9605_An Examination of Inattentional Blindness in Law Enforcement

Minnesota State University, Mankato
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Theses, Dissertations, and Other Capstone Projects
2018
An Examination of Inattentional Blindness in Law
Enforcement
Gregory Lee
Minnesota State University, Mankato
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Running head: AN EXAMINATION OF INATTENTIONAL BLINDNESS IN LAW
ENFORCEMENT

An Examination of Inattentional Blindness in Law Enforcement

By
Gregory Lee

A Thesis Submitted in Partial Fulfillment of the
Requirements for Degree of
Masters of Arts
In
Clinical Psychology

Minnesota State University, Mankato
Mankato, Minnesota
July 2018
AN EXAMINATION OF INATTENTIONAL BLINDNESS IN LAW ENFORCEMENT

July 30, 2018

An Examination of Inattentional Blindness in Law Enforcement

Gregory Lee

This thesis has been examined and approved by the following members of the student’s
committee.

____________________________________
Dr. Daniel Houlihan, Advisor

____________________________________
Dr. Jeffrey Buchanan, Committee Member

____________________________________
Dr. John O’Neill, Committee Member

AN EXAMINATION OF INATTENTIONAL BLINDNESS IN LAW ENFORCEMENT

Table of Contents
Abstract…………………………………………………………………………………………….1
Introduction…………………………………………………………………………………..……2

Inattentional Blindness…………………………………………………………………….2

Inattentional Deafness……………………………………………………………………..6

Change Blindness………………………………………………………………………….7

Inattentional Blindness and Law Enforcement……………………………………………9
Methods…………………………………………………………………….………….………….11

Participants…………………………………………………………………………….….11

Materials………………………………………………………………………………….11

Procedure…………………………………………………………………………………14

Pilot Data…………………………………………………………………………………17
Results……………………………………………………………………………………………19
Discussion………………………………………………………………………………………..24

Limitations………………………………………………………………………….……28

Future Research………………………………………………………………….………29
References……………………………………………………………………………….……….31
Appendix A – Tables………………………………………………………………….…………36
Appendix B – Figures……………………………………………………………………………38

AN EXAMINATION OF INATTENTIONAL BLINDNESS IN LAW ENFORCEMENT
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Abstract

Inattentional blindness, or the inability to visually detect an unexpected stimulus while
attending to a task or situation, can have detrimental effects on those who are subject to the
phenomenon. This may be particularly true for law enforcement officers, who are often engaged
in cognitively demanding tasks that draw their attention away from potentially deadly hazards.
This study aimed to look at the effects of inattentional blindness within a group of officers of
varying degrees of experience and expertise. The officers were presented with a video-based
scenario in which an unexpected stimulus was placed. The control group was asked to attend to a
general task, while the experimental group was asked to attend to a specific and more demanding
task. Within the context of an active shooter situation, the officers’ ability to detect a large black
suitcase in a hallway during the video was assessed. Overall rates of unexpected stimuli
detection was consistent with existing literature, however detection of the scene-relevant
stimulus was lower than expected.

Keywords: inattentional blindness, memory, law enforcement, police, active shooter

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Introduction
Depending on where we focus our attention during a situation, we may be more apt to
notice or miss particular elements of that scene. For instance, focusing on how many passes
white-jerseyed players make in a basketball game results in many individuals failing to notice a
gorilla walking amongst the players (Simons & Chabris, 1999). Likewise, students engaging in a
cell phone conversation seemed to miss money hanging from a tree, even when they had to
actively avoid running right into it (Hyman et al., 2014). What would cause a person to miss
things that seem so obvious? An explanation may be found in the phenomenon known as
“inattentional blindness.”
Inattentional Blindness
Inattentional blindness is best described as the failure to detect an unexpected visual
stimulus that may be relevant or irrelevant to the task or situation being attended to (Mack &
Rock, 1998). This “blindness” can be explained by the load theory of attention (Lavie et al.,
2004), which suggests that focusing on certain tasks is subject to an individual’s ability to devote
attentional resources. These attentional resources are finite and as an individual engages in more
cognitively-demanding tasks, few attentional resources are left to process peripheral, usually
irrelevant stimuli. Inattentional blindness is the result of an individual’s inability to devote these
attentional resources to other stimuli, resulting in the stimuli going unnoticed (Cartwright-Finch
& Lavie, 2007).

As can be imagined, not all unnoticed stimuli are as irrelevant as a gorilla passing
through a basketball game. Inattentional blindness in cognitively-demanding situations can result
in serious consequences, such as surgeons not seeing misplaced surgical instruments (Hughes-
Hallett et al., 2015), radiologists not noticing unusual spots in a lung cancer screening scan
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(Drew et al., 2013), or security guards failing to see an unusual or suspicious individual on a
security video feed (Nasholm et al., 2014). Inattentional blindness can result in distracted drivers
not seeing a child about to enter traffic (Pammer et al., 2015), or an athlete not seeing an open
teammate during a big game (Memmert & Furley, 2007).

Basic studies. Most studies of inattentional blindness have been relatively rudimentary,
often involving participants focusing on a computer screen in which images or letters are flashed
for fractions of a second (e.g., Most, 2013; Most et al., 2001; Richards et al., 2009). These
studies, which test inattentional blindness in its most basic form, have found that inattentional
blindness can be influenced by cognitive biases such as attentional sets and, perhaps more
importantly, stimulus relevance (Eitam et al., 2013; Most, 2013).

Much like Simons and Chabris’ (1999) study in which individuals focusing on white-
jerseyed players were less likely to notice an all-black gorilla, Most (2013) found that when
individuals focused on a group of letters, 66% of participants noticed an unexpected letter “E”
enter and exit the screen. When individuals were instead focused on a set of numbers, only 39%
noticed the letter “E” enter their field of view. As Most (2013) explains, this is due to individuals
tuning their attention to the features of the category they were tasked to observe, in essence
forming a set of relevant features to look out for.
This relevance not only pertains to the features of the stimuli, but to the task being given
to the individual as well, as demonstrated by Eitam, Yeshurun, and Hassan (2013). The study
found that when individuals were presented with two circles of differing colors and asked to only
attend to one, they were less likely to correctly identify the color of the unattended (i.e.,
irrelevant) circle. Interestingly, Eitam et al. (2013) also found that the duration of stimulus
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presentation did not affect rates of noticing, which suggests that inattentional blindness is a result
of irrelevance rather than the amount of time a stimulus is presented.
Eitam et al.’s (2013) demonstration of the effects of stimulus relevance is particularly
important due to the fact that their study did not place a large cognitive load on the participants,
thus showing that the non-detection of stimuli may have been a result of irrelevance alone as
opposed to a lack of attentional resources. As shown by Most (2013), Eitam et al. (2013) and
others (e.g., Most et al., 2001; Simons & Chabris, 1999), stimulus irrelevance due to differing
stimulus features (i.e., attentional sets), the demand placed on the individual (e.g., “pay attention
to this, not that”), or more often a combination of the two, can result in the missed detection of
an irrelevant stimulus that is not necessarily as obvious as a gorilla walking through the scene. In
other words, any unattended stimulus can be irrelevant depending on the context in which it is
presented, even if it shares many of the same features as the attended stimuli.

Dynamic scenarios and experience. Since many early studies looked at inattentional
blindness using simple detection tasks, there has recently been a steady increase in research
utilizing more dynamic and complex visual scenarios similar to Simons and Chabris’ (1999)
well-known gorilla video. In addition, more studies have begun to look at the effects that
experience and expertise may have on the detection of unexpected stimuli. It is logical to assume
that individuals who have experience with particular scenarios and situations may be better able
to detect unexpected stimuli due to their familiarity with the task or situation. Their familiarity
with the task or scenario results in less attentional resources being used, resulting in more
attentional resources available for other peripheral stimuli.
Nasholm, Rohlfing, and Sauer (2014) looked at whether having experience watching
closed-circuit television (CCTV) footage led to better detection of suspicious individuals and
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unusual individuals (i.e., relevant and irrelevant stimuli, respectively). They used a dynamic
visual scenario that involved footage of multiple people interacting in an alleyway, during which
either a suspicious person or an unusual person (a pirate) entered and exited the scene. Despite
having experience with monitoring CCTV footage, active-duty infantry personnel did no better
at detecting the pirate in the scene than university students. What was predictive of detection,
however, was the relevance of the unexpected stimuli (the suspicious person) to the task of
monitoring for suspicious activity. Put simply, experience did not lead to better detection of the
pirate because the pirate was irrelevant to the task at hand (detecting suspicious people).
Contrary to what Nasholm et al. (2014) found, Greig, Higham, and Nobre’s (2014) study
of inattentional blindness in medical professionals found that experience did in fact have some
influence on rates of detection. Their study, involving individuals with a range of experience in
resuscitation, found that those with more experience were more likely to notice situation-relevant
changes (e.g., an oxygen tube disconnection) in a video of a staged resuscitation of a patient.
While the results of the study support the idea that experts may be less susceptible to
inattentional blindness, it is important to note that it is difficult to discern whether the rate of
detection was truly influenced by the experience of the individual or whether detection was
instead influenced by the relevance of the stimuli.
In an attempt to further understand the effects of experience on stimulus detection, Laio
and Chiang (2016) looked at Taiwanese construction workers and their ability to detect safety
hazards placed throughout a construction scene. The results of their study indicate that
experience did impact rates of detection. Specifically, the authors found that workers with more
safety training and work experience were more likely to notice subtle safety hazards throughout
the scene. Due to the fact that all of the stimuli in the scene were construction related, the results
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seem to indicate that experience may very well have some influence on detection rates, at least
for task-relevant stimuli.
Inattentional Deafness Studies
It is clear that the ability to detect unexpected visual stimuli is most likely affected by the
experience of the individual as well as the task relevance of the stimuli in question. The same
holds true for auditory stimuli. For example, Koreimann, Gula, and Vitouch (2014) demonstrated
that individuals with musical expertise and those familiar with the composition Thus Spoke
Zarathustra were more likely to notice an unexpected guitar solo inserted into the piece. In
addition, much like inattentional blindness, inattentional deafness has also been exhibited in
dynamic auditory and multimodal scenes, demonstrating that stimulus relevance plays an
important role in the detection of unexpected, irrelevant stimuli.
A study by Dalton and Fraenkel (2012) involved a 3-dimensional auditory scene that
consisted of conversations between two men and two women. Participants were asked to attend
to one of these conversations, unaware that a man would enter the scene unexpectedly and walk
around the scene stating, “I am a gorilla.” 90% of participants who were asked to listen to the
male conversation noticed the “gorilla,” while only 30% of individuals noticed the man when
listening to the conversation between women.
Wayand, Levin, and Varkin (2005) created a multimodal video scenario similar to
Simons and Chabris’ (1999) video of a group of people passing basketballs around. In this
scenario however, rather than a gorilla entering the scene, a woman enters and scratches her nails
on a chalkboard that is in the center of the room. Participants were tasked with counting
basketball passes, and despite having both visual and auditory cues, nearly 60% of participants
failed to both see and hear the woman.
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Change Blindness
Similar to inattentional blindness and inattentional deafness, most individuals are also
subject to a phenomenon known as “change blindness.” Much like inattentional blindness,
change blindness is the inability to detect generally large, obvious changes in a scene (Rensink et
al., 1997). This “blindness” is also a result of attentional focus, however the mechanisms behind
it are different from inattentional blindness and deafness. Rather than suffering from a lack of
attentional resources to devote to unexpected changes and stimuli, in change blindness the
inability to detect changes is due to a failure to remember and compare information from one
moment to the next (Simons & Rensink, 2005). Thus, unlike inattentional blindness, attention
may be placed on an object and changes to the object may go unnoticed if the changes aren’t
pertinent to the information needed at that moment.
Basic studies. Not unlike inattentional blindness, initial change blindness studies utilized
relatively basic methods to assess the phenomenon. Early studies established the existence of
change blindness by testing for participants’ ability to detect differences between certain dot
patterns (French, 1953), letter patterns (Pashler, 1988), and pictures (Friedman, 1979; Gur &
Hilgard, 1975). These studies typically presented two images separated by a blank screen
distractor for fractions of a second, with participants asked to find subtle differences between the
two images.
More recent studies have recreated these early findings, incorporating different methods
to serve as the distractor that masks the change. These distractors range from using the
participant’s own eye movements (Rensink, 1997) to mudsplashes that only cover a portion of
the changing image (O’Regan, Rensink, & Clark, 1999).
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Dynamic scenarios. Studies have even transitioned to examining change blindness in
more dynamic scenarios such as movies (e.g., Levin & Simons, 1997). These studies, often
mimicking the continuity errors seen in motion pictures, have changes that occur during a
camera pan or cut. In Levin and Simons’ (1997) study, a short video segment of a conversation
between two people was created and shown to participants. During the video, objects placed in
the scene (e.g., plates on a table) changed colors or disappeared entirely as the scene cut from
one angle to another. Overall, nine changes occurred throughout the film, yet only one in ten
participants noticed any of the changes.

Simons and Levin (1998) further pushed the bounds of dynamic scenarios by conducting
a study in which changes occurred during real life personal interactions. Participants on a college
campus were approached by an experimenter asking for directions. During their conversation,
the two would be interrupted and separated by a group of people carrying a door, during which
time the experimenter switched positions with one of the individuals carrying the door. Despite
the differences in voice and appearance of the new person talking to the participant, two-thirds to
half of participants failed to realize that they were talking to an entirely new person.
Effect of expertise. Like inattentional blindness and deafness, studies have also begun to
assess the degree to which expertise factors into change blindness. Werner and Thies (2000)
addressed this by comparing rates of change detection in a football scene between football
experts and novices. The football experts, who had familiarity with and expectations of football
scenes, were hypothesized to better detect changes in images of a football game than the novice
group who had no experience playing or watching football. The researchers found that the
experts noticed changes in the images faster than the novices, particularly when these changes
held some semantic meaning (e.g., the addition or removal of a football). This suggests that the
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experts encoded and processed relevant visual stimuli more efficiently and effectively than the
novices, allowing the experts to detect changes in 92% of trials compared to the novices’ 82%
detection rate.
Inattentional Blindness and Law Enforcement
Since experts may be susceptible to inattentional blindness, deafness, and possibly
change blindness, it is important that more research be conducted with professionals in fields that
involve high cognitive loads. One such profession is that of the law enforcement officer (LEO).
LEOs are regularly subjected to situations involving high amounts of stress (Violanti et al., 2016)
and attentional demand (Anderson et al., 2005) and are routinely depended upon to provide
information and testimony from memory. With such demands continually placed on an officer, it
is not illogical to assume that they may be susceptible to inattentional blindness and deafness.
However, law enforcement officers are trained to perceive and react to situations in a particular
way, sometimes relying upon hypervigilance and an expectation of danger. It is possible that
LEO training may have an effect on inattentional blindness and deafness such that officers are
less likely to miss unexpected stimuli, both relevant and irrelevant, in the situations they
encounter.
With current events revolving around police action and use-of-force, understanding the
potential for inattentional blindness and deafness, as well as change blindness, in LEOs may play
a vital role in understanding how officers perceive situations with high cognitive load. In
addition, the ability to detect unexpected stimuli has implications for both officer and civilian
safety. If LEOs have a better understanding of how inattentional blindness and deafness may
affect their performance in high-stress situations, they may be better able to design training to
address anticipation of unexpected stimuli in general. This in turn translates into situations in
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which officers are less likely to be caught off guard, thus lowering the risk of harm to the officer
and potential bystanders.
Simons and Schlosser (2017) attempted to look at rates of inattentional blindness in a law
enforcement sample by having both police academy trainees and experienced police officers
engage in a simulated traffic stop. The scenario involved either a cooperative or non-cooperative
driver as well as a handgun serving as the unexpected stimulus placed on the passenger side
dashboard. Simons and Schlosser found that 58% of police academy trainees and 33% of
experienced officers failed to see the handgun regardless of how the driver had acted, supporting
the notion that experts are subject to inattentional blindness of relevant unexpected stimuli in an
interactive scenario. In addition, the experience level of the officer may have played a factor in
rates of detection.
Understanding inattentional blindness and deafness in law enforcement officers also has
implications in the courtroom, where questionable police actions in the eyes of the public may be
explainable by the phenomena. While inattentional blindness and deafness should not serve as a
catch-all for police behavior, it may certainly play a role in situations in which an important
unexpected stimulus may have been missed by the officer. A prime example of this was
demonstrated by Chabris et al. (2011) when they attempted to answer the question of how police
officer Kenny Conley was able to run by a fellow officer being assaulted without actually
witnessing the event. What was found was that only 35% of participants were able to notice a
simulated three-person fight they had run by under low-light conditions similar to those
experienced by Officer Conley. Detection rates of the fight increased to between 42% and 72%
when participants passed the fight in broad daylight. Chabris et al.’s findings, while ultimately
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not influencing Officer Conley’s conviction appeal, did shed some light on how an officer may
have missed such a seemingly obvious event.
Despite the role that inattentional blindness and deafness may play in LEO behavior, little
research currently exists that looks at its effects in this population. This current study aims to
further research into this particular area by looking at whether LEOs are subject to inattentional
blindness and if so, how much their training and experience may play a role in rates of
unexpected stimuli detection.
Method
Participants and Design

A between-subjects group design was used for this experiment. One hundred and twenty
law enforcement officers (LEO) were contacted to participate via an email list maintained by a
Midwest law enforcement training facility.
It is hypothesized that significantly more participants in the control condition will detect
the unexpected stimulus (i.e., the large black suitcase) than participants in the experimental
condition. Based on existing literature (e.g., Drew et al., 2013; Simons & Chabris, 1999), it is
expected that approximately greater than 50% of participants in the control condition will see the
unexpected stimulus while less than 50% of participants in the experimental condition will see
the unexpected stimulus. A chi-square goodness-of-fit test will be conducted to determine if the
rates of detection obtained are significantly different from the expected rates of detection of the
unexpected stimulus.
Materials
In order to test for inattentional blindness, participants were shown one video of a mock
active shooter scenario in a school setting. The video contained an unexpected stimulus (i.e., a
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large black suitcase) visible midway through the video and in clear view for approximately 12
seconds.
The scenario video was recorded with a GoPro Hero5 Session handheld camera with a
wide-angle lens in 1920×1440 resolution and 60 frames per second. The video was recorded by
the primary author and was exported and trimmed using Quicktime video software on an iMac
computer. The video survey was then uploaded to the Qualtrics online survey platform.
The video duration was 46 seconds, which included a 2 second fade-to-black blank
screen at the conclusion of the scenario. The video scenario took place in the hallways and one
classroom of an elementary school (see Figure 1). Hallway 1 measured approximately 64 feet
long and 8.5 feet wide. The Open Space consisted of a 17 feet by 17 feet square and contained a
glass trophy cabinet against the back wall. Hallway 2 was identical to Hallway 1 in terms of
dimensions. Room 234 (Art Instruction) measured approximately 25.5 feet by 18 feet, with a
12.75 feet by 8.5 feet hallway entrance.
The video began in the foyer of the school entrance and proceeded down Hallway 1
where five victims were positioned. Victim 1 was positioned at the entrance of the hallway
against the right wall. Approximately 15 feet down the hallway was Victim 2, sitting against the
left wall. Fifteen feet further down the hallway was Victim 3, laying on his back in the middle of
the floor. Victims 4 and 5 were approximately 15 feet further down the hallway, with Victim 4
sitting against the right wall and Victim 5 approximately 7 feet further down sitting against the
left wall. As the camera approached Victim 4, two victims (Victims 6 and 7) rounded the corner
and entered Hallway 1. They proceeded to run down the hallway and past the camera as it
approached Victim 5.
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Once the camera exited Hallway 1 and entered the Open Space, it focused on Victims 8
and 9 who were seated in front of a trophy cabinet directly opposite of the Hallway 1 exit. The
camera then turned left and proceeded down Hallway 2 where Victims 10 and 11, approximately
22 feet from the Open Space, were positioned against the right and left walls, respectively.
Midway down Hallway 2, the camera reached the entrance to Room 234 (Art Instruction). At
this point, the camera turned left and focused on Victim 12, who was sitting against the left wall
of the Room 234 entrance, before entering the classroom. As the camera entered, it panned to the
left to provide a view of the classroom interior before panning right and stopping on the
simulated active shooter. Inside Room 234 (Art Instruction), 7 victims were present. Victims 13,
14, 15, 16, and 17 were sitting at tables, while Victim 18 was positioned against the back wall on
the floor. Victim 19 was sitting in a chair, however due to the positioning of the camera as it
entered the room, only Victim 19’s legs were in view for a very short period of time. As a result,
it was not expected that any participants would notice and count Victim 19.
As the camera approached each victim, it panned and focused on each individual,
allowing the victim to be in the center of view for approximately one and a half seconds. The
unexpected stimulus was a black suitcase and measured 30” by 22” by 10.5” (HxLxW). The
suitcase was placed diagonally in the corner of the wall outside of Room 233 such that the sides
of the suitcase were making contact with both walls of the corner and the broad face of the
suitcase faced the camera, as shown in Figure 1.
Anticipated stimulus detection rates are presented in Figure 3. According to our
alternative hypothesis, participants in the control group will notice the unexpected stimulus at a
statistically significant higher rate than the experimental group.

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Procedures
Individuals interested in participating in the experiment were provided an online link to
the survey. Upon arriving at the webpage, participants were shown a consent form and were
required to indicate whether they were 18 years of age or older and gave their consent to
participate. The consent form stated that the individuals would be participating in an experiment
designed to assess their memory following a video depicting a mock active-shooter scenario.
Due to the nature of inattentional blindness (i.e., thinking about it reduces the likelihood of it
occurring), no mention of the phenomenon was made to ensure that participants were not primed
to expect any unusual stimuli during the experiment.
Upon providing their consent, participants were then presented with an optional
demographic survey that asked for the participant’s age range, race, and gender. Responses to the
questions were optional and participants were made aware that their responses would not impact
their ability to participate in the study.
Control condition. Following the demographic survey, participants who were randomly
placed in the control condition were presented with the following instructions on screen:
The following page contains a video with sound. To ensure that you have the best
viewing experience, please check that your SCREEN BRIGHTNESS and VOLUME is
turned up. It is suggested that you watch the video with HEADPHONES.

After a short loading screen, the video will begin to play automatically. YOU WILL NOT
BE ABLE TO PAUSE OR REWIND THE VIDEO ONCE IT BEGINS. Be sure that you
are ready for the video before clicking the Next button.
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The participants were then required to click the “Next” button on screen. The next page
of the survey contained the instructions: “While watching the video, please pay close attention
to the details of the video.”
The participants were then instructed to click the “NEXT” button. The following page
contained the video scenario, along with the instructions: “Once the video ends, please scroll
down the page and click the “NEXT” button.”
The video was set to automatically play and was embedded into the survey so that
participants could not click the video to pause or rewind it. After the video concluded, the
“NEXT” button appeared at the bottom of the page that would take the participant to the question
and answer portion of the survey.

Experimental condition. Individuals in the experimental condition followed the same
initial procedure as control condition participants, however prior to the video page the survey
displayed a different set of instructions:
While watching the video, please pay close attention to the number of victims you see.
You will be asked to recall the number of victims following the conclusion of the video.
Similar to the control condition, upon clicking the “NEXT” button the participants were
taken to the video page. Neither condition allowed the video to pause, rewind, or restart at any
point during the trial.
Survey. Following completion of the video, participants in both conditions were
presented with a series of nine questions pertaining to what they had seen in the video, with one
to four questions per webpage. Participants were required to provide an answer to any open
questions before being allowed to progress to the next page and set of questions.
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The first question was designed to assess for the participant’s recollection of the number
of victims and the degree to which participants in the experimental condition followed task
instructions accurately. Question 1 asked “How many victims were present in the video?” The
next three questions were related to any unusual items they may have seen in the hallway and
increased in specificity. Question 2 asked “During the video, did you notice anyone/anything
unusual other than the victims in the hallway?” If the participant answered “No,” they were
directed to Question 3. If the participant answered “Yes,” they were then asked 2b: “Who or
what did you see?” and 2c: “What about it was unusual?” before being asked 2d: “During the
video, did you notice any other unusual items in the hallway?” If the participant answered “No,”
they were directed to Question 4. If the participant answered “Yes,” they were then asked 2e:
“What did you see?” and 2f: “What about it was unusual?” Question 3 asked “During the video,
did you notice any unusual items in the hallway?” If the participant answered “No,” they were
directed to Question 4. If the participant answered “Yes,” they were then asked 3b: “What did
you see?” and 3c: “What about it was unusual?” Question 4 asked “During the video, did you
notice a suitcase in the hallway?” If the participant answered “No,” they were then directed to
Question 5. If the participant answered “Yes,” they were then asked 4b: “Please describe the
location of the suitcase,” 4c: “Please describe the size of the suitcase,” 4d: “Please describe the
color of the suitcase,” and 4e: “Please describe anything else unusual about the suitcase.”
Question 5 asked, “If you were to see a suitcase during an active-shooter school scenario, what
would you think it might contain?” and was intended to gauge the participant’s perception of the
stimulus as a potentially deadly threat (e.g., an improvised explosive device). Questions 6 and 7
were designed to assess response integrity and guesses. Question 6 asked, “During the video, did
you notice a firearm in the hallway?” If the participant answered “No,” they were directed to
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Question 7. If the participant answered “Yes,” they were asked 6b: “Please describe the location
of the firearm,” 6c: “Please describe the size of the firearm,” and 6d: “Please describe the color
of the firearm.” Question 7 asked, “During the video, did you notice a knife in the hallway?” If
the participant answered “No,” they were directed to Question 8. If the participant answered
“Yes,” they were then asked 7b: “Please describe the location of the knife, 7c: “Please describe
the size of the knife, and 7d: “Please describe the color of the knife.” Neither a firearm nor knife
were present in the video, suggesting that positive responses were a result of either a guess or
poor visual acuity. Any participant responses indicating a positive identification of one or both
items resulted in that individual’s data being highlighted for further analysis. Question 8 asked
“Have you ever participated in an experiment like this?” and Question 9 asked “Have you ever
heard of the phenomenon known as inattentional blindness?” Similar to the previous two
questions, any positive responses to either of these questions resulted in the participant’s data
being highlighted for further analysis.
Upon completion of the survey questions, participants were then presented a screen that
thanked them for their time, revealed that the experiment was designed to assess for inattentional
blindness, provided a brief definition of inattentional blindness, and instructed the participants to
not share anything regarding the study, the video, or the study’s purpose with other participants.
Pilot Data
Prior to conducting the full experiment, a pilot test was conducted to determine which of
four video conditions provided the best opportunity for stimulus detection in the control
condition.
The videos utilized two different unexpected stimuli across the four experimental
conditions. Condition 1 and 2 used a large black suitcase that measured 30” by 22” by 10.5”
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(HxLxW). Condition 3 and 4 used a pressure cooker as the unexpected stimulus. The pressure
cooker was made of reflective stainless steel with black plastic handles and had an 11” diameter
lid (17” including the handle) and a height of 7.25”.
Condition 1 used the same large black suitcase and location that was used in the full
experiment.
Condition 2 used this same large black suitcase in the same position, this time with a
white and orange paper sign taped to the front of the suitcase. The sign measured 8.5” by 11”
with a 6” by 6” orange diamond in the center and was positioned one inch from the top of the
suitcase. The orange sign had the word “EXPLOSIVE” written across it, the number “1” in the
bottom corner, as well as a symbol representing an exploding object. Conditions 1 and 2 had the
large black suitcase in view for approximately 12 seconds.
Condition 3 had the pressure cooker placed in the same corner as the suitcase, with the
handle touching the wall closest to Room 233 and the side of the pressure cooker against the wall
adjacent to the Open Space. Due to its smaller size, the pressure cooker in Condition 3 was
visible for 9 seconds.
As the camera approached and focused on Victim 5, the unexpected stimulus was in clear
view for the first three conditions the entire time until the camera passed the stimulus.
Condition 4 had the pressure cooker placed in the Open Space, approximately 1.5 feet to
the left of Victim 9 and 1.5 feet away from the back wall (see Figure 2). The unexpected
stimulus (i.e., pressure cooker) was in clear view as the camera approached and focused on
Victims 8 and 9. The pressure cooker in Condition 4 was in view for approximately 10 seconds.
Each victim in the videos, except for Victims 6 and 7 (i.e., runners), was assigned an
injury location. The victims indicated their injury location by placing one or both hands on that
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specific body part. Injury locations were either the head, one arm, one leg, or the torso (from
neck to hips). Victims were only assigned one injury and all injury and victim positions remained
consistent across conditions. The victims were instructed to either yell for help, yell in pain and
indicate location of injury (e.g., “He shot my arm”), or remain silent throughout the entire video.
Thirty-six Minnesota State University, Mankato undergraduate students were randomly
assigned to one of the four different conditions. All participants were given the same instructions
as the control condition in the full experiment so as to allow for a higher probability of stimulus
detection, as compared to the instructions in the experimental condition. The participants were
given the same instructions and engaged in the trials in the same fashion as the full experiment.
Zero students in the first condition, one student in the second condition, zero students in the third
condition, and zero students in the fourth condition were able to see the unexpected stimulus.
These rates of detection were below expectations, wherein approximately 50% of participants
were expected to notice the stimuli. As a result, it was decided that the first condition (i.e., the
suitcase with no sign) would be used for the main portion of the study. This was decided based
on the fact that the suitcase was the largest stimulus and in view for the longest duration, thus
being the most likely to be visually noticeable. Although the suitcase with the “EXPLOSIVE”
sign was noticed by a student, it was decided that the suitcase alone was more representative of a
real life scenario.
Results
Demographics
The online survey was distributed and open to participants for twenty-eight days. A total
of 120 responses were gathered while the survey was open. 53 responses were removed from the
total for being incomplete. Multiple responses originating from the same IP address were
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considered for removal, however it was determined that multiple participants may have
completed the survey from a shared computer (e.g., a work computer), resulting in the same IP
address appearing several times. Although participants were randomly assigned to either the
control or experimental condition, the two conditions were not evenly distributed as some
individuals backed out before completing the survey. In total, 67 responses were included for
analysis, with 56.7% (n=38) in the control condition and 43.3% (n=29) in the experimental
condition.
Providing demographic information was optional and did not have any impact on the
participant’s ability to complete the online survey. The participant demographics are presented in
Appendix A – Table 1. One participant did not provide demographic information.
Data

Prior to analysis, one participant in the experimental condition answered that they had
noticed the suitcase, however when asked to describe the size, location, and color of the suitcase
the participant responded “I didn’t see it.” As a result, their response to the question of whether
they had seen the unexpected stimulus was retroactively changed to “No.” This participant also
answered “Yes” to the question of: “During the video, did you notice a knife in the hallway?”
However, when asked to describe the location, size, and color of the knife, the participant
responded “I didn’t see it.” As a result, their response to the question of whether they had seen
the knife was also retroactively changed to “No.”

Two participants in the control condition also indicated that they had seen the suitcase,
however when asked to describe the size, location, and color, the participants answered “no clue”
or “N/A.” As a result, their responses were also retroactively changed to “No” to indicate that
they had not seen the suitcase.
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Question 1 was intended to assess participants’ recollection of the number of victims
present in the scenario and whether those in the experimental condition followed specific
instructions. Mean and standard deviation for victim counts can be found in Appendix A – Table
2. A two-tailed independent samples t-test was conducted to determine whether the difference in
mean victim counts for the control and experimental conditions was significant. Levene’s test
was found to be significant (F = 6.03, p = .02), indicating unequal variances. As such,
participants in the control condition counted significantly more victims (M = 16.48, SD = 4.39)
than participants in the experimental condition (M = 14.45, SD = 1.88), t(45.44) = 2.31, p = .03.

Chi-square goodness-of-fit tests were performed to determine whether detection of the
unexpected stimulus was consistent with expected rates of detection for Questions 2: “During the
video, did you notice anyone or anything unusual other than the victims in the hallway?”, 2d:
“During the video, did you notice any other unusual items in the hallway?”, 3: “During the
video, did you notice any unusual items in the hallway?”, and 4: “During the video, did you
notice a suitcase in the hallway?”
For Question 2 in the control condition, participants did not significantly notice unusual
items or individuals any more or less than would be expected, χ2(1) = .42, p = .52. Participants
who answered “Yes” to Question 2 were then asked: “During the video, did you notice any other
unusual items in the hallway?” Responses were significantly skewed towards “No,” χ2(1) = 7.12,
p < .05. Participants who answered “No” to Question 2 were asked Question 3: “During the video, did you notice any unusual items in the hallway?” Participant responses were again significantly skewed towards “No,” χ2(1) = 3.86, p = .05. Lastly, all participants in the control condition were asked Question 4: “During the video, did you notice a suitcase in the hallway?” A chi-square goodness-of-fit test indicated that rates of unexpected stimulus detection in the control