noise final 1 word

Running Head: DISTRACTING NOISE AFFECT ON POLICE PERFORMANCE

Police Officer’s Cognitive Performance Affected by

Background Noise During Witness Interviews

Kevin E. Hendry

Florida Gulf Coast University at Fort Myers

DISTRACTING NOISE AFFECT ON POLICE PERFORMANCE2

Police officers hold the front line in the protection and prevention of criminality. Their

patrol functions are vast, including but not limited to; vehicular traffic stops, crash investigations,

criminal mischief, burglaries, robberies, sexual assault, kidnappings, abductions, and murders.

Crime types vary in seriousness, for example; a public affray is more serious than a parking vio-

lation, a drunken driver is more serious than a petit theft, and a child abduction is more than a

public affray. A reported child abduction is one of the more critical calls for service police offi-

cers respond to. An officer’s accuracy and timely handling of the incident could mediate the dif-

ference between murder and a safe recovery.

More than half the time, child abductions are reported to law enforcement as a lesser de-

gree of service: A missing child (McKenna, 2006). Law enforcement responds to approximately

2,000 children reportedly missing each day in America (Prestridge, 2011). The Federal Bureau

of Investigations reviewed 775 cases of child abductions between 1968 and 2002 and concluded

76 percent of them were murdered within three-hours of the abduction (Office of the Inspector

General, 2009). Sixty percent of those cases had a two-hour delay from the reporter’s initial

knowledge the child was missing to the time law enforcement was notified (Office of the Inspec-

tor General, 2009). Only one-hour remained for police officers to locate and save the abducted

child. A similar conclusion was noted in a study by the Attorney General of Washington

(McKenna, 2006), who reported an average two-hour delay in making the initial missing person

report, and those murdered, they were killed within three-hours. Human trafficking has become

the fastest growing and largest criminal enterprise in the world, producing thirty-two-billion dol-

lars annually (Prestridge, 2011), so improvements are needed for the recovery and safe return of

abducted children. Accuracy and timely information decimation between reporters and wit-

nesses to police officers is one critical factor for the safe recovery of abducted children.


Deputy Sheriff K. E. Hendry served the past 12 years with the Collier County Sheriff’s

Office as a first response patrol officer, and a previous 10 years as a patrol officer in other juris-

dictions as a patrol officer. He described the following response of police officers involved in an

abduction or missing person case:

Typically, only one police officer responds to the scene of a missing person, unless the vic-

tim is a child under 12 years of age, otherwise several officers respond. In any event, there

will be a primary officer who is the initial responding officer taking the report, and sec-

ondary officers who generally canvass the area for the missing child. The primary police

officer on scene with the reporter gathers information from witnesses and bystanders. Si-

multaneously, if a single officer is on scene, he must listen and respond to the police radio

while retrieving and disseminating victim, subject, and vehicle (if any) information over

the radio to fellow officers looking for the child; and sometimes, being distracted by multi-

ple witnesses talking at the same time. If an officer fails to respond to the police radio, he

could be reprimanded (personal communication, March 30, 2013).

Any of the aforementioned distractions could lower a police officer’s reporting accuracy and

timely response due to attenuating to dual events and distractions. As previously iterated, the po-

lice officer only has a one hour window to locate an abducted child before she is likely killed.

Previous studies have examined the effects of auditory distractions on cognitive perfor-

mance (e.g., Kjellberg, Ljung, & Hallman, 2008; Hughes, Hurlstone, Marsh, Vachon, & Jones,

2013; Friedrich, Scherer, Sonnleitner, & Neuper, 2011; Roeber, Berti, Muller, Wildmann, &

Schroger, 2008; Lv, Wang, Qiu, Feng, Tu, & Wei, 2010). The dual-task model of distraction on

cognition supports the basis of this study: Performance will decline when attention is divided. In

this case, performance is the accuracy and timeliness of the police officer’s interview, and the di-


vided attention is moderated by environmental stimuli such as the police radio’s auditory tones

and a bystander’s communication.

The effect of noise on memory during speech communication was examined by Kjellberg

et al. (2008) to determine if background noise affects the recall of words and recognition of sen-

tences orally presented. Working memory (WM) capacity performance during background noise

was examined with three hypothesis; recall of words is better when they are presented without

background noise, recognition of sentences is less sensitive to the noise than the recall of words,

and the expected noise effect on recall and recognition, will be weaker for subjects with high

WM capacity (Kjellberg, et al. 2008).

Kjellberg, et al. (2008) utilized a within-subject design with two conditions: With or

without (control) background noise. Thirty-two Swedish speaking participants with normal hear-

ing (23 women and 9 men, within 18-34 years of age) conducted a word recall and a sentence

recognition test in a 20° Celsius sound isolated climate chamber. Participants were seated at a

desk in the middle of the room, while the speech and noise were presented with loudspeakers 1.5

meters in front of the subject at an angle of 45 degrees. The speech had a sound level of 64 dB,

and the noise condition had a background noise of 60dB, giving a S/N ratio of 4dB. The control

condition had a background noise of 37 dB, giving a S/N ratio of 27 dB. A laptop was used as a

visual presentation for the recognition study.

The first study examined the effects of noise on the recall of words. The within-subject

design contained two phonically balanced word lists with 50 one-syllable words being presented

orally to the participants. One list was presented with and the other without background noise in

a counterbalanced order. After the lists were presented, the participants were asked to write

down on a paper all the words that they could recall.


The second study examined the effects of noise on recognition of sentences using the

same within-subject participants. The Hagerman test for assessing the recognition of sentences

was utilized (Hagerman, 1982). Participants were shown sentences using two lists containing 10

sentences each. One list was presented in the noise condition, and one in the control condition.

Then, the participants were shown a series of 20 sentences, 10 had been previously presented,

and asked to determine if each sentence was one of the old ones or a new one. The number of

correct answers and response times (including reading time) were measured.

The third study examined the correlation between reading span scores and recall scores,

with reading span performance as the predictor. Working memory capacity was assessed with a

reading span test using the cognitive test battery TIPS (Hallgren, Larsby, Lyxell, & Arlinger,

2001). The participant’s had to decide whether the sentences were absurd or normal and to recall

either the first or the final words of these presented sentences. The number of correctly recalled

words was used as the performance measure. The final study rated effort (between 0-10) by the

participants using the Borg’s CR10 scale (Borg, 1998). It was conducted directly after the pre-

sentations of the word and sentence lists to validate the assumption that word identification be-

came more effortful by the noise.

Initially, participants performed the Reading Span Test, followed by the auditory recall

and recognition tests in the two conditions. The complete experimental session lasted approxi-

mately 40 minutes per participant between 9 AM and 4 PM. The participants were informed in

the beginning of the study that the exercise was about memory.

The results indicated the background noise condition negatively affected participant’s

memory (mean = 8.50) greater than the control condition (mean = 11.03), respectively, F(1,30) =

17.28; p < 0.01, n2 = 0.365); thus, verifying the hypothesis that recall of words is better when


they are presented without background noise. Recognition of sentences had no significant differ-

ence between groups, causing the hypothesis to be rejected: Recognition of sentences is less sen-

sitive to the noise than recall of words. The effect of noise on recall of words supported the hy-

pothesis: Noise effect on recall and recognition will be weaker for subjects with high working

memory capacity.

The Kjellberg, et al. (2008) study illustrates how a police officer’s memory is negatively

affected by background noise, and the level of affectedness is mediated by the police officer’s

WM capacity. The study also highlights how background noise has little effect on sentences be-

ing relayed to police officers, but individual words are affected (e.g., hair color, clothing descrip-

tions, height, weight, and body structure). Information relayed by witnesses are often times one

word specifics.

The duplex-mechanism account DMA model was tested using twenty-seven col-

lege students in 45 trials for extra credit, on a 2 (deviant: no deviant vs. deviant) × 2 (task-diffi-

culty: low vs. high) within-participant design (Hughes et al., 2013). Participants viewed to-be-

remembered lists of single digits shown on a computer screen one at a time. The digits were ei-

ther clearly visible (low task-difficulty) or degraded and faded (high task-difficulty). Following

the list, participants had 15 seconds to recall the list in forward serial order and write them down

on paper. Then the second phase of testing began, the to-be-ignored auditory sequence, having

two sets of 10 spoken letters auditory presented to participants over headphones at 65db (Hughes

et al., 2013). The to-be-ignored auditory sequence had 2 forms: No deviant sequence using the

same voice, and deviant sequence having the sixth letter conveyed in a different voice. With

both conditions, the onset of the to-be-ignored auditory sequence preceded the onset of the to-be-


remembered digits by 150 ms, with a 350 ms inter-stimulus interval between each spoken letter.

The trails took about 40 minutes to complete.

The background noise distracts in two ways as described by the DMA model. According

to DMA, one reason auditory distraction affects a patrol officer is the conflict between obligatory

processing of background noise and the cognitive processing utilized to perform focal tasks.

DMA, more popularly known as interference-by-processing (Hughes, et al., 2013), illus-

trates change in tonal frequency disrupts serial recall, whereas repeated same tonal frequency

does not. The second auditory distraction within DMA is attentional capture (AC), which

describes auditory stimuli having personal significance or relevance that deviates from recent au-

ditory content, then disruption in performance will occur by drawing attention away form the

prevailing task (Hughes et al., 2013).

An analysis of variance (ANOVA) was utilized on the DMA model and it identified a

main effect of deviant, F(1,26) = 18.41, MSE = 0.073, p < .001, r = .64, and the main effect of

task-difficulty, F(1,26) = 19.32, MSE = 0.071, p < .001, r = .65 (Hughes et al., 2013). Impor-

tantly, there was a significant task-difficulty × deviant interaction: F(1,26) = 15.50, MSE =

0.059, p < .01, indicating that under low-task difficulty, serial recall performance was poorer on

“deviant” and “no deviant” trials, t(26) = 6.56, p < .001, r = .44, and this difference was not ap-

parent under high task-difficulty, t(26) = .28, p = .784, r = .02 (Hughes et al., 2013).

Hughes et al., (2013) viewed the results as a top-down modulation of the allocation of se-

lective attention. During the low task-difficulty, a voice-deviant irrelevant auditory stimuli

markedly impaired serial recall, but during high task-difficulty, the effect was eliminated. The

results indicate when a police officer conducts a witness interview, and it is perceived as having

low task-difficulty, then that officer will be prone to high error rates in the presence of irrelevant


distractors (e.g., having to listen to the police radio of other dispatch calls to various police offi-

cers on other calls). It also explains that when a police officer conducts an interview that is per-

ceived as having high task-difficulty, then cognitive attention to the interview will be more accu-

rate, but will interfere with his abilities to listen and respond to the police radio. This phenome-

non aligns with previous studies that individuals high in working memory capacity are less sus-

ceptible to the deviation effect (Sorqvist, 2010) while maintaining task-goal representation (Kane

& Engle, 2003).

Using an imagery-based brain-computer-interface (BCIs), Friedrich et al., (2011) investi-

gated the impact of auditory distraction on task related performance. The study included 14 par-

ticipants to conduct ten 2-hour sessions during a 5 week period. There were two screening ses-

sions followed by 8 response sessions, with distraction used only in the second screening and the

last 2 response sessions. The study only analyzed data from the last two response sessions.

There were three conditions in the study; no distraction, passive distraction, and active distrac-

tion. The mental tasks with auditory distraction included imagery tasks in random order, includ-

ing; word association, mental subtraction, motor imagery, and spatial navigation. Auditory dis-

traction was presented during the imagery tasks in the passive and active conditions, and P300

waves, or event related potentials (ERP), responses and changes in oscillatory electroencephalo-

gram (EEG) components (event-related (de)synchronization ERD/S) were analyzed (Friedrich, et

al., 2011). The log normalized variance of the spatially EEG time series was computed from

two-second segments. The EEG was recorded from 29 Ag/AgCI scalp electrodes and referenced

to the left and grounded at the right mastoid. The participants performed the imagery tasks in six

8-minute runs, having a total of 54 trials per task, and per session, which lasted 2 hours for every

session.


The results of the dual task study revealed the performance averaged over tasks was sig-

nificantly above chance level p ≥ 0.25 ± 0.09 for 12 out of 14 users. For online performance,

participants had higher accuracies in the passive than in the active and no distraction condition,

F₂,₂₂ = 4.74, p < 0.05; n² = 0.30. The P300 occurred with shorter latency in the passive than in

the active conditions, F (1,11) = 9.51, p < 0.01; n² = 0.32. As task relevance was kept constant

across conditions of distraction, participants were most accurate in the passive condition (Noise

to be ignored). The higher performance in the passive condition than the no distraction condition

was due to an increased challenging state, however; the passive condition was less accurate than

the active distraction condition due to the dual-task model: There is a decline in performance

when the focus of attention is divided (Kok, 2001).

The Friedrich et al., (2011) study indicates distracting irrelevant-noise would increase an

officer’s accuracy by forcing him to focus more on the task at hand, but background noise that

could not be ignored (e.g., a police officer’s radio responses) would decrease his performance.

The associative comparison between the Friedrich et al., (2011) study and the distractions facing

police officers on scene maintains an interrelated compatibility, therefore; the officer’s P300 am-

plitude would diminish while latency times increase as active distractors are elevated.

Lv et al., (2010) examined the physiological processes from the effect of distraction on

working memory (WM) and selective attention in a task performance study. Fourteen college

students were randomly assigned and participated in the experiment for monetary consideration.

They were given a WM visual task of eight digits displayed in the center of a 17-inch computer

monitor. Using a between subject design, the participants were divided into two conditions

(Low-load condition and high-load condition). Those in the low-load condition had to remember

the order of three digits, while those in the high load condition had to remember the order of


seven digits. An auditory stimulus, a repetitive standard (tone of 1000hz) or environmental

novel (e.g., drill, hammer, rain, door) sound was presented in each trial at 85dB using head-

phones. Participants were required to memorize the order of digits, followed by an auditory

stimulus, and actively press corresponding keys for the digits that appeared. The experiment was

divided into 4 blocks with each block having 150 trials: Two blocks per WM load condition.

During which time, brain activity was recorded using 64 scalp sites. The epoch for ERP started

100ms before and ended 600 ms after the onset of the auditory stimulus.

The results of the study using repeated measures analysis of variance (ANOVA) for mean

accuracy and mean RTs showed that the main effects of WM load were significant: F(1,13) =

57.08, p < 0.001; RTs F(1,13) = 93.35, p < 0.001. The amplitude of Novelty-P3 in high-load

condition was smaller than that in low-load condition. The results of the ANOVA verified the

main effect of WM load for the two components were significant; MMN: F(1,13) = 6.81, p <

0.05; Novelty-P3: F(1,13) = 5.83, p < 0.05, and the main effect of the electrode were also signif-

icant (Lv et al., 2010). The MMN rose with an increase in the WM load, but the amplitude of the

Novelty-P3 was small under high-load condition.

Previous studies of ERP determined three stages of processing of task-irrelevant auditory

change; an early change detection process, a subsequent actual switching of attention toward the

auditory change, and a process refocusing attention back to the task (Lv et al. 2010). The first

stage detection process creates a mismatch negativity (MMN) component, that peaks on average

around 150-200ms from change onset (SanMiguel, Corral, & Escera, 2008). The MMN level re-

flects the automatic change detection process, which transmits an interrupt signal to higher cog-

nitive processes where there are environmental stimuli (Lv et al., 2010). The study found the

MMN amplitude increased when participants received task-irrelevant novel sounds, which indi-


cates more active change detection process when WM load was heightened. The MMN pro-

cesses are consistent with Lavie’s load theory (Lavie et al. 2005), which determined task-irrele-

vant change detection could be actively suppressed and excluded from further processing, but be-

ing dependent upon available resources of executive cognitive control functions. In the Lv et al.

(2010) study, high load on WM consumed the resources and consequently caused a failure in the

suppression. It is suspected that a competition occurred between WM task and the actual atten-

tion processing of the novel sounds for the same attentional resources. Therefore, the WM task

in the high load condition consumed most of the attenuating resources, leaving too few atten-

tional resources to processes the novel sounds, causing a decrease in Novelty-P3 amplitude.

The Lv et al. (2010) study focuses on the task-relevant and task-irrelevant modes of

sound stimulus. A single patrol officer on a scene with a witness has dual task-relevant modes of

auditory stimulus; the police radio with additional police officers communicating with him, the

witness reporting the abduction of a child, and sometimes additional witnesses speaking simulta-

neously. The Lv et al. (2010) study suggests that WM cognition has limited capacity with a per-

ceptual mechanism being what a police officer determines to be relevant or not. If a police offi-

cer perceives listening and responding to the police radio equally important as interviewing a

witness, then cognitive impairment would become dependent upon the WM capacity of the po-

lice officer in question. However, stimulus that a police officer perceives to be task-irrelevant or

less significant (e.g., secondary witness, weather, traffic conditions, telephone ringing) would in-

terfere with his cognitive performance on a plasticity variance dependent upon the police offi-

cer’s perception of load-condition of the primary stimuli. In other words, if a police officer per-

ceived the interview of a witness as a high-load condition, then less significant stimulus (low-

load conditions) would decrease the MMN amplitude, which would elicit an attenuating Novelty


P3 amplitude. The ultra small Novelty P3 amplitude would indicate the police officer having a

reduction in involuntary orienting of attention to the distraction. With that stated, the police offi-

cer’s selective attention is mediated by the officer’s level of WM.

The cognitive overload study (Kjellberg et al., 2008) revealed background noise nega-

tively affected WM and word recall had higher performance without background noise, while the

DMA model (Hughes et al., 2013) goes further in explaining that performance diminished only

during perceived low-task difficulty on deviant and no deviant trials. But Friedrich et al. (2011)

determined accuracy of performance improved with passive background noise, but showed

agreement with Kjellberg et al., (2008) and Hughes et al., (2013) in that background noise that

had to be actively responsive to declined in performance due to divided attention. In sum, back-

ground noise that a police officer does not have to respond to that does not possess task rele-

vancy will not likely diminish performance (Kjellberg et al., 2008; Hughes et al., 2013; Friedrich

et al., 2011; Lv et al., 2010). The DMA model (Hughes et al., 2013), Dual task model (Friedrich

et al.., 2011), and the load theory (Lv et al., 2010) all suggest background noise effects WM per-

formance, but all three differ in specifics. The DMA model (Hughes et al., 2013) indicates per-

formance of serial recall is negatively affected by relevant and non-relevant background noise

only under low-task difficulty conditions. The Dual task model indicates performance of WM is

increased by passive background noise, but decreased by active background noise. The Lavie’s

load theory (Lv et al., 2010) indicated background noise may impair performance if two condi-

tions are met: (1) If the police officer perceived the background noise to be relevant, and (2) if

the police officer had low WM capacity.

All occupations are not equal in responsibility. Police officers have a greater responsibil-

ity than many other careers. Within the operations of daily activity, police officers are required


to handle various calls-for-service, and they do not always carry the same responsibility. One of

the more critical calls-for-service involves the handling of an endangered missing person case.

Reports show, time is of the essence to recover the person. The longer a person is missing, the

greater the chance for death. Once a police officer is on scene, the witness is located and ques-

tioned. This is when understanding and memory of spoken information is vital. As the officer

listens to the reporter, he is also required to listen to his police radio and monitor the ongoing ac-

tivity on the radio for other patrol officers. There may be several witnesses trying to speak at the

same time. The police officer is faced with noise from other people, transportation, and other en-

vironmental stimuli that takes away from his available cognitive resources. The noise the officer

must face impedes with the accuracy of what is said by the witnesses, which could lead to devas-

tating consequences for the victim. Considering the Kjellberg et al. (2008) study, reducing noise

would allow the police officer to more accurately receive oral information from witnesses, and

transmit that information to other police officers who are looking for the victim. Theoretically,

noise effectually disrupts short and long term memory by overloading working memory.

Method

Participants

A total of 32 law enforcement officers (26 men and 6 women with an age range of 24-

52 years) from the Collier County Sheriff’s Office, who will be randomly assigned to the experi-

ment. The mean age of the participants will be 36.8 years (SD = .63). The ethnic difference of

the participants will be 83.2% White-not of Hispanic Origin, 10.8% African American, and 6%

Mexican American. All participants will be native English speakers and all will report their

hearing to be normal. All participants will volunteer for the study and will be compensated free

coffee and bagels.


Procedure

Certified law enforcement officers with a training certification administered the study.

The affect of noise on police officers during witness interviews, an experimental between-subject

design will be conducted with two conditions, with or without background noise (Noise and

Control condition). Each participant will be dispatched to a mock facility (empty & vacant build-

ing) consisting of three confederates (witnesses). Participants in the Noise condition maintained

auditory listening to their police radios (continually airing communication) at 85 dB and the mi-

crophone attached to the collar on the police officer’s uniform, including responding to dispatch

checks every 3 minutes. As the police officer speaks to confederate 1 in the noise condition,

confederates 2 and 3 will speak to each other with a S/N ration of about 5 dB less than confeder-

ate 1, and within the same distance to the police officer as confederate 1. Confederate 1 in the

noise condition will orally state to the participant thirty identifiable features and information of

an abducted missing child.

In the control condition, the participants police radio will have no radio traffic emitting

from it and the dispatcher will not ask the participant for status checks. Also, confederates 2 and

3 will be present, but will remain silent. Confederate 1 will orally state the same thirty identifi-

able features and information of an endangered missing person as in the noise condition.

Once confederate 1 completes the list of descriptor words, the participant will write down

all words the can be remembered (dependent variable). The results will be evaluated by an inde-

pendent-measures test to determine the mean difference. If supported, the results will indicate a

significant difference between the mean differences, thus demonstrating a negative relationship

between noise and the police officer’s cognitive accuracy during witness interviews.


Useful methods of combating unnecessary noise being developed would allow greater ef-

ficiency in handling child abduction cases, which would save precious lives. For example, when

law enforcement determines a call-for-service is a child abduction case, then a secondary police

officer (if available) should accompany the primary officer on scene to provide the following as-

sistance: First, handle all police radio traffic for the primary officer. Second, separate other wit-

nesses from the general area of the primary officer and the witness being interviewed.

Discussion

By having a secondary police officer on scene to reduce background noise for the pri-

mary officer, the communicated information about the abducted child’s description, and possibly

the suspect and his vehicle’s description, will be more accurately and timely conveyed to the var-

ious additional patrol officers in the district to canvass neighborhoods and attempt to locate them

the victim and suspect. Saving lives is the primary focus in law enforcement, and constant atten-

tion to improving performance and success should always a motive of any police agency.

This study does not address the effects of background noise in other facets of police offi-

cer duties. Thus, future studies are needed to identify other environmental background noises

that degrade performance of police officers. This study has far reaching implications in the field

of law enforcement. For example, this study suggests that background noise negatively affects

the cognitive performance under high load conditions which could include; shooting situations,

basic interviews, noise inside police vehicle while writing reports, phone conversations, and tac-

tical decisions during a physical altercation. This study presented empirical data from several

fields of psychology (e.g., Cognitive psychology, physiological psychology, experimental psy-

chology) that constructively provides greater support for the environmental psychology perspec-

tive on distracting noise affects on police officer and witness intercommunication.


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