Emotion
2008, Vol. 8, No. 6, 810 – 819
Copyright 2008 by the American Psychological Association
1528-3542/08/$12.00 DOI: 10.1037/a0013731
Recognizing Masked Threat: Fear Betrays, But Disgust You Can Trust
Stefan Wiens
Nathalie Peira
Stockholm University and Karolinska Institute
Stockholm University
Armita Golkar
Arne Öhman
Stockholm University and Karolinska Institute
Karolinska Institute
If emotions guide consciousness, people may recognize degraded objects in center view more accurately
if they either fear the objects or are disgusted by them. Therefore, we studied whether recognition of
spiders and snakes correlates with individual differences in spider fear, snake fear, and disgust sensitivity.
Female students performed a recognition task with pictures of spiders, snakes, flowers, and mushrooms
as well as blanks. Pictures were backward masked to reduce picture visibility. Signal detection analyses
showed that recognition of spiders and snakes was correlated with disgust sensitivity but not with fear
of spiders or snakes. Further, spider fear correlated with the tendency to misinterpret blanks as
threatening (response bias). These findings suggest that effects on recognition and response biases to
emotional pictures vary for different emotions and emotional traits. Whereas fear may induce response
biases, disgust may facilitate recognition.
Keywords: fear, recognition, masking, disgust sensitivity, signal detection
(Becker & Rinck, 2004; Öhman & Soares, 1994; Windmann &
Krüger, 1998; Winton, Clark, & Edelmann, 1995; for an early
review, see Mathews & MacLeod, 1994). In these studies, threat
pictures were shown briefly and were followed immediately by a
scrambled picture to reduce picture visibility (backward masking;
for a review, see Wiens & Öhman, 2007). The studies found no
relationship between social anxiety and recognition of masked
negative facial expressions among masked neutral facial expressions (Winton et al., 1995), between panic disorder and recognition
of masked threat words (Windmann & Krüger, 1998), and between
small-animal phobia and recognition of spiders or snakes (spider
fear, Becker & Rinck, 2004; spider and snake fear, Öhman &
Soares, 1994).
Although the null findings for small-animal phobia do not
support an association between fear of spiders or snakes and threat
recognition (Becker & Rinck, 2004; Öhman & Soares, 1994), they
may have been because of methodological problems and low
power. First, the Öhman and Soares (1994) study had only a small
sample size (n ⬍ 9 in each group) and thus low power. Second,
because in masking, pictures are flashed briefly, participants may
have difficulty recognizing the brief pictures even without masking. So, because the Becker and Rinck (2004) study did not
demonstrate that participants could actually recognize the brief
pictures when they were not masked, it is unresolved whether
general difficulties in recognizing the pictures may have limited
performance range and thus reduced the study’s power to detect a
relationship between spider fear and spider recognition.
Further, even if fear plays no role in affecting recognition
performance, other emotions may do so. In particular, disgust may
affect recognition of threat from small animals such as spiders,
cockroaches, maggots, snails, slugs, snakes, and rats. In part, these
animals may be threatening for the same reason that large animals
are: A physical attack may motivate fear associated with predator
Sensory systems have only limited capacity (Shevrin & Dickman,
1980), but emotions may play an important role in overcoming this
limitation by allocating sensory processing resources effectively
(LeDoux, 2000; Öhman & Mineka, 2001). First, people may direct
attention to emotional rather than nonemotional input (e.g., attentional
bias; Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van
Ijendoorn, 2007). Second, people may process spatially attended
emotional input even if they remain unconscious of the input (e.g.,
subliminal emotion perception; Wiens, 2006a). Third, people may be
more likely to become conscious of attended input if the input is
emotional (e.g., attentional blink, Anderson & Phelps, 2001). This
preferential access to consciousness would facilitate strategic and
flexible responding (Dehaene & Naccache, 2001). So, if it is true that
attended objects are recognized preferentially if they have emotional
value, then people who are afraid of spiders should be able to
recognize spiders in center view even if these are barely visible
(Becker & Rinck, 2004). Because recognition performance is often
used as an index of consciousness (Wiens, 2007), such a finding
would support the notion that fear and maybe other emotions can
facilitate consciousness of attended input.
However, several studies suggest that individual differences in
fear as a trait variable do not correlate with recognition of threat
Stefan Wiens and Armita Golkar, Department of Psychology, Stockholm University and Psychology, Department of Clinical Neuroscience,
Karolinska Institute; Nathalie Peira, Department of Psychology, Stockholm
University; Arne Öhman, Psychology, Department of Clinical Neuroscience, Karolinska Institute.
This work was supported by the Swedish Research Council. We thank
Silke Anders for comments and her inspiration for the title, Steve Palmer
for editorial comments, and Gilles Pourtois for helpful discussions.
Correspondence concerning this article should be addressed to Stefan
Wiens, Frescati Hagväg 14, Psykologiska Institutionen, Stockholms Universitet, 106 91 Stockholm, Sweden. E-mail: sws@psychology.su.se
810
MASKED THREAT
defense (Öhman, 1986). More important, these animals may be
threatening because they can be carriers of harmful diseases. This
threat of contamination may motivate disgust associated with
disease avoidance (Curtis & Biran, 2001; Matchett & Davey,
1991). In support of the idea that small-animal phobia is associated
with disgust, various studies have found that spider-fearful participants rate spiders as highly disgusting (Sawchuk, Lohr, Westendorf, Meunier, & Tolin, 2002; Thorpe & Salkovskis, 1998; Tolin,
Lohr, Sawchuk, & Lee, 1997), show disgusted facial expressions
to spiders (de Jong, Peters, & Vanderhallen, 2002; Vernon &
Berenbaum, 2002), and avoid eating a cookie that was touched
(and thus contaminated) by a spider (Mulkens, de Jong, &
Merckelbach, 1996).
Research has further shown that small-animal phobia correlates
positively with disgust sensitivity. Disgust sensitivity is a trait that
affects how easily a person responds with disgust in several
contexts: food, body products, sex, animals, body envelope violations, death, hygiene, and magical thinking (Haidt, McCauley, &
Rozin, 1994). When measured with a 32-item questionnaire, disgust sensitivity exhibits good test–retest reliability (r ⫽ .79 for a
2-month interval) and predicts actual disgust responses to disgusting stimuli (Rozin, Haidt, McCauley, Dunlop, & Ashmore, 1999).
However, although it has been argued that the disgust contexts can
be separated (Haidt et al., 1994), evidence suggests that only the
global score has acceptable psychometric properties (Björklund &
Hursti, 2004). Research has found a positive relationship between
disgust sensitivity and spider fear (de Jong & Merckelbach, 1998;
Merckelbach, de Jong, Arntz, & Schouten, 1993; Mulkens et al.,
1996; Osswald & Reinecker, 2004; Sawchuk, Lohr, Tolin, Lee, &
Kleinknecht, 2000; Tolin et al., 1997) and between disgust sensitivity and snake fear (Klieger & Siejak, 1997). Although the causal
role of disgust in fear is debated (Davey & Bond, 2006; Edwards
& Salkovskis, 2006; Marzillier & Davey, 2005), disgust sensitivity
may correlate with spider fear independently of other variables
(e.g., trait anxiety, neuroticism) (Mulkens et al., 1996; Olatunji,
2006) and predict disgust responses to spiders over and above
spider fear, negative affect, contamination fear, and trait anxiety
(Olatunji & Deacon, 2008).
Because it may be that disgust sensitivity rather than fear
correlates with threat recognition in center view, we studied correlations between spider fear, snake fear, and disgust sensitivity
and recognition of spiders, snakes, flowers, and mushrooms. On
each trial, a picture from one of these categories or a blank (catch
trial) was shown briefly and followed by a scrambled picture to
reduce the visibility of the first picture (backward masking). After
each trial, participants indicated whether the first picture was a
spider, snake, flower, or mushroom. Based on these responses,
signal detection analyses (Macmillan & Creelman, 2005) were
performed to distinguish between recognition (d⬘) and response
bias (C). We expected that if fear facilitates recognition, spider
fear (or snake fear) would be correlated with recognition of spiders
(or snakes) but not with recognition of flowers and mushrooms.
Similarly, if disgust sensitivity facilitates recognition, disgust sensitivity would be correlated with recognition of spiders and snakes
but not with recognition of flowers and mushrooms.
Whereas previous studies found no evidence that fear facilitates
threat recognition, several studies have found that fear correlates
with response biases (Becker & Rinck, 2004; Kolassa et al., 2007;
Windmann & Krüger, 1998; Winton et al., 1995). In these studies,
811
response biases were associated with a greater tendency to misinterpret nonthreatening input as threatening (false alarms). For
example, spider-fearful individuals were not better than nonfearful
individuals in detecting spiders but had a stronger tendency to
misinterpret distorted original pictures (catch trials) as spiders
(Becker & Rinck, 2004). However, the results of the Becker and
Rinck study may be attributable, in part or completely, to the
specific task setup. Because participants were told before each
block that pictures would be taken only from a particular category,
spider-fearful individuals might have been primed to indicate that
they saw spiders during the spider block. This tendency might have
been enhanced by the fact that pictures shown in catch trials were
actually distorted versions of the original pictures that retained the
color and maybe even other features of the original pictures. To
avoid these problems, we presented participants with four pictures
categories and informed them before the task that the four picture
categories would be shown equally often. In addition, catch trials
were blank to avoid any resemblance with the actual pictures.
In summary, this study assessed correlations of spider fear,
snake fear, and disgust sensitivity with recognition and response
biases to masked pictures of spiders, snakes, flowers, and mushrooms. Picture visibility was manipulated with stimulus onset
asynchronies (SOAs) of 12, 24, 36, and 200 milliseconds between
pictures and masks. Blank trials (i.e., no target pictures) were
included to assess participants’ tendency to interpret nonthreatening input (blanks) as threatening (false alarms). Blanks were
shown only at the shortest SOA to enhance participants’ beliefs
that there was a target picture on each trial. The longest SOA (200
milliseconds) was included as a control condition to demonstrate
that participants could detect targets well if pictures were shown
briefly but masking was ineffective. The three short SOAs were
included to determine whether any relationship of recognition with
fear and disgust sensitivity would vary with changes in picture
visibility (cf. Wiens, 2006b). However, a potential difficulty of this
approach is that with complete masking, recognition might be
eliminated for all participants, and this floor effect might reduce
power in detecting correlations between recognition performance
and other variables. Because this risk was considerable for results
from the 12-ms SOA, power in detecting effects was presumed to
be strongest at the 24- and 36-ms SOAs.
Method
Participants
Participants were 53 women (mean age ⫽ 24.98, SD ⫽ 3.72,
range was 20 to 35 years) who responded to advertisements for
female participants at Stockholm University, Sweden. Participants
were informed that they would be shown brief pictures of snakes,
spiders, mushrooms, and flowers and that their task would be to
recognize the pictures. They were asked to fill out short questionnaires either in person or online about their fears of spiders and
snakes. Later, they were contacted and scheduled for an individual
session that lasted 45 minutes. There were no selection criteria
except that only women were recruited because too few men report
spider or snake fear to assess gender effects (e.g., Becker & Rinck,
2004). Participation was based on informed consent and was
rewarded with a movie voucher (worth $8 U.S.).
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WIENS, PEIRA, GOLKAR, AND ÖHMAN
Materials
Forty pictures each of spiders, snakes, flowers, and mushrooms were selected from various sources (e.g., World Wide
Web). For each picture, the background was removed, color
converted to eight-bit gray scale, and size adjusted to fit within
a window of 512 ⫻ 512 pixels. Pictures were further adjusted
so that mean number of pixels, mean luminance, and mean
contrast (i.e., standard deviation of luminance) did not differ
among the four picture categories. Thus, luminance, contrast,
and number of pixels could not confound results. The resulting
160 gray-scale pictures served as targets. Two additional pictures of each category were used for practice. Backgrounds and
masking pictures were created from a collage (520 ⫻ 520
pixels) of original color pictures from all four categories. This
collage was divided into squares of 10 ⫻ 10 pixels, and the
positions of the 2704 (52 ⫻ 52) squares in the collage were
shuffled randomly so that target features were no longer discernable (scrambled). This shuffling procedure was repeated
100 times to generate 50 background and 50 masking pictures.
Figure 1 shows examples of target pictures with backgrounds.
The experiment was run on a desktop PC with a standard
17-inch CRT monitor (Dell, E771p). Screen resolution was
1024 ⫻ 768 pixels, refresh rate was 85 Hz, and the experiment was
programmed in Presentation 9.9 (Neurobehavioral Systems,
www.neurobs.com). Pictures were shown at a distance of 1 meter;
thus, they were shown within horizontal and vertical visual angles
of 9.3 degrees.
Participants completed several questionnaires before and after
the experiment. Before recruitment, they filled out questionnaires
that were modeled after the SAS (Spinnenangstscreening) for
spiders (Rinck et al., 2002) and assessed how much participants
were afraid of spiders (or snakes), avoided them, became physiologically upset, and were bothered by their fear. Each of the four
items was rated on a 7-point scale (from 0 to 6), and the points
were added to yield a separate score for spider and snake fear
between 0 and 24. After the recognition task, participants rated
their own performance in recognizing each picture category compared to the performance of the average participant on a nine-point
scale from ⫺4 (much worse than average) to ⫹4 (much better than
average). Participants also rated the extent of discernable details
(clarity) of each picture category across trials on a 5-point scale.
Further, they rated (in percent) how often they saw (consciously)
spiders, snakes, mushrooms, flowers, or nothing discernable. At
the end of the experiment, participants completed short versions of
the Spider Phobia Questionnaire (SPQ) and the Snake Phobia
Questionnaires (SNAQ) (Klorman, Weerts, Hastings, Melamed, &
Lang, 1974). The SPQ consisted of 18 true-or-false items and the
SNAQ of 20 items. Participants also completed a 32-item ques-
Figure 1. Four example target pictures with backgrounds. Targets were grayscale spiders, snakes, flowers, and
mushrooms; these were shown on a colored scrambled background. Targets were adjusted so that mean numbers
of pixels, luminance, and contrast did not differ among categories. On each trial, a single 12-ms target or blank
(i.e., catch trial with background only) in center view was followed by a 200-ms mask (i.e., backward masked)
at one of four stimulus onset asynchronies (12, 24, 36, or 200 milliseconds). Different versions of a randomly
scrambled color collage served as backgrounds and masks.
MASKED THREAT
tionnaire on disgust sensitivity (Björklund & Hursti, 2004; Haidt et
al., 1994) and the 20-item STAI-trait anxiety inventory
(Spielberger, 1983).
Procedure
Recognition task. Participants were informed that they would
be shown two brief pictures shortly after each other and that the
second picture would always be a scrambled picture. Their task
was to indicate whether they thought that the first picture depicted
a snake, spider, flower, or mushroom. Participants were further
instructed that because the first picture would be shown only
briefly, they might have difficulties in recognizing the picture.
Nonetheless, they were to respond anyway even if they were
guessing. After each picture presentation, a response prompt appeared in the center of the screen and individual category labels
replaced each other with mouse movements. The order of the
labels was randomized for each participant. Participants moved
the mouse until the label of their choice was shown, and clicked
the left mouse button to indicate their response. There was no time
limit in responding. Participants were told that the four categories
would be shown equally often and that trial order would be random
and thus independent of their responses.
Target pictures were shown for a constant duration of 12 milliseconds (1 refresh cycle at an 85-Hz refresh rate) (Wiens et al.,
2004). Stimulus onset asynchrony (SOA) between target and mask
was 12 milliseconds (1 refresh cycle), 24 milliseconds (2 cycles),
36 milliseconds (3 cycles), or 200 milliseconds (17 cycles). Masking pictures were shown for 200 milliseconds (17 refresh cycles).
The response prompt appeared 300 milliseconds after the mask.
After a response, the next trial started randomly after between 300
and 500 milliseconds. On 50 consecutive trials, the 50 background
and 50 masking pictures were used once in random order.
The main task consisted of two blocks (200 trials each) separated by a 5-minute rest. Each block contained 4 (picture category) ⫻ 4 (SOA) ⫻ 10 ⫽ 160 target trials. The remaining 40 trials
consisted of blank trials (i.e., background as target) with a 12milliseconds SOA between target and mask. For each participant,
10 of the 40 target pictures in each category were randomly
assigned to each of the four SOAs. Trial order was randomized for
each participant and each block. Before the actual task, participants performed a practice task to familiarize them with the use of
the mouse and with the experience that picture recognition would
be difficult. The practice task consisted of 10 trials. Eight practice
pictures (two in each category) were shown at the longest SOA and
two blank trials at the shortest SOA. After the actual task, participants answered questions about their experience of the task (i.e.,
ratings of performance, picture clarity, and picture count).
Picture rating task. After the recognition task, participants
rated emotional valence of each of the 160 target pictures on a
9-point scale that ranged from ⫺4 (very negative) to ⫹4 (very
positive). For each participant, trial order was randomized. Below
each picture, a response prompt was shown and was replaced by
number labels (between ⫺4 and ⫹4) that changed with mouse
movements. Pictures were shown until participants responded, but
participants were instructed to indicate their spontaneous impression of the pictures. Before this task, participants familiarized
themselves with the task by rating the practice pictures.
813
Data Reduction
Signal detection analyses (Macmillan & Creelman, 2005) of the
recognition data separated recognition (d⬘) from response bias (C)
for each category and SOA. Signal detection theory stipulates that
participants can only discriminate between signal (e.g., spider
pictures) and noise (e.g., blanks) if signals generally tend to evoke
a greater sensory strength of evidence than noise (for a discussion
of signal detection in masking studies, see Wiens, 2006b). Responses are coded as hits (e.g., spider response to spider pictures)
and false alarms (e.g., spider response to blanks). Participants who
can discriminate between spiders and blanks would respond spider to
most of the spider pictures (i.e., hit rate is high) but not to blanks (i.e.,
false alarm rate is low). The discrimination index d⬘ is computed as
d⬘ ⫽ zhit rate – zfalse alarm rate; thus, it is the distance between the means
of the signal and noise distributions in z scores. The criterion C is
computed as C ⫽ ⫺0.5 ⴱ (zhit rate ⫹ zfalse alarm rate); thus, it is the
z-score distance from the intersection point of signal and noise distributions. Participants are unbiased if they are as likely to misinterpret
noise as signal (false alarm) as they are likely to report signal as
noise (miss); thus, if false alarm rate equals miss rate, then C ⫽
0. For example, if the hit rate is 0.80 and the false alarm rate is
0.20, then the miss rate (which is 1 – hit rate) is also 0.20.
Because for a hit rate of 0.80, z hit rate ⫽ 0.842, and for a false
alarm rate of 0.20, zfalse alarm rate ⫽ ⫺.842, C ⫽ ⫺0.5 ⴱ (0.842 –
0.842) ⫽ 0. Participants with a liberal response bias would be
more willing to produce false alarms (C ⬍ 0) whereas participants
with a conservative response bias would be less willing to produce
false alarms (C ⬎ 0).
Because z scores (for d⬘ and C) can be computed only for rates
that are greater than 0 and less than 1, we avoided these extreme
rates as follows: To compute each rate, half a trial was added as a
response (in numerator) and one trial was added to the total
number of possible responses (in denominator) (Snodgrass &
Corwin, 1988). For example, the corrected hit rates for spiders at
each SOA were: (Number of spider hits ⫹ 0.5)/(total number of
spider trials ⫹ 1); the total number of spider trials at each SOA
was 20. Because 0.5 was added in the numerator, the numerator
was never zero and, thus, each rate exceeded zero. In addition,
because 1 was added in the denominator, the denominator was
always greater than the numerator and, thus, each rate was always
less than 1. Similar to the hit rate, the corrected false alarm rate for
spiders was: (Number of spider false alarms ⫹ 0.5)/(total number
of blank trials ⫹ 1). Because all blanks (total number of trials was
80) were shown at the shortest SOA (12 milliseconds), the false
alarm rate for each category was constant for the four SOAs.
Because blanks were used to determine false alarms, this signal
detection analysis isolated how well participants could distinguish
between specific targets and blanks. Results were comparable for
an analysis (not reported here) that assessed how well participants
could distinguish targets from nontargets other than blanks.
A repeated-measures ANOVA was performed to study effects
of SOA on recognition (d⬘). Although a similar analysis was
performed on response biases (C), it is not reported because its
meaning is limited and because it is irrelevant for the interpretation
of the present results. First, because the false alarm rate for a
category was constant over SOAs (as it was derived from the blank
trials), C changed as a direct consequence of changes in recognition. That is, with the constant false alarm rate over SOAs, an
WIENS, PEIRA, GOLKAR, AND ÖHMAN
814
increase in hit rates with longer SOAs resulted in increases in d⬘
and also (as a concomitant) in a stronger tendency to indicate that
a target was recognized (i.e., C would appear to be lower). Second,
because the present study focused on individual differences
(between-subjects effects) at particular SOAs rather than on
changes of response biases over SOAs (within-subjects effects),
this aspect of the analysis is irrelevant for the interpretation of the
present results.
In most cases, the direction of effects was clearly predicted from
theory (e.g., spider fear would correlate with more liberal response
biases to spiders). Therefore, significance tests were two-tailed
only if findings of an association were novel (e.g., relationship
between disgust sensitivity and threat recognition). Furthermore,
for all ANOVAs with repeated measures, significance levels ( p ⬍
.05) were Greenhouse-Geisser corrected.
Results
Spider Fear, Snake Fear, Disgust Sensitivity,
and Trait Anxiety
Scores on the prerecruitment 4-item questionnaires for spider
fear and snake fear covered the full range of the scales (between 0
and 24). These fear scores correlated specifically with spider fear
(SPQ) and snake fear (SNAQ) assessed at the end of the experiment (rs ⬎ .82, p ⬍ .001). Because SPQ has 18 items and the
SNAQ has 20 items, fear was expressed as percentage scores to
permit direct comparison of mean levels of spider and snake fear.
The means (SD) were 32.60% (27.93) on the SPQ and 26.89%
(24.98) on the SNAQ; thus, mean levels of fear were comparable,
t ⫽ 1.20. Mean disgust sensitivity was 15.40 (3.99) and mean trait
anxiety was 38.98 (7.86). Split-half reliabilities (odd vs. even
items) were, after Spearman-Brown correction for number of
items, r ⫽ .93 for SPQ, .91 for SNAQ, .75 for disgust sensitivity,
and .84 for trait anxiety. Results reported below remained unaffected after trait anxiety was partialed out.
Although earlier evidence indicated that the subscales of the
disgust sensitivity scale do not exhibit acceptable psychometric
properties (Björklund & Hursti, 2004), a recent study suggests the
use of three revised subscales (core, animal reminder, and
contamination-based disgust) as well as a revised global scale after
removal of seven problematic items from the original disgust
sensitivity scale (Olatunji et al., 2007). In the present study, the
original global scale correlated highly with the revised global scale
(r ⫽ .95) and also with the subscales (core, r ⫽ .83; animal
reminder, r ⫽ .77; contamination-based, r ⫽ .59). Results are
reported only for the original global disgust scale unless findings
for the revised scales deviated from those of the original score.
The top part of Table 1 shows correlations among spider fear
(SPQ), snake fear (SNAQ), and disgust sensitivity. As shown,
spider fear and snake fear were not correlated. Disgust sensitivity
did not correlate with spider fear but with snake fear.
Picture Ratings
A repeated-measures ANOVA of picture ratings showed a significant main effect of picture category, F(3, 156) ⫽ 95.22, p ⬍
.001; and subsequent t tests between the categories were also
significant, paired t(52) ⬎ 5.14, p ⬍ .001. Mean ratings decreased
Table 1
Correlations of Questionnaire Data, Picture Ratings, and SelfReported Recognition With Spider Fear, Snake Fear, and
Disgust Sensitivity
Variable
Spider fear
Snake fear
Disgust
sensitivity
Snake fear
.12
Disgust sensitivity
.09
.55ⴱⴱⴱ
a
Picture ratings
Spiders
⫺.74 (⫺.77)ⴱⴱⴱ .07
⫺.16 (⫺.32†)
Snakes
⫺.09
⫺.70 (⫺.59)ⴱⴱⴱ ⫺.50ⴱⴱⴱ (⫺.19)
Self-reported
recognitionb
Spiders
Own performance
.28ⴱ
.02
.18
Picture clarity
.25ⴱ
.13
.10
ⴱ
Picture count
.24
.06
.23
Snakes
Own performance
⫺.10
.24ⴱ
.08
Picture clarity
⫺.05
.27ⴱ
⫺.11
Picture count
.02
.05
.20
Note. Spider fear was measured with an 18-item questionnaire and snake
fear with a 20-item questionnaire (Klorman et al., 1974), and disgust
sensitivity with a 32-item scale (Haidt et al., 1994). N ⫽ 53.
a
Negative correlations indicate that higher fear or disgust sensitivity was
associated with more negative picture ratings. The partial correlations (in
parentheses) control both variables for the variables in the other two
columns. b For spider and snake fear, correlations with ratings are partial
correlations that control for ratings of the other picture category (to
eliminate overall biases in responding). For disgust sensitivity, these are
partial correlations that control for fear.
ⴱ
p ⬍ .05, one-tailed. ⴱⴱ p ⬍ .01, one-tailed. ⴱⴱⴱ p ⬍ .001, onetailed. † p ⬍ .05, two-tailed. †† p ⬍ .01, two-tailed.
significantly from flowers (M ⫽ 1.77, SD ⫽ 1.08) to mushrooms
(M ⫽ 0.53, SD ⫽ .85) to snakes (M ⫽ ⫺.65, SD ⫽ 1.32) to spiders
(M ⫽ ⫺1.96, SD ⫽ 1.32).
The middle part of Table 1 shows correlations of spider fear
(SPQ), snake fear (SNAQ), and disgust sensitivity with spider
ratings and snake ratings. The finding for disgust sensitivity extends previous findings that after spider fear was partialed out,
disgust sensitivity predicted disgust ratings to a (plastic) spider in
a behavioral avoidance test (Olatunji & Deacon, 2008). Although
disgust sensitivity correlated also with more negative snake ratings, this effect was no longer significant after snake fear was
partialed out.
Recognition Task: Self-Report
The bottom part of Table 1 shows correlations of spider fear
(SPQ), snake fear (SNAQ), and disgust sensitivity with selfreported recognition performance, picture clarity, and picture
count. As shown, spider fear correlated with reported spider recognition after potential biases in responding (i.e., reported snake
recognition) were partialed out. Spider fear correlated also with
clarity ratings of spiders after clarity ratings of snakes were partialed out. Further, spider fear correlated with reported number of
seen spiders after reported number of snakes was partialed out.
Similarly, snake fear correlated with self-reported snake recognition and clarity of snake pictures after potential biases were partialed out. In contrast, disgust sensitivity did not correlate with
MASKED THREAT
these self-report measures; all zero-order correlations and partial
correlations (after correcting for spider or snake fear) were not
significant, r ⬍ .23, p ⬎ .10.
Recognition Task: Manipulation Check of SOA
The proportion of (corrected) false alarm rates to the blanks
differed among picture categories, F(3, 156) ⫽ 7.09, p ⬍ .001.
Mean (SD) corrected false alarm rates were 23.75% (10.17) for
spiders, 22.42% (9.60) for snakes, 33.09% (15.91) for flowers, and
21.98% (12.93) for mushrooms. Paired t tests showed that the
mean false alarm rates for flowers exceeded those of the other
categories (t(52) ⬎ 2.98, p ⬍ .005) with no differences among the
other categories (t ⬍ 1). These findings suggests that overall,
participants had a tendency to misinterpret blanks as flowers.
Changes in SOA had strong effects on recognition for each
picture category. Figure 2 shows mean recognition scores (d⬘) for
spiders, snakes, flowers, and mushrooms over SOAs. In a
repeated-measures ANOVA of d⬘ with category (snake, spider,
flower, mushroom) and SOA (four levels) as within-subjects variables, there was an interaction of category with SOA, F(9, 468) ⫽
19.41, p ⬍ .001; a main effect of SOA, F(3, 156) ⫽ 825.74, p ⬍
.001; and a main effect of category, F(3, 156) ⫽ 38.66, p ⬍ .001.
Separate ANOVAs for each category showed that the main effect
of SOA was significant for each category, all F(3, 156) ⬎ 228.70,
p ⬍ .001. As shown in Figure 2, recognition at the 200-ms SOA
showed clear ceiling effects (the absolute maximum d⬘ was 2.65).
In support, Levine tests indicated that the variances over SOAs
were significantly reduced at 200-ms SOA for all picture categories, F(3, 208) ⬎ 16.42, p ⬍ .001. Similarly, the variance was
significantly reduced for flowers from the 24-ms SOA to the
815
12-ms SOA, F(1, 104) ⬎ 3.81, p ⬍ .05. Further, at the 12-ms
SOA, spider and flower recognition were at chance (t ⬍ 1).
Because of these ceiling and floor effects, subsequent correlation
analyses were limited to the middle SOAs to maximize power.
However, note that correlations with disgust sensitivity (reported
below) remained unaffected when recognition scores included the
12-ms SOA as well as the middle SOAs.
Because the interaction of SOA and picture category might have
been confounded by the floor and ceiling effects, a follow up
analysis included only the middle SOAs to determine whether a
change in masking parameters (i.e., SOA changed from 24 to 36
milliseconds) had similar effects on recognition for the four picture
categories. The repeated-measures ANOVA of d⬘ with category
(snake, spider, flower, mushroom) and SOA (24 and 36 milliseconds) as within-subjects variables showed an interaction of category with SOA, F(3, 156) ⫽ 3.35, p ⬍ .05; a main effect of SOA,
F(1, 52) ⫽ 276.69, p ⬍ .001; and a main effect of category, F(3,
156) ⫽ 61.43, p ⬍ .001. Subsequent t tests of mean recognition
across SOAs showed that all picture categories differed from each
other (t(52) ⬎ 5.12, p ⬍ .001) except spiders and flowers (t ⬍ 1).
Subsequent paired t tests of the change scores between 24-ms and
36-ms SOA suggested that recognition of snakes improved less
strongly than recognition of flowers, t(52) ⫽ 3.98, p ⬍ .001 and
mushrooms, t(52) ⫽ 1.94, p ⫽ .058.
Recognition Task: Correlations With Fear
and Disgust Sensitivity
Signal detection indexes (d⬘ and C) were correlated with spider
fear, snake fear, and disgust sensitivity to study effects of individual differences on recognition (d⬘) and response bias (C).
Figure 2. Mean (and SE) recognition scores (d⬘) for spiders, snakes, flowers, and mushrooms over stimulus
onset asynchronies (SOAs, in milliseconds). Note that the 12-ms SOA showed floor effects for spiders and
flowers, whereas the 200-ms SOA showed ceiling effects for all picture categories (absolute maximum d⬘ ⫽
2.65).
WIENS, PEIRA, GOLKAR, AND ÖHMAN
816
Recognition. As shown in Table 2, results provided no evidence that spider fear (or snake fear) correlated with recognition
(d⬘) of spiders (or snakes). Because effects might have been small
but not significant for individual SOAs, recognition was also
computed from combined SOAs of 24 and 36 milliseconds; 12 and
24 milliseconds; and 12, 24, and 36 milliseconds. For spider fear,
the largest correlation with spider d⬘ was r ⫽ .10, p ⬎ .45. For
snake fear, the largest correlation with snake d⬘ was at the combined 24-ms and 36-ms SOA, r ⫽ .21, p ⬍ .07, one-tailed.
However, after disgust sensitivity was partialed out, this correlation dropped to zero, r ⫽ .02. Further inspection of the data did not
reveal curvilinear relationships.
In contrast, disgust sensitivity correlated with spider and snake
recognition (at two-tailed significance testing) but not with recognition of mushrooms and flowers (r ⬍ .17, p ⬎ .20). Indeed, when the
data from the 24-ms and 36-ms SOAs were combined (see Table 2),
the correlations between disgust sensitivity and spider and snake
recognition remained significant (r ⬎ .34) after potential confounds
were partialed out from these variables (i.e., d⬘ for mushrooms and
flowers, spider and snake fear, spider and snake ratings, C for spiders
and snakes, trait anxiety, and age). Notably, the core disgust subscale
of the revised disgust sensitivity scale (Olatunji et al., 2007) showed
similar partial correlations with spider and snake recognition (r ⬎ .37)
Table 2
Correlations of Recognition Performance at Two Stimulus Onset
Asynchronies (24 Milliseconds and 36 Milliseconds) With Spider
Fear, Snake Fear, and Disgust Sensitivity
Variable
Recognition ability (d’)
Spiders
24-ms
36-ms
Combined (24 ⫹ 36-ms)
Snakes
24-ms
36-ms
Combined (24 ⫹ 36-ms)
Response bias (C)b
Spiders
24-ms
36-ms
Combined (24 ⫹ 36-ms)
Snakes
24-ms
36-ms
Combined (24 ⫹ 36-ms)
Spider fear
Snake fear
Disgust
sensitivity
⫺.09
.10
.01
.03
.02
.02
.41††
.14
.36†
⫺.05
⫺.08
⫺.06
.19a
.15a
.21a
.34†
.31†
.35†
⫺.15
⫺.39ⴱⴱc
⫺.29ⴱc
⫺.04
⫺.04
⫺.04
⫺.15
⫺.01
⫺.08
⫺.01
.02
⫺.01
⫺.05
⫺.04
⫺.07
⫺.06
⫺.04
⫺.06
Note. For disgust sensitivity, correlations with d⬘ control both variables
for potential confounds (i.e., d⬘ for mushrooms and flowers, spider and
snake fear, spider and snake ratings, C for spiders or snakes, trait anxiety,
and age). Correlations between disgust sensitivity and d⬘ for mushrooms
and flowers, r ⬍ .17, p ⬎ .20. N ⫽ 53.
a
These trends were eliminated after disgust sensitivity was partialled out,
r ⬍ .02. b Negative correlations indicate that higher fear or disgust
sensitivity was associated with less conservative response biases. c A
partial correlation that controlled both variables for potential confounds
(i.e., d⬘ for spiders and snakes, disgust sensitivity, snake fear, spider and
snake ratings, C for snakes, trait anxiety, and age) remained significant,
r ⫽ ⫺.28ⴱ.
ⴱ
p ⬍ .05, one-tailed. ⴱⴱ p ⬍ .01, one-tailed. ⴱⴱⴱ p ⬍ .001, onetailed. † p ⬍ .05, two-tailed. †† p ⬍ .01, two-tailed.
whereas the animal reminder and contamination-based disgust subscales did not (r ⬍ .13).
Response bias. As shown in Table 2, spider fear but not snake
fear or disgust sensitivity correlated with response biases (C) to
threat pictures. Specifically, fear of spiders was associated with
less conservative response biases (i.e., less positive C) for responding spider. This correlation remained significant (r ⫽ ⫺.28) after
potential confounds were partialed out from both variables (i.e., d⬘
for spiders and snakes, disgust sensitivity, snake fear, spider and
snake ratings, C for snakes, trait anxiety, and age). Notably, the
correlation between spider fear and spider C at the 36-ms SOA
(r ⫽ ⫺.39) was significantly larger than the corresponding correlation of r ⫽ ⫺.04 for snakes, Z ⫽ 1.90, p ⬍ .03. Inspection of the
data did not suggest that there was a curvilinear relationship
between snake fear and response biases to snakes.
Discussion
Although spider fear and snake fear correlated with selfreported threat recognition (spiders or snakes), neither fear correlated with actual threat recognition. In contrast, disgust sensitivity
correlated with recognition of spiders and snakes (but not with
recognition of flowers and mushrooms). Further, spider fear correlated with the tendency to misinterpret blanks as spiders (response bias), and this correlation (at the 36-ms SOA) exceeded the
corresponding correlation between snake fear and response biases
for snakes.
As shown in Figure 2, changes in masking parameters (SOA)
had strong effects on recognition performance. Because of floor
effects at the shortest SOA (12 milliseconds) and ceiling effects at
the longest SOA (200 milliseconds), analyses focused on the
middle SOAs (24 and 36 milliseconds). However, even for these
two intervals, there was an interaction between SOA and picture
category; this suggests that changes in masking parameters may
not have uniform effects on recognition of different picture categories (Wiens, 2006a). As further shown in Figure 2, overall
recognition differed among picture categories. Across participants,
recognition was greater for mushrooms than for snakes and greater
for snakes than spiders and flowers. Although this pattern of
recognition differences among categories appears to challenge the
idea that emotions facilitate recognition, we argue that these results
are not a valid test of this idea. The main reason is that to evaluate
the role of emotion properly, there ought to be little if any difference in perceptual features among the picture categories. Although
we tried to equate pictures on luminance, contrast, and number of
pixels, we cannot rule out that several differences in features (e.g.,
general shape of object) remained. Therefore, we suggest that
differences in recognition among categories are mainly because of
differences in these low-level features. Importantly, any effects of
these features did not confound our results because they would not
bias correlations with individual difference variables.
After the recognition task, participants were asked to rate their
own performance in recognizing each picture category relative to
the performance of the average participant. Results (in Table 1)
showed that spider fear and snake fear correlated with the belief in
one’s own superiority in recognizing threat (spiders or snakes).
This finding corresponds to the observation that spider phobics
reported seeing spiders more quickly than do other people (Mayer,
Merckelbach, & Muris, 2000).
MASKED THREAT
Further, spider fear and snake fear correlated with ratings of
picture clarity of threat. However, results (in Table 2) provided no
evidence that spider fear (or snake fear) was associated with actual
recognition of spiders (or snakes). The strongest trend for a correlation was observed between snake fear and snake recognition;
however, disgust sensitivity could account statistically for this
relationship. In fact, because the present results showed that disgust sensitivity correlated with recognition, these findings suggest
that the null findings for fear did not result from low power.
Therefore, the present null findings replicate and extend previous
evidence that fear is not associated with increased threat recognition in center view (Becker & Rinck, 2004; Öhman & Soares,
1994; Windmann & Krüger, 1998; Winton et al., 1995). However,
because this research has focused on fear as a trait variable, it is
unresolved whether there may be interactions between trait and
state effects. For example, attentional biases in social phobics vary
with state anxiety (Garner, Mogg, & Bradley, 2006). To conclude,
when taken together with meta-analytic evidence that anxious
people show attentional biases to threat (Bar-Haim et al., 2007),
our findings confirm notions that fear and anxiety are not associated with superior threat recognition but with prioritized processing of threat stimuli after their recognition (Mathews & Macleod,
1994).
The present findings further showed that whereas spider fear
and snake fear did not correlate with threat recognition, disgust
sensitivity did. This relationship was significant after potential
confounds were partialed out (i.e., d⬘ for mushrooms and flowers,
spider and snake fear, spider and snake ratings, C for spiders or
snakes, trait anxiety, and age). Further, this relationship was specific to the dimension of core disgust, which refers to direct threat
of disease and a sense of offensiveness (Olatunji et al., 2007).
Thus, aspects of animal reminder disgust (e.g., hand preserved in
a jar) or contamination-based disgust (e.g., chocolate shaped like
dog poo) appear to be irrelevant to threat recognition.
These findings extend previous findings of correlations between
disgust sensitivity and attentional bias toward disgust words in
Stroop tasks (Charash & McKay, 2002), although it is unclear why
previous research did not find a correlation between disgust sensitivity and recognition of disgust in facial expressions and body
movements (Rozin, Taylor, Ross, Bennett, & Hejmadi, 2005).
Because the present study found no evidence that threat recognition correlates with fear of spiders or snakes, individual differences
in threat recognition apparently do not mediate the relationship
between disgust sensitivity and fear of spiders or snakes (Klieger
& Siejak, 1997; Tolin et al., 1997). Although the causal nature of
the relationship between disgust and fear of spiders or snakes
remains unclear (e.g., Edwards & Salkovskis, 2006), disgust sensitivity may be a predisposition rather than a consequence of fear
(Muris, 2006). In support of this possibility, mothers’ disgust
sensitivity predicts spider fear in children (Davey, Forster, &
Mayhew, 1993), and disgust sensitivity is unaffected by behavioral
treatment of spider fear in children (de Jong, Andrea, & Muris,
1997).
Whereas there was no apparent relationship between fear and
threat recognition, there was clear evidence for a relationship
between spider fear and the tendency to misinterpret blanks as
spiders (response bias). First, spider fear correlated with the reported number of seen spiders in the recognition task (see Table 1).
Second, spider fear correlated with less conservative response
817
biases to spiders (see Table 2). This correlation was significant
after potential confounds were partialed out (i.e., d⬘ for spiders and
snakes, disgust sensitivity, snake fear, spider and snake ratings, C
for snakes, trait anxiety, and age). These results replicate and
extend previous findings (Becker & Rinck, 2004) and are consistent with findings that spider phobics report to mistake objects in
daily life for spiders (Mayer et al., 2000). Evidence suggests that
this response bias to spiders is specific to spider fear. When spider
phobics, spider enthusiasts, and nonfearful participants were
shown ambiguous (morphed) pictures of spiders and flowers, the
spider phobics showed a bias toward categorizing ambiguous
pictures as spiders whereas the spider enthusiasts did not show this
bias (Kolassa et al., 2007).
A potential concern with our findings may be that in the recognition task, participants were forced to respond spider, snake,
flower, or mushroom. Because participants could not respond that
they did not see anything, it may be argued that our task produced
response biases. However, because in masking studies, participants
often report that they do not see anything even on target trials
(Wiens & Öhman, 2007), our task maximized sensitivity in assessing both hits and false alarms. Nonetheless, it is possible that
spider-fearful participants did not see (consciously) any spiders at
all and that our results show only that they favor the spider
response button. This explanation is inconsistent with the finding
that spider fear correlated with the number of spiders that participants reported to have seen consciously in the recognition task.
Therefore, the parsimonious explanation of our findings is that
spider-fearful participants are more likely than nonfearful participants to experience blanks as spiders.
Taken together, the studies that have found a relationship between spider fear and response biases to spiders provide strong
evidence for response biases in fear. Thus, fear is associated with
a greater concern for missing a target than for responding with
false alarms. This behavior matches that of a smoke detector:
Many responses may be false alarms and thus wasteful, but the
consequences of missing a target (i.e., fire or feared object) are
considered to be greater than those of many false alarms (Haselton
& Nettle, 2006; Nesse, 2001, 2005).
However, there was no evidence for a relationship of snake fear
with reported number of seen snakes (see Table 1) or with response biases to snakes (see Table 2). It is unlikely that differences
in fear levels or fear variability (restricted range) biased results,
because fear levels and variability were comparable for spider fear
and snake fear. Also, mean recognition and response biases were
comparable for snakes at the 24-ms SOA and for spiders at the
36-ms SOA; nonetheless, only spider fear correlated with response
biases to spiders. However, participants overall rated snakes as less
negative than spiders; but, correlations between levels of fear and
ratings of feared pictures (spiders or snakes) were comparable for
spider fear and snake fear. This suggests that relative to fearless
participants, snake-fearful participants rated snakes to be as negative as spider-fearful participants rated spiders to be negative. At
the minimum, the present results suggest that the relationship
between spider fear and response biases to spiders may be stronger
than the corresponding relationship between snake fear and response biases to snakes. A possible reason for this effect may be
that, compared to spiders, snakes are rare in most industrial countries. Therefore, even if people are afraid of snakes, they may have
little reason to mistake an object for a snake.
WIENS, PEIRA, GOLKAR, AND ÖHMAN
818
Finally, we note a peculiarity in the present results. As shown in
Table 1, spider fear did not correlate with disgust sensitivity.
Because this null finding does not replicate previous findings (e.g.,
de Jong & Merckelbach, 1998), it is possible that our sample was
not entirely representative. However, the remainder of our results
replicated and extended previous results. For example, we found a
strong correlation between snake fear and disgust sensitivity.
Whereas previous research found a relationship with food-related
disgust sensitivity (Klieger & Siejak, 1997), our findings extend
this relationship to general disgust sensitivity.
To conclude, the present study suggests that spider fear and
snake fear may not be associated with threat recognition in center
view but, rather, with the tendency to misinterpret nonthreatening
cues as threatening (response bias). In contrast, disgust sensitivity
may be associated with threat recognition (spiders and snakes) but
not with response bias. Because fearful people reported threats that
were not actually there (false alarms), whereas disgust-sensitive
people actually recognized the threat, these findings imply that fear
betrays, but disgust you can trust.
References
Anderson, A. K., & Phelps, E. A. (2001). Lesions of the human amygdala
impair enhanced perception of emotionally salient events. Nature, 411,
305–309.
Bar-Haim, Y., Lamy, D., Pergamin, L., Bakermans-Kranenburg, M. J., &
van Ijendoorn, M. H. (2007). Threat-related attentional bias in anxious
and nonanxious individuals: A meta-analytic study. Psychological Bulletin, 133, 1–24.
Becker, E. S., & Rinck, M. (2004). Sensitivity and response bias in fear of
spiders. Cognition & Emotion, 18, 961–976.
Björklund, F., & Hursti, T. J. (2004). A Swedish translation and validation
of the Disgust Scale: A measure of disgust sensitivity. Scandinavian
Journal of Psychology, 45, 279 –284.
Charash, M., & McKay, D. (2002). Attention bias for disgust. Journal of
Anxiety Disorders, 16, 529 –541.
Curtis, V., & Biran, A. (2001). Dirt, disgust, and disease: Is hygiene in our
genes? Perspectives in Biology and Medicine, 44, 17–31.
Davey, G. C. L., & Bond, N. (2006). Using controlled comparisons in
disgust psychopathology research: The case of disgust, hypochondriasis
and health anxiety. Journal of Behavior Therapy and Experimental
Psychiatry, 37, 4 –15.
Davey, G. C. L., Forster, L., & Mayhew, G. (1993). Familial resemblances
in disgust sensitivity and animal phobias. Behaviour Research and
Therapy, 31, 41–50.
Dehaene, S., & Naccache, L. (2001). Towards a cognitive neuroscience of
consciousness: Basic evidence and a workspace framework. Cognition,
79, 1–37.
de Jong, P. J., Andrea, H., & Muris, P. (1997). Spider phobia in children:
Disgust and fear before and after treatment. Behaviour Research and
Therapy, 35, 559 –562.
de Jong, P. J., & Merckelbach, H. (1998). Blood-injection-injury phobia
and fear of spiders: Domain specific individual differences in disgust
sensitivity. Personality and Individual Differences, 24, 153–158.
de Jong, P. J., Peters, M., & Vanderhallen, I. (2002). Disgust and disgust
sensitivity in spider phobia: Facial EMG in response to spider and oral
disgust imagery. Journal of Anxiety Disorders, 16, 477– 493.
Edwards, S., & Salkovskis, P. M. (2006). An experimental demonstration
that fear, but not disgust, is associated with return of fear in phobias.
Journal of Anxiety Disorders, 20, 58 –71.
Garner, M., Mogg, K., & Bradley, B. P. (2006). Orienting and maintenance
of gaze to facial expressions in social anxiety. Journal of Abnormal
Psychology, 115, 760 –770.
Haidt, J., McCauley, C., & Rozin, P. (1994). Individual differences in
sensitivity to disgust: A scale sampling 7 domains of disgust elicitors.
Personality and Individual Differences, 16, 701–713.
Haselton, M. G., & Nettle, D. (2006). The paranoid optimist: An integrative evolutionary model of cognitive biases. Personality and Social
Psychology Review, 10, 47– 66.
Klieger, D. M., & Siejak, K. K. (1997). Disgust as the source of false
positive effects in the measurement of ophidiophobia. Journal of Psychology, 131, 371–382.
Klorman, R., Weerts, T. C., Hastings, J. E., Melamed, B. G., & Lang, P. J.
(1974). Psychometric description of some specific-fear questionnaires.
Behavior Therapy, 5, 401– 409.
Kolassa, I. T., Buchmann, A., Lauche, R., Kolassa, S., Partchev, I., Miltner,
W. H. R., et al. (2007). Spider phobics more easily see a spider in
morphed schematic pictures. Behavioral and Brain Functions, 3(59).
LeDoux, J. E. (2000). Emotion circuits in the brain. Annual Review of
Neuroscience, 23, 155–184.
Macmillan, N. A., & Creelman, C. D. (2005). Detection theory: A user’s
guide (2nd ed.). Mahway, NJ: Laurence Erlbaum Associates.
Marzillier, S. L., & Davey, G. C. L. (2005). Anxiety and disgust: Evidence
for a unidirectional relationship. Cognition & Emotion, 19, 729 –750.
Matchett, G., & Davey, G. C. L. (1991). A test of a disease-avoidance
model of animal phobias. Behaviour Research and Therapy, 29, 91–94.
Mathews, A., & Macleod, C. (1994). Cognitive approaches to emotion and
emotional disorders. Annual Review of Psychology, 45, 25–50.
Mayer, B., Merckelbach, H., & Muris, P. (2000). Self-reported automaticity and irrationality in spider phobia. Psychological Reports, 87, 395–
405.
Merckelbach, H., de Jong, P. J., Arntz, A., & Schouten, E. (1993). The role
of evaluative learning and disgust sensitivity in the etiology and treatment of spider phobia. Advances in Behaviour Research and Therapy,
15, 243–255.
Mulkens, S. A. N., de Jong, P. J., & Merckelbach, H. (1996). Disgust and
spider phobia. Journal of Abnormal Psychology, 105, 464 – 468.
Muris, P. (2006). The pathogenesis of childhood anxiety disorders: Considerations from a developmental psychopathology perspective. International Journal of Behavioral Development, 30, 5–11.
Nesse, R. M. (2001). The smoke detector principle: Natural selection and
the regulation of defensive responses. Annals of the New York Academy
of Sciences, 935, 75– 85.
Nesse, R. M. (2005). Natural selection and the regulation of defenses: A
signal detection analysis of the smoke detector principle. Evolution and
Human Behavior, 26, 88 –105.
Öhman, A. (1986). Face the beast and fear the face: Animal and social fears
as prototypes for evolutionary analyses of emotion. Psychophysiology,
23, 123–145.
Öhman, A., & Mineka, S. (2001). Fears, phobias, and preparedness:
Toward an evolved module of fear and fear learning. Psychological
Review, 108, 483–522.
Öhman, A., & Soares, J. J. F. (1994). Unconscious anxiety: Phobic responses to masked stimuli. Journal of Abnormal Psychology, 103, 231–
240.
Olatunji, B. O. (2006). Evaluative learning and emotional responding to
fearful and disgusting stimuli in spider phobia. Journal of Anxiety
Disorders, 20, 858 – 876.
Olatunji, B. O., & Deacon, B. J. (2008). Specificity of disgust sensitivity in
the prediction of fear and disgust responding to a brief spider exposure.
Journal of Anxiety Disorders, 22, 328 –336.
Olatunji, B. O., Williams, N. L., Tolin, D. F., Abramowitz, J. S., Sawchuk,
C. N., Lohr, J. M., et al. (2007). The disgust scale: Item analysis, factor
structure, and suggestions for refinement. Psychological Assessment, 19,
281–297.
Osswald, S., & Reinecker, H. (2004). The associations of disgust and
MASKED THREAT
disgust sensitivity with spider phobia and blood-injection-injury phobia.
Verhaltenstherapie, 14, 23–33.
Rinck, M., Bundschuh, S., Engler, S., Muller, A., Wissmann, J., Ellwart,
T., et al. (2002). Reliability and validity of German versions of three
instruments measuring fear of spiders. Diagnostica, 48, 141–149.
Rozin, P., Haidt, J., McCauley, C., Dunlop, L., & Ashmore, M. (1999).
Individual differences in disgust sensitivity: Comparisons and evaluations of paper-and-pencil versus behavioral measures. Journal of Research in Personality, 33, 330 –351.
Rozin, P., Taylor, C., Ross, L., Bennett, G., & Hejmadi, A. (2005). General
and specific abilities to recognise negative emotions, especially disgust,
as portrayed in the face and the body. Cognition & Emotion, 19,
397– 412.
Sawchuk, C. N., Lohr, J. M., Tolin, D. F., Lee, T. C., & Kleinknecht, R. A.
(2000). Disgust sensitivity and contamination fears in spider and bloodinjection-injury phobias. Behaviour Research and Therapy, 38, 753–
762.
Sawchuk, C. N., Lohr, J. M., Westendorf, D. H., Meunier, S. A., & Tolin,
D. F. (2002). Emotional responding to fearful and disgusting stimuli in
specific phobics. Behaviour Research and Therapy, 40, 1031–1046.
Shevrin, H., & Dickman, S. (1980). The psychological unconscious: A
necessary assumption for all psychological theory. American Psychologist, 35, 421– 434.
Snodgrass, J. G., & Corwin, J. (1988). Pragmatics of measuring recognition
memory: Applications to dementia and amnesia. Journal of Experimental Psychology: General, 117, 34 –50.
Spielberger, C. D. (1983). Manual for the state-trait anxiety inventory. Palo
Alto, CA: Consulting Psychologists.
Thorpe, S. J., & Salkovskis, P. M. (1998). Studies on the role of disgust in
the acquisition and maintenance of specific phobias. Behaviour Research and Therapy, 36, 877– 893.
819
Tolin, D. F., Lohr, J. M., Sawchuk, C. N., & Lee, T. C. (1997). Disgust and
disgust sensitivity in blood-injection-injury and spider phobia. Behaviour Research and Therapy, 35, 949 –953.
Vernon, L. L., & Berenbaum, H. (2002). Disgust and fear in response to
spiders. Cognition & Emotion, 16, 809 – 830.
Wiens, S. (2006a). Current concerns in visual masking. Emotion, 6, 675–
680.
Wiens, S. (2006b). Subliminal emotion perception in brain imaging: Findings, issues, and recommendations. Progress in Brain Research, 156,
105–121.
Wiens, S. (2007). Concepts of visual consciousness and their measurement.
Advances in Cognitive Psychology, 3, 349 –359.
Wiens, S., Fransson, P., Dietrich, T., Lohmann, P., Ingvar, M., & Öhman,
A. (2004). Keeping it short: A comparison of methods for brief picture
presentation. Psychological Science, 15, 282–285.
Wiens, S., & Öhman, A. (2007). Probing unconscious emotional processes:
On becoming a successful masketeer. In J. A. Coan & J. J. B. Allen
(Eds.), The handbook of emotion elicitation and assessment (pp. 65–90):
Oxford University Press.
Windmann, S., & Krüger, T. (1998). Subconscious detection of threat as
reflected by an enhanced response bias. Consciousness and Cognition, 7,
603– 633.
Winton, E. C., Clark, D. M., & Edelmann, R. J. (1995). Social anxiety, fear
of negative evaluation and the detection of negative emotion in others.
Behaviour Research and Therapy, 33, 193–196.
Received September 12, 2007
Revision received July 12, 2008
Accepted July 25, 2008 䡲