3-4 pages journal assignment pdf file

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