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Mood-Induced Shifts in Attentional Bias to Emotional Information Predict Ill- and Well-Being

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Previous research has suggested that biased attention toward emotional (typically threatening) stimuli contributes to ill-being (e.g., high levels of anxiety), but its contribution to well-being is less clear. The researchers assessed naturalistic shifts in attentional bias toward threatening and pleasant schematic face cues in response to five induced mood states in college students. They also assessed state anxiety and satisfaction with life concurrently and 3 weeks later. Controlling for concurrent anxiety, a fear-induced shift in attention to threatening cues was associated with increased levels of later anxiety. Controlling for concurrent life satisfaction, a happiness-induced shift in attention to emotional cues (both threatening and pleasant) was associated with increased levels of later life satisfaction. These results suggest that mood-induced changes in deployment of attention to emotional information may accumulate in ways that impact psychological functioning, yet these effects depend on mood state and the emotional cues afforded by the context.
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Mood-Induced Shifts in Attentional Bias to Emotional Information
Predict Ill- and Well-Being
Sarah R. Cavanagh
Assumption College and Tufts University Heather L. Urry
Tufts University
Lisa M. Shin
Tufts University and Massachusetts General Hospital
Previous research has suggested that biased attention toward emotional (typically threatening) stimuli
contributes to ill-being (e.g., high levels of anxiety), but its contribution to well-being is less clear. The
researchers assessed naturalistic shifts in attentional bias toward threatening and pleasant schematic face
cues in response to five induced mood states in college students. They also assessed state anxiety and
satisfaction with life concurrently and 3 weeks later. Controlling for concurrent anxiety, a fear-induced
shift in attention to threatening cues was associated with increased levels of later anxiety. Controlling for
concurrent life satisfaction, a happiness-induced shift in attention to emotional cues (both threatening and
pleasant) was associated with increased levels of later life satisfaction. These results suggest that
mood-induced changes in deployment of attention to emotional information may accumulate in ways that
impact psychological functioning, yet these effects depend on mood state and the emotional cues afforded
by the context.
Keywords: attentional bias, emotion induction
Emotions may have evolved as predispositions to action, and as
such, the evocation of emotion results in a cascade of experiential,
expressive, physiological, neurobiological, and cognitive changes
(Bradley & Lang, 2000). One such cognitive effect is a focusing of
attention on emotionally salient information in the environment,
which may be adaptive in identifying threats or potential resources
(Öhman & Mineka, 2001). However, an exaggeration of this
preference for emotional stimuli in attention is implicated in ele-
vated anxiety.
Indeed, over the last several decades, an impressive body of
research has demonstrated that people with high levels of trait
anxiety, including patients with anxiety disorders, exhibit biased
attention toward disorder-relevant, emotional, or threatening infor-
mation (Mathews & MacLeod, 1994; Mogg & Bradley, 1998;
Yiend, 2010). For instance, Rutherford, MacLeod, and Campbell
(2004) found that compared to people low in trait anxiety, people
high in trait anxiety exhibit increased attentional bias toward threat
after a period of elevated state anxiety (examination period in
college). This result suggests that increases in state anxiety may
cause an increased attentional bias to threat in vulnerable (i.e., high
trait anxious) individuals. However, as is true of many studies in
this literature, the results of Rutherford et al. were essentially
correlational. The opposite causal direction is also plausible.
Namely, increased attentional bias toward threat in response to an
emotional challenge could cause elevations in state anxiety.
Consistent with this possibility, research has demonstrated that
attentional biases to emotional information may play a causal role
in the experience of anxiety. In a seminal study by MacLeod,
Rutherford, Campbell, Ebsworthy, and Holker (2002), for exam-
ple, participants trained to attend to threat experienced elevated
anxiety in response to a laboratory stressor. Inspired by this work,
other studies have shown that training anxious people to avoid
threat on attentional bias tasks results in symptom reduction over
time (e.g., Schmidt, Richey, Buckner, & Timpano, 2009; See,
MacLeod, & Bridle, 2009). Of interest, individuals appear to differ
in the ease with which they acquire attentional bias in these
training programs. For instance, Clarke, MacLeod, and Shirazee
(2008) found that ease of acquiring a threat bias in an attentional
training paradigm predicted shifts in trait anxiety over the first
semester of university study. This research design, while intrigu-
ing, leaves open the question of whether individual differences in
a more reflexive or naturalistic adoption of attention bias (i.e., not
in the context of a laboratory-controlled training program) can
similarly predict psychological functioning.
In addition, because they focused on trait anxiety, Clarke,
MacLeod, and Shirazee’s (2008) intriguing results leave open the
question of whether shifts in one’s natural level of attentional bias
predict changes in state anxiety. State anxiety, by definition, is a
construct that changes over time and varies according to situational
factors. As such, it exhibits less stability over time than measures
of trait anxiety (Usala & Hertzog, 1991). Importantly, such asso-
ciations between concurrent level of attentional bias and later
changes in state anxiety might critically depend on concurrent
Sarah R. Cavanagh, Department of Psychology, Assumption College,
and Department of Psychology, Tufts University; Heather L. Urry, Depart-
ment of Psychology, Tufts University; Lisa M. Shin, Department of Psy-
chology, Tufts University, and Department of Psychiatry, Massachusetts
General Hospital, and Harvard Medical School.
Correspondence concerning this article should be addressed to Sarah R.
Cavanagh, Department of Psychology, Assumption College, 500 Salisbury
Street, Worcester, MA 01609. E-mail: sarah.cavanagh@alum.bu.edu
Emotion © 2011 American Psychological Association
2011, Vol. 11, No. 2, 241–248 1528-3542/11/$12.00 DOI: 10.1037/a0022572
241
mood state. For example, someone who readily adopts an atten-
tional bias toward threat when induced to feel fear in the laboratory
setting may be someone who routinely does so in response to fear-
or anxiety-provoking situations in their daily lives, and this may
encourage increases in state anxiety over time. This possibility has
not previously been investigated.
Finally, whereas some researchers have included positive stim-
uli in their paradigms in order to explore attentional bias toward
emotion (“emotional selectivity”) versus threat (“negative selec-
tivity;” e.g., Rutherford et al., 2004), the bulk of the work on
attentional bias to emotional information has clearly focused on
attentional bias to threat. Moreover, the majority of existing work
has focused on relations between attentional bias to threat and
indices of ill-being (e.g., anxiety). Might people also demonstrate
attentional biases to positive emotional information? Tamir and
Robinson (2007) found that induction of positive moods re-
sulted in attentional bias toward rewarding words, and Wadlinger
and Isaacowitz (2006) demonstrated that inducing a positive mood
increased attention to peripheral positive and neutral images. In
addition, using the logic adopted above for attentional bias to
threat and increases in later state anxiety, might someone who
readily adopts an attentional bias toward positive cues when in-
duced to feel happiness in the laboratory setting be someone who
routinely does so in response to happiness-provoking situations in
their daily lives? If so, might this encourage increases in well-
being (e.g., life satisfaction) over time? To our knowledge, no
studies have addressed this important question.
The aim of the current study was to assess the degree to which
mood-induced attentional shifts (MIASs) toward both threatening
and/or pleasant cues would be associated with changes in state
anxiety and life satisfaction over time in college students. We
assessed attentional bias toward threatening and pleasant sche-
matic faces using a spatial cueing task before and after induction
of two positive (Happy, Mirth), two negative (Sad, Fear), or a
neutral mood state. We included two different positive and two
different negative inductions in order to determine whether atten-
tional bias depends on the nature of one’s mood state (or if,
instead, findings would fall out as a function of positive or nega-
tive valence). To assess variation in psychological functioning, we
measured self-reported levels of state anxiety and well-being con-
currently (along with attentional bias) and again 3 weeks later. We
chose 3 weeks as a time period during which we could reasonably
expect that participants would have experienced a sufficient num-
ber of mood-eliciting events that might prompt MIASs and, there-
fore, small changes in levels of state anxiety and/or well-being.
In light of the extensive literature documenting mood-congruent
effects on cognitive processing (e.g., Bower, 1981; Gilboa-
Schechtman, Revelle, & Gotlib, 2000) and the previously reviewed
literature on the association between attentional bias to threat and
anxiety, we expected that MIAS toward threat would predict
changes in state anxiety over the follow-up period. We thought this
might emerge only in the negative mood conditions and would be
strongest after fearful mood induction. Similarly, we expected that
MIAS toward pleasant faces would predict changes in future
satisfaction with life. We thought this might be strongest after
happy and mirth mood inductions. Importantly, in these analyses,
we controlled for current state anxiety and well-being so as to be
sure we were assessing individual differences in change in these
variables over time. Whereas our primary focus was on predicting
changes over time, we also examined whether MIAS to threatening
and/or pleasant cues would predict concurrent and future levels of
psychological functioning.
Method
Participants
One hundred forty-seven students at Tufts University partici-
pated in this study (95 female; 100 Caucasian). The second-largest
ethnic groups self-identified as Asian American/Pacific Islander
(18 participants) and Hispanic/Latino American (11 participants).
Participants were randomized to one of five mood conditions,
described below. The mean number of days between the initial
visit (Time 1) and the 3-week follow-up visit (Time 2) was 23.19
(SD 5.55); our retention rate was 84.4%. Participants returning
for follow-up did not differ from the rest of the sample on age,
anxiety, satisfaction with life, or any of our measures of attentional
bias.
Materials and Procedures
Mood induction using film clips. At Time 1, all participants
viewed a 5.44-minute neutral aquatic clip at the beginning of the
experiment as a baseline. In a between-participants manipulation,
they were then randomized to one of five mood-induction clips
(Happy: Dirty Dancing,n29; Mirth: Saturday Night Live clips;
n31; Neutral: Gosford Park,n30; Fear: The Shining,n26;
Sad: Stepmom,n31). Film clips ranged in duration from
approximately 5–6 min; they were validated as effective in elic-
iting the target mood in a pilot study.
Spatial cueing task. At Time 1, participants completed a
spatial cueing task (Posner, Walker, Friedrich, & Rafal, 1984)
twice, once before, and once after mood induction. This task
assessed attentional biases by comparing trials in which a threat-
ening, pleasant, or neutral schematic face cue (from Öhman, Lund-
qvist, & Esteves, 2001) accurately predicted a target (valid trials)
to those in which the cue did not accurately predict the target
(invalid trials). As shown in Figure 1, using a valid trial as an
example, participants saw two empty rectangles with a fixation
cross between them. They were instructed to press the space bar
whenever the target, a small black box, appeared in the lower half
of one of the boxes. Face cues were presented in the upper half of
one of the boxes on each trial.
Each iteration of the spatial cueing task consisted of 120 trials
(40 threatening, 40 pleasant, and 40 neutral). The cue was pre-
sented on the right for 50% of the trials. It was presented on the left
for the remaining 50% of trials. The schematic face accurately
predicted the location of the target (valid trials) on 75% of the
trials. The schematic face did not accurately predict the location of
the target (invalid trials) on the remaining 25% of trials. Partici-
pants are generally faster on valid than invalid trials due to an
engagement of attention on valid trials (leading to faster responses)
and costs associated with having to disengage attention and shift it
to the target on invalid trials (leading to slower responses).
To reduce our familywise error rate, we computed composite
attentional bias scores (as in Mogg, Holmes, Garner, & Bradley,
2008). Importantly, these composite scores incorporated bias in
both engagement and disengagement of attention, because two
242 CAVANAGH, URRY, AND SHIN
recent reviews concluded that attentional biases may be observed
in both types of attention (Cisler, Bacon, & Williams, 2009; Yiend,
2010). We calculated one attentional bias score for each mood
condition for threatening versus neutral and one for pleasant versus
neutral cues, before (pre) and after (post) the mood-induction clip.
With threat as an example, these were computed as follows: (RT
invalid threat – RT valid threat) – (RT invalid neutral – RT valid
neutral). In this example, the composite score represents the extent
to which participants oriented their attention toward (RT valid
neutral cue RT valid emotional cue) and had difficulty disen-
gaging from (RT invalid emotional cue RT invalid neutral cue)
threatening versus neutral stimuli. To evaluate shifts in attentional
bias from pre- to postmood induction, we then calculated change
scores for shifts in attentional bias (⌬⫽post – pre), yielding a total
of 10 composite MIAS scores.
Mood reactivity. At Time 1, participants completed a short-
ened version of the Profile of Mood States scale (POMS-SF;
McNair, Lorr, & Droppleman, 1992) before and after the baseline
aquatic clip and again before and after the mood-induction clip to
document the success of the mood inductions. The POMS-SF asks
participants to indicate to what extent a series of 37 adjectives
describes their current mood (e.g., “grouchy”, “furious”) and
yields the same six subscales as the full version of the POMS. We
focused on three of these scales (Tension-Anxiety, e.g., “anxious”,
“uneasy”; Depression-Dejection, e.g., “sad”, “discouraged”; and
Vigor-Activity, a measure of largely positively valenced arousal,
e.g., “lively”, “cheerful”, “full of pep”).
Psychological functioning. At Time 1, which is also when
participants completed the mood-induction and attentional bias
assessment, participants completed self-report measures of current
psychological functioning, namely, the Spielberger State-Anxiety
Inventory, both state and trait versions (STAI-S and STAI-T,
respectively; Spielberger, Gorsuch, & Lushene, 1970), and the
Satisfaction with Life Scale (SLS; Diener, Emmons, Larsen, &
Griffin, 1985). At Time 2, participants returned to the lab and
completed the STAI-S and SLS again (see Table 1 for means and
standard deviations for Time 1 and Time 2). This was their only
task at this second lab session.
Results
Success of Mood Induction
To verify that there were no significant differences in mood
state before mood induction, we submitted the prefilm clip
POMS-SF measures of Tension-Anxiety, Depression-Dejection,
and Vigor-Activity to a one-way analysis of variance (ANOVA)
with a between-subjects factor of mood condition. None of these
comparisons were significant (smallest p.31). To evaluate
whether the mood inductions were successful, we submitted the
data to a series of one-way ANOVAs that compared the nega-
tive (Sad, Fear), positive (Happy, Mirth), and neutral conditions on
postfilm clip POMS-SF factors of interest (Tension-Anxiety,
Depression-Dejection, and Vigor-Activity). Mood condition had a
significant effect on Tension-Anxiety, F(2, 144) 12.56, p
.001, Depression-Dejection, F(2, 144) 19.79, p.001, and
Vigor-Activity, F(2, 144) 16.76, p.001.
In follow-up analyses using Fisher’s least significant difference,
we determined that people in the negative conditions reported
greater levels of Tension-Anxiety and Depression-Dejection than
people in either the positive (all ps.001) or neutral (all ps.01)
conditions, who did not differ from one another. People in the
positive conditions, on the other hand, reported greater levels of
Vigor-Activity than people in the negative (all ps.001) or
neutral (all ps.001) conditions.
Suggesting specificity in the induction of Fear and Sadness,
people in the Fear condition reported significantly greater levels of
Tension-Anxiety than any of the other conditions (all p.01),
whereas people in the Sad condition reported significantly greater
levels of Depression-Dejection than any of the other conditions (all
ps.01). People in both the Happy and Mirth conditions reported
greater increases in Vigor-Activity than the other conditions
(greatest p.02), but did not differ from one another ( p.58).
Spatial Cueing Task
To prepare the spatial cueing task data for analysis, we first
computed the number of errors separately by valence and validity
at pre- and postmood induction. For each subject, we calculated
the mean and standard deviation of response times on the correct
trials (99% of the total trials) and deleted all data points lying
outside 3 SDs from the mean (see Table 2 for response time means
and standard deviations by timing [pre-, postmood induction] and
mood condition). The percent of deleted outliers per subject aver-
aged 1.41 (SD 0.74). One-way ANOVAs comparing the mood
Figure 1. Schematic of a valid trial in the spatial cueing task.
Table 1
Mean (SD) Ill-Being and Well-Being Measured Concurrently
and at 3-Week Follow-Up
Concurrent (Time 1) Follow-up (Time 2)
STAI-S 44.31 (8.56) 45.02 (9.44)
SLS 24.41 (6.34) 25.05 (6.41)
STAI-T 42.44 (7.88)
Note. STAI-S State-Trait Anxiety Inventory, State version. SLS
Satisfaction with Life Scale. STAI-T State-Trait Anxiety Inventory,
Trait version, collected only at Time 1.
243
ATTENTIONAL SHIFTS PREDICT FUNCTIONING
conditions on preattentional bias scores revealed that the condi-
tions did not differ in their attentional bias toward threatening, F(4,
142) .05, p.995, or pleasant, F(4, 142) 1.5, p.21, cues.
A mixed design 5 (condition: Happy, Sad, Neutral, Fear,
Mirth) 2 (time: Pre-Mood Induction, Post-Mood Induction) 3
(cue valence: Threatening, Pleasant, Neutral) 2 (cue validity:
Valid, Invalid) general linear model (GLM) indicated main effects
of validity (participants responded more rapidly in the valid trials)
and time (participants responded more quickly after mood induc-
tion) (both ps.0001). There were no main effects of valence on
response times and no main effects of or interactions with mood
condition. Entering our measures of concurrent psychological
functioning (SLS, STAI-S) as covariates in the GLM above did not
change these results.
Hypothesis Testing
Using an individual-difference approach, our primary research
aim was to assess whether our measures of MIAS to threatening
and/or pleasant cues would predict changes in state anxiety and life
satisfaction over time. Thus, we computed a series of linear re-
gressions separately by mood condition. These regressions as-
sessed whether attentional bias-change scores (post-pre) at Time 1
were associated with psychological functioning (STAI-S, SLS) at
Time 2. In these analyses, psychological functioning at Time 2 was
the criterion variable; Time 1 psychological functioning was en-
tered on the first step as a control variable, and the attentional bias
composite score was entered on the second step.
Do Mood-Induced Attentional Shifts Predict Ill-Being
(State Anxiety)?
As predicted, in the Fear condition, a shift in attention toward
threatening cues from pre- to postfilm clip at Time 1 was associ-
ated with higher STAI-S scores at Time 2, taking into account
levels of STAI-S at Time 1, ␤⫽.07, p.04, R
2
.14 (see
Figure 2). Higher STAI-S scores at Time 1 were associated with
higher STAI-S scores at Time 2, ␤⫽.54, p.03. A follow-up
ttest indicated that there was no mean change in STAI-S from
Time 1 to Time 2, t(25) .02, p.98, in the sample as a whole.
There were no significant associations between MIAS and state
anxiety 3 weeks later in the Sad, Neutral, Happy, or Mirth mood
groups.
Do Mood-Induced Attentional Shifts Predict
Well-Being (Satisfaction With Life)?
As predicted, in the Happy condition, a shift in attention toward
pleasant cues from pre- to postfilm clip at Time 1 was associated
with higher SLS scores at Time 2, taking into account levels of
SLS at Time 1, ␤⫽.05, p.006, R
2
.17 (see Figure 3).
Interestingly, a shift toward threatening cues in the Happy condi-
tion was also associated with higher SLS scores at Time 2, taking
into account levels of SLS at Time 1, ␤⫽.04, p.01, R
2
.15.
Table 2
Mean (SD) Response Times During Spatial Cueing Task Before and After Mood Induction
Condition
Prefilm clip Postfilm clip
Threatening Neutral Pleasant Threatening Neutral Pleasant
Sad
Valid 246.62 (73.74) 245.51 (72.55) 242.96 (68.91) 223.89 (65.14) 221.31 (65.06) 213.86 (61.16)
Invalid 258.25 (80.40) 259.38 (84.83) 259.67 (84.66) 230.95 (80.01) 232.23 (81.00) 230.69 (81.35)
Fear
Valid 260.75 (76.63) 265.53 (82.07) 266.35 (85.90) 235.22 (77.08) 233.67 (81.67) 235.62 (82.20)
Invalid 286.20 (100.78) 291.45 (84.20) 281.11 (82.64) 258.88 (103.56) 269.42 (103.58) 267.83 (116.79)
Neutral
Valid 277.16 (79.22) 275.34 (75.45) 273.44 (81.83) 250.92 (70.11) 246.18 (67.66) 242.66 (65.71)
Invalid 286.91 (89.81) 284.35 (104.93) 292.63 (87.79) 268.05 (73.25) 266.10 (71.71) 272.75 (77.44)
Mirth
Valid 243.98 (85.34) 245.70 (83.74) 241.72 (76.62) 204.86 (73.39) 207.02 (72.96) 209.52 (73.84)
Invalid 253.79 (89.12) 258.10 (91.41) 259.42 (84.39) 222.49 (89.39) 224.28 (90.62) 225.64 (86.40)
Happy
Valid 247.44 (60.49) 249.40 (61.24) 251.73 (60.19) 229.95 (69.29) 232.69 (69.29) 234.40 (66.65)
Invalid 268.46 (68.94) 279.73 (80.87) 253.98 (79.60) 244.55 (83.99) 253.98 (79.60) 255.80 (83.17)
Figure 2. A scatter plot showing the zero-order correlation between shift
in attentional bias toward threatening faces from before to after the induc-
tion of a fearful mood and an increase in state-anxiety scores 3 weeks later,
as measured with the state form of the State-Trait Anxiety Inventory
(STAI-S; Time 2 Time 1).
244 CAVANAGH, URRY, AND SHIN
Higher SLS scores at Time 1 were associated with higher SLS
scores at Time 2, ␤⫽.70, p.001. A follow-up ttest indicated
that there was no mean change in SLS from Time 1 to Time 2,
t(19) 1.26, p.22, in the sample as a whole. There were no
significant associations between MIAS and well-being 3 weeks
later in the Fear, Sad, Neutral, or Mirth mood groups.
Follow-Up Analyses
Biases in attentional engagement versus disengagement.
To reduce our familywise error rate in the above analyses, we used
composite measures of attentional bias that collapse across en-
gagement and disengagement of attention to emotional cues. How-
ever, previous research has suggested that separating out these two
constructs may be informative (e.g., Fox, Russo, Bowles, & Dut-
ton, 2001). We, therefore, repeated our regression analyses for the
Fear and Happy conditions, this time separately examining atten-
tional engagement and disengagement processes. Engagement of
attention to emotional cues was calculated as RT valid neutral
cue—RT valid emotional cue. Difficulty disengaging attention
from emotional cues was calculated as RT invalid emotional
cue—RT invalid neutral cue. Again, the predictor of interest was
the shift in engagement (or difficulty disengaging) from before to
after mood induction (post-pre).
In the Fear condition, there were no significant associations
between shifts in engagement with or difficulty disengaging from
threatening cues and change in state anxiety over the 3-week
follow-up period, ␤⫽.03, p.66, R
2
.01 and ␤⫽.06, p
.10, R
2
.09, respectively. In the Happy condition, however,
greater difficulty disengaging attention from threatening, ␤⫽.07,
p.002, R
2
.21, and pleasant, ␤⫽.06, p.02, R
2
.14,
cues significantly predicted increases in satisfaction with life over
time. Greater engagement of attention to pleasant cues predicted
only marginally significant increases in satisfaction with life over
time, ␤⫽.08, p.08, R
2
.08.
Are mood-induced attentional shifts equivalent to trait anx-
iety? Based on previous studies demonstrating strong associa-
tions between trait anxiety and attentional biases to emotional
information, might MIAS in the present context represent a proxy
for trait anxiety? If that were true, MIAS should be correlated with
trait anxiety. However, we did not observe any significant corre-
lations between trait anxiety and our measures of MIAS within the
Fear and Happy conditions. The only exception was a trend toward
a significant correlation between trait anxiety and shift toward
threatening faces following the Happy film clip, r(29) .35, p
.06.
Moreover, if MIASs in the present context represent a proxy for
trait anxiety, MIAS should no longer predict change in anxiety or
satisfaction with life at Time 2 when controlling for trait anxiety at
Time 1. However, a follow-up regression in the Fear condition
indicated that entering Time 1 trait anxiety (STAI-T) along with
Time 1 STAI-S on the first step did not eliminate the association
between attention to threatening cues at Time 1 and higher STAI-S
scores at Time 2, ␤⫽.06, p.08, R
2
.09, although it did
reduce this association to a trend-level effect.
Similarly, follow-up regressions in the Happy condition indi-
cated that entering Time 1 trait anxiety (STAI-T) along with Time
1 SLS on the first step did not eliminate the association between
attention to emotional cues at Time 1 and higher SLS scores at
Time 2, pleasant ␤⫽.06, p.005, R
2
.19, and threatening,
␤⫽.05, p.003, R
2
.20, respectively.
Mood-Induced Attentional Shifts and Concurrent and
Future Psychological Functioning
Finally, whereas our primary focus in this article was on
whether MIAS would predict changes in psychological function-
ing over time, we next examined whether MIAS would be asso-
ciated with concurrent and/or future levels of psychological func-
tioning. To this end, we followed up our significant findings in the
Fear and Happy condition by conducting Pearson correlations
between MIAS and concurrent and follow-up measures of psycho-
logical functioning (STAI-S, SLS).
In the Fear condition, there was no association between a shift
in attention toward threatening cues from pre- to postfilm clip at
Time 1 and concurrent levels of state anxiety, r(25) ⫽⫺.01, p
.97. However, there was a trend-level association with follow-up
levels of state anxiety, r(25) .37, p.065. In the Happy
condition, there was no association between a shift in attention
toward threatening cues from pre- to postfilm clip at Time 1 and
either concurrent, r(28) ⫽⫺.08, p.68, or follow-up, r(19)
.33, p.16, levels of satisfaction with life. Also, in the Happy
condition, there was no association between a shift in attention
toward pleasant cues from pre- to postfilm clip at Time 1 and
either concurrent, r(28) ⫽⫺.08, p.68, or follow-up, r(19)
.28, p.23, levels of satisfaction with life.
Discussion
Collectively, our results suggest that, in a sample of college
students not preselected for extreme scores on clinical measures,
naturalistic mood-induced shifts in attention to threatening and
Figure 3. A scatter plot showing the zero-order correlation between shift
in attentional bias toward pleasant faces from before to after the induction
of a happy mood significantly and an increase in satisfaction with life 3
weeks later, as measured with the Satisfaction with Life Scale (SLS; Time
2Time 1).
245
ATTENTIONAL SHIFTS PREDICT FUNCTIONING
positive information are associated with individual variation in ill-
and well-being over time. Namely, a shift in attention to threaten-
ing cues after fear mood induction was associated with increases in
state anxiety. In addition, a shift in attention to emotional cues
(threatening and pleasant) following happy mood induction was
associated with increases in satisfaction with life. These results
were obtained in the absence of mean changes in anxiety and life
satisfaction over the brief, 3-week follow-up period. We discuss
these results, in turn, below.
Links to Existing Literature
As predicted, shifting attention toward threatening stimuli after
fear induction was associated with small elevations in state anxi-
ety. This extends previous work on experimentally induced
changes in attentional bias (e.g., Clarke et al., 2008; Schmidt et al.,
2009) and work examining differential changes in attentional bias
based on an interaction of state and trait anxiety (e.g., Rutherford
et al., 2004). These data add the important observation that natu-
ralistic individual differences in MIASs are associated with indi-
vidual differences in change in state anxiety over time. It is notable
that there were no MIASs in the sample as a whole. In keeping
with Yiend’s (2010) observations, it may be that the threatening
and pleasant faces cues were not sufficiently intense or short
enough in duration to encourage attentional bias or that the mood
inductions were not sufficiently potent to lower the threshold for
detection of emotional information in this unselected sample.
Regardless, people who shifted attention toward threatening
cues when we induced fear in the laboratory were more likely to
experience small increases in state anxiety over the 3 weeks that
followed. On the other hand, people who shifted attention away
from threatening cues when we induced fear in the laboratory were
more likely to experience small decreases in state anxiety. In the
sample as a whole, there was no systematic change in state anxiety
over time. For this reason, an individual-difference approach was
necessary to cull out the intriguing association between MIAS and
increased later anxiety. Importantly, relations between MIAS and
changes in state anxiety over time were still present even when
controlling for levels of trait anxiety, though controlling for trait
anxiety did reduce the effect to a strong trend. Thus, MIASs were
not simply serving as a proxy for trait anxiety.
Shifts in attentional bias toward both threatening and pleasant
cues after happy mood induction were associated with small in-
creases in well-being over time. This result is reminiscent of Tamir
and Robinson’s (2007) finding that induction of positive moods
resulted in attentional bias toward rewarding words, and
Wadlinger and Isaacowitz’s (2006) finding that inducing a positive
mood increased attention to peripheral positive and neutral images.
Our results, however, take the important next step of determining
that these kinds of attentional biases for positive information have
functional consequences. Notably, neither of these studies reported
a relationship between the positive mood inductions and bias
toward negative stimuli. This may be because the methods and
stimuli were quite different from the present study. For example,
whereas the previous studies only assessed attentional bias after
the mood induction, we assessed attentional bias both before and
after. This allowed us to isolate mood-induced shift in attentional
bias, which may have increased our sensitivity. Notably, although
we observed that MIASs toward threat after happy mood induction
were modestly correlated (at a trend level) with concurrent trait
anxiety, including trait anxiety as a predictor, did not eliminate the
relationship between concurrent MIAS and increases in later well-
being. Thus, it appears that these may be unrelated effects.
Our finding that shifts in attention to potentially salient (threat-
ening and pleasant) cues after the induction of happy mood were
associated with higher levels of well-being over a follow-up period
of 3 weeks is consistent with Fredrickson’s broaden-and-build
theory of positive emotion (Fredrickson, 1998, 2001). This theory
suggests that in contrast to negative emotions, which are associated
with specific thought-action repertoires, positive emotions gener-
ally broaden cognition. This allows for creative exploration and the
building of resources required for well-being and resilience. Inter-
preted in light of this theory, broadening one’s attention to both
threatening and pleasant stimuli in one’s environment may allow
for the detection of resources and information that may be impor-
tant for well-being.
Despite similar effects on mood as measured by the POMS-SF,
we did not find a relationship between shifts in attentional bias and
well-being following mirth mood induction. The mirth film clip
consisted of a series of skits from Saturday Night Live 25th
Anniversary Special. As such, the type of humor portrayed was
largely disparagement humor, in which one or more of the char-
acters were being ridiculed or mocked in some way. It may well be
that this type of belittling humor does not lead to the type of
positive affect linked to the broadening of cognition and the
building of resources (such as contentment).
Previous research has suggested that separately considering
processes related to engagement and disengagement of attention to
emotional cues may be informative (e.g., Fox et al., 2001). Indeed,
when in a happy mood, participants who exhibited greater diffi-
culty disengaging from emotional cues experienced increased sat-
isfaction with life 3 weeks later. Although the effect for engage-
ment of attention to pleasant cues showed a trend in a similar
direction, this was only marginally significant. Surprisingly, nei-
ther increased attentional engagement with nor difficulty disen-
gaging from threatening cues when in a fearful mood predicted
increased later anxiety when considered separately. The associa-
tion only held when we collapsed across these two, theoretically
separable attentional processes. Several recent reviews have sug-
gested that attentional bias toward threat may be found for both
forms of attention (Cisler et al., 2009; Yiend, 2010), but another
notes inconsistent findings when using cue durations similar to
ours (Ouimet, Gawronski, & Dozois, 2009). We had no a priori
predictions about the relative importance of attentional engage-
ment or disengagement processes for predicting changes in later
state anxiety and satisfaction with life. It remains to be seen
whether this distinction will be important in future studies, perhaps
using different cue durations.
Although MIAS successfully predicted changes in state anxiety
and life satisfaction over time, we were surprised not to find
similar associations between MIAS and concurrent levels of these
constructs. Indeed, any time period before the MIAS task at Time
1 might reasonably also have contained emotional events that
would have elicited MIAS and, according to our model, affected
psychological functioning at Time 1. In this context, it is important
to note that our concurrent measures of psychological functioning
were collected at the end of the 2-hr study session at Time 1.
Speculatively, it could be that participant fatigue after this rather
246 CAVANAGH, URRY, AND SHIN
long period of time impacted individual differences in concurrent
psychological functioning that might otherwise have been associ-
ated with MIAS. Future work may be benefited by collecting
concurrent measures of psychological functioning at the beginning
of the study session.
Speculation About the Mechanism That Links MIAS
to Changes in Ill- and Well-Being
What might be the mechanism that explains the relations be-
tween mood-induced shifts in attention to emotional information at
one point in time and ill- or well-being 3 weeks later? Although
speculative, we believe that small mood-induced shifts in attention
in the laboratory may be representative of similar shifts that occur
in response to mood-eliciting events in everyday life. Used on a
routine basis, these patterns of mood-induced attentional shifts
may accumulate in such a way that they cause changes in psycho-
logical functioning (e.g., anxiety or satisfaction with life). Of
course, our correlational results do not permit us to do more than
speculate about causal inferences, and as noted earlier, it is unusual
that these effects were only present when examining changes over
time. In future work, it would be useful to measure the frequency
of mood states and life events experienced during the follow-up
period, perhaps using experience-sampling methodology. If what
we are suggesting is true, then people who have more frequent
mood-eliciting events in between the laboratory and follow-up
assessments should experience greater changes in ill- or well-
being. Nevertheless, even if mood-induced attentional shifts to-
ward emotional information do accumulate in ways that cause
changes in ill- and/or well-being, this would surely represent only
one of many causal psychological pathways. Individuals may vary
over time in state measures based on any number of contributing
factors (e.g., life stress, health, rest, and personality). If the results
of this study are replicated, future research would need to explicate
the causal mechanisms.
Theoretical and Clinical Implications
Gross (1998) has suggested, as part of his process model of
emotion regulation, that deployment of attention is one of several
processes that can be used in the service of regulating emotion
experience, expression, and physiology. Evidence for this notion
comes from experiments suggesting that directing attention to
emotional versus neutral information in unpleasant photos influ-
ences emotion experience and expressive behavior (Urry, 2010)
and the late positive potential, a neural index of emotional arousal
(Dunning & Hajcak, 2009; Hajcak, Dunning, & Foti, 2009). Based
on these observations, it may well be that the mood-induced
attentional shifts we measured might actually have had an imme-
diate emotion-regulatory effect in the laboratory. Unfortunately,
we did not collect ratings of mood after the postmood induction
spatial cueing task, which would have allowed us to assess that in
this study.
In addition to possibly having immediate regulatory effects on
mood state, the associations we observed between mood-induced
attentional shifts and later anxiety and well-being are highly con-
sistent with the attentional training literature. Experiments show,
for example, that one can train an attentional bias to threat over
time, and this produces elevated anxiety in response to a laboratory
stressor (MacLeod et al., 2002). Moreover, anxious people who are
trained over time to avoid attending to threat experience reduced
levels of anxiety over time (e.g., Schmidt et al., 2009; See et al.,
2009). Based on the present data, it is possible that attentional
training paradigms might produce stronger effects on later psycho-
logical functioning, if training were to take place in the context of
mood induction. That is, training attention away from threat when
one is afraid/anxious may best discourage later anxiety. Similarly,
training attention toward both threatening and happy cues when in
a happy mood may best encourage later satisfaction with life. This
possibility remains to be tested in future work.
Additional Limitations and Directions for Future
Research
We have made an important, novel contribution by showing that
naturalistic mood-induced shifts in attention to emotional informa-
tion predict changes in ill- and well-being over a 3-week follow-up
period. That being said, there were some notable limitations to the
current study. First, because we did not conduct diagnostic inter-
views, we cannot say to what extent diagnosable psychopathology
accounts for the findings we obtained. Second, our design did not
allow us to assess whether MIAS predicted changes in trait anxiety
over time which, given the past history of work on state/trait
interactions, may have been very informative. Third, given the
between-subjects design for the mood induction, we also had a
relatively small sample size. This may have hindered our ability to
detect significant differences between mood conditions and limited
the generalizability of our findings. Fourth, we used only one
negative facial expression (angry/threatening) as a cue in the
spatial cueing task. We may have observed different effects if we
had used other negative facial expressions (e.g., fearful, sad).
Finally, our findings were generally limited to associations be-
tween MIAS to threatening and/or pleasant cues and change in ill-
and well-being over the 3-week follow-up period. The lack of
associations between MIAS to threatening and/or pleasant cues
and concurrent or follow-up psychological functioning indicates a
need for replication and further exploration of the relationships
between MIAS, state anxiety, and life satisfaction.
Conclusions
In sum, this intriguing pattern of results contributes to the
theories of vulnerability to emotional disorders and promotion of
well-being by suggesting that, in addition to experimentally in-
duced changes in attentional bias, naturalistically adopted atten-
tional bias may contribute to changes in psychological functioning
over time. People who show biased attention to threatening infor-
mation as a function of fearful mood experience increases in state
anxiety over time. By contrast, people who show biased attention
to positive (and threatening) information as a function of happy
mood experience increases in satisfaction with life. It would be
important in future experimental and individual-difference work to
further specify the extent to which subtle changes in attention to
emotional information in the environment as a function of mood
state, particularly happy and fearful moods, are important deter-
minants of ill- and well-being (and vice versa).
247
ATTENTIONAL SHIFTS PREDICT FUNCTIONING
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Accepted December 8, 2010
248 CAVANAGH, URRY, AND SHIN
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Stimmungen beeinflussen unsere kognitiven Prozesse. In diesem zweiten Band zum Thema Stimmung werden wie schon in Stimmung I ausgewählte Paradigmen der kognitiven Psychologie übersichtlich, aktuell und systematisch vorgestellt. Ein besonderer Fokus liegt wiederum auf Experimenten, in denen vor der Durchführung des jeweiligen kognitiven Paradigmas eine Manipulation der Stimmung vorgenommen wurde. Die Experimentaldetails sowie die Ergebnisse dieser Experimente werden ausführlich und möglichst umfassend zusammengefasst. Im vorliegenden Band werden Aufmerksamkeits-, Lern-/Gedächtnis-, Wahrnehmungs-, Denk-/Prolemlöseparadigmen und weitere klassische Experimente behandelt.
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... A mood-congruent disengagement bias in response to a temporarily induced negative mood is consistent with Becker and Leinenger (2011), who demonstrated that negative mood induction can influence very early and basic cognitive processes (i.e., attentional control). Our findings apparently contrast with those reported by Cavanagh et al. (2011) in a non-clinical sample, since they did not obtain changes in ABTs after fear induction. A possible explanation of these divergent findings might be related to the fact that Cavanagh et al. (2011) used a different mood induction procedure (presentation of film clips) that might be less effective of the autobiographical recall in eliciting ABTs. ...
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... Aja), for the induction of fear. To encourage the subjects' empathic identification with the victim (i.e., the protagonist of each scene), the victim had a similar age to our subjects in both cases; each scene lasted around five minutes-a length suitable for elicitation purposes (Cavanagh et al. 2011). 4. Picture MIP (emotional elicitation by watching pictures): Images that 'typically' affect human sensibility, such as insects or blood, were selected to induce disgust. ...
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... It is also possible that individual differences in AB are related to the environmental context of the task. Studies that induce negative moods have altered cognitive processes such as memory for affective words (Cavanagh et al., 2011). Research into the dot-probe task under differing contexts is limited, but suggests that attention can be modulated by the environmental context in which it is assessed (Shechner et al., 2012). ...
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