National Survey on 

Distracted Driving 

Attitudes and Behaviors

2012
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This publication is distributed by the U.S. Department of Transportation, National Highway 

Traffic Safety Administration, in the interest of information exchange. The opinions, findings, 

and conclusions expressed in this publication are those of the authors and not necessarily those 

of the Department of Transportation or the National Highway Traffic Safety Administration. 

The United States Government assumes no liability for its contents or use thereof. If trade names, 

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Suggested APA Format Citation:

Schroeder, P., Meyers, M., & Kostyniuk, L. (2013, April). National survey on distracted driving 

attitudes and behaviors – 2012. (Report No. DOT HS 811 729). Washington, DC: National 

Highway Traffic Safety Administration
i 

Technical Report Documentation Page

1. Report No. 2. Government Accession No. 3. Recipient’s Catalog No.

DOT HS 811 729 

4. Title and Subtitle 5. Report Date

National Survey on Distracted Driving Attitudes and Behaviors -- 2012 April 2013 

6. Performing Organization Code

 

7. Author(s) 8. Performing Organization Report 

No.

Paul Schroeder, Mikelyn Meyers, Lidia Kostyniuk 

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS)

Abt SRBI, Inc.

8403 Colesville Road, Suite 820 

Silver Spring, Maryland 20910

 

11. Contract or Grant No.

DTNH22-11-F-00355

12. Sponsoring Agency Name and Address 13. Type of Report and Period 

Covered

National Highway Traffic Safety Administration

Office of Behavioral Safety Research

1200 New Jersey Avenue SE. 

Washington, DC 20590

FINAL REPORT

14. Sponsoring Agency Code

 

15. Supplementary Notes

Kristie Johnson, Ph.D. served as the Contracting Officer’s Technical Representative (COTR).

16. Abstract

The 2012 National Survey on Distracted Driving Attitudes and Behaviors (NSDDAB) is the second in a series of 

surveys on distracted driving that have provided data to help further the understanding of driving behavior and to 

contribute to the development of countermeasures and interventions to reduce distracted driving on the Nation’s 

roadways. Like the previous 2010 study, this survey yields national estimates of behavior and attitudes toward 

distracted driving in the United States. The present study differs from the earlier study in that it developed and 

used a driver typology based on the pattern of responses across multiple distracted driving behavior questions. 

Cluster analysis identified two distinct groups of drivers with similar overall behavioral tendencies and, among 

those categorized, 33% are distraction-prone and 67% are distraction-averse. Driver type is a powerful predictor 

of norms and attitudes towards distracted driving behavior and sanctions for distracted driving. This report details 

the findings from the 2012 NSDDAB, examining the data using the above mentioned driver typology as well as 

standard demographics. In the final chapter, results from the current study are compared to those of the 2010

NSDDAB. 

 

17. Key Words 18. Distribution Statement

Unsafe driving, distraction, cell phone use, texting, inattention Document is available to the public 

from the National Technical 

Information Service www.ntis.gov

19 Security Classif. (of this report) 20. Security Classif. (of this page) 21 No. of 

Pages

22. Price

Unclassified Unclassified 172 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

ii

TABLE OF CONTENTS

Executive Summary ............................................................................................................ 1 

Chapter 1: Introduction .................................................................................................... 6 

Chapter 2: Description of Respondent Population .......................................................... 8 

Chapter 3: Phone-Related Distracted Driving ................................................................. 24 

Chapter 4: Perceptions of Safety of Distracted Driving .................................................. 38 

Chapter 5: Changes in Cell Phone Related Distracted Driving ...................................... 48 

Chapter 6: Distracted Driving Laws ................................................................................. 53 

Chapter 7: Program Awareness ........................................................................................ 69 

Chapter 8: Educational Messages ..................................................................................... 72 

Chapter 9: Distracted Driving Crashes and Near-Crashes............................................. 82 

Chapter 10: Perceptions of and Responses to Distracted Driving .................................. 87 

Chapter 11: Trend Analysis ............................................................................................... 95 

Conclusion ........................................................................................................................... 104 

References ............................................................................................................................ 108 

APPENDICES

Appendix A: Questionnaire................................................................................................ A1

Appendix B: Methodology ................................................................................................. B1

Appendix C: Output for Raking With Trimming Weight by 

Individual and Global Cap Value Method ....................................................................... C1
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

1 

EXECUTIVE SUMMARY

The 2012 National Survey on Distracted Driving Attitudes and Behaviors (NSDDAB) is the second 

survey conducted by NHTSA to assess attitudes and self-reported behaviors related to distracted driving, 

cell phones, and texting. The first Distracted Driving Survey was conducted in 2010. The 2012 survey 

was designed and administered by Abt SRBI, Inc, a national survey research organization. The survey 

employed a partial overlapping dual frame sample design of households with landline telephones as well 

as households that relied on cell phones, and collected data from interviews with drivers 16 and older. 

Because younger respondents tend to be underrepresented in landline telephone surveys, the survey 

included a landline telephone oversample of drivers 16 to34 years old. Interviewing began on February 

27, 2012, and ended on June 11, 2012. 

This report presents the survey findings from the 2012 NSDDAB. The data is weighted to yield national 

estimates. Readers are cautioned that some subgroup analyses are based on a smaller number of cases. A 

full description of the survey methodology and the questionnaire are presented in the appendices to this 

report.

Driver Characteristics

• Driver Types. A driver typology based on the pattern of responses across 10 questions concerned 

with distracted driving classified 99% of respondents into two distinct groups of drivers with 

similar overall behavioral tendencies. Of those respondents categorized, 33% were classified as 

distraction-prone drivers and 67% were classified as distraction-averse drivers. Drivers classified 

as distraction-prone tend to be younger, be more affluent, and have more formal education than 

distraction-averse drivers. More than half of drivers 35 years and younger were classified as 

distraction-prone compared to 5% of drivers 65 or older. Almost half of drivers with annual 

household incomes exceeding $100,000 were classified as distraction-prone compared to 26% of 

drivers with annual household incomes below $15,000. Among drivers without a high school 

degree, only one-quarter were classified as distraction prone, compared to almost half (47%) of 

drivers with college degrees. There was almost no difference in the proportion of distractionprone and distraction-averse drivers by gender. 

• Driving Frequency. More than 4 in 5 respondents (83%) drive every day or almost every day. 

Thirteen percent report driving a few days a week, while 4% drive a few days a month or less 

often. The highest proportions of distraction-prone drivers were among those who drove every 

day (41%) and also those who drove only a few days a year (38%). The lowest proportion was 

among drivers who drove a few days a week (18%). 

• Vehicle Type. The majority of drivers (56%) report they most often drive a passenger car. 

Seventeen percent of respondents report driving a pickup truck, 16% report driving an SUV, and 

8% report driving a van or a minivan most often. The proportion of distraction-prone drivers 

showed little variation across vehicle types. 

Phone-Related Distracted Driving 

• Cell Phone Ownership. Overall, 91% of respondents report owning some type of cell phone, and 

93% of respondents who report driving every day state that they currently own a cell phone. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

2 

• Talking on Cell Phone While Driving. Almost half (48%) of drivers report answering their cell 

phone when driving at least some of the time. Two in 5 drivers (40%) report never answering 

their phones while driving.

More than half of drivers (58%) who answer their phones while driving continue to drive while 

completing the conversation. Seventeen percent of drivers inform the callers they will call them 

back, 14% report handing the phone to a passenger in the car, and 11% pull over to safe locations 

to continue the conversation. 

Almost a quarter of drivers (24%) report that they are at least sometimes willing to make a cell 

phone call while driving. Nearly half (49%) report that they are never willing to initiate a cell 

phone call while driving. 

 

The majority of drivers who report making or accepting calls at least rarely while driving (77%)

report that the frequency with which they use cell phones when driving has not changed in the 

past 30 days, 19% report a decrease, and 3% report an increase in their frequency of cell phone 

use. Of those who reported a decrease, 24% cited an increased awareness of safety as the reason 

for the change. 

• Text Messaging and E-Mailing While Driving. One in 10 respondents (10%) reported sending 

text messages or e-mails while driving at least sometimes, while almost 80% of respondents 

stated that they never do so. An additional 11% reported sending text messages or e-mails on rare 

occasions. Reading text messages or e-mails while driving was slightly more common, with 14% 

of respondents stating that they do so at least some of the time and almost three-quarters (74%) 

stating that they never do so.

 

Of drivers who send text messages or e-mails, 44% state that they wait until they reach stop lights 

to send the text messages. About one-third (35%) of drivers continue to drive when sending text 

messages. Less frequently, drivers report handing the phone to a passenger (8%), using a voice 

command feature to send a text message (7%), or pulling over to the side of the road (6%). 

The majority of drivers (67%) reported no changes in the frequency of sending text messages in 

the past 30 days, 27% reported a decrease, and 5% reported an increase. Reasons given by those 

who reported decreases included an increased awareness of safety (38%), the law banning text 

messages (8%), and influence and pressure from others (7%). 

• Perception of prevalence of talking and texting while driving. Overall, respondents perceive 

distracted driving behavior to be fairly common, with 70% of respondents stating that more than 

half of drivers talk on cell phones at least occasionally while driving, while 43% of respondents 

estimate that more than half of drivers at least occasionally send text messages or e-mails while 

driving.

Perceptions of Safety

Half of drivers who talk on the cell phone while driving reported no difference in their driving 

when compared to not talking on the cell phone. However, 18% reported that they drove more 

slowly, 17% reported that they were distracted and not as aware, and another 5% stated that they 

were more focused and paid more attention to driving when on the phone. One-third of drivers 

who send text messages or e-mails while driving stated that there was no difference in their 

driving compared to times when they are not texting. However, 24% reported they were 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

3 

distracted and not aware, 21% reported that they drove more slowly, and 11% reported that they 

tended to drift out of their lane of travel. 

• When asked about their feelings concerning safety if they were passengers in a car driven 

by a driver who was also doing various activities while driving, most respondents indicated 

they would feel very unsafe if the driver was watching a movie (96%), using a laptop computer 

(95%), or reading a book or newspaper (95%). A majority reported that they would feel very 

unsafe if the driver were sending e-mails or text messages (86%) or reading e-mails or text 

messages (85%). Distraction-averse respondents were more likely than distraction-prone 

respondents to report feeling unsafe as passengers if their driver were reading or sending text 

messages. Almost all distraction-averse drivers (95%) reported they would feel very unsafe as 

passengers if their driver were reading or sending text messages, compared to 67% of respondents 

classified as distraction-prone drivers. 

Driver activities perceived as least unsafe by passengers included drivers singing along to the 

radio and drivers talking to other passengers. In these cases, 70% and 59% of respondents

respectively stated they would feel safe. Approximately 2 out of 5 respondents (41%) reported 

that they would feel safe if their driver were talking on a cell phone with a hands-free device. 

• Respondents were asked how likely they would be to intervene if their driver were engaged 

in a series of other activities while driving. Overall, 66% of respondents stated that they were at 

least somewhat likely to intervene if they were passengers in a car in which the driver were

talking on a cell phone while holding the phone. Respondents who were classified as distractionaverse were more likely to intervene than respondents classified as distraction-prone. Among 

those classified as distraction-averse, 72% stated they would intervene compared to 57% of 

respondents who were classified as distraction–prone drivers. 

Overall, 87% of respondents indicated that they were at least somewhat likely to intervene if they 

were passengers in a car in which the driver was sending e-mails or text messages. Of 

respondents classified as distraction-averse drivers, 90% stated that they would intervene, 

compared to 81% of respondents classified as distraction-prone drivers.

Crashes

• Six percent of respondents were involved in a crash and 7% were involved in a near-crash in the 

past year. Of those, 2% involved cell phone-related distracted driving and 3% involved sending or 

reading text messages.

Distracted Driving Laws

• Awareness of State Law Banning Talking and Texting on a Hand-Held Cell Phone While 

Driving. Overall, more than half of respondents (54%) reported that their State does have a law 

banning talking on a cell phone while driving, while 15% of respondents were unsure if their 

State had such a law. Regarding a texting ban, 69% reported that their State has a law banning 

texting or e-mailing on a cell phone while driving. Seventeen percent of respondents were unsure 

if their State has such a law.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

4 

In States with laws banning cell phone use while driving, 88% of drivers were aware of the law

and 4% thought their State had no such law. In States without laws banning cell phone use while 

driving, 42% of drivers accurately stated that their State did not have a law banning cell phone 

use, while 28% incorrectly thought their State had such a law, when it did not. 

In States that ban sending or reading text messages and e-mails while driving, 65% of drivers 

knew about the law and 8% thought their State did not have a law. In States without laws that ban 

sending and receiving text messages and e-mails while driving, 29% were aware that their State

did not have such a law, and 37% incorrectly thought their State had such a law, when it did not. 

• Support of a Law Banning Talking on a Hand-Held Cell Phone and Texting or E-mailing 

While Driving. The majority of drivers support State laws banning talking on hand-held cell 

phones while driving (74%). An overwhelming majority (94%) support State laws that ban 

texting or e-mailing while driving. On average, these drivers thought the fine should be $209 for 

talking on a hand-held cell phone while driving and $279 for sending a text message or e-mail 

while driving.

Enforcement Program Awareness

Most respondents (86%) were not aware of any programs or special effort by police to ticket 

drivers in their communities for using hand-held cell phones while driving. Only 12% indicated 

they had heard of any such program.

The ways in which drivers were made aware of special efforts by police to ticket drivers for using 

cell phones while driving included TV news (28%), TV advertisement/public service 

announcements (15%), radio programs or radio news (8%), radio advertisement/public service 

announcements (9%), and billboards/signs (16%). Others were informed by friends or relatives 

(12%), witnessed enforcement activity (11%), or had direct contact with police officers (3%).1

Chances of Receiving a Ticket for Distracted Driving

Overall, slightly more than half of respondents in States with laws banning some form of cell 

phone use while driving (52%) thought a driver who regularly talks on a cell phone while driving 

was likely to get a ticket in the next 6 months, and 44% stated that it was unlikely that the driver 

would be ticketed. There was little difference between distraction-prone and distraction-averse 

drivers in this belief. However, drivers with less formal education were more likely to believe that 

the driver would be ticketed, while those with more formal education were more likely to believe 

that the driver would not be ticketed. 

Just under half of respondents (46%) in States with laws banning texting or e-mailing believed 

that it was at least somewhat likely that drivers who frequently send text messages or e-mails 

while driving would get a ticket for this infraction in the next 6 months. However, 37% thought it 

was at least somewhat unlikely. Overall, there was little difference in this perception by driver 

type. 

 

1 This question was multiple response and some respondents provided more than one answer.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

5 

Educational Messages

Of all respondents, 63% had seen or heard a message discouraging distracted driving in the past 

30 days. Drivers who drove every day were more likely than those who drove less frequently to 

report having seen or heard these messages. Respondents who were classified as distractionaverse were also more likely than distraction-prone respondents to report hearing or seeing these 

messages. Almost three-quarters of respondents (72%) reported TV as the source of the message. 

Billboards were reported by 27% of respondents, and 30% of respondents stated that the radio 

was the source of the message. 

Safe Driving Slogans 

Over 6 out of 10 respondents (61%) reported having heard or seen at least 4 safe driving slogans 

in the past 30 day, with men somewhat more likely than women to report so (66% versus 57%). 

The most frequent slogan reported was Click It or Ticket, with 75% of these respondents stating 

that they heard or saw it in the past 30 days. About 1 in 5 respondents indicated that they heard or 

saw “No Phone Zone,” “Just drive,” “One Text or Call Could Wreck It All,” or “On the Road. 

Off the Phone,” and 1 in 10 reported seeing or hearing “Phone in One Hand. Ticket in the Other” 

and “Put it Down.” 

Trends in Distracted Driving

Although the rates of engaging in the various distracted activities while driving varied slightly 

from 2010 to 2012, there was little change in the proportion of respondents who reported these 

behaviors. Approximately half of respondents (52% in 2010 and 49% in 2012) stated that they 

always or almost always talked to passengers while driving. In 2010, 14% of respondents 

reported always or almost always eating or drinking while driving, while in 2012, this percentage 

was 11%. In both 2010 and 2012, approximately 1% of respondents reported always or almost 

always reading and driving. 

The proportion of respondents who always or almost always answer the phone while driving

decreased between 2010 and 2012. In 2010 and 2012, 33% and 28% of respondents, respectively, 

answered incoming calls. The percentage of respondents always or almost always initiating phone 

calls decreased from 10% in 2010 to 6% in 2012. 

The percentage of drivers who send text messages while driving increased slightly from 12% in 

2010 to 14% in 2012. However, the proportion of drivers who always send or read text messages 

while driving remained the same at approximately 1%.

Both in 2010 and 2012, when asked if their rates of talking on the cell phone while driving or 

texting and driving had changed in the past 30 days, most drivers who engaged in these activities, 

indicated that the rates of these activities remained the same. Declines in cell phone conversations 

while driving were reported by 12% of respondents in 2010 and 19% in 2012. Among these 

drivers, an increased awareness of safety was the reason most often cited (by 31% in 2010 and 

24% in 2012). Decreases in texting in the last 30 days were reported by 31% of respondents in 

2010 and 27% of respondents in 2012. Among these drivers, reasons given for the decrease were

an increased awareness of safety (32% in 2010 and 38% in 2012), the law (6% in 2010 and 8% in 

2012), and influence and pressure from others (1% in 2010 and 7% in 2012). 

Approximately 6 in 10 drivers in both 2010 and 2012 reported having seen or heard at least one 

educational message discouraging talking on cell phones or sending text messages or e-mails 

while driving in the past 30 days. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

6 

Support for laws banning hand-held cell phone use increased from 68% of all respondents in 

2010 to 74% in 2012. Support for laws banning texting or e-mailing remained about the same 

with 93% of respondents in 2010 and 94% of respondents in 2012 supporting such a law. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

7 

CHAPTER 1

INTRODUCTION

Background 

The National Highway Traffic Safety Administration of the U.S. Department of Transportation promotes 

the safety of motor vehicles and their occupants. The broad mission of NHTSA includes the reduction of 

traffic-related fatalities and injuries, reducing the economic repercussions of crashes, and promoting 

issues surrounding improved safety and responsible behavior among drivers. The increase in cell phone 

ownership and usage combined with the widespread availability of many other devices that can easily 

divert drivers’ attention from the task of driving an automobile have made information on drivers’ 

behaviors and attitudes toward distracted driving important to the safety of America’s roadways. 

The most common activities that drivers engage in while driving include talking with other passengers, 

changing radio stations or searching for CDs, making cell phone calls, receiving cell phone calls, dealing 

with children in the back seat, reading maps or directions, personal grooming, reading printed material, 

responding to pagers or beepers, using wireless Internet, and using GPS such as in-car navigation systems 

(Royal, 2003). 

The use of technological devices while driving has become a focus of distracted driving research. In 

particular, use of cell phones while driving has been of increasing interest in the past decade. In 2010, 

41% of drivers in the United States reported using cell phones to make or receive calls on at least some of 

their driving trips, and 17% reported using some type of hands-free device when using cell phones (Tison, 

Chaudhary, & Cosgrove, 2011). 

Driver distraction contributes to crash-related fatalities and injuries, particularly among younger drivers, 

with 13% of drivers in fatal distraction-affected crashes under age 20. Overall, 9% of fatal crashes in the 

United States in 2010 involved driver distraction, and 13% of the drivers in these fatal crashes were 

reported to have been using a cell phone at the time of the crash (National Center for Statistics and 

Analysis, 2012). 

To better understand the attitudes and self-reported behaviors related to cell phones, texting, and 

distracted driving, NHTSA conducted the National Survey on Distracted Driving Attitudes and Behaviors 

in 2010, and again in 2012. This report presents findings from the 2012 National Survey on Distracted 

Driving (NSDDAB). Specifically, the 2012 NSDDAB survey assessed the extent to which drivers are 

distracted by various activities; demographic and typological descriptions of drivers prone to distractions; 

the extent and frequency of using cell phones while driving; attitudes and perceptions about distracted 

driving; the extent and frequency of texting while driving; knowledge of and attitudes toward measures to 

deter distracted driving; perceptions about the danger of distracted driving; exposure to the consequences 

of distracted driving; willingness to intervene when someone is distracted while driving; and changes and

trends in distracted driving behavior and attitudes since 2010. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

8 

Methodology 

A total of 6,016 interviews were conducted among a national representative sample of people 16 or older 

who had driven a motor vehicle. To account for the current shift to cell phone use and the 

underrepresentation of younger people in samples using landline telephones, a partial overlapping dual 

sampling frame of households with landline phones, and households that relied only or mostly on cell 

phones, together with a landline phone oversample of people 16 to 34 years old was used. In all, 3,190 

interviews were completed with people from landline households, 2,144 interviews with people from cell 

phone-only or cell phone-mostly households, and an additional 682 interviews of people 16 to 34 were 

completed from the landline phone oversample. The samples were combined and weighted to produce 

national estimates of the target population within specified limits of expected sampling variability, from 

which valid generalizations can be made to the general population of drivers in the United States. 

The interviews were conducted from February 27 to June 11, 2012. Appendix B contains the complete 

description of the methodology and sample dispositions, including information on the computation of 

weights. There are also tables in Appendix B that show the margin of error for specific estimates (Table 

B-6), a given “N” size (Table B-7), and the comparison of subgroups (Table B-8) given the design effect 

associated with the study. These margins of error should be kept in mind when reviewing the figures and 

tables throughout the report.

The percentages presented in this report are weighted to accurately reflect the national population 16 or 

older. Unweighted sample sizes (Ns) are included so that readers know the exact number of respondents 

answering a given question, allowing them to estimate sampling precision. 

Percentages for some items may not add to 100% due to rounding, or because the question allowed for 

more than one response. In addition, the number of cases involved in subgroup analyses may not sum to 

the grand total who responded to the primary questionnaire item being analyzed. Reasons for this include 

some form of non-response on the grouping variable (e.g., “Don’t Know” or “Refused”), or use of only 

selected subgroups in the analysis. 

For rounding purposes, all variables are rounded based on two decimal places. Any value that had a 

decimal of .50 or greater was rounded up and any value that had a decimal below .50 was rounded down. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

9 

CHAPTER 2

DESCRIPTION OF RESPONDENT POPULATION

To capture a sample of respondents that was representative of drivers 16 and older in the United States, a 

landline cross section sample, a landline oversample of respondents 16 to 34, and a cell phone sample 

were used (see Table 2-1). Of the 6,016 survey respondents, 3,190 (53.0%) were sampled from the 

landline cross section sample, 682 from the landline oversample, and 2,144 from the cell phone sample

(35.6%). The cell phone sample captured several groups often unreachable by landline phones. Drivers 

younger than 20 make up 8.4% of the cell phone sample, and more than 19% of the cell phone sample are 

younger than 25. By contrast, 2.6% of respondents in the landline cross section sample are younger than

25. The landline oversample captured more respondents in the younger age groups, with 41% of 

respondents in the landline oversample being 24 or younger.

Table 2-1: Demographics by Sample Type – Unweighted

Cell Phone

Sample 

(N=2,144) 

Landline Cross 

Section

(N=3,190)

Landline 

Oversample 

(N=6822)

Total Sample

(N=6,016) 

Gender

Female 42.5% 58.0% 53.4% 48.0%

Male 57.5% 42.0% 46.6% 52.0%

Age

Mean 39.98 55.67 25.95 46.64

16 to 20 8.4% 1.4% 24.5% 6.5%

21 to 24 10.8% 1.2% 16.6% 6.4%

25 to 34 23.9% 6.9% 58.9% 18.8%

35 to 44 16.5% 13.8% 0.0% 13.2%

45 to 54 18.8% 20.8% 0.0% 17.7%

55 to 64 12.6% 24.8% 0.0% 17.7%

65 or older 7.3% 28.7% 0.0% 17.8%

2011 Household Income

Less than $10,000 7.4% 3.5% 4.4% 5.0%

$10,000 to $14,999 6.2% 4.3% 5.6% 5.1%

$15,000 to $24,999 9.2% 8.1% 7.8% 8.4%

$25,000 to $49,999 22.9% 18.5% 20.8% 20.3%

$50,000 to $99,999 27.3% 28.6% 25.2% 27.8%

$100,000 to$149,999 10.9% 12.1% 11.4% 11.6%

$150,000 to $199,999 4.0% 4.5% 5.3% 4.4%

$200,000 or more 3.4% 5.8% 4.0% 4.7%

Education

No HS degree 10.2% 5.5% 19.1% 8.7%

HS graduate 28.3% 25.5% 25.4% 26.5%

Some college 24.3% 23.3% 25.2% 23.9%

College graduate 21.2% 21.6% 17.0% 20.9%

 

2 100 respondents completed the oversample survey, but reported that they were older than 34. Those respondents 

were treated as part of the landline survey for analysis purposes.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

10 

Table 2-1: Demographics by Sample Type – Unweighted (Continued)

Cell Phone 

Sample

(N=2,144)

Landline 

Cross Section

(N=3,090)

Landline 

Oversample 

(N=782)

Total Sample

(N=6,016) 

Some graduate school 2.4% 3.4% 2.3% 2.9%

Graduate degree 12.3% 19.5% 10.4% 15.9%

Number of Children 15 or 

Younger in Household

0 60.6% 71.0% 42.1% 64.0%

1 to 3 35.6% 25.6% 52.5% 32.2%

4 or more 2.2% 1.4% 3.8% 2.0%

Ethnicity

Hispanic 16.1% 6.6% 14.1% 10.8%

Not Hispanic 82.6% 92.4% 85.3% 88.1%

Race/Ethnicity

White 68.6% 80.0% 68.8% 74.7%

Black 9.9% 8.2% 10.9% 9.1%

Asian 5.2% 2.3% 4.8% 3.6%

American Indian/Alaska 

Native

3.4% 2.7% 3.2% 3.0%

Native Hawaiian or 

other Pacific Islander

0.9% 0.3% 1.6% 0.7%

(VOL) Hispanic 9.3% 3.6% 7.9% 6.1%

Other 0.7% 0.9% 0.9% 0.8%

Homeowner Status

Own 52.0% 82.3% 47.2% 67.5%

Rent 38.9% 13.5% 29.5% 24.4%

Some other arrangement 7.8% 2.6% 21.7% 6.6%

Frequency of Driving

Everyday 73.9% 69.4% 72.1% 71.3%

Almost everyday 11.7% 14.5% 12.8% 13.3%

Few days a week 10.2% 12.5% 10.6% 11.5%

Few days a month 2.8% 3.0% 3.5% 3.0%

Few days a year 1.3% 0.6% 1.0% 0.9%

Primary Type of Vehicle

Car 56.3% 57.7% 60.1% 57.5%

Van/mini-van 8.1% 8.1% 9.2% 8.2%

SUV 14.9% 18.9% 17.4% 17.3%

Pickup truck 17.6% 13.9% 10.7% 14.9%

Other truck 2.2% 0.7% 1.0% 1.3%

Motorcycle 0.1% 0.3% 0.6% 0.3%

Other 0.5% 0.2% 0.4% 0.3%
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

11 

For the remainder of this report, all percentages that appear in figures and tables are based on the 

weighted data unless otherwise noted. 

In examining drivers’ attitudes and self-reported distracted behaviors, it is useful to group drivers by their 

distracted driving tendencies. Rather than rely on any single indicator of general distracted driving or 

assumptions about appropriate categories of drivers, this study developed a typology of drivers using 

cluster analysis of responses to 10 questions about the frequency of distracted driving behaviors. Cluster 

analysis allowed the identification of discrete types of drivers based on the overall pattern of responses 

across all 10 distracted driving behavior questions.

Table 2-2 shows the 10 distracted driving questions used in the cluster analysis and the response 

distributions for each. Talking to passengers in the vehicle is the activity drivers most often engage in 

while driving with 49% reporting they always or almost always do so while driving. This was followed 

by adjusting the car radio (27%) and interacting with children in the back seat (15%). Activities in which 

drivers are the least likely to engage while driving include reading, with 96.3% of drivers saying they 

never do so, followed by personal grooming (80%), sending text messages or mails (79%), and reading emails or text messages (74%). 

Table 2-2: Distracting Behavior Frequency 

(Used in Cluster Analysis) 

How often do you... N Always Almost 

Always

Sometimes Rarely Never

Q4a. Talk to other passengers in the 

vehicle

6,016 30.8% 17.8% 30.9% 14.1% 6.0%

Q4b. Eat or drink 6,016 5.0% 5.5% 36.5% 25.6% 27.4%

Q4c. Make or accept phone calls 6,016 6.3% 5.8% 27.5% 22.1% 38.2%

Q4d. Read, such as a book, 

newspaper, iPad or Kindle

6,016 0.4% 0.1% 0.8% 2.4% 96.3%

Q4e. Read e-mails or text messages 6,016 1.4% 1.8% 10.9% 11.8% 74.0%

Q4f. Send text messages or e-mails 6,016 1.0% 1.0% 8.3% 11.0% 78.7%

Q4g. Talk or interact with children in 

the back seat

6,016 9.0% 5.5% 21.0% 13.0% 51.2%

Q4h. Do personal grooming, such as 

put on make-up, shave, or look at 

yourself in the mirror

6,016 1.0% 0.8% 7.4% 10.7% 80.1%

Q4i. Adjust the car radio 6,016 15.8% 11.3% 41.3% 15.9% 15.6%

Q4j. Change CDs, DVDs, or tapes? 6,016 3.2% 2.2% 19.2% 19.0% 56.4%
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

12 

Cluster analysis was able to classify 99% of respondents into one of two distinct groups based on their 

responses to the 10 questions. There were 59 respondents that could not be classified because some had 

answered “Don’t know” or “Refused” to one or more distracted driving behavior questions or because 

their responses to these questions did not fit well with any of the clusters. The core characteristic of each 

of the two groups identified in the cluster analysis was determined by examining how each group scored 

on each distracted driving behavior variable. As can be seen in Table 2-3, one group was composed of 

drivers who consistently reported engaging in distracted driving behaviors and the other group was 

composed of drivers who reported distracted driving behaviors less often. The groups were named 

distraction-prone and distraction-averse, respectively, for the purposes of this report. Of those respondents 

categorized, 33% are distraction-prone drivers (N=1,989) and 67% are distraction-averse drivers

(N=3,968). 

Table 2-3: Distracted Driving Behaviors, by Driver Type

How often do you... N3 Always Almost 

Always

Sometimes Rarely Never

Talk to other passengers in the vehicle

Distraction-prone drivers 1,989 51.2% 20.9% 20.3% 6.0% 1.6%

Distraction –averse drivers 3,968 19.5% 16.3% 37.1% 18.6% 8.5%

Eat or drink

Distraction-prone drivers 1,989 9.5% 10.8% 49.6% 22.1% 8.1%

Distraction –averse drivers 3,968 2.6% 2.6% 29.3% 27.8% 37.8%

Make or accept phone calls

Distraction-prone drivers 1,989 15.2% 13.7% 43.7% 21.5% 6.0%

Distraction –averse drivers 3,968 1.4% 1.4% 18.7% 22.5% 55.9%

Read, such as a book, newspaper, iPad, or Kindle

Distraction-prone drivers 1,989 1.0% 0.3% 1.8% 5.8% 91.1%

Distraction –averse drivers 3,968 -- -- 0.3% 0.5% 99.2%

Read e-mails or text messages

Distraction-prone drivers 1,989 4.0% 5.1% 30.4% 30.9% 29.6%

Distraction –averse drivers 3,968 -- 0.1% 0.2% 1.3% 98.4%

Send text messages or e-mails

Distraction-prone drivers 1,989 2.8% 2.8% 23.3% 30.5% 40.5%

Distraction –averse drivers 3,968 -- -- -- 0.2% 99.8%

Talk or interact with children in the back seat

Distraction-prone drivers 1,989 19.3% 9.1% 21.7% 12.2% 37.7%

Distraction –averse drivers 3,968 3.4% 3.6% 20.8% 13.3% 58.8%

Do personal grooming, such as put on make-up, 

shave, or look at yourself in the mirror

Distraction-prone drivers 1,989 2.2% 1.8% 14.0% 18.0% 63.9%

Distraction –averse drivers 3,968 0.3% 0.2% 3.8% 6.7% 88.9%

 

3 The 59 respondents who answered “don’t know” or “refused” to one of the distracted driving behavior questions or 

whose responses did not fit the cluster analysis are excluded from this chart.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

13 

Table 2-3: Distracted Driving Behaviors, by Driver Type (Continued)

How often do you... N Always Almost 

Always

Sometimes Rarely Never

Adjust the car radio

Distraction-prone drivers 1,989 36.6% 19.5% 32.8% 8.5% 2.6%

Distraction –averse drivers 3,968 4.4% 6.9% 46.3% 19.9% 22.5%

Change CDs, DVDs, or Tapes

Distraction-prone drivers 1,989 8.3% 4.9% 23.6% 22.6% 40.5%

Distraction –averse drivers 3,968 0.3% 0.7% 16.8% 17.2% 65.0%
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

14 

Examining driver type by gender shows no relationship between driver type and gender. Just over onethird of men (36%) and women (35%) are classified as distraction-prone drivers based on the cluster 

analysis.

Figure 2-1: Driver Type, by Gender

64.0% 64.8%

36.0% 35.2%

0%

20%

40%

60%

80%

100%

Male (N=2,860) Female (N=3,097)

Distraction-Averse Driver Distraction-Prone Driver

Sa3. Record gender from observation. (Ask only if necessary.) 

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

15 

Figure 2-2 shows a clear age effect on distracted driving tendency. Distraction-averse drivers tend to be 

older while distraction-prone drivers are more likely to be younger. Less than half of drivers between 16 

and 34 were categorized as distraction-averse, while more than half of drivers 35 and older were 

categorized as distraction-averse. 

Figure 2-2: Driver Type, by Age

41.7% 35.2%

44.7%

55.2%

68.4%

82.3%

94.6%

58.3% 64.8%

55.3%

44.8%

31.6%

17.7%

5.4%

0%

20%

40%

60%

80%

100%

16 to 20

(N=391)

21 to 24

(N=380)

25 to 34

(N=1,123)

35 to 44

(N=792)

45 to 54

(N=1,058)

55 to 64

(N=1,049)

65+

(N=1,056)

Distraction-Averse Driver Distraction-Prone Driver

Q24. What is your age?

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

16 

Figure 2-3 examines the relationship between distracted driving tendency and the highest level of 

education completed. Respondents with some graduate school education and college graduates had the 

largest percentage of distraction-prone drivers (48% and 47%, respectively) compared to respondents 

without a high school degree (25%). Additionally, 47% of college graduates were categorized as 

distraction-prone drivers. Overall, drivers with a high school degree or less are more likely to be classified 

as distraction-averse while drivers with at least some college education are more likely to be classified as 

distraction-prone. 

Figure 2-3: Driver Type by Highest Level of School Completed

75.0% 69.3%

60.8%

53.1% 51.9%

61.7%

25.0% 30.7%

39.2%

46.9% 48.1%

38.3%

0%

20%

40%

60%

80%

100%

No HS Degree

(N=518)

High School

Grad

(N=1,582)

Some College

(N=1,420)

College Grad

(N=1,251)

Some Grad

School

(N=173)

Grad Degree

(N=946)

Distraction-Averse Driver Distraction-Prone Driver

Q24e. What is highest grade or year of regular school you have completed?

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

17 

Figure 2-4 shows that the tendency toward distracted driving behavior is relatively similar across most 

racial groups. The highest proportion of distraction-prone drivers was among Black/African-American 

respondents (43%), and the lowest was among American Indian and Alaska Native drivers. The 

percentage of distracted drivers was highest for Native Hawaiian or other Pacific Islander respondents 

(61%); however, due to the small number of respondents in this group (N=40), these results should not be 

interpreted too widely. 

Figure 2-4: Driver Type, by Race

100%

30.4% 34.2% 32.7% 80% 40.9% 43.0%

60.9%

60%

40%

69.6% 65.8% 67.3% 59.1% 57.0%

20% 39.1%

0%

American Asian Black or Native White Hispanic

Indian or (N=216) African Hawaiian or (N=4,452) (N=368)

Alaska Native American other Pacific

(N=178) (N=535) Islander

(N=40)*

Distraction-Averse Driver Distraction-Prone Driver

Q24d. Which of the following racial categories describe you? You may select more than one. [Multiple Record]

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart

*Sample size was less than 50.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

18 

Figure 2-5 shows that the presence of children 15 or younger in the household is related to distracted 

driving tendencies. Respondents without children under 16 in their household (71%) are more likely than 

respondents with children that age to be classified as distraction-averse drivers (53% and 54%). Because 

the presence of children under 16 is often correlated with age, the relationship between the number of 

children and age was examined. Respondents who were categorized as distraction-averse and have no 

children tend to be older than respondents who were categorized as distraction-prone and report having no 

children. 

Figure 2-5: Driver Type, by Children 15 or Younger in Household

70.8%

52.5% 53.8%

29.2%

47.5% 46.2%

0%

20%

40%

60%

80%

100%

0

(N=3,810)

1 to 3

(N=1,924)

4 or more

(N=117)

Distraction-Averse Driver Distraction-Prone Driver

Q24b. How many children age 15 or younger are living in your household at least half of the time or consider it their primary 

residence? 

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

19 

The relationship between homeownership and driver type was also explored. Homeowners were more 

likely to be categorized as distraction-averse drivers (68%) compared to those that rent (59%). Because 

this relationship reflects the age of the respondent, the relationship between age and homeownership was 

examined. Age of respondent and homeownership are correlated, with older respondents more likely to be 

homeowners than younger respondents. Homeowners that were classified as distraction-averse were more 

likely to be older than homeowners that were classified as distraction-prone, which supports the 

conclusion that homeowners tend to be distraction-averse because home-owners tend to be older than 

renters.

Figure 2-6: Driver Type, by Home Ownership

68.1%

58.6%

31.9%

41.4%

0%

20%

40%

60%

80%

100%

Own

(N=4,018)

Rent

(N=1,458)

Distraction-Averse Driver Distraction-Prone Driver

Q24e1. Do you own or rent your home? 

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

20 

Figure 2-7 shows a clear pattern between income and distracted driving tendency. Overall, as annual 

household income increases, drivers were more likely to be classified as distraction prone. In the highest 

household income group ($200,000+), half of drivers were categorized as distraction-prone. In contrast, 

of those in the lowest household income group (<$10,000), only 26% were classified as distraction-prone. 

While income tends to increase with age, very young and very old respondents with high household 

incomes are an exception to this trend. Respondents younger than 20 were more likely to report 

household incomes over $150,000 a year than respondents in their early twenties, probably because they 

still live at home with parents who are older and thus have higher incomes. In addition, respondents over

55 were less likely to report household incomes over $150,000 a year than respondents in their 30s and 

40s. As a result, respondents who live in households that have incomes of more than $150,000 a year tend 

to be younger than those who report a household income less than $150,000, which would account for the 

increase in distraction-prone drivers in this demographic group. 

Figure 2-7: Driver Type, by Income

73.8% 73.9% 72.0% 68.6%

58.3% 55.2%

44.5% 49.8%

26.2% 26.1% 28.0% 31.4%

41.7% 44.8%

55.5% 50.2%

0%

20%

40%

60%

80%

100%

Less than

$10,000

(N=299)

$10,000 to

$14,999

(N=304)

$15,000 to

$24,999

(N=501)

$25,000 to

$49,999

(N=1,207)

$50,000 to

$99,999

(N=1,661)

$100,000

to

$149,999

(N=690)

$150,000

to

$199,999

(N=262)

$200,000+

(N=280)

Distraction-Averse Driver Distraction-Prone Driver

Q24j. What is your approximate household income? [Read List]

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

21 

Figure 2-8 shows the tendency toward distracted driving by respondents’ frequency of driving. The 

highest proportion of distraction-averse drivers is among respondents who drove a few days a week or a 

few days a month, with only about 1 in 5 respondents classified as a distraction-prone driver (18% and 

21%, respectively). Among respondents who drove every day, 41% were classified as distraction-prone. 

Interestingly, 38% of the respondents who drove least often were classified as distraction-prone. This 

indicates that the frequency of one’s driving is not directly related to one’s distracted driving tendencies. 

Figure 2-8: Driver Type, by How Often Do You Drive a Motor Vehicle 

59.1%

71.0%

82.1% 79.0%

62.1%

40.9%

29.0%

17.9% 21.0%

37.9%

0%

20%

40%

60%

80%

100%

Every day

(N=4,248)

Almost every

day

(N=794)

Few days a

week

(N=682)

Few days a

month

(N=178)

Few days a year

(N=52)

Distraction-Averse Driver Distraction-Prone Driver

Q1. How often do you drive a motor vehicle, regardless of whether it is for work or for personal use? Every day, almost every

day, a few days a week, a few days a month, a few days a year, or do you never drive?

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

22 

Figure 2-9 shows that there is no relationship between the tendency toward distracted driving and the type 

of vehicle most often driven. Approximately one-third of drivers with each vehicle type were classified as 

distraction-prone drivers. Respondents who drove SUVs were slightly more likely (39%) and those who 

drove “other” vehicles were slightly less likely (30%) to be classified as distraction-prone. Examples of 

“other” types of vehicles that respondents listed include “ambulance,” “school bus,” “golf cart,” and 

“motorhome.” 

Figure 2-9: Driver Type, by Car Type 

100%

30.0% 36.3% 34.0% 31.9% 36.4% 33.7% 80% 38.6%

60%

40%

68.1% 70.0% 63.7% 66.0% 63.6% 66.3% 61.4%

20%

0%

Car Van or Motorcycle Pickup SUV Other truck Other

(N=3,419) minivan (N=16)* truck (N=1,037) (N=76) (N=20)*

(N=485) (N=891)

Distraction-Averse Driver Distraction-Prone Driver

Q1a. Is the vehicle you drive most often a car, van, motorcycle, sport utility vehicle, pickup truck, or other type of truck?

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart

*Sample size was less than 50.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

23 

Figure 2-10 shows those respondents who own a cell phone are much more likely to be classified as a 

distraction-prone driver (39%) compared to those who do not own a cell phone (4%). The majority of 

respondents owned a cell phone (N=5,580), so these results should be interpreted with this fact in mind. 

Those who do not own cell phones and rely solely on a landline tend to be older, so this is another 

relationship that is attenuated by the age of the respondent. 

Figure 2-10: Driver Type, by Cell Phone Ownership

100% 4.1%

80% 39.1%

60%

95.9%

40%

60.9%

20%

0%

Yes (N=5,580) No (N=375)

Distraction-Averse Driver Distraction-Prone Driver

Q3a. Do you CURRENTLY own any of the following devices? A cell phone [Code 1 (Yes) if mentions any cell phone including 

a smartphone]

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

24 

In Figure 2-11, the percentage of distraction-prone drivers by NHTSA region is shown. It is important to 

note that there is not a large difference in the proportion of distracted drivers between the NHTSA 

Regions. The lowest proportion of distraction-prone drivers is found in Region 10 (27.0%) while the 

highest proportions were found in Region 7 at 38.2% and Region 6 at 38.4%.

Figure 2-11. Proportion of Distraction-Prone Drivers, by NHTSA Region
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

25 

CHAPTER 3

PHONE-RELATED DISTRACTED DRIVING 

This chapter examines the use of cell phones for initiating and receiving calls and text messages, 

including the reasons respondents gave for engaging in this behavior. Table 3-1 shows the proportion of 

respondents who own devices that can distract drivers when operated while driving. Among these, 

ownership of cell phones is the highest at 91%4

Table 3-1. Ownership of Electronic Devices

Q3. Do you currently own any of the following devices? [Multiple 

Record]

Percent

Yes

A cell phone (Code Yes if mentions any cell phone including 

smartphone) 90%

A “smartphone” such as a Droid, iPhone, or Blackberry 44%

A pager or beeper 2%

A portable music play, such as a CD player, iPod, or Zune 46%

A portable navigation system, such as TomTom or Garmin 36%

A navigation system built into the vehicle, such as Onstar or Sync 16%

A laptop computer, iPad, Kindle, or Nook 59%

*A Bluetooth or other hands-free device for your cell phone, such 

as one that plugs into the phone, works wirelessly, or works 

through your vehicle’s car stereo 38%

Unweighted N = 6,016 

Base: All respondents

*Asked of respondents who reported owning a cell phone or smartphone. 

 

 

4 While only 90% of respondents reported that they own “a cell phone,” that percentage increases to 91% when 

respondents who reported owning “a ‘smartphone’ such as a Droid, iPhone, or Blackberry” is included. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

26 

Figure 3-1 shows the proportion of respondents who own cell phones by their frequency of driving. 

Respondents who drove every day, or almost every day, are more likely to own cell phones than 

respondents who drove less frequently. Ownership of cell phones is 93% among those who drove every 

day, and 90% among those who drove almost every day. Among those who drove less frequently, cell 

phone ownership is just under 80%. 

Figure 3-1: Cell Phone Ownership, by Frequency of Driving

93.2% 90.3%

80.6%

77.5% 78.3%

0%

20%

40%

60%

80%

100%

Every day

(N=4,289)

Almost every

day

(N=802)

Few days a

week

(N=689)

Few days a

month

(N=180)

Few days a

year

(N=53)

Q1. How often do you drive a motor vehicle, regardless of whether it is for work or for personal use? Every day, almost every

day, a few days a week, a few days a month, a few days a year, or do you never drive?

Q3. Do you CURRENTLY own any of the following devices? [Multiple Record]

Base: All Respondents

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

27 

When asked how often they answer an incoming cell phone call when driving, 28% of respondents 

reported that they always or almost always answer the phone, and 21% reported that they sometimes

answer an incoming call while driving. However, more than half of respondents said that they rarely 

(11%) or never (40%) answer the phone while driving. (Figure 3.2) 

Figure 3-2: How Often Do Answer Your Phone When Driving

50%

40.3%

40%

30%

20.5%

20%

16.7%

11.4% 11.1%

10%

0%

Always Almost Always Sometimes Rarely Never

Q5a. When you RECEIVE a phone call while you are driving, how often do you ANSWER the call? [Read List]

Base: All Respondents

Unweighted N= 6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

28 

Table 3-2 lists the reasons why respondents are likely to answer an incoming call while driving. The most 

common reason given is the identity of the person calling (39%), followed by how important they think 

the call is (27%). More than 1 in 7 (15%) drivers are likely to answer the phone if it is work-related, while 

10% state that they answer all calls received while driving. A Smaller percentage of drivers reported that 

they are likely to answer if the call is from someone they know (7%), the call is personal or social (7%), 

the call is routine or expected (3%), or it is an emergency situation (3%). 

Table 3-2. Reasons for Answering Phone While Driving

Q5b.What are the reasons you are more likely 

to ANSWER a call while driving? [Multiple 

Record] Percent

Who is calling 38.6%

How important I think the call is 27.2%

Call is work-related 15.2%

I answer all calls 10.0%

Call is from someone I know 7.2%

Call is personal or social 6.8%

Call is routine or expected 3.4%

Urgent/emergency situation 2.6%

Non-stressful traffic conditions 1.6%

Availability of the phone 1.4%

When Bluetooth/hands free technology available 1.2%

Call is unexpected 1.0%

In need of directions or other information 0.8%

Personal safety 0.7%

Boredom 0.4%

Traveling at a low speed 0.2%

Time of day 0.2%

Call is from a number I don't recognize 0.2%

Good weather conditions 0.1%

Tired (talking keeps me awake) 0.1%

Base: Answer phone call while driving at least rarely

Unweighted N = 3,847 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

29 

More than half of respondents who reported answering an incoming phone call while driving stated that 

they usually continue to drive while completing the conversation (58%). Almost 1 in 5 (17%) drivers 

usually inform the caller they will call them back later, and 14% usually hand the phone to a passenger in 

the car. Fewer than 1 in 10 (8%) respondents state that they pull over to a safe location after answering 

the phone, while 3% report that they first pull over to a safe location and then answer the call.

Figure 3-3: Behavior After Answering a Call While Driving

100%

90%

80%

70%

60% 57.9%

50%

40%

30%

20% 16.5% 14.2%

10% 7.5%

3.0%

0%

Continue to drive Promptly pull Inform the caller Pull over to a safe Hand the phone

while completing over to a safe you will call back location first and to a passenger to

the conversation location later then speak to the answer if you

caller have one

Q5c. When you answer a call while driving, do you USUALLY... [READ LIST]

Base: Respondents Who Answer the Phone While Driving

Unweighted N= 3,847
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

30 

When asked how often they are willing to make a phone call while driving, 49% of drivers stated that 

they are never willing to make a phone call when driving. Few respondents stated that they are always 

(2.3%) or almost always (3.4%) willing to make a call while driving. While 18% indicated that they 

sometimes and 27% indicated that they rarely are willing to do so. 

Figure 3-4: Willingness to Make Phone Calls When Driving

2.3% 3.4%

18.2%

27.4%

48.5%

0%

10%

20%

30%

40%

50%

Always Almost Always Sometimes Rarely Never

Q6a. When you are driving, how often are you willing to MAKE a phone call? [Read List]

Base: All Respondents

Unweighted N= 6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

31 

Table 3-3 shows the reasons respondents gave for making calls on their cell phone while driving. Almost 

half of respondents (45%) stated that they are willing to make phone calls if they think it is important or 

urgent, and 16% are willing to initiate a phone call if it is work related. More than 1 in 10 respondents 

stated that they are willing to make calls if they need directions or other information (13%), that it 

depends on who they are calling (13%), or if it’s a personal or social call (11%). Other reasons for making 

calls while driving included reporting an emergency (5%) and boredom (2%).

Table 3-3. Reasons For Making Calls While Driving

Q6b. What are the reasons you are more likely 

to MAKE a call while driving? [Multiple 

Record] Percent

How important/urgent I think the call is 45.3%

Work-related 15.6%

If I need directions or other information 12.7%

Who I'm calling 12.7%

Personal or social 11.4%

Report a traffic crash/emergency 5.5%

Boredom 2.4%

Report a medical emergency 1.7%

Availability of the phone 1.2%

Personal Safety 1.0%

Non-stressful traffic conditions 0.9%

I think it's safe to call 0.5%

Time of day 0.3%

Traveling at a low speed 0.3%

Tired (talking keeps me awake) 0.2%

Good weather conditions 0.2%

No police officers in sight 0.1%

If state law permits 0.1%

Base: Make phone calling while driving at least rarely

Unweighted N = 3,324 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

32 

When asked how they make a call while driving, 53% of respondents stated that they use the speed dial or 

the favorites feature on their cell phone. Over 2 in 5 respondents mentioned dialing manually (43%), 42% 

mentioned selecting the number by scrolling through saved numbers, and 40% mentioned using voice 

dialing by speaking the number or person’s name into the microphone of the cell phone. One in 5 

respondents (20%) said that the method varies. 

Figure 3-5: Method of Dialing Phone Number While Driving

53.0%

43.4% 42.1% 39.8%

19.5%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Speed dial or

favorites

Manual dialing Scroll through

saved numbers

and select

Voice-dial

(speaking a name

or phone number)

Varies

Q6c. Which of the following ways do you usually MAKE a call while driving? Please answer Yes or No after I read each item.

Base: Respondents Who Make Phone Calls Driving

Unweighted N= 3,324
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

33 

Respondents were asked if their driving is any different when they are talking on a cell phone. Half (50%) 

of respondents stated that there is no difference in their driving Almost 1 in 5 respondents (18%) reported

that they drove more slowly when they were on the phone and 17% reported that they are more distracted 

and not as aware if they were driving and talking on the phone. One out of 20 respondents (5.2%) believe 

they are more focused and pay more attention to the road if they are on the phone, while a small 

percentage noted that they may drift out of the lane or roadway (1.6%), or drive more erratically (0.4%) 

while on the phone. 

Table 3-4. Perceived Difference in Driving When Talking on a Cell Phone 

7. How, if at all, would you say your driving is 

different when you are TALKING on the phone?

[Multiple Record] Percent

No difference 50.3%

Drive slower 17.9%

Distracted/not as aware of things 17.2%

More focused/pay more attention 5.2%

Drift out of the lane or roadway 1.6%

Never use cell phone with car is in motion 1.0%

Change lanes less frequently 0.9%

Avoid changing lanes altogether 0.9%

Drive faster 0.9%

Look in your rear or side view mirrors more 

frequently 0.5%

Apply the brakes suddenly 0.5%

Drive erratic/less careful 0.4%

Look in your rear or side view mirrors less 

frequently 0.4%

Follow lead vehicle more closely 0.2%

Increase distance from lead vehicle 0.1%

Change lanes more frequently 0.1%

Base: Answer a call at least rarely, or make a call at least rarely

Unweighted N = 3,887 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

34 

Earlier in the survey, 21% of respondents answered that they sent text messages (either always, almost 

always, sometimes, or rarely – See Table 2-2, Q4f). These respondents were asked a follow-up question 

to confirm this behavior. More than two-thirds of respondents (67%) who had previously stated that they 

rarely, sometimes, almost always, or always sent texts or e-mails while driving confirmed this was the 

case by responding positively when asked if they had ever done so. Upon further examination, it appears 

that respondents who earlier in the survey stated that they rarely or sometimes send texts or e-mails while 

driving were less likely to state that they send texts or e-mails while driving when asked again. Thus, the 

overall percentage of all drivers who admit to sending text messages while driving is 14%.

Figure 3-6: Confirmation - Do You Send Text Messages or E-mails While Driving

Yes, 14.3%

No, 85.7%

Q9. Do you ever SEND text messages or e-mails when you are driving?

Base: All respondents

Unweighted N= 6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

35 

Examining the confirmation question by age shows that younger drivers were more likely to confirm that 

they send messages while operating a vehicle. Around 7 in 10 respondents 16 to 20 (71%) confirm that 

they have sent messages while driving. More than two-thirds of respondents (69%) 35 to 44, and 50% of 

those in the 45-to-54 age group confirm that they send text messages. Among older drivers who initially 

stated that they had at least rarely sent a text message while driving, less than half (55 to 64 (45%) and 65 

or older (33%)) confirm that they send messages while driving.

Figure 3-7: Confirmation of Text Messaging Behavior, by Age

71.1% 69.2% 73.7% 69.1%

50.0% 45.3%

33.3%

28.9% 30.3% 26.3% 30.9%

50.0%

50.9%

66.7%

0.5% 3.8%

0%

20%

40%

60%

80%

100%

16 to 20

(N=177)

21 to 24

(N=187)

25 to 34

(N=416)

35 to 44

(N=226)

45 to 54

(N=177)

55 to 64

(N=79)

65+

(N=16)*

Yes No Not Sure

Q9. Do you ever SEND text messages or e-mails when you are driving?

Q24. What is your age?

Base: Respondents Who Send Text Messages While Driving

Unweighted N= See Chart

*Sample size was less than 50.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

36 

Respondents who confirmed that they send texts or e-mails while driving were asked under what 

conditions they are more likely to do so (see Table 3-5). Almost half of these respondents (49%) report 

that they are more likely to send a message if it is important. Another 14% reported that it depends on 

who they are messaging and 12% are more likely to send a message if it is work-related. Another 1 in 10

(10%) are more likely to send a message if it is personal or social in nature, and 9% will do so if the 

message is a short reply. Respondents were less likely to cite reasons such as being in need of directions 

(2.4%), non-stressful traffic conditions (1.8%), or boredom (1.6%). 

Table 3-5. Reasons for Sending Text Message or E-mail While Driving

10a. What makes it more likely you will 

SEND a text message or e-mail while 

driving? [Multiple Record]5 Percent

How important I think the message is 48.8%

Who I'm messaging 13.6%

Work-related 12.2%

Personal or social 10.0%

Making/responding to a quick/short 

message/call 9.1%

In need of directions or other information 2.4%

Non-stressful traffic conditions 1.8%

Boredom 1.6%

Time of day 0.9%

I think it's safe to call 0.9%

Personal Safety 0.8%

Report a traffic crash/emergency 0.7%

Report a medical emergency 0.6%

Traveling at a low speed 0.6%

Good weather conditions 0.3%

If state law permits 0.3%

If no police officers are in sight 0.3%

Base: Ever send text messages or e-mails while driving

Unweighted N = 872 

 

5 Respondents volunteered the answers to this question and were not read answer options. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

37 

When asked what they usually do when sending a message while driving, 44% reported that they wait 

until they are stopped at a red light or a stop sign to send the message. More than one-third of respondents 

(35%) stated that they continue to drive while composing and sending the message, while 8% hand the 

phone to a passenger and dictate the message. Slightly more than 1 in 20 (7%) respondents use a voice 

command feature or pull over to a safe location to compose and send the message (6%). Overall, 79% of 

respondents, who send text messages report that they are manually composing messages while on the 

roadways. 

Figure 3-8: How Text Messages Are Sent While Driving

50%

43.5%

40%

35.3%

30%

20%

10% 7.8% 6.5% 6.2%

0%

Wait until you Continue to drive Hand the phone to Use a voice Pull over to a safe

reach a red light or while completing a passenger to do command feature location to send

stop sign to send the message your messaging (speech dictation) the message

the message

Q10. If you SEND a text message or e-mail while driving, do you USUALLY...[Read List]

Base: Respondents Who Send Text Messages While Driving

Unweighted N= 872
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

38 

Respondents who sent messages while driving were asked how their driving was different when they 

were sending messages from their normal driving (Table 3-6). One-third of drivers (33%) claimed that 

there was no difference in their driving. About one-quarter (24%) said they were distracted and not as 

aware of things happening on the roadway, and 21% reported that they drive more slowly while 

messaging. More than 1 in 10 respondents (11%) reported that they drift out of the roadway or lane while 

messaging, while 3% claimed they are more focused and pay more attention to what is going on around 

them. 

Table 3-6. Perceived Difference in Driving When Sending Text Messages 

Q11. How would you say your driving is different when 

you are SENDING TEXT OR E-MAIL MESSAGES?

[Multiple Record] Percent

No difference 32.9%

Distracted/not as aware of things 24.3%

Drive slower 21.1%

Drift out of the lane or roadway 10.9%

More focused/pay more attention 2.7%

Drive erratic/less careful 2.1%

Never use cell phone with car is in motion 1.6%

Drive faster 1.0%

Avoid changing lanes altogether 0.9%

Change lanes more frequently 0.8%

Follow lead vehicle more closely 0.7%

Apply the brakes suddenly 0.6%

Change lanes less frequently 0.5%

Look in your rear or side view mirrors more frequently 0.5%

Look in your rear or side view mirrors less frequently 0.4%

Increase distance from lead vehicle 0.4%

Use turn signal less regularly 0.2%

Base: Ever send text messages while driving

Unweighted N = 872 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

39 

CHAPTER 4 

PERCEPTIONS OF SAFETY OF DISTRACTED DRIVING

This chapter examines the respondents’ assessment of safety in a variety of situations in which they are 

passengers in vehicles operated by drivers who are engaged in other activities while driving. All 

respondents were asked how safe they would feel as a passenger if the driver were to engage in certain 

activities listed in Table 4-1. Almost all respondents stated that they would feel very unsafe if their driver 

was watching a movie (96%), using a laptop computer (95%) or reading (95%) while operating the 

vehicle. A large majority of respondents stated that they would feel very unsafe if the driver was sending 

(86%) or reading (85%) text messages or e-mails. More than 7 in 10 respondents (72%) said that they 

would feel very unsafe if the driver was doing personal grooming. About 3 in 5 respondents (63%) stated 

that they would feel very unsafe if the driver was wearing headphones and listening to music, and 42% 

said they would feel very unsafe if the driver was talking on the cell phone with the phone in hand. In 

addition, 34% of respondents would feel very unsafe if the driver was manipulating the navigation system 

for driving directions while driving.

Table 4-1. Perceived Safety as a Passenger

Q14. How safe would you feel if the 

driver was to... 

N Very 

unsafe

Somewhat 

unsafe

A little 

less 

safe

Safe

Talk to other passengers in the vehicle 6,016 6.6% 12.9% 21.3% 58.5%

Eat or drink 6,016 18.5% 22.6% 33.4% 24.8%

Talking on a cell phone while holding the 

phone

6,016 41.8% 24.3% 23.1% 10.3%

Talking on a cell phone with a hands-free 

device

6,016 14.7% 19.7% 23.4% 41.4%

Read, such as a book, newspaper, iPad or 

Kindle?

6,016 94.7% 3.2% 1.5% 0.5%

Read e-mails or text messages 6,016 84.9% 10.3% 3.8% 0.8%

Send text messages or e-mails 6,016 85.9% 9.4% 3.7% 0.9%

Talk or interact with children in the back 

seat

6,016 22.7% 33.7% 23.8% 18.8%

Do personal grooming, such as put on 

make-up, shave, or look at yourself in the 

mirror

6,016 72.0% 18.4% 7.8% 1.6%

Adjust the car radio, tapes, or CD player 6,016 13.4% 31.9% 23.5% 30.6%

Singing along to a song on the radio 6,016 3.6% 11.6% 13.7% 70.5%

Using a laptop computer 6,016 94.8% 3.4% 1.3% 0.4%

Using a portable music player with 

headphones on

6,016 63.0% 22.4% 8.3% 5.7%

Manipulating a navigation system for 

driving directions

6,016 34.3% 37.1% 18.2% 9.2%

Watching a movie 6,016 96.4% 2.2% 1.0% 0.2%

Base: All respondents
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

40 

Responses to the questions listed in Table 4-1 were examined by driver type to assess if an 

individual’s perceptions of safety while a passenger were related to his/her behavioral tendencies 

toward distracted driving. When certain behaviors are broken out by driver type, distractionprone drivers tend to be less likely to feel unsafe as a passenger when the driver engages in 

distracted behaviors. Figure 4-1 shows the perceptions of safety by driver type of respondents 

who are passengers in a vehicle in which the driver is talking to other passengers while driving. 

Slightly less than half of respondents classified as distraction-averse drivers (49%) compared to 

77% of respondents classified as distraction-prone drivers stated that they would feel safe if the 

driver was conversing with others in the car while driving. More than one-quarter of respondents 

classified as distraction-averse drivers (26%) compared to 9% of respondents classified as 

distraction-prone reported they would feel at least somewhat unsafe. 

Figure 4-1: Perception of Safety, by Driver Type: Driver Is Talking to Other Passengers 

100%

90%

80% 76.5%

70%

60%

48.6% 50%

40%

30% 24.9%

20% 16.8% 15.0%

8.7% 10% 5.8%

2.7%

0%

Very unsafe Somewhat unsafe A little less safe Safe

Distraction-Averse Driver (N=3,968) Distraction-Prone Driver (N=1,989)

Q14-a. Now I’m going to read a list of things people sometimes do while driving. Tell me how safe you would feel if you were a 

passenger riding in a car while your driver was doing the following. For each please tell me if you would feel very unsafe, 

somewhat unsafe, a little less safe, or safe – no problem – would not pay any more attention. a. Talking to other passengers in the 

vehicle. 

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

41 

Figure 4-2 shows that respondents who have children under 16 in the household are more likely than 

those without children of that age in the household to feel safe in a car when the driver is interacting with 

children in the backseat. Among respondents with children under 16, 29% indicated that they would feel

safe. Among those without any children under 16 in the household, only 13% indicated they would feel 

safe in a car if the driver was interacting with children in the back seat. 

Figure 4-2 Respondents Who Feel Safe When Driver Is Talking to Children in the 

Backseat, by Number of Children in the Household 

13.2%

28.7% 28.8%

0%

10%

20%

30%

40%

50%

0 (N=3,853) 1 to 3 (N=1,937) 4 or more (N=119)

Q14-h. Now I’m going to read a list of things people sometimes do while driving. Tell me how safe you would feel if you were a 

passenger riding in a car while your driver was doing the following. For each please tell me if you would feel very unsafe, 

somewhat unsafe, a little less safe, or safe – no problem – would not pay any more attention. h. Talking or interacting with 

children in the back seat

Base: All Respondents

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

42 

Figure 4-3 compares the perceptions about safety of distraction-averse and distraction-prone people when 

the driver is talking on a cell phone while holding the phone. Overall, distraction-averse people were 

much more likely to feel very unsafe than the distraction-prone people. Just over half of people classified 

as distraction-averse drivers (55%) reported that they would feel very unsafe in this situation, while only 

17% of people classified as distraction-prone stated they would feel very unsafe. Conversely, 21% of 

distraction-prone people and only 5% of distraction-averse people said they would feel safe if the driver 

was talking on the phone while holding it in hand. 

Figure 4-3: Perception of Safety, by Driver Type: Driver Is Talking on Cell Phone While 

Holding Phone 

55.4%

21.9%

17.4%

4.6%

17.1%

28.6%

33.3%

20.7%

0%

20%

40%

60%

80%

100%

Very unsafe Somewhat unsafe A little less safe Safe

Distraction-Averse Driver (N=3,968) Distraction-Prone Driver (N=1,989)

Q14-c. Now I’m going to read a list of things people sometimes do while driving. Tell me how safe you would feel if you were a 

passenger riding in a car while your driver was doing the following. For each please tell me if you would feel very unsafe, 

somewhat unsafe, a little less safe, or safe – no problem – would not pay any more attention. c. Talking on a cell phone while 

holding the phone. 

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

43 

Respondents were asked how likely they were to intervene if they were passengers in a vehicle in which 

the driver was talking on a cell phone while holding the phone and driving. Overall, 66% of all 

respondents reported that they were at least somewhat likely to intervene. People classified as distractionprone drivers were less likely than those classified as distraction-averse to report that they would 

intervene if the driver was talking on a phone while driving. While 53% of distraction-averse drivers are 

very likely to intervene, 32% of distraction-prone drivers said that they would do so. Almost one-quarter 

of distraction-prone drivers (23%) and 17% of distraction-averse drivers said they were very unlikely or 

would never intervene. 

Figure 4-4: How Likely Are You to Intervene if the Driver Is Talking on a 

Cell Phone While Holding the Phone, by Driver Type

53.2%

18.7%

10.3% 9.7% 7.2%

32.1%

24.5%

19.6%

13.7%

9.3%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Very Likely Somewhat

Likely

Somewhat

Unlikely

Very Unlikely Never would

intervene

Distraction-Averse Driver (N=3,968) Distraction-Prone Driver (N=1,989)

Q14b. How likely are you to do or say something to your driver if they’re TALKING on a hand-held cell phone while driving?

[Read List] 

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

44 

Figure 4-5 compares the perception about safety of distraction-prone and distraction-averse people in a 

situation where their driver is reading e-mails or text messages while driving. Distraction-averse people 

perceived this situation as more unsafe than distraction-prone people. Almost all those people classified 

as distraction-averse drivers (95%) reported they would feel very unsafe compared to 67% of people who 

were classified as distraction-prone drivers. While only 2% of distraction-prone people indicated that they 

would feel safe in this situation, 31% indicated that they would feel somewhat unsafe or a little less safe 

in this situation. 

Figure 4-5: Perception of Safety by Driver Type: Driver Is 

Reading E-mails or Text Messages 

94.7%

3.4% 1.4% 0.3%

66.9%

22.9%

8.3%

1.8%

0%

20%

40%

60%

80%

100%

Very unsafe Somewhat unsafe A little less safe Safe

Distraction-Averse Driver (N=3,968) Distraction-Prone Driver (N=1,989)

Q14-f. Now I’m going to read a list of things people sometimes do while driving. Tell me how safe you would feel if you were a 

passenger riding in a car while your driver was doing the following. For each please tell me if you would feel very unsafe, 

somewhat unsafe, a little less safe, or safe – no problem – would not pay any more attention. f. Reading e-mails or text messages. 

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

45 

Figure 4-6 compares the perceptions about safety of distraction-prone and distraction-averse people for 

the situation where they are passengers in vehicles with drivers who are also sending text messages or emails while driving. The overwhelming majority of distraction-averse people (95%) and 68% of

distraction-prone people reported that they would feel very unsafe if the driver was engaged in this 

behavior while driving. Just under one-third (29%) of people classified as distraction-prone drivers 

reported that they would feel somewhat unsafe or a little less safe in this situation. No distraction-averse 

people and only 2.1% of distraction-prone people indicated that they would feel safe if the driver was 

sending e-mails or text messages while driving. Overall, the degree to which respondents reported feeling 

safe if a driver was sending electronic messages was very similar to their perceptions about safety if the 

driver was reading messages while driving. 

Figure 4-6: Perceptions of Safety by Driver Type: 

Driver Is Sending Text Messages or E-mails 

95.4%

3.0% 1.1% 0.2%

68.4%

21.2%

8.3%

2.1%

0%

20%

40%

60%

80%

100%

Very unsafe Somewhat unsafe A little less safe Safe

Distraction-Averse Driver (N=3,968) Distraction-Prone Driver (N=1,989)

Q14-g. Now I’m going to read a list of things people sometimes do while driving. Tell me how safe you would feel if you were a 

passenger riding in a car while your driver was doing the following. For each please tell me if you would feel very unsafe, 

somewhat unsafe, a little less safe, or safe – no problem – would not pay any more attention. g. Sending text messages or e-mails.

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

46 

Overall, 87% of respondents stated that they were at least somewhat likely to intervene if they were 

passengers in a vehicle when a driver was sending e-mails or text messages. Figure 4-7 shows the 

likelihood of intervention by people classified as distraction-prone and distraction-averse if they are 

passengers in a vehicle in which the driver is sending e-mails or text messages while driving. Overall, the 

majority of distraction-averse and distraction-prone drivers were very likely to intervene. More than 8 in

10 (83%) distraction-averse and 6 in 10 (61%) distraction-prone drivers would be very likely to intervene. 

Very few respondents indicated that they were never likely to intervene. The percentage of the noninterveners was 4% for those classified as distraction-prone drivers, and 2% for those classified as 

distraction-averse. 

Figure 4-7: How Likely Are You to Intervene if Driver Is Sending E-mails or Text 

Messages, by Driver Type

100%

82.7%

80%

61.2%

60%

40%

19.9%

20%

9.2% 6.9% 4.6% 5.6% 2.8% 3.9% 2.2%

0%

Very Likely Somewhat Somewhat Very Unlikely Never would

Likely Unlikely intervene

Distraction-Averse Driver (N=3,968) Distraction-Prone Driver (N=1,989)

Q14c. How likely are you to do or say something to your driver if they’re SENDING TEXT MESSAGES OR E-MAILS while 

driving? [Read List]

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

47 

Respondents were asked how many seconds they believe a driver can take his eyes off the road before it 

becomes significantly more dangerous. The majority of respondents across all age groups gave an answer 

between 0 and 2 seconds. Younger respondents were more likely than older respondents to give an 

answer between 3 and 6 seconds, with 44% of respondents 16 to 20 giving an answer between 3 and 6

seconds while only 29% of respondents 65 and older did so. 

Figure 4-8: Number of Seconds a Driver Can Safely Take His Eyes Off the Road, by Age

50.2%

57.5%

68.0%

64.1%

69.6% 70.1%

64.0%

44.2%

38.5%

27.7% 30.4%

26.1% 25.6%

28.8%

5.6% 4.0% 4.3% 5.5% 4.2% 4.3%

7.2%

0%

20%

40%

60%

80%

100%

16-20

N=389

21-24

N=371

25-34

N=1,109

35-44

N=776

45-54

N=1,044

55-64

N=1,036

65+

N=1,040

0-2 secs 3-6 secs 7+ secs

Q13. How many seconds do you believe a driver can take his eyes off the road before driving becomes significantly more 

dangerous?

Base: All Respondents 

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

48 

Figure 4-9 compares the number of seconds a respondent believes drivers can safely take their eyes of the 

road by driver type. While a majority of both distraction-averse and distraction-prone drivers provided an 

answer that was between 0 and 2 seconds, 35% of distraction-prone drivers gave an answer of 3 to 6 

seconds, while only 27% of distraction-averse drivers did so.

Figure 4-9: Number of Seconds a Driver Can Safely Take His Eyes Off the Road 

By Driver Type

67.3%

61.1%

26.9%

35.1%

5.8% 3.8%

0%

20%

40%

60%

80%

100%

Distraction-Averse Driver (N=3,652) Distraction-Prone Driver (N=2,168)

0-2 secs 3-6 secs 7+ secs

Q13. How many seconds do you believe a driver can take his eyes off the road before driving becomes significantly more 

dangerous? 

Base: All Respondents Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

49 

CHAPTER 5 

CHANGES IN CELL PHONE RELATED DISTRACTED DRIVING

To assess whether drivers’ cell phone-related distracted driving behavior is changing, respondents were 

asked if the frequency with which they make or receive calls, or send text messages or e-mails while 

driving, has changed in the past 30 days. Most respondents reported that the frequency with which they 

make and receive calls while driving has stayed the same, but some respondents did report a decrease. 

More than three-quarters of respondents (77%) stated that the frequency with which they make or receive 

calls is the same now as it was in the past 30 days. Fewer than 1 in 20 respondents (3%) said that they are 

making or receiving calls more often, while 19% said they are making calls less often. 

Figure 5-1: Has Your Frequency of Making and Receiving Phone Calls While Driving 

Increased, Decreased, or Stayed the Same

2.5%

19.1%

76.8%

1.4%

0%

20%

40%

60%

80%

100%

Increased Decreased Stayed the same Never used a phone

while driving

Q15. In the past 30 days, has your frequency of making and receiving phone calls while driving increased, decreased, or stayed 

the same?

Base: Respondents That Make or Accept Phone Calls While Driving

Unweighted N= 3,968
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

50 

Table 5-1 lists the reasons for the decrease in making and receiving phone calls while driving given by 

respondents who reported a decrease in phone calls while driving in the past 30 days. Overall, the most 

frequent reason given was an increased awareness of safety, with 24% providing this as their reason for 

the decrease in the past 30 days. About 1 in 6 (17%) said they were not receiving as many calls and 16% 

said that they do not make calls while driving. Almost 1 in 10 (8%) reported the reason as driving less 

often, while 6% cited laws that ban cell phone usage and 6% said they were getting fewer work-related 

calls. Fewer than 1 in 20 respondents reported that the change was due to influence or pressure from 

others (3.0%), a relationship change (2.9%), not wanting to receive a ticket (2.4%), the weather (2.4%), 

problems with their phone (2.2%), or having family in the car (1.5%). 

Table 5-1. Reasons for Decrease in Making and Receiving Phone Calls While Driving

15a. What caused your frequency of making and 

receiving phone calls while driving to decrease?

[Multiple Record] Percent

Increased awareness of safety 24.3%

Less use/busy/less people call/text/have number 16.7%

Don't make/take calls/text while driving 15.7%

Driving less/not on the road as much 8.4%

Law that bans cell phone use 6.0%

Job-related (work less/lost job/don't get as many work calls) 5.5%

Influence/pressure from others 3.0%

Less use due to family/relationship changes 2.9%

Don't want to get a ticket 2.4%

The weather 2.4%

Phone issues (all mentions) 2.2%

Family/children in the car 1.5%

Nothing/no specific reason 0.9%

More long distance driving 0.5%

Was in a crash 0.1%

Other (specify) 4.3%

Not sure 7.0%

 Base: Respondents whose frequency of using phone in vehicle decreased 

 Unweighted N = 735 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

51 

Figure 5-2 shows the frequency with which respondents reported making and receiving phone calls while 

driving by driver type. Regardless of driver type, most respondents report no changes in the frequency 

with which they make calls. Fewer than 1 in 20 distraction-averse drivers (2%) as well as distractionprone drivers (4%) stated that the frequency of making and receiving phone calls increased in the past 30 

days, while 18% of distraction-averse drivers and 20% of distraction-prone drivers stated that they are 

making calls less often. More than three-quarters of distraction-averse drivers (77%) and distractionprone drivers (76%) reported that the frequency with which they make calls remained the same. 

Figure 5-2: Has Your Frequency of Making and Receiving Phone Calls While Driving 

Increased, Decreased, or Stayed the Same, by Driver Type

1.5%

18.3%

77.2%

3.5% 2.7%

19.8%

76.4%

0.2%

0%

20%

40%

60%

80%

100%

Increased Decreased Stayed the same Never used a phone

while driving

Distraction-Averse Driver (N=2,043) Distraction-Prone Driver (N=1,890)

Q15. In the past 30 days, has your frequency of making and receiving phone calls while driving increased, decreased, or stayed 

the same?

Base: Respondents Who Make or Accept Phone Calls While Driving and Were Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

52 

When asked whether the frequency of sending text messages while driving has increased, decreased or 

stayed the same over the past 30 days, 67% of respondents reported the frequency has stayed the same. 

More than a quarter (27%) stated the frequency had decreased, while 5% said that it had increased. 

Respondents who had sent a text message or e-mail while driving reported a comparatively larger 

decrease in the frequency with which they had done so in the past 30 days than respondents who have 

placed or received a call while driving reported in the past 30 days. 

Figure 5-3: Has Your Frequency of Sending Text Messages or E-mails While Driving 

Increased, Decreased, or Stayed the Same

100%

80%

67.4%

60%

40%

26.6%

20%

5.1%

0%

Increased Decreased Stayed the same

Q15b. In the past 30 days, has the frequency with which you send and receive text messages or e-mails while driving increased, 

decreased, or stayed the same?

Base: Respondents That Send Text Messages or E-mails While Driving

Unweighted N= 838
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

53 

Table 5-2 shows respondents’ reasons for decreasing the frequency with which they send and receive text 

messages and e-mails while driving in the past 30 days. Almost 4 in 10 respondents (38%) cited an 

increased awareness of safety, while 10% mentioned not being as busy and 9% mentioned driving less 

often. More than 1 in 20 respondents cited laws that ban texting (8%), job-related reasons (7%), or 

pressure from others (7%). Fewer than 1 in 20 respondents mentioned not wanting to get a ticket (3.8%), 

the weather (3.4%), problems with their phone (2.4%), changes in their relationships (1.6%), or having 

family in the car (1.6%). Overall, the most frequently provided reason for decreases in sending and 

receiving text messages while driving in the past 30 days was an increased awareness of safety.

Table 5-2. Reasons for Decrease in Sending and Receiving Text Messages 

and E-mails While Driving

Q15c. What caused the frequency with which you send 

and receive text messages or e-mails while driving to 

decrease? [Multiple Record] Percent

Increased awareness of safety 37.7%

Less use/busy/less people call/text/have number 9.5%

Driving less/not on the road as much 8.7%

Don't make/take calls/text while driving 8.4%

Law that bans texting/e-mailing 7.6%

Job-related (work less/lost job/don't get as many work calls) 7.3%

Influence/pressure from others 6.7%

Don't want to get a ticket 3.8%

The weather 3.4%

Phone issues (all mentions) 2.4%

Less use due to family/relationship changes 1.6%

Family/children in the car 1.6%

More long distance driving 0.9%

Was in a crash 0.8%

Driving faster 0.6%

Other (specify) 6.7%

Not sure 1.6%

Base: Respondents whose use of text/e-mail in vehicle has decreased

Unweighted N = 230
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

54 

CHAPTER 6 

DISTRACTED DRIVING LAWS

Respondents were asked a series of questions about their knowledge and support of laws banning cell 

phone use or sending and reading text messages and e-mails while driving. They were also asked about 

the likelihood of receiving a ticket for talking on a cell phone or sending text messages or e-mails while 

driving. 

Overall, 54% of respondents reported that their state does have a law banning talking on a hand-held cell 

phone while driving, with 45% of respondents stating that their state has such a law, and 9% stating that 

their state “probably” has such a law. Almost one-third of respondents (31%) stated that their State has no 

such law, while an additional 15% were not sure. 

Figure 6-1: Does Your State Have a Law Banning Talking on a Hand-Held Cell Phone 

While Driving

Not Sure

15.4%

Yes

44.8%

No

30.8%

Yes, 

probably

9.0%

Q16. Does [SAMPSTAT] have a law banning talking on a hand-held cell phone while driving?

Base: All Respondents

Unweighted N= 6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

55 

Examining the responses for States with and without laws banning talking on hand-held cell phones while 

driving, Figure 6-2 shows that in States with such laws, 88% of respondents are aware of the law, 5% 

think the State probably has such a law, 4% report that the State does not have the law, and 3% are not 

sure. 

More than 2 in 5 respondents (42%) in States without laws banning talking on hand-held cell phones 

while driving are aware that the State does not have such a law. More than 1 in 5 (21%) are not sure, 28%

stated that the State had a law and 11% think that the State probably has such a law. 

Figure 6-2: Does Your State Have a Law Banning Talking on a Hand-Held Cell Phone 

While Driving, by Actual State Law 

No Not Sure

Yes, 3.5% 3.1% probably

5.2%

Yes

88.2%

Not Sure Yes

20.6% 27.7%

Yes, 

No probably

41.6% 10.5%

Q16. Does [SAMPSTAT] have a law banning talking on a hand-held cell phone while driving?

Base: All Respondents

Unweighted N= See Chart

Yes, State Has Law 

N = 1,687

No, State Does Not Have Law 

N = 4,329
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

56 

Respondents in States with laws banning hand-held use of cell phones while driving were asked 

about the likelihood of a driver who frequently uses his/her cell phone receiving a ticket for this 

infraction in the next 6 months. Overall, 52% of respondents thought that the driver was likely to 

get a ticket and 44% stated that it was unlikely that the driver would be ticketed. More than onequarter of respondents (27%) thought it was very likely, and 25% of respondents thought it was 

somewhat likely that the driver would be ticketed. An equal percentage of respondents (22% 

each) thought it was very unlikely or somewhat unlikely that the driver would be ticketed. A 

small percentage of respondents (4%) was not sure. 

Figure 6-3: Likelihood of Ticket for Talking on a Cell Phone While Driving

50%

40%

30%

26.9%

25.4%

22.4% 21.7%

20%

10%

3.6%

0%

Very likely Somewhat likely Somewhat Very unlikely Not Sure

unlikely

Q16a. Assume that over the next six months someone frequently TALKS on a hand-held cell phone while driving. How likely do 

you think that person would be to receive a ticket for talking on a cell phone while driving? [Read List]

Base: Respondents That Live in States With Banning Talking on a Cell Phone While Driving

Unweighted N= 3,981
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

57 

Respondents’ perceptions of the likelihood of a frequent cell phone user receiving a ticket in the next 6 

months in States with laws banning hand-held cell phone use were examined by the education level of 

respondents. Figure 6-4 shows a clear pattern where respondents with less formal education are more 

likely to believe that the driver will receive a ticket and respondents with more formal education are more 

likely to state that the driver will not receive a ticket. 

More than one-third of respondents (35%) with no high school degree believe that the driver is very likely 

to receive a ticket, while 27% of respondents with a graduate degree believe that it is very unlikely that 

the driver will receive a ticket. Conversely, only 16% of respondents without a high school degree believe 

that the driver is very unlikely to be ticketed, and 18% of respondents with graduate degrees believe that 

the driver is highly likely to receive a ticket. Respondents with some college education but no degree are 

almost evenly split between the two extremes, with 23% stating that it would be very likely for the driver 

to get a ticket and 22% stating it would be very unlikely. 

Figure 6-4: Likelihood of Ticket for Talking on a Cell Phone While Driving, by Highest 

Level of School Completed

50%

40%

35.2%

30.6%

30% 26.6% 25.0% 23.4% 23.9% 22.6%22.3% 22.2%

19.5% 20% 17.8%

15.5%

10%

0%

Very likely Very unlikely

No Hs Degree (N=401)

High School Graduate (N=1,110)

Some College (N=969)

College Graduate (N=740)

Some Graduate School (N=107)

Graduate Degree (N=600)

Q16a. Assume that over the next six months someone frequently TALKS on a hand-held cell phone while driving. How likely do 

you think that person would be to receive a ticket for talking on a cell phone while driving? [Read List]

Base: Respondents Who Live in States That Ban Talking on a Cell Phone While Driving

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

58 

Figure 6-5 shows that there is little difference in respondents’ perception of the likelihood that a driver 

talking on a cell phone would receive a ticket, by driver type. Overall, distraction-prone and distractionaverse drivers were about equally divided into those who believed the driver would be ticketed or not 

ticketed, with 53% of distraction prone drivers and 52% of distraction-averse drivers indicating that it was

at least somewhat likely that the driver would get a ticket. Among distraction-averse drivers, 29% 

indicated that it was very likely, and 23% stated that it was somewhat likely that the driver would get a 

ticket. Among distraction-prone drivers, 23% stated it was very likely that the driver would receive a 

ticket, and 30% stated that it was somewhat likely. A similar percent of distraction-prone drivers and 

distraction averse drivers indicated that the driver was somewhat unlikely to receive a ticket (24% versus

22%), that the driver was very unlikely to receive a ticket (19% versus 23%), or they were not sure (3% 

versus 4%).

Figure 6-5: Likelihood of Ticket for Talking on a Cell Phone While Driving, by Driver Type

50%

40%

30.4%

30% 28.7%

24.4%

22.9% 23.3% 22.7% 21.7%

19.2% 20%

10%

3.6% 3.1%

0%

Very likely Somewhat likely Somewhat Very unlikely Not Sure

unlikely

Distraction-Averse Driver (N=2,734) Distraction-Prone Driver (N=1,203)

Q16a. Assume that over the next six months someone frequently TALKS on a hand-held cell phone while driving. How likely do 

you think that person would be to receive a ticket for talking on a cell phone while driving? [Read List]

Base: Respondents Who Live in States That Ban Talking on a Cell Phone While Driving and Were Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

59 

Respondents were asked whether they support a State law that bans talking on a hand-held cell phone 

while driving. The majority of respondents (74%) were in favor of such a law, regardless of whether their 

State had a ban. However, respondents who live in States that do not have a ban on talking on a hand-held 

cell phone while driving were more likely to oppose a ban than respondents living in States that already 

have a ban (29% versus 10%). 

Figure 6-6: Do You Support a Law Banning Talking on a Hand-Held Cell Phone While 

Driving

Yes

87.9%

No

10.3%

Don’t 

Know

1.5%

Refused

0.2%

Yes

68.4%

No

28.5%

Don't 

Know

2.9%

Refused

0.2%

Q17. Do you support a State law banning talking on a hand-held cell phone while driving?

Base: All Respondents

Unweighted N= 6,016

N = 1,546Yes, State 

Has Law 

 

No, State Does Not Have Law 

N = 4,329
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

60 

 

Figure 6-7 shows that respondents’ support for a State law banning talking on a hand-held cell phone 

while driving is related to driver type. Distraction-averse drivers were more likely to support such a law, 

while distraction-prone drivers were more likely to oppose such a law. More than 4 in 5 distraction-averse 

drivers (82%) and 60% of distraction-prone drivers stated that they support a law banning talking on a 

cell phone while driving. About 1 in 6 (16%) distraction-averse drivers and 37% of distraction-prone 

drivers are opposed to such a law. 

Figure 6-7: Support for Law Banning Talking on a Hand-Held Cell Phone While Driving 

By Driver Type 

81.9%

15.6%

2.5%

59.5%

37.4%

3.0%

0%

20%

40%

60%

80%

100%

Yes No Not Sure

Distraction‐Averse Driver (N=3,968) Distraction‐Prone Driver (N=1,989)

Q17. Do you support a State law banning talking on a hand-held cell phone while driving? 

Base: All Respondents Assigned a Driver Type 

Unweighted N= See Chart 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

61 

Respondents who stated that they supported a ban on talking on a hand-held cell phone while driving, or 

who were unsure whether they supported such a ban, were asked how much they thought the fine should 

be for talking on a hand-held cell phone while driving. While the mean amount volunteered by 

respondents across age groups did not vary much, older respondents favored slightly higher fines. 

Respondents 21 to 24 had the lowest mean amount with only $178, while respondents 45 to 54 had the 

highest mean amount with $236. On average, respondents of all ages supported a fine of $209. 

Figure 6-8: Average Fine for Talking on Hand-Held Cell Phone While Driving, by Age 

$194.00

$178.00

$203.00

$190.00

$236.00

$225.00

$199.00

$0

$50

$100

$150

$200

$250

$300

16‐20

N=253

21‐24

N=213

25‐34

N=659

35‐44

N=511

45‐54

N=697

55‐64

N=709

65+

N=796

Q17a. What do you think the fine should be for talking on a hand-held cell phone while driving? 

Base: Respondents Who Support a Ban on Talking on a Hand-Held Cell Phone While Driving, or Don’t Know 

Unweighted N= 4,487 

 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

62 

When compared to driver type, the average fine volunteered by distraction-averse drivers for talking on a 

hand-held cell phone while driving was higher than the average fine volunteered by distraction-prone 

drivers ($229 versus $173). 

Figure 6-9: Average Fine for Talking on Hand-Held Cell Phone While Driving 

By Driver Type 

$229.00

$173.00

$0

$50

$100

$150

$200

$250

$300

Distraction-Averse Driver (N=2,654) Distraction-Prone Driver (N=1,211)

Q17a. What do you think the fine should be for talking on a hand-held cell phone while driving? 

Base: Respondents Who Support a Ban on Talking on a Hand-Held Cell Phone While Driving, or Don’t Know and Were 

Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

63 

Respondents were asked whether their State has a law that bans sending text messages or e-mails 

while driving. More than half of respondents (58%) reported that their State has such a law, and 

14% of respondents stated that their State does not have a law that bans sending electronic 

messages while driving. Almost 3 in 10 respondents (28%) were either unsure (17%), or thought 

it was likely but could not say for certain (11%), if their State has such a law. 

Figure 6-10: Does Your State Have a Law Banning Texting or E-mailing While Driving

Yes

Yes, probably 57.6%

11.4%

No

13.9%

Not Sure

17.1%

Q16b. Does [SAMPSTAT] have a law banning TEXTING OR E-MAILING while driving?

Base: All Respondents

Unweighted N= 6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

64 

Figure 6-11 shows driver’s awareness of State laws banning texting or e-mailing while driving by 

whether or not their State has such a law. In States with laws banning texting or e-mailing, 65% of 

respondents knew about the law, 11% thought that the State probably had such a law, 15% were not sure, 

and 8% stated that their State did not have such a law. 

In States without a law banning texting or e-mailing while driving, 29% of respondents were aware that 

there was no such law, 22% were not sure, and many believed that their State had (37%) or probably had 

(12%) such a law. 

Figure 6-11: Does Your State Have a Law That Bans Sending Electronic Messages While 

Driving, by Actual State Law

Yes

65.3%

Yes, 

probably

11.1%

No

8.2%

Not Sure

15.3%

Yes

37.0%

Yes, 

probably

12.1%

No

29.2%

Not Sure

21.7%

Q16b. Does [SAMPSTAT] have a law banning TEXTING OR E-MAILING while driving?

Base: All Respondents

Unweighted N=See Chart

Yes, State Has Law 

N = 4,470

No, State Does Not Have Law 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

65 

Respondents that reported living in a State with laws banning texting or e-mailing while driving were 

asked about the likelihood of a driver who frequently sends text messages or e-mails while driving 

receiving a ticket for this infraction in the next 6 months. Similar to Figure 6-3, Figure 6-12 shows that 

slightly more respondents believe it is likely that the driver would receive a ticket, with 53% stating it 

would be at least somewhat likely while 43% think it is at least somewhat unlikely. Almost 3 in 10 (29%) 

thought it was very likely, 24% thought it was somewhat likely, and more than 1 in 5 thought it was 

somewhat unlikely (21%) or very unlikely (22%). 

Figure 6-12: Likelihood of Ticket for Sending Text Messages or E-mails While Driving

28.8%

24.2%

21.0% 21.9%

3.8%

0%

10%

20%

30%

40%

50%

Very likely Somewhat likely Somewhat

unlikely

Very unlikely Not Sure

Q16c. Assume that over the next six months someone frequently sends text messages or e-mails while driving. How likely do you 

think that person would be to receive a ticket for sending text messages or e-mails while driving? [Read List]

Base: Respondents That Report Living in a State that Bans Sending Text Messages and E-mails While Driving

Unweighted N=5,115
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

66 

Figure 6-13 shows respondents’ perception of the likelihood that a driver sending electronic messages 

while driving would receive a ticket, by driver type. More than half of distraction-averse drivers (55%) as 

well as distraction-prone drivers (51%) thought that it was at least somewhat likely that the driver would 

be ticketed. 

Distraction-averse drivers were more likely to state that the driver was very likely to receive a ticket, 

while distraction-prone drivers more often reported the driver was only somewhat likely or not likely to 

receive a ticket, with 32% of distraction-averse drivers and 23% of distraction-prone drivers stating that 

the driver was very likely to receive a ticket. There was little difference by driver type in the frequency 

with which respondents stated that the driver was very unlikely to receive a ticket, with 22% of both 

distraction-prone and distraction-averse drivers stating that it was very unlikely. Almost a quarter of 

distraction-averse drivers (23%) and 28% of distraction-prone drivers thought it was somewhat likely that 

the driver would receive a ticket. 

Figure 6-13: Likelihood of Ticket for Sending Text Messages or E-mails While Driving, by 

Driver Type

31.8%

22.6%

19.3%

21.5%

4.8%

23.1%

27.5%

24.9%

22.0%

2.5%

0%

10%

20%

30%

40%

50%

Very likely Somewhat likely Somewhat

unlikely

Very unlikely Not Sure

Distraction-Averse Driver (N=3,400) Distraction-Prone Driver (N=1,662)

Q16c. Assume that over the next six months someone frequently sends text messages or e-mails while driving. How likely do you 

think that person would be to receive a ticket for sending text messages or e-mails while driving? [Read List]

Base: Respondents That Report Living in States that Ban Sending Text Messages and E-mails While Driving and assigned a

Driver Type

Unweighted N=See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

67 

Respondents were asked whether they would support a State law that bans texting or e-mailing while 

driving. The overwhelming majority of respondents (94%) were in favor of a law that bans sending 

electronic message while driving. However, as in Figure 6-6, respondents who live in States without such 

a ban were slightly more likely to oppose a ban than respondents living in a State that already has one 

(9% versus 5%). 

Figure 6-14: Do You Support a Law Banning Texting or E-mailing While Driving 

Yes

94.8%

No

4.7%

Don’t

Know

0.4%

Refused

0.1%

Yes

90.0%

No

8.7%

Don't

Know

1.3%

Refused

0.1%

Q17b. Do you support a State law banning texting or e-mailing while driving? 

Base: All Respondents 

Unweighted N= 6,016 

 

Yes, State Has Law  

N = 4,470

No, State Does Not Have Law  

N = 1,546
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

68 

Respondents who supported a ban on sending text messages or e-mails while driving, or who were unsure 

whether they supported such a ban, were asked what the average fine should be for sending text messages 

or e-mails while driving. Overall, younger respondents favored lower average fines than older 

respondents. Respondents 21 to 24 volunteered the lowest average fine at $206, and respondents 45 to 54 

volunteered the highest at $325. On average, respondents of all ages supported a fine of $279. 

Figure 6-15: Average Fine for Sending Text Messages or E-mails While Driving, by Age 

$230.00

$206.00

$248.00 $262.00

$325.00 $324.00

$274.00

$0

$50

$100

$150

$200

$250

$300

$350

$400

16‐20

N=325

21‐24

N=307

25‐34

N=940

35‐44

N=676

45‐54

N=926

55‐64

N=907

65+

N=899

Q17c. What do you think the fine should be for sending text messages or e-mails while driving?

Base: Respondents Who Support a Ban on Talking on a Hand-Held Cell Phone While Driving, or Don’t Know

Unweighted N= 5,663 

 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

69 

When compared by driver type, distraction-averse drivers who supported bans on sending electronic 

messages while driving volunteered higher average fines than distraction-prone drivers ($306 versus

$220). 

Figure 6-16: Average Fine for Sending Text Messages While Driving 

by Driver Type 

$306.00

$220.00

$0

$50

$100

$150

$200

$250

$300

$350

$400

Distraction-Averse Driver (N=3,187) Distraction-Prone Driver (N=1,828)

Q17c. What do you think the fine should be for sending text messages or e-mails while driving? 

Base: Respondents Who Support a Ban on Talking on a Hand-Held Cell Phone While Driving, or Don’t Know and Were 

Assigned a Driver Type

Unweighted N= See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

70 

CHAPTER 7 

PROGRAM AWARENESS

Respondents were asked whether they had seen or heard of any special effort by police to ticket drivers in 

their community for using hand-held cell phones while driving. The majority of respondents (86%) were 

not aware of any special programs or efforts to ticket drivers using hand-held cell phones while driving. 

Slightly more than 1 in 10 respondents (12%) reported that they were aware of a special effort to ticket 

drivers using cell phones while driving and an additional 2% were unsure. 

Figure 7-1: Heard of Special Effort to Ticket Drivers Using Hand-Held Cell Phone While 

Driving

Yes

11.8%

No

85.9%

Not Sure

2.3%

Q18. In the past 30 days, have you seen or heard of any special effort by police to ticket drivers in your community for using 

hand-held cell phones while driving?

Base: All Respondents

Unweighted N= 6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

71 

When we limit the responses to those of respondents who reside in States where there are laws banning 

the hand-held use of cell phones while driving, the prevalence of awareness of these programs increases. 

One in 5 respondents (20%) had seen or heard about a special effort by police to ticket those using hand 

held cell phones while driving. Most (77%) had not seen a special effort and 3% were not sure.

Figure 7-2: Heard of Special Effort to Ticket Drivers Using Hand-Held Cell Phone While 

Driving (Respondents Who Reside in States With Hand-Held Ban)

Yes

19.6%

No

77.1%

Not Sure

3.3%

Q18. In the past 30 days, have you seen or heard of any special effort by police to ticket drivers in your community for using 

hand-held cell phones while driving?

Base: Respondents Who Reside in States With Hand Held Ban

Unweighted N= 1,687
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

72 

Respondents were asked how they became aware of the special efforts in their community to ticket 

drivers using hand-held cell phones while driving. Table 7-1 shows that many respondents became aware 

of special enforcement through television news or advertisements, with 42% mentioning some type of 

television programming. The second most frequent source of information about special enforcement 

efforts was through print media, with 26% of respondents citing some type of print media, such as 

billboards or newspapers/magazines. About 1 in 6 respondents (17%) mentioned radio programming as 

their source. Other commonly mentioned sources included conversations with friends or relatives (12%) 

or witnessing enforcement activity (11%). One in 40 respondents (2.5%) mentioned learning about the 

special enforcement effort via the internet. 

Table 7-1: How Respondents Were Made Aware of Special Effort

Q18a. Where did you see or hear about that special effort?

[Multiple Record] Percent

TV 42.4%

TV - news 27.6%

TV - advertisement/public service announcement 14.5%

Print Media 26.0%

Billboard/signs 16.3%

Newspaper/magazine 9.5%

Radio 16.9%

Radio - advertisement/public service announcement 8.5%

Radio - news 8.3%

Internet 2.5%

Social networking website (Facebook, MySpace, Twitter) 1.3%

Online news/blog 0.7%

Internet ad/banner 0.2%

Online video (YouTube, Google Video) 0.2%

Other 33.3%

Friend/relative 11.8%

Witnessed enforcement activity 11.3%

Direct contact by police officer 2.7%

Educational program 1.7%

School zones/around/from school 1.3%

I'm a police officer/judge 1.2%

Other (SPECIFY) 4.4%

Not Sure 2.2%

Base: Respondents aware of special effort to ticket distracted drivers

Unweighted N =651
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

73 

CHAPTER 8

EDUCATIONAL MESSAGES

This chapter examines respondents’ exposure to educational messages about distracted driving that 

encourage people not to talk on cell phones or text while driving. Respondents were asked if they had 

seen or heard such messages in the past 30 days, and the circumstances under which they saw or heard 

these messages. 

Respondents were first asked if they had seen or heard a message within the last 30 days that encouraged 

people not to talk on phones or send electronic messages while driving. Almost two thirds of respondents 

(63%) stated that they had been exposed to such a message within the past 30 days. 

FIGURE 8-1: Percentage of Respondents who Heard a Message Discouraging Distracted 

Driving in Past 30 Days 

Yes

63.1%

No

35.7%

Not Sure

1.2%

Q19. In the past 30 days, have you seen or heard any messages that encourage people not to talk on phones or send 

electronic messages while driving? This could be public service announcements on TV, messages on the radio, signs 

on the road, news stories, or something else. 

Base: All respondents

Unweighted N = 6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

74 

Of those respondents who reported seeing or hearing a message that encourages people not to talk on 

phones or send electronic messages while driving, 71% reported that they drive every day. Another 13% 

stated that they drive almost every day or at least a few days a week. Finally, 3% drive a few days a 

month and 1% reported driving only a few days a year. 

FIGURE 8-2: Frequency of Driving of Respondents Exposed to Messages Discouraging 

Cell Phone Related Distracted Driving 

71.1%

12.7% 12.5%

2.9% 0.8%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Every day Almost every

day

Few days a

week

Few days a

month

Few days a year

Q19. In the past 30 days, have you seen or heard any messages that encourage people not to talk on phones or send 

electronic messages while driving? This could be public service announcements on TV, messages on the radio, signs 

on the road, news stories, or something else. 

Base: Reported hearing or seeing a message discouraging cell phone-related distracted driving in past 30 days

Unweighted N = 3,846
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

75 

Distraction-averse drivers were more likely to report seeing or hearing messages that discourage 

distracted driving than distraction-prone drivers (Figure 8-3). Among drivers who reported seeing or 

hearing any messages that encourage people not to talk on phones or send electronic messages while 

driving, 65% were people classified as distraction-averse and 35% were classified as distraction-prone 

drivers. 

FIGURE 8-3: Respondents Exposed to Messages Discouraging Cell Phone Distracted 

Driving, by Driver Type

100%

90%

80%

70% 65.3%

60%

50%

40% 34.7%

30%

20%

10%

0%

Distraction-Averse (N=2,215) Distraction-Prone (N=3,742)

Q19. In the past 30 days, have you seen or heard any messages that encourage people not to talk on phones or send 

electronic messages while driving? This could be public service announcements on TV, messages on the radio, signs 

on the road, news stories, or something else. 

Base: All Respondents Assigned a Driver Type

Unweighted N = 6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

76 

Respondents who reported that they heard or saw messages that encourage drivers not to talk on cell 

phones or send electronic messages while driving in the past 30 days were asked where they heard or saw 

the message. More than one source could be given. Almost half (47%) of these respondents had seen such 

a message on a TV advertisement or public service announcement. More than one-quarter (27%) had seen 

such a message on a billboard or sign, and another 25% had seen a news segment featuring such a 

message. More than 1 in 5 respondents (22%) had heard the message on a radio public service 

announcement, while 8% heard a radio news segment featuring the message. A small number of 

respondents saw or heard the message in a newspaper or magazine (5.0%), in an internet ad or banner 

(2.7%), on the road (1.5%), from a friend or relative (1.4%), or at an educational program (1.2%). 

Table 8-1: Source of Messages Discouraging Cell Phone-Related

Distracted Driving

Q19a. Where did you see or hear these messages? 

[Multiple Record] Percent

TV - advertisement/public service announcement 47.0%

Billboard/signs 26.9%

TV - news 25.3%

Radio - advertisement/public service announcement 21.6%

Radio - news 7.7%

Newspaper/magazine 5.0%

Internet ad/banner 2.7%

Personal observation/on the road 1.5%

Friend/relative 1.4%

Educational program 1.2%

Social networking website (Facebook, MySpace, Twitter) 1.0%

Online news/blog 0.7%

Online video (YouTube, Google Video) 0.5%

Internet game 0.1%

I'm a police officer/judge 0.1%

Other (SPECIFY) 3.7%

Not Sure 1. 0%

Base: Respondents who heard messages encouraging drivers not to 

talk on phone or send messages while driving 

Unweighted N= 3,846 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

77 

Figure 8-4 shows the reported distribution of media sources that delivered messages to those respondents 

who recalled having heard or seen the message in the past 30 days. The most frequent sources of the 

messages discouraging cell phone-related distracted driving were television programming, print media, 

and radio programming. More than three-quarters of respondents (77%) listed some form of television 

programming as their source of the message. Almost a third (32%) reported some type of print media like 

billboards or newspapers, while 29% reported hearing the message on the radio. Exposure to the message 

via the internet was reported by 5% of respondents, while 8% mentioned sources such as conversations 

with friends or an educational program. 

FIGURE 8-4: Source of Messages Discouraging Cell Phone-Related Distracted Driving 

100%

90%

80% 77.1%

70%

60%

50%

40%

31.9% 29.4% 30%

20%

10% 8.0%

4.9%

0%

TV Print Media Radio Internet Other

Q19a. Where did you see or hear these messages? [Multiple Record] 

Base: Respondent saw a message discouraging distracted driving in past 30 days

Unweighted N = 3,846
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

78 

The source by which respondents were exposed to messages discouraging cell phone distracted driving in 

the past 30 days was examined further by age (Figure 8-5). The most common sources of the message 

across all respondents were TV, print media, and radio. Only a few respondents mentioned the internet. 

However, there are some correlations between respondent age and message source. Across most age 

groups, it was increasingly likely that older respondents would mention the TV as a source of exposure to 

such messages, ranging from 59% of respondents 25 to 34 mentioning TV to 93% of respondents 65 and 

older. While differences by age were less systematic when examining the percentage of respondents who 

mentioned print media or radio, respondents 25 to 34 were the most likely to mention print media (which 

includes newspapers, magazines and billboards), with 41% of respondents mentioning print media as

their source of message. The 35 to 44 age group was the most likely to mention radio, with 36% stating 

that they heard the message on the radio. Younger respondents were more likely than older respondents to 

list the internet as their source. Around 1 in 10 of the younger respondents 16 to 24 (8%), 25 to 34 (10%), 

and 35 to 44 (8%) mentioned the internet, while only 2% or fewer of respondents 45 and older mentioned

the internet. 

FIGURE 8-5: Source of Messages Discouraging Cell Phone-Related Distracted Driving, by

Age 

74.4%

37.1%

25.6%

8.2%

58.8%

40.8%

35.4%

10.1%

69.4%

33.1%

36.3%

8.2%

77.1%

32.6%

29.8%

1.4%

89.2%

25.0%

27.9%

1.5%

93.4%

24.2% 22.1%

1.3%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

TV Print Media Radio Internet

16-24 (N=306) 25-34 (N=702) 35-44 (N=518)

45-54 (N=691) 55-64 (N=698) 65+ (N=673)

Q19a. Where did you see or hear these messages? [Multiple Record] 

Base: Respondent Who Saw a Message Discouraging Distracted Driving in Past 30 Days

Unweighted N = See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

79 

Figure 8.6 shows the sources of messages discouraging cell phone distracted driving as reported 

by distraction-prone and distraction-averse drivers. Distraction-averse drivers were more likely 

than distraction-prone drivers to list television programming, with 82% of distraction-averse 

drivers compared to 68% of distraction-prone drivers listing television programming as a source 

of the message. On the other hand, distraction-prone drivers are slightly more likely than 

distraction-averse drivers to mention print media, which includes newspapers and billboards, 

with 36% of distraction-prone drivers mentioning print media as compared to 30% distractionaverse drivers (30%). Approximately 3 in 10 distraction-prone drivers (31%) as well as

distraction-averse drivers (29%) mentioned the radio as a source of the message they heard. Less 

than 1 in 10 distraction-prone drivers (8%) mentioned the internet as a source as do 3.5% of 

distraction-averse drivers. Most respondents, regardless of driver type, mentioned television 

programming as a source of messages that discourage distracted driving. 

FIGURE 8-6: Source of Messaging, by Driver Type

82.0%

30.0% 28.5%

3.5%

68.2%

35.6%

31.3%

7.6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

TV Print Media Radio Internet

Distraction-Averse Driver (N=2,392) Distraction-Prone Driver (N=1,419)

Q19a. Where did you see or hear these messages? [Multiple Record] 

Base: Saw Messages and Assigned a Driver Type

Unweighted N=See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

80 

Respondents were read educational slogans concerned with safe driving and asked if they had 

heard each message in the past 30 days. Figure 8.7 shows the percentage of respondents who 

reported having heard 7 slogans in the past 30 days that are applicable to cell phone-related

distracted driving. Twenty-two percent had heard “No Phone Zone” or “One Text or Call Could 

Wreck It All” in the past 30 days. Approximately 1 in 5 respondents reported having heard “Just 

Drive,” (21%) and “u txt i tikit” (19%) in the past 30 days, while 18% of respondents had heard 

“On the Road. Off the Phone.” One in 10 had heard “Phone in One Hand. Ticket in the Other” 

(10%) and 9% had heard “Put It Down.” 

FIGURE 8-7: Heard Slogans in Past 30 Days 

9.1%

9.9%

18.2%

18.7%

21.4%

21.6%

21.8%

0% 20% 40% 60% 80%

Put It Down

Phone In One Hand, Ticket In The Other

On The Road, Off The Phone

u txt I tikit

Just Drive

One Text Or Call Could Wreck It All

No Phone Zone

Q20. Do you recall hearing or seeing the following slogans in the past 30 days? 

Base: All Respondents

Unweighted N=6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

81 

In addition to slogans pertaining to cell phone-related distracted driving, respondents were asked 

if they had heard or seen other safe driving slogans. Figure 8.8 shows the total number of 

different safe driving slogans that respondents reported having heard in the past 30 days. Almost 

1 in 3 (29%) reported hearing between 6 and 10 slogans, 25% of respondents reported hearing 4 

or 5, 13% recognized three slogans, 11% recognized two, and 8% reported hearing one. The 

same percentage (7%) reported hearing more than 11 of the slogans, or none in the last 30 days. 

FIGURE 8-8: Number of Slogans Heard in Past 30 Days 

50%

40%

30% 29.0%

24.6%

20%

13.4%

10.9%

10% 8.2% 7.3% 6.7%

0%

None One Two Three 4 to 5 6 to 10 11 to 16

Q20. Do you recall hearing or seeing the following slogans in the past 30 days? 

Base: All Respondents

Unweighted N=6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

82 

Figure 8.9 shows the number of slogans that respondents reported hearing in the last 30 days by 

gender. Women reported hearing fewer slogans in the past 30 days than did the men. Two-thirds 

of men (66%) recognized 4 or more slogans, compared to 57% of women. Women were also 

more likely than men to mention that they heard no slogans (9% versus 6%) and only one slogan 

(10 versus 7%). However, the number of slogans that respondents reported hearing did not vary 

much by respondent gender. 

FIGURE 8-9: Number of Slogans Heard in Past 30 Days, by Gender

5.9% 6.6%

10.7%

12.7%

25.6%

30.1%

9.5% 8.6% 9.7%

11.1%

14.1%

23.6%

27.8%

5.0%

0%

10%

20%

30%

40%

50%

None One Two Three 4 to 5 6 to 10 11 to 16

Male (N=2,889) Female (N=3,127)

Q20. Do you recall hearing or seeing the following slogans in the past 30 days? 

Base: All Respondents

Unweighted N=6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

83 

CHAPTER 9

DISTRACTED DRIVING CRASHES AND NEAR-CRASHES

Figure 9-1 shows the proportions of drivers by their involvement in vehicle crashes and near-crashes 

while driving a vehicle in the past year. Most drivers (86%) reported that they were not involved in any 

crash or near-crash events in the past year. However, 6% of drivers reported a crash involvement and 7% 

reported involvement in a near-crash. 

FIGURE 9-1: Had a Crash or Near-Crash in Past Year 

Crash, 6.4%

Near Crash, 

7.0%

No, 86.4%

Q21. Have you been involved in a crash or near-crash as a driver in the past year? 

Base: All Respondents

Unweighted N=6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

84 

Of the respondents who were in at least one crash or near-crash in the past year, the overwhelming 

majority (96%) reported that they were not using a cell phone at the time of the incident. However, 4.2% 

were using their cell phone at the time of the crash or near-crash; 1.6% of these respondents reported that 

they were talking on a cell phone, 1.6% reported that they were sending a text message, and 1.0% 

reported that they were reading a text message. 

FIGURE 9-2: Using Cell Phone at Time of Most Recent Crash or Near-Crash

Talking, 1.6% Reading Text, 

1.0%

Sending Text, 

1.6%

No, 95.8%

Q21a. Were you using a cell phone at the time of the LAST (crash/near-crash) you were in? 

Base: Drivers who were in a crash or near-crash in the past year

Unweighted N=790
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

85 

Figure 9-3 shows the frequency with which respondents reported having a crash or near-crash in the past 

year, according to the respondent gender. Overall, more men than women report being involved in a crash 

in the past year, with 8% of men and 5% of women reporting having had a crash in the past year. The 

proportion of male and female drivers reporting at least one near-crash in the past year is the same, with

7% of each group reporting being in a near-crash. 

FIGURE 9-3: Had Crash or Near-Crash in Past Year, by Gender

100%

87.9% 84.9%

80%

60%

40%

20%

7.9% 5.0% 7.1% 6.9%

0%

Crash Near Crash No

Male (N=2,889) Female (N=3,127)

Q21. Have you been involved in a crash or near-crash as a driver in the past year? 

Base: All Respondents

Unweighted N=See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

86 

Figure 9-4 shows the proportion of each age group that reported having a crash, a near-crash or neither in 

the past 12 months. Overall, younger respondents are more likely to report a crash or near-crash event in 

the past 12 months than older respondents. Among respondents 16 to 20, 11% report being in a crash in 

the past year, as did 8% of respondents 21 to 24 and 25 to 34, 6% of respondents 35 to 44, 45 to 54 and 

55 to 64, and 4% of respondents 65 and older. 

Younger drivers also reported more near-crash involvement in the past 12 months, with approximately 1 

in 10 respondents 16 to 20 (13%), 21 to 24 (10%), and 25 to 34 (8%) stating they were in a near-crash. 

Close to 1 in 20 respondents 35 to 44 (6%), 45 to 54 (6%), 55 to 64 (5%), and 65 and older (5%) reported

being in a near-crash. 

FIGURE 9-4: Had Crash or Near-Crash in Past Year, by Age

10.7% 12.9%

76.4%

7.8% 9.8%

81.9%

7.7% 8.4%

83.8%

5.5% 6.0%

88.2%

6.2% 5.9%

87.8%

6.0% 5.4%

88.6%

4.1% 5.3%

90.4%

0%

20%

40%

60%

80%

100%

Crash Near Crash No

16-20 (N=392) 21-24 (N=383) 25-34 (N=1,134) 35-44 (N=794)

45-54 (N=1,066) 55-64 (N=1,062) 65+ (N=1,072)

Q21. Have you been involved in a crash or near-crash as a driver in the past year? 

Base: All Respondents

Unweighted N=See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

87 

Figure 9-5 shows the proportion of drivers of each driver type reporting a crash, near-crash, or neither in 

the past 12 months according to their driver type. Among distraction-prone drivers, 17% were involved in 

a crash (9%) or near-crash (8%). Among distraction-averse drivers, 12% were involved in crash (6%) or 

near-crash (6%) incidents.

FIGURE 9-5: Had Crash or Near-Crash in Past Year, by Driver Type

6.1% 5.7%

87.9%

8.7% 7.6%

83.7%

0%

20%

40%

60%

80%

100%

Crash Near crash No Crash

Distraction-Averse Driver (N=3,742) Distraction-Prone Driver (N=2,215)

Q21. Have you been involved in a crash or near-crash as a driver in the past year? 

Base: All drivers assigned a driver type

Unweighted N=See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

88 

CHAPTER 10

PERCEPTIONS OF AND RESPONSES TO DISTRACTED DRIVING

Respondents were asked what percentage of drivers they believe talk on a cell phone at least occasionally 

while driving. Fully 70% of respondents believe that more than half of drivers talk on cell phones at least 

occasionally, with 30% of respondents believing that more than 80% of drivers do so. 

See Figure 3-2, which indicates that 40% of respondents stated that they never answer their cell phones 

while driving and 60% stated that they answer their cell phones while driving at least occasionally (11% 

rarely, 21% sometimes, 17% almost always and 11% always). 

FIGURE 10-1: Perception of Proportion of Drivers Talking on Phone While Driving

2.7% 2.6%

5.0% 3.8%

12.9%

6.2%

8.6%

24.7%

17.4%

13.1%

0%

10%

20%

30%

40%

50%

0-10% 11-20% 21-30% 31-40% 41-50% 51-60% 61-70% 71-80% 81-90% 91-100%

Q22. What percentage of drivers do you believe at least occasionally TALK on a cell phone while driving? 

Base: All Respondents

Unweighted N=6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

89 

Respondents were asked what percentage of drivers they believe send text messages or e-mails on a cell 

phone at least occasionally while driving. More than two in 5 respondents (43%) think that more than half 

of drivers send electronic messages while driving. 

See Figure 3-6 which indicates that, overall, the percentage of drivers who admit to sending text messages 

while driving is 14%.

FIGURE 10-2: Perception of Proportion Sending Texts or E-Mails While Driving

4.9% 6.0%

9.6%

8.0%

21.6%

8.0% 6.9%

15.4%

8.3%

4.8%

0%

10%

20%

30%

40%

50%

0-10% 11-20% 21-30% 31-40% 41-50% 51-60% 61-70% 71-80% 81-90% 91-100%

Q22a. What percentage of drivers do you believe at least occasionally SEND TEXT MESSAGES OR E-MAILS on 

a cell phone while driving? 

Base: All Respondents

Unweighted N=6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

90 

Respondents were asked about their comfort level when riding in a car as a passenger with a driver who is 

talking on a cell phone. Approximately one-third of respondents indicated that they would be 

comfortable, with 11% stating they would be very comfortable and 23% stating they would be aware but 

not uncomfortable. Two-thirds of respondents indicated some level of discomfort in this situation, with 

26% stating that they would be somewhat uncomfortable, 14% indicating uncomfortable, and 25% stating 

that they would be very uncomfortable riding with a driver talking on the phone. 

FIGURE 10-3: Comfortable Riding With a Driver Talking on the Phone

11.0%

23.1%

26.3%

13.8%

24.5%

1.3%

0%

10%

20%

30%

40%

50%

Very

Comfortable

Aware, but not

Uncomfortable

Somewhat

Uncomfortable

Uncomfortable Very

Uncomfortable

Not sure

Q23. When riding as a passenger, how comfortable would you feel if your driver was TALKING on a cell phone 

while driving? [Read List]

Base: All Respondents

Unweighted N=6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

91 

Respondents were also asked how comfortable they would be riding in a car as a passenger with a driver 

sending text messages or e-mails. Most respondents (93%) indicated some level of discomfort, with 70% 

stating that they would be very uncomfortable, 12% stating that they would be uncomfortable, and 11% 

saying that they would be somewhat uncomfortable as a passenger in a car with the driver sending 

electronic messages. Only 8% of respondents indicated that they would be comfortable, including 4% 

who stated they would be very comfortable and 4% who stated they would be aware, but not 

uncomfortable in this situation. 

Respondents reported discomfort more often at the prospect of being a passenger when the driver was 

sending text messages than they did at the prospect of being a passenger when the driver was talking on a 

cell phone. 

FIGURE 10-4: Comfortable Riding With Driver Sending Texts or E-mails While Driving

3.6% 3.5%

10.6% 12.0%

69.6%

0.8%

0%

20%

40%

60%

80%

100%

Very

Comfortable

Aware, but not

Uncomfortable

Somewhat

Uncomfortable

Uncomfortable Very

Uncomfortable

Not sure

Q23a. When riding as a passenger, how comfortable would you feel if your driver was SENDING TEXT 

MESSAGES OR E-MAILS while driving? [Read List]

Base: All Respondents

Unweighted N=6,016
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

92 

Figure 10-5 shows respondents’ level of comfort riding in a car with a driver talking on a cell phone by 

respondent gender. Overall, men are more likely than women to state that they are very comfortable (13% 

versus 9%), while women are more likely than men to report being somewhat uncomfortable (27% versus

25%) or very uncomfortable (26% versus 23%). Two-thirds of women (66%) are at least somewhat 

uncomfortable with a driver talking on cell phones while the respondent is a passenger in the car, 

compared with 62% of men. While the majority of all respondents report discomfort with drivers talking 

on cell phones, men are somewhat more likely to report feeling comfortable than women. 

FIGURE 10-5: Comfortable Riding With a Driver Talking on the 

Phone, by Gender

12.7%

23.1%

25.0%

14.3%

23.0%

1.9%

9.4%

23.1%

27.4%

13.3%

26.0%

0.7%

0%

10%

20%

30%

40%

50%

Very

Comfortable

Aware, but not

Uncomfortable

Somewhat

Uncomfortable

Uncomfortable Very

Uncomfortable

Not sure

Male (N=2,889) Female (N=3,127)

Q23. When riding as a passenger, how comfortable would you feel if your driver was TALKING on a cell phone 

while driving? [Read List]

Base: All Respondents

Unweighted N=See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

93 

Figure 10-6 shows respondents’ level of comfort riding with a driver who is talking on a cell phone, 

according to the respondents’ driver type. Overall, respondents who were classified as distraction-prone 

drivers were more likely to be comfortable with drivers talking on cell phones, while respondents 

classified as distraction-averse drivers were more likely to report discomfort. While only 6% of 

distraction-averse drivers stated that they would be very comfortable with the driver using a cell phone, 

20% of distraction-prone drivers reported that they would be very comfortable. The largest difference 

between the comfort levels of distraction-prone and distraction-averse drivers was evident among those 

respondents who reported being very uncomfortable with a driver talking on a cell phone while driving, 

with 8% of distraction-prone drivers and 33% of distraction-averse drivers stating that this situation 

would make them very uncomfortable. Overall, distraction-averse drivers indicated more discomfort 

about being a passenger in a car in which the driver was using a cell phone, with 76% stating that they 

would be at least somewhat uncomfortable, while only 43% of distraction-prone drivers stated that they 

would be at least somewhat uncomfortable.

FIGURE 10-6: Comfortable Riding With a Driver Talking on the 

Phone, by Driver Type

6.1%

16.3%

26.0%

17.0%

33.4%

1.2%

19.8%

35.7%

27.0%

7.8% 8.4%

1.2%

0%

10%

20%

30%

40%

50%

Very

Comfortable

Aware, but not

Uncomfortable

Somewhat

Uncomfortable

Uncomfortable Very

Uncomfortable

Not sure

Distraction-Averse Driver (N=3,742) Distraction-Prone Driver (N=2,215)

Q23. When riding as a passenger, how comfortable would you feel if your driver was TALKING on a cell phone 

while driving? [Read List]

Base: All Respondents assigned a driver type

Unweighted N=See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

94 

Figure 10-7 shows respondents’ comfort level as a passenger in a car with a driver sending text messages 

or e-mails according to the respondents’ gender. The vast majority of both genders reported some level of 

discomfort with drivers sending electronic messages while driving, but women were more likely to report 

extreme discomfort than men. Overall, 91% of men and 93% of women reported feeling at least 

somewhat uncomfortable. While 66% of men reported feeling very uncomfortable with the driver sending 

electronic messages while driving, 73% of women reported feeling very uncomfortable. 

FIGURE 10-7: Comfortable Riding With a Driver 

Sending Texts or E-mails, by Gender

4.1% 4.0%

12.2% 13.1%

65.6%

1.0% 3.0% 3.0%

9.1% 10.9%

73.3%

0.7%

0%

20%

40%

60%

80%

100%

Very

Comfortable

Aware, but not

Uncomfortable

Somewhat

Uncomfortable

Uncomfortable Very

Uncomfortable

Not sure

Male (N=2,889) Female (N=3,127)

Q23a. When riding as a passenger, how comfortable would you feel if your driver was SENDING TEXT 

MESSAGES OR E-MAILS while driving? [Read List]

Base: All Respondents

Unweighted N=See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

95 

Figure 10-8 shows respondents’ comfort level riding with a driver who is sending electronic messages by 

driver type. Respondents who were classified as distraction-averse drivers were more likely than

distraction-prone drivers to indicate extreme discomfort at the prospect of their driver sending text 

messages or e-mails while driving. While only half of distraction-prone drivers (50%) stated that they 

would be very uncomfortable, 80% of distraction-averse drivers stated that they would be very 

uncomfortable. The overwhelming majority of both distraction-averse (96%) and distraction-prone (86%) 

drivers indicated that they would be at least somewhat uncomfortable in this situation. 

FIGURE 10-8: Comfortable Riding With a Driver 

Sending Texts or E-mails, by Driver Type

2.4% 1.2%

5.3%

10.3%

80.2%

0.7%

5.8% 7.7%

20.4%

15.2%

50.2%

0.7%

0%

20%

40%

60%

80%

100%

Very

Comfortable

Aware, but not

Uncomfortable

Somewhat

Uncomfortable

Uncomfortable Very

Uncomfortable

Not sure

Distraction-Averse Driver (N=3,742) Distraction-Prone Driver (N=2,215)

Q23a. When riding as a passenger, how comfortable would you feel if your driver was SENDING TEXT 

MESSAGES OR E-MAILS while driving? [Read List]

Base: All Respondents assigned a Driver Type

Unweighted N=See Chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

96 

CHAPTER 11

TREND ANALYSIS

As noted earlier, this document presents the results of the second NHTSA National Survey on Distracted 

Driving Attitudes and Behaviors. The first such study was conducted in 2010. Comparing responses to 

questions that appeared in both 2010 and 2012 provides insight into how distracted driving behaviors and 

attitudes have changed in the past 2 years. 

Both surveys asked respondents how often they engage in a set of specific activities while driving. 

Overall, respondents reported always or almost always engaging in these activities at similar rates from 

2010 to 2012. In 2010 and 2012, approximately half of respondents (52% in 2010 and 49% in 2012) 

stated that they talked to other passengers in the vehicle while driving. In 2010, 14% of respondents 

reported eating or drinking while driving, while in 2012 this percentage was 11%. In 2010, 15% of 

respondents reported making or accepting phone calls, and in 2012, 12% of respondents reported doing 

so. The largest difference between reported behaviors in 2010 and 2012 is for adjusting car radios, with 

34% of respondents doing so in 2010 and 27% of respondents doing so in 2012. The next largest 

difference is using a portable music player with external speakers. In 2010, 15% of respondents report 

that they used this system, while 10% of respondents did so in 2012. Respondents in 2010 were slightly 

more likely than respondents in 2012 to use a navigation system while driving, with 10% of respondents 

stating that they did so in 2010 and 8% reported using this type of system while driving in 2012. The rate 

of participation in behaviors such as personal grooming, using a music player with headphones, or using 

their phone for directions while driving changed very little between 2010 and 2012. 

Table 11-1. Engaging in Distracted Driving Activities (Always or Almost Always)

2010

(N=5,907)

2012

(N=6,016)

a. Talk to other passengers in the vehicle 52% 49%

b. Eat or drink 14% 11%

c. Make or accept phone calls 15% 12%

d. Read, such as a book, newspaper, iPad, or Kindle 0% 1%

e. Read e-mails or text messages 3% 3%

f. Send text messages or e-mails 2% 2%

h. Do personal grooming 2% 2%

i. Adjust the car radio 34% 27%

j. Change CDs, DVDs, or tapes 6% 5%

k. Use a portable music player with headphones on 1% 2%

l. Use a portable music player with external speakers 15% 10%

m. Use a smartphone for driving directions 5% 5%

n. Use a navigation system for driving directions 10% 8%

2010 – Q5. I’m going to read a list of activities, and for each I’d like you to tell me how often YOU do each while 

driving? For each, please tell me if you do the activity on all driving trips, on most driving trips, on some driving 

trips, rarely, never? How often do you...

2012 – Q4. I’m going to read a list of activities, and for each I’d like you to tell me how often YOU do each while 

driving? For each, please tell me if you do the activity always, almost always, sometimes, rarely, or never? How 

often do you...

2010 Base: Respondents who drive at least a few times a year

2012 Base: All Respondents
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

97 

Both surveys asked about respondents’ willingness to answer or initiate cell phone calls while driving. 

Figure 11-1 shows how often respondents in 2010 and 2012 reported always or almost always answering 

a call while driving, as well as making a call while driving. The percentage of drivers who are always or 

almost always willing to answer a call on their cell phone while driving decreased from 2010 to 2012 with 

33% of drivers in 2010 and 28% of drivers in 2012 stating that they are willing to do so. There was also a 

slight decrease in the percentage of drivers willing to initiate a call between 2010 and 2012. In 2010, 10% 

of respondents were always or almost always willing to make a call while driving. In 2012, this 

percentage decreased to 6%. 

FIGURE 11-1: Answering a Call While Driving and Making a Call While Driving – 

Always and Almost Always 

32.9%

9.6%

28.1%

5.7%

0%

10%

20%

30%

40%

50%

Answer a call while driving Make a call while driving

2010 (N=5,907) 2012 (N=6,016)

2010 – Q8a. When you RECEIVE a phone call while you are driving, how often do you ANSWER the call?

2012 – Q5a. When you RECEIVE a phone call while you are driving, how often do you ANSWER the call?

2010 – Q9a. When you are driving, how often are you willing to MAKE a phone call?

2012 – Q6a. When you are driving, how often are you willing to MAKE a phone call?

2010 Base: All Respondents

2012 Base: All Respondents

Unweighted N=See chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

98 

There was a small increase in the proportion of drivers sending text messages when driving between the 

two years compared in this report. When asked if they ever send text messages or e-mails while driving, 

12% of respondents in 2010, and 14% of respondents in 2012 state that they do so. 

FIGURE 11-2: Do You Send Text Messages or E-mails While Driving – % Yes

12.0%

14.3%

0%

10%

20%

30%

40%

50%

2010 (N=5,907) 2012 (N=6,016)

2010 – Q12. Do you ever SEND text messages or e-mails when you are driving?

2012 – Q9. Do you ever SEND text messages or e-mails when you are driving?

2010 Base: All Respondents

2012 Base: All Respondents

Unweighted N=See chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

99 

Figure 11-3 shows the response distribution in both surveys to a question that asked about changes in 

frequency of initiating or taking cell phone calls while driving in the past 30 days. In both 2010 and 2012, 

most respondents reported that the rate at which they use a cell phone had stayed the same (68% in 2010 

and 77% in 2012). In 2012, 19% of respondents stated that the rate at which they made and received calls 

decreased in the past 30 days, while in 2010, 12% reported a decrease in their rate of making and 

receiving cell phone calls. The percentage of respondents who reported never using phones while driving 

was 18% in 2010. This percentage dropped sharply to only 1% of respondents in 2012. 

FIGURE 11-3: Has Your Frequency of Making and Receiving Phone Calls While Driving 

Increased, Decreased, or Stayed the Same

2.3%

11.7%

67.5%

18.2%

2.5%

19.1%

76.8%

1.4%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Increased Decreased Stayed the same Never use a phone

while driving

2010 (N=5,907) 2012 (N=3,968)

2010 – Q19. In the past 30 days, has your frequency of making and receiving phone calls while driving increased, 

decreased, or stayed the same?

2012 – Q15. In the past 30 days, has your frequency of making and receiving phone calls while driving increased, 

decreased, or stayed the same?

2012 Base: Respondents who drive at least a few days a year

2012 Base: Respondents who make or accept phone calls while driving at least some of the time

Unweighted N=See chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

100 

In both 2010 and 2012, respondents who reported that the frequency with which they make and receive 

phone calls had decreased in the past 30 days were asked what caused the rate to decrease. The most 

common answer from respondents in both 2010 and 2012 was an increased awareness of safety (31% in 

2010 and 24% in 2012), followed by a law that bans cell phone usage (12% in 2010 and 6% in 2012), and 

not wanting to get a ticket (5% in 2010 and 2% in 2012). 

While only 1% of respondents in 2010 reported that pressure from others led them to make and receive 

fewer calls, 3% of respondents in 2012 mentioned the influence of others as a reason for making and 

receiving fewer calls. 

FIGURE 11-4: Reasons for Decrease in Making and Receiving Phone Calls While Driving

31.2%

11.7%

4.5%

0.4% 1.2%

24.3%

6.0%

2.4% 0.1% 3.0%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Increased

awareness of

safety

Law that bans cell

phone use

Don't want to get

a ticket

Was in a crash Influence/pressure

from others

2010 (N=608) 2012 (N=735)

2010 – Q19a. What caused your frequency of making and receiving phone calls while driving to decrease? [Multiple 

Record]

2012 – Q15a. What caused your frequency of making and receiving phone calls while driving to decrease? [Multiple 

Record]

Base: Respondents who report a decrease in the frequency with which they make or receive calls while driving in 

the last 30 days

Unweighted N=See chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

101 

In both 2010 and 2012, respondents who indicated that they had ever sent or received a text message or email while driving were asked if the frequency with which they send and receive text messages or e-mails 

in the past 30 days had changed. In both 2010 and 2012, most respondents reported that the rate at which 

they send electronic messages had stayed the same (64% in 2010 and 67% in 2012). In 2010, 31% of 

respondents reported a decrease in the rate at which they send electronic messages, while in 2012, 27% of 

respondents reported a decrease. The percentage of respondents who reported an increase was 4% in 2010 

and 5% in 2012. In both 2010 and 2012, less than 1% of respondents stated that they never use a phone 

while driving when asked this follow up question about sending or receiving electronic messages.

FIGURE 11-5: Has Your Frequency of Sending and Receiving Text Messages or E-mails 

While Driving Increased, Decreased, or Stayed the Same

100%

90%

80%

70% 67.4% 64.4%

60%

50%

40%

31.1%

30% 26.6%

20%

10% 3.9% 5.1%

0.6% 0.1%

0%

Increased Decreased Stayed the same Never used a phone

while driving

2010 (N=510) 2012 (N=838)

2010 – Q19b. In the past 30 days, has the frequency with which you send and receive text messages or e-mails while 

driving increased, decreased, or stayed the same?

2012 – Q15b. In the past 30 days, has the frequency with which you send and receive text messages or e-mails while 

driving increased, decreased, or stayed the same?

Base: Respondents who have ever sent or received a text message or e-mail while driving

Unweighted N=See chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

102 

In 2010 and 2012, respondents who reported sending or receiving fewer electronic messages while 

driving in the past 30 days were asked what caused this decrease. The most common answer from

respondents in both 2010 and 2012 was an increased awareness of safety (32% in 2010 and 38% in 2012), 

followed by a law that bans cell phone use (6% in 2010 and 8% in 2012). In 2012, there was an increase 

in the number of respondents who cited not wanting to get a ticket and pressure from others as reasons for 

their decrease in sending or receiving electronic messages while driving (1% for both in 2010 and 4% and 

7%, respectively, in 2012). 

FIGURE 11-6: Reasons for Decrease in Sending and Receiving Text Messages While 

Driving

100%

90%

80%

70%

60%

50%

40% 37.7%

32.2%

30%

20%

10% 6.4% 7.6% 6.7% 3.8% 1.1% 0.9% 0.8% 0.6%

0%

Increased Law that bans cell Don't want to get Was in a crash Influence/pressure

awareness of phone use a ticket from others

safety

2010 (N=153) 2012 (N=230)

2010 – Q19c. What caused the frequency with which you send and receive text messages or e-mails while driving to 

decrease? [Multiple Record]

2012 – Q15c. What caused the frequency with which you send and receive text messages or e-mails while driving to 

decrease? [Multiple Record]

Base: Respondents who report a decrease in the frequency with which they send or receive text messages or e-mails 

while driving in the last 30 days

Unweighted N=See chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

103 

Both surveys asked respondents if they support a law banning talking on a hand-held cell phone while 

driving. Support for such laws increased between 2010 and 2012 from 68% in 2010 to 74% in 2012. In 

both 2010 and 2012, an overwhelming majority of respondents supported laws banning texting or emailing while driving, with 93% of respondents in 2010 and 94% in 2012 supporting such laws. 

FIGURE 11-7: Do You Support a Law Banning Talking on a Hand-Held Cell Phone While 

Driving, or a Law Banning Texting or E-mailing While Driving? – % Yes

67.7%

93.0%

73.9%

93.5%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Support a law banning talking on hand-held

cell phone while driving

Support a law banning texting or emailing

while driving

2010 (N=6,002) 2012 (N=6,016)

2010 – Q21. Do you support a State law banning talking on a hand-held cell phone while driving?

2012 – Q17. Do you support a State law banning talking on a hand-held cell phone while driving?

2010 – Q21b. Do you support a State law banning texting or e-mailing while driving?

2012 – Q17b. Do you support a State law banning texting or e-mailing while driving?

Base: All respondents

Unweighted N=See chart
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

104 

FIGURE 11-8: Was Respondent Stopped by Police for Using a Hand-held Cell Phone 

While Driving in Past 30 Days, Percentage of Respondents Exposed to Messages 

Discouraged Distracted Driving – % Yes

100%

90%

80%

70%

63.1%

59.6%

60%

50%

40%

30%

20%

10%

0.2% 0.3%

0%

Stopped for using handheld cell phon

N=6,016

e Seen a message in past 30 days

N=6,002 N=6,016

by police for using a hand-held cell phone while driving in the past 30 

by police for using a hand-held cell phone while driving in the past 30 

ed 

ed 

2010 2012

2010 – Q22b. Were you personally stopp

days?

2012 – Q18b. Were you personally stopp

days?

2010 – Q23. Now, I would like to ask you a few questions about educational or other types of activities. In the past 

30 days, have you seen or heard any messages that encourage people not to talk on phones or send electronic 

messages while driving? This could be public service announcements on TV, messages on the radio, signs on the 

road, news stories, or something else.

2012 – Q19. Now, I would like to ask you a few questions about educational or other types of activities. In the past 

30 days, have you seen or heard any messages that encourage people not to talk on phones or send electronic 

messages while driving? This could be public service announcements on TV, messages on the radio, signs on the 

road, news stories, or something else.

Base: All respondents

Unweighted N=See chart

N=5,911

In both surveys, respondents were asked whether they had been stopped by police in the past 30 days for 

using a cell phone while driving and whether they had seen or heard an educational message that 

discourages cell phone-related distracted driving in the past month. Overall, there was little change over 

the two years in the percentage of respondents who reported being stopped for using a cell phone while 

driving, while the percentage of respondents who reported seeing or hearing a message that discourages

cell phone-related distracted driving increased over time.

In both 2010 and 2012, less than 1% of respondents reported being stopped by police in the past 30 days 

for using a hand-held cell phone while driving. In 2010, 60% of respondents reported that in the past 30 

days they had seen a message that discourages drivers from talking on phones or sending electronic 

messages while driving, while in 2012, 63% of respondents reported seeing such messages. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

105 

CONCLUSION

The 2012 National Survey on Distracted Driving Attitudes and Behaviors is the second in a series of 

national studies conducted by NHTSA to assess the attitudes and behaviors toward distracted driving in 

the United States and to increase the understanding of this behavior to inform the development of 

effective countermeasures and interventions. Telephone interviews were conducted with more than 6,000 

drivers across the United States, and the responses were weighted to represent the driving population of 

the United States

This survey differed from the first NSDDAB conducted in 2010 in that a driver typology classifying 

drivers by their behavioral tendencies toward distracted driving was used to examine some of the 

behaviors and attitudes. Cluster analysis of 10 questions concerned with distracted driving behavior 

classified 99% of the respondents into two distinct groups, labeled distraction-prone and distractionaverse. Of those respondents classified, 33% were classified as distraction-prone drivers and 67% were 

classified as distraction-averse drivers. In terms of demographics, the distraction-prone drivers tend to be 

younger, more affluent, with more formal education than distraction-averse drivers. There was no 

relationship with gender, and men and women were about equally likely to be classified as distractionprone or distraction-averse. 

Overall, 91% of respondents own cell phones, with 99% of distraction-prone drivers and 86% of 

distraction-averse respondents reporting owning a cell phone. Cell phone use while driving is widespread. 

Nearly half of drivers answer their cell phone at least some of the time when driving, and 58% of these 

drivers continue to drive as they engage in the phone conversation. Almost a quarter of drivers (24%) are

at least sometimes willing to make a phone call while driving. Of these drivers, many have to take their 

eyes off the road at least momentarily to initiate the call because 43% of them often manually enter the 

phone number and 42% often scroll through entered numbers to make a selection. 

A large portion of drivers does not believe that their driving performance is affected by cell phone use. 

Half (50%) of drivers who talk on cell phones while driving believe that there is no difference in their 

driving while on or off the cell phone. On the other hand, 38% of drivers do notice deterioration in their 

driving performance. Eighteen percent state that they tend to drive more slowly when on cell phones, 17% 

say that they are more distracted and not as aware, and 3% say that they drift out of their lane or drive 

erratically. Interestingly, 5% of drivers believe that they are more focused and pay more attention to 

driving when they are on the phone. 

 

Respondents’ perceptions of the safety of cell phone-distracted driving are different when they are not 

drivers, but rather passengers in a car driven by someone who is talking on a cell phone. Overall, 66% of 

respondents would feel very or somewhat unsafe if their driver was talking on a hand-held cell phone 

while driving. Two-thirds (66%) of respondents stated that they would be very or somewhat likely to do 

or say something to the driver if he/she was talking on a cell phone. 

Distraction-averse people were much more likely to feel very unsafe as passengers in a car driven by 

someone who was talking on a cell phone than the distraction-prone people, with 55% of the distractionaverse stating that would feel very unsafe in this situation, compared to 17% of distraction-prone people. 

Conversely, 21% of distraction-prone people and only 5% of distraction-averse people said they would 

feel safe if their driver was talking on a hand-held phone while driving. Distraction-averse respondents 

were also more likely to intervene than respondents classified as distraction-prone. Among distractionaverse respondents, 72% stated they would intervene compared to 57% of distraction–prone respondents. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

106 

Sending text messages or e-mails is not as widespread among drivers as talking on the cell phone while 

driving. Almost 80% of respondents stated that they never send text messages or e-mails while driving, 

while 10% reported that they send text messages at least sometimes and 11% reported that they rarely do. 

Of drivers who send electronic messages, 44% stated that they wait until they reach a stop light to send 

the text message and 35% continue to drive. One-third of drivers who send text messages or e-mails while 

driving believe that there is no difference in their driving compared to times when they are not texting. 

However, 24% reported they are distracted and not as aware, 21% reported that they drive more slowly, 

and 11% reported that they tend to drift out of their lane of travel. 

A large majority of respondents reported that they would feel very unsafe if their driver was sending emails or text messages (86%), or reading e-mails or text messages (85%). The majority of respondents 

(87%) said that they would be very likely or somewhat likely to do or say something to the driver if the 

driver was sending text messages or e-mails. Distraction-averse respondents were more likely than 

distraction-prone respondents to report feeling unsafe. Almost all distraction-averse drivers (95%) 

reported they would feel very unsafe if their driver was sending e-mails or text messages, compared to 

68% of distraction-prone drivers. Distraction-averse respondents were also more likely to say they would 

intervene if their driver was sending text messages or e-mails while driving. Of respondents classified as 

distraction-averse drivers, 90% stated that they would be very or somewhat likely to intervene if their 

driver was sending e-mails or text messages, compared to 81% of respondents classified as distractionprone drivers.

Few respondents reported involvement in crashes or near-crashes in the past year. In all, 6% of drivers 

reported a crash and 7% reported a near-crash in the past year. Of these events, 2% involved cell phone 

distractions, and 3% involved distractions from sending or reading text messages. 

Respondents perceived distracted driving behaviors like talking on a cell phone while driving to be fairly 

prevalent, with 70% of respondents estimating that more than half of drivers talk on the cell phone at least 

occasionally. However, respondents perceived texting while driving to be a less frequent occurrence, with 

43% of respondents estimating that more than half of drivers send electronic messages while driving. 

The majority of respondents support laws banning talking on hand-held cell phones and texting or emailing while driving. Almost three-quarters of respondents (74%) support a ban on cell phone use while 

driving and 94% support a law banning texting or e-mailing while driving. Support for a hand-held cell 

phone ban law is higher among distraction-averse drivers than among distraction-prone drivers (82% 

versus 60%, respectively).

Respondents are generally aware of laws that ban talking on cell phones or texting while driving in their 

state when the State in which the respondent is located has a law, but respondent perceptions are less 

accurate when asked about such laws when there is no law in the State. In States with laws that ban handheld cell phone use while driving, 88% of drivers were aware of the law and an additional 5% thought the 

State probably had such a law, while only 4% incorrectly thought their State did not have such a law. In 

States without laws that ban talking on cell phones while driving, 42% knew that their State did not have 

such a law, while 28% incorrectly thought that their State had such a law and an additional 11% thought 

the State probably had such a law, when it did not. 

 

In States that ban sending or reading text messages and e-mails while driving, 65% of drivers knew about 

the law and an additional 11% thought the State probably had such a law, while only 8% incorrectly 

thought their State did not have such a law. In States without laws that ban sending and receiving text 

messages and e-mails while driving, 29% were aware that their State did not have such a law, while 37% 

incorrectly thought that their State had a law and an additional 12% thought the State probably had such a 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

107 

law, when it did not. Among all respondents, 17% were not sure whether their State had a law banning 

texting while driving.

Although 10 States have laws banning the use of hand-held cell phones while driving, most respondents 

who reside in these States were not aware of any special enforcement efforts, and respondents were about 

equally split on whether offenders of the law will be ticketed. 

Most respondents in States with laws banning forms of cell phone use while driving were not aware of 

any special enforcement programs. One in 5 respondents (20%) reported that they were aware of a special 

effort to ticket drivers using cell phones while driving, and an additional 3% were unsure.

Overall, 52% of respondents who reported living in a State with laws banning some form of cell phone 

use while driving thought a driver who regularly talks on a cell phone while driving was likely to get a 

ticket in the next 6 months, while 44% stated that it was unlikely that the driver would be ticketed. There 

was little difference between distraction-prone and distraction-averse drivers in this belief. However, 

drivers with less formal education were more likely to believe that the driver would be ticketed, while 

those with more formal education were more likely to believe that the driver would not be ticketed. 

Just over half of respondents (53%) who reported living in a State with laws banning texting or e-mailing 

believed that it was at least somewhat likely that drivers who frequently sends text messages or e-mails 

while driving would get a ticket for this infraction in the next 6 months; 43% think it is at least somewhat 

unlikely. Overall, there was little difference in this perception by driver type. 

Safe driving messages are reaching drivers, with 63% reporting that they had seen or heard a message 

discouraging distracted driving in the past 30 days. Drivers who drove every day were more likely than 

those who drove less frequently to report having seen or heard these messages, and distraction-averse 

people were more likely than distraction-prone respondents to report hearing or seeing these messages. 

The media sources for these messages were TV, reported as the source by 72% of respondents, billboards 

as reported by 27% of respondents, and radio as reported by 30% of respondents. 

Although 93% of respondents reported having heard or seen at least one safe driving slogan in the past 30 

day, most of the individual messages associated with cell phone distracted driving are reaching about 1 in

5 drivers. Approximately 20% of respondents report hearing or seeing “ No Phone Zone”, “Just Drive”, 

“One Text or Call Could Wreck It All”, “On the Road, Off the Phone”, and 1 in 10 report seeing or 

hearing “ Phone in One Hand, Ticket in the Other” and “Put It Down” in the past 30 days. 

While the majority of drivers (77% and 67%) who talk on cell phones or send text messages when driving 

state that the frequency of these behaviors has not changed in the past 30 days, some respondents reported 

decreases. Nineteen percent of the cell phone users stated that there was a decrease in their talking on cell 

phone while driving and 27% of those who text and drive also reported a decrease. An increased 

awareness of safety was cited by 24% in the first group and 38% in the second group as the reason for 

these decreases. Influence and pressure from others was also cited. 

There were few changes in attitudes and behaviors concerned with distracted driving between 2010 and 

2012. The rates of talking with passengers while driving, eating or drinking while driving, and reading 

(books, newspapers, iPods) while driving stayed essentially the same. The proportion of respondents who 

always or almost always answer the phone decreased between 2010 and 2012. In 2010 and 2012, 33% 

and 28% of respondents, respectively, answered an incoming call. The percentage of respondents always 

or almost always initiating phone calls decreased from 10% in 2010 to 6% in 2012. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

108 

The percentage of drivers who send text messages while driving increased slightly from 12% in 2010 to 

14% in 2012. However, the proportion of drivers who always send or read text messages while driving 

remained the same at approximately 1%.

Approximately 3 in 5 drivers in both 2010 and 2012 reported having seen or heard at least one public 

information or educational message discouraging talking on cell phones or sending text messages or emails while driving in the past 30 days. 

Support for laws banning hand-held cell phone use increased from 68% of all respondents in 2010 to 74% 

in 2012. Support for laws banning texting or e-mailing remained about the same with 93% of respondents 

in 2010 and 94% of respondents in 2012 supporting such a law. 

Although the rates of engaging in various distracting activities while driving varied slightly from 2010 to 

2012, there was little change in the proportion of respondents reporting these behaviors. Approximately 

half of respondents (52% in 2010 and 49% in 2012) stated that they always or almost always talked to 

passengers while driving. In 2010, 14% of respondents reported always or almost always eating or 

drinking while driving, while in 2012, this percentage was 11%. In both 2010 and 2012, approximately 

1% of respondents reported always or almost always reading and driving. 

In both 2010 and 2012, when asked if their rates of talking on the cell phone while driving or texting and 

driving had changed in the past 30 days, most drivers who engaged in these activities, indicated that the 

rates of these activities remained the same. Declines in cell phone conversations while driving were 

reported by 12% of respondents in 2010 and 19% in 2012. Among these drivers, increased awareness of 

safety was the reason most often cited (by 31% in 2010 and 24% in 2012). Decreases in texting in the last 

30 days were reported by 31% of respondents in 2010 and 27% of respondents in 2012. Among these 

drivers, reasons given for the decrease were an increased awareness of safety (32% in 2010 and 38% in 

2012), the law (6% in 2010 and 8% in 2012), and influence and pressure from others (1% in 2010 and 7% 

in 2012). 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

109 

REFERENCES

National Center for Statistics and Analysis. (2012, September). Distracted Driving 2010. (Report No. 

DOT HS 811 650). Washington, DC: National Highway Traffic Safety Administration. 

Royal, D. (2003). National Survey of Distracted and Drowsy Driving Attitudes and Behavior - 

2002 Volume I: Findings. (Report No. DOT HS 809 566). Washington, DC: National Highway Traffic 

Safety Administration.

Tison, J., Chaudhary, N., & Cosgrove, L. (2011). National Phone Survey on Distracted Driving Attitudes 

and Behaviors. (Report No. DOT HS 811 555). Washington, DC: National Highway Traffic Safety 

Administration. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A1 

Appendix A

Questionnaire
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A2 

5460 NHTSA Distracted Driving 

Abt SRBI

March 14, 2012

V1.7

2012 National Survey of Distracted Driving Attitudes and Behaviors

Questionnaire

Sample Read-ins:

State [sampstat]

Metro Status

Telephone number 

INTRODUCTION – SCREENING QUESTIONS 

QLAN WHICH LANGUAGE INTERVIEW CONDUCTED IN 

1 English 

2 Spanish 

5460C: CELL SAMPLE

SC1 Hello, I am _____ calling on behalf of the U.S. Department of Transportation. We are conducting 

a national study of Americans' driving habits and attitudes. 

[IF NEEDED: Any answers you give are kept strictly private. A federal agency may not conduct or 

sponsor, and a person is not required to respond to, nor shall a person be subject to a penalty for 

failure to comply with a collection of information subject to the requirements of the Paperwork 

Reduction Act unless that collection of information displays a current valid OMB Control Number. 

The OMB number for this solicitation is 2127-0665 and it expires on February 28, 2013.] 

Are you currently driving?

1 Yes THANK & END, CALLBACK

2 No

9 Refused THANK AND END

SC1a Are you in a safe place to talk right now? 

1 Yes

2 No, call me later SCHEDULE CALLBACK

3 No, CB on land-line RECORD NUMBER, schedule call back

4 Cell phone for business only THANK & END - BUSINESS#

9 Refused THANK AND END 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A3 

SC2 As I mentioned, I am calling on behalf of the Department of Transportation. This collection of 

information is VOLUNTARY and will be used for statistical purposes only so that we may develop 

and evaluate programs designed to reduce the number of traffic-related injuries and deaths. The 

interview will take approximately 20 minutes. Your participation is anonymous, and we will not 

collect any personal information that would allow anyone to identify you. Are you 16 years old or 

older? 

[IF NEEDED: If you would like to learn more about the survey, you can call our toll-free number at 1-

866-898-5285 or visit the DOT website at www.nhtsa.gov and read the Distracted Driving Survey 

Research in Progress notice for more information. The OMB number for this solicitation is 2127-0665 

and it expires on February 28, 2013.] 

1 Yes 

2 Yes, no time SCHEDULE CALLBACK

3 No SCREEN OUT

9 Refused THANK AND END 

Qualified Level 1

SC2a How many persons, age 16 and older, live in your household? 

[ENTER NUMBER 1-10] 

10 10 or more

98 NONE SCREEN OUT, SKIP TO SCR1

99 Don’t know/Refused THANK AND END

SC5 Not counting (this/these) cell phone(s), do you also have a regular landline phone at home? 

1 Cell is only phone SKIP TO SA3

2 Has regular phone at home 

9 Don’t know/Refused THANK AND END

SC6 Of all the telephone calls that you or your family receives, are . . (Read List) 

1 All or almost all calls received on cell phones

2 Some received on cell phones and some on regular phones (SCRN OUT: NOT CELL 

MOSTLY) SKIP TO SCR1

3 Very few or none on cell phones (SCRN OUT: NOT CELL MOSTLY) SKIP TO SCR1

8 (VOL) Don’t know (SCRN OUT: NOT CELL MOSTLY) SKIP TO SCR1

9 (VOL) Refused (SCRN OUT: NOT CELL MOSTLY) SKIP TO SCR1

SC7 Thinking about just your LANDLINE home phone, NOT your cell phone, if that telephone rang 

when someone was home, under normal circumstances, how likely is it that the phone would be 

answered? Would you say it is ... (Read List) 

1 Very likely the landline phone would be answered, 

2 Somewhat likely,

3 Somewhat unlikely, 

4 Very Unlikely, or 

5 Not at all likely the landline phone would be answered 

8 (VOL) Don’t know 

9 (VOL) Refused 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A4 

5460L: LANDLINE SAMPLE

SL1 Hello, I am _____ calling on behalf of the U.S. Department of Transportation. We are conducting 

a national study of Americans' driving habits and attitudes. This collection of information is 

VOLUNTARY and will be used for statistical purposes only so that we may develop and evaluate 

programs designed to reduce the number of traffic-related injuries and deaths. The interview will take 

approximately 20 minutes. Your participation is anonymous, and we will not collect any personal 

information that would allow anyone to identify you. 

[IF NEEDED: If you would like to learn more about the survey, you can call our toll-free number 

at 1-866-898-5285 or visit the DOT website at www.nhtsa.gov and read the Distracted Driving 

Survey Research in Progress notice for more information. A federal agency may not conduct or 

sponsor, and a person is not required to respond to, nor shall a person be subject to a penalty for 

failure to comply with a collection of information subject to the requirements of the Paperwork 

Reduction Act unless that collection of information displays a current valid OMB Control Number. 

The OMB number for this solicitation is 2127-0665 and it expires on February 28, 2013.] 

How many persons, age 16 and older, live in this household? 

[ENTER NUMBER 1-10] 

10 10 or more 

98 NONE SCREEN OUT

99 Don’t know/Refused THANK AND END

Qualified Level 1

ASK IF SL1=1.

SL1b May I speak with that person?

1 Rspn on line SKIP TO SA3

2 Rspn called to phone GO TO SL1d

3 Rspn unavailable SCHEDULE CALLBACK

9 Refused THANK AND END 

ASK IF SL1>1

SL1c In order to select just one person to interview, may I please speak to the person in your 

household, 16 or older, who (RANDOMIZE: has had the most recent/will have the next) 

birthday? 

1 Rspn on line GO TO SA3

2 Rspn called to phone 

3 Rspn unavailable SCHEDULE CALLBACK

9 Refused THANK AND END 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A5 

SL1d Hello, I am _____ calling on behalf of the U.S. Department of Transportation. We are conducting 

a national study of Americans' driving habits and attitudes. This collection of information is 

VOLUNTARY and will be used for statistical purposes only so that we may develop and evaluate 

programs designed to reduce the number of traffic-related injuries and deaths. The interview will take 

approximately 20 minutes. Your participation is anonymous, and we will not collect any personal 

information that would allow anyone to identify you. 

[IF NEEDED: If you would like to learn more about the survey, you can call our toll-free number 

at 1-866-898-5285 or visit the DOT website at www.nhtsa.gov and read the Distracted 

Driving Survey Research in Progress notice for more information. A federal agency may 

not conduct or sponsor, and a person is not required to respond to, nor shall a person be 

subject to a penalty for failure to comply with a collection of information subject to the 

requirements of the Paperwork Reduction Act unless that collection of information displays 

a current valid OMB Control Number. The OMB number for this solicitation is 2127-0665 

and it expires on February 28, 2013.] 

Could I please confirm that you are a household member 16 or older? 

1 Yes 

2 No SCHEDULE CALLBACK

9 Refused THANK AND END – Soft Refusal

SKIP TO SA3
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A6 

4548O: LANDLINE OVERSAMPLE

SO1 Hello, I am _____ calling on behalf of the U.S. Department of Transportation. We are conducting a 

national study of Americans' driving habits and attitudes. This collection of information is 

VOLUNTARY and will be used for statistical purposes only so that we may develop and evaluate 

programs designed to reduce the number of traffic-related injuries and deaths. The interview will 

take approximately 20 minutes. Your participation is anonymous, and we will not collect any 

personal information that would allow anyone to identify you. 

[IF NEEDED: If you would like to learn more about the survey, you can call our toll-free number 

at 1-866-898-5285 or visit the DOT website at www.nhtsa.gov and read the Distracted Driving 

Survey Research in Progress notice for more information. A federal agency may not conduct or

sponsor, and a person is not required to respond to, nor shall a person be subject to a penalty for 

failure to comply with a collection of information subject to the requirements of the Paperwork 

Reduction Act unless that collection of information displays a current valid OMB Control Number. 

The OMB number for this solicitation is 2127-0665 and it expires on February 28, 2013.] 

How many people, 16 to 34, live in this household?

[ENTER NUMBER 1-10] 

10 10 or more 

98 NONE SCREEN OUT

99 Don’t know/Refused THANK AND END

Qualified Level 1

ASK IF SO1=1.

SO1b May I speak with that person?

1 Rspn on line SKIP TO SA3

2 Rspn called to phone GO TO SO1d

3 Rspn unavailable SCHEDULE CALLBACK

9 Refused THANK AND END 

ASK IF SO1>1

SO1c In order to select just one person to interview, may I please speak to the person in your 

household, 16 to 34, who (has had the most recent/will have the next) birthday? 

1 Rspn on line GO TO SA3

2 Rspn called to phone 

3 Rspn unavailable SCHEDULE CALLBACK

9 Refused THANK AND END 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A7 

SO1d Hello, I am _____ calling on behalf of the U.S. Department of Transportation. We are conducting 

a national study of Americans' driving habits and attitudes. This collection of information is 

VOLUNTARY and will be used for statistical purposes only so that we may develop and evaluate 

programs designed to reduce the number of traffic-related injuries and deaths. The interview will take 

approximately 20 minutes. Your participation is anonymous, and we will not collect any personal 

information that would allow anyone to identify you. 

[IF NEEDED: If you would like to learn more about the survey, you can call our toll-free number 

at 1-866-898-5285 or visit the DOT website at www.nhtsa.gov and read the Distracted 

Driving Survey Research in Progress notice for more information. A federal agency may 

not conduct or sponsor, and a person is not required to respond to, nor shall a person be 

subject to a penalty for failure to comply with a collection of information subject to the 

requirements of the Paperwork Reduction Act unless that collection of information displays 

a current valid OMB Control Number. The OMB number for this solicitation is 2127-0665 

and it expires on February 28, 2013.] 

Could I please confirm that you are a household member 16 to 34?

1 Yes 

2 No SCHEDULE CALLBACK

9 Refused THANK AND END 

SA3 Record gender from observation. (Ask only if Necessary) 

1 Male

2 Female

Qualified Level 2

GENERAL DRIVING INFORMATION 

Q1) How often do you drive a motor vehicle, regardless of whether it is for work or for personal use? 

Every day, almost every day, a few days a week, a few days a month, a few days a year, or do you never 

drive? 

[DO NOT READ LIST] 

1 Every day

2 Almost every day 

3 Few days a week 

4 Few days a month 

5 Few days a year 

6 Never SKIP TO Q24 [SCREEN OUT – DEMOS ONLY]

7 (VOL) Other (SPECIFY) 

98 (VOL) Don’t know SKIP TO Q24 [SCREEN OUT – DEMOS ONLY]

99 (VOL) Refused SKIP TO Q24 [SCREEN OUT – DEMOS ONLY]
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A8 

Q1a) Is the vehicle you drive most often a car, van, motorcycle, sport utility vehicle, pickup truck, or 

other type of truck? 

[NOTE: IF RESPONDENT DRIVES MORE THAN ONE VEHICLE OFTEN, ASK:] “What kind of 

vehicle did you LAST drive?” 

1 Car 

2 Van or minivan 

3 Motorcycle 

4 Pickup truck 

5 Sport Utility Vehicle 

6 Other truck (SPECIFY) 

7 (VOL) Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refused 

PERCEPTIONS OF ENFORCEMENT 

Q2 When you pass a driver stopped by the police IN THE DAYTIME, what do you think the stop was 

most likely for? 

[DO NOT READ LIST - MULTIPLE RECORD] 

1 Speeding 

2 Seat Belt Violation 

3 Drunk Driving 

4 Reckless Driving 

5 Cell phone use 

6 Texting or sending e-mails while driving 

7 Registration Violation 

8 Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refused 

Q2a) When you pass a driver stopped by the police IN THE NIGHTTIME, what do you think the stop 

was for? [DO NOT READ LIST - MULTIPLE RECORD] 

1 Speeding 

2 Seat Belt Violation 

3 Drunk Driving 

4 Reckless Driving 

5 Cell phone use 

6 Texting or sending e-mails while driving 

7 Registration Violation 

8 Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refused 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A9 

OWNERSHIP OF MOBILE ELECTRONICS 

Q3) Do you CURRENTLY own any of the following devices? 

[READ A-H AND CODE FOR EACH:] 

a) A cell phone [Code 1 (Yes) if mentions any cell phone including a smartphone] 

b) A ‘smartphone’ such as a Droid, iPhone, or Blackberry 

c) A pager or beeper 

d) A portable music player, such as a CD player, iPod, or Zune 

e) A portable navigation system, such as TomTom or Garmin 

f) A navigation system built into the vehicle, such as OnStar or Sync 

g) A laptop computer,iPad, Kindle, or Nook 

h) [ASK IF 3a OR 3b= Yes] A Bluetooth or other hands-free device for your cell phone, such as one that 

plugs into the phone, works wirelessly, or works through your vehicle’s car stereo

1 Yes 

2 No 

3 Mixed/Shared Use 

98 (VOL) Don’t know 

99 (VOL) Refused 

FREQUENCY OF DISTRACTED DRIVING 

Q4) I’m going to read a list of activities, and for each I’d like you to tell me how often YOU do each 

while driving? For each, please tell me if you do the activity always, almost always, sometimes, rarely, or 

never? How often do you... 

[READ A-N AND CODE FOR EACH:] 

a) Talk to other passengers in the vehicle 

b) Eat or drink 

c) Make or accept phone calls 

d) Read, such as a book, newspaper, iPad or Kindle 

e) Read e-mails or text messages 

f) Send text messages or e-mails 

g) Talk or interact with children in the back seat 

h) Do personal grooming, such as put on make-up, shave, or look at yourself in the mirror 

i) Adjust the car radio 

j) Change CDs, DVDs, or tapes 

k) Use a portable music player, including a smartphone, with headphones on 

l) Use a portable music player, including a smartphone, with external speakers or with the car’s speakers 

m) Use your Smartphone for driving directions 

n) Use a navigation system for driving directions 

1) Always

2) Almost always

3) Sometimes

4) Rarely 

5) Never 

98) (VOL) Don’t know 

99) (VOL) Refuse 

IF (Q4c=5) SKIP TO Q9
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A10 

ANSWERING AND MAKING CELL PHONE CALLS WHILE DRIVING 

Q5a) When you RECEIVE a phone call while you are driving, how often do you ANSWER the call? 

[READ LIST] 

1 Always

2 Almost always 

3 Sometimes 

4 Rarely 

5 Never [SKIP TO Q6a] 

98 (VOL) Don’t know 

99 (VOL) Refuse 

Q5b) What are the reasons you are more likely to ANSWER a call while driving? 

[DO NOT READ LIST - MULTIPLE RECORD] 

1 I answer all calls 

2 Who is calling 

3 How important I think the call is 

4 Availability of the phone 

5 Call is work-related

6 Call is personal or social 

7 Call is routine or expected 

8 Call is unexpected 

9 Call is from someone I know 

10 Call is from a number I don’t recognize 

11 Non-stressful traffic conditions 

12 Good weather conditions 

13 Traveling at a low speed 

14 Time of day 

15 Boredom 

16 In need of directions or other information 

17 Personal safety 

18 If State law allows 

19 No police officers in sight 

20 Tired (talking keeps me awake) 

21 Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refuse 

Q5c) When you answer a call while driving, do you USUALLY... [READ LIST] 

1 Answer and continue to drive while completing the conversation 

2 Answer and promptly pull over to a safe location 

3 Answer and inform the caller you will call back later 

4 Pull over to a safe location first and then speak to the caller 

5 Hand the phone to a passenger to answer if you have one 

98 (VOL) Don’t know 

99 (VOL) Refuse 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A11 

Q5d) Which of the following do you USUALLY do when you answer a call while driving? Please answer 

Yes or No after I read each item. 

[READ LIST] MULTIPLE RECORD.

1 Hold the phone in your hand 

2 Squeeze the phone between your ear and shoulder 

3 Use a hands-free earpiece 

4 Use a built-in-car system (OnStar, Sync, or built-in Bluetooth) 

5 Use the cell phone’s speakerphone feature 

6 Varies 

98 (VOL) Don’t know 

99 (VOL) Refuse 

Q6a) When you are driving, how often are you willing to MAKE a phone call? 

[READ LIST] 

1 Always

2 Almost always

3 Sometimes

4 Rarely 

5 Never [SKIP TO Q7] 

98 (VOL) Don’t know 

99 (VOL) Refuse 

Q6b) What are the reasons you are more likely to MAKE a call while driving? 

[DO NOT READ LIST - MULTIPLE RECORD] 

1 Who I’m calling 

2 How important/urgent I think the call is 

3 Availability of the phone 

4 Work-related 

5 Personal or social 

6 Non-stressful traffic conditions 

7 Good weather conditions 

8 Traveling at a low speed 

9 Time of day 

10 Boredom 

11 If I need of directions or other information 

12 I think it’s safe to call 

13 Personal Safety 

14 If State law permits 

15 No police officers in sight 

16 Report a traffic crash/emergency 

17 Report a medical emergency 

18 Tired (talking keeps me awake) 

19 Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refuse 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A12 

Q6c) Which of the following ways do you usually MAKE a call while driving? Please answer Yes or No 

after I read each item. 

[READ LIST – MULTIPLE RECORD]

1 Manual dialing 

2 Voice-dial (speaking a name or phone number) 

3 Speed dial or favorites 

4 Scroll through saved numbers and select 

5 Varies 

98 (VOL) Don’t know 

99 (VOL) Refuse 

[IF Q5a = 5 (Never) AND Q6a = 5 (Never), SKIP TO Q9] 

Q7) How, if at all, would you say your driving is different when you are TALKING on the phone? 

[DO NOT READ, MULTIPLE RECORD] 

1 No difference 

2 Drive slower 

3 Drive faster 

4 Change lanes more frequently 

5 Change lanes less frequently 

6 Avoid changing lanes altogether 

7 Apply the brakes suddenly 

8 Drift out of the lane or roadway 

9 Use turn signal less regularly 

10 Use turn signal more regularly 

11 Increase distance from lead vehicle 

12 Follow lead vehicle more closely 

13 Look in your rear or side view mirrors more frequently 

14 Look in your rear or side view mirrors less frequently 

15 Other [SPECIFY] 

98 (VOL) Don’t Know 

99 (VOL) Refused 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A13 

Q8) Is there any driving situation in which you would NEVER TALK on a phone while driving? 

[DO NOT READ, MULTIPLE RECORD] 

1 When moving (not at stop signs or stop lights) 

2 on long trips 

3 on short trips 

4 Fast moving traffic (freeway) 

5 Bumper to bumper traffic 

6 on an empty roadway 

7 Merging with traffic 

8 Bad weather 

9 Driving a familiar route

10 Driving in unfamiliar area/roads 

11 Driving at nighttime 

12 Marked school zones 

13 Residential streets 

14 Parking lots 

15 With other adult passengers in the car 

16 With a baby or child on board 

17 Winding/curving roads 

18 Marked construction zones 

19 When I see a police officer 

20 When driving in a place where it is prohibited 

21 Other [SPECIFY] 

98 (VOL) Don’t Know 

99 (VOL) Refused 

TEXTING OR E-MAILING WHILE DRIVING 

IF (Q4f=5) SKIP TO Q13 

Q9) Do you ever SEND text messages or e-mails when you are driving? 

1 Yes 

2 No [SKIP TO Q13] 

98 (VOL) Don’t Know 

99 (VOL) Refused 

Q10) If you SEND a text message or e-mail while driving, do you USUALLY... 

[READ LIST] 

1 Continue to drive while completing the message 

2 Pull over to a safe location to send the message 

3 Hand the phone to a passenger to do your messaging 

4 Use a Voice Command feature (speech dictation) 

5 Wait until you reach a red light or stop sign to send the message 

98 (VOL) Don’t know 

99 (VOL) Refuse 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A14 

Q10a) What makes it more likely you will SEND a text message or e-mail while driving? 

[DO NOT READ LIST - MULTIPLE RECORD] 

1 Who I’m messaging 

2 How important I think the message is 

3 Work-related

4 Personal or social 

5 Non-stressful traffic conditions 

6 Good weather conditions 

7 Traveling at a low speed 

8 Time of day 

9 Boredom 

10 In need of directions or other information 

11 I think it’s safe to call 

12 Personal Safety 

13 If State law permits 

14 If no police officers are in sight 

15 Report a traffic crash/emergency 

16 Report a medical emergency 

17 Tired (texting keeps me awake) 

18 Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refuse 

Q11) How would you say your driving is different when you are SENDING TEXT OR E-MAIL

MESSAGES? 

[DO NOT READ, MULTIPLE RECORD] 

1 No difference 

2 Drive slower 

3 Drive faster 

4 Change lanes more frequently 

5 Change lanes less frequently 

6 Avoid changing lanes altogether 

7 Apply the brakes suddenly 

8 Drift out of the lane or roadway 

9 Use turn signal less regularly 

10 Use turn signal more regularly 

11 Increase distance from lead vehicle 

12 Follow lead vehicle more closely 

13 Look in your rear or side view mirrors more frequently 

14 Look in your rear or side view mirrors less frequently 

15 Other [SPECIFY] 

98 (VOL) Don’t Know 

99 (VOL) Refused 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A15 

Q12) Is there any driving situation in which you would NEVER SEND a text or e-mail message while 

driving? 

[DO NOT READ, MULTIPLE RECORD:] 

1 When moving (not at stop signs or stop lights) 

2 on long trips 

3 on short trips 

4 Fast moving traffic (freeway) 

5 Bumper to bumper traffic 

6 on an empty roadway 

7 Merging with traffic 

8 Bad weather 

9 Driving a familiar route 

10 Driving in unfamiliar area/roads 

11 Driving at nighttime 

12 Marked school zones 

13 Residential streets 

14 Parking lots 

15 With other adult passengers in the car 

16 With a baby or child on board 

17 Winding/curving roads 

18 Marked construction zones 

19 When I see a police officer 

20 When driving in a place where it is prohibited

21 Other [SPECIFY] 

98 (VOL) Don’t Know 

99 (VOL) Refused 

PERCEPTIONS ABOUT DANGER OF DISTRACTIONS 

Q13) How many seconds do you believe a driver can take his or her eyes off the road before driving 

becomes significantly more dangerous? 

ENTER VALUE: _____

11 11 seconds or more 

98 (VOL) Don’t know 

99 (VOL) Refuse 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A16 

Q14) Now I’m going to read a list of things people sometimes do while driving. Tell me how safe you 

would feel if you were a passenger riding in a car while your driver was doing the following. For each 

please tell me if you would feel very unsafe, somewhat unsafe, a little less safe, or safe – no problem – 

would not pay any more attention. 

[READ A-O AND RECORD FOR EACH:] 

a) Talking to other passengers in the vehicle 

b) Eating or drinking 

c) Talking on a cell phone while holding the phone 

d) Talking on a cell phone with a hands-free device 

e) Reading, such as a book, newspaper, or an iPad or Kindle 

f) Reading e-mails or text messages 

g) Sending text messages or e-mails 

h) Talking or interacting with children in the back seat 

i) Doing personal grooming, such as putting on make-up, shaving, looking in the mirror 

j) Adjusting the car radio, tape, or CD player 

k) Singing along to a song on the radio 

l) Using a laptop computer 

m) Using a portable music player with headphones on 

n) Manipulating a navigation system for driving directions 

o) Watching a movie 

1 Very unsafe 

2 Somewhat unsafe 

3 A little less safe 

4 Safe, no problem, would not pay any more attention 

98 (VOL) Don’t know 

99 (VOL) Refuse 

Q14b) How likely are you to do or say something to your driver if they’re TALKING on a hand-held cell 

phone while driving?

[READ LIST] 

1 Very likely 

2 Somewhat likely 

3 Somewhat unlikely SKIP TO Q14c

4 Very unlikely SKIP TO Q14c

5 Never would intervene SKIP TO Q14c

98 (VOL) Don’t know SKIP TO Q14c

99 (VOL) Refused SKIP TO Q14c

Q14bo) What would you say? 

(SPECIFY)

PROBE: Anything Else?
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A17 

Q14c) How likely are you to do or say something to your driver if they’re SENDING TEXT MESS OR 

E-MAILS while driving? 

[READ LIST] 

1 Very likely 

2 Somewhat likely 

3 Somewhat unlikely SKIP TO Q15

4 Very unlikely SKIP TO Q15

5 Never would intervene SKIP TO Q15

98 (VOL) Don’t know SKIP TO Q15

99 (VOL) Refused SKIP TO Q15

Q14co) What would you say? 

(SPECIFY)

PROBE: Anything Else?

CHANGES IN DISTRACTED DRIVING 

Q4c = 5 SKIP TO Q16]

Q15) In the past 30 days, has your frequency of making and receiving phone calls while driving 

increased, decreased, or stayed the same? 

1 Increased SKIP TO Q15b 

2 Decreased 

3 Stayed the same SKIP TO Q15b 

4 New Driver SKIP TO Q15b 

5 Never used a phone while driving SKIP TO Q16

98 (VOL) Don’t know SKIP TO Q15b 

99 (VOL) Refuse SKIP TO Q15b 

Q15a) What caused your frequency of making and receiving phone calls while driving to decrease? 

[DO NOT READ LIST - MULTIPLE RECORD] 

1 Increased awareness of safety 

2 Law that bans cell phone use 

3 Don’t want to get a ticket 

4 Was in a crash 

5 Influence/pressure from others 

6 More long distance driving 

7 The weather 

8 Driving faster 

9 Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refused 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A18 

Q15b) [ASK IF Q9 = 1] In the past 30 days, has the frequency with which you send and receive text 

messages or e-mails while driving increased, decreased, or stayed the same? 

1 Increased SKIP TO Q16 

2 Decreased 

3 Stayed the same SKIP TO Q16 

4 New Driver SKIP TO Q16 

5 Never used a phone while driving SKIP TO Q16 

98 (VOL) Don’t know SKIP TO Q16 

99 (VOL) Refuse SKIP TO Q16 

Q15c) [ASK IF Q9 = 1] What caused the frequency with which you send and receive text messages or emails while driving to decrease? 

[DO NOT READ LIST - MULTIPLE RECORD] 

1 Increased awareness of safety 

2 Law that bans texting/e-mailing 

3 Don’t want to get a ticket 

4 Was in a crash 

5 Influence/pressure from others 

6 More long distance driving 

7 The weather 

8 Driving faster 

9 Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refused 

DISTRACTED DRIVING LAWS 

Q16) Does [SAMPSTAT] have a law banning talking on a hand-held cell phone while driving? 

1 Yes 

2 Yes, probably 

3 No SKIP TO Q16b 

98 (VOL) Don’t Know 

99 (VOL) Refused SKIP TO Q16b 

Q16a) Assume that over the next six months someone frequently TALKS on a hand-held cell phone while 

driving. How likely do you think that person would be to receive a ticket for talking on a cell phone while 

driving? 

[READ LIST] 

1 Very likely 

2 Somewhat likely 

3 Somewhat unlikely 

4 Very unlikely 

98 (VOL) Don’t know 

99 (VOL) Refused 

Q16b) Does [SAMPSTAT] have a law banning TEXTING OR E-MAILING while driving?

1 Yes 

2 Yes, probably 

3 No SKIP TO Q17 

98 (VOL) Don’t Know 

99 (VOL) Refused SKIP TO Q17 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A19 

Q16c) Assume that over the next six months someone frequently sends text messages or e-mails while 

driving. How likely do you think that person would be to receive a ticket for sending text messages or emails while driving? 

[READ LIST] 

1 Very likely 

2 Somewhat likely 

3 Somewhat unlikely 

4 Very unlikely 

98 (VOL) Don’t know 

99 (VOL) Refused 

Q17) Do you support a State law banning talking on a hand-held cell phone while driving? 

1 Yes 

2 No SKIP TO Q17b 

98 (VOL) Don’t Know 

99 (VOL) Refused SKIP TO Q17b 

Q17a) What do you think the fine should be for talking on a hand-held cell phone while driving? 

[RECORD VALUE] 

0 No fine 

997 $997 or more 

998 (VOL) Don’t know 

999 (VOL) Refuse 

Q17b) Do you support a State law banning texting or e-mailing while driving? 

1 Yes 

2 No SKIP TO Q18 

98 (VOL) Don’t Know 

99 (VOL) Refused SKIP TO Q18 

Q17c) What do you think the fine should be for sending text messages or e-mails while driving? 

[RECORD VALUE] 

0 No fine 

997 $997 or more 

998 (VOL) Don’t know 

999 (VOL) Refuse 

PROGRAM AWARENESS 

Q18) In the past 30 days, have you seen or heard of any special effort by police to ticket drivers in your 

community for using handheld cell phones while driving? 

1 Yes 

2 No SKIP TO Q18b 

98 (VOL) Don’t Know SKIP TO Q18b 

99 (VOL) Refused SKIP TO Q18b 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A20 

Q18a) Where did you see or hear about that special effort? 

[DO NOT READ LIST - MULTIPLE RECORD] 

1 TV - advertisement/public service announcement 

2 TV - news 

3 Radio - advertisement/public service announcement 

4 Radio - news 

5 Online news/blog 

6 Internet ad/banner 

7 Social networking website (Facebook, MySpace, Twitter) 

8 Online video (YouTube, Google Video) 

9 Friend/relative 

10 Newspaper/magazine 

11 Witnessed enforcement activity 

12 Billboard/signs 

13 Educational program 

14 I’m a police officer/judge 

15 Direct contact by police officer 

16 Internet game 

17 Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refused 

Q18b) Were you personally stopped by police for using a handheld cell phone while driving in the past 30 

days?

1 Yes 

2 No SKIP TO Q19 

98 (VOL) Don’t Know SKIP TO Q19 

99 (VOL) Refused SKIP TO Q19 

Q18c) Did you receive a ticket or warning? 

1 Yes - ticket for talking on a cell phone 

2 Yes - warning for talking on a cell phone 

3 Yes - ticket for texting or sending an e-mail 

4 Yes - warning for texting or sending an e-mail 

5 No 

98 (VOL) Don’t Know 

99 (VOL) Refused 

OTHER EDUCATIONAL MESS

Q19) Now, I would like to ask you a few questions about educational or other types of activities. In the 

past 30 days, have you seen or heard any messages that encourage people not to talk on phones or send 

electronic messages while driving? This could be public service announcements on TV, messages on the 

radio, signs on the road, news stories, or something else. 

1 Yes 

2 No SKIP TO Q20 

98 (VOL) Don’t Know SKIP TO Q20 

99 (VOL) Refused SKIP TO Q20 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A21 

Q19a) Where did you see or hear these messages? 

[DO NOT READ LIST - MULTIPLE RECORD] 

1 TV - advertisement/public service announcement 

2 TV – news 

3 TV show storyline 

4 Radio - advertisement/public service announcement 

5 Radio - news 

6 Online news/blog 

7 Internet ad/banner 

8 Social networking website (Facebook, MySpace, Twitter) 

9 Online video (YouTube, Google Video) 

10 Friend/relative 

11 Newspaper/magazine 

12 Personal observation/on the road 

13 Billboard/signs 

14 Educational program 

15 I’m a police officer/judge 

16 Direct contact by police officer 

17 Internet game 

18 Other (SPECIFY) 

98 (VOL) Don’t know 

99 (VOL) Refused 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A22 

Q20) Do you recall hearing or seeing the following slogans in the past 30 days? 

[READ A-R AND RECORD FOR EACH:] 

a) Friends don’t let friends drive drunk 

b) Click it or Ticket 

c) on the Road, Off the Phone 

d) Drive by the Rules, Keep the Privilege 

e) u txt i tikit 

f) Phone in One Hand, Ticket in the Other 

g) Just Drive 

h) You Drink and Drive. You Lose. 

i) No Phone Zone 

j) Get the keys 

k) Drunk Driving Over the Limit under Arrest 

l) Four Steps for Kids 

m) Put it Down 

n) If they’re under FOUR FEET, NINE INCHES, they need a booster seat 

o) One Text or Call Could Wreck it All

p) Drive Sober or Get Pulled Over 

1 Yes 

2 No 

98 (VOL) Don’t Know 

99 (VOL) Refused 

EXPOSURE TO DISTRACTED DRIVING CRASHES AND STORIES 

Q21) Have you been involved in a crash or near-crash as a driver in the past year? 

1 Yes - near-crash 

2 Yes - crash 

3 No SKIP TO Q22 

98 (VOL) Don’t Know SKIP TO Q22 

99 (VOL) Refused SKIP TO Q22 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A23 

Q21a) Were you using a cell phone at the time of the LAST [crash/near-crash] you were in? 

1 Yes - talking 

2 Yes - reading electronic text 

3 Yes - sending text message or e-mail 

4 No 

98 (VOL) Don’t Know 

99 (VOL) Refused 

PERCEPTIONS OF AND RESPONSES TO OTHER DISTRACTED DRIVERS 

Q22) What percentage of drivers do you believe at least occasionally TALK on a cell phone while 

driving? 

[RECORD VALUE] 

998 (VOL) Don’t know 

999 (VOL) Refuse 

Q22a) What percentage of drivers do you believe at least occasionally SEND TEXT MESS OR E-MAILS 

on a cell phone while driving? 

[RECORD VALUE] 

998 (VOL) Don’t know 

999 (VOL) Refuse 

INTERVENING AS A PASSENGER 

Q23) When riding as a passenger, how comfortable would you feel if your driver was TALKING on a 

cell phone while driving? 

[READ LIST] 

1 Very comfortable – No problem 

2 Aware but not uncomfortable 

3 Somewhat uncomfortable 

4 Uncomfortable 

5 Very uncomfortable 

98 (VOL) Don’t know 

99 (VOL) Refused 

Q23a) When riding as a passenger, how comfortable would you feel if your driver was SENDING TEXT 

MESS OR E-MAILS while driving? 

[READ LIST] 

1 Very comfortable – No problem 

2 Aware but not uncomfortable 

3 Somewhat uncomfortable 

4 Uncomfortable 

5 Very uncomfortable 

98 (VOL) Don’t know 

99 (VOL) Refused 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A24 

DEMOGRAPHIC QUESTIONS 

[SAY:] Now, I need to ask you some basic information about you and your household. Again, this 

information is confidential and will not be used to identify you personally. 

Q24) What is your age? 

[RECORD VALUE] RANGE: 16-101/998/999 

 101 101 or older 

998 (VOL) Don’t know 

999 (VOL) Refuse 

IF (SAMPLE=LANDLINE X-SECTION OR CELL) SKIP TO Q24b

Q24a) Including yourself, how many people, 16 or older, are living in your household at least half of the 

time or consider it their primary residence? 

[RECORD VALUE] RANGE: 0-11/998/999 

 11 11 or more 

998 (VOL) Don’t know 

999 (VOL) Refuse 

Q24b) How many children 15 or younger are living in your household at least half of the time or consider 

it their primary residence? 

[RECORD VALUE] RANGE: 0-11/998/999 

 11 11 or more 

998 (VOL) Don’t know 

999 (VOL) Refuse 

Q24c) Do you consider yourself to be Hispanic or Latino? 

1 Yes 

2 No 

98 (VOL) Don’t Know 

99 (VOL) Refused 

Q24d) Which of the following racial categories describe you? You may select more than one. 

[READ LIST - MULTIPLE RECORD] 

1 American Indian or Alaska Native 

2 Asian 

3 Black or African American 

4 Native Hawaiian or other Pacific Islander 

5 White 

6 (VOL) Hispanic

7 Other (SPECIFY)

99 (VOL) Refused 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A25 

Q24e) What is highest grade or year of regular school you have completed? DO NOT READ 

1 No formal schooling 

2 First through 7th grade 

3 8th grade 

4 Some high school 

5 High school graduate 

6 Some college 

7 Four-year college graduate 

8 Some graduate school 

9 Graduate degree 

10 (VOL) Refused 

Q24e1) Do you own or rent your home? 

1 Own

2 Rent 

3 Some other arrangement 

98 (VOL) Don’t Know 

99 (VOL) Refused 

Q24f) How many landline telephone numbers do you have in your household? 

[RECORD VALUE] RANGE: 0-97/98/99 

97 97 or more 

98 (VOL) Don’t know 

99 (VOL) Refuse 

Q24g) How many separate cell phone numbers do you have in your household? 

[RECORD VALUE] RANGE: 0-97/98/99 

97 97 or more 

98 (VOL) Don’t know 

99 (VOL) Refuse 

ASK ONLY IF LANDLINE SAMPLE OR OVERSAMPLE AND (Q24G>0 AND Q24G<98)

Q24h Of all the telephone calls that you or your family receives, are . . (Read List) 

1 All or almost all calls received on cell phones 

2 Some received on cell phones and some on regular phones 

3 Very few or none on cell phones 

98 (VOL) Don’t know 

99 (VOL) Refused 

ASK ONLY IF LANDLINE SAMPLE OR OVERSAMPLE AND (Q24G>0 AND Q24G<98)

Q24i Thinking about just your LANDLINE home phone, NOT your cell phone, if that telephone rang 

when someone was home, under normal circumstances, how likely is it that the phone would be 

answered? Would you say it is ... (Read List) 

1 Very likely the landline phone would be answered, 

2 Somewhat likely,

3 Somewhat unlikely, 

4 Very Unlikely, or 

5 Not at all likely the landline phone would be answered 

98 (VOL) Don’t know 

99 (VOL) Refused 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

A26 

Q24j) What is your approximate household income? 

[READ LIST] 

1 Less than $10,000 

2 $10,000 to $14,999 

3 $15,000 to $24,999 

4 $25,000 to $49,999 

5 $50,000 to $99,999 

6 $100,000 to $149,999 

7 $150,000 to $199,999 

8 $200,000 or more 

98 (VOL) Don’t Know 

99 (VOL) Refused 

Q24j1) Have you visited the distraction.gov website or looked for distracted driving information on 

nhtsa.gov? 

1 Yes 

2 No

8 (VOL) Don’t Know 

9 (VOL) Refused 

Q24k. May I please have your zip code? 

ENTER 5 DIGIT ZIP CODE:

99998 (VOL) Don’t Know 

99999 (VOL) Refused 

[READ:] That completes the survey. Thank you very much for your time and cooperation. If you would 

like information about traffic safety, please visit www.nhtsa.gov. 

SCR1 I am sorry but you are not eligible to participate in the survey today. Thank you for your 

cooperation and I hope you have a pleasant evening.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B1 

Appendix B 

Methodology
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B2 

Survey Methodology for the 2012 National Survey on Distracted Driving Attitudes and Behaviors

The goal of the 2012 National Survey on Distracted Driving Attitudes and Behavior was to obtain a 

“snapshot” of the attitudes and behaviors with regards to distracted driving activities of the population of 

drivers in the United States using a telephone survey of U.S. drivers 16 and older. Only surveys based on 

probability samples can be used to create mathematically sound statistical inferences about a larger target 

population. Most statistical formulas for specifying the sampling precision (estimates of sampling 

variance), given particular sample sizes, are premised on simple random sampling. However, random 

sampling requires an enumeration of all of the elements in the population. Since no enumeration of the 

total population of the United States (or its subdivisions) is available, all surveys of the general public are 

based upon complex sample designs that may employ stratification and two or more stages of sampling. 

A sampling design using geographic stratification (NHTSA Region), an oversample of young drivers, 

sampling frames of households with landlines and cell phones, together with an overall sample size of 

6,000 was developed and implemented for this survey. The final sample consisted of 6,016 respondents, 

which included an oversample of 682 drivers 16 to 34 years old, with 35.6% of respondents coming from 

cell phone only or cell phone mostly households. Weights were developed to yield national estimates of 

the target population within specified limits of expected sampling variability. This appendix describes the 

methods of sample construction and survey administration, and shows the sample disposition and 

computation of weights. 

Sample Construction

Strata - The initial stage in the construction of this sample required the development of a national 

probability sample of the non-institutionalized population of the United States aged 16 and older. 

Stratification (i.e., division of the population into collectively exhaustive and mutually exclusive 

homogenous groups), an efficient way of achieving high statistical precision with a smaller overall 

sample size, was employed. The United States was stratified into 10 strata, each consisting of the States in 

NHTSA’s 10 regions.

6

 

The estimated distribution of the target population by stratum was calculated on the basis of the U.S. 

Census Bureau, Population Estimates by State by Single Year of Age, Sex, Race, and Hispanic Origin: 

2008. The population estimates were taken for the population 16 and older. Based on these Census 

estimates of the geographic distribution of the target population, the total sample was proportionately 

allocated by stratum. 

Oversample of respondents 16 to 34 - Given NHTSA’s interest in the driving behaviors of young 

drivers, it was very important that the subsample of drivers 16 to 34 years old in this survey be large 

enough for meaningful statistical analysis. However, the population prevalence of this age group was not 

 

6 Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont

Region 2: New Jersey, New York, Pennsylvania, Puerto Rico, and the Virgin Islands

Region 3: Delaware, District of Columbia, Kentucky, Maryland, North Carolina, Virginia, West Virginia

Region 4: Alabama, Florida, Georgia, South Carolina, Tennessee

Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin

Region 6: Indian Nations, Louisiana, Mississippi, New Mexico, Oklahoma, Texas

Region 7: Arkansas, Iowa, Kansas, Missouri, Nebraska

Region 8: Colorado, Nevada, North Dakota, South Dakota, Utah, Wyoming

Region 9: Arizona, California, Hawaii, Pacific Territories

Region 10: Alaska, Idaho, Montana, Oregon, Washington
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B3 

large enough to generate the desired subsample size, given a total sample of 6,000 for the survey so an 

oversample was included. Based on year 2008 Census Bureau estimates of the civilian noninstitutionalized population, we estimated that in a population based sample about 33 percent of drivers 

should be 16 to 34. Our experience with recent telephone surveys using only conventional random digit 

dialing (RDD) of landline households indicates that the subsample of respondents 16 to 34 obtained by 

this method would fall short of the desired 33 percent of the total sample. For example, in the 2007 Motor 

Vehicle Occupant Safety Survey (MVOSS) that relied on RDD of landline phones, respondents 16 to 34 

made up only 18% of the entire sample. 

Table B1 shows the national population figures and projected sample distribution by age for the total 

sample of 6,000 respondents. The fourth column shows the desired sample from a population based 

sample, and the last two columns show and what could be expected from a conventional RDD landline 

approach such as that used in MVOSS 2007 study. 

Table B-1. Expected Population and Sample Distribution** by Age Based on June 1, 2008 Census 

Bureau Estimates

Target Population

Sample Distribution

Population 

Based

Expected Distribution Based on 

2007 MVOSS Response 

(N in 1000s) % n n %

Total (16+) 233,627 100% 6,000 6,000 100%

 16-24 37,476 16.0% 962 366 6.1%

 25-34 39,960 17.1% 1,026 732 12.2%

 35-44 41,735 17.9% 1,072 1,086 18.1%

 45-64 77,397 33.1% 1,988 2,406 40.1%

 65+ 37,060 15.9% 952 1,410 23.5%

U.S. Bureau of the Census, Population Estimates, Age Category Estimates, 6/01/08

Source: http://www.census.gov/popest/index.html

 ** Sample distribution from MVOSS 2007 with RDD landline survey 

The reasons for this discrepancy include a lower response rate among younger adults, a higher proportion 

of people 16 to 34 living in group quarters (e.g., dormitories), and a higher proportion of this age group 

living in cell phone only households. Hence, a simple proportionate sample of the adult driver population 

based on RDD landline methodology would not meet the needs of this study design. Consequently, an 

oversample of 682 respondents 16 to 34 was included in the sample design at the start of the study.

Landline and Cell Phone RDD samples - As noted above, RDD landline telephone sampling has been 

the conventional approach for conducting surveys of the U.S. household population for the past few 

decades. However, households are increasingly turning to cell phones, and some households have 

abandoned landline phones altogether. For example, the second half of 2011, the percentage of cell phone 

only households (households with no landline but accessible by cell phone) was 29.7% according to the 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B4 

National Health Interview Survey (NHIS) (Blumberg & Luke, 2012). Current RDD landline sampling 

procedures exclude telephone exchanges and banks of telephone numbers used exclusively for cell 

phones. This makes it difficult to reach people in subpopulations with high cell phone only usage. For 

example, almost 7 out of 10 (69.4%) adults living with unrelated roommates and over half (53.5%) of 

adults aged 25 to 29 years live in cell phone only households. These are some of the same groups that are 

increasingly under-represented in conventional RDD landline telephone surveys. As the percentage of cell 

phone only households continues to grow, the conventional RDD landline sampling model can no longer 

reliably provide adequate population coverage required for sampling the U.S. household population. To 

overcome this challenge and to account for drivers that rely solely or mostly on cell phones, this survey 

used both a RDD sample of landline phones and a RDD sample of cell phones. 

Cell Phone Households - A stratified random sample of cellular phone numbers was drawn and used to 

contact potential respondents. This was feasible because the 10 strata used in this study are defined in 

terms of States and cellular phone codes are also defined by States. However, cell phones are portable and 

some respondents could be living in States other than that indicated by their cell phone area code. To 

address this possible scenario, all cell phone respondents were asked their ZIP code. 

Two types of cell phone households were identified through screening; cell phone only households and 

cell phone mostly households. Cell phone only households do not have a landline phone. Cell phone 

mostly households have both landline and cellular telephone service (dual service) but the landline is not 

often used for receiving calls, and therefore the probability of reaching such a household through the 

landline sample is greatly diminished. Because cell phone mostly households are also included in the 

sample frame of landline households, the estimation procedures that account for the overlapping dual 

service sample are more complicated than those that use non overlapping (mutually exclusive) samples of 

cell phone only households and landline households (with or without cell phone). Indeed, most surveys 

conducted to date with cell phone samples used strictly cell phone only households. However, it was 

important to include the cell phone mostly households in the study sample for the representativeness of 

the population and to capture respondents in the critical group of 16 to 34-year-olds. 

Cell phones were treated as personal devices and only the person with the cell phone was screened for 

eligibility. The number of interviews to be achieved for these groups was derived using Cochran’s 

formula for the optimal allocation to strata when unit costs differ between the strata. 

Landline Households - A stratified sample of landline telephone numbers was drawn and potential 

respondents were contacted using conventional RDD methods. The households were screened for 

eligibility, and an eligible driver was selected for the interview. Landline respondents were not offered 

any incentives. A total of 3,872 interviews were conducted with respondents from the landline sample. 

This includes the oversample of 682 respondents 16 to 34.7

 

Table B2 shows the number of interviews from each sample type by age. Age quotas were not used 

during data collection except for the 682 person landline oversample for the 16 to 34-year-old group. 

 

7 While 782 respondents completed the landline oversample survey, only 682 met the age eligibility criterion to 

participate in the survey. The 100 respondents who completed the survey and stated that they were older than 34 

were reassigned to the main landline survey for analysis purposes.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B5 

Table B-2. Sample Size by Type and Age

Age Landline Landline 

Oversample

Cell Phone 

Sample TOTAL

16-34 302 682 925 1,909

35+ 2,812 0 1,182 3,994

Not Reported 76 0 37 113

TOTAL 3,190 682 2,144 6,016

Survey Administration 

The objective of survey administration is to conduct the data collection portion of the survey in a 

systematic, uniform, and consistent manner. Survey administration includes the cognitive testing of the 

instrument, survey procedures, monitoring of the interviews, and tracking of the sample disposition. 

Spanish Instrument Cognitive Testing 

The Spanish language questionnaire was cognitively tested among nine (9) native Spanish speakers in the 

Washington, DC area. Each respondent was interviewed individually and asked probing questions about 

the instrument such as, “What does this question mean to you?” or “Do you understand what we mean 

when we say ______?” Based on feedback from the 9 respondents the Spanish questionnaire was revised 

to ensure the Spanish-speaking respondents would understand the questions in the same way they would 

be understood by the English-speaking respondents. The English language questionnaire had been 

cognitively tested prior to the 2010 administration and due to the slight changes in the questionnaire from 

2010 to 2012, it was determined that only the Spanish language questionnaire would undergo cognitive 

testing.

Calling Protocol

The calling protocol used in this study consisted of a maximum of 13 attempts for the landline sample, 

including the oversample of drivers 16 to 34. If someone in the household was contacted on one of these 

attempts, then the overall maximum attempts for that household was 23. For the cell phone sample, the 

maximum number of attempts to reach someone was 5. If contact was made with someone, then the 

maximum number of attempts was set at 10. 

If a person selected for the sample politely refused (also known as a “soft refusal”) to participate in the 

survey, he or she was re-contacted approximately one to two weeks after the initial refusal, giving them a 

“cooling off” period before the re-contact. 

Monitoring of Telephone Interviewers

For quality control, the telephone interviews were monitored by field supervisory staff using a silent line 

and screen monitoring. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B6 

Answering Machines

The strategy for handling answering machines with a 23-call protocol has to balance the objectives of 

reaching the household and avoiding annoyance of the household. Thus, messages were left on the 

answering machine or voice mail on the fifth, seventh, and ninth calls, if an answering machine or voice 

mail was encountered on those attempts. The first answering machine message explained that the 

household had been selected as part of a U.S. DOT study of American driving habits and attitudes, and 

asked the respondent to call Abt SRBI’s toll-free number to schedule an interview. The subsequent 

answering messages also included this information. 

For cell phones voice messages were left on the first or second call if a voice mailbox was reached. The 

rationale behind this is that respondents would see the number of the call center, not recognize it, and 

therefore be more likely to screen the call and not answer their cell phone. Leaving a message early on let 

the respondent know who was calling and the purpose of the call. When we call back and the same 

number appears the respondent may be more likely to take the call since there is additional information 

pertaining to the number. 

Sample Dispositions

The final dispositions for each of the three independent samples are given in the following tables: Table 

B-3: Landline Cross-section, Table B-4: Cell Sample, and Table B-5: Landline Oversample. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B7 

Table B-3. Landline Cross-Section Final Disposition Report

Original 

Count

Estimated 

Qualified 

Household*

Estimated 

Response 

Eligible^

T1 TOTAL 54,763

A NON-Usable Numbers 38,331

A1 Not in service/Disconnected/Change# 32,627

A2 Non-residential # 3,213

A3 Computer/Fax tone 2,028

A4 Line problem 463

T2 Total Usable Numbers 16,432

B UNKNOWN ELIGIBLE HOUSEHOLD*^ 6,028 1,809 1,475

B1 Probable unassigned number 2,065

B2 No answer/Busy 1,825

B3 Answering machine 2,138

C NOT ELIGIBLE RESPONDENT^ 1,614 1,614 1,316

C1 Language barrier 350

C2 Health/Deaf 1,069

C3 Respondent away for duration 195

D UNKNOWN ELIGIBLE RESPONDENT^ 4,512 3,679

D1 Callback 958

D2 Spanish Callback not screened 1

D3 Refusals not screened 3,553

E CONTACTS SCREENED 1,088

E1 Qualified callback 83 83

E2 Refusals – Qualified 215 215

E3 Terminates 0

E4 Screen-outs 790

F COMPLETE 3,190 3,190

A' ESTIMATED ELIGIBLE HH RATE =T2/T1 30.01%

B' ELIGIBLE RESPONSE RATE = E+F-E4/(E+F) 81.53%

C' SUM RESPONSE ELIGIBLE COUNT 9,957

D' RESPONSE RATE = F/C' 32.04%

*Estimated Qualified HH=Original Count * A'

^Response Eligible = Qualified Household Count * B'
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B8 

Table B-4. Cell Phone Final Disposition Report 

Original 

Count

Estimated 

Qualified 

Household*

Estimated 

Response 

Eligible^

T1 TOTAL 43,821

A NON-Usable Numbers 16,456

A1 NIS/DIS/Change#/Intercepts 13,794

A2 Non-residential # 1,721

A3 Computer/Fax tone 110

A4 Line problem 831

T2 Total Usable Numbers 27,365

B UNKNOWN ELIGIBLE HOUSEHOLD*^ 11,786 7,360 3,649

B1 Probable unassigned number 49

B2 No answer/Busy 4,447

B3 Answering machine 7,290

C NOT ELIGIBLE RESPONDENT^ 1,912 1,912 948

C1 Language barrier 1,070

C2 Health/Deaf 607

C3 Respondent away for duration 235

D UNKNOWN ELIGIBLE RESPONDENT^ 8,370 4,149

D1 Callback 3,024

D2 Spanish Callback not screened 38

D3 Refusals not screened 5,308

E CONTACTS SCREENED 3,153

E1 Qualified callback 246 246

E2 Refusals – Qualified 236 236

E3 Terminates 0

E4 Screen-outs 2,671

F COMPLETE 2,144 2,144

A' ESTIMATED ELIGIBLE HH RATE =T2/T1 62.45%

B' ELIGIBLE RESPONSE RATE = E+F-E4/(E+F) 49.58%

C' SUM RESPONSE ELIGIBLE COUNT 11,372

D' RESPONSE RATE = F/C' 18.85%

*Estimated Qualified HH=Original Count * A'

^Response Eligible = Qualified Household Count * B'
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B9 

Table B-5. Landline Oversample Final Disposition Report

Original 

Count

Estimated 

Qualified 

Household*

Estimated 

Response 

Eligible^

T1 TOTAL 109,092

A NON-Usable Numbers 75,924

A1 NIS/DIS/Change#/Intercepts 64,579

A2 Non-residential # 6,073

A3 Computer/Fax tone 3,910

A4 Line problem 1,362

T2 Total Usable Numbers 33,168

B UNKNOWN ELIGIBLE HOUSEHOLD*^ 12,486 3,796 259

B1 Probable unassigned number 3,812

B2 No answer/Busy 4,235

B3 Answering machine 4,439

C NOT ELIGIBLE RESPONDENT^ 929 929 63

C1 Language barrier 299

C2 Health/Deaf 494

C3 Respondent away for duration 136

D UNKNOWN ELIGIBLE RESPONDENT^ 5,427 371

D1 Callback 999

D2 Spanish Callback not screened 17

D3 Refusals not screened 4,411

E CONTACTS SCREENED 13,644

E1 Qualified callback 127 127

E2 Refusals – Qualified 170 170

E3 Terminates 0

E4 Screen-outs 13,347

F COMPLETE 682 682

A' ESTIMATED ELIGIBLE HH RATE =T2/T1 30.40%

B' ELIGIBLE RESPONSE RATE = E+F-E4/(E+F) 6.83%

C' SUM RESPONSE ELIGIBLE COUNT 1,673

D' RESPONSE RATE = F/C' 40.77%

*Estimated Qualified HH=Original Count * A'

^Response Eligible = Qualified Household Count * B'
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B10 

Precision of Sample Estimates 

The confidence interval for an estimate derived 

ݖොേݕ

from the distracted driver survey sample is: 

where: 

ଵିఈ⁄ଶ

ݕො = an estimate of the population proportion; 

ඥܸܽݎሺݕොሻ

ݖ

90%

ݎܸܽ

ଵିఈ

ሺ

⁄

ොሻݕ

ଶ

ߙ

 = is the sim

ሺ1 െ ߙ

ݖ

⁄2ሻ

ple random sampling (srs) variance8

 of ; and 

 = th percentile of the standard normal distribution 

ොݕ

(95%: = 5%, = 1.96; 

: = 10%, = 1.645). 

For best results, data users should use statistical software such as SAS, SPSS, STATA or 

ߙ

SUDAAN to

ݖ

calculate the confidence intervals for a complex sampling design. However, data users can use the tables 

that follow to approximate the confidence interval based on a simple formula. 

Sampling Error 

The sampling variance for an estimate is a measure of uncertainty that reflects the fact that the estimate is 

derived from a sample drawn from the population. If one were to draw a second sample in the exact same 

manner, the estimate would be different from the first simply due to the fact that our sample contains 

different members of the population. A third sample would be different from the first two, and so on. The 

sampling variance measures how different the estimates would be had we drawn different samples. 

The sam

ߪଶ ൌ

pling error for a complex survey depends on three things, 

1. ௬ the population variance for the characteristic: the sampling variance is higher when there is a lot 

of variability in the population (large ) and lower when there is little variability in the population. 

2. n = the sample size: the sampling variance is higher 

௬ߪ

ଶ

when the sample size is small and lower when 

the sample size is large. The sampling variance for estimates of subgroups is based on the sample size 

for those subgroups. 

3. DEFF = design effect:9 Sampling design features such as stratification, clustering, dual-frame 

sampling, and surve

ܨܨܧܦ

y

ൌ

 weighting all contribute to 

	.ොሻݕሺ ݎ⁄ܸܽොሻݕሺݎܸܽ

the sampling variability. The design effect is a 

measure of inefficiency (or efficiency) of the complex sample relative to a simple random sample, 

calculated as srs

Using this r

srsݎܸܽ

populati

ሺݕොሻ ൈ ܦ

e

ܧ

lationship, 

௬ߪ 	 ൌ ܨܨ

ଶ⁄

we can writ

.ܨܨܧܦ ൈ	 ݊

e the sampling variance of the complex design as: 

 Therefore, one can calculate the sampling variance with the

on variance (or an estimate of the population variance); the sample size; and the design effect. 

ܸܽݎሺݕොሻ ൌ

                                                            

8

 A simple random sample is a sample on n units drawn directly from a population of N units. 

9 Kish, L. (1965). Survey Sampling, New York: John Wiley & Sons. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B11 

Estimating the Population Variance 

The population variance is often estimated from the survey data, 

percentages, the population variance ߪ = P×(1-P) and can be e

ݏ

sti

ଶ

m

ൌ

ated fro

ଵ

ଶ ௡ ∑௡ሺݕ௜

௬ m

ݕ െ

 the surve

തሻଶ

ݏ

. In the case of 

ଶ

y estimate 

. An alternative is to use the variance estimates based on the percent presented in Table 

B-6. Rounding the estimated percentage up to the nearest 5 percentage points (e.g., 17% to 20%, 34% to 

35%) is a conservative estimate of the population variance. The variance for a percentage is low when a 

small percentage of the po

ൌ ݌ ൈ ሺ1 െ ݌ሻ

pulation has the characteristic (or a large percentage of the population has the 

characteristic) and high when the percentage of the population with the characteristic is equal (50/50).

Estimating Design Effects 

The sampling design impacts the variance for each data item differently. Therefore the design effect for 

one survey estimate might be higher or lower than the design effect of another survey estimate. The 

design effect will also vary for different subpopulations represented in the sample, such as males and 

females. To simplify the calculations of the sampling error, design effect approximations are presented in 

Table B-6 below. These approximations are based on the average design effect for over 60 data items. 

 

̂ ̂
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B12 

Table B-6. Estimated 95% Error Margins Overall and Various Population Subgroups

P = 50, 50 45, 55 40, 60 35, 65 30, 70 25, 75 20, 80 15, 85 10, 90 5, 95

DEFF n 0.2500 0.2475 0.2400 0.2275 0.2100 0.1875 0.1600 0.1275 0.0900 0.0475

Overall 1.81 6,016 1.7% 1.7% 1.7% 1.6% 1.6% 1.5% 1.4% 1.2% 1.0% 0.7% 

Region

1 1.77 336 7.1% 7.1% 7.0% 6.8% 6.5% 6.2% 5.7% 5.1% 4.3% 3.1%

2 1.78 833 4.5% 4.5% 4.4% 4.3% 4.2% 3.9% 3.6% 3.2% 2.7% 2.0%

3 1.76 680 5.0% 5.0% 4.9% 4.8% 4.6% 4.3% 4.0% 3.6% 3.0% 2.2%

4 1.73 847 4.4% 4.4% 4.3% 4.2% 4.1% 3.8% 3.5% 3.2% 2.7% 1.9%

5 1.71 981 4.1% 4.1% 4.0% 3.9% 3.8% 3.5% 3.3% 2.9% 2.5% 1.8%

6 1.81 659 5.1% 5.1% 5.0% 4.9% 4.7% 4.4% 4.1% 3.7% 3.1% 2.2%

7 1.69 356 6.7% 6.7% 6.6% 6.4% 6.2% 5.8% 5.4% 4.8% 4.0% 2.9%

8 2.00 283 8.2% 8.2% 8.1% 7.9% 7.6% 7.1% 6.6% 5.9% 4.9% 3.6%

9 1.71 719 4.8% 4.8% 4.7% 4.6% 4.4% 4.1% 3.8% 3.4% 2.9% 2.1%

10 1.68 322 7.1% 7.1% 6.9% 6.8% 6.5% 6.1% 5.7% 5.1% 4.3% 3.1%

Frequent driver (q1=1,2)

Yes 1.80 5,091 1.8% 1.8% 1.8% 1.8% 1.7% 1.6% 1.5% 1.3% 1.1% 0.8%

No 1.82 925 4.3% 4.3% 4.3% 4.1% 4.0% 3.8% 3.5% 3.1% 2.6% 1.9%

Type of vehicle

Car 1.82 3,457 2.3% 2.2% 2.2% 2.1% 2.1% 1.9% 1.8% 1.6% 1.4% 1.0%

Van or minivan 1.73 494 5.8% 5.8% 5.7% 5.5% 5.3% 5.0% 4.6% 4.1% 3.5% 2.5%

Pick-up truck 1.74 895 4.3% 4.3% 4.2% 4.1% 4.0% 3.7% 3.5% 3.1% 2.6% 1.9%

SUV 1.75 1,042 4.0% 4.0% 3.9% 3.8% 3.7% 3.5% 3.2% 2.9% 2.4% 1.8%
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B13 

Table B-6. Estimated 95% Error Margins Overall and Various Population Subgroups (Continued)

P = 50, 50 45, 55 40, 60 35, 65 30, 70 25, 75 20, 80 15, 85 10, 90 5, 95

DEFF n 0.2500 0.2475 0.2400 0.2275 0.2100 0.1875 0.1600 0.1275 0.0900 0.0475

Gender

Male 1.79 2,889 2.4% 2.4% 2.4% 2.3% 2.2% 2.1% 1.9% 1.7% 1.5% 1.1%

Female 1.84 3,127 2.4% 2.4% 2.3% 2.3% 2.2% 2.1% 1.9% 1.7% 1.4% 1.0%

Age group

16-20 1.83 392 6.7% 6.7% 6.6% 6.4% 6.1% 5.8% 5.4% 4.8% 4.0% 2.9%

21-24 1.69 383 6.5% 6.5% 6.4% 6.2% 6.0% 5.6% 5.2% 4.6% 3.9% 2.8%

25-34 1.92 1,134 4.0% 4.0% 4.0% 3.8% 3.7% 3.5% 3.2% 2.9% 2.4% 1.8%

35-44 1.49 794 4.2% 4.2% 4.2% 4.0% 3.9% 3.7% 3.4% 3.0% 2.5% 1.8%

45-54 1.73 1,066 4.0% 3.9% 3.9% 3.8% 3.6% 3.4% 3.2% 2.8% 2.4% 1.7%

55-64 1.80 1,062 4.0% 4.0% 3.9% 3.8% 3.7% 3.5% 3.2% 2.9% 2.4% 1.8%

65+ 1.62 1,072 3.8% 3.8% 3.7% 3.6% 3.5% 3.3% 3.1% 2.7% 2.3% 1.7%
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B14 

Table B-7. Estimated 95% Error Margins for Various Sample Sizes

P = 50, 50 45, 55 40, 60 35, 65 30, 70 25, 75 20, 80 15, 85 10, 90 5, 95

DEFF n 0.2500 0.2475 0.2400 0.2275 0.2100 0.1875 0.1600 0.1275 0.0900 0.0475

1.81 6,000 1.7% 1.7% 1.7% 1.6% 1.6% 1.5% 1.4% 1.2% 1.0% 0.7% 

5,500 1.8% 1.8% 1.7% 1.7% 1.6% 1.5% 1.4% 1.3% 1.1% 0.8% 

5,000 1.9% 1.9% 1.8% 1.8% 1.7% 1.6% 1.5% 1.3% 1.1% 0.8% 

4,500 2.0% 2.0% 1.9% 1.9% 1.8% 1.7% 1.6% 1.4% 1.2% 0.9% 

4,000 2.1% 2.1% 2.0% 2.0% 1.9% 1.8% 1.7% 1.5% 1.2% 0.9% 

3,500 2.2% 2.2% 2.2% 2.1% 2.0% 1.9% 1.8% 1.6% 1.3% 1.0% 

3,000 2.4% 2.4% 2.4% 2.3% 2.2% 2.1% 1.9% 1.7% 1.4% 1.0% 

2,500 2.6% 2.6% 2.6% 2.5% 2.4% 2.3% 2.1% 1.9% 1.6% 1.1% 

2,250 2.8% 2.8% 2.7% 2.6% 2.5% 2.4% 2.2% 2.0% 1.7% 1.2% 

2,000 2.9% 2.9% 2.9% 2.8% 2.7% 2.5% 2.4% 2.1% 1.8% 1.3% 

1,750 3.1% 3.1% 3.1% 3.0% 2.9% 2.7% 2.5% 2.2% 1.9% 1.4% 

1,500 3.4% 3.4% 3.3% 3.2% 3.1% 2.9% 2.7% 2.4% 2.0% 1.5% 

1,250 3.7% 3.7% 3.6% 3.6% 3.4% 3.2% 3.0% 2.7% 2.2% 1.6% 

1,000 4.2% 4.1% 4.1% 4.0% 3.8% 3.6% 3.3% 3.0% 2.5% 1.8% 

750 4.8% 4.8% 4.7% 4.6% 4.4% 4.2% 3.8% 3.4% 2.9% 2.1% 

500 5.9% 5.9% 5.8% 5.6% 5.4% 5.1% 4.7% 4.2% 3.5% 2.6% 

400 6.6% 6.6% 6.5% 6.3% 6.0% 5.7% 5.3% 4.7% 3.9% 2.9% 

300 7.6% 7.6% 7.4% 7.3% 7.0% 6.6% 6.1% 5.4% 4.6% 3.3% 

200 9.3% 9.3% 9.1% 8.9% 8.5% 8.1% 7.4% 6.6% 5.6% 4.1% 

150 10.8% 10.7% 10.5% 10.3% 9.9% 9.3% 8.6% 7.7% 6.5% 4.7% 

100 13.2% 13.1% 12.9% 12.6% 12.1% 11.4% 10.5% 9.4% 7.9% 5.7% 

50 18.6% 18.5% 18.2% 17.8% 17.1% 16.1% 14.9% 13.3% 11.2% 8.1% 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B15 

Testing for Statistical Differences 

Sampling error is also used to determine whether two population subgroups (or domains) are significantly 

different with respect to a certain statistic, that is, the difference in the sampled subgroup estimates is 

large enough that it would be unlikely to randomly occur if the statistics were the same for the subgroups. 

Consider the hypothesis test for comparing two domains: 

H0: Y1 = Y2 or Y1 – Y2 = 0 

H1: Y1 ≠ Y2 or Y1 – Y2 ≠ 0 

One method to test whether Y1 is different from Y2 is to calculate a confidence interval around the 

difference in the sample estimates,10 . If the interval does not contain 0, 

we conclude that Y1 is different from

ݕሺ

 Y

ොଵ

2 

ݕ െ

–the observed difference in the sa

ොଶሻേݖଵିఈ⁄ଶඥܸܽݎሺݕොଵ െ ݕොଶሻ

mple estimates is not likely to 

randomly occur if Y1 was equal to Y2, therefore there is evidence to indicate a difference in the population 

ݎܸܽ

statistics.

insufficient evidence to indicate a diffe

variances are esti

differences b

ሺݕො െ ݕ

 If t

ො ሻ

he interval does not contain 0, we can

ൌ ܸܽݎሺݕො ሻ ൅ ሺݕො ሻ

not conclude that Y1 is different from Y2 – there is 

rence in the population statistics. 

ଵ ଶ ଵ , the sum of the variances for two population subgroups. The subgroup 

mated as described 

ଶ

above. Table B-8 includes the estimated 95% error margins for the 

etween subgroups of various. If the observed difference is less than or equal to the error 

margin, the difference is not statistically significant at the α = 0.05 significance level. If it is greater than 

the error margin, the difference is statistically significant at the α = 0.05 significance level. 

                                                            10 This method should only be used for large sample sizes. One rule of thumb is n1 and n2 both greater than 30. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B16 

Table B-8. Estimated 95% Error Margins For the Difference Between Two Subgroups

DEFF n1 P n2 = 6000 5000 4000 3000 2000 1500 1000 500 400 300 200 100 50

1.81 6000 50,50 2.4% 2.5% 2.7% 2.9% 3.4% 3.8% 4.5% 6.1% 6.8% 7.8% 9.5% 13.3% 18.7%

40,60 2.4% 2.5% 2.6% 2.9% 3.3% 3.7% 4.4% 6.0% 6.7% 7.6% 9.3% 13.0% 18.3%

30,70 2.2% 2.3% 2.5% 2.7% 3.1% 3.5% 4.1% 5.6% 6.2% 7.1% 8.7% 12.2% 17.2%

20,80 1.9% 2.0% 2.2% 2.4% 2.7% 3.0% 3.6% 4.9% 5.4% 6.2% 7.6% 10.6% 15.0%

10,90 1.4% 1.5% 1.6% 1.8% 2.0% 2.3% 2.7% 3.7% 4.1% 4.7% 5.7% 8.0% 11.2%

5000 50,50 2.5% 2.6% 2.8% 3.0% 3.5% 3.9% 4.6% 6.2% 6.9% 7.8% 9.5% 13.3% 18.7%

40,60 2.5% 2.6% 2.7% 3.0% 3.4% 3.8% 4.5% 6.1% 6.7% 7.7% 9.3% 13.0% 18.4%

30,70 2.3% 2.4% 2.6% 2.8% 3.2% 3.6% 4.2% 5.7% 6.3% 7.2% 8.7% 12.2% 17.2%

20,80 2.0% 2.1% 2.2% 2.4% 2.8% 3.1% 3.7% 4.9% 5.5% 6.3% 7.6% 10.7% 15.0%

10,90 1.5% 1.6% 1.7% 1.8% 2.1% 2.3% 2.7% 3.7% 4.1% 4.7% 5.7% 8.0% 11.2%

4000 50,50 2.7% 2.8% 2.9% 3.2% 3.6% 4.0% 4.7% 6.3% 6.9% 7.9% 9.6% 13.3% 18.8%

40,60 2.6% 2.7% 2.9% 3.1% 3.5% 3.9% 4.6% 6.1% 6.8% 7.7% 9.4% 13.1% 18.4%

30,70 2.5% 2.6% 2.7% 2.9% 3.3% 3.7% 4.3% 5.7% 6.3% 7.2% 8.8% 12.2% 17.2%

20,80 2.2% 2.2% 2.4% 2.5% 2.9% 3.2% 3.7% 5.0% 5.5% 6.3% 7.6% 10.7% 15.0%

10,90 1.6% 1.7% 1.8% 1.9% 2.2% 2.4% 2.8% 3.8% 4.1% 4.7% 5.7% 8.0% 11.3%

3000 50,50 2.9% 3.0% 3.2% 3.4% 3.8% 4.2% 4.8% 6.4% 7.0% 8.0% 9.6% 13.4% 18.8%

40,60 2.9% 3.0% 3.1% 3.3% 3.7% 4.1% 4.7% 6.2% 6.9% 7.8% 9.4% 13.1% 18.4%

30,70 2.7% 2.8% 2.9% 3.1% 3.5% 3.8% 4.4% 5.8% 6.4% 7.3% 8.8% 12.3% 17.2%

20,80 2.4% 2.4% 2.5% 2.7% 3.0% 3.3% 3.9% 5.1% 5.6% 6.4% 7.7% 10.7% 15.0%

10,90 1.8% 1.8% 1.9% 2.0% 2.3% 2.5% 2.9% 3.8% 4.2% 4.8% 5.8% 8.0% 11.3%

2000 50,50 3.4% 3.5% 3.6% 3.8% 4.2% 4.5% 5.1% 6.6% 7.2% 8.2% 9.8% 13.5% 18.9%

40,60 3.3% 3.4% 3.5% 3.7% 4.1% 4.4% 5.0% 6.5% 7.1% 8.0% 9.6% 13.2% 18.5%

30,70 3.1% 3.2% 3.3% 3.5% 3.8% 4.1% 4.7% 6.0% 6.6% 7.5% 9.0% 12.4% 17.3%

20,80 2.7% 2.8% 2.9% 3.0% 3.3% 3.6% 4.1% 5.3% 5.8% 6.5% 7.8% 10.8% 15.1%

10,90 2.0% 2.1% 2.2% 2.3% 2.5% 2.7% 3.1% 4.0% 4.3% 4.9% 5.9% 8.1% 11.3%

1500 50,50 3.8% 3.9% 4.0% 4.2% 4.5% 4.8% 5.4% 6.8% 7.4% 8.3% 9.9% 13.6% 19.0%

40,60 3.7% 3.8% 3.9% 4.1% 4.4% 4.7% 5.3% 6.7% 7.3% 8.2% 9.7% 13.3% 18.6%

30,70 3.5% 3.6% 3.7% 3.8% 4.1% 4.4% 4.9% 6.2% 6.8% 7.6% 9.1% 12.5% 17.4%

20,80 3.0% 3.1% 3.2% 3.3% 3.6% 3.9% 4.3% 5.4% 5.9% 6.7% 7.9% 10.9% 15.2%

10,90 2.3% 2.3% 2.4% 2.5% 2.7% 2.9% 3.2% 4.1% 4.5% 5.0% 6.0% 8.2% 11.4%
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B17 

Table B-8. Estimated 95% Error Margins For the Difference Between Two Subgroups (Continued)

DEFF n1 P n2 = 6000 5000 4000 3000 2000 1500 1000 500 400 300 200 100 50

1.81 1000 50,50 4.5% 4.6% 4.7% 4.8% 5.1% 5.4% 5.9% 7.2% 7.8% 8.7% 10.2% 13.8% 19.1%

40,60 4.4% 4.5% 4.6% 4.7% 5.0% 5.3% 5.8% 7.1% 7.6% 8.5% 10.0% 13.5% 18.7%

30,70 4.1% 4.2% 4.3% 4.4% 4.7% 4.9% 5.4% 6.6% 7.1% 8.0% 9.4% 12.7% 17.5%

20,80 3.6% 3.7% 3.7% 3.9% 4.1% 4.3% 4.7% 5.8% 6.2% 6.9% 8.2% 11.1% 15.3%

10,90 2.7% 2.7% 2.8% 2.9% 3.1% 3.2% 3.5% 4.3% 4.7% 5.2% 6.1% 8.3% 11.5%

500 50,50 6.1% 6.2% 6.3% 6.4% 6.6% 6.8% 7.2% 8.3% 8.8% 9.6% 11.0% 14.4% 19.6%

40,60 6.0% 6.1% 6.1% 6.2% 6.5% 6.7% 7.1% 8.2% 8.7% 9.4% 10.8% 14.2% 19.2%

30,70 5.6% 5.7% 5.7% 5.8% 6.0% 6.2% 6.6% 7.6% 8.1% 8.8% 10.1% 13.2% 17.9%

20,80 4.9% 4.9% 5.0% 5.1% 5.3% 5.4% 5.8% 6.7% 7.1% 7.7% 8.8% 11.6% 15.6%

10,90 3.7% 3.7% 3.8% 3.8% 4.0% 4.1% 4.3% 5.0% 5.3% 5.8% 6.6% 8.7% 11.7%

400 50,50 6.8% 6.9% 6.9% 7.0% 7.2% 7.4% 7.8% 8.8% 9.3% 10.1% 11.4% 14.7% 19.8%

40,60 6.7% 6.7% 6.8% 6.9% 7.1% 7.3% 7.6% 8.7% 9.1% 9.9% 11.2% 14.4% 19.4%

30,70 6.2% 6.3% 6.3% 6.4% 6.6% 6.8% 7.1% 8.1% 8.5% 9.2% 10.5% 13.5% 18.1%

20,80 5.4% 5.5% 5.5% 5.6% 5.8% 5.9% 6.2% 7.1% 7.5% 8.1% 9.1% 11.8% 15.8%

10,90 4.1% 4.1% 4.1% 4.2% 4.3% 4.5% 4.7% 5.3% 5.6% 6.0% 6.9% 8.8% 11.9%

300 50,50 7.8% 7.8% 7.9% 8.0% 8.2% 8.3% 8.7% 9.6% 10.1% 10.8% 12.0% 15.2% 20.1%

40,60 7.6% 7.7% 7.7% 7.8% 8.0% 8.2% 8.5% 9.4% 9.9% 10.5% 11.8% 14.9% 19.7%

30,70 7.1% 7.2% 7.2% 7.3% 7.5% 7.6% 8.0% 8.8% 9.2% 9.9% 11.0% 14.0% 18.5%

20,80 6.2% 6.3% 6.3% 6.4% 6.5% 6.7% 6.9% 7.7% 8.1% 8.6% 9.6% 12.2% 16.1%

10,90 4.7% 4.7% 4.7% 4.8% 4.9% 5.0% 5.2% 5.8% 6.0% 6.5% 7.2% 9.1% 12.1%

200 50,50 9.5% 9.5% 9.6% 9.6% 9.8% 9.9% 10.2% 11.0% 11.4% 12.0% 13.2% 16.1% 20.8%

40,60 9.3% 9.3% 9.4% 9.4% 9.6% 9.7% 10.0% 10.8% 11.2% 11.8% 12.9% 15.8% 20.4%

30,70 8.7% 8.7% 8.8% 8.8% 9.0% 9.1% 9.4% 10.1% 10.5% 11.0% 12.1% 14.8% 19.1%

20,80 7.6% 7.6% 7.6% 7.7% 7.8% 7.9% 8.2% 8.8% 9.1% 9.6% 10.5% 12.9% 16.7%

10,90 5.7% 5.7% 5.7% 5.8% 5.9% 6.0% 6.1% 6.6% 6.9% 7.2% 7.9% 9.7% 12.5%

100 50,50 13.3% 13.3% 13.3% 13.4% 13.5% 13.6% 13.8% 14.4% 14.7% 15.2% 16.1% 18.6% 22.8%

40,60 13.0% 13.0% 13.1% 13.1% 13.2% 13.3% 13.5% 14.2% 14.4% 14.9% 15.8% 18.3% 22.4%

30,70 12.2% 12.2% 12.2% 12.3% 12.4% 12.5% 12.7% 13.2% 13.5% 14.0% 14.8% 17.1% 20.9%

20,80 10.6% 10.7% 10.7% 10.7% 10.8% 10.9% 11.1% 11.6% 11.8% 12.2% 12.9% 14.9% 18.3%

10,90 8.0% 8.0% 8.0% 8.0% 8.1% 8.2% 8.3% 8.7% 8.8% 9.1% 9.7% 11.2% 13.7%
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B18 

Table B-8. Estimated 95% Error Margins For the Difference Between Two Subgroups (Continued)

DEFF n1 P n2 = 6000 5000 4000 3000 2000 1500 1000 500 400 300 200 100 50

1.81 50 50,50 18.7% 18.7% 18.8% 18.8% 18.9% 19.0% 19.1% 19.6% 19.8% 20.1% 20.8% 22.8% 26.4%

40,60 18.3% 18.4% 18.4% 18.4% 18.5% 18.6% 18.7% 19.2% 19.4% 19.7% 20.4% 22.4% 25.8%

30,70 17.2% 17.2% 17.2% 17.2% 17.3% 17.4% 17.5% 17.9% 18.1% 18.5% 19.1% 20.9% 24.2%

20,80 15.0% 15.0% 15.0% 15.0% 15.1% 15.2% 15.3% 15.6% 15.8% 16.1% 16.7% 18.3% 21.1%

10,90 11.2% 11.2% 11.3% 11.3% 11.3% 11.4% 11.5% 11.7% 11.9% 12.1% 12.5% 13.7% 15.8%
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B19 

Weighting Methodology 

Weights were calculated for the 6,016 completed interviews with people 16 and older residing in 

households in the United States (50 States and the District of Columbia). The population weights 

(DD_FINAL_POP_WT) sum to the December 2011 Census Bureau population estimate of 242,093,969 

people 16 and older in the civilian noninstitutionalized population of the United States A sample weight 

(DD_FINAL_SAMP_WT) was also created. The sample weights sum to 6,016 completed interviews. 

SAS variable names are capitalized.

Base Sampling Weight

The overall random-digit-dialing sample consisted of three components (FPROJ). The first component 

(Landline Sample) was a NHTSA Region-stratified sample of landline telephone numbers. One person 

age 16 years and older was randomly selected from the households. The second component (Landline 

Screening Sample) was a NHTSA Region-stratified screening sample of landline telephone numbers. One 

person 16 to 34 years and older was randomly selected from the households with one or more age-eligible 

people. The third component (Cellular Sample) was a NHTSA Region-stratified sample of cellular 

telephone numbers. The cellular telephone was treated as a personal communication device and therefore 

an interview was attempted if the person was 16 or older. To be eligible for the interview the person also 

needed to be classified as cell-only individual or a cell-mostly individual. Cell-mostly people were 

defined as also having a landline telephone but “all or almost all calls are received on cell phones.” 

For each sample component a base sampling weight (BSW) was calculated for each NHTSA Region 

(XREGION). The base sampling weight equals the population count of telephone numbers in the NHTSA 

Region divided by the sample size of telephone numbers drawn from that NHTSA Region and released 

for interview attempts (see Table B-6).

Table B-9. Base Sampling Weights (BSW) by Sample Component 

NHTSA Region Landline Sample Landline Screening 

Sample Cellular Sample

1 5,204.71 2,632.63 9,868.48

2 5,186.19 2,598.74 9,872.69

3 5,205.28 2,607.62 9,931.47

4 5,225.54 2,613.10 9,918.51

5 5,209.94 2,591.44 9,879.75

6 5,238.33 2,614.55 9,869.05

7 5,228.13 2,632.14 9,893.85

8 5,228.10 2,623.25 9,864.53

9 5,181.01 2,599.00 9,849.48

10 5,168.47 2,614.92 9,956.98

The two landline sample components result in an oversampling of people 16 to 34 years relative to people 

35 and older. This was accounted for in the weight calculations by adjusting downwards the weights of 

people 16 to 34. The sum of the base sampling weights of all people 16 to 34 in the landline sample was 

calculated (1,593,077). The sum of the base sampling weights of all people 16 to 34 in the landline 

sample and the landline screening sample was also calculated (3,386,699). The base sampling weights of 

people 16 to 34 in the two landline sample components were multiplied by the resulting ratio of 0.47039 

to form the adjusted base sampling weight (BSW_ADJ). The adjusted base sampling weight for people 35 

and older equals the base sampling weight. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B20 

Landline sample and landline screening sample people residing in households with two or more landline 

telephone numbers has a higher probability of selection compared to people living in households with one 

landline telephone number. The adjusted base sampling weight was divided by two if the person reported 

that their household had two or more landline telephone numbers (Q24F_R) to form the base sampling 

weight adjusted for multiple landline telephones (BSW_NUMPHONE). For landline and landline 

screening sample people with one landline telephone number and for cell phone sample people the base 

sampling weight adjusted for multiple landline telephones equals the adjusted base sampling weight.

The final step in the base sampling weight calculation process was to account for the random selection of 

one person 16 and older (NUM_16PLUS_R) from the landline sample and one person 16 to 34 

(QSO1_R) from the landline screening sample. The base sampling weight adjusted for multiple landline 

telephones was multiplied by the number of eligible people in the household to form the base sampling 

weight adjusted for within household sampling (BSW_NUMADULT). For people in the cell phone 

sample the base sampling weight adjusted for within household sampling equals the base sampling weight 

adjusted for multiple landline telephones.

Interview Nonresponse Adjustment

Some age-eligible sampled people did not complete the interview. For each of the three sample 

components it was possible to classify sample people as interview respondents versus interview 

nonrespondents (ELIG). One can calculate an interview nonresponse adjustment for a given sample 

component by calculating the ratio of the sample count of respondents and nonrespondents to the sample 

count of respondents. The reciprocal of this ratio is the interview response rate.

We took advantage of sampling frame variables to calculate the interview nonresponse adjustment for 

each sample component by NHTSA Region (XREGION), and NHTSA Region by directory-listed

residential status (XSTATUS) for the landline sample (see Table B-7). Directory-listed residential status 

was available for the landline sample. Past research has demonstrated that directory-listed (i.e., White 

Pages) households are generally more likely to respond to a survey than households that do not have a 

directory listed telephone number (Camburn et al., 1995) and we found that to also hold for this landline 

sample.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B21 

Table B-10. Interview Nonresponse Adjustment Factors

Sample Component Nonresponse Adjustment Cell Nonresponse 

Adjustment Factor

Cell Phone Sample NHTSA Region 1 1.43590

Cell Phone Sample NHTSA Region 2 1.62609

Cell Phone Sample NHTSA Region 3 1.27311

Cell Phone Sample NHTSA Region 4 1.46687

Cell Phone Sample NHTSA Region 5 1.35613

Cell Phone Sample NHTSA Region 6 1.35135

Cell Phone Sample NHTSA Region 7 1.18056

Cell Phone Sample NHTSA Region 8 1.29703

Cell Phone Sample NHTSA Region 9 1.52290

Cell Phone Sample NHTSA Region 10 1.19643

Landline Screening Sample NHTSA Region 1 1.54286

Landline Screening Sample NHTSA Region 2 1.52419

Landline Screening Sample NHTSA Region 3 1.43478

Landline Screening Sample NHTSA Region 4 1.36986

Landline Screening Sample NHTSA Region 5 1.29688

Landline Screening Sample NHTSA Region 6 1.31579

Landline Screening Sample NHTSA Region 7 1.25641

Landline Screening Sample NHTSA Region 8 1.12821

Landline Screening Sample NHTSA Region 9 1.49398

Landline Screening Sample NHTSA Region 10 1.22857

Landline Sample NHTSA Region 1, Directory Listed 1.19018

Landline Sample NHTSA Region 1, Not Directory Listed 1.22449

Landline Sample NHTSA Region 2, Directory Listed 1.29392

Landline Sample NHTSA Region 2, Not Directory Listed 1.50898

Landline Sample NHTSA Region 3, Directory Listed 1.23616

Landline Sample NHTSA Region 3, Not Directory Listed 1.26882

Landline Sample NHTSA Region 4, Directory Listed 1.28803

Landline Sample NHTSA Region 4, Not Directory Listed 1.35897

Landline Sample NHTSA Region 5, Directory Listed 1.35083

Landline Sample NHTSA Region 5, Not Directory Listed 1.41803

Landline Sample NHTSA Region 6, Directory Listed 1.33333

Landline Sample NHTSA Region 6, Not Directory Listed 1.31915

Landline Sample NHTSA Region 7, Directory Listed 1.17600

Landline Sample NHTSA Region 7, Not Directory Listed 1.28889

Landline Sample NHTSA Region 8, Directory Listed 1.19318

Landline Sample NHTSA Region 8, Not Directory Listed 1.34000

Landline Sample NHTSA Region 9, Directory Listed 1.27149

Landline Sample NHTSA Region 9, Not Directory Listed 1.42254

Landline Sample NHTSA Region 10, Directory Listed 1.15323

Landline Sample NHTSA Region 10, Not Directory Listed 1.25000

The interview nonresponse adjusted base sampling weight (NRA_BSW) equals the base sampling

weight adjusted for within household sampling times the nonresponse adjustment factor.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B22 

Combining the Two Landline Samples With the Cell Phone Sample

All respondents were classified into one of 5 telephone service categories (I_TELEPHONE_STATUS_2): 

1. Cell-only 

2. Landline only 

3. Cell phone sample, dual user, cell-mostly

4. Landline samples, dual user, cell-mostly

5. Landline samples, dual user, not cell-mostly

The two landline samples cannot be simply combined with the cell phone sample because dual user 

(landline and cell phone) people who are classified as cell-mostly can be sampled through the two 

landline samples or through the cell phone sample. This is referred to as a partial overlap dual frame 

design because dual user people who are not cell-mostly were sampled just through the two landline 

samples. 

The samples were combined by compositing the cell-mostly people from the landline samples with the 

cell-mostly respondents from the cell phone sample. The compositing factor, λ, was calculated using the 

effective sample sizes for the two cell-mostly samples (see Table B-8). This process involved three steps. 

First, the design effect due to unequal weighting was calculated for each of the two telephone service 

groups. The design effect equals one plus the square of the coefficient of variation of the nonresponse 

adjusted base sampling weight. Second, the effective sample size for each of the two telephone service 

groups equals the sample size of completed interviews for the telephone service group divided by the 

design effect due to unequal weighting for that telephone service group. Third, the compositing factor for 

each of the two telephone service groups equals the effective sample size for the telephone service group 

divided by the total effective sample size (555.3 + 772.0 = 1,327.3). The two compositing factors sum to 

one. 

Table B-11. Compositing Factors

Telephone Service 

Group

Sample Size of 

Completed 

Interviews 

Design Effect Due 

to Unequal 

Weighting

Effective Sample 

Size

Compositing 

Factor (λ)

3. Cell phone 

sample, dual user, 

cell-mostly 560 1.008 555.3 0.4184

4. Landline 

samples, dual user, 

cell-mostly 982 1.272 772.0 0.5816

For the above two telephone service groups the composite weight (BSW_COMPOSITE) equals interview 

nonresponse adjusted base sampling weight times the compositing factor. For the other three telephone 

service groups the composite weight equals the interview nonresponse adjusted base sampling weight.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B23 

Raking to Population Control Totals 

A survey sample may cover segments of the target population in proportions that do not match the 

proportions of those segments in the population itself. The differences may arise, for example, from 

sampling fluctuations, from nonresponse, or because the sample design was not able to cover the entire 

target population. In such situations one can often improve the relation between the sample and the 

population by adjusting the sampling weights of the cases in the sample so that the marginal totals of the 

adjusted weights on specified characteristics, referred to as control variables, agree with the 

corresponding totals for the population. This operation is known as raking ratio estimation, raking, or 

sample-balancing, and the population totals are usually referred to as control totals. Raking is most often 

used to reduce biases from nonresponse and noncoverage in sample surveys. 

Raking usually proceeds one variable at a time, applying a proportional adjustment to the weights of the 

cases that belong to the same category of the control variable. The initial design weights in the raking 

process are often equal to the inverse of the selection probabilities and may have undergone some 

adjustments for unit nonresponse and noncoverage. The weights from the raking process are used in 

estimation and analysis. 

The adjustment to control totals is sometimes achieved by creating a cross-classification of the categorical 

control variables (e.g., age categories × gender × race × household-income categories) and then matching 

the total of the weights in each cell to the control total. This approach, however, can spread the sample 

thinly over a large number of adjustment cells. It also requires control totals for all cells of the crossclassification. Often this is not feasible (e.g., control totals may be available for age × gender × race but 

not when those cells are subdivided by household income). The use of raking with marginal control totals 

for single variables (i.e., each margin involves only one control variable) often avoids many of these 

difficulties.

The procedure known as raking adjusts a set of data so that its marginal totals match control totals on a 

specified set of variables. The term “raking” suggests an analogy with the process of smoothing the soil in 

a garden plot by alternately working it back and forth with a rake in two perpendicular directions. 

In a simple 2-variable example the marginal totals in various categories for the two control variables are 

known from the entire population, but the joint distribution of the two variables is known only from a 

sample. In the cross-classification of the sample, arranged in rows and columns, one might begin with the 

rows, taking each row in turn and multiplying each entry in the row by the ratio of the population total to 

the weighted sample total for that category, so that the row totals of the adjusted data agree with the 

population totals for that variable. The weighted column totals of the adjusted data, however, may not yet 

agree with the population totals for the column variable. Thus the next step, taking each column in turn, 

multiplies each entry in the column by the ratio of the population total to the current total for that 

category. Now the weighted column totals of the adjusted data agree with the population totals for that 

variable, but the new weighted row totals may no longer match the corresponding population totals. 

This process continues, alternating between the rows and the columns, and close agreement on both rows 

and columns is usually achieved after a small number of iterations. The result is a tabulation for the 

population that reflects the relation of the two control variables in the sample. Raking can also adjust a set 

of data to control totals on three or more variables. In such situations the control totals often involve 

single variables, but they may involve two or more variables. 

Ideally, one should rake on variables that exhibit an association with the key survey outcome variables 

and that are related to nonresponse and/or noncoverage. This strategy will reduce bias in the key outcome 

variables. In practice, other considerations may enter. A variable such as gender may not be strongly 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B24 

related to key outcome variables or to nonresponse, but raking on it may be desirable to preserve the “face 

validity” of the sample. For more details on raking survey data see Battaglia et al. (2009).

Eight control variables were used in the raking:

1. Telephone service using 4 categories (I_TELEPHONE_STATUS_2_R) 

2. NHTSA Region (XREGION)

3. Number of people 16 and older in the household (NUM_16PLUS_R) 

4. Number of people 0 to 15 years old in the household (I_Q24B_R) 

5. Home ownership status (I_Q24E1_R)

6. Education (I_Q24E_R)

7. Race/ethnicity (I_RACE_ETHNICITY_R)

8. Age group by gender (I_Q24_R_QSA3) 

The control totals were obtained for people 16 and older living in households from the 2010 American 

Community Survey PUMS. The telephone service control totals were constructed from information 

published by the National Center for Health Statistics (Blumberg & Luke, 2012). The control totals for 

each variable were ratio-adjusted to sum to the December 2011 Census Bureau population estimate of 

242,093,969 people 16 and older in the civilian noninstutionalized population of the United States. 

The IGCV SAS raking macro (Izrael et al., 2009) was used calculate the final weights for the combined 

(landline and cell phone) sample. The population control totals and weighted sample distributions prior to 

raking are shown in Table 4 (see Weighted Distribution Prior to Raking, Iteration 0). The raking macro 

was set to a maximum of 100 iterations and a convergence criterion of a maximum difference of 0.05 

percentage points between a control total percent and the corresponding weighted sample percent.

The IGCV raking macro used weight trimming during the raking iteration to help avoid extreme weights. 

The raking used the four trimming parameters shown below. Izrael et al. (2009) discuss weight trimming 

during raking and provide details on IGCV weight trimming procedures. Basically, the approach used 

decreases high weight values by not allowing weight values to exceed the respondent’s 

BSW_COMPOSITE weight times factor A. The approach used also decreased high weight values by not 

allowing weight values to exceed the mean BSW_COMPOSITE weight times factor C. The weight

trimming also avoided the situation where respondents end up with very small weights by not allowing 

weight values to be lower than the respondent’s BSW_COMPOSITE times factor B. The approach used 

also increased low weight values by not allowing weight values to be below the mean 

BSW_COMPOSITE weights times factor D. 

IGCV weight trimming values:

A = 4.0 /* weight will be decreased to individual weight times A */ 

B = 0.25 /* weight will be increased to individual weight times B */ 

C = 6.0 /* weight will be decreased to mean weight times C */

D = 0.167 /* weight will be increased to mean weight times D */ 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

B25 

Appendix B References

Battaglia, M., Izrael, D., Hoaglin, D., & Frankel, M. (2009, April). Practical considerations in raking 

Survey data. Survey Practice. Retrieved 

from http://surveypractice.wordpress.com/2009/06/29/raking-survey-data/ 

Blumberg, S. J., & Luke, J. V. (2012). Wireless substitution: Early release of estimates from the National 

Health Interview Survey, July – December 2011. Retrieved 

from www.cdc.gov/nchs/data/nhis/earlyrelease/wireless201206.pdf 

Camburn, D. P., Lavrakas, P. J., Battaglia, M. P., Massey, J. T., & Wright, R. A. (1995). Using advance 

letters in random-digit-dialing telephone surveys. 1995 Proceedings of the Section on Survey 

Research Methods (pp. 969-974). American Statistical Association. 

Izrael, D., Battaglia, M., & Frankel, M. (2009). SAS Raking Macro. Available 

from http://abtassociates.com/Expertise/Surveys-and-Data-Collection/Raking-Survey-Data-(a-ka--Sample-Balancing).aspx

Kish, L. (1965). Survey Sampling. New York: John Wiley & Sons. 
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

C1 

APPENDIX C

Output for Raking With Trimming Weight by 

Individual and Global Cap Value Method
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

C2 

The raking output is shown in the Table - Weighted Distribution After Raking.

Raking Results

RAKING WITH TRIMMING WEIGHT BY INDIVIDUAL AND GLOBAL CAP VALUE (IGCV) METHOD

Sample size of completed interviews 6,016

Raking input weight (adjusted to population total) BSW_COMPOSITE

Minimum value of raking input weight 2265.74

Maximum value of raking input weight 89846.35

Coefficient of variation of raking input weight 0.61

Global low weight cap value factor: Mean input weight times - (D) 0.167

Global high weight cap value factor: Mean input weight times - (C) 6.0

Individual low weight cap value (ILCV) factor: Respondent's weight times - (B) 0.25

Individual high weight cap value (IHCV) factor: Respondent's weight times - (A) 4

The FREQ Procedure

WEIGHTED DISTRIBUTION PRIOR TO RAKING. (ITERATION 0)

I_TELEPHONE_STATUS_2_R

Input Weight 

Sum of 

Weights11

Population 

Total12

Sum of 

Weights 

Difference13

% of 

Input 

Weights14Population 

%15

Difference 

in %16

1 cell only 121651755.7 79721544 41930211.70 50.250 32.930 17.320

2 landline only 8552619.36 20965338 -12412718.4 3.533 8.660 -5.127

3 cell/landline sample dual users cell mostly 32599397.75 42269607 -9670209.24 13.466 17.460 -3.994

6 landline sample dual users not cell mostly 79290196.20 99137480 -19847284.1 32.752 40.950 -8.198

 

11 Weighted count of adults based on BSW_COMPOSITE. 12 Population count of adults based on American Community Survey. 13 Input weight sum of weights minus population total. 14 Weighted percent of adults based on BSW_COMPOSITE. 15 Population percent of adults based on American Community Survey. 16 % of input weights minus population %.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

C3 

The FREQ Procedure

REGION 

Input Weight 

Sum of 

Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Input 

Weights

Population 

%

Difference 

in %

1 NHTSA Region 1 11788948.68 11498562 290387.09 4.870 4.750 0.120

2 NHTSA Region 2 33199801.79 32524501 675300.91 13.714 13.435 0.279

3 NHTSA Region 3 25451987.85 24447771 1004216.82 10.513 10.098 0.415

4 NHTSA Region 4 37381859.88 35126764 2255096.37 15.441 14.510 0.931

5 NHTSA Region 5 40415626.74 40554396 -138769.71 16.694 16.752 -0.057

6 NHTSA Region 6 28482848.18 29303910 -821061.85 11.765 12.104 -0.339

7 NHTSA Region 7 13751759.58 12942059 809700.57 5.680 5.346 0.334

8 NHTSA Region 8 10226846.65 9660108 566738.31 4.224 3.990 0.234

9 NHTSA Region 9 29946763.45 35123726 -5176963.00 12.370 14.508 -2.138

10 NHTSA Region 10 11447526.19 10912172 535354.49 4.729 4.507 0.221

The FREQ Procedure

Number of persons 16+ in HH

Input Weight 

Sum of 

Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Input 

Weights

Population 

%

Difference 

in %

1 Person 16+ in HH 74977805.35 37505709 37472096.21 30.971 15.492 15.478

2 Persons 16+ in HH 108387723.3 117123793 -8736069.47 44.771 48.379 -3.609

3 Persons 16+ in HH 34287972.08 49335012 -15047040.2 14.163 20.378 -6.215

4+ Persons 16+ in HH 24440468.29 38129455 -13688986.5 10.095 15.750 -5.654

The FREQ Procedure

Imputed value of Q24B : Number of persons in 

HH under 16 years

Input Weight 

Sum of 

Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Input 

Weights

Population 

%

Difference 

in %

1 0 Children under 16 in HH 162356500.5 157964058 4392442.26 67.063 65.249 1.814

2 1 Child under 16 in HH 36989111.36 38612796 -1623684.79 15.279 15.950 -0.671

3 2 Children under 16 in HH 28978271.63 29007247 -28975.46 11.970 11.982 -0.012

4 3+ Children under 16 in HH 13770085.47 16509867 -2739782.01 5.688 6.820 -1.132

The FREQ Procedure

Imputed value of Q24E1 : Tenure

Input Weight 

Sum of 

Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Input 

Weights

Population 

%

Difference 

in %

1 Own 153873777.3 166230650 -12356873.0 63.560 68.664 -5.104

2 Rent 88220191.69 75863319 12356873.00 36.440 31.336 5.104
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

C4 

The FREQ Procedure

Imputed value of Q24E : Education

Input Weight 

Sum of 

Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Input 

Weights

Population 

%

Difference 

in %

1 Less than HS 21313941.82 41985786 -20671843.8 8.804 17.343 -8.539

2 HS/GED 68274183.60 66849482 1424702.05 28.202 27.613 0.588

3 Some college 58616390.92 71652752 -13036361.2 24.212 29.597 -5.385

4 College graduate 93889452.66 61605950 32283503.0

5

38.782 25.447 13.335

The FREQ Procedure

Imputed value : Race Ethnicity

Input Weight 

Sum of 

Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Input 

Weights

Population 

%

Difference 

in %

1 Hispanic 30954545.12 35342925 -4388379.84 12.786 14.599 -1.813

2 White Nonhispanic 168672122.6 161436752 7235370.11 69.672 66.684 2.989

3 Black Nonhispanic 20625808.44 27879936 -7254127.51 8.520 11.516 -2.996

4 Asian/NHOPI Nonhispanic 9554626.39 12094157 -2539530.65 3.947 4.996 -1.049

5 AI/AN Nonhispanic 3478811.82 1531178 1947633.76 1.437 0.632 0.804

6 Other/Multiracial Nonhispanic 8808054.63 3809020 4999034.13 3.638 1.573 2.065

The FREQ Procedure

Age group by Gender

Input Weight Sum 

of Weights

Population 

Total

Sum of Weights 

Difference

% of Input 

Weights

Population 

%

Difference 

in %

11 16-24, Male 17861071.74 18793464 -932392.17 7.378 7.763 -0.385

12 16-24, Female 14028602.50 18256925 -4228322.33 5.795 7.541 -1.747

21 25-29, Male 13013213.06 10292008 2721205.15 5.375 4.251 1.124

22 25-29, Female 9089586.55 10577641 -1488054.44 3.755 4.369 -0.615

31 30-34, Male 10073154.84 9855219 217936.15 4.161 4.071 0.090

32 30-34, Female 10135005.35 10177155 -42149.50 4.186 4.204 -0.017

41 35-39, Male 9550390.90 9989841 -439450.43 3.945 4.126 -0.182

42 35-39, Female 8209992.93 10394638 -2184644.90 3.391 4.294 -0.902

51 40-49, Male 22746131.20 21581222 1164909.28 9.396 8.914 0.481

52 40-49, Female 18611664.16 22501190 -3889526.21 7.688 9.294 -1.607

61 50-59, Male 22372514.95 20526706 1845809.22 9.241 8.479 0.762

62 50-59, Female 26145607.68 21909400 4236207.21 10.800 9.050 1.750

71 60-69, Male 17344861.11 14213132 3131729.42 7.165 5.871 1.294

72 60-69, Female 17711446.08 15794147 1917298.86 7.316 6.524 0.792

81 70+ , Male 10311029.18 11449643 -1138614.25 4.259 4.729 -0.470

82 70+ , Female 14889696.76 15781638 -891941.07 6.150 6.519 -0.368

**** Program terminated at iteration 8 because all current percents differ from target percents by less than 0.05 ****
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

C5 

The FREQ Procedure

WEIGHTED DISTRIBUTION AFTER RAKING

I_TELEPHONE_STATUS_2_R

Output 

Weight Sum 

of Weights17

Population 

Total18

Sum of 

Weights 

Difference19

% of 

Output 

Weights20Population 

%21

Difference 

in %22

1 cell only 79738802.48 79721544 17258.49 32.937 32.930 0.007

2 landline only 20936197.84 20965338 -29139.88 8.648 8.660 -0.012

3 cell/landline sample dual users cell mostly 42288670.83 42269607 19063.84 17.468 17.460 0.008

6 landline sample dual users not cell mostly 99130297.85 99137480 -7182.46 40.947 40.950 -0.003

Weighted Distribution After Raking

The FREQ Procedure

REGION 

Output 

Weight Sum 

of Weights

Population 

Total

Sum of 

Weights

Difference

% of 

Output 

Weights

Population 

%

Difference 

in %

1 NHTSA Region 1 11498000.02 11498562 -561.58 4.749 4.750 -0.000

2 NHTSA Region 2 32522418.68 32524501 -2082.20 13.434 13.435 -0.001

3 NHTSA Region 3 24451455.69 24447771 3684.66 10.100 10.098 0.002

4 NHTSA Region 4 35131406.38 35126764 4642.88 14.511 14.510 0.002

5 NHTSA Region 5 40568228.01 40554396 13831.56 16.757 16.752 0.006

6 NHTSA Region 6 29306365.68 29303910 2455.65 12.105 12.104 0.001

7 NHTSA Region 7 12944929.38 12942059 2870.36 5.347 5.346 0.001

8 NHTSA Region 8 9658818.78 9660108 -1289.56 3.990 3.990 -0.001

9 NHTSA Region 9 35103306.89 35123726 -20419.56 14.500 14.508 -0.008

10 NHTSA Region 10 10909039.51 10912172 -3132.20 4.506 4.507 -0.001

The FREQ Procedure

Number of persons 16+ in HH

Output 

Weight Sum 

of Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Output 

Weights

Population 

%

Difference 

in %

1 Person 16+ in HH 37512064.26 37505709 6355.12 15.495 15.492 0.003

2 Persons 16+ in HH 117137715.6 117123793 13922.82 48.385 48.379 0.006

3 Persons 16+ in HH 49327285.31 49335012 -7727.00 20.375 20.378 -0.003

4+ Persons 16+ in HH 38116903.86 38129455 -12550.95 15.745 15.750 -0.005

 

17 Weighted count of adults based on raked (output) weight. 18 Population count of adults based on American Community Survey. 19 Output weight sum of weights minus population total. 20 Weighted percent of adults based on raked (output) weight. 21 Population percent of adults based on American Community Survey. 22 % of output weights minus population %.
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

C6 

The FREQ Procedure

Imputed value of Q24B : Number of persons in 

HH under 16 years

Output 

Weight Sum 

of Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Output 

Weights

Population 

%

Difference 

in %

1 0 Children under 16 in HH 157893067.6 157964058 -70990.72 65.220 65.249 -0.029

2 1 Child under 16 in HH 38637761.72 38612796 24965.57 15.960 15.950 0.010

3 2 Children under 16 in HH 29040197.53 29007247 32950.44 11.995 11.982 0.014

4 3+ Children under 16 in HH 16522942.20 16509867 13074.72 6.825 6.820 0.005

The FREQ Procedure

Imputed value of Q24E1 : Tenure

Output 

Weight Sum 

of Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Output 

Weights

Population 

%

Difference 

in %

1 Own 166147943.9 166230650 -82706.40 68.630 68.664 -0.034

2 Rent 75946025.10 75863319 82706.40 31.370 31.336 0.034

The FREQ Procedure

Imputed value of Q24E : Education

Output 

Weight Sum 

of Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Output 

Weights

Population 

%

Difference 

in %

1 Less than HS 41973965.37 41985786 -11820.30 17.338 17.343 -0.005

2 HS/GED 66844737.52 66849482 -4744.03 27.611 27.613 -0.002

3 Some college 71662042.56 71652752 9290.39 29.601 29.597 0.004

4 College graduate 61613223.55 61605950 7273.93 25.450 25.447 0.003

The FREQ Procedure

Imputed value : Race Ethnicity

Output 

Weight Sum 

of Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Output 

Weights

Population 

%

Difference 

in %

1 Hispanic 35368929.51 35342925 26004.56 14.610 14.599 0.011

2 White Nonhispanic 161394634.5 161436752 -42118.04 66.666 66.684 -0.017

3 Black Nonhispanic 27881090.57 27879936 1154.63 11.517 11.516 0.000

4 Asian/NHOPI Nonhispanic 12107406.28 12094157 13249.24 5.001 4.996 0.005

5 AI/AN Nonhispanic 1531595.24 1531178 417.18 0.633 0.632 0.000

6 Other/Multiracial Nonhispanic 3810312.94 3809020 1292.44 1.574 1.573 0.001
National Survey on Distracted Driving Attitudes and Behaviors – 2012 

C7 

The FREQ Procedure

Agegroup by Gender

Output 

Weight Sum 

of Weights

Population 

Total

Sum of 

Weights 

Difference

% of 

Output 

Weights

Population 

%

Difference 

in %

11 16-24, Male 18793463.91 18793464 0.00 7.763 7.763 0.000

12 16-24, Female 18256924.83 18256925 0.00 7.541 7.541 0.000

21 25-29, Male 10292007.90 10292008 0.00 4.251 4.251 0.000

22 25-29, Female 10577640.99 10577641 0.00 4.369 4.369 0.000

31 30-34, Male 9855218.68 9855219 0.00 4.071 4.071 0.000

32 30-34, Female 10177154.85 10177155 0.00 4.204 4.204 0.000

41 35-39, Male 9989841.33 9989841 -0.00 4.126 4.126 -0.000

42 35-39, Female 10394637.83 10394638 0.00 4.294 4.294 0.000

51 40-49, Male 21581221.92 21581222 -0.00 8.914 8.914 -0.000

52 40-49, Female 22501190.37 22501190 0.00 9.294 9.294 0.000

61 50-59, Male 20526705.73 20526706 0.00 8.479 8.479 0.000

62 50-59, Female 21909400.47 21909400 -0.00 9.050 9.050 -0.000

71 60-69, Male 14213131.68 14213132 -0.00 5.871 5.871 -0.000

72 60-69, Female 15794147.22 15794147 0.00 6.524 6.524 0.000

81 70+ , Male 11449643.44 11449643 0.00 4.729 4.729 0.000

82 70+ , Female 15781637.83 15781638 -0.00 6.519 6.519 -0.000

The UNIVARIATE Procedure

Weight Variable

Mean 

Weight

Minimum 

Weight

Maximum 

Weight

Coefficient of 

Variation

BSW_COMPOSITE 40,241.68 2,65.74 89,846.35 0.607

DD_FINAL_POP_WT 40,241.68 6,720.36 241,450.36 0.865

Number of Respondents Who Had Their Weights Decreased by the Trimming: 388. 

Number of Respondents Who Had Their Weights Increased by the Trimming: 1,071. 

Raking output weight: DD_FINAL_POP_WT 
DOT HS 811 729

April 2013

9380-040413-v5