Part 1
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part 2
Psychology Journal
Psychologists publish their research in journals that meet the requirements of using the scientific method of research.
The goal of this assignment is for you to become familiar with psychological research by first going to the American Psychology Association website and then searching through journals to find an article of published primary research that interests you. Do not choose a literature or review of the research article.
Watch the video to https://www.youtube.com/watch?v=ZoYeSM0VI7U&feature=youtu.be
PART 3
Step 3
Copy and paste the document below titled Becoming Acquainted with Research onto a word document onto your desktop. Save it and give it a title.
Answer each question pertaining to your chosen research article. You are now writing your report. Your report will be the question and answer document you are now completing.
Becoming Acquainted with Psychological Research
What is the name of your journal?
For whom does it seem to have been written? For example, is it directed toward a special kind of psychologist? Does it include articles that would be of interest to educators or others outside the field of academic psychology? If so, list several titles.
Choose a representative research article whose title interests you.? Write the name of its title and briefly explain why it interests you.
How long is the article?
List the major sections of the article as defined by the heads.
Does the author state the hypothesis of the research study? Write the hypothesis in the author’s words.
Write the hypothesis in your own words.
Who made up the study population?
Does the article contain a section on the method used in conducting the study? Describe the method.
STOP HERE: IF YOUR ARTICLE DOES NOT HAVE A SECTION ON THE METHODS DO NOT GO ANY FURTHER. ?YOU NEED TO DO ANOTHER SEARCH FOR AN ARTICLE INVOLVING EXPERIMENTAL RESEARCH
Which of the methods of scientific research described in your psychology textbook under Research Methods is used?
Is there a discussion of the significance of results?
Summarize the significance of the results in your own words.
What conclusions are reached in your article?
What is your reaction to the research article? For example, were there sections that you found difficult to understand? Were there sections that seemed very scientific? Are you convinced of the conclusions? Why or why not?
Summarize the article in your own words.? How did it benefit you and how might it benefit us if we were to read it?
THE ARTICLE MUST BE IN YOUR OWN WORDS AND NOTHING COPIED FROM THE ARTICLE. DO NOT USE ANY TECHNICAL LANGUAGE IN YOUR REPORT. MAKE IT SIMPLE; SO SIMPLE THAT YOUR BEST FRIEND CAN READ YOUR REPORT AND UNDERSTAND IT!!!
Do Not Use Acronyms!! -20 Points if acronyms are used
PART 4
SAMPLE OF THE ASSIGNMENT
Scientific Journal + Article
Becoming Acquainted with Psychological Research
1. What is the name of your journal?
The name of the journal I chose my journal assignment from is Journal of Experimental Psychology: Applied.
2. For whom does it seem to have been written? For example, is it directed toward a special kind of psychologist? Does it include articles that would be of interest to educators or others outside the field of academic psychology? If so, list several titles.
I can see this particular article being utilized by quite a few different people. For example this article would be excellent for a driver’s education instructor. This article would even make a wonderful teaching tool for parents of young drivers in order to emphasize the importance of giving the roads and driving conditions their utmost attention. Overall I feel that this article could have advantages to every person who reads it, not only teachers or parents but everyone that drives on our streets and highways.
3. Choose a representative research article whose title interests you. Write the name of its title and briefly explain why it interests you.
The title of the article I chose to acquaint myself with is “Passenger and Cell Phone Conversations in Simulated Driving”. The reason I chose this particular article is because it hits home, it is relative to me and my family. I must confess that I am guilty of talking on the cell phone or having in depth conversations with my passengers while driving my vehicle. The times when I am not on the phone or when I am driving alone I notice other drivers talking on their cell phones and also having conversations with their passengers. Not only did this article appeal to my because of my driving habits but also because I know that society in whole participate in these behaviors as well. This article demonstrates the marked decrease in response time and concentration that is needed to truly be a safe and defensive driver on the roadways, something that I and all drivers should consider paramount for our safety and the safety of others. One of the many hats I wear is that I volunteer as a Texas State Licensed E.M.T. with a local volunteer fire department and see what really happens when that response time and concentration of drivers is interfered with. There have been scenes when thoughts of my own family flash in my mind and even though I see the ramifications of what this article covers, these habits are among the hardest to break.
4. How long is the article?
The study titled “Passenger and Cell Phone Conversations in Simulated Driving” is approximately 7 ½ pages long with an additional 1 ½ pages dedicated to references.
5. List the major sections of the article as defined by the heads.
“Passenger and Cell Phone Conversations in Simulated Driving” include the sections of:
A. Considering Distracted Driving Impairment With Greater Specificity
B. Allocation of Attention and the Distracted Driver
C. Conversing
D. Method
a. Participants
b. Stimuli and Apparatus
c. Procedure
d. Measures
e. Design
E. Results
a. Driving Performance
b. Conversation
F. Discussion
G. References
6. Does the author state the hypothesis of the research study? Write the hypothesis in the author’s words.
The author does state a hypothesis for the research study and in their words, “This study examines how conversing with passengers in a vehicle differs from conversing on a cell phone while driving”.
7. Write the hypothesis in your own words.
This study will demonstrate, by use of simulated driving, how driving acuity becomes markedly deficient when drivers utilize cell phones while driving as opposed to carrying on conversations with passengers in the same vehicle.
8. Who made up the study population?
The study population included 96 adults who ranged in age from 18 years old to 49 years old with 20 years of age being the average age. Of the participants 47 were women and 49 participants were men. All the participants fit into the profile of having normal to corrected-to-normal vision acuity, normal color vision, and had a valid driver’s license from the state of Utah.
9. Does the article contain a section on the method used in conducting the study? Describe the method.
The study population was chosen and the experiment was thoroughly explained to them and their acknowledgement was verified by a signed informed consent. The facilitators of this experiment acquired the necessary driving simulator that was manufactured by L3 Communications I-Sim. The simulator was loaded with a database consisting of a 24-mile multilane beltway to include on and off-ramps, overpasses, and two-lane traffic in both directions. A maximum speed limit of 65 miles per hour was implemented and visibility was programmed to be optimal.
The participants were familiarized with the simulator by using three 5-minute simulated driving scenarios. The scenarios included driving at night in a rural area, another situation was driving in a downtown area involving minimal navigation around various traffic barricades, and the last was daytime highway driving. After every participant was familiarized with the simulator one participant was randomly selected to drive and the other participant, bases on experimental conditions, was either the passenger or talking on the cell phone to the driver from a different location.
The participants were assigned to either speaker or listener and were asked to share a story that they had not discussed in the past. The study consisted of a single-task assignment and a dual-task assignment. The single task assignment only involved the driver driving the vehicle and the dual-task assignment involved the driver either talking on the cell phone or talking to a passenger in the same vehicle.
Several different measurements were taken of driving performance under various circumstances. The measure of operational level was based on how well the participants stayed in the center of their lane without lateral movements and various drifting. In the tactical level speed and following distances were analyzed. The strategic level involved analysis of the participant’s ability to follow instructions included in a navigation task, whether or not they were able to take the correct exits.
10. Which of the methods of scientific research described in Chapter 1 is used?
The article “Passenger and Cell Phone Conversations in Simulated Driving” was conducted using the experiment method of scientific research. The experiment method was used to establish the cause-and effect relationship between the driving conditions of using the cell phone or conversing with passengers. The independent variables in this experiment were the use of the cell phone for the driver of the vehicle and the conversations taking place while driving. The dependent variable is identified as the driving ability of the driver without the introduction of the cell phone or conversation taking place in the vehicles.
11. Is there a discussion of the significance of results?
Yes, the article did include a discussion regarding the significance of the results.
12. Summarize the significance of the results in your own words.
“Passenger and Cell Phone Conversations in Simulated Driving” pointed out that the average age of driving in the cell phone simulation was 19.6 years of age and the average in the conversation simulation was 20.1 years of age. Although the dyad differed by 1 participant, it did point out that the initial differences in driving performance could, in fact, be contributed to the differences in actual driving experience. This article also pointed out that the fact that they were actually measuring, card drift, was greater with drivers involved in cell phone conversations than with conversations with passengers in the same vehicle. They did not notice much, if any, change in the driving speed but a significant difference in the actual following distance with users of the cell phones. Perhaps this could be because the users of the cell phones know that when they are on the cell phones they need the extra distance in order to have more time to react to traffic situations. As far as navigation success goes, the drivers who carried on cell phone conversations were four times more likely to fail the task at hand compared to those in the passenger conditions. It was also uncovered that those involved with conversations with passengers in the same vehicle made more referenced to current traffic conditions and thus were more cognoscente of what was actually happening on the road.
13. What conclusions are reached in your article?
It is concluded in this article that although there were differenced in the operational, strategic and tactical levels that conversation data suggests the probability that passengers take a more active role in supporting the driver. The passengers pointed out driving situations that the driver may have missed, similar to having an extra set of eyes on the road for you. Whereas when driver’s using the hands free devices were essentially on their own when driving and also had additional disadvantages because they were less accurate in their driving acuity, navigation skills, and reaction times as far as exiting when they should have because they were distracted by the use of their cell phones.
14. What is your reaction to the research article? For example, were there sections that you found difficult to understand? Were there sections that seemed very “scientific?” Are you convinced of the conclusions? Why or why not?
Reading this article was definitely an eye opening experience, not only did it specifically point out the quantitive decline in driving acuity but it also, for me, reiterated the potential dangers that my behaviors can bring about. I feel safe in assuming that society is aware of the dangers of talking on the cell phone when driving or carrying on conversations while driving but this study gives proven results of the dangers. To have the measurements equivalent to driving intoxicated was astounding.
There were several references in the measurements section that contained quite a few different formulas that were used to compile the data. I found myself reading over that section a few times to understand exactly what and how they were measuring the data that had been gathered. It was this section that I found to be very “scientific” and the only section that I feel that the layperson may have trouble understanding. Through all the reading and information that I gathered from this article I am convinced that the conclusion reached is accurate. It not only makes sense on a personal level but with the quantitive results that were presented gives little leeway to the contrary.
15. Summarize the article in your own words. How did it benefit you and how might it benefit us if we were to read it?
“Passenger and Cell Phone Conversations in Simulated Driving” was a study that investigated the difference between talking to passengers in the same vehicle and carrying on conversations utilizing a hands free cell phone device. By utilizing a specialized driving simulator the participants were exposed to several different driving scenarios in the form of operational, tactical, and strategic levels of driving. The authors presented the information in a professional manner, taking into effect the differences between age groups and driving experiences. The authors gave enough information for the experiment to be reproduced by supplying the readers with specific information about the simulator used, the age demographic of the participants, the system used to familiarize the study group with the simulators and the different driving scenarios. The authors provided all the necessary formulas that they utilized when gathering their data and eventually reaching the measures that they arrived at.
Not only did the authors present all the information on how they conducted their research they provided concrete information on how the study group performed under each driving circumstance. They presented the information in ways that could be informative to anyone who reads the article. The article will give the readers proof that driving while on the cell phone, even a hands free unit, provides certain hazards to the driver and those on the road with them. It would be beneficial to those who read the article to modify their driving habits when it comes to conversing on the cell phones as opposed to conversing with their passengers in the same vehicle. They will see that passenger conversations aid in the process of navigating and being aware of the different driving conditions.
Journal of Experimental Psychology: Applied 2008, Vol. 14, No. 4, 392–400
Copyright 2008 by the American Psychological Association 1076-898X/08/$12.00 DOI: 10.1037/a0013119
Passenger and Cell Phone Conversations in Simulated Driving
Frank A. Drews, Monisha Pasupathi, and David L. Strayer
University of Utah
This study examines how conversing with passengers in a vehicle differs from conversing on a cell phone
while driving. We compared how well drivers were able to deal with the demands of driving when
conversing on a cell phone, conversing with a passenger, and when driving without any distraction. In
the conversation conditions, participants were instructed to converse with a friend about past experiences
in which their life was threatened. The results show that the number of driving errors was highest in the
cell phone condition; in passenger conversations more references were made to traffic, and the production
rate of the driver and the complexity of speech of both interlocutors dropped in response to an increase
in the demand of the traffic. The results indicate that passenger conversations differ from cell phone
conversations because the surrounding traffic not only becomes a topic of the conversation, helping
driver and passenger to share situation awareness, but the driving condition also has a direct influence
on the complexity of the conversation, thereby mitigating the potential negative effects of a conversation
on driving.
Keywords: shared attention, driver distraction, cell phone conversation, passenger conversation
Driving is a complex perceptual and cognitive task. There is
ample evidence that driving performance is negatively affected by
simultaneously conversing on a cell phone. Previous studies found
that cell phone use impairs the driving performance of younger
(Alm & Nilsson, 1995; Briem & Hedman, 1995; Brookhuis, De
Vries, & De Waard, 1991; Brown, Tickner, & Simmonds, 1969;
Goodman et al., 1999; McKnight & McKnight, 1993; Redelmeier
& Tibshirani, 1997; Strayer, Drews, & Johnston, 2003; Strayer &
Johnston, 2001), and older drivers (Alm & Nilsson, 1995; Strayer
et al., 2003). These impairments have been studied using a wide
range of methodological paradigms including computer-based
tracking tasks (Strayer & Johnston, 2001), high-fidelity simulation
(Strayer et al., 2003), driving of vehicles on a closed circuit
(Treffner & Barrett, 2005), on-road studies (Crudall, Bains, Chapman,
& Underwood, 2005), and epidemiological studies of car
crashes (McEvoy et al., 2005; Redelmeier & Tibshirani, 1997).
The level of impairment is comparable to being intoxicated at a
blood alcohol level of .08 (Strayer, Drews, & Crouch, 2006).
Considering Distracted Driving Impairment With
Greater Specificity
To understand the implications of performing a secondary task
while driving, it is useful to apply a conceptualization of the
driving task that can guide the analysis of performance deficits. In
his task analysis of driving, Groeger (1999) described three levels
of performance (see Michon, 1979, 1985, for similar proposals).
The first level of performance is an operational or control level,
which involves elements that serve the task of keeping a vehicle on
a predetermined course. A deficit at this level is shown, for
example, in a reduction of lateral control, that is, the vehicle may
drift to the side of the road. A number of studies demonstrated that
this operational level is negatively affected by performing an
additional task like conversing on a cell phone (Alm & Nilsson,
1995; Haigney & Westerman, 2001; Stein, Parseghian, & Allen,
1987).
The second level of performance involves skills needed for
maneuvering the vehicle in traffic. This level is called tactical
behavior and examples for deficits at this level are approaching
other vehicles too closely or ignoring approaching vehicles while
turning left at an intersection. Studies that have found deficits on
this level of driving performance describe changes in speed
(Burns, Parkes, Burton, & Smith, 2002; Horberry, Anderson,
Regan, Triggs, & Brown, 2006), changes in acceleration (Strayer
& Drews, 2006), and delayed reaction times (Consiglio, Driscoll,
Witte, & Berg, 2003) when drivers are engaged in a cell phone
conversation. The characterization of driving behavior as “sluggish”
(Strayer et al., 2003) refers to both operational and tactical
levels of driving behavior with driving performance changing such
that drivers drive and accelerate slower and show longer reaction
times when braking (see Drews & Strayer, 2008; Svenson &
Patten, 2005, for reviews).
The third level involves more executive, goal-directed aspects of
driving and reflects strategic performance (Barkley, 2004). Examples
for problems at this level are failures in the execution of
navigation tasks or trip-related planning tasks. Currently, there is
only indirect evidence that deficits on this level can be observed
when drivers converse on a cell phone. In their simulator study Ma
and Kaber (2005) measured situation awareness—a precondition
Frank A. Drews, Monisha Pasupathi, and David L. Strayer, Department
of Psychology, University of Utah.
Portions of the data presented in this paper have been previously
presented at the Annual Human Factors and Ergonomics Conference and
been published in the proceedings to this conference (for further reference,
see Drews, Pasupathi, & Strayer, 2004). We thank two anonymous reviewers
for their helpful comments that significantly improved this article.
Correspondence concerning this article should be addressed to Frank A. Drews,
Department of Psychology, University of Utah, 380 South 1530 East, Room 502,
Salt Lake City, UT 84112. E-mail: [email protected]
Journal of Experimental Psychology: Applied Copyright 2008 by the American Psychological Association
2008, Vol. 14, No. 4, 392–400 1076-898X/08/$12.00 DOI: 10.1037/a0013119
392
for strategic performance—of drivers conversing on a cell phone
while driving compared to a group using an adaptive cruise control
system. The authors found that the use of a cell phone while
driving significantly reduced driver situation awareness and significantly
increased the perceived mental workload relative to no
phone and adaptive cruise control conditions. The application of
Groeger’s (1999) framework highlights a gap of empirical work
investigating the strategic level of performance of drivers engaged
in a cell phone conversation. Thus, at this point it is unclear if the
deficits observed on the operational and tactical level also extend
to the strategic level, or if this level of performance is unaffected
by a cell phone conversation. Based on the assumptions of Michon
(1979, 1985), lower level deficits ought to affect higher level
performance, and we would expect the suggestive findings of Ma
and Kaber to be evident in a task that is more representative of
typical driving.
Allocation of Attention and the Distracted Driver
Most work on driver distraction focused on the assessment of
the impairment rather than on a delineation of the cognitive mechanisms
underlying deficits in driving performance. The small
number of studies that has focused on this theoretically important
question point to a reduction in attention directed toward the
driving task as partly responsible for the deficits. Strayer et al.
(2003) examined the hypothesis that the observed impairment
could be attributed to a withdrawal of attention from the visual
scene resulting in a form of inattention blindness (i.e., a fixated
object is not being processed resulting in either an incomplete or
no mental representation of the object). Their findings indicated
that cell phone conversations impaired both implicit and explicit
recognition memory of visual information even when participants
had fixated upon it. Strayer et al. suggested that the impairment of
driving performance resulting from cell phone conversations is
mediated, at least in part, by reduced attention to visual inputs in
the driving environment. More evidence was presented recently by
Strayer and Drews (2007) demonstrating a reduction in the amplitude
of the P300 as a result of a cell phone conversation in
response to the onset of braking lights of a car that had to be
followed. The P300 component of event-related brain potentials
(ERP) is sensitive to the attention that is allocated to a task
(Sirevaag, Kramer, Coles, & Donchin, 1989), and has been shown
to allow discrimination between levels of task difficulty, decreasing
as the task demand increases (Kramer, Sirevaag, & Braun,
1987). Finally, more evidence for deficits in allocation of attention
comes from investigations of scanning behavior of traffic scenes.
McCarley et al. (2004) showed that conversations result in higher
error rates for change detection and higher numbers of saccades to
locate a changing item. The authors also found reduced fixation
times under dual-task conditions and interpret this as evidence that
a conversation while scanning traffic scenes impacts the peripheral
guidance of attention.
To summarize, the allocation of attention to the driving task is
central to the issues related to driving performance deficits observed
in the context of cell phone use. Thus, the literature appears
to suggest that nearly any task that diverts attention away from the
driving task will cause impairment. Indeed, supporting this assertion
are epidemiological studies (see McEvoy et al., 2005; Redelmeier
& Tibshirani, 1997) that indicate that the relative risk of
being in a motor vehicle accident quadruples when a driver converses
on a cell phone (i.e., odds ratio of an accident when
conversing on a cell phone is 4.2). By contrast, other epidemiological
studies (Rueda-Domingo et al., 2004; see also Vollrath,
Meilinger & Kru¨ger, 2002) have found a strikingly different pattern
for situations in which an adult passenger is in the vehicle. In
particular, when drivers have a passenger in the vehicle, the
relative risk of a motor vehicle accident is lower than when the
driver drives by him or her self (i.e., the odds ratio of an accident
with a passenger in the vehicle is 0.7). Given that in many
instances the passenger and the driver are conversing, these findings
appear to be at odds with the suggestion that any task that
diverts attention away from driving causes impairment. What
accounts for the seemingly paradoxical finding that a conversation
on a cell phone interferes with driving, whereas having a conversation
with a passenger in the vehicle improves driving performance?
Are differences in the allocation of attention partly responsible
for these differences?
How passenger and cell phone conversations differ in their
implications for attention and driving performance is a question of
theoretical and applied importance. It is of theoretical importance
because a comparison between cell phone and passenger conversation
revolves around the similarities or differences between the
two contexts’ impact on the attentional resources of a driver. In
this paper we suggest that the different contexts affect the ability
to allocate attention to a task differently, that is, the allocation of
attention is not independent of contextual variables, even if the
task at the onset seems identical. The question is also of applied
importance because it may help to understand better what contexts
have an impact on a driver’s ability to allocate attention to the task
of driving.
Conversing
From one vantage point a conversation is a conversation. Conversations
require attention from their participants for monitoring
the topic and content, coordinating turn taking, and so on (Clark,
1996). Thus, all conversations are presumably diverting attention
from a driving task and should create at least some impairment.
An alternative perspective, drawn from psycholinguistics, emphasizes
conversations as joint activities that involve shared attention
from all participants, and as dynamic activities that unfold
over time (Clark, 1996). This perspective emphasizes that participants
in a conversation move forward in the joint activity of
conversing by adding to their shared understandings of what is
being talked about. This process is called grounding (Clark &
Schaefer, 1989) and it involves establishing that all parties in a
conversation share relevant knowledge, beliefs, and assumptions.
It also includes awareness of the current context that provides
many cues that can aid in grounding, such as shared visual attention
(Richardson, Dale, & Kirkham, 2007) and shared awareness
of distractions. The critical difference between a cell phone conversation
and an in-vehicle conversation revolves around this
shared awareness of the driving context. That shared awareness
leads to the prediction that in-vehicle conversation will not have
the same detrimental impact on driving performance that cell
phone conversations have. It also opens the possibility for invehicle
conversation to have a positive impact on driving performance,
as is suggested by epidemiological data. Moreover, in
CONVERSATIONS IN SIMULATED DRIVING 393
pointing to conversation as a joint activity unfolding over time, it
suggests two nonexclusive proposals about how conversations
affect the allocation of the driver’s attention to the driving task.
One is simply that an in-vehicle passenger responds to the demands
of the driving context by reducing demand for the conversation
task (e.g., by changing the production rate—a modulation
hypothesis, see Gugerty, Rakauskas, & Brooks, 2004). The second
is that the passenger adopts the driving task as part of the overall
joint activity in which driver and passenger are mutually engaged.
In both cases, the assumption is that this is not likely or possible
for a cell phone conversational partner because they do not have
direct access to the real-time driving conditions.
Another point about this perspective on conversation bears
mention, and it is that many tasks employed to simulate conversation
in studies of cell phone use while driving suffer from serious
ecological validity concerns. Some investigators used putative
conversations in which the participants and a confederate alternately
generated a word and the other person had to generate a
word that began with the last letter of the previous spoken word
(Gugerty et al., 2004). Treffner and Barrett (2004) had participants
perform summations or categorizations. Others identified topics of
interest for the participant by questionnaire and had an experimenter
converse with the participant about such topics (Strayer et
al., 2003). These approaches are limited because they fail, to a
larger or smaller extent, to mimic the coordinated, joint activity
features of naturalistic conversations. In a meta-analysis, Horrey
and Wickens (2006) found that more naturalistic conversations
produced greater interference with driving than did more “synthetic”
information processing tasks, suggesting a greater engagement
for the former. Although not a central aim of this study, we
made a serious effort to develop a conversational task that was
truly applicable to the applied context. Following Bavelas, Coates,
and Johnson (2000), close-call stories as the topic of the conversation
were used in studying the impact of conversations on
driving. Bavelas et al. defined close-call stories as stories about
times when your life was threatened. The advantage of using such
close-call conversations is that they involve the kinds of stories
that are often told among friends and produce a conversation that
is engaging. In addition, unlike in other studies in which at least
one of the partners of the conversation was a confederate, we asked
participants to bring friends with the intention of having them
converse about previously untold close-call stories.
Few authors have studied how passenger conversations affect driving
performance. In their on road study, Crundall et al. (2005) provided
initial evidence that passenger and driver responded to changes
in the cognitive demand of driving when playing a “competitive
[word] game between driver and the partner” (Crundall et al., 2005,
p. 201) that simulated a conversation. For example, passenger
conversations were suppressed during more demanding urban
driving and there was no impact of the driving context on the
conversation during cell phone conversations. It appears as if
the cell phone task imposed a cognitive load independent of the
cognitive demand resulting from the driving conditions, making it
likely that the driver’s cognitive limits were exceeded.
Gugerty et al. (2004) investigated the impact of passenger
conversations on driving performance in a low-fidelity driving
simulator. To simulate a conversation the authors used a word
game task in which the participants took turns saying words with
the constraint that a new word had to begin with the last letter of
the word spoken by the partner. Gugerty et al. tested driving
performance by assessing the driver’s situation awareness for the
surrounding traffic but also measured performance on the verbal
task. Overall there was no evidence that passengers slowed the
verbal task more than remotely communicating participants, and in
Experiment 1 the opposite effect was found, despite the fact that
only the passengers shared visual information about the driving
conditions. Also, the verbal interaction negatively affected situation
awareness in both the passenger and the cell phone condition,
equally impacting a precursor for strategic performance.
More interesting, Amado and Ulupinar (2005) reported a negative
impact of passenger conversation on a driving surrogate: The
authors compared the impact of a hands-free cell phone conversation,
a passenger conversation, and a control condition on attention
in a peripheral detection task that simulated driving. To
simulate the cognitive demand of a conversation, the authors asked
participants questions of low or high complexity. Both simulated
conversation conditions had a similar negative impact on performance
in a peripheral detection task as compared to the control
condition. The lack of a difference between the cell phone conversation
condition and the passenger conversation condition is
notable. One potential reason for the absence of a difference is that
in this study the conversation pace was kept constant artificially
not allowing for modulation. Moreover, the perceptual detection
task is much less complex than the driving task, indicating data
limits in this study.
The limited literature on cell phone and passenger conversations
suggests that modulation (i.e., slowing) of a conversation
is possible, and may occur under natural driving conditions.
However, one of the problems of the existing studies is that the
conversations were highly scripted and often simulated only the
cognitive demand of a conversation. Driving performance
seems to be affected by passenger conversations by reduced
situation awareness and a reduction in the ability to detect
peripheral objects. It appears that there is no difference between
passenger conversations compared to remote conversations in
their negative impact on driving performance.
In the present paper we examined the impact of cell phone and
passenger conversations on driving performance, applying
Groeger’s (1999) conceptualization to guide the operationalization
of driving. Consequently, we used measures of driving performance
that reflect the operational, the tactical, and the strategic
level of driving behavior. In addition, we examined features of the
conversation that shed light on how conversations on cell phones
and conversations with a passenger differ in ways that bear on
attention allocation. We hypothesize that a passenger—provided
he or she has at least minimal driving expertise—monitors the
driving environment. Consequently, when a driver faces an increasing
demand of the driving task, both passenger and driver
may respond by reducing the cognitive demand of the conversation.
These changes can manifest themselves in switching the topic
of the conversation to the driving conditions and the surrounding
traffic (e.g., by pointing out potential hazards) that directs the
driver’s attention toward the surrounding traffic. Also, it is possible
that a reduction of the production rate of speech or its complexity
reflects a response to increases in the cognitive demand for
the driver.
In sum, the goal of this research is to increase our understanding
of how conversing on a cell phone while driving compares with
394 DREWS, PASUPATHI, AND STRAYER
conversing with a passenger while driving. This research uses
naturalistic conversations and measures driving performance at the
operational, tactical, and strategic levels, and also focuses on
measures that reflect changes in the dynamics of the conversation.
Method
Participants
Ninety six adults were recruited in a total of 48 friend dyads and
received course credit for participation. Participants ranged in age
from 18 to 49 with 20 being the average age. Forty-seven participants
were women and 49 participants were men. All participants
had normal or corrected-to-normal visual acuity, normal color
vision (Ishihara, 1993), and a valid Utah driver’s license.
Stimuli and Apparatus
A PatrolSim™ high-fidelity driving simulator, manufactured by
L3 Communications I-Sim (Salt Lake City, UT, USA) was used in
the present study (see Figure 1). The simulated vehicle is based on
the vehicle dynamics of a Crown Victoria® model with automatic
transition built by the Ford Motor Company.
A freeway road database simulated a 24-mile multilane beltway
with on- and off-ramps, overpasses, and two-lane traffic in each
direction. Participants were driving under an irregular-flow driving
condition (Drews, Strayer, Uchino, & Smith, in press). The
irregular-flow driving condition can be characterized as a situation
in which other vehicles, in compliance with traffic laws, changed
lanes and speeds. This traffic requires the participant to pay attention
to the surrounding traffic as opposed to a situation in which
the driver can minimize the attentional requirements and the cognitive
demand by driving exclusively in one lane of travel. In
addition, slow-moving vehicles were sometimes unsuccessfully
attempting to pass vehicles on the left side, significantly slowing
down the overall traffic flow. The speed limit was 65 mph.
Visibility in all scenarios was optimal.
Procedure
After providing informed consent, participants were familiarized
with the driving simulator using a standardized 15-min adaptation
sequence. The adaptation sequence consisted of three 5-min
driving scenarios, one being located in a rural area at night, another
one located in a downtown area, involving some minimal navigation
around traffic barricades, and a final scenario located on a
highway with optimal driving conditions at daytime. After familiarization,
one participant of a dyad was randomly selected to drive
the vehicle, the other, based on experimental condition, was either
the passenger or talking on the cell phone to the driver from a
different location. The assignment of speaker and listener was
counterbalanced over driver and nondriving interlocutor, and the
speaker provided the close-call story. Participants were instructed
to provide a story they had not shared with the partner in the past.
In the single-task condition, the driver was instructed to drive
safely and to follow all the traffic rules. In addition, in the dualtask
condition they were instructed that their task was having a
conversation about a close-call story with their friend who was
either seated next to them as a passenger or conversing on a cell
phone. Finally, the drivers were instructed to leave the highway
once they arrived at a rest area located approximately eight miles
after the beginning of the drive. The passenger/cell phone interlocutor
was instructed to participate actively in the conversation
and told that the driver had the task of leaving the highway when
approaching a rest area. In the dual-task portion of the experiment,
half of the driving participants were either conversing on a cell
phone or talking to a passenger while driving; in the single-task
condition, participants were driving only. The order of the single
and dual-task conditions was counterbalanced and the assignment
to cell phone and in-person conversation was randomized. The
individual driving sequences (single/dual task) took about 10 min
to finish. The entire experiment took approximately 60 min to
completion.
Measures
Driving performance. Multiple measures of driving performance
were taken, distinguishing between measures dealing with
the operational level, the tactical level, and those reflecting more
strategic processes involved in driving. A measure of the operational
level was how well participants stayed in the center of the
lane without lateral movements and drifting. For this purpose, we
defined the lane center of the road and calculated the root mean
standard error (RMSE) between center and the center position of
the car. On the tactical level, we analyzed speed and following
distance. Speed was measured as the average speed of the driver
for the road segment they were driving until they reached the rest
area exit, whereas following distance was measured as the average
distance between the driver’s car and a car that was directly ahead
of them. On the strategic level of performance we were interested
in participants’ ability to follow the instruction of a navigation
task—more specifically— did they take the correct exit?
Conversation. The transcribed conversations between interlocutors
in the dual-task conditions were coded by two independent
Navigation task
10
15
20
25
passenger cell phone
number of participants succeeding
Figure 1. Frequency of successful task completion in the navigation task.
CONVERSATIONS IN SIMULATED DRIVING 395
coders. Though the instruction for participants was for one person
to tell a story about close calls, in all cases after a short time both
participants were lively engaged in the conversation. The coding of
the conversations focused on the number of references to traffic,
intercoder-reliability Pearson’s r(47) _ .92; who initiated the
reference (driver and nondriver; Cohen’s kappa(47) _ 1), and the
number of turn takes with reference to the traffic event after a
reference to traffic was made, intercoder-reliability Pearson’s
r(47) _ .98. All conversations were analyzed from transcripts of
the conversations by trained coders who were blind to the condition
under which the conversation took place.
The rationale for analyzing traffic references was that referring
to the surrounding traffic is an attempt to create shared situation
awareness and indicates support for the driving task. The number
of turn takes after a reference to traffic was made was analyzed
because it is a reflection of the willingness of both partners to
engage in a conversation about traffic rather than the close-call
story. Included in this analysis were only turn takes with statements
about the event that provoked the initial traffic reference.
A second analysis focused on the impact of the driving environment.
Because the impact on driving has been well documented
in the past (e.g., Brookhuis et al., 1991) this analysis focuses on the
impact of traffic complexity on the conversation. For this purpose
two independent coders coded the traffic as low or moderately
demanding, intercoder-reliability Cohen’s kappa(47) _ .98. Low
demanding traffic was defined as a situation in which the participant’s
vehicle was surrounded by maximally one vehicle (either in
front, behind, or on the left lane), in which a situation of moderately
demanding traffic involved more than one other vehicle in
close proximity to the participant’s vehicle. For both types of
driving situations, the speech production rate of the driver and the
interlocutor in syllables per second was analyzed. The production
rate of the driver and the passenger in this context reflects the
degree to which the cognitive demand imposed by the traffic
context has an impact on the conversation, potentially leading to
some modulation of the conversation (see Berthold, 1998; Mu¨ller,
Gro_mann-Hutter, Jameson, Rummer, & Wittig, 2001). As an
additional measure, the number of syllables per word for the driver
and the interlocutor was analyzed. The number of syllables per
word is thought to measure the complexity of an utterance
(Berthold, 1998). Production rate and complexity of utterance are
used to test the hypothesis that both conversation partners in the
passenger condition adjust their conversation in response to
changes in the cognitive demand of the traffic imposed on the
driver, reflecting implicit collaboration on the driving task (see
Crundall et al., 2005). Due to the lack of situation awareness of the
interlocutor on a cell phone, modulation is unlikely in the cell
phone condition.
Design
The design of the study was a between-subject design with
dual-task condition (cell phone vs. passenger conversation) as a
between-subjects factor. Each participant’s driving performance
was also assessed in the single-task condition (driving only). To
control for any between-subject variability we analyzed driving
behavior using the difference scores between single- and dual-task
performance for each participant.
Results
Driving Performance
The following analyses of driving performance include data
from 41 dyads (21 passenger conversation) due to technical problems
with data collection in the driving simulator. Counterbalancing
of the task order for both conditions was not affected by this
data loss, because these dyads had identical task sequences. All of
the following driving performance analyses that compare the cell
phone and passenger conversation use difference scores between
the single- and dual-task condition for each participant, thus reflecting
the difference in impact of the two dual-task conditions.
The use of difference scores was indicated because the initial
analyses revealed some minor differences in single-task driving
performance between groups (see Table 1). Analyses of the demographic
variables revealed that the average age of driving
participants in the cell phone condition was 19.6 years (range 18 to
23) and in the passenger condition was 20.1 years (range 18 to 26).
In the cell phone condition, 10 female and 10 male drivers participated,
whereas in the passenger conversation condition, 11 female
and 10 male drivers participated. Thus, it is possible that the initial
differences in driving performance as reported in Table 1 can be
attributed to slight differences in driving experience.
Operational level of driving performance. The first analysis
focused on the drivers’ ability to stay in the center of the lane
without drifting sideways. Focusing on the RMSE between actual
vehicle position and center of the lane, we analyzed the differences
between cell phone and passenger conversation condition using a
Table 1
Means and Standard Deviations for Lane Keeping, Driving Speed, and Distance for Both
Experimental Conditions and Single and Dual Task
Passenger Cell phone
Single task Dual task Single task Dual task
M (SD) M (SD) M (SD) M (SD)
Lane keeping (RMSE) 0.4 (0.8) 0.4 (1.0) 0.5 (0.5) 1.0 (0.9)
Mean speed (mph) 63.8 (4.2) 63.9 (3.8) 65.8 (3.5) 65.9 (3.7)
Mean distance (meters) 72.3 (27.4) 62.1 (21.0) 63.9 (17.8) 85.3 (47.0)
Note. RMSE _ root mean standard error; mph _ miles per hour.
396 DREWS, PASUPATHI, AND STRAYER
t test. The analysis revealed a significant difference between conditions,
t(39) _ _2.1, p _ .05, Cohen’s d _ 0.7, with drivers
showing a more pronounced tendency to drift during cell phone
conversations compared to the passenger conversation condition
(see Table 1).
Tactical level of driving performance. We used a t test identical
to the one described above to analyze the differences for
average speed. The analyses revealed no changes in driving speed,
t(39) _ .1 in both conditions (see Table 1).
The next analysis focused on the distance drivers kept between
their own vehicle and vehicles ahead of them. The t test revealed
a significant difference between the two conditions, t(39) _ 2.4,
p _ .05, Cohen’s d _ 0.8, with following distance being greater in
the cell phone condition (see Table 1).
Strategic level of driving performance: Navigation. The last
part of the analysis of driving performance focused on behavior on
the strategic level (i.e., successfully accomplishing the driving task
by exiting the highway at the rest area). Figure 2 shows the number
of participants who finished the task successfully. Analyzing task
completion for cell phone conversation and passenger conversation
condition revealed a difference between the two conditions,
_2(1, N _ 40) _ 7.9, p _ .05, w _ 0.6: drivers in the cell phone
condition were four times more likely to fail task completion than
drivers in the passenger condition.
Conversation
References to traffic and turn taking. The transcripts of the
conversations were analyzed for references to traffic and number of
turns taken following an initial traffic reference that still centered on
the traffic topic. The latter indicates the extent to which the driving
task became a conversational topic in its own right, temporarily
superseding the close-call stories. The number of traffic references
in the passenger conversation condition and the cell phone conversation
condition are shown in Table 2. Clearly, fewer references
to traffic were made in the cell phone condition, t(46) _ 3.0, p _
.01, Cohen’s d _ 0.9.
To determine who initiated the reference to traffic, we analyzed
the number of initializations made in the cell phone conversation
condition and the passenger conversing condition using t tests. The
number of references by the driver did not differ, t(46) _ 1.7, p _
.1, although there was a reliable difference in the number of
references initiated by the nondriving interlocutor, t(46) _ 2.4,
p _ .05, Cohen’s d _ 0.7; with fewer references initiated in the
cell phone condition.
The next analysis focused on the number of turns between the
interlocutors who continued conversing about traffic after an initial
reference to traffic was made. The number of turns for both
conditions is shown in Table 2. Overall more than twice as many
turns occurred in the passenger condition as compared to the cell
phone condition, t(46) _ 3.4, p _ .01, Cohen’s d _ 1.0.
Production rate and complexity of speech. The final analyses
focused on the production rate of the driver and interlocutor and
the complexity of their speech (see Table 3) as a function of the
demand of the driving conditions. Because driving condition (low
and moderate demand) is added to the analyses as independent
variable analyses of variance (ANOVA) were performed. In moderately
demanding driving conditions, the production rate of the
driver decreased when talking to a passenger but increased when
talking on a cell phone as indicated by a significant interaction
between driving condition and conversation condition, F(1, 39) _
4.3, p _ .05, partial _2 _ 0.1. No differences were observed in the
nondriving interlocutors production rates for conversation condition,
demand, and the interaction (the F values for the main effects
and the interaction were all _ .16 and effect sizes, partial _2 _
.03). Analyzing the complexity of speech indicated that both
driver, F(1, 43) _ 5.5, p _ .05, partial _2 _ 0.1 and interlocutor,
F(1, 43) _ 4.8; p _ .05; partial _2 _ 0.1, responded to an increase
in the cognitive demand of driving by reducing the number of
syllables per word. Neither the main effect of conversation condition
nor the interaction reached significance.
Discussion
The present study investigated how conversing with a passenger
differs from talking on a hands-free cell phone in terms of its
impact on driving performance at the operational, tactical, and
strategic level and how the dynamics of the conversations are
affected by contextual factors elicited by the driving task.
Michon (1979, 1985) suggested that lower level deficits of driving
behavior ought to affect higher level performance. The present study
provides evidence in support of this hypothesis under dual-tasking
conditions. For the cell phone condition, the data suggest that deficits
on lower levels of driving behavior also are present (though in
different form) at higher levels. For example, drivers conversing on a
cell phone showed more lane keeping variability (operational level)
than participants conversing with a passenger.
Figure 2. Participant talking on a cell phone in the I-Sim driving
simulator.
Table 2
Means and Standard Deviations of References to Traffic and
Turns for Both Experimental Conditions
Passenger Cell phone
M (SD) M (SD)
References 3.8 (2.4) 2.1 (1.6)
Turns at speech 19.2 (13.8) 8.6 (6.7)
CONVERSATIONS IN SIMULATED DRIVING 397
Similarly, on the tactical level, cell phone drivers do differ from
participants in the passenger condition on some measures (e.g.,
changes in following distance). However, no changes in driving
speed were observed in the dual-task condition, seemingly at odds
with previous findings of slower driving cell phone drivers (e.g.,
Strayer & Drews, 2007; Strayer et al., 2003). One explanation for
this discrepancy could be procedural differences, with studies
demonstrating slower driving speed using a car following paradigm
as opposed to the free driving paradigm that was used here.
On the strategic level of performance, cell phone drivers performed
poorly at the navigation task. Two nonmutually exclusive
explanations can be provided for this deficit: First, drivers conversing
on a cell phone may experience problems with keeping the
intention of exiting at the rest area in working memory, or second,
drivers may not sufficiently process information from the driving
environment (exit signs). Some support for the latter hypothesis
comes from studies demonstrating inattention blindness in cell
phone drivers (Strayer et al., 2003). The performance of participants
in the passenger conversation condition indicates that these
drivers may have paid more attention to the navigation task, partly
due to the passenger. Indeed, examination of the video taped
driving segments found several instances in which the passenger
helped the driver navigate to the rest area.
Overall, the study clearly documents that relative to a driving
only condition, cell phone use negatively impacts lane keeping,
increases the headway and leads to an impairment in a navigation
task while passenger conversations have only little effect on all of
the three measures.
Contrary to prior suggestions (e.g., Crundall et al., 2005;
Gugerty, Rando, Rakauskas, Brooks, & Olson, 2003), we did not
find evidence that in-vehicle drivers and passengers were better
able to modulate their production speed to match changes in the
complexity of the driving task. Instead, we found some evidence of
modulation of the complexity of speech, indicated by syllablesper-
word, in response to the demand of the driving task. Thus, the
present findings suggest a process of modulation, but this process
is not tied to production rate as it is in the original proposal of
Gugerty et al. (2003). Contrary to Gugerty et al. this study reports
an increase in performance on the strategic level in the passenger
condition, which should not have been observed if situation awareness
had been negatively affected in both conversation conditions.
Also, quite surprisingly drivers conversing on the cell phone
increased their production rate when talking on the cell phone,
which is contrary to the predictions of the modulation hypothesis.
More interesting, this happened even as those drivers in the passenger
condition tended to reduce their production rate.
Some of the differences in findings may be explained by important
methodological differences related to the study of conversation
behavior in the context of driving. To realistically measure
the impact of a conversation on driving performance, tasks that are
not conversation tasks but traditional information processing tasks
may miss central compensatory mechanisms of conversations, thus
underestimating a conversations complex nature. Also, the use of
low-fidelity simulations in passenger conversations may have a
significant impact on the process of grounding in a conversation,
thereby not reflecting a conversation’s context that is central for
processes of allocation of attention. One issue in naturalistic conversation
revolves around managing turn-taking—and these differential
changes in production rates for drivers, changes that
depended on the nature of the conversation—may reflect differences
in how participants attempted to manage turn-taking. Drivers
on cell phones may have attempted to dominate the conversation to
avoid having to engage in speech comprehension, whereas with
in-vehicle partners, it may be easier to relinquish control, given
that the partner can be relied on to accommodate with his or her
contributions.
The conversation data suggest that passengers take an active
role in supporting the driver as indicated by passengers more
frequently talking about the surrounding traffic. It seems likely that
a passenger supports the driver by directing attention to the surrounding
traffic when perceived necessary. As mentioned above,
this conclusion is also supported by the analysis of the video
recordings (in some cases passengers mentioned the exit sign or
pointed to the exit). Thus, the higher driving performance in the
passenger condition is due in part to the shared situation awareness
between driver and passenger due to grounding. This interpretation
is also supported by the reliable difference in traffic references
initiated by the passenger and the cell phone interlocutor.
In addition, the results provide evidence for even more subtle
support between interlocutors. In both dual-task conditions, there
is evidence that interlocutors respond to an increase in the cognitive
demand from the driving context by reducing the complexity
of their utterances. This difference seems to be driven by changes
in the complexity of utterances by the driver because the conversation
partner on the cell phone cannot be aware of changes in the
driving environment.
Table 3
Means and Standard Deviations for Production and Complexity for Driver and Passenger in
Both Experimental Conditions and Low Demand and Moderate Demand Driving Scenarios
Passenger Cell phone
Low demand Moderate demand Low demand Moderate demand
M (SD) M (SD) M (SD) M (SD)
Driver Productiona 4.1 (1.0) 3.6 (1.0) 3.8 (0.9) 4.2 (1.8)
Complexityb 1.3 (0.2) 1.1 (0.3) 1.2 (0.1) 1.0 (0.4)
Passenger Productiona 3.7 (1.6) 4.0 (1.2) 3.8 (1.4) 3.6 (0.9)
Complexityb 1.2 (0.1) 1.1 (0.3) 1.3 (0.2) 1.1 (0.4)
a Given in syllable per second. b Given in syllable per word.
398 DREWS, PASUPATHI, AND STRAYER
The results also draw an intriguing picture about the allocation
of attention under dual-tasking conditions: Two similar situations
with identical tasks and instructions lead to fundamentally different
performance outcomes indicating that contextual variables can
have a significant impact on overall performance.
The present findings are of theoretical and applied importance.
On the theoretical side they raise general questions about how
much current models of attention predict performance of dyads or
groups in complex environments with regard to the allocation of
attention (see Cooke, Salas, Cannon-Bowers, & Stout, 2000).
Models of attention traditionally focus on individuals; however,
conceptualizing shared attention is of importance for any general
theory of attention. Of more specific theoretical importance here,
is the question of the mechanisms involved in the above processes:
Does a passenger just provide cues that help to optimize the
allocation of attention or does the passenger qualitatively change
the way that a driver allocates attention, thereby creating a form of
joint or distributed attention?
On the practical side, the findings allow predictions about how
contexts can negatively affect dual-task performance. On one
hand, passengers not engaged in the driving task either because
they are not able to direct the attention of the driver toward traffic,
or do not know how to identify important events in the driving
environment (e.g., children in the vehicle) have a potentially
negative impact on driving performance. On the other hand, it is
possible that overengagement can also have a potentially negative
impact. For example a passenger who is too “supportive” by
constantly commenting and directing attention in an overcontrolling
fashion has a potentially negative impact on performance.
In conclusion, the data indicate that cell phone and passenger
conversation differ in their impact on a driver’s performance
and that these differences are apparent at the operational, tactical,
and strategic levels of performance. The difference between
these two modes of communication stems in large part
from the changes in the difference in the structure of cell phone
and passenger conversation and the degree to which the conversing
dyad shares attention.
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Received January 26, 2007
Revision received June 5, 2008
Accepted June 9, 2008 _
Call for Nominations
The Publications and Communications (P&C) Board of the American Psychological Association
has opened nominations for the editorships of Developmental Psychology, Journal of Consulting
and Clinical Psychology, and Psychological Review for the years 2011–2016. Cynthia Garcı´a
Coll, PhD, Annette M. La Greca, PhD, and Keith Rayner, PhD, respectively, are the incumbent
editors.
Candidates should be members of APA and should be available to start receiving manuscripts in
early 2010 to prepare for issues published in 2011. Please note that the P&C Board encourages
participation by members of underrepresented groups in the publication process and would particularly
welcome such nominees. Self-nominations are also encouraged.
Search chairs have been appointed as follows:
● Developmental Psychology, Peter A. Ornstein, PhD, and
Valerie Reyna, PhD
● Journal of Consulting and Clinical Psychology, Norman Abeles, PhD
● Psychological Review, David C. Funder, PhD, and Leah L. Light, PhD
Candidates should be nominated by accessing APA’s EditorQuest site on the Web. Using your
Web browser, go to http://editorquest.apa.org. On the Home menu on the left, find “Guests.” Next,
click on the link “Submit a Nomination,” enter your nominee’s information, and click “Submit.”
Prepared statements of one page or less in support of a nominee can also be submitted by e-mail
to Emnet Tesfaye, P&C Board Search Liaison, at [email protected].
Deadline for accepting nominations is January 10, 2009, when reviews will begin.
400 DREWS, PASUPATHI, AND STRAYER
PART 5
Minimum Length 3-4 pages = -20 points for each number of pages falling above or below the minimum or maximum.
Your article is interesting and deals with current issues = 10 points
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