Although there is abundant literature on both inattentional
blindness (IB) and eyewitness memory as separate areas of research,
there has been little focus on integrating these two. Laney and Loftus
(2010) made a strong case for conducting research that combines IB and
change blindness (CB) with eyewitness memory. In eyewitness studies that
are conducted in laboratory settings, the participants are usually
expecting to see something happen and are aware that they will be
questioned about the material. In approximately two thirds of eyewitness
studies reviewed, researchers showed participants a video, slideshow or
series of photos and implied or explicitly told them they would be asked
questions about the stimuli. These instructions may have led them to pay
closer attention to the events portrayed in the materials than they
would have if they had been actual witnesses to the real-life event.
This heightened level of expectancy in many of the studies may have
resulted in greater frequencies of noticing than would be expected
outside of the laboratory where real witnesses are often engaged in some
other task or activity when the event occurs. Others (Ihlebaek, Love,
Eilertsen, & Magnussen, 2003; Malpass, Sporer, & Koehnken, 1996)
have acknowledged these problems with traditional eyewitness studies and
Lane (2006) directly addressed effects of concurrent tasks on eyewitness
memory. She found that participants who engaged in a secondary task were
more susceptible to misinformation presented after viewing a slide show.
However, her secondary task was auditory, unrelated to the eyewitness
slide sequence, and did not produce inattentional blindness.
IB is the failure to notice an unexpected stimulus because
attention is focused on another task or object (Mack & Rock, 1998).
A few studies have directly addressed how IB and the related phenomenon
of CB are relevant in criminal cases. Chabris and Simons (2010)
suggested Boston police officer Kenny Conley may have been
inattentionally blind to the beating of African-American undercover
officer Michael Cox by uniformed officers who mistook Cox for a suspect.
Conley, who reportedly ran by within feet of the beating, claimed to
have not noticed the assault. Chabris, Weinberger, Fontaine and Simons
(2011) simulated this situation in a recent study. They found that 35%
of undergraduates following a fellow jogger at night failed to notice
three students engaged in a staged fight. Davis, Loftus, Vanous, and
Cucciare (2007) conducted a study on CB, which occurs when a change to a
visual scene goes undetected. Participants watched a video of a theft in
a grocery store. As in typical IB studies, participants were given a
task to complete (memorizing items from aisles) while watching the
video. Sixty-four percent of participants failed to notice that the
person who emerged from behind a display was not the thief who had
recently gone behind it, and overall misidentifications were over 70%.
The visual attention literature, encompassing both IB and CB, addresses
issues pertinent to eyewitness memory performance, such as failure to
encode features of a scene or failure to distinguish differences
properly. Incorporating aspects of the IB paradigm, like dual task
procedures, may result in findings that are more applicable to real-life
eyewitness situations where bystanders are not maximally attentive to
the important event occurring in front of them.
Since Mack and Rock (1998) first coined the term, there have been
numerous studies to demonstrate the applicability of IB to various
situations. In a well-known study building on Neisser (1979), Simons and
Chabris (1999) instructed participants to count basketball passes
between team members wearing either white or black shirts in a video.
While players passed the ball, a woman in a gorilla costume or a tall
woman with an umbrella appeared on screen for 5 seconds, walking through
the middle of the screen. Despite the salience of the event, only 54% of
A variety of tasks and stimuli have been used in IB studies, such
as following shapes on a computer screen (Most et al., 2001; Most,
Scholl, Clifford, & Simons, 2005) or making decisions during a
sports simulation (Memmert & Furley, 2007). Others have explored
more serious consequences. Participants in driving simulators have
missed signs or pedestrians because they were talking on a cell phone
(Strayer, Cooper & Drews, 2004; Strayer, Drews & Johnston, 2003)
and have been slow to notice an oncoming motorcycle when attending to
traffic signals (Most & Astur, 2007), and pilots in a flight
simulator have failed to see a plane on the runway they were landing on
Most et al. (2005) expanded on the perceptual cycle framework
(Neisser, 1979) that describes how instances of attention capture and
awareness capture can occur at different stages of processing. Attention
capture is the shifting of unconscious attention to stimuli due to their
salience, and does not require the capture of awareness. Awareness
capture refers to when stimuli are acknowledged on the conscious level
(Most et al., 2005; Neisser, 1979). An individual's attentional set
consists of the specific characteristics of stimuli to which an
individual is devoting his or her attention at any given time. In IB
research, the attentional set is established by the instructions given
for the primary task. The occurrence of IB is affected by attentional
sets based on color (Most & Astur, 2007; Most et al., 2001; Simons
& Chabris, 1999), shape, luminescence, motion (Most et al., 2001),
number (White, & Davies, 2008), and semantic meaning (Koivisto &
Revonsuo, 2007). Whether a stimulus captures awareness depends on the
interaction of salience and attentional set. Some stimuli may capture
attention, but unless they are consistent with the attentional set, they
will not capture awareness. Other stimuli may be so salient that they
capture awareness regardless of the attentional set (Most et al., 2005).
Karns and Rivardo (2010) found attentional set for expected action
could affect noticing of an unexpected fight between two students.
Participants who watched surveillance video in an attempt to find a
person known to have been in physical confrontations with another
student were more likely to notice a physical confrontation between two
students than to notice a conspicuous person in a gorilla suit.
Participants who were told to look for the target person to inform him
about a family emergency were more likely to notice the gorilla than the
confrontation. In each of these studies, only the effect of attentional
set on noticing the unexpected event was examined; the accuracy of
participants' memory for the features of the unexpected object or
the details of the unexpected event were not examined.
Clearly, the IB literature shows that salient stimuli can pass
through one's visual field without being noticed and these findings
are relevant to eyewitness memory. If witnesses are not able to notice
something that occurs right in front of them, then they are incapable of
correctly reporting the incident. In real life situations, people are
likely to be engaged in other tasks when eyewitness events occur so IB
may lead to worse memory performance than has been reported in the
Eyewitness memory is often inaccurate and impressionable. In
laboratory studies, researchers can affect accuracy of eyewitness memory
by using techniques that result in the misinformation effect. The
misinformation effect refers to changes in a person's memory for
past events due to exposure to incorrect information (for review see
Loftus, 2005). Misinformation can lead to alterations in the reporting
of details of an event or to the creation of completely false memories
for events that never occurred.
Through the lost in the mall technique (Lindsay, Hagan, Read, Wade
& Garry, 2004; Loftus, 1993; Loftus & Pickrell, 1995),
researchers have created false memories for events that never occurred.
Examples of such false memories include childhood memories of being lost
in a mall as a child (Loftus & Pickrell), being hospitalized
overnight, spilling punch on the parents of a bride at a wedding,
evacuating a grocery store because the overhead sprinklers were
mistakenly set off, causing a car accident in a parking lot by releasing
the parking brake on a car (Hyman, Husband, & Billings, 1995) and
riding in a hot air balloon (Wade, Garry, Read, & Lindsay, 2002).
Using a mock advertisement, Braun and colleagues led participants to
believe that they had met Bugs Bunny at Disney World even though Bugs
Bunny is a Warner Bros character and would not be at Disney World
(Braun, Ellis, & Loftus, 2002; Braun-LaTour, LaTour, Pickrell &
Loftus, 2004). Given the ease with which memories of events can be
created, it is easy to see how participants who are initially
inattentionally blind to the event might form memories for that event
based upon information provided later.
Misleading post event information can be presented in a variety of
ways. Post event narratives containing misinformation can lead to the
false reporting of misled details (e.g. Gabbert, Memon, Allan, &
Wright, 2004; Searcy, Bartlett, & Memon, 2000; Wright & Stroud,
1998). Leading questions can also cue distortions in several ways. The
intensity of verbs used in the question can affect speed estimates
(Loftus & Palmer, 1974) and misinformation can be implied in
questions, for example by asking if participants saw children getting
off the bus when a bus was never shown (Loftus, 1975; Loftus, Miller,
& Burns, 1978). Others have found misinformation effects through
co-witness collaboration (e.g. Gabbert, Memon, & Allan, 2003; Luus
& Wells, 1994).
Although Davis et al. (2007) examined change blindness in an
eyewitness memory study, no known published study has been found that
has combined the techniques of IB and eyewitness memory research. In
typical eyewitness studies, participants who do not notice the critical
event are removed from the data pool. We included the individuals who
were inattentionally blind and we attempted to create false memories of
the critical event that they did not notice by presenting false
information in a post event summary of the video. Participants who did
notice the event were also exposed to the misinformation and were
expected to show misinformation effects as well.
As in all IB experiments, participants were given a primary,
attentional task to complete and were exposed to an unexpected event.
Participants watched a video portraying a food court at a local mall.
The primary task varied in the attentional set that it induced in
participants. The unexpected event was the theft of a young woman's
shopping bag by a young man. Participants in the consistent attentional
set condition were told to count shopping bags, those in the low
consistency attentional set condition were told to count shoppers
wearing blue shirts, and those who were given no instructions to count
represented the control group, which was meant to represent the type of
attentional set typically induced in eyewitness memory studies.
[FIGURE 1 OMITTED]
Participants were also given instructions that would manipulate
their level of expectancy. Some participants were told they would be
asked about content of video after they watched it (high expectancy) and
some were just told to watch it while they waited to recall a word list
(low expectancy). The high expectancy control group was most similar to
what participants in traditional eyewitness studies experience; they
knew that they would be asked about the events in the video and they
were not given a primary attentional task. After answering questions to
assess whether they were inattentionally blind, participants read a
brief summary of the theft that contained some true and some false
information before answering additional questions about the video.
We hypothesized that IB and misinformation effects would
coincide--conditions that produced higher rates of IB should have also
produced larger misinformation effects and lower accuracy. We expected
participants in the high expectancy condition to notice the theft more
often than those in the low expectancy condition because they were
expecting to be asked about the video. Those in the high expectancy
condition should also have a smaller misinformation effect because their
instructions indicated they would be asked questions after watching the
video, which should have caused them to pay more attention to the
details, increasing the chances that they would have a memory trace for
the theft. As for the attentional set manipulation, we hypothesized that
participants in the consistent attentional set condition would notice
the theft more often than participants in the inconsistent condition.
According to the attentional set theory, participants in the consistent
condition should have noticed the theft more because their task of
counting shopping bags created sensitivity for noticing shopping bags,
which matched the critical event, the theft of a shopping bag. Also, the
participants in the consistent condition should have had a smaller
misinformation effect than those in the inconsistent condition because
they were most likely to notice the theft, which is what the
misinformation concerned. The participants in the control condition
should have scored between the consistent and inconsistent groups for
dependent measures because they were not influenced to pay more or less
attention to the critical event. However, being free from counting might
make them more likely to detect the theft than if they were counting
shirts, and it might also make them more likely to notice the theft than
if they counted shopping bags simply because they did not need to devote
any attention to another task and were expecting something interesting
to occur. As for the interaction of the attentional set and expectancy,
the aforementioned pattern for attentional set was expected to hold true
for the consistent and inconsistent conditions but the control
conditions were expected to differ from each other based on expectancy.
Participants in the control condition did not count anything, so the
expectancy manipulation was expected to have a greater effect.
Participants in the high expectancy control condition were predicted to
notice the theft more often and be much less susceptible to the
misinformation effect than those in the low expectancy control
One hundred eighty-seven undergraduate students (131 female) from
Saint Vincent College participated individually in groups of up to 12.
Students were recruited from classes across disciplines. They were
randomly assigned to 1 of 12 combinations of conditions. Some
participants received extra credit for their participation.
The present study incorporated a 3 (attentional set) x 2
(expectancy) x 2 (question type) factorial design for mixed groups. The
attentional set manipulation relates to the similarity between what
participants were told to count and the critical item, the shopping bag
involved in the unexpected theft. In the consistent attentional set
group, participants were asked to count the number of individuals in the
video, keeping separate counts for those carrying shopping bags and
those without shopping bags. In the inconsistent attentional set group,
participants were asked to count the number of shoppers wearing blue
shirts and not wearing blue shirts in the video. In the control
condition, participants were not told to count anything. The expectancy
manipulation concerned whether participants were told that they were
going to be asked general questions about the content of the video. In
the high expectancy condition, participants were told that they would be
asked questions about the video's content after they viewed it, but
in the low expectancy condition participants were not told that they
would be asked about the content of the video, they were only told to
watch it. The question type refers to the misinformation that was
presented to participants in the short narrative. All participants
received misinformation about two of seven details of the theft but to
control for the variable, two different forms were used.
Materials & Procedures
After providing their written consent to participate, participants
received a packet. The first page in the packet was the word list and
participants were given 1 min to study and memorize the list. The word
list contained 20 words (see Appendix), which participants were told to
memorize. The words were checked against free association norms to
verify that they were not related (Nelson, McEvoy, & Schreiber,
2004). Participants were told that they would be given a free recall
test on the words after they watched a video. The free recall served
several purposes. First, it served to delay the recall of information
from the video. Secondly, it gave credibility to the low expectancy
control condition because the instructions to participants in that
condition implied that the purpose of the video was to delay the free
recall of the word list, thereby giving participants a reason to watch
the video without giving them reason to believe they would be tested on
the content. Participants then read the instructions pertaining to the
video they were about to watch according to the expectancy and
attentional set conditions to which they were randomly assigned.
Participants in the consistent attentional set condition received
instructions that directed them to count the number of individuals
carrying shopping bags and the number who were not, and participants in
the inconsistent attentional set condition were told to count the number
of individuals wearing and not wearing blue shirts. Participants who
were instructed to count were told to use tally marks to keep track.
Because the number of shopping bags and blue shirts were not equal and
high working memory load (Fougnie & Marois, 2007) and perceptual
load (Macdonald & Lavie, 2008; White & Davies, 2008) have been
shown to increase IB (but see Koivisto & Revonsuo, 2009) ,
participants were asked to count individuals who both met and did not
meet the criterion so that the attentional load would be consistent
After reading their instructions and being permitted to ask
questions, participants watched a 2 min and 34 s video that was recorded
in the food court of a local shopping mall. In the video a college age
man (thief) in a white t-shirt sat reading a newspaper in the foreground
with shoppers walking by or buying food from a pizza shop in the
background. At 24s a young woman (victim) placed her shopping bag in a
chair at a table adjacent to the one the young man was using and then
sat down across the table from it. She texted until 1:05 and then
casually watched the people walk by and occasionally checked her
cellular telephone. At 2:13 a friend walking buy noticed her, at which
point she stood up and they hugged. At 2:19 the thief glanced at the
women as they stood talking with their backs to the shopping bag. He
then stood up and walked past the victim's table casually grabbing
the shopping bag at 2:25 and disappearing off screen to the left at
2:27. At 2:30, the victim and friend sat down at the table with the
friend sitting in the chair where the bag had been left. At 2:33 the
victim expressed surprise that her shopping back was missing before the
video ended with a grey static screen.
After watching the video, participants completed the rest of the
packet at their own pace. Participants in the consistent and
inconsistent attentional set conditions were asked to total their
tallies. After writing as many of the 20 words from the word list as
they could recall, participants responded to 7 inattentional blindness
based questions about the content of the video. The first question asked
participants to describe, in their own words, what happened in the
video. The questions became increasingly specific, with the last
question asking participants if they noticed the theft of a shopping
bag. Then participants read a two-sentence narrative of the theft. We
selected four details to mislead participants about, but each
participant was only misled on two of the four. The accurate details are
presented in parentheses in the narrative below.
Following the narrative were 7 detailed questions about the theft.
Participants were then asked to fill out a demographic questionnaire.
Lastly, they were given an 8-item Objective Eyewitness Questionnaire
(Appendix) that asked additional questions about the theft, including
questions about the misinformation, and asked participants to rate their
confidence in the accuracy of their answers using a 4-point Likert
Several analyses were conducted to assess the hypotheses. First, to
see whether instances of IB were more likely to occur under particular
attentional set and expectancy conditions, Chi-square analyses were
conducted. Next, ANOVAs were conducted to determine whether recall
accuracy and susceptibility to misinformation were related to whether
participants noticed the theft. Third, an ANOVA was conducted to
determine whether recall accuracy was affected by attentional set,
expectancy, and information type (misled, not misled, not mentioned),
which essentially enabled us to determine if the misinformation effect
varied by attentional set and expectancy. Next, effects on confidence
and accuracy or recall were examined and finally an ANOVA was conducted
to determine whether confidence varied as a function of attentional set
and being inattentionally blind.
IB was scored by counting participants who claimed to have seen the
theft as noticing the event and those who claimed not to see the event
as being inattentionally blind. Chi-square analyses were conducted to
determine if noticing differed by conditions (see Table 1). Frequency of
IB in the low expectancy, [chi square] (2, 93) = 28.38, p < .001 and
high expectancy, [chi square] (2, 94) = 41.16, p < .001, conditions
varied by attentional set. Fisher's Exact tests revealed that in
both the high and low expectancy conditions, participants were
inattentionally blind less often in the control condition than in either
the inconsistent or consistent attentional set conditions (all p's
< .001). Differences in IB between the consistent and inconsistent
attentional set conditions were not significant for the low (p = .10)
and high (p = .064) expectancy conditions. No differences in IB based on
expectancy were found (all p's > .33), so data were collapsed
across expectancy conditions. Subsequently, the consistent attentional
set condition was found to have a lower frequency IB than the
inconsistent attentional set condition (p = .015).
[FIGURE 2 OMITTED]
How inattentional blindness was related to eyewitness accuracy
(proportion correct) and misinformation reporting was evaluated with a
factorial ANOVA for mixed groups and independent samples t-tests.
Overall, accuracy varied as a function of information type, F(2, 340) =
80.35, p < .001, [[eta].sub.p.sup.2] = .32. Accuracy for misled
information (M = .81, SD = .25) was lower than for both information not
misled (M = .94, SD = .17) and information not mentioned (M = .88, SD =
.21; both ps < .001), and accuracy for information not mentioned was
lower than accuracy for not misled information (p = .001). The
interaction of information type and IB was also significant, F(2, 340) =
16.38, p < .001, [[eta].sub.p.sup.2] = .09 As shown in Figure 2,
participants who were inattentionally blind were especially susceptible
to the misinformation (p < .001) but differences for information not
mentioned in the narrative (p < .001) and not misled (p = .023) were
also reliable. When making an error on questions pertaining to misled
information, sometimes participants gave novel responses rather than
reporting the misled information. An independent samples t-test revealed
that participants who were inattentionally blind reported the specific
misinformation 45% (SD = 38.8) of the time compared to participants who
noticed the theft who reported the misinformation just 8% (SD = 18.8) of
the time, t(130.84) = 8.09, p <.001.
Participants who were inattentionally blind to the theft were less
accurate and reported more misinformation. A mixed factorial ANOVA was
conducted to examine differences in recall accuracy (proportion correct)
by information type (misled, not misled, not mentioned in the
narrative), attentional set (control, inconsistent, consistent), and
expectancy (high, low). Information type affected recall accuracy, F(2,
332) = 79.78, p < .001, [[eta].sub.p.sup.2] = .32. Responses
pertaining to misled information were less accurate (M = .64, SD = .38)
than not misled (M = .94, SD = .17) and not mentioned (M = .88, SD =
.21; both p's < .001), which also differed from each other (p =
.001). Expectancy did not affect recall accuracy, F(1, 166) = 0.04, p =
.84. Recall accuracy of participants in the high expectancy (M = .82, SE
= .02) and low expectancy (M = .81, SE = .02) conditions did not differ.
Recall accuracy varied by attentional set, F(2, 166) = 16.12, p <
.001, [[eta].sub.p.sup.2] = .16. Accuracy in the control condition (M =
.91, SE = .02) was greater than in the inconsistent (M = .75, SE = .02)
and consistent (M = .78, SE = .02) conditions (both p's < .001),
but the consistent and inconsistent conditions did not differ from each
other (p = .45).
The only interaction that reached significance was that of
similarity and information type, F(4, 332) = 4.00, p = .004,
[[eta].sub.p.sup.2] = .05. As reported above, accuracy for misled
information was lower than for information that was not misled or not
mentioned in the narrative. As shown in Figure 3, the difference in
accuracy between misled information and the other two types of
information was greater in the inconsistent and consistent conditions
than in the control condition. The information type by expectancy, F(2,
332) = 1.38, p = .25, similarity by expectancy, F(2, 166) = 0.22, p =
.80, and information type by attentional set by expectancy, F(4, 332) =
0.56, p = .69, interactions failed to reach significance.
The previous analysis examined accuracy for misled information, but
errors included cases where participants reported misinformation (e.g.
victim ate a sandwich) and cases where a novel response was given (e.g.
the victim read a magazine). Another ANOVA was conducted on the
proportion of misinformation that was explicitly reported by
participants. Expectancy did not affect misinformation acceptance, 174)
= .932, p = .34, but similarity did, F(2,178) = 10.65, p < .001,
[[eta].sub.p.sup.2] = .11.
[FIGURE 3 OMITTED]
Participants in the control condition (M = .11, SD = .21) were less
likely to report misinformation than those in the consistent (M = .35,
SD = .38) to reach significance, F(2, 174) = .05, p = .95.
Accuracy for correct responses was coded 1 and accuracy for
incorrect responses was coded -1. This value was multiplied by the
participant's reported confidence in the particular response.
Values close to 4 represent highly confident and correct and values
close to -4 represent highly confident but wrong. Scores closer to zero
indicate lower confidence. As expected, confidence x accuracy differed
by information type, F(2, 330) = 67.60, p < .001, [[eta].sub.p.sup.2]
= .29. Responses pertaining to misled information (M = 1.16, SD = 2.46)
were lower than for both information not mentioned (M = 2.28, SD = 1.63)
and non-misled information (M = 2.99, SD = 1.33), which also differed
from each other (all ps < .001). Scores also differed by attentional
set, F(2, 165) = 19.39, p < .001, [[eta].sub.p.sup.2] = 19.
Reflecting the same pattern found in previous analyses, scores in the
control condition (M = 2.94, SE = 0.17) were lower than in both the
inconsistent (M = 1.49, SE = 0.18) and consistent (M = 1.90, SD = 0.17)
conditions (both ps < .001). However, the consistent and inconsistent
conditions did not differ from each other (p = .096). As in previous
analyses, the effect of expectancy was not significant, 165) = 0.09, p =
.76. The low (M = 2.08, SE = 0.14) and high (M = 2.14, SE = 0.14)
expectancy conditions did not differ in accuracy x confidence. Only the
interaction of information type and attentional set (see Figure 4) was
significant, F(4, 330) = 3.26, p = .012, [[eta].sub.p.sup.2] = .04 (all
other ps > .20). For each condition of attentional set all
differences between information types were significant at the .01 level
except in the control condition where the difference between not
mentioned and not misled was less reliable (p = .045). Across
attentional set conditions the control condition was higher than the
other two conditions for misled and not mentioned (all ps < .001).
Not misled scores did not differ between the control and inconsistent (p
= .058) and control and consistent (p = .432) conditions. This pattern
is similar to that found with overall accuracy except that accuracy x
confidence was lower in the two counting conditions than the control
condition, whereas for overall accuracy those differences were not
[FIGURE 4 OMITTED]
Finally, an ANOVA was conducted to determine if participants who
were inattentionally blind were less confident in their responses and to
see how this affect may have varied by attentional set. Participants who
were inattenionally blind (M = 2.62. SD = 0.68) were less confident than
those who noticed the theft (M = 3.49, SD = 0.65), 180) = 49.25, p <
.001, [[eta].sub.p.sup.2] = .22. Neither attentional set, F(2, 180) =
0.64, p = .53, nor the interaction of IB and attentional set, F(2, 180)
= 1.58, p = .21, were significant.
Fifty-one percent of the participants failed to notice the theft.
On the surface this rate appears to match rates found in the IB
literature (e.g. Simons & Chabris, 1999), however in our experiment
roughly one third of the participants had no secondary task to draw
their attention away from the unexpected event. Seventy-two percent of
the participants who did engage in a counting task were inattentionally
blind; our unexpected event may have been more difficult to notice than
those used in previous research.
Unexpectedly, the frequency of inattentional blindness did not vary
by expectancy condition. We predicted participants who were not told
that they would be asked questions about the content of the video beyond
those pertaining to the counting task would be less likely to notice the
theft. However, during debriefing many participants reported that they
did expect something unusual to happen regardless of which condition
they were in, partially because other participants in the session
received instructions to tally their counts during the video. It is
difficult to convince suspicious research participants that they are
watching a video that was obviously recorded for the experiment, rather
than a clip from a television show for example, just to pass the time.
Fortunately, we used another technique to better approximate the
attentional conditions that might be experienced by actual eyewitnesses;
we gave approximately two thirds of the participants a counting task to
occupy some of their attention.
As expected, IB did vary by attentional set. Having a counting task
reduced participants' ability to notice the theft, and when data
were collapsed across expectancy conditions the difference between the
consistent and inconsistent attentional set conditions was reliable;
participants who were watching to see whether mall visitors were
carrying shopping bags were more likely to notice the theft of a
shopping bag than participants who were attending to the color of shirts
shoppers were wearing. These results are consistent with prior findings
concerning the effects of attentional set on IB (e.g. Most & Astur,
2007; Most et al., 2001; Simons & Chabris, 1999) and more
specifically those concerning the effects of attentional sets based on
more than simple physical characteristics (Karns & Rivardo, 2009;
Koivisto & Revonsuo, 2007). Note that there was no particular reason
for participants to be attending to the bag as it was stolen because it
had appeared in the video, and likely been counted, a full 2 min prior
to the theft.
These findings have several implications for eyewitness memory
research. First, IB may reduce the number of reliable witnesses. We
argue that in real eyewitness situations witnesses are likely to be
doing or thinking about something else when the event occurs; they are
unlikely to be just watching the world around them waiting for a car
accident, a crime, or someone in a gorilla suit to walk by. In addition,
given high expectations that "something will happen" when
participants are asked to watch a video, a secondary task of some sort
is needed to better simulate an eyewitness situation. When a secondary
task is employed, we see that inattentional blindness may reduce the
number of reliable witnesses considerably. Furthermore, participants who
were inattentionally blind to the theft were less accurate on all types
of questions about it, not just those for which misinformation was
One might argue that in real eyewitness situations bystanders who
did not see the event are not considered to be witnesses by law
enforcement personnel and in the present study those who were IB were
less confident in their responses. However, cases where witnesses
initially claim not to have seen anything, or not to have been in a
position to see the event very well and then later testify with high
confidence, have been documented for decades (e.g. Loftus, 1979).
The manipulation of attentional set also affected accuracy and
misinformation reporting directly, but these effects were limited to
information that was misled in the narrative. Accuracy for the misled
information was lower in the consistent and inconsistent attentional set
conditions than in the control condition and the explicit reporting of
that misled information was greater in the consistent and inconsistent
conditions. Having a counting task reduced performance on these measures
but varying the focus of the counting task did not have an appreciable
effect. Although the effects of attentional set were strong enough to
reveal differences in IB, they did not translate into overall
differences in susceptibility to misinformation.
The limited effects of attentional set on accuracy and the high
level of accuracy for inattentionally blind participants were
surprising. Even participants who reported not noticing the theft, were
correct 79% of the time on questions about the incident for which no
information was presented in the narrative. By the end of the video, the
thief may have been very familiar to participants. He was visible from
the beginning of the video until he exited the scene with the shopping
bag. Of all the individuals appearing in the video, the thief was
present the longest and because he was in the foreground he occupied the
most screen space. Even participants who did not notice the theft were
made aware of it through the narrative. In previous research on
unconscious transference (see review and meta-analyses by Deffenbacher,
Bornstein, & Penrod, 2006) participants have identified an innocent
person who was at the scene or seen previously as the suspect.
Similarly, participants in this experiment may have described the thief
merely because he was the most familiar person from the video. In trying
to construct a memory for a theft they did not notice, they used the
information they could readily recall. To test this hypothesis in a
follow-up, an innocent person could be present for a large portion of
the video with the thief making a brief appearance.
In the present study we attempted to simulate an eyewitness
situation in a laboratory type study. In previous studies, researchers
have seldom engaged participants in other tasks that would consume
attentional resources as would be the case in a real eyewitness
situation. As Laney and Loftus (2010) suggested, the IB literature is an
appropriate place to look to learn more about how distractions might
hinder eyewitness accuracy. We were successful in replicating effects of
attentional set on IB in the eyewitness memory paradigm and found that
participants who were inattentionally blind were more susceptible to
misinformation. Despite high rates of IB, participants were very
accurate in describing the thief, which on the surface appears to
suggest IB may not have lasting effects on the accuracy of eyewitness
memory. However because the thief was on screen in the foreground for
nearly the entire video participants may have implicitly or explicitly
identified him as the thief after they were told a theft had occurred.
In a scenario where the thief is just another passerby, an innocent
bystander may be identified as the perpetrator. Our findings serve to
partially bridge the gap between the IB and eyewitness memory
literature, but also call attention to the need to consider specifically
whether IB may increase instances of unconscious transference.
Plate, Door, Green, Teach, Prime, Aardvark, Foot, Silent, Left,
Box, Sticker, Chain, Mascara, Lay, Absurd, Pen, Demand, Table, Increase,
Objective Eyewitness Questions
1. What color was the stolen shopping bag?
2. What color was the shirt of the shopping bag's owner?
3. What was the owner doing prior to being approached by her
4. What color was the shirt the thief was wearing?
5. What was the thief doing before stealing the shopping bag?
6. What was the sex of the thief? Male Female
7. In which direction did the thief walk after stealing the
Toward camera Away from camera
Note: Robert Minjock is now at the Department of Psychology,
Central Michigan University. Gina Gowen is now at the Counseling
Department, Franciscan University of Steubenville.
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Mark G. Rivardo, Kelly A. Brown, Alexis D. Rodgers, Sara V. Maurer,
Tyler C. Camaione, Robert M. Minjock, & Gina M. Gowen Saint Vincent
Author info: Correspondence should be sent to: Dr. Mark G. Rivardo,
Department of Psychology, Saint Vincent College, 300 Fraser Purchase
Road, Latrobe, PA 15650, firstname.lastname@example.org
The owner of the purple (white) shopping bag sat at a table and ate
a sandwich (read a newspaper) right before her friend approached
her. The thief of the shopping bag was wearing a green (white)
shirt and was reading a newspaper before she (he) took the bag.
TABLE 1 Frequency of Innattentional Blindness by Conditions
Control Inconsistent Consistent
Low Expectancy 4/31 25/32 18/30 47/93
High Expectancy 2/31 27/32 20/31 49/94
6/62 52/64 38/61