Psychology and Aging
1998, Vol. 13, No. 3, 445-461
Copyright 1998 by the American Psychological Association, Inc.
0882-7974/98/$3.00
Relation of Task Switching to Speed, Age, and Fluid Intelligence
Timothy A. Salthouse, Nathanael Fristoe, Katheryn E. McGuthry, and David Z. Hambrick
Georgia Institute of Technology
Two studies were conducted to investigate whether a meaningful task-switchingconstruct could be
identified and, if so, to determine how it was related to measures of higher order cognition and to
adult age. Both studies revealed that measures of task switching were moderately correlated across
differentcombinationsof tasks and that a switchingconstruct could be distinguishedfrom a construct
reflecting processing speed. The results of the 2nd study revealed that although the task-switching
construct was related to age and to measures of episodic memory, inductive reasoning, and spatial
visualization,most of the relations between the switching construct and both age and other measures
of cognition were shared with other variables.
There is considerable evidence that measures of perceptual
speed share large proportions of age-related variance with many
cognitive variables. It has even been postulated that processing
speed, which is hypothesized to be a primary construct assessed
by measures of perceptual speed, may be involved in the mediation of much of the age-related influences on measures of cognitive functioning (Salthouse, 1993b, 1994, 1996). However, perceptual speed may not be the most primitive psychological variable responsible for age-related individual differences in
processing efficiency. That is, because perceptual speed tasks
are so simple, the primary way that performance can vary across
people is in terms of the time needed to complete the activities,
but this does not necessarily mean that alterations in the speed
of executing cognitive operations are the cause of the individual
differences observed on those tasks.
Perceptual speed tasks involve a series of repetitive operations
and responses. The nature of the operations varies according to
the type of task because search, comparison, matching, and
substitution operations have each been used in assessing perceptual speed. However, all perceptual speed tasks seem to require
multiple switching or attention-redirecting operations. For example, in perceptual comparison tasks the respondent needs to
focus on the first element and encode it, switch attention to the
second element and encode it, make a decision, switch attention
to make a response, execute the response, and then switch attention to the next item and repeat the sequence of operations.
Switching ability could be an important cognitive primitive
because nearly all cognitive tasks require processing to be controlled and reallocated across different components. To illustrate,
working memory is often defined as simultaneous storage and
processing, and thus some switching or redirection of attention
between aspects of storage and processing is presumably necessary for successful functioning of working memory. Failure of
this type of attentional control could also be manifested in problems of perseveration, difficulties in dividing attention, etc. In
fact, some theorists (e.g., Baddeley, 1996) believe that these
processes are so important that they are considered to be primary functions of a central executive system.
These speculations raise the possibility that efficiency of
switching may be a critical factor contributing to age-related
differences in both perceptual speed and higher order cognitive
abilities. In other words, it may not be individual operations
that are slowed with increasing age, but rather the processes
responsible for switching between operations. Speed differences
associated with increasing age could therefore be restricted to
an inertia related to altering the nature of the processing carried
out and not necessarily to reductions in the efficiency of executing a particular operation once it is selected and initiated.
At least two possible approaches might be employed to investigate the role of task switching on adult age differences in
cognitive functioning. One approach could attempt to minimize
or eliminate switching operations in the task to determine
whether this would lead to smaller individual (and age-related)
differences on the measures of performance and weaker relations
between those measures and various cognitive variables. That
is, if switching is a critical process contributing to age-related
differences in cognitive functioning, then one would predict that
measures from tasks with fewer switching requirements should
be less related to age and to measures of performance in many
cognitive tasks involving attentional control than measures from
tasks with greater switching requirements.
Some evidence relevant to this prediction is available from
several previous studies. For example, a number of studies have
administered digit digit and digit symbol reaction time tasks to
participants of a wide range of ages. Both of these tasks require
the respondent to make rapid binary decisions about pairs of
items presented in the middle of a computer screen. In the digit
symbol task a code table at the top of the screen contains pairs
of digits and symbols, and the decision is whether the probe
items are associated with one another according to the code
TimothyA. Salthouse, Nathanael Fristoe, KatherynE. McGuthry,and
David Z. Hambrick, School of Psychology, Georgia Institute of
Technology.
This research was supported by National Institute on Aging Grant
R37 AG06826. We would like to acknowledge the valuable assistance
in testing participants and scoring of data of Kellie Hocking, Stephanie
Sherwood, and Michelle Wolbrette.
Correspondence concerningthis article should be addressed to Timothy A. Salthouse, School of Psychology, Georgia Institute of Technology, Atlanta, Georgia 30332-0170. Electronic mail may be sent to
tim.salthouse@psych.gatech.edu.
445
446
SALTHOUSE, FRISTOE, McGUTHRY, AND HAMBRICK
table. In the digit digit task both items in the probe pair are
digits and, because the decision is whether the two members of
the pair are physically identical, there is no need to refer to the
code table because it merely contains identical pairs of digits.
The digit digit task almost certainly has fewer switching requirements than the digit symbol task because there is no need to
consult the code table, or to try and remember the pairings of
digits and symbols. A consistent finding across several studies
has been that the age relations are smaller on the digit digit
measure than on the digit symbol measure and that there is
significant residual age-related variance on the digit symbol
measure after control of the digit digit measure (e.g., see Salthouse, 1996, for a review). The relations to various cognitive
variables are also generally smaller with the digit digit measure
than with the digit symbol'measure (e.g., Salthouse, 1994).
Although results with the digit digit and digit symbol tasks are
consistent with the hypothesis that switching is a fundamental
construct involved in age-cognition relations, they cannot be
considered conclusive because the relevant tasks do not differ
merely in the amount of switching that is required, but also
in the amount of cognitive processing. That is, the additional
operations in the digit symbol task are more cognitive in nature
than the operations involved in the digit digit task (e.g., retrieval
of learned associates, or search of the code table), and therefore
the critical difference between the tasks may be with respect to
the degree of cognitive involvement rather than the amount of
switching. Attempts could be made to increase the complexity of
the response to vary the amount of switching without increasing
cognitive complexity. However, this would probably not be easy
to achieve because the cognitive demands in the situation will
likely increase whenever a more complex or extended response
is required.
Another reason why the approach of varying the amount of
required switching does not appear promising is that even the
simplest repetitive tasks are likely to involve multiple switching
requirements because there is always a need to switch from one
item to the next and, within a given item, to switch between
operations such as encoding and response. It might therefore be
quite difficult to create a powerful contrast between tasks in
which there were small and large amounts of attentional
switching.
A second approach to investigating the role of switching in
age-cognition relations is to attempt to measure the efficiency
of switching directly. That is, a task (or tasks) might be administered in which it is possible to measure the time and accuracy
costs of switching. Several studies have been reported with tasks
that might be suitable for this purpose. For example, adult age
differences in switching have been examined in tasks requiring
alternations between two auditory or visual channels (e.g., Barrett, Mihal, Panek, Stems, & Alexander, 1977; Braune & Wickens, 1985; Stankov, 1988; Wickens, Braune, & Stokes, 1987).
Most of these studies found reduced effectiveness of switching
with increased age, although several of them only reported age
relations on factor scores based on other variables in addition
to those reflecting the efficiency of switching. A number of
researchers have also compared performance on single and alternating versions of simple tasks such as addition and subtraction,
or providing antonyms and synonyms (e.g., Botwinick, Brinley, & Robbin,1958; Brinley, 1965; Schaie, 1958). Each of these
studies reported that with increased age there was a greater
increase in time for alternating problems than for the average
of the single problems.
A great many age-comparative studies have examined the
Trail Making Test (Reitan, 1992), in which the task is to connect
a series of targets as rapidly as possible. There are two versions
of the test. In Version A the targets are numbers (e.g., 1-2-3-4,
etc.), and in Version B the targets are alternating letters and
numbers (e.g., 1-A-2-B, etc.). The typical finding in studies with
adults of different ages is much larger age-related differences on
the time to complete the B version than the A version, which
has been attributed, among other things, to a difficulty in alternation or switching (see references in Salthouse & Fristoe, 1995).
In a recent study, Salthouse, Fristoe, and Rhee (1996) administered a battery of different cognitive tests, including the Trail
Making Test and several tests of perceptual speed, to 259 adults
between 18 and 94 years of age. Because Trails B requires
alternation between numbers and letters whereas Trails A does
not, the time difference between the B and A versions of the
Trail Making Test can be used as an index of switching time.
The data from the Salthouse et al. (1996) study were therefore
reanalyzed with structural equation models to examine the relations among age, speed, switching, and measures of cognitive
performance. Two models (Figure 1 ) were considered that were
structurally identical except that in one case a path was specified
from the switching measure to the speed construct, and in the
other case the direction of this path was reversed. Both models
had the same fit to the data; for example, X2(41, N = 259) =
147.09, NNFI = .90, CFI = .93, Std. RMR = .05.1 However,
two of the three relations among age, speed, and the switching
measure were stronger when the path was from the speed construct to the switching measure instead of from the switching
measure to the speed construct. Further examination of the resuits in Figure 1 reveals that statistical control of speed reduces
the age-switch relation by 64% (from .53 to .19), whereas
statistical control of the switching measure reduces the agespeed relation by only 22% (i.e., -.73 to - . 5 7 ) . One possible
implication of these results is that perceptual speed may be
more fundamental with respect to relations between age and
cognition than a construct related to switching.
Unfortunately, a weakness of this reanalysis is that the Salthouse et al. (1996) study had a very gross measure of switching.
That is, the Trails B minus Trails A measure is crude because
it includes many processes in addition to switching. As just
one example, connecting the targets in alphabetic sequences
is usually slower than connecting them in numeric sequences
(Salthouse & Fristoe, 1995), and hence the B version relative
to the A version involves both the requirement to switch between
sequences and the introduction of a more difficult sequence.
The strategy employed in the current project involved administering several sets of tasks in single and alternating versions.
1The degree of fit in structural equation models can be evaluated in
terms of the chi-square statistic assessing deviations of fit (i.e., smaller
is better), in terms of the Non-NormedFit Index (NNFI) and the Comparative Fit Index (CFI) reflectingthe extent to which the model reproduces the covariance matrix (i.e., closer to 1.0 is better) and in terms
of the standardizedroot mean square residual (Std. RMR) between the
fitted and observed covariance matrices (i.e., closer to 0 is better).
TASK SWITCHING
447
Figure 1. TWo structural models based on data from Salthouse, Fristoe, and Rhee (1996). The variables
in the analysis were letter comparison (LetCom), pattern comparison (PatCom), digit symbol substitution
(DigSym), the difference between time on Trial Making versions B and A (Trails B-A), object assembly
(ObjAssm), block design (BlkDes), number of categories in the ,WisconsinCard Sorting Test (WCST),
Shipley Abstraction Test (Shipley), Rey Auditory Verbal Learning Test (RVLT), and paired associates
(PairAssoc). Note that the relation between age and speed was negative because speed was assessed in
terms of paper-and-penciltests in which performance was represented by the number of items completed
in a fixed period of time. The top panel portrays the coefficients when there is a path from the Trails B Trails A measure to perceptual speed, and the bottom panel portrays the coefficients when this path is
reversed.
However, there are at least two reasons why performance could
be slower when tasks must be performed in alternation compared
to when they are performed in isolation (cf. Rogers & Monsell,
1995). First, the response time could be delayed whenever a
switch between tasks is required (i.e., the direct costs of switching), and second, the time could be slower even on nonswitch
responses because of the uncertainty associated with expecting
or preparing for a switch. An assumption of our approach is
that it should be possible to distinguish between these processes
with suitable reaction time procedures in which time and accuracy are measured on each response.
The tasks in the studies to be described are related to those
used in several recent studies of task switching reported by
Allport, Styles, and Hsieh (1994); Duncan, Emslie, Williams,
Johnson, and Freer (1996); Kramer, Hahn, and Gopher (in
press); Rogers and Monsell ( 1995 ); and Rubenstein, Meyer, and
Evans (in press). In each set of tasks two different, but equally
simple, decisions can be made to the same stimuli. The trials
within the critical switching condition began with a set of responses according to one decision rule, and then on some trials
a signal was presented indicating that the responses should
switch to the other decision rule. The time and accuracy of the
initial and subsequent responses following the switch signal
relative to the time and accuracy of responses prior to the switch
448
SALTHOUSE, FRISTOE, McGUTHRY, AND HAMBRICK
signal can be used as the measures of switching costs. Furthermore, the time and accuracy of responses prior to the switch
signal can be compared with the time and accuracy of responses
when no switches occur to evaluate uncertainty costs, or what
Rogers and Monsell (1995) describe as the time " t o maintain
two task-sets in an available state rather than o n e " (p. 216).
Our procedure involved presenting a task with one version or
decision rule, then a task involving the same stimuli with a
second decision rule, then two blocks of alternating tasks, followed by the second and first tasks again.
A major limitation of much of the earlier research concerned
with switching, and of the reanalysis of the Salthouse et al.
(1996) data, was the use of only a single set of tasks. The
theoretical construct of interest, in this case switching efficiency,
is therefore confounded with a specific operationalization of it.
This general problem has been recognized at least since the
classic article by Garner, Hake, and Erikson (1956), who suggested that converging operations are needed to ensure that the
constructs under investigation are not specific to the particular
methods by which they are operationalized.
As a means of addressing this problem, each participant in
the current studies performed three pairs of tasks involving
different types of decisions. Figure 2 illustrates the three tasks,
with responses based on the digits appearing on the right versus
on the left ( A ) , responses based on m o r e - l e s s versus o d d even decisions ( B ) , and responses based on addition versus
subtraction (C), In each case a box surrounding the target stimulus served as the signal to switch to the other response rule.
Note that the tasks are structurally parallel to allow similar
measures of switching performance to be derived from each.
Figure 3 illustrates possible measures of performance in these
tasks. The description is in terms of time, but comparable measures can be derived from error percentages. The dashed line
labeled F refers to the average times across the single tasks in
the first two and last two blocks of trials, when no switches
are required. The remaining points refer to times in the switch
condition for the switch response and for the three responses
preceding and following the switch. The duration labeled A,
corresponding to the difference between the reaction time on
the switch trial and the average reaction time across the three
immediately preceding trials, can be postulated to reflect the
time to redirect attention to the new task and implement the
relevant decision rule. Durations corresponding to B, C, and D
reflect any residual costs of the switch on responses following
the trial in which the switch was to have occurred.
Because of the interest in investigating the interrelations of
measures from different tasks, correlations among the measures
were examined. Two important prerequisites for the meaningful
interpretation of correlations are adequate reliability and moderately large samples. Estimates of the reliability of the relevant
measures should be obtained because they indicate the proportion of variance in the variables that is systematic and available
to be associated with other variables. That is, if the reliability
estimates, essentially representing the degree to which the variable correlates with itself, are not fairly high, then one cannot
expect the variable to have high correlations with other variables. Moderately large samples are needed to have narrow
confidence intervals around the estimates of the correlations.
Although correlations can be computed with any size sample,
(A)
StartwithRIGHT
Response
6
2
4
SwitSwitchtoRiGHTII I
(B)
st=twith MORE/LESS
5
3
Response
Z
/
X
Z
(c)
StartwithADDITION
Response
5
1
SUBTRACTION~
3
Switchto
ADDITION
114 311
I'
I
7
Figure 2. Displays of the series of events in the Right/Left (A), More/
Odd (B), and Add/Subtract (C) switching tasks. Note that different
sets of response keys were used for the more/less and odd/even tasks
in panel (B).
the precision of the correlation is inversely related to the size
of the sample on which it is based.
Two studies are reported in the current article. The purpose
of the first study was to investigate the reliability of the various
switching measures and to determine whether a switching construct can be identified that is distinct from speed. Because the
initial study was focused on methodological issues, only college
students served as participants. The second study was designed
to investigate the mediational role of switching in age-cognition
relations, and thus the participants consisted of adults from a
wide range of ages.
Study 1
Method
Participants. The sample of participants consisted of 100 college
students (53 males, 47 females), with a mean age of 20.0 years and a
standard deviation of 2.8 years. Each received credit for a course requirement as compensation for participation.
449
TASK SWITCHING
t..
LU
(D
A = InitialSwitchCost
B = Switch+ 1 Cost
to
C = Switch + 2 Cost
D = Switch+ 3 Cost
O
EL
¢D
E
t-
E = Uncertainty Effect
....................................................................
~
F
° ~
F -- Performance with no switches
O
13
¢u
nr"
I
-3
I
-2
I
-1
I
0
I
+1
I
+2
I
+3
Switch Position
Figure 3. Schematic illustration of possible measures of task switching.
Procedure. All participants performed the three sets of tasks in the
same order (right-left, more-odd, and add-subtract). The decision
rules for the tasks were to press the key corresponding to the digit
appearing on either the right (right) or left (left) of the display, press
the slash (/) key if the digit was more than 5 and the Z key if it was
less than 5 (more-less), or press the period (.) key if the digit was
even and the X key if the digit was odd (odd-even), and press the digit
corresponding to either the sum of (addition) or the difference between
(subtraction) the two digits. The same digits were never repeated on
successive trials, and the digit 5 never appeared in the more-less and
odd-even tasks. When two digits were presented simultaneously, the
one on the left was always greater than the one on the right, and all
answers in the addition and subtraction tasks were between 1 and 9.
Whenever the tasks were to be alternated an instruction as to which task
was to be performed first was displayed prior to the initial trial in the
block. Nine trials with a particular task occurred between presentations
of the signal indicating a switch to the other task. 2
Each task was administered in a set of nine blocks of trials after the
presentation of written instructions. The first two blocks each consisted
of 10 trials of practice with one of the two tasks in the set. The next
practice block consisted of 20 trials in which two switches were required.
If there were no questions following the practice trials the sequence of
experimental trials began. This consisted of 50 trials with one task (e.g.,
respond to the right digit), 50 trials with the other task (e.g., respond
to the left digit), two blocks each of 100 trials with 10 switches in the
alternating or switch condition, 50 trials with the second task (e.g.,
respond to the left digit), and 50 trials with the first task (e.g., respond
to the right digit).
In each set of tasks the participants were instructed to respond, with
the index fingers of each hand, as rapidly and accurately as possible.
The stimuli resembled those illustrated in Figure 2, with each digit
occupying a visual angle of approximately 10.2 degrees at a viewing
distance of 50 cm; however, it should be noted that viewing distance
was not constrained. A given stimulus was displayed until the occurrence
of a response, and that response was followed immediately by the presentation of the next stimulus. The rectangle serving as the switch signal
appeared simultaneously with the stimulus on the switch trials.
Results and Discussion
Assessment of switch costs. T h e m e d i a n times and error
p e r c e n t a g e s w e r e c o m p u t e d in the t w o blocks o f each condition
for e a c h participant, and the values for the t w o blocks w e r e
averaged for s u b s e q u e n t analyses. Figure 4 illustrates the m e a n
reaction times and error p e r c e n t a g e s for the relevant m e a s u r e s
in the t h r e e tasks. The m e a n reaction times for the single tasks
in each task set w e r e similar and highly c o r r e l a t e d with o n e
another (i.e., right = 864, left = 856, r = .89; m o r e - l e s s =
596, o d d - e v e n = 633, r = .76; and add = 1,006, subtract =
1,080, r = .87), and thus the t w o values were averaged to f o r m
a single baseline reaction time m e a s u r e for e a c h pair o f tasks.
A s y m m e t r y o f switching was e x a m i n e d by c o m p u t i n g the m e dian time for switch r e s p o n s e s in each direction (e.g., add-tosubtract and s u b t r a c t - t o - a d d ) . T h e s w i t c h times w e r e similar,
and not significantly ( p < .01) different, for both t y p e s o f
s w i t c h e s in each task c o m b i n a t i o n (i.e., r i g h t - l e f t = 1,415 ms,
l e f t - f i g h t = 1,442 ms, t = 1.64, p > .10; m o r e - o d d = 1,567
ms, o d d - m o r e = 1,488 ms, t = 2.30, p > .02; a d d - s u b t r a c t
= 1,516 ms, s u b t r a c t - a d d = 1,477 ms, t = 1.46, p > .15).
The slight a s y m m e t r i e s m a y be attributable to d i f f e r e n c e s in the
baseline and p o s t s w i t c h reaction times in each task. In fact,
w h e n the s w i t c h times were e x p r e s s e d as ratios o f m e d i a n reaction time on the switch trial to m e d i a n reaction time on the
p o s t s w i t c h task, the values were quite similar across t y p e s Of
s w i t c h (i.e., f i g h t - l e f t = 1.57, l e f t - f i g h t = 1.60; m o r e - o d d =
2.24, o d d - m o r e = 2.18; a d d - s u b t r a c t = 1.36, s u b t r a c t - a d d --1.37). All s u b s e q u e n t analyses w e r e therefore b a s e d on the average s w i t c h times across the t w o types o f switches in each task
combination.
It is apparent in Figure 4 that the reaction times, and to a
lesser extent the error percentages, w e r e substantially higher on
trials w h e n a switch was required than o n the three p r e c e d i n g
trials. T h e switch costs in the reaction time m e a s u r e were largest
2 Although it is conceivable that participants could have detected this
regularity in the interval between switches, none of them reported doing
so. Furthermore, the overall pattern of responding was very similar in a
subsequent study in which the switch trials occurred randomly within
a range of 5-15 intervening trials.
450
SALTHOUSE, FRISTOE, McGUTHRY, AND HAMBRICK
Right/Left
More/Odd
Add/Subtract
2,000
1,800
1,600
0
°
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~
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io
800
°
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n-
Switch Position
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8
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Switch Position
10
9
8
7
6
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4
3
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Switch Position
...........................
I
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2,000
1,800
1,600
1,400
1,200
1,000
8O0
6OO
4OO
2OO
10
9
8
7
6
5
4
3
2
1
I
Switch Position
Switch Position
Switch Position
Figure 4. Mean reaction time (top panel) and error percentages (bottom panel) in the three tasks as a
function of the position of the switch signal, Study 1.
in the more-odd task, which may be attributable to the necessity
of changing both the decision rule and the response assignment
in this set of tasks.
Table 1 contains the means, standard deviations, and estimates
of reliability for the switching measures corresponding to the
variables specified in Figure 3. Also present in Table 1 are the
results of statistical significance tests evaluating whether the
mean value was significantly different from zero. With the exception of the baseline measure, all of the measures were created
by subtracting one value from another (e.g., the Switch 0 measure corresponds to the difference between the reaction time or
error percentage on the switch trial and the average of those
values on the three preceding trials). Estimates of reliability for
all measures were computed by boosting the correlation between
the estimates from the first three blocks of trials and the estimates from the second three blocks of trials by the SpearmanBrown formula. Inspection of the table reveals that the reliabilities were quite high for the baseline reaction time measures and
in the moderate range for the Switch 0 reaction time measure.
Reliabilities were generally low for the error percentage
measures.
Analyses were also conducted on the differences in the reaction time switch costs (Switch 0) across the two blocks of trials
in each task combination. Although the absolute magnitude of
the switch cost was smaller in the second block of trials than
in the first block of trials in two of the three tasks, in no case
was the difference statistically significant (i.e., all ts < 1.84,
all ps > .06). The mean differences and the percentages of
participants with a positive difference (indicating smaller switch
costs on the second block) were right-left 32 ms, 59%; moreodd 98 ms, 71%; and add-subtract 0 ms, 57%.
It is noteworthy that the switch costs for the reaction time
measures persist to at least one postswitch trial for each task.
Although the costs on the Switch + 1 trial are much smaller
than those on the switch trial, they were significantly greater
than zero in every task combination. The negative values for the
switch costs on the second and third responses following the
switch in the more-odd task are surprising because they indicate
that these postswitch responses were actually faster than the
preswitch responses. This phenomenon may reflect an initial
period of rapid responding after the shift to a new response
assignment. However, it also may simply represent a chance
anomaly because it was not apparent in the same task in the
subsequent study, or in the other tasks in either study.
The patterns apparent in the means were also reflected in the
percentages of participants with switch costs (in reaction time)
greater than zero. These percentages for the switch trial and the
three following trials were, respectively, 100, 78, 55, and 46 for
the right-left task; 100, 79, 31, and 33 for the more-odd task;
and 100, 64, 55, and 46 for the add-subtract task.
Interrelations of variables. As a means of investigating the
pattern of interrelations among variables, an exploratory factor
analysis (promax rotation) was conducted on the reaction time
measures with the baseline measures from the three switch tasks
TASK SWITCHING
Table 1
Means, Standard Deviations, and Estimated Reliabilities f o r
Switching Measures, Study 1
Reaction time
Switching measure
M
SD
% Error
Rel.
M
SD
1.74~
1.82
2.25 ~
0.60
0.40
0.50
2.03
8.71
5.66
3.51
3.66
3.38
Rel.
Right-left
Baseline
Uncertainty
Switch 0
Switch + 1
Switch + 2
Switch + 3
860~
39a
518 ~
89~
8
-2
93
54
162
99
61
67
.91
.35
.71
.47
.33
.23
.26
0
.18
.21
0
0
614 ~
74 ~
826 ~
93 a
-25 ~
-26 ~
81
71
385
144
84
79
.94
.62
.46
.60
.33
.26
4.87"
0.85
1.33
0.78
0.38
0.13
5.13
8.13
7.09
5.72
6.15
5.51
.95
.20
.61
2.54"
1.08a
2.43 a
0.68
0.02
0.03
2.10
3.24
6.72
4.79
4.54
4.36
.21
.33
.35
.15
.25
.21
Add - subtract
Baseline
Uncertainty
Switch 0
Switch + 1
Switch + 2
Switch + 3
1,043 a
56~
381 a
71"
11
-10
139
69
179
137
91
90
0
0
0
within each task set were positive (i.e., r i g h t - l e f t = .27; m o r e odd = .33; and add-subtract = .07).
There are two major results from this initial study. First,
despite the fact that all of the switching measures were based
on difference scores and hence might be expected t o have low
reliability (e.g., Cohen & Cohen, 1983), the Switch 0 reaction
time measures had respectable reliabilities. Second, the various
measures were correlated in a pattern consistent with the existence of distinct constructs corresponding to speed (i.e., baseline
reaction time) and task switching (i.e., the additional delay in
responding when the decision rule is changed).
Study 2
More-odd
Baseline
Uncertainty
Switch 0
Switch + 1
Switch + 2
Switch + 3
451
.68
0
.25
.04
.45
.36
Note. Estimates of reliability less than zero are replaced by values of
zero. Rel. = estimated reliability.
a Value significantly different from zero at p < .01 by within-subjects t
test.
as potential indicators for the speed construct, the three Switch
0 measures as potential indicators of the switching construct,
and measures of uncertainty and postswitch costs. (The error
measures were not analyzed in this fashion because few of
them were significantly different from zero, and many had low
estimated reliabilities.) The analysis yielded five factors with
eigenvalues greater than 1, and the loadings on the factors and
correlations among factors are reported in Table 2. The first
factor corresponds to baseline reaction time or speed, the second
through the fourth factors primarily seem to reflect uncertainty
and postswitch times for each separate task, and the fifth factor
can be interpreted as representing switching. The discovery that
the three Switch 0 measures formed a factor distinct from those
of the other measures is important because it suggests that a
task-independent construct of switching can be identified.
The first (speed) and fifth (switching) factors were correlated
- . 3 1 with one another, suggesting that faster baseline reaction
time was associated with larger switch costs. However, this correlation is somewhat misleading and may largely represent task
differences. This is because the baseline reaction times were
fastest in the m o r e - o d d tasks and slowest in the add-subtract
tasks, whereas the switch costs were largest in the m o r e - o d d
tasks and smallest in the add-subtract tasks. Indeed, all correlations between the baseline reaction time and the Switch 0 costs
The major focus of the second study was on the roles of task
switching and speed as potential mediators of relations between
age and measures of fluid cognition. As noted earlier, many
studies have been reported in which statistical control of paperand-pencil and reaction time measures of speed reduced or eliminated the relations of age to various measures of higher order
cognitive functioning, including episodic memory, inductive reasoning, and spatial visualization. The primary interest in this
study is whether task switching might be more fundamental than
processing speed in terms of the relations to age and measures
of cognition. If so, strong and independent relations of measures
of switching to age and to cognition would be expected when
measures of speed are controlled.
Three tests of cognitive functioning were administered to
assess fluid or process aspects of cognition. These were a test
of inductive reasoning (matrix reasoning), a test of spatial visualization (cube assembly), and a test of episodic memory (free
recall). Increased age has frequently been associated with lower
levels of performance on tests such as these, and thus they
should provide a reasonable basis for examining the role of the
switching and reaction time measures as potential mediators of
the age-cognition relations.
Finally, the data were also subjected to an analysis designed
to identify variables with unique or independent age-related influences. Baddeley (1996) has recently described why efforts
of this type are desirable:
One problem in attempting to carry out theoretically driven studies
on ageing stems from the fact that almost every physical and cognitive function shows some decline. Consequently, showing that the
elderly perform poorly on any given task cannot be regarded as
evidence for the task's peculiar vulnerability to aging, unless other
factors are ruled out. (p. 19)
Although one could argue that the use of difference scores, that
is, subtracting the reaction time on the three preswitch trials
from the reaction time on the switch trial, provides a relevant
comparison, this procedure merely indicates whether the absolute difference between the two measures varies as a function
of age, and not whether the age-related influence on the derived
measure was independent of, and distinct from, the age-related
influences on other measures (see Salthouse & Coon, 1994).
The following method was therefore used in the current study:
First the variance that all variables had in common was determined, and then the age-related effects on an estimate of those
common aspects was statistically controlled before examining
452
SALTHOUSE, FRISTOE, McGUTHRY, AND HAMBRICK
Table 2
Results of Exploratory Factor Analysis on Switching Variables, Study 1
Factor
Variable
RL-RT
MO-RT
AS - R T
MO-Uncert.
MO-SW + 1
MO-SW + 2
MO-SW + 3
RL-Uncert.
RL-SW + 1
RL-SW + 2
RL-SW + 3
AS-Uncert.
AS-SW + 1
AS-SW + 2
AS-SW + 3
RL-SW0
MO-SW0
AS - S W 0
Speed
More-odd
Right-left
Add-subtract
0.88
0.70
0.91
0.03
0.36
-0.06
-0.04
0.14
0.32
-0.05
-0.24
0.06
0.34
0.23
-0.20
0.45
0.28
0.04
0.04
-0.19
0.09
-0,74
0,45
0,67
0,78
-0.18
0.31
0,03
0,01
-0,11
0.52
0.33
-0.16
0.14
-0.26
-0.10
-0.09
-0.24
-0.14
-0.16
-0.21
0.21
0.06
-0.77
0.45
0.85
0.74
-0.40
-0.13
-0.18
0.13
0.15
-0.14
0.03
0.03
-0.18
-0.02
-0.07
-0.47
-0.27
0.17
-0.25
-0.09
0.09
0.12
-0.72
0.41
0.60
0.66
-0.19
-0.13
0.17
Proportion of variance
Cumulative variance
.182
.182
.154
.336
.128
.464
Switching
0.16
0.46
0.33
0.12
0.01
-0.12
-0.07
-0.09
-0.03
-0.14
0.14
-0.01
0.50
0.18
-0.11
0.67
0.57
0.79
.094
.558
.074
.628
Factor correlations
Speed
More-odd
Right-left
Add-subtract
Switching
--
-.16
--
.16
-.09
--
.13
-.08
-.05
--
-.31
.04
.02
-.12
Note. RL = right/left; RT = the baseline reaction time; MO = more/odd; AS = add/subtract; Uncert. =
the difference between reaction time on the three preswitch trials and the baseline reaction time; SW0
through SW3 = the additional times on the switch and postswitch trials relative to the three preswitch
trials.
the a g e - r e l a t e d e f f e c t s o n i n d i v i d u a l variables. A n a d v a n t a g e o f
this analytical p r o c e d u r e is that it a l l o w s the d e t e r m i n a t i o n o f
t h e e x t e n t to w h i c h the a g e - r e l a t e d i n f l u e n c e s o n the s w i t c h i n g
v a r i a b l e s are s h a r e d w i t h o t h e r variables.
The three switching tasks were administered in the same manner as
in Study 1. The digit digit and digit symbol reaction time tasks were
also administered on computers and were presented in the following
sequence: 18 trials of practice on digit digit, 90 trials on digit digit, 18
trials of practice on digit symbol, two blocks of 90 trials each on digit
Method
Participants. A total of 161 adults between 18 and 80 years of
age contributed complete data, and their descriptive characteristics are
summarized in Table 3. An additional 37 individuals performed some
of the tasks but either did not complete all of them within the 2.5 hour
time limit imposed on the session (n = 17), or apparently did not
understand one or more of the tasks because they had accuracy of less
than 75% on the three trials prior to the switch trial in the switch
condition of at least one of the three tasks (n = 20). The individuals
whose data were not analyzed were somewhat older than those included
in the analyses (i.e., mean age = 52.8 years vs. 44.1 years), but no
other distinguishing characteristics of those dropped from subsequent
analyses were apparent.
Procedure. All participants received the tasks in the following order:
background demographic questionnaire, synonym and antonym vocabulary, pattern comparison, letter comparison, number matching, pattern
matching, free recall, matrix reasoning, cube assembly, digit digit reaction time, digit symbol reaction time, right-left switching, m o r e - o d d
switching, and add-subtract switching.
Table 3
Demographic Characteristics o f Participants in Study 2
Age range (years)
18-39
(n = 66)
40-59
(n = 62)
60-80
(n = 33)
Variable
M
SD
M
SD
M
SD
Age
% Women
Self-rated health
Years of education
Synonym vocabulary
Antonym vocabulary
28.1
54.5
2.0
14.8
5.3
4.6
6.7
48.0
69.3
2.2
15.1
6.0
5.5
5.8
68.8
57.6
2.2
15.0
7.9
6.5
5.1
1.0
2.2
2.7
2.7
0.8
2.1
3.1
3.1
1.0
3.0
2.5
3.3
Note. Self-rated health is on a 5-point scale, ranging from 1 (excellent)
to 5 (poor).
TASK SWITCHING
symbol, followed by a final 90 trials on digit digit. The stimulus displays
in both tasks consisted of a code table at the top of the screen containing
nine pairs of items and a probe pair in the middle Of the screen. The
pairs of items in the digit symbol task consisted of digits and symbols,
and thus the research participant had to refer to the code table to determine whether the items in the digit symbol probe pair were associated
with one another. All items in the digit digit task consisted of digits,
and thus the research participant merely had to decide whether the probe
digits were physically identical. The instructions were that responses
(i.e., slash [/] for same and Z for different) should be made as rapidly
and accurately as possible.
The remaining tasks, which were all developed locally, were administered with paper-and-pencil procedures. The vocabulary tests consisted
of 10 five-alternative multiple-choice questions each for the antonym
and synonym portions. A total of 5 min were allowed to complete both
of these tests. Each of the perceptual speed tests (i.e., pattern comparison, letter comparison, number matching, and pattern matching) involved
an instruction page with several examples and two test pages for which
participants were allowed 30 s each.
Items in the pattern comparison test consisted of 30 pairs of patterns
composed of three to nine line segments, and items in the letter comparison test consisted of 21 pairs of three to nine letters. Approximately one
half of the pairs in each test page were identical, and one half differed
in the identity of a single element. Participants were instructed to write
an S between the pairs that were the same, to write a D between the
pairs that were different, and to do so as rapidly and accurately as
possible.
Items in the number-matching and pattern-matching tests consisted of
a two-digit target number or target pattern on the left and five alternative
numbers or patterns on the right. The task was to circle the alternative
on the right that matched the target on the left and to do so as rapidly
and accurately as possible. There were 30 items in each matching test.
The free-recall test was based on the Rey Auditory Verbal Learning
Test (Schmidt, 1996) and consisted of five study-test trials of a list of
15 words presented in the same order (i.e., drum, curtain, bell, coffee,
school, parent, moon, garden, hat, farmer, nose, turkey, color, house,
river). The words were read by the examiner at a rate of about 1 word
every 2 s, and 45 s was allowed for written recall after each list. Each
recall attempt was written on a separate page in a booklet.
The matrix reasoning test resembles the Raven's Progressive Matrices
Test (Raven, 1962) and was initially developed to be computer administered (i.e., Salthouse, 1993a, 1994). Each item in the test contained a
3 × 3 matrix of geometric patterns with the lower right cell blank.
Immediately below the matrix was a set of eight alternatives representing
possible completions of the matrix. The task for the participant was to
mark the best completion of the matrix from the set of alternatives. The
test began with two practice problems with the answers provided and
then participants were allowed 10 min to complete as many of the 20
problems as possible.
The cube-assembly test was based on a test described by Shepard
and Feng (1972). Items in the test consisted of displays of six connected
squares that were to be assembled to form a cube. One of the squares
was shaded to represent the base of the cube, and two of the squares
contained arrows. The task for the participant was to decide whether
the arrows would point at one another when the cube was assembled
and to indicate the decision by marking Y for yes or N for no. Two
illustrated practice problems preceded the test of 24 items, for which
participants were allowed 10 min.
Results a n d D i s c u s s i o n
Mean reaction times and error percentages for the relevant
measures in the three switching tasks are portrayed in Figure
5. The data are separated into three age groups for purposes of
453
illustration, but most of the analyses were based on treating the
sample as continuous with respect to age. As in Study 1, the
means for the single tasks in each set of tasks were similar and
highly correlated (i.e., right = 1,078 ms, left = 1,061 ms, r =
.95; m o r e - l e s s = 728 ms, o d d - e v e n = 731 ms, r = .83; and
add = 1,200 ms, subtract = 1,361 ms, r = .87), and thus the
two values were averaged to form a single baseline measure.
A s y m m e t r y of switching was examined in the same manner
described in Study 1. The switch times, and ratios of switch
times to times in the new task, were: r i g h t - l e f t = 1,997 ms, r
= 1.70; l e f t - r i g h t = 2,108 ms, r = 1.83; m o r e - o d d = 3,074
ms, r = 3.80; o d d - m o r e = 2,902 ms, r = 3.38; a d d - s u b t r a c t
= 1,982 ms, r = 1.39; and s u b t r a c t - a d d = 1,903 ms, r = 1.47.
As in Study 1, the two switch times within each task set were
generally similar, particularly when expressed relative to the
time in the new task. The averages of the two types of switches
in each task combination were therefore used in all subsequent
analyses.
Again as in Study 1, analyses were conducted on the differences in switch costs across the two blocks of switching trials.
Unlike Study 1, significant reductions in the time costs of
switching were evident from the first to the second block of
trials in each set of tasks. The mean difference (i.e., switch cost
for Block 1 minus switch cost for Block 2) and the percentage
of participants with differences greater than zero were: r i g h t left 112 ms, 68%; m o r e - o d d 444 ms, 76%; and a d d - s u b t r a c t
108 ms, 67%. The discrepancy across studies may be attributable to the greater heterogeneity of the sample, and slower overall responses, in the current study compared to the previous
study. However, none of the correlations between age and the
magnitude of the Block 1 minus Block 2 difference score were
statistically significant (i.e., r i g h t - l e f t , r = .05; m o r e - o d d , r
= . 12; and a d d - subtract, r = . 15).
Inspection of Figure 5 reveals that both reaction time and the
error percentages were greater with increased age and that the
age differences were larger on the switch trials than on the
preswitch or baseline trials. This latter point is evident in the
greater separation of the functions for the three age groups on
the switch trials than on the three trials preceding the switch,
or on the baseline functions. Analyses of variance with age (i.e.,
1 8 - 3 9 , 4 0 - 5 9 , and 6 0 - 8 0 ) and trial type (i.e., Switch 0 trial
vs. either average of the baseline trials or average of the three
preswitch trials) were conducted on both the time and accuracy
measures. The Age × Trial Type interactions were all statistically
significant, as the F ratios for the Age x Trial Type interaction
in the time comparisons all exceeded 15, and o n l y one of the
ratios in the accuracy comparisons was less than 5.3.
Means, standard deviations, reliabilities, significance tests,
and age correlations for the switching measures are presented
in Table 4. Notice that the reliabilities were high for the baseline
reaction times, moderate for the Switch 0 reaction times, and
moderate to low for the postswitch reaction times. The same
overall pattern is evident in the error percentages, albeit with
generally lower absolute values. The patterns of switch time
costs evident in the means were also apparent in terms of the
percentages of participants with switch costs (in reaction time)
greater than zero. For example, the percentages in the r i g h t left task for the 0, + 1, +2, and + 3 responses were, respectively,
100, 91.3, 66.5, and 55.3. Corresponding percentages in the
SALTHOUSE, FRISTOE, McGUTHRY, AND HAMBRICK
454
Right/Left
More/Odd
Add/Subtract
4,000
4,000
o
3,500
E
3,000
¢/3
q)
._E
6O-80
3,500
3,000
60-80
2,500
6O8O
2,500
I-2,000
¢-
2,000
.0_ 1,500
1,500
15
1,000
1,000
5OO
5OO
n-
Switch Position
Switch Position
Switch Position
18
18
2L .
LU
19
O)
¢0
E19
2
15
6O.8O
15
12
12
4O-59
9
9
6
6
O
a.
3
3
g::: .....
I
I
I
I
-3
-2
-1
0
1
Switch Position
2
3
Switch Position
Switch Position
Figure 5. Mean reaction time (top panel) and error percentages (bottom panel) in the three tasks as a
function of the position of the switch signal and age group, Study 2.
m o r e - o d d task were 100, 85.1, 62,7, and 57.8, and those in the
add-subtract task were 100, 77.6, 49.7, and 50.3.
It can also be seen in Table 4 that there were significant
correlations between age and the baseline reaction time measures in each task and between age and the Switch 0 and Switch
+ 1 measures. Increased age was also associated with significantly more errors on the switch trial in the m o r e - o d d tasks.
However, with one exception there were no significant relations
between age and the uncertainty measures, suggesting that adults
of varying ages did not differ in the degree to which overall
performance was affected by the requirement of switching between tasks on some trials in the block. The age relations on
the reaction time measures indicate that with increased age performance was slower in the baseline single task conditions, in
the amount of additional time needed to respond on the trial in
which the switch signal occurs, and on the immediately following trial. The age relations on the error measures may reflect
difficulties in understanding the switch condition when it was
first performed (i.e., the r i g h t - l e f t tasks were the first switching
tasks performed in the session) and in remembering the change
in response type (i.e., from Z and a slash mark [/] to X and a
period [. ]) as well as the change in decision rule in the switch
condition in the m o r e - o d d tasks.
Interrelations o f variables. Table 5 contains the correlation
matrix for all of the primary variables in the study along with
estimates of their respective reliabilities. Performance in the four
perceptual speed tests was evaluated in terms of the number of
correct responses minus the number of incorrect responses, and
the measures in the digit digit and digit symbol reaction time
tasks Were the median reaction times in milliseconds. Scores on
the cognitive tests correspond to the number of correct items in
the matrix reasoning test, the difference between the number of
correct and number of attempted but incorrect responses in the
cube-assembly test, and the average number of words recalled
across the five trials of the free-recall test.
Three points should be noted about the data in Table 5. First,
all of the reliabilities are respectable, indicating that there was
considerable systematic variance in each measure. Second, all
of the measures were significantly correlated with age, and in
every case except the two vocabulary measures, increased age
was associated with poorer performance (i.e., lower scores in
terms of number correct, or higher reaction times). Third, the
highest correlations tended to be among measures of the same
type. The two vocabulary measures were correlated .77, and the
correlations among the three baseline reaction time measures in
the switch tasks ranged between .62 and .72.
A more systematic method of exploring the interrelations
among the measures consisted of performing a confirmatory
factor analysis on all of the variables in Table 5 except age. The
analysis specified five factors, defined according to the loading
pattern in Table 6. This model provided a good fit to the data,
X2(109, N = 161) = 175.17, NNFI = .95, CFI = .96, Std.
R M R = .05, and the loadings on the factors and correlations
among the factors are presented in Table 6. Notice that the
TASK SWITCHING
455
Table 4
Means, Standard Deviations, Estimated Reliabilities, and Age Correlations
for Switching Measures, Study 2
Reaction time
Switching
measure
M
SD
% Error
Rel.
Age corr.
M
SD
1.57"
1.03"
8.27"
3.71"
2.34"
1.00
2.93
4.21
13.65
10.99
6.49
5.39
.52
.26
.76
.73
.55
.54
.13
.30*
.17
.10
.04
.04
3.95"
0.54
6.50"
2.53"
1.59"
1.04
6.64
6.64
11.46
7.18
6.67
6.30
.68
.37
.62
.28
.41
.18
.03
-.06
.25*
.11
.10
.11
1.94 i
0.57"
4.10"
0.75
0.59
0.31
2.02
2.72
8.91
4.40
4.41
4.13
.68
.23
.59
-.01
.02
.19
.12
.08
.00
Rel.
Age corr.
Right-left
Baseline
Uncertainty
Switch 0
Switch + 1
Switch + 2
Switch + 3
1,069"
73"
898"
243 a
66"
28
182
85
485
301
170
138
.96
.37
.71
.51
.51
.43
.64*
.18
.38*
.26*
.23*
.05
More-odd
Baseline
Uncertainty
Switch 0
Switch + 1
Switch + 2
Switch + 3
730 ~
85"
2,197"
214"
88"
32"
128
106
1,788
321
270
121
.86
.51
.89
.31
.54
.21
.50*
.06
.38*
.20*
.15
.21"
Add-subtract
Baseline
Uncertainty
Switch 0
Switch + 1
Switch + 2
Switch + 3
1,281"
64"
587"
135'
11
-1
259
78
319
211
121
106
.97
.13
.78
.64
.32
0
.36*
-.04
.41"
.29*
.04
.01
0
.17
0
Note. Estimates of reliability less than zero are replaced by values of zero.
"Value significantly different from zero at p < .01 by within-subjects t test.
*p <
.01.
reaction time and perceptual speed constructs were very highly
correlated with one another (i.e., - . 9 3 ) and that both were
highly related to the cognition construct (i.e., - . 8 5 and .88).
Perhaps the most interesting results from this table are that there
is again evidence, as in Study 1, for the existence of a distinct
switching construct, and all of the speed measures are highly
correlated with one another and with the latent cognition
construct)
t
'
Mediational models. The next set of analyses e x a m i n e d tffo
different structural models in which the reaction time speed and
task-switching constructs functioned as possible mediators of
the relation between age and the construct representing fluid or
process aspects of cognition. Only the baseline reaction time
measures from the switch tasks were included in these analyses
to provide the purest comparison of the effects of reaction time
speed and task switching. The initial model, portrayed in the
top panel of Figure 6, assumed that switching was more fundamental than speed, and thus the switching construct was postulated to mediate at least some of the relations between age
and speed. The direct relation from age to cognition was not
significant in any o f the analyses to be considered. All o f the
postulated relations in this model were significantly different
from zero, and the model provided a good fit to the data; X2(31,
N = 161) = 54.14, N N F I = .95, CFI = .97, Std. R M R = .04.
However, a more parsimonious model, in the sense that there
were fewer significant relations, resulted when the direction of
the relation between the switching and speed constructs was
reversed. This model, which is portrayed in the bottom panel
of Figure 6, also provided a good fit to the data; X2(33, N =
161 ) = 60.14, NNFI = .95, CFI = .96, Std. R M R = .05. Notice
that when task switching is assumed to be another manifestation
of speed, by virtue of the relation from the speed construct to
the switching construct, the switching construct is no longer
significantly related either to age or to a latent construct representing several measures of cognition. Moreover, even when
switching is assumed to be more fundamental than speed by
postulating a relation from the switching construct to the speed
construct (as in the top panel of Figure 6 ) , there are still significant relations of age to speed, and the relations to the cognition
construct are considerably stronger for the speed construct than
for the switching construct.
Single common factor analysis. The final analysis consisted
of a structural equation model in which each variable was re-
3 The correlation of .78 between the reaction time speed and switch
factors in this analysis is considerably higher than, and in the opposite
direction of, the correlation of -.31 in Study 1. In fact, when the same
type of exploratory factor analysis on only the time measures from the
switch tasks was performed on the data from this study, the baseline
reaction time and Switch 0 measures loaded on the same factor. This
pattern suggests that the reaction time speed and switch constructs may
tend to converge in a sample with a wide range of ages.
SALTHOUSE, FRISTOE, McGUTHRY, AND HAMBRICK
456
I1./
.= .=
~ .=
.~
=
-~°
~
III
. p.~
J:=
C~
0
~
~.~
~'~
.
~
.
~
.
~:
~ - ~~ ~
•~
=~
I'N
.
~
~
~
~
~
0
" ~
~,,~.
Illl
o~.
III
~Zi~
i~
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o.~
TASK SWITCHING
Table 6
Results of Confirmatory Factor Analysis, Study 2
Factor
Variable
Vocab
Syn. voc.
Ant. voc.
Pat. com.
Let. com.
Pat. mat.
Num. mat.
DDRT
DSRT
RL-RT
MO-RT
AS-RT
RL-SW
MO-SW
AS-SW
Matrix reasoning
Cube assembly
Free recall
.87
.91
PPSpd
RTSpd
Switch
Cognition
.72
.75
.84
.66
.72
.84
.86
.81
.79
.67
.72
.69
.78
.44
.75
Correlations
Vocab
PPSpd
RTSpd
Switch
Cognition
--
.11
--
-.08
-.93
--
-.07
-.69
.78
--
.32
.88
-.85
-.74
Note. Vocab = vocabulary; PPSpd = perpetual speed; RTSpd = reaction time speed; Syn. voc. = synonym vocabulary; Ant. voc. = antonym
vocabulary; Pat. com. = pattern comparison; Let. com. = letter comparison; Pat. mat. = pattern matching; Num. mat. = number matching;
DDRT = median digit digit reaction time; DSRT = median digit symbol
reaction time; RL-RT, MO-RT, and AS-K'r = the baseline reaction
times in the right-left, more-odd, and add-subtract tasks; RL-SW,
MO-SW, and A S - S W = the switch costs on the switch trial in the
right-left, more-odd, and add-subtract tasks.
lated to a single corrlmon factor that was related to age, and then
it was determined if there were any significant direct relations of
age to individual variables. The initial step in this procedure
consisted of freely estimating the coefficients for the variablecommon and a g e - c o m m o n relations. These parameters were
then fixed to the estimated values and the relations between age
and each individual variable examined. If the coefficient for
the age-variable relation differed from zero by more than two
standard errors, it was retained in the model and otherwise was
dropped. The model resulting from these steps is illustrated in
Figure 7.
Because the focus in this type of analysis is on the shared
and unique relations of age to the variables, and not on the
relations among all variables, the fit of the model to the complete
data is only of secondary interest. Nevertheless, the fit of the
model portrayed in Figure 7 was respectable; X2( 117, N = 161 )
= 234.30, NNFI = .92, CFI = .92, Std. R M R = .06. Three
points should be noted about this figure. First, all of the variables
had moderate to strong loadings on the common factor, indicating that they shared considerable variance with one another.
Second, there was a strong negative relation between age and
the common factor, indicating that increased age was associated
457
with lower levels of what the variables had in common. Third,
there were independent and distinct age-related influences only
on the baseline reaction time measures in the r i g h t - l e f t and
add-subtract tasks. The former relation, which was positive in
direction, may reflect the additional difficulty associated with
initially performing the tasks because the r i g h t - l e f t task was
the first of these types of tasks performed during the session.
The negative coefficient for the add-subtract baseline reaction
time indicates that the age-related influences on that measure
were overestimated from the effects through the common factor
(i.e., the product of the coefficients for the relevant paths, - . 6 5
and - . 8 3 , is .54, and the age correlation was .36). The fact that
the age relations were smaller than expected on the basis of
influences via the common factor on this measure may be another manifestation of the finding that age-related differences
are often relatively small in measures of simple arithmetic (e.g.,
Geary, Salthouse, Chen, & Fan, 1996).
General Discussion
Before discussing the results it is useful to briefly summarize
five important characteristics of the three sets of tasks used in
these studies. First, each member of the pair of tasks had similar
baseline reaction times when performed alone, suggesting that
they were roughly comparable in terms of difficulty or familiarity. Second, in both tasks of the pair the same stimuli were used
with different decision rules, such that the cueing of stimuli to
responses was ambiguous. Third, each task within the pair had
the same number of possible responses, with a total of nine in
the r i g h t - l e f t and add-subtract tasks and two in the m o r e - o d d
tasks. Fourth, switch and nonswitch trials were mixed together
within the same trial blocks and thus were unlikely to differ
with respect to general factors such as motivation, anxiety, and
so forth. And fifth, the three pairs of tasks were structurally
equivalent such that similar measures of switching performance
could be derived from each combination of tasks.
A clear finding in both studies was that, with only one exception, there were significant costs of switching from one task to
another in both the time and error measures. Furthermore, these
switch costs exhibited reliable individual differences, and the
measures from different combinations of tasks were positively
correlated with one another, indicating that people systematically differ in the extent to which their performance is disrupted
by the requirement to switch from one task to another. The
discovery that there were significant correlations among the
switch costs in the three sets of tasks suggests that similar
processes were involved despite variations in the types of tasks
and relations between them. The switch costs were operationally
defined as the additional time and errors on trials when the
decision rule has to be changed relative to the averages across
the three preceding trials. They can therefore be interpreted as
representing the difficulty, in either time or errors, of retrieving
and implementing a different set of decision rules and/or mapping of stimuli to responses.
Two additional findings in both studies provide further information about the nature of the switch costs. The first is that the
switch costs were greater when both the decision rule and the
response mapping changed (i.e., the m o r e - o d d tasks) than when
only the decision rule changed (i.e., the r i g h t - l e f t and a d d -
458
SALTHOUSE, FRISTOE, McGUTI-IRY, AND HAMBRICK
Speed
.34 /
~
\
/
~
-.~
.54
.57 ~ . ,
/
\
J
-.a0
Switch
Figure 6. Two structural models with speed and switch constructs, Study 2. The top panel portrays the
coefficients when there is a path from the switch construct to the speed construct, and the bottom panel
portrays the coefficients when the direction of this path is reversed. The speed construct is assessed with
reaction time measures scaled in units of time per response and thus the relation from age is positive rather
than negative as in Figure 1. RL-RT = baseline reaction time in the right-left task; MO-RT = baseline
reaction time in the more-odd task; AS-RT = baseline reaction time in the add-subtract task; RL-SW,
MO-SW, and A S - S W = Switch 0 time costs in the right-left, more-odd,and add-subtract tasks; Cube
Assm. = cube-assembly score; Mat. Reas. = matrix reasoning score; Free Recall = average number of
words recalled across five lists.
subtract tasks). This result makes sense if it is assumed that the
switch costs are proportional to the magnitude of the required
changes in the shift from one task to another. A second relevant
finding is that the switch costs persisted for one to three responses after the presentation of the switch signal. This result
is inconsistent with results reported by Rogers and Monsell
( 1995, Experiment 6 ) , in which the switch costs were found to
be confined to the trial in which the switch was to occur. A
variety of procedural differences, such as the use of sequences
with alternations on every fourth trial and potentially low power
due to a sample of only eight individuals in the Rogers and
Monsell experiment, may have been responsible for this discrepancy. Regardless of the reasons for the different results, however,
the data from the current studies indicate that at least some of
TASK SWITCHING
459
-.65
.08
.68
.75
.80
.65
.69
.69
.39
-.70
-.83
Figure 7. Structural model with a single common factor contributing to the age-related influences on all
variables, Study 2. The variables in the analysis were pattern comparison (PatCom), letter comparison
(LetCom), pattern matching (PatMat), number matching (NumMat), median digit digit reaction time
(DDRT), median digit symbol reaction time (DSRT), baseline reaction time in the right-left task (RLRT), baseline reaction time in the more-odd task (MO-RT), baseline reaction time in the add-subtract
task (AS-RT), Switch 0 time costs in those same three tasks (i.e., RL-SW, MO-SW, and AS-SW),
matrix reasoning score (Mat. Reas.), cube-assembly score (CubeAssm), and average number of words
recalled across five lists (Recall).
the effects associated with changing from one task to another
persist for several subsequent responses, as though there is some
residual hesitancy in implementing the decision rules corresponding to the new task.
The results just described indicate that the phenomenon of
costs of task switching is not specific to a single set of tasks and
that there are reliable individual differences in a task-switching
construct. The next question of interest concerned the relations
of this switching construct to other variables. In particular, what
are the relations of switching to age and to fluid or process
aspects of cognition, and are those relations independent of
other constructs, such as processing speed? The issue of the
independence of age-related influences is particularly important
because a very large number of cognitive variables have been
reported to be significantly related to age, and they are not all
necessarily independent of one another. When researchers focus
on a single variable there is a tendency to emphasize taskspecific interpretations of the age-related differences on that
variable, but the validity of these types of interpretations can
be examined only in the context of a broader range of variables.
Even when it has been established that there are coherent
individual differences on the relevant measures, such that a construct can be identified that is distinct from other potentially
related constructs, it could still be the case that most of the
relations of that construct to other constructs are shared and are
not distinct. As a somewhat fanciful example, a researcher might
find distinct constructs corresponding to arm strength and to leg
strength based on results that correlations among measures of
arm strength and leg strength were higher among themselves
than with measures of the other limb. This pattern would be
consistent with the existence of distinct arm strength and leg
strength constructs, but there could still be almost complete
overlap of the two constructs in terms of their relations to other
variables, such as age and cognitive performance. Multivariate
analytical methods are therefore needed to determine if, and
to what extent, a given variable or construct has unique (i.e.,
independent) relations to other variables.
One type of multivariate method involves examining the fit
of mediational models in which different relations among the
variables are postulated. The models in Figures 1 and 6 are
examples of this analytical technique. Although the structural
relations in these models must be interpreted cautiously because
they are based on data from a single point in time, they are
nonetheless informative because the patterns of relations could
be inconsistent with postulated relationships. Moreover, by comparing alternative models differing in the relations between particular constructs it is possible to draw inferences about which
constructs are more encompassing or comprehensive with respect to the relations they have with other variables. It is in this
latter respect that the contrast between the switch and speed
constructs is relevant. Specifically, the discovery that there were
fewer, but larger, direct relations among variables when increased age was postulated to affect speed, which in turn affects
switching, compared to when increased age was postulated to
affect switching, which then contributed to speed, suggests that,
at least with respect to relations with age and with higher order
cognition, the speed construct may be more fundamental than
the switching construct.
460
SALTHOUSE, FRISTOE, McGUTHRY, AND HAMBRICK
The second type of multivariate analytical procedure used in
these studies is the single common factor technique in which
the age-related influences on what all the variables have in
common are statistically controlled before examining the relations of age to individual variables. The results of this procedure
are portrayed in Figure 7. Several points should be noted about
this figure. The first is that all variables had moderate to high
loadings on the factor representing what is shared among the
variables, with the highest loadings for the reaction time variables and the lowest loading for the cube-assembly score. Because many of the variables appear to have little resemblance
to one another (e.g., reaction time to respond with the digit on
the left or right of the display and the number of unrelated
words recalled after an auditory presentation), the discovery
that they all shared moderate amounts of variance with one
another may be considered somewhat surprising. A second important point about the model portrayed in Figure 7 is that there
was a strong negative age-related influence on the common
factor, but independent age-related influences were evident on
only two variables. The negative age-common relation indicates
that increased age was associated with lower levels of whatever
all variables had in common, and the small number of independent or direct relations from age to individual variables suggests
that for most of the variables almost all of the age-related influences were shared with other variables. Inspection of Figure 7
reveals that this was also true for the three switch measures,
which implies that there is apparently nothing special about
these variables in terms of their age-related influences.
The two variables with independent or unique age-related
influences in this analysis were the baseline reaction times in
the right-left and add-subtract tasks. As noted earlier, the underestimation of the age relation for the R L - R T variable may
be attributable to somewhat slower learning on the part of older
adults because this was the first task of this type performed in
the session, and the overestimation of the age relation for the
A S - R T variable may be a reflection of the relative preservation
of simple arithmetic skills on the part of older adults.
Different perspectives could obviously be adopted with respect to a construct like task switching. For example, one perspective could focus on trying to understand the processes involved in the costs of switching between tasks and determining
the relative contribution of each under different conditions. The
studies by Allport et al. (1994), Rogers and Monsell (1995),
and Rubenstein et al. (in press) are examples of this approach.
However, an alternative perspective is concerned with understanding the nature of individual differences in task switching
and the relations of switching measures to other types of variables. The current studies are obviously closer to this second
perspective than to the first. Nevertheless, the results of the
second study have an interesting implication with respect to
components of switching. Assume that task switching consists
of several different components or processes, such as reallocation of the focus of attention, change in mental set, reinstatement
of a different mapping of decisions to responses, proactive interference, etc. Now consider the results of Study 2 that the aggregate switch measures had little or no relation to age or to meat
sures of higher order cognition when the measures of baseline
reaction time, postulated to reflect a construct Of processing
speed, were statistically controlled. This pattern of results sug-
gests that any component measures of switching are also unlikely to have independent relations with age or measures of
cognitive functioning because the more global and inclusive
measures do not have independent relations. Of course it is
possible that complicated trade-offs could occur such that there
were positive relations with one component and negative relations with another component that precisely canceled one another to produce no overall relation in the aggregate variable,
but additional evidence is probably needed before this possibility could be considered plausible.
It is instructive to compare our results with those of three
studies recently reported by Kramer et al. (in press) because in
both cases adults of different ages were compared in measures
of task switching. In the Kramer et al. (in press) studies only
a single set of tasks was used, and the participants had an
opportunity to prepare for the switch in advance of its occurrence either because a signal was presented prior to the switch
(Studies 1 and 2) or because the participants were informed
that the switch occurred on every fifth trial. However, as in the
current studies, the switching measures were found to have
reliable individual variance independent of the other reaction
time measures, suggesting that they represented a distinct construct. Furthermore, there were substantial age differences in the
switch measures when the opportunities for advance preparation
were limited by short intervals between trials. Kramer et al.
reported significant reductions in the absolute magnitude of the
switch costs with practice, but the amount of independent agerelated variance in the switch measures increased with practice
in each study and thus it is not clear how the practice effects
in those studies should be interpreted.
To summarize, the results of these studies indicate that people
differ in the ease with which they can shift from one task to
another, in addition to the efficiency with which they can perform each individual task. Task switching is therefore a meaningful theoretical construct and is not restricted to a particular
set of tasks. Measures of task switching were found to be significantly related to adult age (i.e., older adults had more difficulty switching) and to measures of cognitive functioning (i.e.,
faster switchers had higher levels of cognitive performance).
However, those relations were not independent of other constructs. In particular, if measures of baseline reaction time were
statistically controlled, there were no longer any significant relations of switching either to age or to measures of higher order
cognition. The implication is that although task switching can
be identified as a distinct construct, most of the relations it has
with other variables are shared and are not unique to switching.
References
Allport, A., Styles, E. A., & Hsieh, S. (1994). Shifting intentional set:
Exploring the dynamic control of tasks. In C. Umilta & M. Moscovitch
(Eds.), Attention and performance XV (pp. 421-452). Cambridge,
MA: MIT Press.
Baddeley, A. (1996). Exploring the central executive. Quarterly Journal
of Experimental Psychology, 49A, 5-28.
Barrett, G. B., Mihal, W. L., Panek, P.E., Sterns, H. L., & Alexander,
R.A. (1977). Information processing skills predictive of accident
involvementfor younger and older commercial drivers. Industrial Gerontology, 4, 173-182.
Botwinick, J., Brinley J. E, & Robbin, J. S. (1958). Task alternation
TASK SWITCHING
time in relation to problem difficulty and age. Journal of Gerontology,
13, 414-417.
Braune, R., & Wickens, C. D. (1985). The functional age profile: An
objective decision criterion for the assessment of pilot performance
capacities and capabilities. Human Factors, 27, 549-554.
Brinley, J. E ( 1965 ). Cognitive sets, speed and accuracy of performance
in the elderly. In A. T. Welford & J. E. Birren (Eds.), Behavior, aging,
and the nervous system (pp. 114-149). Springfield, IL: Charles C
Thomas.
Cohen, J., & Cohen, P. ( 1983 ). Applied multiple regression~correlation
analysis for the behavioral sciences ( 2nd ed.). Hillsdale, N J: Edbaum.
Duncan, J., Emslie, H., Williams, P., Johnson, R., & Freer, C. (1996).
Intelligence and the frontal lobe: The organization of goal-directed
behavior. Cognitive Psychology, 30, 257-303.
Garner, W.R., Hake, H.W., & Erikson, C. W. (1956). Operationism
and the concept of perception. Psychological Review, 63, 149-159.
Geary, D. C., Salthouse, T. A., Chen, G. P., & Fan, L. (1996). Are East
Asian versus American differences in arithmetical ability a recent
phenomenon? Developmental Psychology, 32, 254-262.
Kramer, A. E, Hahn, S., & Gopher, D. (in press). Task coordination and
aging: Explorations of executive control processes in the task switching paradigm. Acta Psychologica.
Raven, J. (1962). Advanced Progressive Matrices, Set I1. London: H. K.
Lewis.
Reitan, R.M. (1992). Trail Making Test: Manual for administration
and scoring. Tucson, AZ: Reitan Neuropsychology Laboratory.
Rogers, R.D., & Monsell, S. (1995). Costs of a predictable switch
between simple cognitive tasks. Journal of Experimental Psychology:
General, 124, 207-231.
Rubenstein, J., Meyer, D. E., & Evans, J. E. (in press). Executive control
of cognitive processes in task switching. Journal of Experimental
Psychology: Human Perception and Performance.
Salthouse, T. A. (1993a). Influence of working memory on adult age
461
differences in matrix reasoning. British Journal of Psychology, 84,
171-199.
Salthouse, T. A. (1993b). Speed mediation of adult age differences in
cognition. Developmental Psychology, 29, 722-738.
Salthouse, T. A. (1994). The nature of the influence of speed on adult
age differences in cognition. Developmental Psychology, 30, 240259.
Salthouse, T. A. (1996). The processing speed theory of adult age differences in cognition. Psychological Review, 103, 403-428.
Salthouse, T.A., & Coon, V.E. (1994). Interpretation of differential
deficits: The case of aging and mental arithmetic. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 11721182.
Salthouse, T. A., & Fristoe, N. M. (1995). Process analysis of adult age
effects on a computer-administered trail making test. Neuropsychology, 9, 518-528.
Salthouse, T. A., Fristoe, N., & Rbee, S. H. (1996). How localized are
age-related effects on neuropsychological measures? Neuropsychology, 10, 272-285.
Schaie, K.W. (1958). Rigidity-flexibility and intelligence: A crosssectional study of the adult life span from 20 to 70. Psychological
Monographs, 72(Whole No. 9).
Schmidt, M. (1996). Rey Auditory Verbal Learning Test: A Handbook.
Los Angeles: Western Psychological Services.
Shepard, R. N., & Feng, C. (1972). A chronometric study of mental
paper folding. Cognitive Psychology, 3, 228-243.
Stankov, L. (1988). Aging, attention, and intelligence. Psychology and
Aging, 3, 59-74.
Wickens, C. D., Braune, R., & Stokes, A. (1987). Age differences in
the speed and capacity of information processing: 1. A dual-task
approach. Psychology and Aging, 2, 70-78.
Received N o v e m b e r 24, 1997
Revision received February 17, 1998
Accepted February 25, 1998 •