9)*
173
69.5 (6.5)
242
70.8 (8.2)
M age
*p Ͻ .05; **p Ͻ .01; ***p Ͻ .001, after controlling for age and education.

ANXIETY AND COGNITION
P251
Table 2. Correlation Matrix
Variable
1
2
3
4
5
6
7
8
9
10
11
1
2
3
4
5
6
7
8
9
. Information
. Synonyms
. Analogies
. Figure Logic
. Block Design
. Card Rotations
. Figure Identification
. Symbol Digit
. Digit Span
—
.68
.48
.40
.42
.24
.26
.43
.29
—
.59
.43
.49
.27
.37
.52
.43
.36
—
.46
.50
.40
.34
.51
.40
.29
—
.57
.47
.43
.52
—
.60
.59
.68
.39
—
.53
.58
.30
.23
—
.69
.31
—
.43
.44
.30
.28
—
.29
1
1
Age
0. Names and Faces
.27
.41
.36
—
1. Thurstone’s Picture Memory
.30
Ϫ.15
.37
.43
Ϫ.18
.39
.35
Ϫ.31
.44
.34
Ϫ.32
.29
.46
Ϫ.41
.33
.27
Ϫ.41
.21
.37
Ϫ.46
.21
.44
Ϫ.53
.33
.27
Ϫ.20
.27
.39
Ϫ.36
.24
—
Ϫ.26
.23
Education
State Anxiety
Neuroticism
Autocorrelations
IPT 1–IPT 2
IPT 2–IPT 3
Ϫ.08
Ϫ.06
Ϫ.11
Ϫ.07
Ϫ.14
Ϫ.06
Ϫ.06
Ϫ.06
Ϫ.12
Ϫ.10
Ϫ.09
Ϫ.03
Ϫ.00
Ϫ.01
Ϫ.05
Ϫ.05
Ϫ.04
Ϫ.03
Ϫ.08
Ϫ.09
Ϫ.10
Ϫ.11
.88
.87
.87
.88
.67
.70
.55
.58
.82
.82
.71
.81
.73
.79
.80
.84
.69
.66
.65
.68
.67
.69
Notes: IPT ϭ in-person testing. Correlation matrix depicts data from IPT 2, except for autocorrelations. Correlations above approximately .09 are significant at
p Ͻ .05.
Table 3 also shows the intercept and parameter estimates
tercepts are variance components and may be interpreted as
the variances of the participant-specific intercepts.
associated with each covariate as well as with state anxiety
and the State Anxiety ϫ Gender interaction (from Model 1).
The intercept reflects the average percent correct on each
cognitive test. The value of each parameter reflects the dif-
ference in percent correct on each cognitive test for each
point above the mean on the relevant variable (e.g., age, ed-
ucation, state anxiety). Women were considered the default
gender in these analyses, so parameter estimates for gender
were used to adjust scores for men. The random effects in-
Overall, state anxiety appears to have a significant effect
on visual learning (Names and Faces and Thurstone’s Pic-
ture Memory), even after controlling for covariates. Parame-
ter estimates indicate that for each point above the mean on
state anxiety, individuals score 0.20 and 0.25 below the
mean on Names and Faces and Thurstone’s Picture Mem-
ory, respectively. State anxiety was also associated with sig-
nificantly poorer performance on Synonyms, Analogies, and
Table 3. Model Fit Statistics and Fixed and Random Effect Parameters for Cross-Sectional Models With State Anxiety
Fixed Effectsc
Random Effects
Model
vs. 2
⌬␹ (1)
Model
2 vs. 3
⌬␹ (1)
State
Anxiety ϫ
Gender
1
State
Anxiety
2
a
2
b
Cognitive Test
Intercept
Gender
Age
Education
Intercept
Residual
Information
Synonyms
Analogies
Figure Logic
0.5
0.1
2.3
1.6
0.2
5.5*
2.8
0.0
8.5*
2.1
0.1
0.7
6.4*
9.0*
0.9
12.0*
2.1
0.3
3.4
0.1
4.8*
8.5*
69.86
65.22
55.76
59.81
46.57
42.88
51.93
39.17
58.67
15.35
77.88
6.59
Ϫ2.23
0.37
2.65
Ϫ1.63
7.29
Ϫ4.53
Ϫ1.75
Ϫ0.26
Ϫ4.16
Ϫ6.61
Ϫ0.16
Ϫ0.26
Ϫ0.43
Ϫ0.41
Ϫ0.77
Ϫ0.80
Ϫ0.69
Ϫ0.67
Ϫ0.23
Ϫ0.49
Ϫ0.47
6.10
6.77
5.64
3.22
4.88
1.73
1.83
2.77
3.23
2.39
3.52
Ϫ0.03
Ϫ0.26
Ϫ0.15
Ϫ0.01
Ϫ0.26
0.01
0.04
Ϫ0.10
0.11
Ϫ0.13
0.06
118.93
104.54
28.51
26.71
88.88
75.67
26.88
32.84
42.38
33.34
50.06
114.16
148.38
115.72
116.45
115.53
154.06
94.87
50.81
101.84
79.75
Ϫ0.25
Ϫ0.21
Ϫ0.08
Ϫ0.49
Ϫ0.25
Ϫ0.01
Ϫ0.45
0.21
Block Design
Card Rotations
Figure Identification
Symbol Digit
Digit Span
Names and Faces
Thurstone’s Picture Memory
Ϫ0.20
Ϫ0.25
Ϫ0.07
169.80
aThe chi-square values in this column represent the difference between the Ϫ2 Log (L) values associated with two nested models: Model 1 contains a random inter-
cept term and fixed intercept, gender, age, education, state anxiety, and State Anxiety ϫ Gender terms. Model 2 contains a random intercept term and fixed intercept,
gender, age, education, and state anxiety terms. The chi-square difference between these values tests the significance of the State Anxiety ϫ Gender interaction.
bThe chi-square values in this column represent the difference between the Ϫ2 Log (L) values associated with two nested models: Model 2 contains a random inter-
cept term and fixed intercept, gender, age, education, and state anxiety terms. Model 3 contains a random intercept term and fixed intercept, gender, age, and education
terms. The chi-square difference between these values tests the significance of the main effect of state anxiety.
cBecause the State Anxiety ϫ Gender interaction was significant for two cognitive tests, Card Rotations and Digit Span, parameter estimates are presented for
Model 1.
*p Ͻ .05.

P252
WETHERELL ET AL.
Block Design in this sample. No significant effects of state
anxiety were observed for Figure Identification, Symbol Digit,
Figure Logic, and Information. Men were more adversely af-
fected than women on Card Rotations and Digit Span.
ping the main effect of time. The comparison between
Models 3 and 4 tests the significance of the main effects of
neuroticism. Finally, the comparison between Models 3 and
5 tests whether, on average, scores decline over time for
each cognitive test.
Neuroticism, Cognitive Performance,
and Cognitive Decline
Model fitting statistics for longitudinal models (⌬␹ ) are
After controlling for all other effects, significant individ-
ual variation for time (random effects) was found for Infor-
mation, Block Design, Card Rotations, Symbol Digit, Fig-
ure Identification, Digit Span, and both memory tests.
Results indicate no significant interactions with neuroticism
over time on cognitive abilities. The main effect of neuroti-
cism on cognitive function was significant for Block De-
sign, Symbol Digit, and Names and Faces. The main effect
for neuroticism is not entirely consistent with results for
state anxiety reported above: Both state anxiety and neuroti-
cism were associated with poorer performance on one visuo-
spatial test (Block Design) and on a visual learning measure
(Names and Faces). State anxiety but not neuroticism was
associated with poorer performance on Synonyms, Analo-
gies, and Thurstone’s Picture Memory, and neuroticism but
not state anxiety was associated with poorer performance on
Symbol Digit. Only speeded and spatial tasks (Block De-
sign, Card Rotations, Symbol Digit, and Figure Identifica-
tion) evidenced a significant average effect of time.
2
presented in Table 4. Model 1 includes as fixed effects the
main effects of time, gender, age, education, and neuroti-
cism, and the interactions between neuroticism and gender,
neuroticism and time, and Neuroticism ϫ Gender ϫ Time,
as well as an intercept term. Random effects include an in-
tercept term and time. Model 2 includes the same set of
fixed effects but drops the random effect of time. The com-
parison between Models 1 and 2 tests whether there is sig-
nificant individual variation in change over time on each
cognitive test. Model 3 includes the random effects intercept
term and time and drops the fixed effects interaction terms
Neuroticism ϫ Time, Neuroticism ϫ Gender, and Neuroti-
cism ϫ Gender ϫ Time. The comparison between Models 1
and 3 tests the significance of the interaction terms, includ-
ing interactions with time, in the fixed effects model. Model
4
is the same as Model 3 after dropping the main effect of
neuroticism, and Model 5 is the same as Model 3 after drop-
Table 4 also presents the intercepts and parameter esti-
Table 4. Model Fit Statistics and Fixed and Random Effect Parameters for Longitudinal Models With Neuroticism
Fixed Effectse
Random Effectsf
Model Model Model
Model
1
vs. 2 1 vs. 3 3 vs. 4 3 vs. 5
Edu- Neurot-
2
a
2
b
2
c
2
d
Cognitive Test
⌬␹ (2) ⌬␹ (4) ⌬␹ (1) ⌬␹ (1) Intercept Gender
Age
cation
icism
Time
Intercept Time
rINT,TIME Residual
Information
Synonyms
Analogies
13.6*
0.8
1.4
1.2
4.7
1.2
0.4
4.0
1.7
1.9
1.3
3.1
2.4
1.0
2.1
3.3
1.4
9.4*
2.1
2.0
4.0*
0.1
6.5*
2.4
0.0
0.0
68.97
65.22
55.05
59.86
48.39
43.10
51.68
41.39
58.59
15.32
8.11
Ϫ2.11
1.54
2.94
Ϫ0.54
7.56
Ϫ3.43
Ϫ1.77
0.14
Ϫ0.34
Ϫ0.35
Ϫ0.54
Ϫ0.48
Ϫ0.87
Ϫ0.76
Ϫ0.75
Ϫ0.74
Ϫ0.24
Ϫ0.53
6.70
7.91
5.95
3.55
4.92
2.24
2.07
3.26
3.53
2.38
Ϫ0.24
Ϫ0.38
Ϫ0.22
Ϫ0.21
Ϫ0.71
Ϫ0.35
Ϫ0.24
Ϫ0.30
Ϫ0.04
Ϫ0.40
0.11
0.01
0.00
219.11
238.57
96.59
68.86
203.90
168.12
87.25
62.58
80.15
70.78
0.41
0.15
0.16
0.24
1.15
0.52
0.38
0.30
0.17
0.57
Ϫ0.41
36.50
40.98
63.97
74.50
47.97
69.50
38.05
23.53
51.37
41.76
Ϫ0.16
Ϫ0.26
Ϫ0.20
Ϫ0.42
0.04
Ϫ0.06
0.12
0.35
Figure Logic
Block Design
Card Rotations
Figure Identification
Symbol Digit
Digit Span
Names and Faces
Thurstone’s Picture
Memory
1.6
0.0
0.00
20.5*
10.4*
9.0*
17.3*
6.4*
6.3*
16.2*
24.5*
9.3*
79.4*
3.5
Ϫ0.36
Ϫ0.50
Ϫ0.24
Ϫ0.62
Ϫ0.15
0.03
0.1
Ϫ4.36
Ϫ0.27
17.9*
4.0
2.1
1.0
78.23
Ϫ6.28
Ϫ0.53
3.43
Ϫ0.32
0.11
150.21
1.89
Ϫ0.25
76.25
aThe chi-square values in this column represent the difference between the Ϫ2 Log (L) values associated with two nested models: Model 1 contains random time
and intercept terms and fixed intercept, time, gender, age, education, neuroticism, and Neuroticism ϫ Gender, Neuroticism ϫ Time, and Neuroticism ϫ Gender ϫ
Time terms. Model 2 contains a random intercept term and fixed intercept, time, gender, age, education, neuroticism, and Neuroticism ϫ Gender, Neuroticism ϫ Time,
and Neuroticism ϫ Gender ϫ Time terms. The chi-square difference between these values tests the significance of individual variations in change over time.
bThe chi-square values in this column represent the difference between the Ϫ2 Log (L) values associated with two nested models: Model 1 contains random time
and intercept terms and fixed intercept, time, gender, age, education, neuroticism, and Neuroticism ϫ Gender, Neuroticism ϫ Time, and Neuroticism ϫ Gender ϫ
Time terms. Model 3 contains random time and intercept terms and fixed intercept, time, gender, age, education, and neuroticism terms. The chi-square difference be-
tween these values tests the significance of interactions between neuroticism and gender, neuroticism and time, and Neuroticism ϫ Gender ϫ Time.
cThe chi-square values in this column represent the difference between the Ϫ2 Log (L) values associated with two nested models: Model 3 contains random time
and intercept terms and fixed intercept, time, gender, age, education, and neuroticism terms. Model 4 contains random time and intercept terms and fixed intercept,
time, gender, age, and education terms. The chi-square difference between these values tests the significance of the main effect of neuroticism.
dThe chi-square values in this column represent the difference between the Ϫ2 Log (L) values associated with two nested models: Model 3 contains random time
and intercept terms and fixed intercept, time, gender, age, education, and neuroticism terms. Model 4 contains random time and intercept terms and fixed intercept,
gender, age, education, and neuroticism terms. The chi-square difference between these values tests the significance of the main effect of time.
e
Parameter estimates are presented for Model 3.
f
The random variance parameters are the sum of within-pair and between-pair systematic variance components calculated from factor analytic loadings. The corre-
lation between intercept and slope, denoted rINT,TIME, is the correlation calculated on the basis of the systematic variance/covariance matrix (the sum of within-pair and
between-pair variance/covariance components calculated from factor analytic loadings).
*
p Ͻ .05.

ANXIETY AND COGNITION
P253
mates for Model 3, including the main fixed effects for neu-
roticism and time but not including any interaction terms
with neuroticism. In these analyses, the main effect of vari-
ables such as age, education, and neuroticism reflects the
difference in percent correct on each cognitive test for each
point above the mean on the score for that variable. The
fixed effect for time quantifies the rate of change in percent
correct on each cognitive test per year. The parameter esti-
mate for gender is used to adjust scores for men. The ran-
dom effects intercept and time may be interpreted as the
variances of the participant-specific intercepts and slopes,
respectively. The correlation between the participant-
specific (random effects) intercept and time indicates that,
for example, individuals with higher initial scores on Infor-
mation and Block Design have steeper rates of decline,
whereas individuals with higher initial scores on Digit Span
have slower rates of decline (flatter slopes).
more than working memory. As appears to be the case with
Figure Identification, anxiety-related differences on Symbol
Digit performance may be negligible compared with the ef-
fect of age on processing speed in this older sample. Failure
to find an effect of state anxiety on Figure Logic, while find-
ing such effects for Block Design and, for men, Card Rota-
tions, may be explained by the fact that Figure Logic was
easier than the other visuospatial tasks (Table 1). Figure
Logic may have been insufficiently difficult to call on the re-
sources of the central executive enough to be vulnerable to
the effects of state anxiety on working memory. The main
effect of state anxiety on Synonyms performance cross-
sectionally was unexpected because Synonyms is often con-
sidered a test of well-learned knowledge. In this sample,
Synonyms correlated most highly with Information, another
test that is considered a measure of verbal knowledge (Table
2). However, Eysenck (1992) cited evidence from younger
samples that high neuroticism is associated with long-term
basic deficits such as poorer vocabulary and with behaviors
that could interfere with learning, such as poorer study hab-
its. Although we did not find an association between neurot-
icism and Synonyms performance, these mechanisms may
account for state-anxiety–based deficits in verbal knowl-
edge in this sample.
As a measure of effect size, we calculated the proportion
of variance explained by the growth model (variance ex-
plained by intercept and slope as a percent of total vari-
ance). Results ranged from .48 for Figure Logic to .85 for
Information and Synonyms, with a median of .71.
DISCUSSION
We hypothesized that higher levels of state anxiety would
be associated with poorer performance on tests that tap the
phonological loop or central executive functions of working
memory, namely Analogies, Block Design, Card Rotations,
Digit Span, Figure Logic, Names and Faces, Symbol Digit,
and Thurstone’s Picture Memory, but not on tests of verbal
knowledge such as Information and Synonyms or simple vi-
sual pattern matching as in Figure Identification. This hy-
pothesis was partially supported: Significant effects of state
anxiety were found for visual learning and complex visu-
ospatial skills, as expected, and were not found for Informa-
tion or Figure Identification. Additionally, significant inter-
actions between state anxiety and gender were found for
two tests, Card Rotations and Digit Span. For both of these
tests, men with higher levels of state anxiety performed
more poorly than less anxious men did. However, contrary
to expectations, the association between state anxiety and
cognitive performance was not significant for Figure Logic
or Symbol Digit and was significant for Synonyms.
We failed to support our second hypothesis that neuroti-
cism, a proxy for trait anxiety, would be associated with de-
clines in memory and complex visuospatial skills but not
with declines in other cognitive domains. We found no sup-
port for neuroticism as a predictor of age-associated decline
on any test in this cognitively intact older sample. Neuroti-
cism was associated with poorer average performance
across time on one measure of visuospatial skills, one mea-
sure of visual memory, and a test of perceptual speed and
processing. We found decline over time on average on
speeded and spatial tasks and individual differences in de-
cline on speeded, spatial, and memory tasks, as well as on
Information. These findings suggest that higher levels of
neuroticism are not generally associated with longitudinal
cognitive decline in normal aging.
Limitations and Advantages
One limitation of this study involves the measurement of
anxiety. Ideally, the state anxiety measure should have been
given within minutes, rather than days, of cognitive testing.
Furthermore, the state anxiety measure was completed in a
more familiar environmental setting (the person’s home)
than the cognitive testing was. A scale administered at the
same time and place as the cognitive battery would probably
have produced higher and more variable state anxiety scores
than were observed in the present study, because vulnerable
individuals would likely experience greater anxiety in a
novel setting when about to undergo cognitive testing. In-
creased variability of state anxiety scores would provide
greater power to discover relationships between anxiety and
cognitive performance. Hence, our methodology likely
underestimated the effects of state anxiety on cognitive
performance.
Additionally, neuroticism was used as a proxy for trait
anxiety. Although these constructs are related, they are not
identical. Neuroticism may capture additional elements
(such as vulnerability to other negative emotions like de-
pression or anger) that are not inherently part of trait anxi-
ety. Use of a true trait anxiety scale may have increased
power to detect significant longitudinal relationships be-
tween anxiety and cognition.
Other investigators have found that the way anxiety is
measured can influence results. Domain-specific measures
assessing anxiety about cognitive abilities tend to be more
sensitive predictors of memory performance than general
state anxiety measures are (Cavanaugh & Murphy, 1986;
Davidson, Dixon, & Hultsch, 1991; Lachman, Baltes, Nes-
selroade, & Willis, 1982). The present study used a very
commonly employed general state anxiety measure, not a
measure of test anxiety. If anything, this approach may have
minimized the effects of anxiety on cognitive performance.
The failure to find an effect of state anxiety on Symbol
Digit suggests that this test may assess perceptual speed

P254
WETHERELL ET AL.
The sample was composed of racially and culturally ho-
ure Identification) than on working memory was not related
to state anxiety.
mogeneous Swedish twins; findings may differ in a more di-
verse sample. Twins may differ from single-birth individu-
als in ways that affect cognition or anxiety in later life,
although evidence suggests that registry-based twin samples
are representative, and findings from twin samples are com-
monly considered generalizable to a broader population.
Previous investigations have used twin samples such as the
National Heart, Lung, and Blood Institute Twin Study and
the Australian Twin Registry for longitudinal analyses,
treating participants as genetically unrelated individuals
The pattern of results further suggests that cognitive per-
formance is more sensitive to state anxiety than to neuroti-
cism, a proxy for trait anxiety. This would also be consistent
with processing efficiency theory’s emphasis on verbal pro-
cesses such as worry interfering with cognitive perfor-
mance. These processes are a state phenomenon, although
they may occur more frequently in individuals with high
trait anxiety.
Finally, this study provides no support for neuroticism as
a risk factor for cognitive decline. Although tasks that typi-
cally show age-related decline may be affected by anxiety,
general anxiety proneness does not appear to be related to
accelerated rates of decline. Of course, neuroticism is not
synonymous with trait anxiety. Future research should re-
visit the relationship between anxiety and cognitive decline
using a better measure of trait anxiety than neuroticism.
(
Dunne, Martin, Pangan, & Heath, 1997; Swan et al., 1998).
In this study, we used random effects models to allow for
the analysis of dependent observations, in effect controlling
for correlations between twin partners, to test hypotheses
about the relationship between anxiety and cognitive perfor-
mance across individuals. A related study could use these
models to explore individual differences by comparing pre-
dicted values to actual performance, but this was not the fo-
cus of the present investigation. A further limitation is that
approximately half of the sample were separated from their
twin partner in early life. This unusual feature may limit
generalizability, although age and education level, on which
differences were found between twins reared apart and
those reared together, were included as covariates in these
analyses.
Both memory measures in this battery tested visual, as
opposed to verbal, memory. Tests of nonverbal memory
have typically been overlooked in studies of anxiety in older
samples, an important reason for using them here. However,
because verbal memory tasks draw on resources from both
the phonological loop and the central executive of working
memory, they may be more vulnerable to the effects of anx-
iety than visual memory tests are.
Acknowledgments
The Swedish Adoption/Twin Study of Aging is supported by National
Institute on Aging Grants AG-04563 and AG-10175, the MacArthur Foun-
dation Research Network on Successful Aging, and the Swedish Council
for Social Research. Support for the dementia evaluations comes from Na-
tional Institute on Aging Grant AG-08724. Julie Loebach Wetherell was
supported by National Institute of Mental Health Grant NRSA MH-11972.
Julie Loebach Wetherell is now with the Department of Psychiatry, Uni-
versity of California, San Diego and the VA San Diego Healthcare System.
Address correspondence to Julie Loebach Wetherell, Department of
Psychiatry, University of California at San Diego, VA San Diego Health-
care System (116A-1), 3350 La Jolla Village Drive, San Diego, CA 92161.
E-mail: jwetherell@ucsd.edu
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&
Received April 5, 2000
Accepted July 18, 2001
Decision Editor: Margie E. Lachman, PhD
7