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Abstract

Aesthetic appeal of a visual image can influence performance in time-critical tasks, even if it is irrelevant to the task. This series of experiments examined whether aesthetic appeal can act as an object attribute that guides visual search. If appeal enhances the salience of the targets pre-attentively, then appealing icons would lead to more efficient searches than unappealing targets and, conversely, appeal of distractors would reduce search efficiency. Three experiments (N = 112) examined how aesthetic appeal influences performance in a classic visual search task. In each experiment, participants completed 320 visual search trials, with icons varying in rated aesthetic appeal and either visual complexity (Experiments 1 and 2) of concreteness (Experiment 3) among two, four, eight, or 11 distractor icons. While target appeal did not influence search efficiency it sped up search times in all three experiments: appealing targets led to faster response time (RT) than unappealing targets across all experiments, and compared to neutral distractors, appealing distractors slowed search RT down. These findings are the first to show that an object's aesthetic appeal influences visual search performance.
Aesthetic appeal influences visual search performance
Irene Reppa
1
&Siné McDougall
2
Accepted: 2 September 2022
#The Author(s) 2022
Abstract
Aesthetic appeal of a visual image can influence performance in time-critical tasks, even ifit is irrelevantto the task. This series of
experiments examined whether aesthetic appeal can act as an object attribute that guides visual search. If appeal enhances the
salience of the targets pre-attentively, then appealing icons would lead to more efficient searches than unappealing targets and,
conversely, appeal of distractors would reduce search efficiency. Three experiments (N= 112) examined how aesthetic appeal
influences performance in a classic visual search task. In each experiment, participants completed 320 visual search trials, with
icons varying in rated aesthetic appeal and either visual complexity (Experiments 1and 2) of concreteness (Experiment 3)among
two, four, eight, or 11 distractor icons. While target appeal did not influence search efficiency it sped up search times in all three
experiments: appealing targets led to faster response time (RT) than unappealing targets across all experiments, and compared to
neutral distractors, appealing distractors slowed search RT down. These findings are the first to show that an objectsaesthetic
appeal influences visual search performance.
Keywords Visual search .Aesthetic appeal .Visual complexity .Concreteness
Introduction
The term aesthetic appeal,orjustappeal, refers to mild aes-
thetic experiences and is revealed by simple rating judgements
made on the basis of liking (see Reber et al., 2004, for review).
Aesthetics can influence our behaviour across a range of ev-
eryday life activities. We go to art galleries, fill our homes
with things we like, and purchase products not only based
on functionality but based on how much joy we get from
interacting with them.
Aesthetic appeal influences not only our everyday behav-
iour but also our performance with the objects around us.
This is not entirely surprising, because as a visual attribute
of the world around us appeal is perceived extremely quickly
within 50 ms (e.g., Lindgaard et al., 2006)rendering it a
good candidate to influence time-critical performance.
However, only a handful of studies using a variety of tasks
have examined whether visual aesthetic appeal might influ-
ence performance and findings have been mixed (see
Thielsch, Scharfen, et al., 2019b, for a recent review and
meta-analysis). Some studies have found no effect of stimulus
appeal on task performance (e.g., Hartmann et al., 2007;
Sonderegger et al., 2012; Thüring & Mahlke, 2007;
Tractinsky et al., 2000). Other studies have found positive
effects of appeal on performance suggesting that appealing
stimuli can increase performance efficiency (e.g., Moshagen
et al., 2009; Reppa et al., 2021; Reppa & McDougall, 2015;
Sonderegger & Sauer, 2010). In contrast, decreased perfor-
mance efficiency for appealing stimuli has sometimes been
reported (e.g., Ben-Bassat et al., 2006; Meyer et al., 1997;
Sauer & Sonderegger, 2009,2011;Tufte,1983).
The current study used a classic visual search task to deter-
mine whether appeal is a visual attribute that can guide the
deployment of attention: of particular interest was whether
any performance boost due to appeal affected search efficiency
or search times. Use of classic visual search tasks allow calcu-
lation of search slopes based on the linear relationship between
search time and set size. Search slopes are commonly used to
determine whether stimulus dimensions such as aesthetic
appeal can be attributes that efficiently guide the deployment
of attention (e.g., see Wolfe & Horowitz, 2004,2017, for
reviews). In general, a stimulus attribute can be classed as at-
tention-guiding, when it is independent of set size and its search
slope is flat at near zero. Such flat slopes are typically called
very efficient, while slopes of between 5 and 10 ms are called
quite efficient, and slopes of over 10 ms inefficient.
*Irene Reppa
i.reppa@swansea.ac.uk
1
School of Psychology, Swansea University, Swansea SA2 8PP, UK
2
Department of Psychology, Bournemouth University,
Bournemouth, UK
Attention, Perception, & Psychophysics
https://doi.org/10.3758/s13414-022-02567-3
Research to date suggests that stimulus attributes rarely
produce near zero search slopes although attributes that are
threatening or evolutionarily relevant are notable exceptions
(Becker et al., 2011; Eastwood et al., 2001; Fox et al., 2001;
Öhman et al., 2001). Many stimulus dimensions, however,
lead to more or less efficient searches without necessarily
producing pop-outeffects (Golan et al., 2014;Hershler&
Hochstein, 2005; see also Frischen et al., 2008 for a review).
Alternatively, a stimulus attribute may simply speed up or
slow down search times without affecting search efficiency,
i.e., there is no effect on the search slope but overall response
times (RTs) during search are changed (Della Libera &
Chelazzi, 2009;Lee&Shomstein,2014).
In the present investigation we examined the effect of aes-
thetic appeal on visual search performance. However, stimu-
lus characteristics known to influence performance are highly
correlated with appeal and are known to have a significant
effect on performance. Perceptions of aesthetic appeal are
strongly influenced by several stimulus dimensions (e.g., col-
our: Bonnardel et al., 2011; Palmer et al., 2013; concreteness:
Kawabata & Zeki, 2004; familiarity: Reber et al., 2004; Reppa
& McDougall, 2015; symmetry and harmony: Palmer &
Griscom, 2013; visual complexity: Eisenman, 1967;Reppa
et al., 2021). Similar stimulus dimensions including visual
complexity, concreteness, and familiarity are also known to
influence performance in search and localisation tasks (e.g.,
Byrne, 1993; Isherwood et al., 2007; Jacobsen & Höfel, 2002;
Kawabata & Zeki, 2004; McDougall et al., 2000;McDougall
&Reppa,2008; Vartanian & Goel, 2004).
In order to conduct this research in a well-controlled man-
ner, we needed a micro-world of well-defined and controlled
stimuli that allow examination of the aesthetic appeal-
performance relationship, while carefully controlling for con-
founding variables. Icons are such a micro-world, not least
because their characteristics are well documented both regard-
ing their relationship with ratings of appeal and regarding task
performance (e.g., McDougall et al., 1999; McDougall et al.,
2000; McDougall & Reppa, 2008). McDougall and Reppa
(2008) found that three icon characteristics in particular, fa-
miliarity, concreteness, and visual complexity, accounted for a
significant amount of the variance in aesthetic appeal ratings.
In sum, visual complexity, concreteness, and familiarity
contribute to (e.g., Jacobsen & Höfel, 2002; Kawabata &
Zeki, 2004; Martindale et al., 1988; Vartanian & Goel,
2004; Zajonc, 1968,2000), while also being strongly corre-
lated with (e.g., McDougall & Reppa, 2008), ratings of aes-
thetic appeal while at the same time having been shown to
affect performance (e.g., Byrne, 1993; Green & Barnard,
1990; Isherwood et al., 2007; McDougall et al., 2000;
McDougalletal.,2006; McDougall & Isherwood, 2009;
Rogers & Oborne, 1987; Scott, 1993; Stotts, 1998).
Therefore, although icons (especially those used in the current
investigation) may not elicit the kind of strong emotive
response one may associate with a strong aesthetic experience,
they are known to elicit reliable appeal and emotional re-
sponses (e.g., McDougall & Reppa, 2008; Prada et al.,
2016). Moreover, they offer an ideal stimulus set to systema-
tically examine the effect of aesthetics on performance,
allowing control of stimulus factors, to ensure that any effects
of appeal do not actually reflect effects ofconfounding factors
contributing to appeal and performance.
In Experiments 1and 2icon appeal and visual complexity
were varied orthogonally while holding icon concreteness and
familiarity constant. This made it possible to examine the rela-
tive effects of appeal and complexity on search without being
affected by other icon attributes likely to affect search. In
Experiment 1we examined the effect of appeal and visual com-
plexity on search times and search slopes to examine if appeal
has an independent effect on the speed of search (search RT) and
on search efficiency (search RT slopes). Appeal was defined
both by using pre-existing normative appeal ratings for the icons
employed in the task (McDougall & Reppa, 2008)aswellas
individual participantsown subjective ratings of appeal. This
allowed us to examine whether independently and subjectively
defined appeal yields similar influence on search performance.
Experiment 2extended Experiment 1to examine the effect of
appealing distractors on search performance. Experiment 3fo-
cused on icon appeal and concreteness, and appeal and familiar-
ity varying these icon attributes orthogonally, while holding icon
complexity constant.
Previous work has suggested that appealing stimuli may be
inherently rewarding (e.g., Kirk et al., 2009; Reppa et al.,
2021). Furthermore, there is evidence to show increased effi-
ciency for stimuli we personally like and thus find more re-
warding (e.g., Della Libera & Chelazzi, 2009;Lee&
Shomstein, 2014). Therefore, appeal may increase
motivation, which in turn can speed up search performance
and increase performance efficiency, especially for those
icons that are subjectively appealing. If appealing stimuli act
as other rewarding stimuli, like food or money, then they may
be processed faster than their unappealing counterparts.
Experiment 1: The effect of target complexity
and target appeal on visual search
Experiment 1examined the effect of aesthetic appeal of target
icons on visual search performance. Distractors were chosen
that were rated as neutral in terms of appeal (see Table 1).
Targets varied orthogonally in terms of previously rated aes-
thetic appeal (based on the ratings obtained in McDougall &
Reppa, 2008) as well as rated visual complexity, while keep-
ing concreteness and familiarity constant (based on ratings
obtained in McDougall et al., 1999). Based on previous evi-
dence (e.g., Krasich et al., 2019;Reppa&McDougall,2015;
Sonderegger & Sauer, 2009) it was hypothesized that
Attention, Perception, & Psychophysics
aesthetically appealing icons would have significant influence
on task performance, reducing response times, compared to
unappealing ones. Importantly, the use of a classic visual
search task made it possible to examine whether appeal of a
target stimulus is pre-attentively processed and guides atten-
tion more efficiently around the display. If appeal acts as an
attention-guiding attribute, then appealing targets would lead
to more efficient searches the search slopes for appealing
targets would be shallower than the slopes for unappealing
targets.
Prior to the visual search task, participants provided ratings
of appeal for all the target icons that were later used as targets
in a visual search task. Obtaining appeal ratings from partici-
pants of the target icons allowed us to examine whether any
effect of appeal on performance would be stronger for targets
defined by appeal ratings obtained from the participants them-
selves rather than ratings provided prior to the experiment by
others, as is normally the case.
Previous research on attentional capture a task where the
nature of distractors is manipulated to examine its effect on
performance with target stimuli has shown thatattention can
be captured by distractors that are appealing to the participants
themselves (e.g., favourite team logos), but not by distractors
that are neutral to the participant (other team logos; e.g., Biggs
et al., 2012; Krasich et al., 2019). Therefore, it may be the case
that any effect of appeal on performance is stronger when
participants are looking for targets that they themselves have
rated as appealing, compared to those that they rated as neutral
or unappealing.
Method
Participants
Forty undergraduate and postgraduate Swansea University
students, 34 females and eight males, took part in the study
in exchange for participant pool credits. The usual sample size
for visual search experiments manipulating variables within-
participants is between ten and 25 participants. For current
study G*Power (3.1) analysis suggested a minimum of 18 to
obtain a medium effect size (.06) for the key Appeal and Set
Size interaction. Here we recruited a little over double the
required participants ensuring a sufficient number of subjec-
tive icon ratings. Specifically, as participants would be asked
to rate icons in terms of attractiveness, we needed to avoid
missing values for some categories for some participants.
Participant ages ranged from 19 to 35 years (M=22.95,SD
= 3.81). Recruitment primarily took place via the Psychology
Departments participant pool, with additional students
sourced via posters across the Universityscampus.Thestudy
was approved by the College of Human & Health Sciences,
Swansea University, Research Ethics Committee.
Table 1 Materials employed in Experiment 1and Experiments 2a and 2b
(A) Mean Likert-scale ratings (and standard deviations) for Targets and Neutral Distractors (used in Experiments 1and 2a) and Appealing Distractors (used in Experiment 2b)
Icon
characteris-
tics
Appealing Complex AC
(N=10)
Appealing Simple AS (N=10) Unappealing Complex
UC (N=10)
Unappealing Simple US (N=10) Neutral Distractors ND
(N=72)
Appealing Distractors AD (N=72)
Appeal 3.50 (0.88) 3.50 (0.53) 2.45 (0.15) 2.61 (0.10) 3.00 (0.40) 3.45 (0.27)
Complexity 3.49 (0.15) 1.68 (0.80) 3.69 (0.26) 1.82 (0.23) 2.55 (0.77) 2.46 (0.73)
Concreteness 3.85 (1.11) 3.61 (0.88) 3.26 (0.90) 2.27 (0.84) 3.18 (0.89) 3.58 (0.96)
Familiarity 3.19 (0.62) 3.59 (0.94) 2.70 (0.87) 2.96 (0.85) 2.87 (0.90) 3.26 (0.87)
(B) Results of one-way analyses of variance and Newman-Keuls Comparisons examining differences between 1-5 Likert scale ratings for (a) target icon types (b) target icons and neutral distractors (c) target icons and
appealing distractors. The symbols >and <mean higher and lower ratings respectively, while the =symbolmeansnodifferenceintherateddimension
(a) Comparisons between target icon types (b) Comparisons between target icon types and neutral distractors (c) Comparisons between target icon types and appealing distractors
Icon
characteris-
tics
ANOVA result Newman-Keuls comparisons of
each icon type
ANOVA result Newman-Keuls comparisons of icon types
with distractors
ANOVA result Newman-Keuls comparisons of icon types
with distractors
Appeal F(3,36)=40.03, p<.001 AC=AS>UC=US F(4,107)=18.83, p<.001 AC=AS>ND
UC=US<ND
F(4,107)=45.30,
p<.001
AC=AS=AD
UC=US<AD
Complexity F(3,36)=48.48, p<.001 AC=UC>AS=US F(4, 107)=19.54, p<.001 AC=UC>ND
AS=US<ND
F(4,107)=22.68,
p<.001
AC=UC>AD
AS=US<AD
Concreteness F<1, p>.05 p<.001 AC=AS=UC=US F(4, 107)=1.26, p=.29 AC=AS=UC=US=ND F(4,107)=0.76, p=.55 AC=AS=UC=US=AD
Familiarity F(3,36)=2.17, p>.05 AC=AS=UC=US F(4, 107)=1.89, p=.12 AC=AS=UC=US=ND F(4,107)=2.18, p=.08 AC=AS=UC=US=AD
Attention, Perception, & Psychophysics
Apparatus and materials
In the search task, 40 target icons and 72 distractor icons were
chosen from the icon corpus in McDougall et al. (1999). Stimuli
were all black and appeared against white background. They
were viewed from approximately 60 cm (no headrest was used
but we ensured participants were sitting so that their eyes were at
a distance of 60 from the monitor). From that distance, all icons
measured approximately 2
o
×2
o
of visual angle. The place-
holders the icons appeared within, were squares measuring 4
o
×4
o
with a border of 3 pixels, and a distance of 2
o
between them.
The ratings of visual complexity and visual aesthetic appeal
were used to vary the target icons orthogonally. Four icon
types were created: appealing complex, appealing simple, un-
appealing complex, and unappealing simple (Fig. 1). Ratings
of visual complexity, concreteness, and familiarity were
obtained from McDougall et al. (1999) and ratings of appeal
were obtained by McDougall and Reppa (2008). Table 1
shows the findings from univariate ANOVAs examining
differences between icon types: icons differed significantly
in terms of their rated visual complexity and appeal but did
not differ in terms of concreteness and familiarity.
Seventy-two icons from the original icon corpus were used
as distractors, whose characteristics (visual complexity, con-
creteness, familiarity, and appeal) appear in Table 1a.
Distractors were chosen to be neutral in terms of rated appeal.
Comparisons between target and distractor icons in terms of
appeal, visual complexity, concreteness, and familiarity ap-
pear in Table 1b. To obtain individual, rather than normative,
ratings participants were asked to rate 60 icons (40 icons that
were targets in the visual search task and 20 filler icons). The
20 filler icons were from the original icon set in McDougall
et al. (1999) and were chosen so that they were neutral in
terms of appeal (based on ratings obtained by McDougall &
Reppa, 2008). Table 2shows the appeal ratings given by the
participants to the icons previously identified as appealing,
unappealing and neutral (here used as filler trials in the rating
task) and based on McDougall and Reppas(2008)findings.
Example target icons in Experiments 1 and Experiment 2
Complex
appealing
Complex
unappealing
Simple
appealing
Simple
unappealing
Example distractor icons in Experiment 2
Appealing distractors Neutral appeal distractors
Example target icons in Experiment 3
Abstract
appealing
Abstract
unappealing
Concrete
appealing
Concrete
unappealing
Fig. 1 Examples of target and distractor icons used in the current experiments
Attention, Perception, & Psychophysics
Design
The visual search task was based on a 2 (Target Presence: present
vs. absent) × 4 (Set Size: 3, 6, 9, 12) × 2 (Complexity: complex
vs. simple) × 2 (Appeal: appealing vs. unappealing) repeated-
measures design yielding 32 experimental conditions. There
were ten trials per condition trials per condition, yielding 320
trials per participant. The dependent measure was RT.
Procedure
Participants were tested individually in a quiet well-lit labora-
tory. Participants first completed the rating task followed by a
computer-based visual search task. For the rating task, each
participant was presented with a booklet of 60 icons which
included instructions and examples. Participants rated each
icon by circling a Likert scale response from 1 (Really
Dislike) to 5 (Really Like). The booklets started on different
pages for each participant to avoid any potential order effects.
Following the ratings task participants carried out the visual
search task. Trial presentation and recording of responses was
controlled via PsyScope (Cohen et al., 1993) run on a Mac
OS11, connected to a 19-in. Samsung flat-screen monitor. An
example trial is illustrated in Fig. 2. In each trial, the target icon
was presented in the top left of the screen for 2 s. Following target
offset, an array of three, six, nine or 12 icons appeared on the right
part of the screen within a 3 × 4 grid. The array remained visible
until the participant responded. Half of the participants indicated
whether the target was present among those icons by pressing the
key Mor absent by pressing the key Z. The assignment of keys
was reversed for the remaining half of the participants.
Participants were prompted to respond as fast and accurately as
possible, and told that the target would be present 50% of the time.
Incorrect responses (e.g., stating that a target icon was present in
the array when it was not, and vice versa) were followed by a 500-
ms beep sound. Target and distractor icons were presented ran-
domly in each of the 12 possible locations. Presentation of each of
the 32 conditions was fully randomised across a 45-min experi-
ment with three chances to take a break at approximately equal
intervals. Each icon was presented once as a target, and eight
times as a distractor. None of the 20 filler icons from the partici-
pantsrating booklet appeared in the visual search task.
Data analysis
For all experiments reported here, separate analyses were carried
out on target-present and target-absent search data. The dependent
measures examined were correct mean RT in milliseconds, and
search slopes. In all experiments, RT that was 3 standard devia-
tions above or below the mean per participant per condition was
removed from the data and not analysed further. Those removals
accounted for no more than 1.6% of the data in any of the exper-
iments. Search slopes of correct RT × Set Size are the most
commonlyusedindexoftheefficiency of the search. Search
slopes give an estimate of the cost of adding an item to the visual
display (Wolfe, 2001). Partial eta-squared (ηp
2
) was reported for
all significant effects (Cohen, 1973), to indicate the proportion of
the variance in response times and slopes attributable to each
variable separately. Finally, Cohensdwas reported for all
pairwise comparisons investigating significant interactions.
Results
In the rating task, the majority (38 out of the 40) of participants
used the full scale of appeal ratings. No participants used fewer
than 3 points on the Likert scale. Appeal ratings per icon type are
showninTable2. Overall, icons deemed appealing using the
McDougall and Reppa (2008) norms were more likely to be
rated as appealing than neutral or unappealing and, similarly,
unappealing icons were more likely to be rated as unappealing
than appealing or neutral.
For the visual search task, errors (4.29%) were removed
from the data and analysed separately. Correct responses that
were ±3 SDs from the mean per participant per condition
(1.5% of correct trials) were classed as outliers, removed from
the data, and not analysed further.
RT analyses using independent appeal ratings
In this set of analyses, appealing and unappealing icons were
determined based on ratings provided by participants in
McDougall and Reppa (2008). Separate analyses were carried
out for target present and target-absent RT. Correct mean RT
per condition is shown in Fig. 3.Table3presents a summary
of the findings from the statistical analyses reported below.
Table 2 Experiment 1: Previously obtained mean normative ratings (and standard deviations) and participantsown ratings of appealing, unappealing
and neutral filler icons
Normative ratings
McDougall and Reppa (2008)
Participantsown ratings
Appealing 3.50 (0.37) 3.41 (1.12)
Unappealing 2.53 (0.15) 2.54 (0.97)
Neutral filler items 3.18 (0.03) 3.20 (1.04)
Note. The filler icons were only included in the ratings booklet and were selected to be of medium levels of appeal
Attention, Perception, & Psychophysics
Target-present RT
A 4 (Set Size: 3, 6, 9, 12) × 2 (Complexity: complex versus
simple) × 2 (Appeal: appealing vs. unappealing) repeated-
measures ANOVA, with appeal determined based on the rat-
ings obtained by McDougall and Reppa (2008), was carried
out on correct RT.
The main effect of Set Size was significant with RT increas-
ing as set size increased. The main effects of Complexity and of
Appeal were also significant. There was also a significant
Complexity × Appeal interaction: pairwise comparisons con-
firmed that search RT was faster for complex appealing com-
pared to complex unappealing icons, t(39) = 5.10, p< .001, d=
.81.Thesamedifferencewasobservedbetweensimpleappeal-
ing and unappealing icons, but the effect size was smaller, t(39)
=3.87,p= .003, d= .61. The Set Size × Complexity interaction
was also significant with shallower slopes for simple compared
to complex icons (see target-present slopes analysis below).
There were no other significant interactions.
Target-present slopes
The RT by set size slopes for target-present trials were sub-
mitted to a 2 (Complexity: complex vs. simple) × (Appeal:
appealing vs. unappealing) repeated-measures ANOVA.
There was only a significant main effect of Complexity with
steeper slopes for complex (18 ms/item) compared to simple
icons (14 ms/item). The main effect of Appeal was not signif-
icant and neither was the Complexity × Appeal interaction.
Overall, icon appeal interacted with visual complexity to
boost search times when the target was present in the array
search RT was faster when targets were appealing compared
to unappealing icons with this difference being larger for un-
appealing complex icons. In contrast, search efficiency was
influenced by complexity only, with shallower slopes for vi-
sually simple compared to visually complex icons.
Target-absent RT
A repeated-measures ANOVA for target-absent RT showed a
significant main effect of Set Size with increasing RT as the
number of distractors increased. The main effects of
Complexity and Appeal were significant as was Complexity
× Appeal interaction. Pairwise comparisons to examine the
interaction, showed that target-absent RT was overall faster
when looking for complex appealing compared to unappeal-
ing targets, t(39) = 4.73, p<.001,d= .75, while there was no
difference in search RT between simple appealing and simple
unappealing target, t(39) = .29, p=.78,d=.05.
There was also a significant interaction between Set Size
and Complexity, F(3, 117) = 7.75, p< .001, ηp
2
=.17,
reflecting steeper RT slopes for complex compared to simple
targets (see target-absent slopes analyses below). The Set Size
× Appeal interaction was not significant but the significant
three-way interaction was significant.Thethree-way
Target (2 seconds)
Search array until
response (Yes or No).
Fig. 2 Example of a target present experimental trial with a search array of 12 items. The target appeared aloneon the top left of the screenfor 2 s. After 2
s, the target disappeared and the array of icons (3, 6, 9 or 12) appeared until response
Attention, Perception, & Psychophysics
interaction was driven by the interaction between Complexity
and Appeal on search slopes (see slopes analysis below).
Target-absent slopes
Search slopes for target-absent trials were submitted to a 2
(Complexity: complex vs. simple) × (Appeal: appealing vs.
unappealing) ANOVA and reveal a significant main effect of
Complexity but not Appeal. The Complexity × Appeal inter-
action was significant: pairwise comparisons confirmed that
search slopes when looking for complex targets were shallow-
er when they were appealing (53 ms/item) compared to when
they were unappealing (64 ms/item), t(39) = 2.60, p<.001,d
= .41, with no significant difference between simple appealing
and simple unappealing slopes (50 and 43 ms/item respective-
ly), t(39) = 1.95, p=.07,d=.25.
Overall, for target-absent trials appeal interacted with visu-
al complexity to influence overall search RT: search was ter-
minated later for unappealing compared to appealing targets,
with this difference being larger for complex compared to
simple target icons. Search efficiency was also determined
by the interaction between visual complexity and appeal, with
shallower search slopes when searching for appealing targets,
especially when they were complex.
RT analyses using participantsown appeal ratings
Appeal was coded separately for each participant depending
on their own ratings of the target icons. That means that an
icon rated as high in appeal for one participant may have been
rated as neutral or unappealing by another. As before separate
analyses were carried out for target-present and target-absent
trials. The results of these analyses are shown in Table 3.
Target-present RT
A 4 (Set Size: 3, 6, 9, 12) × 2 (Complexity: complex versus
simple) × 3 (Appeal: appealing, neutral, unappealing)
(A) Target Present
(B) Target Absent
Fig. 3 Mean correct response time (RT) per condition for target-present trials (a) and target-absent (b) trials in Experiment 1. Means appear separately
for target icons that were independently or subjectively appealing (see text for details). The search slope for each icon type appears in parentheses
Attention, Perception, & Psychophysics
repeated-measures ANOVA, with appeal determined based
on each participants subjective appeal ratings, was carried
out on correct RT. The main effect of Set Size was significant
with reaction times increasing as set size increased. The main
effects of Complexity and Appeal were significant but, this
time, the Complexity × Appeal interaction was not significant.
The Set Size × Complexity interaction was significant reveal-
ing shallower slopes for simple compared to complex icons
(see target-present slopes analysis below). There were no oth-
er significant interactions.
Target-present slopes
The RT by set size slopes for target-present trials were sub-
mitted to a 2 (Complexity: complex vs. simple) × (Appeal:
appealing vs. unappealing) repeated-measures ANOVA.
There was only a significant main effect of Complexity with
steeper slopes for complex (18 ms/item) compared to simple
icons (9 ms/item). The main effect of Appeal was not signif-
icant and neither was the Complexity × Appeal interaction.
Overall, both icon appeal and visual complexity indepen-
dently boosted search times when the target was present in the
array search RT was faster when targets were appealing
compared to when unappealing, and faster when they were
simple compared to visually complex. In contrast to the pat-
tern of results when appeal was based on pre-existing ratings,
when appeal was determined subjectively, there was no longer
an interaction between appeal and complexity.
Search efficiency was only influenced by complexity, with
shallower slopes for visually simple compared to visually
complex icons. Nevertheless, the slopes for simple appealing
and simple neutral icons were less than 10 ms per item which
is in the quite efficientsearch range.
Target-absent RT
A repeated-measures ANOVA for target-absent RT showed a
significant main effect of Set Size, with increasing RT as the
number of distractors increased, as well as Complexity and
Appeal. The Complexity × Appeal interaction was not
Table 3 Experiment 1: Summary of findings from analyses with appeal scores based on McDougall and Reppas(2008) ratings and on participants
own ratings. Effect sizes are only provided for significant effects
McDougall and Reppa (2008) normative ratings of appeal Participantsown ratings of appeal
Target present df F p ηp
2
df F p ηp
2
RT analyses
Set size 3,117 82.96 <.001 .68 3,96 36.16 <.001 .53
Complexity 1,39 119.26 <.001 .75 1,32 34.28 <.001 .52
Appeal 1,39 40.34 <.001 .51 2,64 13.33 <.001 .29
Complexity × Appeal 1,39 4.75 .03 .11 2,64 0.55 .58 -
Set Size × Complexity 3,117 5.38 .003 .12 3,96 6.82 <.001 .18
Set Size × Appeal 3,117 0.63 .59 - 3,96 0.50 .81 -
Set Size × Complexity × Appeal 3,117 0.31 .81 - 6,192 0.26 .95 -
Slopes analyses
Complexity 1,39 15.49 <.001 .28 1,39 27.23 <.001 .41
Appeal 1,39 1.79 .19 - 1,39 0.06 .94 -
Complexity × Appeal 1,39 0.09 .76 - 1,39 0.31 .74 -
Target absent df F p ηp
2
df F p ηp
2
RT analyses
Set size 3,117 152.50 <.001 .80 3,99 125.91 <.001 .79
Complexity 1,39 21.79 <.001 .36 1,33 10.41 <.001 .24
Appeal 1,39 10.01 .003 .20 2,66 9.48 <.01 .23
Complexity × Appeal 1,39 8.97 .005 .19 2,66 0.02 .98 -
Set Size × Complexity 3,117 7.75 .001 .17 3,99 4.72 <.01 .12
Set Size × Appeal 3,117 1.46 .34 - 6,198 1.07 .38 -
Set Size × Complexity × Appeal 3,117 3.06 .03 .07 6,198 0.85 .53 -
Slopes analyses
Complexity 1,39 13.84 <.001 .26 1,39 9.39 .004 .19
Appeal 1,39 2.53 .12 - 2,78 0.94 .39 -
Complexity × Appeal 1,39 6.32 .02 .14 2,78 2.14 .15 -
Attention, Perception, & Psychophysics
significant. There was a significant interaction between Set
Size and Complexity reflecting steeper RT slopes for complex
compared to simple targets (see target-absent slopes analyses
below). No other interactions were significant.
Target-absent slopes
Search slopes for target-absent trials were submitted to a 2
(Complexity: complex vs. simple) × (Appeal: appealing vs.
unappealing) ANOVA, showed only a significant main effect
of Complexity with steeper slopes when looking for complex
(56 ms/item) compared to simple (46 ms/item) targets. The
main effect of Appeal was not significant and neither was
Complexity × Appeal interaction.
Overall, for target-absent trials both appeal and visual
complexity influenced overall search RT: search was terminat-
ed later for unappealing compared to appealing targets, and for
complex compared to simple targets. Search efficiency was
only determined by visual complexity, with steeper search
slopes when looking for complex targets.
Discussion
Experiment 1examined whether appeal may be an attention-
guiding visual object attribute. Participants searched displays
of icons for targets that were orthogonally manipulated along
appeal and visual complexity. The key findings were as fol-
lows. First, both visual complexity and appeal of target icons
influenced search times, with faster search times for simple as
opposed to complex icons, and for appealing compared to
unappealing icons. However, only visual complexity influ-
enced search efficiency. Second, appeal facilitated search re-
gardless of whether it was independently or subjectively de-
fined (i.e., whether what was considered appealing was deter-
mined by previous normative ratings or by the ratings provid-
ed individually by current participants). Third, appeal
interacted with visual complexity when appeal was defined
independently (based on previous ratings) but not when
appeal was defined subjectively (based on each participants
ratings in the current study). Those findings are discussed in
turn.
Search efficiency
Visual complexity significantly slowed down search times
and led to more inefficient searches. Previous work using
search tasks without manipulating search array size has found
a negative impact of visual complexity icons and symbols on
performance (e.g., Byrne, 1993;Gerlach&Marques,2014;
Isherwood et al., 2007; McDougall et al., 2000;McDougall,
Scott, 1993; Reppa et al., 2008; Reppa & McDougall, 2015;
McDougall et al., 2006). The only other study that has to our
knowledge examined the effect of visual complexity on a
search task was carried out by Sun and Firestone (2021). In
a series of experiments, they manipulated the visual complex-
ity of target and distractor geometric shapes. Their findings
were complimentary to those found here: when visually com-
plex targets were embedded in a set of simple distractors,
visually simple distractors led to easier processing and faster
rejection (see also Wolfe & Horowitz, 2017, for a similar
discussion and McDougall et al., 2000, for discussion of
distinctiveness effects when target icons are embedded in
contrasting distractors).
Search speed
Visual search performance was not blind to appeal in the cur-
rent study. Target appeal boosted search performance corrob-
orating previous evidence showing that appealing icons are
localised faster than unappealing icons (e.g., Reppa &
McDougall, 2015; Reppa et al., 2021), and improved search
times and memory for preferred websites (e.g., Baughan et al.,
2020). However, a key question that a classic visual search
task can address is whether or not a particular object feature or
attribute can guide attention during a search task. As noted
earlier, efficient searches are typically less than 10 ms per item
and are thought to reflect pre-attentive processing of that fea-
ture while inefficient searches are typically greater than 10 ms
per item and suggest that the target feature is not pre-
attentively processed and not used to guide attention across
the display. Even when appeal was determined based on par-
ticipantsown ratings, there was no difference in search slopes
between appealing and unappealing targets. Therefore, al-
though aesthetic appeal can influence visual search perfor-
mance overall, there was no evidence in Experiment 1that it
is registered pre-attentively and guides visual search.
The faster search times for appealing targets suggests that
appeal may lead to better processing, particularly since search
for unappealing targets was longer for both target-present and
target-absent trials. The longer search times for unappealing
targets suggests that unappealing targets are processed less
effectively than appealing targets, corroborating previous ev-
idence using different tasks (e.g., Reppa & McDougall, 2015;
Thielsch, Haines, & Flacke, 2019a).
Independentversus subjectiveappeal
Finally, Experiment 1revealed a difference in the effect of
appeal on search depending on whether appeal was deter-
mined based on previous normative ratings (independent
appeal) or based on the ratings of the participant themselves
(subjectiveappeal). Specifically, when appeal was defined
independently, based on previous ratings, it interacted with
visual complexity: appeal sped up search times but only for
complex icons, while search times were not affected by target
appeal when icons were simple. This pattern of results
Attention, Perception, & Psychophysics
replicates previous findings with icons and websites showing
that appeal can influence performance but only under task
duress (i.e., when looking for a visually complex target or
through hard to navigate websites; Moshagen et al., 2009;
Reppa & McDougall, 2015). However, a more ubiquitous
effect of appeal was revealed when appeal was defined sub-
jectively target icons that the participants themselves found
appealing (based on their own ratings), were found faster re-
gardless of whether they were visually complex or simple.
One reason for the ubiquitous effect of appeal on performance
when appeal was determined subjectively may be that appeal-
ing icons were only those rated highly in terms of appeal, and
unappealing icons were only those rated very low in appeal.
All other icons were categorised as neutral. Search perfor-
mance closely followed those categorisations appealing
icons were found faster than unappealing icons and neutral
icons were in-between. Therefore, subjective ratings of appeal
allowed us to observe the effect of highly appealing compared
to highly unappealing stimuli on search performance. Under
those circumstances, the effect of appeal was not conditional
on visual complexity but had a strong independent influence
on performance.
Experiment 2: The effects of neutral versus
appealing distractors on visual search
The purpose of Experiment 2was twofold. First, to replicate
the effects observed in Experiment 1and second to examine
the effect of target-distractor similarity in terms of appeal on
search performance. Participants searched for appealing and
unappealing targets among neutral distractors in Experiment
2a and among appealing distractors in Experiment 2b.
According to a saliency account, target-distractor similarity
should uniquely determine search efficiency, with more effi-
cient searches when the target defined bya specific attribute or
feature differs from the average distribution of the distractors
on that feature (e.g., Itti & Koch, 2000; Rosenholtz, 1999;
Treisman & Gelade, 1980). So, when distractors are appeal-
ing, unappealing targets should be more salient, resulting in
better visual search performance and more efficient search
slopes. However, appealing targets should be less salient
amongst the appealing distractors, resulting in poorer visual
search performance.
Alternatively, search can be determined by whether the
target contains the attribute in question, as opposed to the
overall target-distractor similarity on that attribute. If that is
the case, then unappealing targets lack the attribute of appeal
which is present in appealing distractors. When searching for a
target that is defined by the absence of feature e.g., searching
for an O among Qs, then search slopes are steeper than when
searching for a target that is defined by a feature that is present,
e.g., searching for a Q among Os (e.g., Wolfe, 2001).
Therefore, if aesthetic appeal is a unique visual attribute de-
termining search performance, then when distractors are ap-
pealing, unappealing targets should not guide search as they
lack the attribute of appeal search slopes for unappealing
target should be no different between Experiments 2a and 2b.
Meanwhile, search for appealing targets should be more inef-
ficient when surrounded by appealing distractors compared to
neutral distractors thus, search slopes for appealing targets
should be steeper in Experiment 2b (appealing distractors)
compared to Experiment 2a (neutral distractors).
Previous work has shown similarly that high-reward
distractors can capture attention and thus slow search perfor-
mance (e.g., Anderson et al., 2011). If appealing stimuli act as
rewarding stimuli do, then it may be harder to disengage from
them. Therefore, we would expect steeper search slopes when
distractors were appealing (Exp. 2b) compared to neutral
(Exp. 2a).
Experiment 2a: Neutral distractors
Method
Participants
Twenty-six university-age undergraduate students (18 fe-
males and eight males) were recruited in exchange of partici-
pant pool credits. Participants had normal or corrected-to-
normal vision and were naïve to the aim of the experiment.
The study was approved by the College of Human & Health
Sciences, Swansea University, Research Ethics Committee.
Apparatus and materials
The same apparatus was used as in Experiment 1. The target
and distractor icons were identical to those used in Experiment
1. Distractor icons were all neutral in terms ofaesthetic appeal
and visual complexity (see Table 1). Appeal was defined
based on the ratings obtained by McDougall and Reppa
(2008).
Design, procedure and analyses
The design and procedure were identical to that of Experiment
1. The statistical analyses were identical to those employed in
Experiment 1.
Results
Error trials accounted for 5.50% of all trials with 1.2% false
alarms (saying yes to a target-absent trial) and 4.2% misses
(saying No in a target-present trial). All error trials were re-
moved from the calculation of correct mean response times
Attention, Perception, & Psychophysics
(RT) and analysed separately. RT that was ±3SDs from the
mean per participant and per condition (1.4%) were removed
from the correct RT data and not analysed further. Cell means
for correct RT in target-present and target-absent trials for
Experiment 2are shown in Fig. 4. A summary of the findings
from the analyses carried out is presented in Table 4.
Target-present RT analyses
A repeated-measures ANOVA on target-present trials only
revealed a significant main effect of Set Size with increasing
RT with larger set sizes. The main effect of Complexity was
significant with simple icons being found faster than complex
icons. The main effect of Appeal was also significant with
appealing icons found significantly faster than unappealing
icons. The Complexity × Appeal interaction was significant.
Pairwise comparisons to examine the Complexity × Appeal
interaction showed longer search RT for complex unappealing
compared to complex appealing targets (difference = 54 ms,
t(25) = 4.69, p<.001,d= .92), but a nonsignificant difference
between simple appealing and unappealing targets (difference
=15ms,t(25) = 1.46, p=.16,d= .29). There were no other
significant interactions.
Target-present slopes analyses
Search slopes for target-present trials were submitted to a 2
(Complexity: complex vs. simple) × (Appeal: appealing vs.
unappealing) repeated-measures ANOVA. Neither the main
effect of Appeal, nor Complexity were significant, and neither
was their interaction.
Overall, both visual complexity and appeal influenced
search RT when the target was present in the array, with faster
searches when the target was simple and when the targets
(A) Target Present
(B) Target Absent
Fig. 4 Mean correct response time (RT) per condition for target-present (a) andtarget-absent (b) trials, in Experiment 2a where distractors were of neutral
rated appeal, and Experiment 2b where distractors were appealing. Error bars indicate standard error of the mean
Attention, Perception, & Psychophysics
were appealing. Search efficiency was influenced neither by
visual complexity nor by appeal.
Target-absent RT analyses
A repeated-measures ANOVA for target-absent RT
showed a significant main effect of Set Size with increas-
ing RT as the number of distractors increased. The main
effect of Complexity was significant as was the main ef-
fect of Appeal. The Complexity × Appeal interaction was
significant. Pairwise comparisons to examine the interac-
tion, showed that target-absent RT was overall faster
when looking for complex appealing targets, compared
to unappealing targets (difference = 65 ms, t(25) = 5.67,
p<.001,d = 1.11) and while there was no difference in
search RT between simple appealing and unappealing tar-
get (difference = 17 ms, t(25) = 1.38, p=.18,d=.27).
The only other significant interaction was between Set
Size and Complexity, reflecting steeper RT slopes for
complex compared to simple targets (see slopes analyses
below). Neither the Set Size × Appeal nor the three-way
interaction were significant.
Target-absent slopes analyses
Search slopes for target-absent trials were submitted to a 2
(Complexity: complex vs. simple) × (Appeal: appealing vs.
unappealing) ANOVA, showed a significant main effect of
Complexity, with steeper slopes for complex (60 ms/item)
compared to simple (50 ms/item) target icons. Neither the
main effect of Appeal nor the interaction were significant.
Overall, Experiment 2a results largely replicated the pattern
of results in Experiment 1when appeal was defined indepen-
dently (based on previous ratings). For target-absent trials
appeal interacted with visual complexity to influence overall
search RT: search was terminated later for unappealing com-
pared to appealing targets, with this difference being larger for
complex compared to simple target icons. Search efficiency
was determined only by visual complexity, with steeper search
slopes when searching for complex compared to simple
targets.
Table 4 Experiment 2: Summary of findings in Experiments 2a (neutral distractors) and 2b (appealing distractors)
Experiment 2a Neutral distractors Experiment 2b Appealing distractors
Target present df F p ηp
2
df F p ηp
2
RT analyses
Set size 3,75 70.31 <.001 .74 3,72 80.94 <.001 .77
Complexity 1,25 41.64 <.001 .62 1,24 79.22 <.001 .77
Appeal 1,25 20.77 <.001 .45 1,24 0.47 .50 -
Complexity × Appeal 1,25 5.70 .02 .19 1,24 8.27 <.01 .26
Set Size × Complexity 3,75 0.76 .52 .50 3,72 3.71 <.01 .13
Set Size × Appeal 3,75 1.14 .34 - 3,72 0.59 .62 -
Set Size × Complexity × Appeal 3,75 0.88 .45 - 3,72 1.29 .27 -
Slopes analyses
Complexity 1,25 1.27 .27 - 1,24 8.73 <.007 .41
Appeal 1,25 1.62 .21 - 1,24 0.70 - -
Complexity × Appeal 2,25 0.42 .52 - 2,24 0.68 - -
Target absent df F p ηp
2
df F p ηp
2
RT analyses
Set size 3,75 148.99 <.001 .86 3,72 105.17 <.001 .81
Complexity 1,25 30.84 <.001 .55 1,24 59.66 <.001 .71
Appeal 1,25 9.63 .005 .28 1,24 3.05 .09 -
Complexity × Appeal 1,25 19.13 <.001 .43 1,24 4.08 .05 .14
Set Size × Complexity 3,75 4.34 .007 .15 3,72 17.75 <.001 .42
Set Size × Appeal 3,75 0.75 .52 - 3,72 1.93 .13 -
Set Size × Complexity × Appeal 3,75 1.14 .34 - 3,72 0.39 .76 -
Slopes analyses
Complexity 1,25 10.68 .003 .30 1,24 40.31 <.001 .63
Appeal 1,25 .69 .41 - 1,24 0.05 .82 -
Complexity × Appeal 2,25 1.81 .19 - 2,24 0.09 .77 -
Attention, Perception, & Psychophysics
Experiment 2b: Appealing distractors
In Experiment 2b appealing and unappealing targets appeared
among appealing distractors (see Table 4). All other aspects of
the methodology were identical to Experiment 1and 2a.
Method
Participants
Twenty-six new participants, 17 females and nine males, with
ages ranging from 19 to 55 years (M=25.09, SD =10.45)
took part in Experiment 2b. Participants were recruited via an
advertisement displayed on televisions around Swansea
University Singleton Campus Psychology students received
participant pool credits, while non-psychology participants
received £6 for their time. Participants were all native
English speakers and reported normal or corrected-to-normal
vision. The study was approved by the College of Human &
Health Sciences, Swansea University, Research Ethics
Committee.
Apparatus and materials
The same apparatus was used as in Experiment 1and 2a.
Target icons were the same as those used in Experiment 2a
varying orthogonally in terms of appeal and visual complex-
ity while matched in terms of concreteness and familiarity.
However, a new set of 72 distractor icons was used in
Experiment 2b, with the criterion that they were all rated high
in terms of aesthetic appeal (greater than a rating of 3). The
characteristics of the distractor icons used in Experiment 2b
appear in Table 1, along with the comparisons between target
and distractor icons on each icon characteristic.
Design, procedure and analyses
The design and procedure for Experiment 2b was identical to
that of Experiment 2a, with the exception of the level of appeal
of the distractor icons. Unlike Experiment 2a, only appealing
icons were chosen as distractors, based on the appeal ratings
from McDougall and Reppa (2008).
Results
Trials with incorrect responses (4.42%) and correct trials with
responses that were ±3 SDs from the mean per participant per
condition (1.6%) were removed from the data and were not
analysed further. One participants data was removed fromthe
calculation of mean RT as their overall RT exceeded 3 stan-
dard deviations from the group mean. Mean correct response
times (ms) for the remaining 25 participants per condition are
shown in Fig. 4. The findings from the analyses carried out
appears in Table 4.
Target-present RT analyses
A repeated-measures ANOVA on correct RT of target-
present trials only, revealed a significant main effect of Set
Size and a significant main effect of Complexity. The main
effect of Appeal was no longer significant but there was a
significant Complexity × Appeal interaction. Pairwise com-
parisons showed no difference in RT between simple appeal-
ing and unappealing target icons, t(24) = 1.82, p=.08,but
search times were faster for complex appealing compared to
complex unappealing icons, t(24) = 2.51, p<.01,d=.50.The
interaction between Complexity × Set Size was also signifi-
cant with steeper search slopes for complex compared to sim-
ple target icons (see slopes analyses below). There were no
other significant interactions, including the theoretically rele-
vant Set Size by Appeal interaction.
Target-present slopes analyses
Search slopes for target-present trials were submitted to a 2
(Complexity: complex vs. simple) × (Appeal: appealing vs.
unappealing) repeated-measures ANOVA. The main effect of
Complexity was significant with steeper slopes for complex
(28 ms/item)compared to simple targets (19 ms/item). Neither
the main effect of Appeal nor the interaction were significant.
Target-absent RT analyses
A repeated-measures ANOVA on correct RT of target-absent
trials, showed a significant main effect of Set Size significant
main effect of Complexity as well as a significant Set Size ×
Complexity interaction reflecting steeper search slopes for
complex targets (see slopes analyses below). The main effect
of Appeal was not significant. The Complexity × Appeal in-
teraction was significant, with faster search termination RTs
for complex appealing targets comparedto unappealing coun-
terparts (t(24) = 2.57, p=.001,d= .51), but no difference in
search RT between simple appealing and unappealing targets
[t(24) = 0.13, p= .90). None of the other interactions were
significant.
Target-absent slopes analyses
Search slopes for target-absent trials were submitted to a 2
(Complexity: complex vs. simple) × (Appeal: appealing vs.
unappealing) ANOVA. Only the main effect of Complexity
was significant with steeper slopes for complex (80 ms/item)
compared to simple targets (63 ms/item). Neither the main
effect of Appeal, nor the interaction were significant.
Attention, Perception, & Psychophysics
In summary, when distractor icons were appealing, search
RT and search efficiency for target-present and target-absent
trials were only influenced by the visual complexity of the
target icon. Target appeal no longer facilitated search or search
termination times.
Comparison between Experiment 2a and Experiment 2b
Experiments 2a and 2b were identical in every aspect apart
from the level of appeal of the distractor icons. The aim was to
examine the effect that distractor appeal might have on search
efficiency, as captured in search slopes, for appealing and
unappealing target icons. A summary of the results from the
analyses comparing the search slopes in Experiments 2a and
2b appears in Table 5.
Comparison of target-present slopes
A mixed 2 (Complexity: complex vs. simple) × 2 (Target
Appeal: appealing vs. unappealing) × 2 (Distractor Appeal:
neutral vs. appealing) ANOVA was carried out on search
slopes for target-present trials, with Distractor type as the
between-participants variable. There was a significant main
effect of Complexity steeper slopes for complex compared
to simple targets, and of Distractor Appeal with steeper slopes
when distractors were appealing compared to when they were
of medium appeal. Target appeal interacted with Complexity,
with steeper slopes for complex unappealing compared to
complex appealing targets,t(49) = 2.02, p= .04, d= .28,
but no such significant difference between simple appealing
and unappealing targets, t(49) = .52, p= .60. Target Appeal
did not have a significant main effect on search slopes but it
interacted with Distractor Appeal. Pairwise comparisons con-
firmed that appealing targets yielded flatter slopes when
distractors were neutral in appeal, (17 ms/item) compared
to when distractors were appealing (25 ms/item), t(49) =
3.07, p=.003,d= .86. Unappealing targets yielded similar
slopes irrespective of whether they appeared among neutral or
appealing distractors (20 ms/item and 22 ms/item, respective-
ly), t(49) = .41, p= .68, d= .11. The Distractor Appeal ×
Complexity interaction was not significant and neither was
the three-way interaction.
In summary, when the target was present, distractor appeal
influenced search slopes overall, with more inefficient
searches when distractors were of high compared to neutral
appeal. Distractor appeal also interacted with target complex-
ity to yield steeper slopes for complex target icons when they
were surrounded by appealing compared neutral appeal
distractors. Critically, distractor appeal interacted with target
appeal, with steeper slopes for appealing targets amongst ap-
pealing distractors compared to neutral appeal distractors.
Comparison of target-absent slopes
The same ANOVA on target-absent trials, showed a signifi-
cant main effect of Distractor Appeal with steeper search
slopes when search was among appealing distractors (71 ms/
item) compared to neutral distractors (55 ms/item). Target
Complexity was also significant on target-absent slopes with
steeper slopes for complex (70 ms/item) compared to simple
targets (56 ms/item). There were no significant interactions.
Table 5 Experiment 2: Summary of analyses comparing search slopes in Experiments 2a and 2b
df F p ηp
2
Target-present search slopes
Target Complexity 1,49 8.96 .004 .16
Target Appeal 1,49 0.01 .97 -
Distractor Appeal 1,49 4.19 .05 .08
Target Complexity × Target Appeal 1,49 0.76 .39 -
Target Complexity × Distractor Appeal 1,49 2.19 .14 -
Target Appeal × Distractor Appeal 1,49 4.58 .04 .09
Target Complexity × Target App × Distractor App 1,49 0.01 .92 -
Target-absent search slopes
Target Complexity 1,49 40.99 <.001 .45
Target Appeal 1,49 0.45 .51 -
Distractor Appeal 1,49 4.51 .04 .07
Target Complexity × Target Appeal 1,49 1.17 .28 -
Target Complexity × Distractor Appeal 1,49 2.62 .11 -
Target Appeal × Distractor Appeal 1,49 0.32 .57 -
Target Complexity × Target App × Distractor App 1,49 0.98 .33 -
Attention, Perception, & Psychophysics
Discussion
Experiment 2examined the effect of distractor aesthetic appeal
on search times for appealing and unappealing targets.
Distractor appeal influenced search slopes, slowing search
times down overall. Distractor appeal also interacted with target
appeal: searching for appealing targets among appealing
distractors resulting in more inefficient search compared to
searching for appealing targets among distractors of medium,
or neutral, levels of appeal. Meanwhile, unappealing targets did
not benefit from being surrounded by appealing distractors. In
other words, lack of appeal did not lead to more efficient
searches when looking through appealing distracting stimuli,
compared to when looking through icons of neutral appeal.
Taken together the findings from Experiments 2a and 2b
suggest that what leads to faster searches for appealing targets
is the attribute of appeal itself, as opposed to target-distractor
similarity. Previous literature shows that the speed at which
distractors are rejected can depend on target-distractor similarity
(e.g., Duncan & Humphreys, 1989) in terms of low-level fea-
tures but also in terms of non-perceptual attributes. Here, the
target-distractor similarity was based on appeal a high-level
and subjective attribute of objects. However, as unappealing
target icons were defined by the absence of appeal (e.g.,
Wolfe, 2001; Wolfe & Horowitz, 2004) and absence is not a
feature that can influence search slopes (e.g., Treisman, 1986),
the consistently steep search slopes for unappealing targets re-
gardless of distractor appeal, suggest that they lacked the attri-
bute of appeal that was needed to facilitate search times.
Search slopes were steeper when distractors were appealing,
compared to when they were neutral in appeal, and that was the
case both for target-present and target-absent trials. This sug-
gests that appealing crowdsare searched slower than crowds
of neutral appeal. The slower search among appealing
distractors, may be due to the difficulty in disengaging from
appealing distractors (e.g., Fox et al., 2002), or because appeal
constricts the focus of attention leading to steeper search slopes
(e.g., Fenske & Eastwood, 2003). Therefore, despite the lack of
evidence for pre-attentive processing of appeal (as would be
evidenced by flatter search slopes) or search inequality between
appealing and unappealing targets, the steeper search slopes
among appealing distractors, suggest that the appeal of items
inasearcharrayinfluences search performance.
Experiment 3: The effect of target
concreteness and target appeal on visual
search
This is the first examination, to our knowledge, of whether con-
creteness the degree to which an image refers to something in
the real world which is a key characteristic of pictures, icons
and symbols, is an attention guiding attribute. Previously icon
concreteness has been associated with better performance in lo-
calisation and identification tasks (e.g., Green & Barnard, 1990;
Isherwood et al., 2007; McDougall & Isherwood, 2009; Rogers
&Oborne,1987; Stotts, 1998). This makes it a good candidate as
a possible icon characteristic which may improve search efficien-
cy as well as search speeds. This experiment mirrors Experiment
1in terms of design, procedure and analyses with the primary
difference between that target concreteness, rather than target
complexity, was varied orthogonally with target appeal.
Method
Participants
Twenty new undergraduate Swansea University students (13
females, seven males), with ages ranging from 19 to 39 years
(M=24.12, SD = 9.46) and with normal or corrected-to-
normal vision, took part in Experiment 3in exchange for
psychology participant pool credits. Participants were naïve
to the purpose of the experiment. The study was approved by
the College of Human & Health Sciences, Swansea
University, Research Ethics Committee.
Apparatus and materials
The apparatus was the same as in the previous experiments. Forty
target icons and seventy-two distractor icons were chosen from
the icon corpus in McDougall et al. (1999). The target icons
orthogonally varied their rated Concreteness and Appeal, leading
to four icon types: appealing concrete, appealing abstract, unap-
pealing concrete, and unappealing abstract (Table 6). Ratings of
visual complexity, concreteness, and familiarity were obtained
from McDougall et al. (1999), and ratings of appeal were obtained
by McDougall and Reppa (2008). A set of univariate ANOVAs
showed differences between the Icon Types in terms of rated
Concreteness, Familiarity, and Appeal, and the lack of difference
in terms of Visual Complexity (see Table 6for details). Seventy-
two icons from the original icon corpus were used as distractors,
whose characteristics (visual complexity, concreteness, familiari-
ty, and appeal) appear in Table 1. Distractors were chosen to be
neutral in terms of rated appeal. Comparisons between target and
distractors icons in Experiment 3appear in Table 6.
As shown in Table 6the four icon types differed not only in
terms of Concreteness but also in terms of Familiarity.
Concreteness and familiarity are highly correlated and their ef-
fects cannot easily be separated (see McDougall et al., 1999,and
Prada et al., 2016). We carried out two sets of analyses in the
first we coded the icons in terms of their independently rated
concreteness and appeal, and in the second in terms of their rated
familiarity and appeal. When the icons were coded in terms of
Familiarity and Appeal, there were 13 icons for familiar appeal-
ing, ten icons for familiar unappealing, seven icons for unfamiliar
appealing, and ten icons for unfamiliar unappealing.
Attention, Perception, & Psychophysics
Design and procedure
A 2 (Target Presence: present vs. absent) × 4 (Set Size: 3, 6, 9,
or 12) × 2 (Concreteness: concrete vs. abstract) × 2 (Appeal:
appealing vs. non-appealing) repeated-measures design was
used, yielding 32 within-participant conditions. There were
ten trials per condition yielding a total of 320 trials per partic-
ipant. The dependent measure was RT.
The procedure of the visual search task was identical to that
in Experiment 1.
Results
Error rates were low accounting for about 6.2% of all trials
(4.6% misses and 1.6 % false alarms). Error trials were
removed from the correct RT analyses, prior to estimating
the mean RT per condition. Correct trials with responses
that were ±3 SDs from the mean per participant per condi-
tion (0.33%) were excluded from the analyses. Correct
mean RT per condition for target-present and target-
absent trials appear in Fig. 5. The summary of results from
the analyses of RT and slope data of Experiment 3appears
in Table 7.
Target-present RT analyses
A 4 (Set Size: 3, 6, 9, 12) × 2 (Concreteness: concrete vs.
abstract) × 2 (Appeal: appealing vs. non-appealing)
repeated-measures ANOVA was carried out on correct RT
of target-present trials. The main effect of Set Size was sig-
nificant with RT increasing with larger set sizes. The main
effect of Concreteness was significant faster search termina-
tion times for concrete icons compared to abstract icons. The
main effect of Appeal was also significant with faster search
termination times for appealing icons compared to unappeal-
ing icons. None of the interactions were significant.
Target-present slopes analyses
A 2 (Concreteness: concretevs. abstract) × 2 (Appeal: appeal-
ing vs. unappealing) repeated-measures ANOVA on search
slopes, showed no significant main effect of Concreteness
no significant main effect of Appeal and no significant
interaction.
In summary, when the target was present, appeal and
concreteness independently influenced search RT -ittookless
time to find the target if it was appealing than unappealing,
and when it was concrete, as opposed to abstract. Neither
appeal nor concreteness however influenced search efficiency
when the target was present.
Table 6 Experiment 3: Mean ratings (and standard deviations) for icon concreteness, aesthetic appeal, visual complexity and familiarity for each type of icon, and the results of one-way analyses and
Newman-Keuls comparisons examining differences between icon ratings in each condition in Experiment 3
Icon characteristics Target icon types (a) Comparisons between target icon types Neutral Distractors ND (b) Comparisons between target icons and distractors
Appealing
Abstract AA
Appealing
Concrete AC
Unappealing
Abstract UA
Unappealing
Concrete UC
F-value Newman-Keuls
comparisons
F-value Newman-Keuls
comparisons
Appeal 3.52 (0.18) 3.5 (0.10) 2.51 (0.11) 2.58 (0.17) F(3 36)=204.89, p<.001 AA=AC>UA=UC 3.00 (0.40) F(4, 107)=22.07, p<.001 AA=AC>ND
UA=UC<ND
Complexity 3.00 (0.53) 2.67 (0.95) 3.1 (0.75) 3.22 (0.76) F(3, 36)=0.96, p=.42 AA=AC=UA=UC 2.55 (0.77) F(4, 107)=2.29, p=.03 AA=AC=ND
UA=UC=ND
Concreteness 2.06 (0.35) 4.57 (0.25) 2.17 (0.20) 4.55 (0.15) F(3,36)=319.71, p<.001 AA=UA<AC=UC 3.18 (0.98) F(4, 107)=21.95, p<.001 AA=UA<ND
AC=UC>ND
Familiarity 2.47 (0.96) 3.7 (0.43) 2.08 (0.57) 3.78 (0.35) F(3, 36)=18.89, p<.001 AA=UA<AC=UC 2.86 (0.90) F(4, 107)=8.36, p<.001 AA=UA<ND
AC=UC>ND
Note. The Appeal values and statistics are from McDougall and Reppa (2008), and the Complexity, Concreteness, and Familiarity values are from McDougall et al. (1999)
Attention, Perception, & Psychophysics
Target-absent RT analyses
A 4 (Set Size: 3, 6, 9, 12) × 2 (Concreteness: concrete vs.
abstract) × 2 (Appeal: appealing vs. non-appealing)
repeated-measures ANOVA was carried out on correct
RT of target-absent trials. This showed a significant main
effect of Set Size with RT increasing with larger set sizes.
The main effect of Concreteness was significant with
faster termination times for concrete compared to abstract
target icons. The main effect of Appeal was also signifi-
cant with faster termination times when looking for ap-
pealing compared to unappealing targets. There were no
significant interactions.
Target-absent slopes analyses
A 2 (Concreteness: concrete vs. abstract) × 2 (Appeal:
appealing vs. unappealing) repeated-measures ANOVA
on search slopes for target-absent trials, showed a signif-
icant main effect of Concreteness. There was no signifi-
cant main effect of Appeal but the interaction was signif-
icant simple effects analysis confirmed that slopes were
steeper in unappealing compared to appealing target trials
when targets were abstract (p< .05), but not when they
were concrete (p> .05).
Overall, when the target was absent from the array,
appeal and concreteness influenced search RT, with
search terminated earlier when looking for appealing com-
pared to unappealing targets, and when looking for con-
crete compared to abstract targets. Search efficiency was
influenced by the interaction between appeal and
concreteness search was more efficient when looking
for appealing as opposed to unappealing targets, especial-
ly when they were abstract.
Table 7 Experiment 3summaryofanalyses
Target present df F p ηp
2
RT analyses
Set size 3,60 41.08 <.001 .67
Concreteness 3,60 18.55 <.001 .48
Appeal 3,60 18.60 <.001 .48
Concreteness × Appeal 1,20 0.17 .68 -
Set size × Concreteness 3,60 0.68 .56 -
Set size × Appeal 3,60 0.12 .94 -
Set size × Concreteness × Appeal 3,60 1.66 .18 -
Slopes analyses
Concreteness 1,20 0.36 .55 -
Appeal 1,20 0.01 .92 -
Concreteness × Appeal 1,20 0.51 .48 -
Target absent df F p ηp
2
RT analyses
Set size 3,60 165.89 <.001 .89
Concreteness 3,60 11.14 .003 .36
Appeal 3,60 5.82 .02 .22
Concreteness × Appeal 1,20 2.96 .28 -
Set size × Concreteness 3,60 1.96 .13 -
Set size × Appeal 3,60 1.23 .28 -
Set size × Concreteness × Appeal 3,60 2.31 .08 -
Slopes analyses
Concreteness 1,20 0.93 .35 -
Appeal 1,20 3.48 .08 -
Concreteness × Appeal 1,20 0.45 .51 -
(A) Target Present
(B) Target Absent
Fig. 5 Mean correct response time (RT) per condition for (a) target-
present trials and (b) target-absent trials in Experiment 3where target
icons differed in appeal and concreteness and appeared among neutral
appeal distractors. Error bars indicate standard error of the mean
Attention, Perception, & Psychophysics
The role of icon familiarity
A further set of analyses was carried out, with the icons re-
coded in terms of Familiarity instead of Concreteness. This
was done in order to systematically contrast and compare the
effects of familiarity vs concreteness on visual search. This
was because it was difficult to control the effects of familiarity
separately from concreteness as a result of their close
correlation.
Target-present RT analyses
Correct cell mean RT appear in Fig. 6, and results of the
analyses appear in Table 8. A 2 (Familiarity: familiar vs. un-
familiar) × 2 (Appeal: appealing vs. unappealing) × 4 (Set
size: 3, 6, 9 and 12) repeated-measures ANOVA on target-
present RT showed that all three main effects were significant.
Correct RTs increased with Set Size, familiar icons were
found faster than unfamiliar ones and appealing icons were
found faster than unappealing ones. There were no significant
interactions.
Target-present slopes analyses
A 2 (Familiarity: familiar vs. unfamiliar) × 2 (Appeal: appeal-
ing vs. unappealing) repeated-measures ANOVA on search
slopes, showed no significant main effect of Familiarity, and
only a marginally significant effect of Appeal and no signifi-
cant interaction.
In summary, when the target was present, appeal and
familiarity independently influenced search RT it took less
time to find the target if it was appealing than unappealing,
and when it was concrete, as opposed to abstract. As was the
case with concreteness and appeal, neither appeal nor
(A)Target Present
(B) Target Absent
600
700
800
900
1000
1100
36912
RT (m s)
Set Size
Target present
Unfamiliar unappealing
(25 ms/item)
Unfamiliar appealing
(28 ms/item)
Familiar unappealing
(22 ms/item)
Familiar appealing
(21 ms/item)
600
800
1000
1200
1400
1600
36912
RT (m s)
Set Size
Target absent
Unfamiliar unappealing
(60 ms/item)
Unfamiliar appealing
(53 ms/item)
Familiar unappealing
(55 ms/item)
Familiar appealing
(50 ms/item)
Fig. 6 Mean correct response time (RT) per condition for (a) target-
present trials and (b) target-absent trials in Experiment 3where target
icons differed in appeal and familiarity and appeared among neutral
appeal distractors. Error bars indicate standard error of the mean
Table 8 Experiment 3summary of analyses based on icon familiarity
and appeal (see text for details)
Target present df F p ηp
2
RT analyses
Setsize 3,5749.20<.001.72
Familiarity 1,19 22.43 <.001 .54
Appeal 1,19 4.57 .05 .19
Familiarity × Appeal 1,19 0.20 .66 -
Set size × Familiarity 3,57 1.71 .17 -
Set size × Appeal 3,57 0.05 .98 -
Set size × Familiarity × Appeal 3,57 0.20 .66 -
Slopes analyses
Familiarity 1,19 1.62 .22 -
Appeal 1,19 0.07 .79 -
Familiarity × Appeal 1,19 0.20 .66 -
Target absent df F p ηp
2
RT analyses
Setsize 3,5773.81<.001.79
Familiarity 1,19 8.66 .008 .31
Appeal 1,19 2.79 .11 -
Familiarity × Appeal 1,19 0.24 .63 -
Set size × Familiarity 3,57 1.10 .36 -
Set size × Appeal 3,57 2.30 .09 -
Set size × Familiarity × Appeal 3,57 0.25 .62 -
Slopes analyses
Familiarity 1,19 0.75 .40 -
Appeal 1,19 3.77 .07 -
Familiarity × Appeal 1,19 0.09 .76 -
Attention, Perception, & Psychophysics
familiarity however influenced search efficiency when the tar-
get was present.
Target-absent RT analyses
A 4 (Set Size: 3, 6, 9, 12) × 2 (Familiarity: familiar vs. unfa-
miliar) × 2 (Appeal: appealing vs. non-appealing) repeated-
measures ANOVA was carried out on correct RT of target-
absent trials. This showed a significant main effect of Set Size
with RT increasing with larger set sizes. The main effect of
Familiarity was significant with faster termination times for
familiar compared to unfamiliar target icons. The main effect
of Appeal was not significant, and there were no significant
interactions.
Target-absent slopes analyses
A 2 (Familiarity: familiar vs. unfamiliar) × 2 (Appeal: appeal-
ing vs. unappealing) repeated-measures ANOVA on search
slopes for target-absent trials, showed than neither of the two
main effects were significant. The interaction was only mar-
ginally significant (p=.09)
Overall, when the target was absent from the array,
appeal and concreteness influenced search RT, with
search terminated earlier when looking for appealing com-
pared to unappealing targets, and when looking for con-
crete compared to abstract targets. Search efficiency was
not influenced by appeal or familiarity although their in-
teraction approached significance, with a trend for a big-
ger difference between appealing and unappealing unfa-
miliar items compared to the difference between appeal-
ing and unappealing familiar items.
Discussion
The current findings showed that search was terminated
sooner, and it was faster for concrete compared to abstract
icons. This finding confirms that icon concreteness is an
important variable in task performance when speed is
emphasised for the task (i.e., localisation and search
tasks), even when it is not task relevant. However, unlike
visual complexity it did not influence search efficiency
search slopes were in the quite inefficientrange for both
abstract and concrete icons and there was no search asym-
metry between the two conditions. Therefore, even though
concreteness can speed search up it only does so after the
item is attended to. Separate analyses showed that the
effects of familiarity on visual search are similar to those
of concreteness. This is not surprising given their high
correlation: concrete icons rely on the use of visual met-
aphors with the real world, often using familiar objects to
represent mean producing a close relationship between the
two icon characteristics.
Critically, as in the previous experiments, icon appeal
moderated search performance: search was faster when
looking for an appealing target, compared to unappealing
targets. This finding corroborates previous evidence from
a localisation task, showing that appealing icons are lo-
calised faster than unappealing icons (e.g., Reppa &
McDougall, 2015). However, although previous work
found that the beneficial effect of appeal on localisation
performance was contingent on task difficulty - i.e., only
observed for abstract icons, which are typically harder to
localise, we found no such interaction here. Instead, the
beneficial effect of appeal was observed in visual search
regardless of whether icons were concrete or abstract.
This could potentially be due to the difference in task
demands. In localisation tasks response times are typically
longer (ranging between ~1 s and 1.8 s) and encompass
both the time to find the icon in the display and the time
to move the cursor to its location. In a visual search task,
only time to find the target in the display is measured and
that time ranged between ~0.6 and 1.2 s.
As in Experiments 1and 2, despite the overall effect of
appeal on search time, there was no evidence that search
was more efficient for appealing targets compared to unap-
pealing targets. Search slopes were generally inefficient at
around 20 ms per item. Search for unappealing targets lasted
longer for both target-present and target-absent trials. That is,
when the target was present unappealing icons took longer to
find, and when the target was absent, it took longer to termi-
nate the search for unappealing targets. This pattern of results
suggests that unappealing targets may be processed less effec-
tively than appealing targets.
General discussion
Attractiveness of objects, people, or interfaces is key to much
of our everyday life decisions and behaviours, with significant
socio-economic impact (e.g., Jylhä & Hamari, 2019). But do
attractiveobjects guide attention to themselves? The overarch-
ing aim of the current study was to examine whether aesthetic
appeal can influence visual search performance. We manipu-
lated visual complexity and aesthetic appeal of a set of icons,
while controlling for other icon characteristics. The key find-
ings were as follows:
(i) Search efficiency was determined by visual complexity,
with icons rated as visually simple guiding search more
efficiently than those rated as visually complex.
(ii) Visual search performance was not blind to beauty to
borrow a term from Gerritsen et al. (2008). Search times
for appealing targets were faster than for unappealing
targets, across all three experiments.
Attention, Perception, & Psychophysics
(iii) There was no evidence that appeal was pre-attentively
processed and guided search.
(iv) When distractors were appealing, the search advantage
for appealing targets was reduced, and it was not re-
placed by advantage for unappealing targets.
(v) Appealing distractors took longer than neutral
distractors to be rejected - as evidenced by the slower
search times and less efficient searches among appealing
compared to neutral distractors. Those findings are dis-
cussed in turn.
Visual complexity guides search
The current study is one of the few to date examining the role
of visual complexity in a classic visual search task (see also
Sun & Firestone, 2021). Previous work using search tasks
without manipulating search array size, has found a negative
impact of visual complexity icons and symbols on perfor-
mance (e.g., Byrne, 1993; Gerlach & Marques, 2014;
Isherwood et al., 2007; McDougall et al., 2000;McDougall
et al., 2006; Scott, 1993; Reppa & McDougall, 2015).
Manipulating set size allowed us to examine whether and to
what extend visual complexity can influence search efficien-
cy. Search for visually simple targets never approach the ef-
ficient rangeof approximately <