Journal of Motor Behavior
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/vjmb20
Gaze Control and Tactical Decision-Making Under
Stress in Active-Duty Police Officers During a Live
Use-of-Force Response
Nicholas P. Murray, William Lewinski, Gustavo Sandri Heidner, Joshua
Lawton & Robert Horn
To cite this article: Nicholas P. Murray, William Lewinski, Gustavo Sandri Heidner, Joshua
Lawton & Robert Horn (2023): Gaze Control and Tactical Decision-Making Under Stress in
Active-Duty Police Officers During a Live Use-of-Force Response, Journal of Motor Behavior,
DOI: 10.1080/00222895.2023.2229946
To link to this article: https://doi.org/10.1080/00222895.2023.2229946
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Published online: 29 Jun 2023.
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Journal of Motor Behavior, 2023
# 2023 The Author(s). Published with license by Taylor & Francis Group, LLC
RESEARCH ARTICLE
Gaze Control and Tactical Decision-Making Under Stress in
Active-Duty Police Officers During a Live Use-of-Force
Response
Nicholas P. Murray1
, William Lewinski2, Gustavo Sandri Heidner3, Joshua Lawton1, Robert Horn3
1
R LTD,
Department of Kinesiology, East Carolina University, Greenville, NC, USA. ; 2Division of Research, Force ScienceV
Mankato, MN, USA.3Department of Exercise Science & Physical Education, Montclair State University, Montclair,
NJ, USA
behavioral and physiological response (Beatty & Janelle,
2020). Exposure to these emotional stimuli leads to the
activation of brain regions that are associated with affective, perceptual, cognitive, and motor processes. Further,
the emotional response can be dominated by highly arousing stimuli which can result in an increase in sympathetic
nervous system (SNS) response, including elevated skin
conductance, increased pupil dilation, elevated heart rate,
and modified visual function.
Considerable work has demonstrated the impact of
emotional regulation and heightened SNS in sport (e.g.,
Korobeynikov et al., 2016; Sessa et al., 2018). However,
only recently have researchers demonstrated the impact of
heightened SNS response on police performance (e.g.,
Andersen & Gustafsberg, 2016; Baldwin et al., 2021). In
Baldwin et al., 122 active-duty police officers performed a
realistic scenario that included lethal force to induce
stress. The investigators found that the scenario caused
elevated heart rates and visual changes including reporting
tunnel vision. The average performance rating (which
reflected a composite score from 3 measures: Deadly
Force Judgment and Decision-Making, Tactical Social
Interaction, and Crisis Intervention Team surveys) for the
officers was 59%, with 27% of the participants committing at least one lethal force mistake, with more mistakes
occurring when stress was higher. No effect was found
when comparing the level of standard police training with
cardiovascular stress reactivity or other symptoms caused
by stress. This may indicate that current training techniques do not improve an officer’s ability to operate under
stress. Similar results were found by Baldwin et al. (2019)
who collected autonomic responses and GPS positioning
of 64 police officers during duty and were able to correlate
ABSTRACT. Police officers during dynamic and stressful
encounters are required to make rapid decisions that rely on
effective decision-making, experience, and intuition. Tactical
decision-making is influenced by the officer’s capability to recognize critical visual information and estimation of threat. The
purpose of the current study is to investigate how visual search
patterns using cluster analysis and factors that differentiate
expertise (e.g., years of service, tactical training, related experiences) influence tactical decision-making in active-duty police
officers (44 active-duty police officers) during high stress, high
threat, realistic use of force scenario following a car accident
and to examine the relationships between visual search patterns
and physiological response (heart rate). A cluster analysis of
visual search variables (fixation duration, fixation location difference score, and number of fixations) produced an Efficient
Scan and an Inefficient Scan group. Specifically, the Efficient
Scan group demonstrated longer total fixation duration and differences in area of interests (AOI) fixation duration compared
to the Inefficient Scan group. Despite both groups exhibiting a
rise in physiological stress response (HR) throughout the highstress scenario, the Efficient Scan group had a history of tactical training, improved return fire performance, had higher
sleep time total, and demonstrated increased processing efficiency and effective attentional control, due to having a background of increased tactical training.
Keywords: policeuse of forcetraininguse of forcevisual control
actical decision-making is the process of reassessing
the environment and actors to control the situation
(Boulton & Cole, 2016) and is an essential element for
effective perception that is influenced by an officer’s
capability to recognize critical visual information, evaluate threat, and regulate emotions (Fallon et al., 2014).
During dynamic and stressful encounters, officers are
required to make rapid decisions that rely on effective
decision-making processes, experience, tacit knowledge,
and intuition (Penney et al., 2022). These encounters can
be potentially uncontrollable, novel, and often involve
time pressure that can lead to dire consequences, including injury or death (Andersen et al., 2016; Cohen et al.,
1998). Combined, these factors influence an officer’s
propensity to formulate efficient and proper tactical decisions, prepare, initiate, and execute a response behavior.
Emotional experiences, such as those experienced by
officers in dynamic, dangerous encounters will often cycle
through a process that includes exposure to emotional
stimuli, attention to the stimulus, appraisal, and finally a
T
Correspondence address: Nicholas Murray, Department of
Kinesiology, East Carolina University, Greenville, NC 27858,
USA. E-mail:murrayni@ecu.edu
This article has been corrected with minor changes. These
changes do not impact the academic content of the article.
This is an Open Access article distributed under the terms of the
Creative Commons Attribution License (http://creativecommons.
org/licenses/by/4.0/), which permits unrestricted use, distribution,
and reproduction in any medium, provided the original work is
properly cited. The terms on which this article has been published
allow the posting of the Accepted Manuscript in a repository by
the author(s) or with their consent.
1
N. P. Murray et al.
an officer’s heart rate to specific times/stressors. The
researchers found that the physiological stress of the officers is swayed specifically by the phase of the call and
incident factors and not officers’ years of experience.
An officer’s heart rate is often elevated due to stress
during dynamic encounters; however, this may not have
a direct impact on performance as both high and low
performance outcomes are associated with elevated cardiac levels. Nieuwenhuys and Oudejans (2011) compared
the shooting behaviors of officers under either high anxiety (targets shoot back) or low anxiety conditions (targets do not shoot back). Each participant took a pre- and
post-test, with four 1-h training sessions in between
(under high or low anxiety conditions), and a retention
test 4 months post-training. Although the two groups had
similar shot accuracy for the pretest, the post-test results
showed the high anxiety group had better accuracy than
the low anxiety group, and this continued in retention.
These findings indicate that specific high-anxiety training
can improve performance in police officers in both the
short- and long-term and can improve performance outcomes over standard police training.
The Integrative Model of Stress, Attention, and
Human Performance (IMSAHP) accounts for the effects
of stress on performance. It also explains the influence
of emotional modifications on attentional control, processing efficiency, and how emotions influence subsequent visuomotor performance. According to IMSAHP,
when a stimulus is perceived as a threat, the stimulusdriven attentional system disproportionally taxes cognitive resources, increases physiological responses, reduces
performance, modifies gaze characteristics, and results in
heightened distractibility from relevant cues (Vine et al.,
2016). These modified gaze characteristics result in
increased fixation quantities, decreases in fixation durations, and increases in the number of saccades (e.g.,
Bradley et al., 2011; Przybyło et al., 2019). Increases in
emotional and task demands can also disrupt cognitive
processing efficiency and result in narrowed attention,
increases in saccades, and heightened distractibility during which there is a delay in decision-making and motor
responses (Murray & Janelle, 2003). For example, firearms training programs lead to relatively high accuracy
during qualifying tests (above 90%), but low accuracy
during highly emotional in-field encounters (35% accuracy; Donner & Popovich, 2019). Performance effectiveness is the quality of the performance, whereas
processing efficiency is the relationship of performance
effectiveness and the amount of cognitive effort invested
in the task (Murray & Janelle, 2003). Generally, highly
emotional, and arousing states result in a decrease in performance effectiveness and increase in processing efficiency demands (Murray & Janelle, 2007). The
consequence is heightened distractibility and focus away
from relevant cues for performance success.
2
In contrast, when stressful tasks or environments are
perceived as a challenge or as an opportunity to demonstrate competence and achieve success, performance effectiveness and processing efficiency improves. Considerable
evidence demonstrates that effective visuomotor strategies
through relevant training optimizes emotional regulation
and allocation of attention to performance-relevant stimuli
(e.g., Vine & Wilson, 2011, Ferri et al., 2016).
Researchers have investigated optimal visuomotor strategies utilized by experts in both self-paced (e.g., Janelle
et al., 2000; Vine et al., 2011; Ziv & Lidor, 2015), and
externally paced tasks (e.g., Hunfalvay & Murray, 2018).
These studies consistently conclude that skilled behaviors
are marked by specific visuomotor strategies, one of which
is quiet eye duration (Helsen et al., 2000; Rodrigues et al.,
2002; Vickers et al., 2019; Vincze et al., 2022). Quiet eye
represents the final fixation or tracking gaze at a task-relevant location prior to the initiation of the final phase of
the movement (Vickers et al., 2019). Causer et al. (2010)
found that expert shotgun shooters enter a quiet eye state
earlier and remain in it for longer durations compared to
sub-elite shooters. It was also found that when experts
missed their shots, their quiet eye onset was later and duration was shorter than when they hit the target.
Extensive research has been conducted focusing on the
differences between expert and novices within a multitude
of performance environments (e.g. de Oliveira et al., 2008;
Nagano et al., 2004; Rienhoff et al., 2012; Vickers &
Williams, 2007). Multiple studies have specifically looked
at the phenomenon of visual search within the realm of
performance settings. However, most of these studies have
been conducted in laboratory environments (e.g., Moore
et al., 2012; Vine et al., 2011), while only few have been
conducted in real world or outside lab simulated settings
(Vine & Wilson, 2010; Wilson & Pearcy, 2009).
Evidence suggests that the context of testing, training,
and expert performance in policing matters. In the absence
of stressors, differences between those with and without
training may be minimized. For example, when tested for
accuracy using a Grey Man target with only a time duress,
Lewinski et al. (2015) found minimal differences between
police recruits, who passed their firearms qualifications and
were about to finish their formal police training, and novices who had never fired a handgun in their life. In contrast,
Vickers and Lewinski (2012) found performance differences between elite officers with extensive experience and
training in firearms incidents, and rookie officers as they
faced a potentially lethal encounter. The officers had to
decide if the person they were observing was a threat while
the person was pulling an item out of their waist band. If the
item was a weapon, the person was deemed a threat and the
officer had to deploy their handgun. Alternatively, if the
person pulled out a cellphone, the officer would not deploy
their handgun. Overall, the elite officers shot more accurately (74%) than the rookie officers (53.8%) and made very
Journal of Motor Behavior
Gaze Control and Tactical Decision-Making in Active-Duty Police Officers
few decision errors in the cell phone condition. The elite
officers had a longer quiet eye duration on the cue (i.e.,
assailant’s weapon/cellphone) or where the cue was going
to appear prior to firing and an increased number of fixations on the assailant’s weapon and preattack actions with
their limbs and hands. Vickers and Lewinski’s work highlighted the need for more sophisticated firearms training,
game knowledge, and practice in the role of optimal gaze
control when under extreme pressure.
Tactical decision-making is also influenced by the officer’s capability to recognize critical visual information and
estimation of threat. When an individual is in a stressful
situation there is evidence that the stress leads to behavioral
errors and high-order cognitive processes. A recent review
by Anderson et al. (2019) supports this notion in policing
and further indicates there is reduced drop in performance
under stress even when an officer has relevant training.
Based on these recent studies showing the effects of the
test and training environment, it is clear that researchers
must examine police officer performance in situations that
mimic the stress induced in realistic, threatening situations.
It is presently unknown what defines visual expertise in
officers (e.g., years of service, tactical training, related
experiences) when they encounter a threat or potential
threat. The purpose of the current study is to investigate
how visual search patterns using cluster analysis and factors
that differentiate expertise (e.g., years of service, tactical
training, related experiences) influence tactical decision
making in active-duty police officers (44 active-duty police
officers) during a high stress, high threat, realistic use of
force scenario. The role of physiological arousal on visual
search during a high stress, high threat, realistic use of force
scenario is also unclear. Rather than use an arbitrary definition of expertise, the purpose of this research was to differentiate groups via visual search patterns using cluster
analysis, to examine scenario-related gaze characteristics
including fixation location, fixation duration (ms), and saccades, and to determine factors that differentiate these
groups in a high stress, high threat, realistic use of force
scenario. Consistent with previous studies (Lebeau et al.,
2016; Mann et al., 2007), highly skilled officers defined by
cluster analysis will demonstrate fewer fixations of longer
duration on higher threat locations than lower skilled officers who are expected to exhibit more fixations for shorter
duration and more fixations on non-threat locations. That is
highly skilled officers will exhibit more efficient visual
search patterns (longer durations and fewer fixations) which
will be associated with better scenario performance.
Methods
Participants
Forty-four active-duty police officers (M age ¼
32.86 ± 7.2 years) with experience ranging between 7 wk
23 years (Mean ¼7.05 ± 6.16 years) participated in the
study.
Procedure
Upon arrival, participants completed the informed consent forms and were explained the purpose of the study
(Figure 1). Prior to the commencement of the scenario,
all participants completed a safety check of all their duty
equipment. All lethal weapons were removed from the
participants and secured at the location. Officers received
a neon yellow Velcro tag to wear on their uniform indicating visually they have been properly safety-checked.
Only the two officers who were the test participants
were evaluated within each trial; the remaining police
trainers were confederates who were actors in the scenario. Prior to starting the scenario, each officer was outfitted with an eye tracker, heart rate monitor, and their
vest with simulated weapon and simulated taser. The
scenario ran for approximately 15 min. Each scenario
included two police officer participants, and four additional pre-scripted police trainers (e.g., actors). Of the
four actors, one acted in the capacity as an off-duty
patrol officer who was involved in a crash, one was a
passenger in the assailant’s car, one was the driver
(assailant) who caused the crash and later attacked the
officers, and one was another motorist who stopped to
assist the passenger in the assailant’s car. The study
design enabled us to create nine time points of critical
events as we increased the police officers’ stress
response within this scenario. These nine points are identified below within the description of the scenario.
This scenario revolved around a citizen/assailant’s traffic crash into a police car. The assailant’s car was occupied by the actor who played the role of the assailant
and another occupant (or passenger) actor. The study
participants (two officers) on cue responded at the
request of the on-scene officer asking for backup. The
study participants entered their squad car (Time Point 1)
and were given the instruction of ‘green’ (Time Point 2)
to start the scenario. Following the officers completed a
loop driving course while receiving ‘Code 2’ (non-emergency) response from a dispatch noting the confrontation
(Time point 3). Shortly after the Code 2, the study participants received a ‘Code 3’(emergency) response from
dispatch (Time Point 4) and then were required to complete a slalom course that simulated fast driving and
sharp turns while being informed that the suspect was
becoming agitated, verbally threatening to the on-scene
off-duty officer and had a warrant out for his arrest. The
officers pass a victim (Time Point 5) and then enter the
staged part of the scenario by driving around a corner
(Time Point 6). As the study participants arrived, they
responded as their training and police experience dictated, with the goal to defuse the agitated driver and
resolve the conflict at the crash scene. Once the officers
3
N. P. Murray et al.
FIGURE 1. Methodological infographic: data collection and data analysis.
exited their car (Time Point 7), the witness role-player
became involved by attempting to communicate with the
primary responding participant officer and the hostile
driver. With both officers (study participants) involved in
de-escalation attempts toward the hostile driver, he then
became increasingly agitated and eventually acquired and
discharged a firearm at the officers (Time Point 8). The
study participants were given an opportunity to react as
their training dictated and respond appropriately by
returning fire or taking cover. Following completion of
the scenario (Time Point 9), the study participants completed the questionnaire (survey).
Measures
Eye movements were tracked using two infrared eye
trackers: Tobii 3 Eye Tracking Glasses (50 hz;
Stockholm, Sweden), and Pupil-Labs Invisible eye tracking glasses (200 hz; Berlin, Germany). The Tobii 3 has
an accuracy of .6 degrees of visual angle and the Pupil
Invisible accuracy is .5 degrees of visual angle. ECG
physiological data were acquired using a Biopac MP 150
(Goleta, CA, USA). Participants had their skin shaved
(when needed), abraded, and cleaned of oils and sweat
before three Ag/AgCl ECG electrodes were placed in an
inverted triangle over the right side of their chest. The
electrodes were secured in place with tape. Video was
obtained through the eye tracking glasses giving a point
of view (P.O.V.) of the officers, the body cameras on the
4
officers, which was a mounted Hero8 GoPro (San
Mateo, CA., USA) on the officer’s chest, and through
many high-resolution scene cameras that were positioned
to record places of interest. The videos were examined
for behavioral outcomes such as where the officers were
visually attending, the type and speed of their responses
to the changing dynamics in the scenario, and how
quickly the situation was resolved, and then were used to
compare these behaviors to the officers’ questionnaire
responses as a manipulation check.
In addition, performance was indicated by the
response to time to return fire and whether the officer
returned fire. We deemed this as an appropriate measure
as it related to their perception of the scenario and the
appropriateness of their response. That is the ones who
were more prepared to return fire were better at processing the threat and situation.
Survey/Questionnaire
The demographic survey which was completed after
the scenario finished consisted of 30 questions that
included personal variables (e.g., gender, age, height,
weight, fitness, disease status, sleep quality), education
level, and variables related to law enforcement including
duration in law enforcement, current rank, current assignment, tactical training, military training, informal training, duration of current shift, etc. The questions related
Journal of Motor Behavior
Gaze Control and Tactical Decision-Making in Active-Duty Police Officers
to law enforcement were open-ended to capture the
breadth of possibilities from our participant pool.
Data Analysis
All eye tracking data was processed through iMotions
Biometric Research Platform (v 9.3; iMotions (93), 2022).
iMotions is multi-modal software suite that allows for
comparison across eye trackers from two different manufacturers plus it allows for the collection of HR data
within the same platform. Visual search variables included
the number of fixations (defined as 100 ms), fixation
durations, saccades, and search rate or the number of fixations in a defined period of time. Area of interests (AOIs)
were established for four different areas: threat, potential
threat, witnesses, and the suspect’s truck. The truck was
included as it represented a distractor, limited visual information, and functioned as an irrelevant cue.
Hierarchical and nonhierarchical cluster analyses were
conducted using a two-step process to improve stability
in the cluster solution (Hair et al., 2010). Using standardized scores, the observed variables (fixation duration,
fixation location difference score and number of fixations) were entered into the cluster analysis. The first
stage involved a hierarchical cluster analysis using
Ward’s linkage method with squared Euclidean distance
measure to determine the number of clusters in the data.
Ward’s method is an agglomerative clustering method
based on sum-of-squares criterion and produces groups
that minimize within-group dispersion (Hair et al., 2010).
The second stage involved a k-means (nonhierarchical)
cluster analysis by specifying the most appropriate cluster solution from stage 1.
After identifying the visual profiles, we performed a
Group (2) Time (9) repeated measures ANOVAs on the
time points identified in the methods above and on heart
rate data, and separate Group (2) AOI (4: Threat,
Potential Threat, Witness, and Truck) repeated measures
ANOVAs using the dependent visual control variables
(fixation duration, fixation location, and number of fixations). Significant main effects and interactions for the
ANOVAs were followed-up with appropriate post hoc
test. In addition, we examined the relationship between
heart rate change (entering the car to arriving on the scene)
to initial arrival on the search rate and saccadic activity.
Saccadic variables included number of saccades, average
saccade duration, average amplitude, and peak saccadic
acceleration. Amplitude represents the distance traveled
by a saccade during an eye movement and peak saccadic
acceleration is the maximum velocity during the duration
of a saccade (Brunye et al., 2019).
Next, we conducted two multiple regression analyses
with one to predict the total number of fixations that officers used and to assess the relative input of various visual
targets to the overall search rate. The predictors were fixation durations on the threat, potential threat, witnesses,
and truck, while the criterion variable was overall search
rate. The second was to examine the total number of fixations that officers used and to assess the relative input of
various visual targets to the time to duration in law
enforcement. The predictors were fixation durations on
the threat, potential threat, witnesses, and truck, while the
criterion variable was duration in law enforcement. For all
analyses, test of assumptions was completed and if violated then appropriate non-parametric analysis would be
used. Significant multivariate effects (p < .05) were followed up with post hoc comparisons between cluster
groupings variables using a t-test with Bonferroni adjustments as appropriate and chi-square test for proportional
group data comparisons. Lastly, partial eta squared (g2p)
was used to determine effect sizes.
Results
Hierarchical Cluster Analysis
For the hierarchical cluster analysis, the agglomeration
schedule coefficient and the dendrogram classified either
two or three clusters as two possible solutions. A twocluster solution (an Efficient Scan Group and an
Inefficient Scan Group) was deemed the best fit according to empirical considerations (specific patterns of the
observed variables) and how interpretable the cluster
solution was. Next, a k-means cluster analysis was conducted on the standardized visual control variables for
the two-cluster solution. The nonhierarchical solution
provided support for the hierarchical analysis. To provide
a descriptive indication of the strength of our cluster
solution, we conducted a MANOVA on the multivariate
effect of cluster membership. The MANOVA revealed a
significant multivariate effect on cluster membership,
Wilks’ Lambda ¼ 0.486, F(2, 26) ¼6.69, p <.01, np2 ¼
0.514, thus indicating reasonable support for our cluster
solution. Clusters significantly differed on saccades (p <
.001), fixation duration (p < .001), and average saccadic
duration (p < .001) which further supports our two-cluster solution.
Profile of Each Cluster
Experience, wakefulness, and performance profile of
each cluster (Table 1).
In terms of performance, þ85.5% of the Efficient scan
group returned fire, whereas only 50% of the Inefficient
Scan group returned fire (Figure 2). For those officers
who returned fire, there was no significant difference in
response time to fire (p ¼ .787; Efficient scan group
M ¼ 1.18 sec, SD ¼ 0.69; Inefficient Scan group
M ¼ 1.02 sec, SD ¼ 0.75)
Heart Rate Change
There was not a significant difference in heart rate
change between the groups (p ¼ .754) and there was not
5
N. P. Murray et al.
TABLE 1. Summarizes the experience and wakefulness profiles of the efficient and
inefficient scan groups.
Factor
Experience
Duration in law enforcement (months)
Tactical traininga
Military traininga
Lethal force experience
Detective
Officer
Officer in training
No college
</¼2 Years of college
Undergraduate degreea
Masters degreea
Wakefulness (SD)
Time on shift before testing
Time awake before testing
Last sleep lengthb
How rested they felt (1–5 scale; M & SD)
a
Efficient scan group
Inefficient scan group
80.92 (69.56)
72%
28%
21.43%
14.29%
85.71%
0.00%
21.43%
42.89%
21.43%
14.29%
104.07 (77.72)
53%
10%
20.70%
24.14%
72.41%
3.45%
13.79%
51.72%
34.48%
0.00%
3.90 (3.01) hours
7.63 (3.2) hours
6.01 (1.27) hours
3.29 (0.87)
4.42 (4.71) hours
8.79 (5.13) hours
6.90 (1.58) hours
3.52 (1.27)
p<.05; bindicates not all participants answered this question.
FIGURE 2. Percentage of officers who returned fire by group. Overall 85% of the efficient scan group returned fire whereas
50% of the Inefficient Scan group did.
a significant interaction of Group Time (p ¼ .289).
However, heart rate significantly increased over time as
the officers approached and entered scenario F(8, 208) ¼
72.14; p < .001, g2p ¼ 0.742 (Figure 3). Tukey’s post
hoc test revealed that is heart rate significantly increased
6
at each point and from time point to time point from
Code 2 to the end of the scenario (Time Points 4–9).
The only time points not significantly different were
Enter Car and Enter Track (Time Points 1 and 3).
Furthermore, a modest relationship between Heart Rate
Journal of Motor Behavior
Gaze Control and Tactical Decision-Making in Active-Duty Police Officers
FIGURE 3. Heart rate change across meaningful time points; heart range from the start point where the officers were kitted
up, to the end of the scenario was 86–181 bpm (p <.05).
Change and Search Rate (r ¼ 0.43, p < .05) following
Code 3 driving occurred.
Visual Response Data
Descriptive statistics for the areas of interest, vision variables including fixation locations and fixation duration
for the two clusters were evaluated by separate repeated
measure analysis of variance. The ANOVA for fixation
location was significant, F(3, 21) ¼ 6.168, p < .05, g2p ¼
0.227. Tukey post hoc analysis for fixation location indicated significant differences between four locations:
threat, potential threat, witness, and truck AOI locations.
Overall, threat and potential threat had the highest number
of fixations compared to witness and truck AOI locations.
In addition, Group differences for total fixation duration
and AOI fixation duration were significant (F(3, 126) ¼
10.439, p < .01, g p 2 ¼ 0.199; F(3, 126) ¼ 9.108, p <
.01, gp2 ¼ 0.178; respectively) and a significant interaction
effect between cluster and AOI duration (F(3, 126) ¼
4.24, p ¼ .009, gp2 ¼ 0.168). A post-hoc analysis using a
simple effects model revealed a higher fixation duration
by the Efficient scan group on the threat, potential threat,
and witness with lower duration for the truck (Figure 4).
In addition, we examined saccadic activity (i.e., visual
search rates) including the number of saccades, average
duration, average amplitude, and peak saccadic acceleration. All these measures indicated differences in visual
search rates and scanning activity between the Efficient
Scan Group and the Inefficient Scan Group. Specifically,
the Efficient Scan Group had fewer saccades with longer
saccade durations and higher amplitudes with lower peak
accelerations (Table 2).
Multiple regression was used to predict the total number of fixations that officers used and to assess the relative input of various visual targets to the overall search
rate. Fixation durations on the threat, potential threat,
witnesses, and truck were used as predictors. The model
was significant, as indicated by F(5, 15) ¼ 3.48, p ¼
.044. Overall, 64% (R2 ¼ 0.635) of the variance in total
number of fixations was explained by this model. The
results revealed that fixation duration, t(3.248) ¼
3.163, p < .01 was a significant predictor of the total
number of fixations. The negative value of the slope
weight indicates that as officers were more fixated on
the threat, their overall search rate decreased (Table 3).
Discussion
In this study, we sought to investigate factors such as
years of service, history of tactical training, related experiences, factors that influence behavior outcomes, and
physiological arousal on visual search behavior, tactical
decision making, and performance. To challenge their
emotional control, cognitive response, and motor behavior, a complex task was developed involving all stages
of a response to a traffic incident that included a both
7
N. P. Murray et al.
FIGURE 4. Total fixation duration (SD) by area of interest by group (p < .01).
TABLE 2. Univariate test statistics for Saccadic activity variables.
Saccadic activity
Number of saccades
Average duration
Average amplitude
Peak acceleration
F
12.91
8.023
12.38
5.823
Sig.
<.001
<.01
<.001
¼.021
gp2
0.259
0.178
0.251
0.136
ESG Mean (SD)
47.85 (22.63
90.5 ms (29.26
8.00 (2.47)
7469 (9354.93
ISG Mean (SD)
99.92 (51.24)
62.60 ms (29.63
5.55 (1.84)
15720.02 (10691.63)
ESG: efficient scan group; ISG: inefficient scan group.
TABLE 3. Estimated results for model coefficients: Beta (B), Standard Error (S.E.),
T-stat (T), and levels of significance in the regression model.
Response time to weapon discharge (sec)
Fixation duration of threat
Fixation duration of potential threat
Fixation duration of witness
Fixation duration of truck
B
1.416
13.782
4.399
24.508
3.537
S.E.
2.124
4.243
5.393
12.728
3.447
T
0.667
3.248
0.816
1.926
1.026
Sig.
0.52
0.009
0.434
0.083
0.329
Multiple regression was used to predict the total number of fixations that officers used and to
assess the relative input of various visual targets to the duration of law enforcement. Fixation
durations on the threat, potential threat, witnesses, and truck were used as predictors. The model
was not significant, R2 ¼ 0.091, F(9, 30) ¼ 0.332, p ¼ .957.
high stress and high threat in a realistic use of force
scenario. In that scenario, officers were submitted to progressive complexity and danger, from the first instructions from dispatch to an escalating confrontation that
8
resulted in the discharge of a firearm against the officers
and other actors on site.
The Integrative Model of Stress, Attention, and
Human Performance was used as a framework to assess
Journal of Motor Behavior
Gaze Control and Tactical Decision-Making in Active-Duty Police Officers
the emotionally-driven changes to attentional control,
information processing efficiency, and visuomotor performance (Vine et al., 2016). In our study, both groups
experienced significant arousal when presented with the
escalating scene, evidenced by increased heart rate.
According to IMSAHP, it would be expected for both
groups to experience reduced task performance, modified
gaze characteristics, and reduced focus on relevant cues
as physiological arousal occurred concomitantly with a
disproportionate taxation of their cognitive resources. In
other words, as expected in situations in which bottomup sensory processing becomes dominant. However, the
performance of the officers with relevant training had
more efficient gaze behavior and resulted in better performance outcomes (e.g., being in a position to return
fire). We found visual search variables in the more
Efficient Scan Group to be representative of a more
planned approach. This group had fewer saccades with
longer saccade durations and higher amplitudes with
lower peak accelerations. In addition, the Efficient Scan
Group comprised of officers having a higher amount of
tactical training who were able to exert better control of
their visual searches and attentional focus, despite the
stress-inducing environment, suggesting a relationship
between relevant training, visuomotor performance, and
processing efficiency. This can be seen by the fact that
out of the Efficient Scan group 72% of the officers had
tactical training (28% had military training), whereas in
the Inefficient Scan group only 53% of the officers had
tactical training. A qualitative assessment of the tactical
training demonstrated that although varied the Efficientscan group had more training relevant to skills needed
in this use of force scenario. For example, the Efficient
Scan group had combat deployments within the military
deployment, advanced firearms training, street crime
advanced training, firearms instructor, swat school, scenario training, and defense tactics instructor. These results
indicate that officers with relevant training exhibited
lower scan rates and a greater focus on the threat, potential threat, and the witness, respectively, while the less
trained officers spent more time cycling through visual
cues and focusing on the truck, an irrelevant cue. This
supports the findings of Nieuwenhuys and Oudejans
(2011) that found officers who trained in high-anxiety
environments performed better on high-anxiety tests
than officers who trained low-anxiety environments,
regardless of police experience. The officers that did the
high-anxiety training scored similarly on their post-test
and retention test, inferring that the training has a lasting
positive impact. It is important to note that in our study,
having more real-world police experience did not correlate with having a lower scan rate, which aligns with
past research (Baldwin et al., 2021; Nieuwenhuys &
Oudejans, 2011).
Our expectation for this study was that better performances would occur with more efficient visual search patterns (fewer fixations and longer durations) and a robust
history of tactical training. The data supports this expectation as efficient search patterns commonly resulted in
better performance. This expectation was further supported by the fact that more efficient visual search pattern was a greater indicator of better performance
compared to the officer’s duration of professional experience. The increased efficiency can be seen in Figure 4
where the Efficient Scan group spent most of their time
looking at the threat, with the potential threat being
looked at second most, and had a return fire rate of 85%.
The Inefficient Scan group (lower efficiency) looked at
the truck for the majority of the time, with the threat
being looked at second most, and had a return fire rate
of only 50%. The result of increased training bettering
performance is supported by previous research (Clark
et al., 2020; Vine et al., 2011).
An increase in performance due to efficient visual
search patterns, regardless of experience, supports past
findings of visual stability resulting in a regulation of
emotions (Beatty & Janelle, 2020). Furthermore, substantial evidence demonstrates that appropriate attentional
allocation can improve emotional regulation. Attentional
focus on relevant cues can be an effective regulatory
strategy. The Efficient Scan group, although demonstrating significant arousal response (and similar to the
Inefficient Scan group) was better at managing visual
motor control and regulating emotional responses.
Deploying attention and selecting relevant visual cues
attentionally may serve as a regulator for the impact of
physiological response and mitigate emotional regulatory
processes. For example, officers in the Efficient Scan
group had considerably more controlled actions and were
better apt to engage suspect. Fewer fixations for longer
durations represents greater processing efficiency and
aligns with previous research (e.g., Murray & Janelle,
2003, Murray & Janelle, 2007, Wilson, 2008). Bell
(2004) proposed an inextricable link between cognitive
and emotional processing, with both processes drawing
from the same pool of resources. Furthermore, increased
saccadic activity results in saccadic suppression or loss
of information processing during an eye movement and
can blur vision (Schweitzer & Rolfs, 2020). Within sport
related literature highly skilled performers are better at
acquiring perceptual cues which leads to improved
response accuracy and lowered response time compared
with novices (Lebeau et al., 2016; Mann et al., 2007).
Experts are able to extract more task-relevant information and, as we noted here, tend to have fewer fixations,
but of much longer duration (Kredel et al., 2017).
Other factors that may have impacted the findings are
that the Efficient Scan group was on shift 31.2 min less
on average before testing compared to the Inefficient
9
N. P. Murray et al.
Scan group. Also, the Efficient Scan group was awake
for 1.16 h less than the Inefficient Scan group before
testing on average. Previous research has found a link
between more total time awake and worse sleep quality
leading to worse decisions by police officers, however,
the officers were affected more during non-shooting
tasks than shooting tasks (Blake & Cumella, 2015).
These findings allude to the importance some factors of
overall officer quality of life inside and outside of work
may play in their ability to respond properly in disproportionally stressful conditions. Precisely, sleeping
schedules and sleep quality may have affected, to some
degree, their ability to visually scan, process identifying
information (i.e., relevant cues), and make timely decisions based on their assessment and training recollection.
Overall, expertise levels were associated with better performance in a high stress, realistic scenario involving an
active shooter. However, tactical expertise was the main
determinant of outcomes while the mere amount of time
working as a police officer was not. Specifically, officers
that had undergone a greater amount of tactical training
were able to identify the assailant faster and maintain their
focus on him for longer periods of time while the officers
that had less previous tactical training spent more time
switching their visual focus between cues on site and spent
less time focusing on the visually compelling behavior of
the assailant. As a result, experts were able to appropriately detect the evolving threat and return fire 85% of the
time, while those with less tactical expertise only managed
to detect the evolving threat and only responded appropriately with gunfire 50% of the time. It is possible that some
of the performance decrease in participants with less tactical expertise was due to being awake, on duty for more
hours, but this assumption requires further research to
investigate it specifically.
Conclusion
Although both groups had a significant arousal
response, additional tactical training in their career led
to increased processing efficiency and effective attentional control. Selective attention represents a mechanism
through which officers filtered the abundant, and sometimes complex sensory stimuli within their environments
at any given moment. Due to the fact that attentional
resources are limited, appropriate professional training is
necessary to help officers capture salient stimuli across
and within their different operating environments that
can then direct their relevant and appropriate future
choices and behaviors.
Funding
R LTD.
This project was supported by Force ScienceV
10
ORCID
Nicholas P. Murray
2109
http://orcid.org/0000-0001-9968-
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Received December 13, 2022
Revised March 21, 2023
Accepted June 15, 2023
Journal of Motor Behavior