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107 Texting and Driving Essay Topic Ideas & Examples

Inside This Article

Texting and driving is a dangerous combination that has become a major issue on the roads today. According to the National Highway Traffic Safety Administration, texting while driving is six times more dangerous than driving drunk. Despite the risks, many drivers continue to engage in this dangerous behavior, putting themselves and others at risk.

If you have been tasked with writing an essay on texting and driving, you may be struggling to come up with a topic. To help you get started, here are 107 texting and driving essay topic ideas and examples:

The dangers of texting and driving
The statistics on texting and driving accidents
The psychological effects of texting and driving
The legal consequences of texting and driving
The impact of texting and driving on society
The role of technology in preventing texting and driving
The effectiveness of texting and driving laws
The influence of peer pressure on texting and driving
The impact of distracted driving on insurance rates
The relationship between texting and driving and other risky behaviors
The role of education in preventing texting and driving
The impact of distracted driving on emergency response times
The effects of texting and driving on cognitive function
The correlation between texting and driving and car accidents
The role of social media in promoting safe driving habits
The impact of distracted driving on workplace productivity
The relationship between texting and driving and mental health
The effects of texting and driving on personal relationships
The role of parents in preventing texting and driving
The impact of distracted driving on pedestrian safety
The correlation between texting and driving and road rage
The relationship between texting and driving and substance abuse
The effects of texting and driving on sleep patterns
The role of technology in detecting and preventing texting and driving
The impact of distracted driving on academic performance
The correlation between texting and driving and anxiety
The relationship between texting and driving and self-esteem
The effects of texting and driving on decision-making skills
The role of law enforcement in preventing texting and driving
The impact of distracted driving on job prospects
The correlation between texting and driving and depression
The relationship between texting and driving and eating disorders
The effects of texting and driving on memory retention
The role of healthcare providers in preventing texting and driving
The impact of distracted driving on financial stability
The correlation between texting and driving and physical health
The relationship between texting and driving and emotional well-being
The effects of texting and driving on social skills
The role of government agencies in preventing texting and driving
The impact of distracted driving on community safety
The correlation between texting and driving and social isolation
The relationship between texting and driving and substance use disorders
The effects of texting and driving on decision-making processes
The role of technology companies in preventing texting and driving
The impact of distracted driving on family dynamics
The correlation between texting and driving and learning disabilities
The relationship between texting and driving and physical fitness
The effects of texting and driving on problem-solving abilities
The role of media in preventing texting and driving
The impact of distracted driving on stress levels
The correlation between texting and driving and communication skills
The relationship between texting and driving and time management
The effects of texting and driving on creativity
The role of advocacy groups in preventing texting and driving
The impact of distracted driving on personal development
The correlation between texting and driving and career advancement
The relationship between texting and driving and academic success
The effects of texting and driving on physical coordination
The role of technology addiction in preventing texting and driving
The impact of distracted driving on mental acuity
The correlation between texting and driving and emotional intelligence
The relationship between texting and driving and problem-solving skills
The effects of texting and driving on decision-making abilities
The role of social media addiction in preventing texting and driving
The impact of distracted driving on social relationships
The correlation between texting and driving and academic achievement
The relationship between texting and driving and professional success
The effects of texting and driving on personal growth
The role of peer pressure in preventing texting and driving
The impact of distracted driving on physical health
The correlation between texting and driving and mental well-being
The relationship between texting and driving and emotional health
The effects of texting and driving on social development
The impact of distracted driving on emotional intelligence
The correlation between texting and driving and cognitive abilities
The relationship between texting and driving and decision-making skills
The effects of texting and driving on problem-solving skills
The impact of distracted driving on interpersonal relationships
The correlation between texting and driving and academic performance
The relationship between texting and driving and career success
The effects of texting and driving on personal fulfillment
The impact of distracted driving on physical well-being
The correlation between texting and driving and mental health
The impact of distracted driving on social connections

These are just a few examples of texting and driving essay topics that you can explore in your writing. Remember to choose a topic that interests you and that you feel passionate about, as this will make your essay more engaging and impactful. By raising awareness about the dangers of texting and driving through your writing, you can help make the roads safer for everyone.

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Distracted Driving

Types of Distraction
How big is the problem?
Who is most at risk for distracted driving?
How to Prevent Distracted Driving
What States are Doing to Prevent Distracted Driving
What the Federal Government is Doing to Prevent Distracted Driving
Distracted Driving Fact Sheet
Additional Resources

Nine people in the United States are killed every day in crashes that are reported to involve a distracted driver . 1

Distracted driving is doing another activity that takes the driver’s attention away from driving. Distracted driving can increase the chance of a motor vehicle crash.

Anything that takes your attention away from driving can be a distraction. Sending a text message, talking on a cell phone, using a navigation system, and eating while driving are a few examples of distracted driving. Any of these distractions can endanger you, your passengers, and others on the road.

There are three main types of distraction: 2

Visual: taking your eyes off the road
Manual: taking your hands off the wheel
Cognitive: taking your mind off driving

In the United States, over 3,100 people were killed and about 424,000 were injured in crashes involving a distracted driver in 2019. 1
About 1 in 5 of the people who died in crashes involving a distracted driver in 2019 were not in vehicles―they were walking, riding their bikes, or otherwise outside a vehicle. 1

Sources: National Highway Traffic Safety Administration, 2010-2013 , 2014–2018 and 2019

You can visit the National Highway Traffic Safety Administration (NHTSA) website for more information on how data on motor vehicle crash deaths are collected and the limitations of distracted driving data.

Young adult and teen drivers

A higher percentage of drivers ages 15–20 were distracted than drivers age 21 and older.
39% of high school students who drove in the past 30 days texted or emailed while driving on at least one of those days. 4
Texting or emailing while driving was more common among older students than younger students (see figure below) and more common among White students (44%) than Black (30%) or Hispanic students (35%). 4
Texting or emailing while driving was as common among students whose grades were mostly As or Bs as among students with mostly Cs, Ds, or Fs. 4
more likely to not always wear a seat belt;
more likely to ride with a driver who had been drinking alcohol; and
more likely to drive after drinking alcohol. 4

Source: National Highway Traffic Safety Administration , 2019

Source : Transportation Risk Behaviors Among High School Students — Youth Risk Behavior Survey, United States, 2019

What drivers can do

Do not multitask while driving. Whether it’s adjusting your mirrors, selecting music, eating, making a phone call, or reading a text or email―do it before or after your trip, not during.
You can use apps to help you avoid cell phone use while driving. Consider trying an app to reduce distractions while driving.

What passengers can do

Speak up if you are a passenger in a car with a distracted driver. Ask the driver to focus on driving.
Reduce distractions for the driver by assisting with navigation or other tasks.

What parents can do 5

Remind them driving is a skill that requires the driver’s full attention.
Emphasize that texts and phone calls can wait until arriving at a destination.
Familiarize yourself with your state’s graduated driver licensing system and enforce its guidelines for your teen.
Know your state’s laws on distracted driving . Many states have novice driver provisions in their distracted driving laws. Talk with your teen about the consequences of distracted driving and make yourself and your teen aware of your state’s penalties for talking or texting while driving.
Set consequences for distracted driving. Fill out CDC’s Parent-Teen Driving Agreement [PDF – 465 KB] together to begin a safe driving discussion and set your family’s rules of the road. Your family’s rules of the road can be stricter than your state’s law. You can also use these simple and effective ways to get involved with your teen’s driving: Parents Are the Key.
Set an example by keeping your eyes on the road and your hands on the wheel while driving.
Learn more: visit NHTSA’s website on safe teen driving .
The Insurance Institute for Highway Safety tracks cell phone use laws and young passenger restrictions by state.
4.1% to 2.7% in the Sacramento Valley Region in California, 6
6.8% to 2.9% in Hartford, Connecticut, 7
4.5% to 3.0% in the state of Delaware, 6 and
3.7% to 2.5% in Syracuse, New York. 7
Graduated driver licensing (GDL) is a system which helps new drivers gain experience under low-risk conditions by granting driving privileges in stages. Comprehensive GDL systems include five components 8- 9 , one of which addresses distracted driving: the young passenger restriction. 10 CDC’s GDL Planning Guide [PDF – 3 MB] can assist states in assessing, developing, and implementing actionable plans to strengthen their GDL systems.
Some states have installed rumble strips on highways to alert drowsy, distracted, or otherwise inattentive drivers that they are about to go off the road. These rumble strips are effective at reducing certain types of crashes. 10
CDC has developed the Parents Are the Key campaign, which helps parents, pediatricians, and communities help keep teen drivers safe on the road.
In 2022, the U.S. Department of Transportation released the National Roadway Safety Strategy [PDF – 42 pages] . Part of the strategy includes supporting vehicle technology systems that detect distracted driving.
In 2021, Congress provided resources to add distracted driving awareness as part of driver’s license exams as part of the Bipartisan Infrastructure Law [PDF – 1039 pages] .
In 2009, President Obama issued an Executive Order prohibiting federal employees from texting while driving government-owned vehicles or when driving privately owned vehicles on official government business.
In 2010, the Federal Railroad Administration banned cell phone and electronic device use for railroad operating employees on the job.
In 2010, the Federal Motor Carrier Safety Administration banned commercial vehicle drivers from texting while driving.
In 2011, the Federal Motor Carrier Safety Administration and the Pipeline and Hazardous Materials Safety Administration banned all hand-held cell phone use by commercial drivers and drivers carrying hazardous materials.
NHTSA has several campaigns to raise awareness of the dangers of distracted driving, including their annual “U Drive. U Text. U Pay.” campaign, which began in April 2014.
NHTSA has issued voluntary guidelines to promote safety by discouraging the introduction of both original, in-vehicle [PDF – 177 pages] and portable/aftermarket [PDF – 96 pages] electronic devices in vehicles.

This fact sheet provides an overview of distracted driving and promising strategies that are being used to address distracted driving.

Distracted Driving Summary Fact Sheet [PDF – 660 KB]

CDC MMWR – Transportation Risk Behaviors Among High School Students — Youth Risk Behavior Survey, United States, 2019
CDC MMWR – Mobile Device Use While Driving — United States and Seven European Countries, 2011
NHTSA – Distracted Driving
Governors Highway Safety Association – Distracted Driving
Insurance Institute for Highway Safety – Distracted Driving
World Health Organization – Mobile Phone Use: A Growing Problem of Driver Distraction
National Institute for Occupational Safety and Health (NIOSH) – Distracted Driving at Work
National Highway Traffic Safety Administration (NHTSA) – Campaign Materials
National Highway Traffic Safety Administration. (2021). Traffic Safety Facts Research Note: Distracted Driving 2019 (DOT HS 813 111) . Department of Transportation, Washington, DC: NHTSA. Accessed 8 February 2022.
National Highway Traffic Safety Administration. (2010). Overview of the National Highway Traffic Safety Administration’s Driver Distraction Program (DOT HS 811 299) [PDF – 36 pages] . U.S. Department of Transportation, Washington, DC. Accessed 8 February 2022.
Centers for Disease Control and Prevention. Youth Risk Behavior Surveillance System . Accessed 8 February 2022.
Yellman, M.A., Bryan, L., Sauber-Schatz, E.K., Brener, N. (2020). Transportation Risk Behaviors Among High School Students — Youth Risk Behavior Survey, United States, 2019 . MMWR Suppl, 69(Suppl-1),77–83.
National Highway Traffic Safety Administration. Teen Driving . Accessed 8 February 2022.
Chaudhary, N.K., Connolly, J., Tison, J., Solomon, M., & Elliott, K. (2015). National Highway Traffic Safety Administration. Evaluation of the NHTSA Distracted Driving High-Visibility Enforcement Demonstration Projects in California and Delaware [PDF – 72 pages] (DOT HS 812 108) . U.S. Department of Transportation, Washington, DC.
Chaudhary, N.K., Casanova-Powell, T.D., Cosgrove, L., Reagan, I., & Williams, A. (2012). National Highway Traffic Safety Administration. Evaluation of NHTSA Distracted Driving Demonstration Projects in Connecticut and New York [PDF – 80 pages] (DOT HS 811 635) . U.S. Department of Transportation, Washington, DC.
Centers for Disease Control and Prevention. (2019). Motor Vehicle Injuries . Accessed 8 February 2022.
Venkatraman, V., Richard, C. M., Magee, K., & Johnson, K. (2021). Countermeasures that work: A highway safety countermeasures guide for State Highway Safety Offices, 10 th edition, 2020 (Report No. DOT HS 813 097) [PDF – 641 pages] . U.S. Department of Transportation, Washington, DC.
Federal Highway Administration. (2011). Technical Advisory: Shoulder and Edge Line Rumble Strips (T 5040.39, Revision 1) [PDF – 9 pages] . Department of Transportation, Washington, DC: FHWA. Accessed 24 August 2020.

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117 Distracted Driving Essay Topic Ideas & Examples

🏆 best distracted driving topic ideas & essay examples, 🎓 good research topics about distracted driving, 💡 most interesting distracted driving topics to write about, ⭐ simple & easy distracted driving essay titles, ❓ questions about distracted driving.

Texting While Driving Should Be Illegal To begin with, it has been observed from recent studies that have been conducted that majority of American citizens are in complete agreement that texting while one is driving should be banned as it is […]
Banning Phone Use While Driving Will Save Lives For instance, a driver may receive a phone call or make one, and while tending to the call, takes his mind of the road and increasing the chances of causing an accident. We will write a custom essay specifically for you by our professional experts 808 writers online Learn More
Persuading People Not to Text While Driving It is believed that the main reasons for the growing number of car accidents and deaths on the roads is the development of new technologies and, as a result, the irresponsible driving of individuals who […]
Dangers of Texting while Driving The research paper will present some statistics to prove that texting while driving is one of the biggest contributors of road accidents in American roads.
Drinking and Driving: The Negative Effects The combination of drinking and driving is dangerous and characterized by such effects as physiological changes, problems with the law, and innocent victims. One of the main effects of drinking and driving is the increase […]
Age Limitation on Driving Privileges Thus, the increase in the level of accidents has forced the state to consider whether age is among the factors that have led to the increase in cases accidents.
Public Service Announcement and Distracted Driving To conclude, PSAs help to reduce the amount of distracted driving occurrences. As a result, public service announcements should be utilized to raise public awareness of the hazards of distracted driving and assist save lives.
Driving in the Winter and in the Summer To conclude, winter and summer driving are comparable in practices of handling the vehicle but are associated with contrasting dangers. In the summer, the temperature is higher, leading to the expansion of tires, and there […]
Safe Driving and Use of Cellphones in Cars In conclusion, it is recommended that all drivers have a cell phone in the car to assist with emergencies, navigation, and reporting crime.
Substance Abuse and Driving Under Influence The list of felonies consists of possession of substances, possession of ammunition with marijuana and the distribution of substances. This way, a person would be able to enhance their well-being and the state of mental […]
Dangerous Driving Case: Description, Investigation, Judicial Process, and Results The court maintained that the offense in the case was a statutory offense that implied the dangerous driving of the accused, whose eventuality resulted in the death of the woman victim.
Anti-Drink Driving Intervention Plan Overall, the ultimate goal of this paper lies in identifying key tasks that would be undertaken at all stages of the social marketing intervention planning process and evaluating the potential success of the plan.
Developing Strategic Plan for TLC Commission Future Self-Driving Cars A SWOT analysis of the issue would reveal that not many would trust the safety of self-driving cars. The research would be of much help as it would reveal that self-driving cars are not that […]
Self-Driving Technologies and Supply Chain Management Due to the large-scale implementation of such technologies, the whole transportation system will be changed. Self-driving technologies can significantly improve the development of the transportation industry.
Mobile Phone Use and Driving: Modelling Driver Distraction Effects Therefore, in order to increase attention during driving and improve the reaction to road events, it is advisable to prohibiting hand-held phone use while driving in all 50 states.
Tougher Punishment for Texting While Driving However the Center for Cognitive Brain Imaging reported that texting while driving is a greater distraction than talking to others due to the time eyes are away from the road and the amount of cognitive […]
The Use of Mobile Phone While Driving a Car The purpose of the study was to explore the effects of drivers’ use of mobile phones on the risk of a crash.
Addressing a Problem of Elderly Driving The authors claim that there are two possible ways to address the issue of elderly driving: developing social programs and integrating modern technology. These actions will be beneficial to the safety of older individuals and […]
Regulations on Multitasking While Driving Consequently, safe and effective driving is a task that demands concentration by the driver, and multi-tasking while driving should be discouraged and avoided for safety.
Cell Phones While Driving: Is It Legal? The message conveyed over the phone takes priority and driving takes a back seat which inevitably results in an accident, the severity of the same depends on more factors than one, the most important of […]
Local Crisis: Teenage Driving Fatalities in Alabama It was reported in the reader’s digest of the 2008 August edition that out of 50 states, Alabama had the 4th highest rate of deaths at 39.
Cause and Effect of Teenagers Crazy Driving They have to acknowledge that they are the childhood role model for the kids and this includes being the indirect driving teacher of the child.
Cell Phone Use and Driving: Mian vs. City of Ottawa However, the judge considers the disclosure of the disciplinary records to be irrelevant to the case. However, the Crown specifically stated that the disclosure of these records is not relevant to the case without O’Connor’s […]
Cell Phone Use While Driving: Policy Analysis Therefore, in a public policy debate, proponents of regulation would argue that per capita healthcare savings and resulting QALY measures are significant enough to justify a ban on the use of private cellphones in driving […]
Safe Driving Among American Youth as Health Issue It reviews the organization’s perspective on the issue and the strategies it proposes to reduce the risks of car accidents. The paper concentrates on safe driving for young people, summarizing the National Safety Council’s position […]
Cell Phone Use in Driving and Recommended Policies Auditory, when on phone, drivers shift their focus to the sound of the phone instead of listening to the adjoining atmosphere on the road.
Outcomes of the Phone Usage While Driving To the end of their lives, neither the victims’ loved ones nor the driver will be able to cope with the tragedy that resulted. The assertion that driving and texting or talking on the phone […]
Driving Under the Influence: US Policies Driving under the influence is known to be one of the most threatening tendencies in the world of nowadays. One of the most common policies provided in order to decrease the risk of drunken driving […]
Impacts of Texting While Driving on the Accidents The development of technologies used by adolescents for texting while driving leads to increasing the rates of accidents. Hypothesis: The development of technologies used by adolescents for texting while driving leads to increasing the rates […]
The New Application “Stop Texting and Driving App” The application installed in the driver’s smartphone will disable every function when the vehicle is in motion. The device and the application have more features in order to reduce the rate of having an accident.
Technology Development and Texting while Driving Working thesis: Although certain modern gadgets can be used to avoid texting while driving, the development of the sphere of mobile technologies has the negative impact on the dangerous trend of messaging while driving a […]
Distracted Driving Behaviors in Adults The article notes that the results of the study highlighted the dangers of DDB other than texting and using cell phones.
The South Dakota Legislature on Texting and Driving According to the authors of the article, the South Dakota Legislature needs to acknowledge the perils of texting and driving and place a ban on the practice.
Injury Prevention Intervention: Driving Injury in Young People According to Gielen and Sleet study, the trends indicate that despite the preventive measures, the likelihood for young people involved in injuries is increasing. The collective objectives are to reduce the probability of young people […]
Effects of Ageing Population as Driving Force Positive effects Negative effects An increased aging population will lead to a bigger market for goods and services associated with the elderly.
Cognitive Psychology on Driving and Phone Usage For this reason, it is quite difficult to multitask when the activities involved are driving and talking on the phone. Holding a phone when driving may cause the driver to use only one hand for […]
Banning Texting while Driving Saves Lives Other nations have limited use of phones, by teenagers, when driving, and a rising number of states and governments have prohibited the exact practice of texting while driving.
Saving Lives: On the Ban of Texting While Driving To achieve the goals of the objectives proposed above, a comprehensive case study needs to be conducted on the risks of texting while driving and how the prohibition of the act will save lives.
A Theoretical Analysis of the Act of Cell Phone Texting While Driving The past decade has seen the cell phone become the most common communication gadget in the world, and the US has one of the highest rates of cell phone use.
Drivers of Automobiles Should Be Prohibited From Using Cellular Phones While Driving When a driver is utilizing a hand-held or hands-free cellular phone at the same time as driving, she or he should dedicate part of their concentration to operating the handset and sustaining the phone discussion […]
Should People Be Banned From Using Cell Phones When Driving? Why or Why Not? Many people have blamed the cell phones to the current high increases in the number of road accidents witnessed worldwide, while others argue that the use of mobile phones while driving is not wholly to […]
Problem of the Elderly Driving in the US When comparing the survey results to accumulated scientific data as well as statistics on the number of vehicular accidents involving the elderly it can be seen that the respondents were unaware of the potential danger […]
The Dangers of Using Cell Phone While Driving The authors further note the subsequent increase in the count of persons conversing on cell phones while driving unaware of the risks they pose to themselves and their passengers.
An Analysis of the Use of Cell Phones While Driving The first theory is the theory of mass society, and the second theory is the theory of the culture industry. The theory of mass society states that, popular culture is an intrinsic expression of the […]
Popular Culture: The Use of Phones and Texting While Driving Given that rituals and stereotypes are a part of beliefs, values, and norms that society holds at a given instance of history, the use of phones in texting while driving has rituals and stereotypes associated […]
The Use of the Cell Phone While Driving Indeed, many of the culprits of this dangerous practice are teens and the youth, ordinarily the most ardent expressers of popular culture in a society.
Road Rage and the Possibilities of Slow Driving There is also a need for people to plan their daily activities early and give some time allowance to the expected driving time.
Theta and Alpha Oscillations in Attentional Interaction During Distracted Driving
Car Accidents and Distracted Driving
The Pros and Cons of Distracted Driving
Societal Crisis and Distracted Driving
Texting and Driving Accident Statistics – Distracted Driving
Major Safety Issue: Distracted Driving
Distracted Driving Should Not Be Banned
Making Laws Against Distracted Driving
Distracted Driving Regulation and Education
Prevent Distracted Driving
The Problem Distracted Driving Creates
Distracted Driving and Highway Fatalities
Cell Phones and the Dangers of Distracted Driving
Texting and Driving: Distracted Driving
Distracted Driving: Increase in Cell Phone Related Fatalities
Cause and Effect: Non-distracted Driving and Distracting Driving
Distracted Driving Involving Cell Phones
The Most Dangerous Type of Distracted Driving
Accidents and Distracted Driving
Distracted Driving and Doing Another Activity
The Primary Factors Contributing to the Problem of Distracted Driving
Distracted Driving Prevention: Texting or Handheld Cellphone Use While Driving
Attention and Distracted Driving
The Dangers of Distracted Driving
Distracted Driving and Its Effects on Safety
Motor Vehicle Safety: Distracted Driving
Distracted Driving While Using Handheld Electronic Device
Mobile Communication and Local Information Flow: Evidence From Distracted Driving Laws
Distracted Driving Prevention Act of 2011
Texting While Driving: The Development and Validation of the Distracted Driving Survey and Risk Score Among Young Adults
Causes, Impacts and Prevention Strategies of Distracted Driving
Distracted Driving: The Danger of the Technological Age
Distracted Driving: How Badly Does Cell Phone Use Affect Drivers
Opposing Perspectives and Solutions of Distracted Driving
Distracted Driving: The Preventable Killer
The Facts About Distracted Driving
Distracted Driving Bans Should Be Stronger
The Cautionary Measures Against Distracted Driving Proposed by the State
Distracted Driving and Dangerous Being Distracted While Driving
What Are the Causes of Distracted Driving?
What Is the Harm of Mobile Phones in Distracted Driving?
What Are the Consequences of Distracted Driving?
Should Distracted Driving Bans Be Stronger?
What Are the Strategies to Prevent Distracted Driving?
What Is the Act to Prevent Distracted Driving?
How to Regulate Distracted Driving?
Are Distracted Driving Fatalities Increasing?
What Are Two Major Issues That Can Cause Distracted Driving?
How Are Distracted Driving Laws Made?
What Are the State Proposed Distracted Driving Precautions?
What Is the Most Dangerous Type of Distracted Driving?
What Are the Main Contributing Factors to the Problem of Distracted Driving?
Why Has Distracted Driving Become a Societal Crisis?
What Are Signs of a Distracted Driver?
What Is an Example of a Mental Distraction Driving?
What Types of Drivers Are More Susceptible to Distractions?
Distracted Driving: How to Drive Safely?
Does Distracted Driving Threaten the Safety of Not Only the Driver?
How Many Accidents Are Caused by Distracted Driving?
How to Learn Not to Be Distracted From Driving?
What Issues Are Discussed at the Distracted Driving Summit?
How Does Media Influence Distracted Driving?
What Are the Opposing Views and Solutions to Distracted Driving?
What Age Group Drives Distracted the Most?
What Is the Most Dangerous Kind of Distracted Driving?
How Many Highway Collisions Are Caused by Distracted Drivers?
Can Fear Behind the Wheel Distract From Driving?
How Many Americans Have Died From Distracted Driving?
What Are Theta and Alpha Oscillations in the Interaction of Attention During Distracted Driving?
Chicago (A-D)
Chicago (N-B)

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Texting While Driving: A Literature Review on Driving Simulator Studies

Affiliations.

1 Department of Automotive and Transport Engineering, Transilvania University of Brașov, 29 Eroilor Blvd., 500036 Brasov, Romania.
2 Department of Transportation Planning and Engineering, National Technical University of Athens, 5 Heroon Polytechniou str., GR-15773 Athens, Greece.
PMID: 36901364
PMCID: PMC10001711
DOI: 10.3390/ijerph20054354

Road safety is increasingly threatened by distracted driving. Studies have shown that there is a significantly increased risk for a driver of being involved in a car crash due to visual distractions (not watching the road), manual distractions (hands are off the wheel for other non-driving activities), and cognitive and acoustic distractions (the driver is not focused on the driving task). Driving simulators (DSs) are powerful tools for identifying drivers' responses to different distracting factors in a safe manner. This paper aims to systematically review simulator-based studies to investigate what types of distractions are introduced when using the phone for texting while driving (TWD), what hardware and measures are used to analyze distraction, and what the impact of using mobile devices to read and write messages while driving is on driving performance. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) guidelines. A total of 7151 studies were identified in the database search, of which 67 were included in the review, and they were analyzed in order to respond to four research questions. The main findings revealed that TWD distraction has negative effects on driving performance, affecting drivers' divided attention and concentration, which can lead to potentially life-threatening traffic events. We also provide several recommendations for driving simulators that can ensure high reliability and validity for experiments. This review can serve as a basis for regulators and interested parties to propose restrictions related to using mobile phones in a vehicle and improve road safety.

Keywords: distracted driving; literature review; simulator study; texting while driving.

Publication types

Research Support, Non-U.S. Gov't
Accidents, Traffic
Automobile Driving*
Cell Phone*
Reproducibility of Results
Text Messaging*

Grants and funding

PN-III-P2-2.1-PED-2019-4366/Romanian Ministry of Education and Re-696 search

Texting And Driving Essay Sample

In today’s fast-paced world, people are constantly on the go. This is especially true of young drivers, who have a tendency to text and drive because it can be difficult to juggle all their responsibilities. However, this habit could be deadly as texting while driving increases the chances of being involved in an accident by 23%. In this essay, we will explore what makes texting while driving so risky and how you can avoid it.

Texting and driving essay writing help through the following sample is given by experts to the students. Students can refer to this essay for writing their own assignments.

Essay Example of Texting And Driving

Thesis Statements of Texting And Driving Essay
Introduction of Texting And Driving Essay
Examples that shown that texting and driving is not good
How to Stop the Practice of Texting and Driving

Thesis Statements of Texting And Driving Essay Texting and driving is a grave threat to our world today, but by taking the necessary precautions as drivers we can better ensure that it does not affect us or those close to us. Introduction of Texting And Driving Essay The modern time of technology has brought the mobile revolution to the entire world. Today you can see people of every age group fiddling their fingers on mobile phones. No real communication and dialogues have remained behind due to these mobile phones. Social networking sites are serving the purpose better for this cause. We can see that people keep on chatting for hours through these social networking sites. You must have come across many people on a regular basis that uses their mobile phone while driving. Either they are talking on the phone on chatting with their social friends while driving. This is very dangerous to texting while you are driving a vehicle. It can distract your focus from driving to your mobile screen. As a consequence of which you can become the reason for the death of an innocent person, or it could be you as well. Main Body of Texting And Driving Essay Examples that shown that texting and driving is not good There is enough evidence that has shown that texting and driving are not good for a safe life. It is just like the other form of the situation when you are driving and drinking. So many incidences and accidents have taken place so far due to this habit of people. Here are some points that will make you aware of the seriousness of the issue. A person who was texting while driving his car fails to listen to the horn of a truck that was coming from the opposite direction. As a result of which he meets with a drastic accident that takes away his life. A man was hospitalizing his pregnant wife during her labor pain, at the same time he was busy on phone. The results were very scary when they meet an accident in between the road. A similar case happens with a person who was listening to the music by plugging headphones in their ear, at the same time was busy with his texting to the friend on social media. He had to lose his life due to this ignorance of concentrating on driving. A lady who was dropping her kids at the school suddenly meets with a major accident on the road while chatting with her husband. There are several such examples that take our breath away from us owing to their seriousness. We really need to do something to eradicate this issue of texting and driving. Otherwise, it will eat our people like that of termite and we will not be aware of it. Get Non-Plagiarized Custom Essay on Texting And Driving in USA Order Now How to Stop the Practice of Texting and Driving Here are some ideas and tips that can help you to save yourself and others as well by not texting while driving. So go through these points very carefully. Try to Call your Friends when you get Time – If you are very keen to talk with your friends, it is very important to avoid them while you are driving. This is because by texting at the time of driving you are not just putting your life in danger but others as well. You might end up in the life of an innocent person due to your bad habit of texting and driving. Decide a Proper Time to Communicate or Chat with your Social Media Friends – In case you are not comfortable making a call to your social media friends and communicate with them through chat only, decide a proper time for that. It could be at the end of the day, or as per your time schedule, but make sure that you are not using the time of driving for this purpose. Be a responsible citizen by following the traffic rules of your country. Avoid Keeping your Mobile Phone in Front of you while Driving – When you will place your mobile phone in front of you it will keep on distracting you by forcing you to see the popup on the screen. Better you keep your phone in the pocket or bag, do not forget to turn off the message ringtone or popup while driving. This way you will be able to better concentrate on driving. Do not make social media Your World – Some people keep on chatting on their social media accounts all the time. This should be kept in mind that social media is a mean that helps you to communicate with the friends which are hard to do otherwise. But you cannot afford to lose the ones who are living with you. So drive safe and be responsible towards your family. Do Meditation and Self-Introspection on Regular Basis – When you will continuously get yourself involved in regular Yoga and exercise, it will help you to develop inner mental strength. You will come to know about the real purpose of life by forgetting to spend your entire day on social media. So make sure that you are doing exercise on daily basis. Hire USA Experts for Texting And Driving Essay Order Now Conclusion The discussions of the entire essay suggest us that we should avoid driving and texting to save the life of people on road along with our own life. This could be done when we are mentally aware of the destruction of texting and driving for mankind.

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Texting While Driving Essay Examples

Why is texting while driving dangerous.

Put simply, texting and driving are dangerous because texting diverts your attention away from the road. Although many people argue that texting only takes your eyes off the road for a few seconds, what they don’t realize is that in that few seconds, something unexpected could happen. Additionally, if you’re traveling at high rates of speed, you can travel significant distances in just a few seconds. Those few seconds that you are on your phone could be used to hit the breaks or swerve out of the way of a quickly approaching article. If your eyes are on your phone instead of on the road, you lose valuable time that could have been used to mitigate an accident.

How do you Break the Habit of Texting While Driving?

One of the best ways to stop yourself from texting while driving is to create a habit that will keep your eyes on the road and your hands on the wheel. For many people who rely on their phones for so much, this may seem like a difficult task. However, if you think about it, there are several things that you do habitually when driving a car that you don’t even think about, such as putting on a seatbelt or locking your car after you park it. The key is to incorporate putting your phone away as part of those routines. In that way, you’re not so much breaking the habit of texting and driving, but instead, creating new habits that prevent you from using your phone while in the car.

Making a new habit can be challenging. The key is to stay consistent and continually remind yourself of your goal until it becomes second nature. Try attaching a sticky note to the wheel of your car to remind yourself to not text and drive. Another good trick is to make a pact with a friend to help keep each other accountable. It is important to stick with your habit, not give in to temptation and always keep in the back of your mind the benefits of staying focused on the road and not driving while distracted.

The most ideal habit you can build is to simply turn your phone off when you get in the car. That way there is never any sort of distraction when you’re in the car – any notifications, no browsing social media, and no distractions while you try to pick the next song to listen to. However, this might not always be an option when you need to use your GPS or if you use your phone for entertainment purposes while driving. Fortunately, there are other solutions. You can use an app while you drive (we make some suggestions for good apps below!) and simply make a habit of activating the app before you hit the road. If you often drive with others in the car, another good option is to hand your phone to another passenger to hold onto until you reach your destination. If instead you typically drive alone, you can always close up your phone in the glove compartment, your purse, in the center storage console under your armrest or in any other place where you cannot reach it. That way, you can have your phone connected to the vehicle for entertainment purposes but will avoid texting and driving.

Can you go to Jail for Texting While Driving?

In Pennsylvania, drivers are prohibited from driving and texting. If you are pulled over texting and driving, you will be issued a fine. However, if you are texting and driving and you cause an accident, there may be criminal consequences for those actions that could result in jail time. The more severe the accident, the more jail time you can face. For example, if you cause a fatality by texting and driving, you may face up to five years in jail.

How many People are Killed by Texting While Driving?

The National Highway Traffic Safety Administration estimates that in 2017, over 3,000 people were killed in accidents caused by distracted driving. In Pennsylvania alone, a study estimated that in 2015, distracted driving caused nearly 15-thousand car crashes and at least 66 deaths.

Apps That Help to Prevent Texting While Driving

Nowadays, there are many apps available to drivers to deter them from texting while driving. Here are some of our favorites:

Drive Safe & Save– Designed by State Farm Auto Insurance, this app tracks your driving habits every time you get behind the wheel. Not only does it track when you’re using your phone while in the car, but also identifies when you’re speeding, breaking too hard or accelerating too quickly. The app will also provide tips on how to improve your driving habits. If you’re a State Farm customer, you can send your driving data to them and receive discounts for good driving on your monthly insurance bill too!
LifeSaver – This app was designed for insurance companies and large trucking fleet – but is available for families too! For parents who are concerned about their children texting and driving, the app blocks the child’s phone while driving and alerts the parents when they have safely arrived at their destination. The app works quietly in the background when you start driving to block mobile distractions but provides options to unlock for emergency situations. It also provides reports on how safely family members are driving and parents can also unlock a reward system to incentivize good driving habits.
AT&T DriveMode– Similarly, this app turns on when it senses that the phone is moving more than 15 miles per hour. Once activated, the app silences all incoming notifications, and will automatically respond to the caller or texter with a text stating that the person they are attempting to contact is currently driving. Parents are also alerted when the app is turned off, so you can help ensure your child is always safe.
DriveSafe.ly – This app has to be activated each time you get in the car. However, once it’s turned on, this app will read aloud each text message you receive. It will also automatically reply to the sender that you are currently driving.

Check your Smart Phone – Many smartphones have “Do Not Disturb” or Drive Mode settings that you can turn on when getting behind the wheel.

Considering the importance of this matter and increase awareness to the next generation, we had organized the “Texting and Driving Essay” contest on for students. We are very happy to find that we got many great articles which show our next generation is pretty aware of this matter. The following four Texting and Driving Essay essays are the best entries:

Texting and Driving Essay: Statistics on texting and using your phone while driving and ideas to break those habits

By Leticia Pérez Zamor

Every day in the United States around one out of ten people are killed by distracted drivers, and around 1500 are injured in some way in crashes by these irresponsible, distracted drivers. One of the most dangerous, distracting activities that many people do is texting while driving. It is extremely dangerous because people who do this are putting more attention in texting, and they take their eyes off the road while they are driving, which increases the chance that the driver can lose the control of the vehicle, and could cause a crash or even in a worst-case could kill other people. When a person is texting, she/he is thinking about other things besides concentrating on driving. This is very dangerous because it could make the driver lose control of the car and slow her/his brain’s reaction time in case of a potential accident.

The statistics are very sad because according to the CDC (Centers for Disease Control and Prevention) in 2011, 3,331 people were killed in crashes involving a distracted driver, and 387,000 people were injured in motor vehicle crashes involving a distracted driver. Additionally, a recent study by the Virginia Tech Transportation Institute showed that drivers who are texting are twice as likely to crash, or almost crash, as those who are focused on the road. These statistics are reaching higher numbers because people are using their cell phones more and more, especially adolescents.

For this reason, it is very important that we find some ideas to break off this bad habit of texting while driving. I think that one of the easiest and best ways to break this habit is simply to turn off your phone. In this case, the driver wouldn’t be distracted by the ringing or buzzing of the phone, and it wouldn’t tempt the driver to text while driving. Another way to break this habit is to download some of the new applications that can disable cell phones while people are driving. Also, there are other applications that automatically send a text to whoever is texting the driver to tell that person that she/he is driving and that the text will be answered later. There are a great variety of applications to choose I think that we can use these to help us with the problem of texting while we are driving. Additionally, if a driver is waiting for an important call or text and has company in the car, the phone can be given to a passenger to check it out. Also, there are some programs that are helping to raise awareness about the dangers of distracted driving and to keep it from occurring. In these anti-texting programs, people can drive in a simulated situation, where they are driving but also texting, and can see how many accidents are caused by this problem.

Something very important is that many of the states have started to pass some laws that order drivers to stop texting while driving. However, we need to be sincere: none of these laws will be effective if we as a society don’t understand that texting while driving could have terrible consequences, not only for us as drivers but also for other innocent people. I don’t think that answering texts is more important than the lives of other people; texting can wait until drivers arrive at their destination.

The Dangers of Texting While Driving Essay

By LoryYau, St. Johns University

With the advanced technology in today’s world, people are very connected to each other and are constantly on their phone texting friends, going on social media, or using the phone to pass time. However, this also includes texting back a friend while driving. As simple as it might seems, texting and driving is very dangerous and should be taken seriously. In fact, in 2011, at least 23% of auto collisions involved cell phones. That’s about 1.3 million crashes! Not only that but texting while driving is actually more dangerous than driving while being drunk or high on marijuana. Every year almost a million people in the United States get into accidents, the majority: teens. Unfortunately, the number just keeps increasing.

Though texting and driving caused many injuries and deaths, there are still people who don’t think it’s a problem and are confident that they can use their phone and drive simultaneously. However, 34% of teens aged sixteen to seventeen spend about 10% of their driving time outside of their lane. This affects other people who are driving and can cause the deaths of innocent lives. In a 2012 Cell Phone and Driving Statistic, it is reported that 3,328 people were killed and 421,000 people were injured due to distracted drivers. Furthermore, it is said that talking or listening on the phone increases the risk of crashing by 1.3 times while reaching for a device is 1.4. Dialing is 2.8 times more risk of crashing while texting is 23 more times. Additionally, talking on a cell phone and driving at the same time can make the driver’s reaction time to be as slow as that of a seventy-year-old.

To break these habits, people can either turn off their phone or put it on silent before driving. This will force them to concentrate on the road only. But if this method doesn’t work on some people, you can use S voice or Seri to command your phone to read out your messages or to reply back. This will allow your eyes to focus on the road instead of your phone. No more reaching for your phone to text “Lol” or “Lmao” and endangering your own life and many others. Though you are still talking while driving, it still decreases your chance of crashing. An app in smartphones that works similarly to the method I described before is called DriveSafe.ly. Basically, it reads your text messages and emails out loud and has a customizable auto-responder. A few other apps that help prevent texting are called Safely Go and TXT ME L8R. Both apps work by either blocking the phone’s ability to text, receive and use apps or locking the phone. Then both phones automatically send a message to inform your friends or family that you are driving. For parents, you can give your phones to your kids while you’re driving. You won’t be able to get them back when they’re too busy playing Angry Bird or Cut the Rope.

To stop people from texting and driving, one of the major phone companies, AT&T, address this problem by creating AT&T’s It Can Wait to text and driving campaign to spread awareness. Many stories and documentaries are also posted online to support this campaign. You can also join millions of others who have signed the pledge to never text and drive and to instead take action to educate others about the dangers of it. If you still believe you can get home safely by texting and driving, AT&T’s simulator will prove you wrong. It gives you a real-life experience of texting and driving. With this game, you’ll only find out that it’s not as easy as it sounds. Before you look at a text, remember that it is not worth dying for.

The Issue of Texting While Driving Essay

By Justin Van Nuil

It seems that everyone has a cell phone, and they cannot be separated from it. Cell phones have made a huge impact in the world, both good and bad. Most of the bad come when people, especially teens, decide to use the phone when behind the wheel of a vehicle. There are some huge statistics against texting and talking on the phone while driving, and people are trying to bring awareness to this expanding problem across the United States.

Staggering statistics are out there for everyone to see, yet we go about our lives ignoring the signs and warning against using our cell phones while driving. Textinganddrivingsafety.com tells us that texting while driving increases the probability of getting in a crash twenty-three times the normal amount, and thirteen percent of the young adults, eighteen to twenty, have admitted to talking or texting before the course of the accident. This is due to the time our eyes are off the road, and our mind’s capacity to do only one task at a time. Just taking our eyes off the road for five seconds, while the car is traveling at fifty-five miles per hour, is the same as traveling a football field without noticing what is going on around us. Seeing the danger in this is very evident, especially around intersections. Taking eyes off the road through an intersection is probably the highest risk, the light could be changing causing the car in front to stop, or worse, traveling through the red light or a stop sign into flowing traffic.

Texting is a major factor when it comes to crashes and creating a hazardous situation, so preventing the usage of cell phones while driving would be a large step in limiting the number of crashes that happen in the United States. There are multiple associations that are already trying to prevent cell phone usage. Associations such as the NHTSA, the Nation Highway Traffic Safety Association, which is an organization dedicated fully to tips and facts and videos showing how dangerous it can be to use your cell phone. There are also Facebook and Twitter pages, and blogs. In addition, the driving course in Michigan has a section in the lesson on the hazards of using cell phones while driving.

These are just programs that are helping to prevent texting while driving. Easy and simple ways that everyone can do as they enter the car. Firstly, by putting the phone in the glovebox, you eliminate the temptation to reach for it and use it while your driving. If you decide not to use that method, and you have a passenger, just give the phone to them, they can rely on the information to you if it is that important. Just keeping the phone out of reach, in general, will help prevent the usage of the device.

Not only are these ways are widespread and easily accomplished, but there should also be a restriction in general for usage while driving. I know multiple states have issued laws against texting, and in some states absolute usage of the cell phone while in the driver’s seat. Although, the overall effects may not be seen in the number of accidents prevented due to these laws, having a larger discipline for doing such activities should help in dropping the number of people on their devices.

Preventing the usage of these everyday devices is very simple, yet rather difficult, and will save lives if it works out. Accidents are deadly to many people, so creating an environment for everyone is better in the long run. As a young adult, I plan to use some of these ideas and promote these websites and encourage others around me to do the same.

Why is Texting and Driving Dangerous?

By Haley Muhammad

It has become such an issue that every time we turn on the TV all we see is that same commercial running about that girl who died because she wanted to text her friend back. Or that now in every major TV show someone always gets in a car accident because they want to text someone that they love them. It’s clear that no one has the decency to pull over to text someone back or even call them to say I will text you later because I’m driving. It’s a rising epidemic that’s destroying the generation of teenagers. I remember when technology was something beautiful because of how helpful it is but, now its become a hazard to the generation alone. Statistics have shown that “ Texting while driving has become a greater hazard than drinking while driving among teenagers who openly acknowledge sending and reading text messages while behind the wheel of a moving vehicle,” stated by Delthia Ricks from Newsday newspaper.

Ever since the emergence of cell phones, this generation has become heavily dependent on it for every minute of every day. Cell phones and texting were created ultimately to provide communication but it has now become so much more than that. Statistics also show that “Seventy-one percent of young people say they have sent a text while driving. As a result, thousands of people die every year in crashes related to distracted driving,” (Distraction.gov). Texting while driving has become a heavy habit for most teens and adults as well but regardless of the commercials and shows and statistics that show the results of texting while driving most people cannot kick the habit. Other statistics include, “Individuals who drive while sending or reading text messages are 23 percent more likely to be involved in a car crash than other drivers. A crash typically happens within an average of three seconds after a driver is distracted,” (donttextdrive.com). Overall all these statistics are saying the same thing, is that one text can wreck all.

So many lives are taken or altered because of the simple decision to send or reply to one text message. If precautions are heavily enforced before adults and teens especially enter the car, then maybe this epidemic can become obsolete. Fines are enforced but how well is the question? Phones are the biggest distraction when you enter a car, this doesn’t completely forget about alcohol or trying to change the radio station but technology has become so advanced that we have voice text and on a star. If the message is that important phones should become voice-activated and only respond to your voice so we can still pay attention to the road and send out a text without removing our hands from the wheel. Technology has also graced us with Bluetooth if you need to stay in communication just use Bluetooth and make a phone call instead which is completely easier than sending a text anyway because it’s faster and you can get responses much quicker than you could with a text message. Reality is one text or call could wreck it all.

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Original Contribution
Open access
Published: 01 March 2016

Texting while driving: the development and validation of the distracted driving survey and risk score among young adults

Regan W. Bergmark ORCID: orcid.org/0000-0003-3249-4343 1 , 2 , 3 ,
Emily Gliklich 1 ,
Rong Guo 2 , 3 &
Richard E. Gliklich 1 , 2 , 3

Injury Epidemiology volume 3 , Article number: 7 ( 2016 ) Cite this article

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Texting while driving and other cell-phone reading and writing activities are high-risk activities associated with motor vehicle collisions and mortality. This paper describes the development and preliminary evaluation of the Distracted Driving Survey (DDS) and score.

Survey questions were developed by a research team using semi-structured interviews, pilot-tested, and evaluated in young drivers for validity and reliability. Questions focused on texting while driving and use of email, social media, and maps on cellular phones with specific questions about the driving speeds at which these activities are performed.

In 228 drivers 18–24 years old, the DDS showed excellent internal consistency (Cronbach’s alpha = 0.93) and correlations with reported 12-month crash rates. The score is reported on a 0–44 scale with 44 being highest risk behaviors. For every 1 unit increase of the DDS score, the odds of reporting a car crash increases 7 %. The survey can be completed in two minutes, or less than five minutes if demographic and background information is included. Text messaging was common; 59.2 and 71.5 % of respondents said they wrote and read text messages, respectively, while driving in the last 30 days.

The DDS is an 11-item scale that measures cell phone-related distracted driving risk and includes reading/viewing and writing subscores. The scale demonstrated strong validity and reliability in drivers age 24 and younger. The DDS may be useful for measuring rates of cell-phone related distracted driving and for evaluating public health interventions focused on reducing such behaviors.

Texting and other cell phone use while driving has emerged as a major contribution to teenage and young adult injury and death in motor vehicle collisions over the past several years (Bingham 2014 ; Wilson and Stimpson 2010 ). Young adults have been found to have higher rates of texting and driving than older drivers (Braitman and McCartt 2010 ; Hoff et al. 2013 ). Motor vehicle collisions are the top cause of death for teens, responsible for 35 % of all deaths of teens 12–19 years old, with high rates of distraction contributing significantly to this percentage (Minino 2010 ). In 2012, more than 3300 people were killed and 421,000 injured in distraction-related crashes in the US, with the worst levels of distraction in the youngest drivers (US Department of Transportation National Highway Traffic Safety Administration 2014 ).

While distracted driving includes any activity that takes eyes or attention away from driving, there has been particular and intense interest on texting and other smartphone-associated distraction as smartphones have become widely available over the past ten years. Multiple studies have examined driving performance while texting or completing other secondary tasks (Yannis et al. 2014 ; Owens et al. 2011 ; Olson et al. 2009 ; Narad et al. 2013 ; McKeever et al. 2013 ; Drews et al. 2009 ; Hickman and Hanowski 2012 ; Leung et al. 2012 ; Long et al. 2012 ). Uniformly, distraction from cell phone use, including texting, dialing or other behaviors, is associated with poorer driving performance (Yannis et al. 2014 ; McKeever et al. 2013 ; Bendak 2014 ; Hosking et al. 2009 ; Irwin et al. 2014 ; Mouloua et al. 2012 ; Rudin-Brown et al. 2013 ; Stavrinos et al. 2013 ). A 2014 meta-analysis of experimental studies found profound effects of texting while driving with poor responsiveness and vehicle control, and higher numbers of crashes (Caird et al. 2014 ). A rigorous case–control study found that among novice drivers, sending and receiving texts was associated with significantly increased risk of a crash or near-crash (O.R. 3.9) (Klauer et al. 2014 ). In commercial vehicles, texting on a cell phone was associated with a much higher risk of a crash or other safety-critical event, such as near-collision or unintentional lane deviation (OR 23.2) (Olson et al. 2009 ). Motor vehicle crash-related death and injury have also been strongly associated with texting (Pakula et al. 2013 ; Issar et al. 2013 ).

Although the dangers of texting and driving are well-established, a focused brief survey on driver-reported texting behavior does not yet exist. Multiple national surveys which include texting while driving as part of a more extensive survey on distracted driving or youth health have found that young drivers have high rates of texting while driving, often in spite of high levels of perceived risk (Hoff et al. 2013 ; Buchanan et al. 2013 ; Cazzulino et al. 2014 ; O’Brien et al. 2010 ; Atchley et al. 2011 ; Harrison 2011 ; Nelson et al. 2009 ). The surveys confirm that young adults are at high risk for distracted driving; in one, 81 % of 348 college students stated that they would respond to an incoming text while driving, and 92 % read texts while driving (Atchley et al. 2011 ). Among several large survey based studies, the National Highway Traffic Safety Administration reported from a 2012 survey that nearly half (49 %) of 21–24 year old drivers had ever sent a text message or email while driving (Tison et al. 2011 -12), and even more alarming, the Centers for Disease Control and Prevention (CDC)’s National Youth Risk Behavior Survey found that nearly as many high school students who drove reported texting in just the past 30 days (41.4 %) ( Kann et al. 2014 ). The problem is not confined to novice drivers. Among US adults ages 18 to 64 years 31 % report reading or sending text messages or emails while driving in prior last 30 days ( Centers for Disease Control and Prevention (CDC) 2013 ).

Given the magnitude of the problem, a very brief questionnaire focused on texting and driving for evaluation of public health measures such as anti-texting while driving laws, cell phone applications and public health campaigns would be useful. The use of self-reported validated surveys is an increasingly common approach to understanding health issues as well as their response to intervention (Guyatt et al. 1993 ; Tarlov et al. 1989 ; Stewart and Ware 1992 ). Current surveys are driving-specific but lengthy and potentially prohibitive for widespread dissemination (Tison et al. 2011 -12, McNally and Bradley 2014 ; Scott-Parker et al. 2012 ; Scott-Parker and Proffitt 2015 ), do not include texting as a survey domain within the realm of distraction (Martinussen, et al, 2013 ), are general health surveys without sufficient information on texting and driving ( Kann et al. 2014 ), or have not been designed or validated to reliably measure and evaluate individual crash risk ( Kann et al. 2014 ). For example, a new survey of reckless driving behavior includes information on multiple driving-related domains of behavior, but administration takes 35 min and the survey does not focus on cell phones (McNally and Bradley 2014 ). Another survey of distraction in youth is similarly comprehensive without a focus on phone use (Scott-Parker et al. 2012 ; Scott-Parker and Proffitt 2015 ). The goal of shorter surveys for evaluation of distracted driving has been well documented and development of the mini Driver Behavior Questionnaire (Mini-DBQ) is an example, although it does not address cell phone related distracted driving (Martinussen et al. 2013 ). However, many interventions target cell phone use specifically rather than distraction broadly. In addition, most surveys do not delve into the specific timing of texting while driving that allows a more precise estimate of the behavior’s prevalence.

The purpose of this study was to develop a reliable self-reported survey for assessing levels of cell phone related distracted driving associated with viewing and typing activities and to validate it in a higher risk population of drivers age 24 years or younger.

Study design and oversight

A literature review and open-ended interviews with experienced and novice drivers were performed to identify the most common domains for item development as well as any existing survey items with validation metrics. The literature review was performed with reviewing terms including “Text*” and “Driv*” reviewing for any studies that included driver-reported outcomes. Initial items were piloted with open-ended responses. Ten novice (18–25 years old) and experienced (30 years old or older with at least 10 years of driving experience) drivers underwent semi-structured interviews about cell phone use while driving to further generate potential survey domains. Text messaging through various applications, map/GPS use, email and social media were prominent themes. “Texting while driving” was interpreted very differently by various participants; some people stated that texting at stop lights or at slow speeds, or reading texts, did not really constitute texting and driving. This finding suggested that a questions that simply asks “do you text and drive?” may be missing a significant proportion of this distracted behavior.

Based on the identified themes, we developed a series of Likert scale and multiple-option items reflecting the most common reading and typing tasks reported on a cell phone (Table 1 ). The format of many of our questions was modeled on the Centers for Disease Control and Prevention National Youth Risk Behavior Survey and after a thorough review of the other surveys described above. The assessed activities included reading or viewing text messages, emails, map directions, internet sites and social messaging boards and typing or writing activities through these same applications. The piloting process revealed that in addition to questions addressing frequency of the activity over the previous 30 days while driving (e.g. every time, most of the time, etc.), it was important to also assess when the activities were performed with respect to vehicular motion or speed (any speed, low speeds, stop and go traffic, etc.) to allow for further risk stratification. Additional items assessed driver attitudes with respect to their perceived level of risk associated with performing these activities. The questionnaire was pre-tested with 30 drivers 18–24 years old and went through multiple iterations. In addition to questions on cell phone reading and writing activities, the questionnaire included demographic information, self-reported “accidents” within the past 12 months of any cause, and potentially high-risk activities such as driving under the influence of alcohol or other substances. Given the colloquial use of the phrase “car accident,” we used the term “car accident” in our survey, but in the results section refer to this number as the crash rate. The question included in the final survey to elicit crash data was, “In the last 12 months, have many car accidents have you been in with you as the driver? (Answers 1, 2, 3, 4, 5 or more).” Based on feedback from the pilot testing, twenty-nine items were selected for testing in the initial questionnaire.

The questionnaire was set up as a web-based survey using standard, HIPAA compliant software. Participants provided informed consent and received a nominal incentive for participating. The study was approved by the Massachusetts Eye and Ear Institutional Review Board.

Participants

Three pools of participants 18–24 years old who had driven in the prior 30 days were recruited: (1) greater Boston metropolitan area were recruited from educational or recreational centers in the greater Boston area with flyers, enrolled through a generic link, and completed a second survey at 14 days for test-retest reliability, after which several questions were eliminated yielding and 11-item questionnaire (2) A panel was used through the software program to recruit participants from two geographic locations, (a) Eastern and (b) Western United States for a larger geographical distribution for further validation. These participants completed the survey a single time.

Item selection: reliability and validity

With the goal of creating a brief and targeted survey, items were selected for inclusion in the total score based on multiple reliability and reliability measures (Table 1 ). Item response distribution was examined prior to analysis. Items with low test-retest reliability in the Boston sample defined as a Spearman correlation of less than 0.4 or a Kappa coefficient below 0.3 were eliminated. Internal consistency was measured with Cronbach’s alpha, examining Cronbach’s alpha for each item and the DDS coefficient with each variable deleted, with any questions with a Cronbach’s alpha under 0.8 eliminated. In addition to face validity, the survey was assessed for criterion-related validity by use of concurrent validity against hypothesized correlates to other assessed variables. We hypothesized a significant correlation to self-reported crashes in the prior 12 months. We additionally postulated that writing related activities would be higher risk than reading or viewing activities alone. Conversely, we hypothesized non-significant correlations with other items (e.g. falling asleep while driving).

Items not focused on cell phone writing and reading behaviors or crash rate also were eliminated from the final survey to allow for brevity. The final survey was then tested in two cohorts of young drivers to confirm internal consistency, time required for survey completion and correlation with crash rate.

Statistical analysis

All data analysis was performed using SAS V9.4 (SAS Institute Inc., Cary, NC). Standard descriptive statistics were reported, mean (SD) for numerical variables, median (min – max) for Likert scale variables and frequency count (%) for categorical variables. The statistical underpinnings of patient-reported outcomes measures and survey design are well established; the reader may reference Fleiss’s Design and Analysis of Clinical Experiments for a detailed discussion of the methods chosen for this study (Fleiss 1999 ).”

An algorithm was created to generate a total Distracted Driving Survey (DDS) score based on the final items selected for the questionnaire where zero represents the lowest possible score. The response for each of the questions included was given a value 1–5 with 1 being the lowest risk answer (ie, no texting and driving) and 5 being the highest risk. For a given subject, the scores for the questions were then summed and reduced by the number of questions such that the lowest score was zero. The final survey, consisting of 11 questions, therefore had a range of possible scores ranging from 0 to 44, with 44 being the highest risk. In addition, two subscores for reading only (DDS-Reading) and writing only (DDS-Writing) related questions were created for further risk stratification based on evidence that writing texts is even more dangerous than reading texts alone (Caird et al. 2014 ). Wilcoxon tests were used for the comparison of DDS score by levels of demographic and behavior variables. In addition, logistic regression was performed to evaluate the effect of DDS score on reported car crashes while adjusting for driving under substance influence.

Study population

There were 228 subjects included in the study (Table 2 ). Of the Boston group, 70 of 79 initial respondents completed the survey at the two-week interval and 14 respondents were additionally excluded for reporting not having driven a motor vehicle in the prior 30 days on one or both surveys. Therefore there were a total of 56 Boston respondents (25 male, 31 female). There were 90 respondents in the Eastern Region and 82 in the Western region.

Of the 228 total respondents, 120 (52.3 %) were female. Participants self-identified as White (63.3 %), Asian (11.4 %), Black/African American (8.0 %) or other (17.3 %). 34 (15.0 %) described themselves as Hispanic. Respondents said their driving was predominantly urban (45.6 %), suburban (44.3 %), or rural (10.1 %). Most (71.5 %) respondents were either in college or had completed some or all of college. Other participants were in or had completed high school (26.3 %), or described their educational status as other (2.2 %).

Item selection: reliability

The survey was first tested in a Boston metropolitan area cohort ( N = 56) and items were reduced based on Cronbach’s alpha and the Kappa statistic (Tables 3 and 4 ). Eliminated questions asked about use of voice recognition software and riding with a driver who texted, as well as use of specific anti-texting programs, all of which did not meet reliability or validity criteria. To keep the survey brief and focused, questions that were not cell-phone specific were also eliminated (i.e., drowsiness when driving, driving under the influence, seatbelt use) even though these questions were statistically reliable. There were 11 items in the final questionnaire; the Spearman correlation coefficient for test-retest reliability was excellent at 0.82 for the final survey based on the Boston data ( N = 56) (Tables 3 , 4 and 5 ).

The DDS-Reading or viewing subscore included six items (2–6, 11). The DDS-Writing subscore included four items that asked about specific writing activities including writing texts and emails and at what speeds (7–10). The Spearman coefficient for the DDS-Reading subscore was similar at 0.82 but lower for the DDS-Writing subscore at 0.63 (Table 5 ). Strong agreement was generally observed for the items included in the DDS. In addition, very good agreement was observed for most of the variables used for concurrent validity testing of the DDS including reported crashes in the last 12 months (Kappa = 0.6).

Internal consistency

The 11-item survey with additional demographic questions was then tested in the Eastern and Western US populations. Standardized Cronbach’s alpha for the final 11-item DDS was excellent at 0.92 ( N = 228) (Table 5 ). The DDS-Reading subscore standardized Cronbach’s alpha was 0.86. The DDS-Writing score standardized Cronbach’s alpha coefficient was 0.85.

Score distribution and association with car crashes

The 11-item questionnaire was then used to calculate the DDS score as described in the methods section with a higher score indicating more risk behaviors. Mean DDS score based on the entire cohort ( N = 228) was 11.0 points with a standard deviation (SD) of 8.99 and a range of 0 to 44 points. The distribution of scores is shown in Fig. 1 . There was no statistically significant difference of DDS total score by region ( p = 0.81). The mean scores for were similar for Boston (11.2, standard deviation 7.14), Eastern United States (11.4, standard deviation 9.48), and Western United States (10.5, standard deviation 9.62).

Distribution of the Distracted Driving Survey (DDS) scores. Scores reflect the final 11-item questionnaire, calculated with a range of 0 to 44 with high scores indicating more distraction

Reading and writing scores specific subscores were also calculated and also significantly correlated with crash rate (Table 5 ). Mean writing score was 3.2 (SD 3.48, range 0–16), and mean viewing reading score was 6.57 (SD 5.16, range 0–24).

A higher DDS score indicating higher risk behavior was significantly associated with the self-reported car crashes (Wilcoxon rank sum test, p = 0.0005). Logistic regression was performed with reported car crashes as the dependent variable and DDS as the independent variable. For every one point increase of the DDS score, the odds of a self-reported car crash increased 7 % (OR 1.07, 95 % confidence interval 1.03 – 1.12, p = 0.0005). The odds ratio for the DDS-Writing subscore (OR 1.17) was the highest among the scores and subscores. As anticipated, DDS score was not significantly associated with either falling asleep while driving ( p = 0.11) or driving under the influence ( p = .09) in the Boston group ( N = 56), and these questions were eliminated for the Eastern and Western US groups.

In order to better characterize the risk of higher DDS, the DDS-11 score was categorized into < =9, 9–15 and >15 using its median (9 points) and third quartile (15). The odds of car crash for subjects with DDS-11 > 15 is 4.7 times greater than that of subjects with DDS score < =9 (95 % CI 1.8–12.6).

Texting and driving behavior

In this cohort of 228 18–24 year old divers (Table 5 ), we found that 59.2 % reported writing text messages while driving in the prior 30 days. Of the 228 drivers, most wrote text messages never or rarely, while 16 % said they write text messages some of the times they drive and 7.4 % said they write text messages most or every time they drive. When all participants were asked about the speeds at which they write text messages, 9.7 % said they write text messages while driving at any speed and an additional 24.1 % said they write text messages at low speeds or in stop and go traffic, with the remainder writing text messages only at stop lights or not writing text messages while driving at all.

Reading text messages was even more common, with 71.5 % of participants saying they read text messages while driving in the past 30 days – 29.0 % rarely, 27.2 % sometimes, 13.2 % most of the time, and 2.2 % every time they drove. Compared to writing texts, a higher percentage read text messages at any speed (12.7 %) and at low speeds (15.6 %), in stop and go traffic (10.1 %), as well as when stopped at a red light (36.3 %). Reading and writing email and browsing social media were less common. Maps were used on a phone by 74.6 % of respondents in the last 30 days.

In contrast to yes/no answers in other surveys about safety of texting and driving, this study found that only 36.4 % of respondents said it was never safe to text and drive. Drivers reported that it was safe to text and drive never (36.4 %) rarely (27.6 %), sometimes (20.2 %), most of the time (8.8 %) and always (7.0 %).” This is in contrast to yes/no answers in other surveys about texting and driving safety.

The purpose of this study was to create a short validated questionnaire to assess texting while driving and other cell-phone related distracted driving behaviors. The Distracted Driving Survey developed in this study proved to be valid and reliable in a population of 18–24 year old drivers, with excellent internal consistency (Cronbach’s alpha of 0.93). The DDS has excellent internal consistency defined as Cronbach’s alpha =0.9 or greater and strong test retest reliability.(Kline 1999 ) The Mini-DBQ, a valid measure which does not include texting or other cell-phone related distracted driving, is considered a valid measure with Cronbachs alpha of less than 0.6, substantially lower than the DDS (Martinussen et al. 2013 ).

The Distracted Driving Survey score was significantly correlated with self-reported crash rates in the prior 12 months with people in the highest tercile of derived scores (here, those with a score >15) more than 4.7 times as likely to have had a crash than subjects with scores in the lowest tercile of risk (here, those <9). Stepwise logistic regression demonstrated this relationship to have a ‘dose response’, with higher scores incrementally associated with higher crash rates. The odds of a reported crash increased 7 % for every increase of one point of the DDS score (OR 1.07, 95 % confidence interval 1.03 – 1.12, p = 0.0005). This relationship was further demonstrated to be independent of such factors as driving under the influence of alcohol or other substances, and falling asleep while driving.

The DDS confirmed prior reports of high levels of texting while driving, and further elucidated specific aspects of the behavior including to what extent people read versus write text messages and and what speeds they perform these activities. 59.2 and 71.5 % of respondents said they wrote and read text messages, respectively, while driving in the last 30 days. Respondents were most likely to do these activities while stopped, in stop-and-go traffic or at low speeds although a small percentage said they have read or written text messages while traveling at any speed. Prior studies have shown high rates of texting while driving in spite of high rates of perceived risk. In this study, Likert-scale questions further demonstrated that most respondents actually felt that texting and driving can be safe at least on rare occasions; only 36.4 % of respondents said it was always unsafe to text and drive. These data correspond more directly to the amount of texting and driving reported here including reading or writing texts while stopped or in stop and go traffic.

Texting and other cell phone use while driving is frequently targeted as a public health crisis, but many of these interventions have unclear impact. Since the advent of the Blackberry in 2003 and the first iPhone in 2007, texting and driving has been highlighted in the news and by cell phone carriers, such as with AT&T’s It Can Wait pledge, to which more than 5 million people have committed (AT&T 2014 ). There are multiple smartphone applications and other interventions aimed at reducing texting and driving (Verizon Wireless 2014 ; Lee 2007 ; Moreno 2013 ), and Ford has even created a Do Not Disturb button in select vehicles blocking all incoming calls and texts (Ford 2011 ). Forty-four U.S. states and the District of Columbia ban texting and driving, with Washington State passing the first ban in 2007 (Governors Safety Highway Association 2014 ), and there is a push for even more aggressive laws and enforcement (Catherine Chase 2014 ). Texting bans have been shown to be effective in some studies. Texting bans are associated with reductions in crash-related hospitalizations (Ferdinand et al. 2015 ). Analysis of texting behavior from the U.S. Centers for Disease Control and Prevention 2013 National Youth Risk Behavior Survey showed that text-messaging bans with primary enforcement are associated with reduced texting levels in high school drivers, whereas phone use bans were not (Qiao and Bell 2016 ). Other studies surveying drivers have found a mixed response of whether behavior is altered, with some drivers not altering their behavior (Mathew et al. 2014 ). However, the impact of many of these interventions has not yet been studied or fully understood. While driver reported surveys exist today, in general these instruments have high respondent burden and have not been designed or validated for individual measurement.

We aimed to develop a validated, reliable and brief survey for drivers to report and self-assess their level of risk and distraction to fill gaps in the literature and facilitate standardized measurement of behavior. Initial validation detailed here focused on a population of young drivers most at risk for motor vehicle crashed and deaths. Survey development was carefully undertaken here with semi-structured interviews, pilot testing and testing of young adults in a major metropolitan area as well as in the Western and Eastern United States. Validity and reliability were measured in multiple ways. While there are multiple functions associated with cell phone use that can be distracting to a driver, we focused on typing and reading or viewing activities as those have been both extensively studied and demonstrated to have significant effect sizes in the simulator literature (Caird et al. 2014 ).

The resulting survey is brief and easy to administer. In automated testing, the full research survey required approximately four and a half minutes to complete and completing the 11-item DDS component takes around two minutes. In actual testing, all respondents were able to complete the survey.

This survey provides self-reported data from young US drivers in a relatively small sample size of 228 drivers age 18–24. Participants voluntarily took the survey so it is possible that the type of driver who took the survey may be more attuned to the risks of texting and driving or that there may be some other selection bias. Tradeoffs were made in the comprehensiveness of the questions selected to purposefully construct a brief instrument, with intentional elimination of questions on certain functions of cell phone use and other forms of distraction. For example, this study did not quantify the driving patterns of the respondents in the prior 30 days. Respondents who had not driven in the last 30 days were excluded. Because this study aimed to validate this survey among young people age 18–24, there are college students included who may have more limited driving patterns. Further studies are needed to validate this survey among drivers of all ages. This survey did not aim to quantify the number of texts or viewing time per mile. Further studies could be done to validate this survey against quantitative measures of viewing and reading behavior, which was beyond the scope of this study. However, the high Cronbach’s alpha and other characteristics suggest that the resulting brief instrument is well suited for large population studies that seek to limit respondent burden. Further research will likely lead to refinement in the scoring algorithms used. The performance of the DDS has not yet been studied in older age groups. Strengths of the study include good ethnic representation closely aligned with US census data and an anonymous format conducive to more accurate reporting of these behaviors.

The DDS is intended to be used to assess behavior patterns and risk and to evaluate the impact of public health interventions aimed at reducing texting and other cell phone-related distracted driving behaviors. The DDS score demonstrated strong performance characteristics in this validation study. Further research is needed to evaluate the instrument in larger and more diverse populations and to evaluate its sensitivity to change following interventions. Since a DDS score can be immediately generated at the time the DDS is completed, another area of research is whether the score itself may have value as an intervention.

The Distracted Driving Survey is a brief, reliable and validated measure to assess cell-phone related distraction while driving with a focus on texting and other viewing and writing activities. This survey is designed to provide additional information on frequency of common reading and viewing activities such as texting, email use, maps use, and social media viewing. The data are informative because different anti-distraction interventions target various aspects of cell phone utilization. For example, some anti-texting cell phone applications would not affect maps viewing, email viewing or writing, or social media use and therefore would not impact those behaviors. Further research is required to determine if these trends also hold true for older drivers. Higher DDS scores, indicating more distraction while driving, were associated with an increase in reported crashes in the prior 12 months in a dose–response relationship. Although this finding does not prove causality, the association is concerning and corroborates other studies demonstrating the risks of texting on crash rates on courses and simulators. This study confirmed prior reports of high rates of texting and driving in a young population, with more detailed reports of behavior on writing and reading text messages, the speeds at which these activities are performed, and respondents’ perception of risk. This measure may be used for larger studies to assess distracted driving behavior and to evaluate interventions aimed at reducing cell phone use, including texting, while driving. An improved understanding of the common cell phone functions used by young drivers should be used to inform the interventions aimed at reducing cell phone use while driving.

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RB, EG and RG conceived of the project and performed the data collection. RG performed statistical analyses with guidance and input from RB and RG, RB and RG wrote the first draft of the paper with subsequent revision from EG and RG. All authors approved of submission.

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Bergmark, R.W., Gliklich, E., Guo, R. et al. Texting while driving: the development and validation of the distracted driving survey and risk score among young adults. Inj. Epidemiol. 3 , 7 (2016). https://doi.org/10.1186/s40621-016-0073-8

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DOI : https://doi.org/10.1186/s40621-016-0073-8

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Texting while driving: A discrete choice experiment

Anne m. foreman.

a National Institute for Occupational Safety and Health, United States

Jonathan E. Friedel

Yusuke hayashi.

b Pennsylvania State University, Hazelton, United States of America

Oliver Wirth

CRediT authorship contribution statement

Texting while driving is one of the most dangerous types of distracted driving and contributes to a large number of transportation incidents and fatalities each year. Drivers text while driving despite being aware of the risks. Although some factors related to the decision to text while driving have been elucidated, more remains to be investigated in order to better predict and prevent texting while driving. To study decision making involved in reading a text message while driving, we conducted a discrete choice experiment with 345 adult participants recruited from Amazon’s Mechanical Turk. Participants were presented with multiple choice sets, each involving two different scenarios, and asked to choose the scenario in which they would be more likely to text while driving. The attributes of the scenarios were the relationship to the text-message sender, the road conditions, and the importance of the message. The attributes varied systematically across the choice sets. Participants were more likely to read a text message while driving if the sender of the message was a significant other, the message was perceived to be very important, and the participant was driving on rural roads. Discrete choice experiments offer a promising approach to studying decision making in drivers and other populations because they allow for an analysis of multiple factors simultaneously and the trade-offs among different choices.

1. Introduction

Distracted driving, or engaging in secondary tasks while driving, results in significant loss of life and monetary damages. In 2018, distracted driving resulted in 2841 deaths in the United States {National Highway Traffic Safety Administration, 2020 #2936}. Districted driving accounted for $39.7 billion or 16 % of all economic costs from motor vehicle crashes in 2010 ( Blincoe et al., 2015 ). Distracted driving can involve three types of distraction: visual, manual, or cognitive ( National Highway Traffic Safety Administration, 2017 ). Common distractions include reaching for an object (visual and manual), eating (manual), or talking to a passenger (cognitive). In 2017, 14 % of fatal crashes caused by distracted driving involved cell phone use ( National Center for Statistics and Analysis, 2019 ). Cell phone use while driving has been found to be just as dangerous as driving under the influence of alcohol. A driving simulations study comparing drivers talking on a phone and drivers with a blood alcohol concentration of 0.08 % found that the distracted drivers suffered performance deficits that were just as pro-found as the drivers under in the influence of alcohol ( Strayer et al., 2006 ).

One of the most pernicious forms of distracted driving is texting while driving (TWD) because it involves visual, manual, and cognitive distractions ( Alosco et al., 2012 ). During a simulated driving task, 66 % of drivers exhibited lane excursions while texting ( Rumschlag et al., 2015 ), and in another simulation study, TWD led to five times more crashes than driving without texting ( Bendak, 2015 ). A study examining the effects of texting on the simulated driving performance of young drivers found that in the TWD condition, drivers spent up to 400 % more time not looking at the road compared to conditions in which they were not texting ( Hosking et al., 2009 ). A meta-analysis of driving simulation studies concluded that reading and typing text messages while driving diverts attention away from the road, increases response time to hazards, and increases the risk of crashing ( Caird et al., 2014 ). Despite the risks, TWD remains prevalent. In a large naturalistic study, 23 % of drivers were observed using their phones and 9 % of drivers were observed TWD ( Kruger et al., 2018 ). Several surveys have also indicated a similar pattern. A survey of U.S. drivers found that for 30 days prior to the survey 48 % and 33 % reported reading or writing texts while driving, respectively ( Gliklich et al., 2016 ). In an online survey of drivers aged 18–64 years old, 31 % reported that they had read or sent text or e-mail messages while driving in the last 30 days ( Naumann and Dellinger, 2013 ).

Drivers text while driving despite being aware of the risks. College students reported TWD with relative frequency despite also agreeing that it is dangerous and should be illegal ( Harrison, 2011 ) and that it is just as dangerous as driving while legally intoxicated ( Terry and Terry, 2016 ). In another study surveying young drivers, the majority of respondents reported that initiating, replying to, and reading a text while driving were more dangerous than talking on a cell phone. The respondents in that study also rated reading a text while driving as a dangerous behavior (a mean score of 4.63 on a scale from 1 to 7), yet 92 % of the young drivers reported reading a text while driving ( Atchley et al., 2011 ). Research also suggests that drivers are more likely to text while driving farther from their destination ( Hayashi et al., 2018 , 2016 ), while stopped at a red light ( Bernstein and Bernstein, 2015 ), or while driving at slower speeds ( Oviedo-Trespalacios et al., 2017 ). Although some of these factors related to the decision to text while driving have been elucidated, more remains to be investigated in order to better predict and prevent texting while driving.

Behavioral economics has been one tool that has been used more recently to quantify some of the factors that affect the decision to text while driving. Behavioral economics has been defined as “the application of economic concepts and approaches to the molar study of individuals’ choices and decisions” ( Bickel et al., 2014 , p. 643). The behavioral economic process of discounting has been used to conceptualize TWD; discounting refers to the process by which delayed or probabilistic outcome loses its value as a function of the delay to or probability of the receipt of the outcome, respectively. Individuals who more steeply discount delayed outcomes are more likely to engage in text messaging while driving ( Hayashi et al., 2015 ). Additionally, discounting can quantify the likelihood with which people are willing to wait to respond to a text message when driving ( Hayashi et al., 2016 ). A similar study examined how the likelihood of a car crash affected the likelihood of waiting to respond to a text message ( Hayashi et al., 2018 ).

1.1. Discrete choice experiments

Although the decision to text while driving likely involves numerous factors, previous studies have only examined some of the factors, usually in isolation of other factors, or studies have compared multiple quantitative outcomes (e.g., distance and probability of a car crash). One method for examining choice behavior that is frequently used in other fields but has not been as broadly applied with safety-related choices is discrete choice experiments (DCEs). With a DCE, one can easily arrange choices among options that differ according to both qualitative and quantitative factors. The approach is also well-suited to choice contexts that include multiple factors that are inextricable or may potentially interact with one another. The goal of the present study was to assess the effects of multiple factors simultaneously on the likelihood of TWD by using a DCE.

DCEs are a behavioral economic approach to systematically assess individual preferences among products or services, and they have been widely implemented in marketing ( Chandukala et al., 2008 ), health economics ( de Bekker-Grob et al., 2012 ), and environmental valuation ( Hoyos, 2010 ), among other fields. For example, a participant in a DCE might be asked to choose between two different products (e.g., cell phones that differ in screen size, storage amount, and price) or two different services (e.g., diabetes treatment programs that differ in length, content, and cost). In a DCE, two or more alternatives presented to the participant are termed a “choice set”, and the characteristics or features of each alternative are termed “attributes”. A typical DCE is comprised of multiple choice sets in which the attributes of the alternatives are systematically varied. Analysis of the participants’ choice patterns across the choice sets can reveal the influence of the different attributes on choice. Additionally, DCEs can be used to understand any trade-offs among the attributes that affect preferences. Previous studies investigating texting while driving have not evaluated multiple qualitative variables (e.g., weather, road conditions, etc.) simultaneously, and the DCE is an appropriate methodology with which to do so.

DCEs were first proposed by McFadden (1974) and are rooted in the random utility theory ( Thurstone, 1927 ) of behavior. As it relates to DCEs, the random utility theory proposes that each choice alternative being considered has a latent “utility” and individuals will always choose the choice alternative that has the greatest utility. As utility is a latent construct, it is not directly observable, but it can be derived by studying choice patterns ( J. J. Louviere, 2001 ). Discrete choice experiments are designed to systematically vary the attributes associated with choice sets to determine the utility derived (or lost) by each attribute. The derived measures of utility consist of two components: systematic utility and random utility ( J. J. Louviere et al., 2010 ). The systematic component consists of the attributes of the alternatives and the characteristics of the individual. The random component consists of the factors responsible for the preference that cannot be identified (for example, if they went unmeasured) and measurement error that is an inherent part of any measurement procedure ( J. Louviere et al., 2000 ). The basic axiom of random utility theory is:

where U ni is the latent, unobservable utility that person n associates with choice alternative i , V ni is the systematic, explainable component of utility that individual n associates with choice alternative i , and ε ni is the random component.

1.2. Study objectives

The present study applied the behavioral economic framework of DCEs to study decision making involved in reading a text message while driving. Participants were presented with multiple choice sets, each involving two different scenarios, and asked to choose the scenario in which they would be more likely to text while driving. The attributes of the scenarios were varied systematically across the choice sets. To select the attributes to include, we conducted reviews of the relevant literature and consulted with subject matter experts. Previous research has found that individuals are more likely to respond to a text immediately rather than waiting to reply when the text sender is closer to them in social distance (e.g., a significant other) in both driving ( Foreman et al., 2019 ) and non-driving contexts ( Atchley and Warden, 2012 ). Other factors, such as the perceived importance of a phone call ( Nelson et al., 2009 ) and road conditions ( Atchley et al., 2011 ) have been found to be a strong predictor of talking on the phone while driving. Both middle-aged adults ( Engelberg et al., 2015 ) and younger adults ( Schroeder and Sims, 2014 ) report TWD at high rates while stopped at red lights. Therefore, we selected relationship to the text message sender, the perceived importance of the message, and road conditions as the attributes for the DCE.

In addition, we compared a sample of drivers who did and did not drive for work to assess whether this factor interacts with the aforementioned factors on the decision to text while driving. Motor vehicle crashes are the leading cause of workplace fatalities ( U.S. Department of Labor, 2019 ), and driver distraction has been shown to increase the likelihood of motor vehicle crashes among commercial large-truck drivers ( Peng and Boyle, 2012 ; Zhu et al., 2011 ) and increase the likelihood that a crash will be fatal ( Bunn et al., 2005 ). Employees who drive for organizations with stronger safety climates and greater management support for safe driving have reported lower rates of distracted driving ( Wills et al., 2006 ) and distracted-related crashes ( Swedler et al., 2015 ). It is conceivable that those who drive for work within an organization that emphasizes safe driving may engage in safer driving practices outside of work. Therefore, it would be important to evaluate whether there were any differences in choice behavior between those who did and did not drive for work in our sample.

The main objective of the present study was to assess the most important factors that influence drivers’ decisions to read a text while driving. Based on the existing evidence, we hypothesized that the relationship to the sender would have the greatest utility in the selection of choice scenarios, followed by the perceived importance of the message and the road conditions. The design and implementation of a DCE to study TWD allowed for a simultaneous assessment of multiple categorical attributes that may affect the decision to read a text while driving in contrast to previous studies in which small numbers of continuous variables were examined independently (e.g., distance to destination and probability of a crash). A secondary objective was to conduct an exploratory analysis of the choices of participants who report driving for work and assess whether their choices differed from those of participants who did not drive for work.

2.1. Participants

Participants ( N = 345) were recruited from Amazon’s Mechanical Turk (MTurk), an online crowdsourcing platform in which individuals are compensated for completing short tasks or surveys (termed human intelligence tasks; HIT). Although a sample size of 100 participants is typically sufficient for DCEs ( Pearmain and Kroes, 1990 ), we wanted ensure sufficient power for evaluating interaction effects. Participants were eligible for the HIT of this study if they lived in the United States, were over 18 years of age, possessed a U.S. driver’s license, and owned or possessed a cell phone capable of sending or receiving text messages. Participants self-reported on each of the eligibility criteria. Individuals who drive for work also had to be employed outside of completing tasks on MTurk and drove a vehicle for work other than commuting. The survey HIT was only available to those who consistently completed HITs with a high degree of accuracy (i.e., 95 % of previously completed HITs accepted as satisfactory). The survey also included questions that were attention checks (see below), and data from participants who did not pass attention checks or who did not answer all of the questions were dropped from the analysis ( n = 20). Participants were compensated $1.00 for successful completion of the survey. The research was conducted with approval from Pennsylvania State University’s Institutional Review Board.

2.2. Materials

The survey was hosted on Qualtrics (Qualtrics XM, Provo, UT). Various sections of the survey, described below, were presented to participants in a pseudorandom order, as determined by Qualtrics’s randomization function. The survey questions contained within each section were presented in a fixed order.

The survey consisted of demographic questions (age, gender, race, ethnicity, and education), a brief assessment of the respondent’s driving habits, and the DCE. Other items that were included in the survey but are not relevant for the present study were the Distracted Driving Survey ( Bergmark et al., 2016 ), the Barratt Impulsiveness Scale (BIS) ( Patton et al., 1995 ) and an eight-item delay discounting questionnaire ( Gray et al., 2014 ). The respondents were asked if they were employed outside of completing HITs on MTurk and whether they drove for work, not including commuting to and from home.

2.3. Discrete choice experiment

Another section of the survey consisted of a DCE. The DCE was constructed based on a well-cited guidance document (e.g., Johnson et al., 2013 ). As an important first step, we conducted a review of the relevant literature related to TWD and consulted subject matter experts to develop a list of potential attributes and levels. The list of potential attributes and levels was then refined to the final three attributes and associated levels (see Table 1 ).

The attributes, levels, and definitions.

Considering the small number of attributes and levels, it was not possible to include all of the attributes in each choice profile while still keeping the total number choice sets to a minimum number necessary for the analysis. One consideration for determining the array of choice sets and the arrangement of those choice sets (i.e., choice alternatives in each question) is that including pairwise comparisons of every permutation of attributes and levels is often impractical, and, therefore, researchers must rely on a limited array of profiles in the final DCE. For example, with our attributes and levels, if all possible combinations of attributes and levels in Table 1 were compared in a two-alternative design, then there would be 36 (4 * 3 * 3) possible profiles and 630 (36 * (36−1) / 2) possible combinations of two-alternative choice questions. There are several techniques to determine a limited array of profiles across choice sets that will lead to sufficient information for later statistical analysis ( Johnson et al., 2013 ; Street et al., 2008 ). We elected to use a Bayesian D-optimal design constructed by JMP software (SAS Institute, Cary, North Carolina, USA). The final design resulted in 2 blocks of 12 choice sets with 2 choice profiles per set; all three attributes were permitted to vary within a choice set. Participants were randomly assigned to see only one of the two blocks of choice sets. A screenshot of one question from the DCE is shown in Fig. 1 as an example.

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A screenshot of a DCE question presented to participants during the survey.

2.4. Data analysis

The analyses for the DCE portion of the survey was conducted with NLogit (Econometric Software, Inc., Plainview, NY). Sociodemographic characteristics that were included in the DCE analysis were modeled as non-random categorical parameters which were dummy coded. The levels for each attribute were also dummy coded. We first conducted analyses using the multinomial logit model based on the following equation: V = β 0 + β 1 RELATIONSHIP + β 2 ROAD + β 3 IMPORTANCE + ε, where V is the utility of a given driving scenario, β 0 is a constant reflecting a right- or left-side bias in scenario selection, and β 1 , β 2 , and β 3 are coefficients indicating the relative importance of each of the attributes. To account for the presence of preference heterogeneity across participants, we then estimated a mixed-logit model that included random effects as well as fixed effects because the random effects can often account for potential variation in relative preferences across participants ( Hauber et al., 2016 ). This is in contrast to the multinomial logit model, which assumes homogeneous preferences across participants ( Train, 2009 ). A mixed-logit model is similar to a mixed-effects regression in that some coefficients are fixed and others are random. The mixed-logit estimation relies on boot-strapped estimators. For our estimation, we specified 2000 Halton draws, indicating that the obtained choice data were a panel (i.e., multiple choices by each participant), and that there was unobserved preference heterogeneity. Initially, the mixed-logit models were estimated with random effects for each attribute and level. To determine the most parsimonious model, if the distribution of a random parameter was not statistically significant (at p < .05), then the specification of the parameter was reverted to a fixed effect. The final model (reported below) included N fixed effects and M random effects. We calculated marginal effects for each level based on the final mixed model ( Hensher et al., 2005 ).

The demographic characteristics of the respondents are shown in Table 2 . Approximately half of the respondents were male (51.1 %), white (83.1 %), non-Hispanic (92.6 %), and had at least some college education (91.4 %). Approximately 50 % of the sample drove for work.

Demographic Characteristics of the Sample.

The parameter estimates for the multinomial and mixed-logit models are in Table 3 . In the mixed logit model, all attribute parameters were initially specified as random linear parameters with normal distributions. In the initial mixed logit, only two of the random parameters (Very Important and Moderately Important) had significant standard deviations, indicating that there was significant variance in those parameters from the mean and thus a fixed parameter was not appropriate. Therefore, the attributes with significant standard deviations were retained as random parameters and attributes with non-significant standard deviations were reverted to fixed parameters. To assess the differences in choices between those who do and do not drive for work, the Drive for Work variable was included in the mixed-model as an interaction term. It is also important to note that the reported regression coefficients relate the attribute levels to the utility associated with responding to a text message that has that attribute. A positive regression coefficient indicates that utility is gained by responding to a text message with that feature and, all else being equal, on average a person is more likely to respond to a text message that has that feature. A negative regression coefficient indicates that utility is lost by responding to a text message with that feature and, all else being equal, on average a person is less likely to respond to a text message that has that feature. A significant coefficient ( p < .05) indicates that the attribute level had a significant effect on the decision to text while driving relative to the base case level, and the sign of the coefficient indicates the direction of the effect.

Beta coefficients and 95 % confidence intervals for the multinomial logit model (left) and mixed-logit model (right).

In the multinomial logit model, all of the regression coefficients were significant. With regard to the effects of the sender on the decision to read a text message while driving relative to the reference case (Casual Friend), Significant Other (β: 1.24, 95 % CI 1.08–1.39) had the greatest impact on utility, followed by Family Member (β: 1.21, 95 % CI 1.05–1.37) and Boss (β: 0.58, 95 % CI 0.43 to 0.72). In terms of the importance of the text message, in comparison to the reference case (Not Important), Very Important (β: 2.03, 95 % CI 1.86–2.20) messages had the greatest influence on utility followed by Moderately Important (β: 1.05, 95 % CI: 0.89–1.20) messages. In terms of the road condition, in comparison to the reference case (Rural), Highway (β: 0.40, 95 % CI 0.53 to 0.27) roads had the greatest influence on utility followed by City (β: 0.19, 95 % CI: 0.33 to 0.07) roads.

The pattern of results obtained with the mixed-logit model were similar to the pattern of results obtained with the multinomial logit model. In the mixed logit model, the coefficients for Moderately Important and Very Important were random effects indicating that there was preference heterogeneity across participants for the strength of the importance of the message in the decision to read a text while driving. This preference heterogeneity indicates that the pattern of results for the multinomial logit model, particularly the coefficients associated with Moderately Important and Very Important text messages, are not accurate.

For the Driving Status by attribute level interactions with the mixed-logit model, there were several significant interactions. In terms of sender, relative to the reference case (Not Drive for Work × Casual Friend), Drive for Work × Family Member (β: 0.86 95 % CI: 1.33 to 0.39) and Drive for Work × Significant Other (β: 0.75, 95 % CI: 1.28 to 0.22) had significantly less of an impact on the utility of a scenario. In terms of importance of the message, relative to the reference case (Not Drive for Work × Not Important), Drive for Work x Very Important (β: 0.75, 95 % CI: 1.28 to 0.22) and Drive for Work × Moderately Important (β: 0.75, 95 % CI: 1.28 to 0.22) also had significantly less of an influence on utility. Additionally, relative to the reference case (Not Drive for Work × Rural), Drive for Work × Highway (β: 0.51, 95 % CI: 0.08 to 0.93) and Drive for Work × City (β: 0.56, 95 % CI: 0.07–1.05) roads had significantly more of an impact on the utility of a texting scenario. The Drive for Work × Boss interaction coefficient was not statistically significant.

The marginal effect of each attribute level on the decision to read a text while driving—expressed as the change in the choice probability—is shown in Fig. 2 . These marginal probabilities indicate how each attribute level affects the likelihood of reading a text message relative to the basal level of reading a text message while driving. For example, a participant was 27 % more likely to read a text message if it was very important relative to their baseline likelihood of reading a text message. Thus, these marginal effects represent the translation of the mixed-logit utility function coefficients into how those attribute levels affect the choice to read a text message. The levels for Importance had the largest effect on choice and the Road Type had the smallest effect on choice. If the text in the scenario was Very Important, the scenario was 27 % more likely to be chosen. If the text in the scenario was Moderately or Not Important the scenario was 17 % more likely and 27 % less likely to be chosen, respectively. For the Relationship to the Sender attribute, if Family Member, Significant Other, or Boss was in the scenario, then that scenario was more likely to be chosen, but if Casual Friend was in the scenario, then it was 14 % less likely to be selected.

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The percent change in the probability of the choice to read a text while driving in comparison to the reference case (on a Rural Road when you receive a Not Important text from a Casual Friend).

4. Discussion

4.1. factors affecting the decision to text while driving.

In the present study, a DCE was used to investigate the decision making of drivers when faced with hypothetical TWD scenarios. When drivers were asked under which of two circumstances they are most likely to read a text message, the factor that had the greatest effect on choice was the importance of the message. These results are consistent with previous studies that found that the perceived importance of a phone call was a strong predictor of talking on a cellphone while driving ( Nelson et al., 2009 ).

The sender of the text message had a smaller but still significant effect on drivers’ decisions to read a text message. The present findings are consistent with other studies on social distance. For example, when the sender of a message or a caller was more socially distant, teen drivers were more likely to ignore texts ( McDonald and Sommers, 2015 ) and less likely to talk on the phone ( LaVoie et al., 2016 ) while driving. In a study that examined texting while driving and social distance, participants were more likely to text while driving as the sender became closer to them in social distance (e.g., dearest friend or relative) ( Foreman et al., 2019 ). The present findings are also consistent with texting behavior outside of a driving context, as a study by Atchley and Warden (2012) that participants were more willing to wait to reply to a text message from someone who was more socially distant compared to senders who were closer to them in social distance.

In the present study, drivers were less likely to read a text message in city traffic (i.e., stop-and-go) compared to highway or rural road conditions. These results contrast the finding that young adult drivers reported that they were more likely to read a text message when stopped at a stop sign as well as in “calm” road conditions, and less likely to read a text message on the highway or in “intense” road conditions ( Atchley et al., 2011 ). The divergence in our results from the prior study may have occurred because the road conditions in the present study included both road type (city, highway, or rural) and amount of traffic (heavy, moderate, or light). It is possible that participants may not have read or completely comprehended the definitions for the different levels of road conditions that were provided. If we had fully separated the type of road conditions (e.g., congested, not congested) from the actions of the cars on that road (e.g., stopped traffic, slow traffic, fast traffic, etc.) then the results may have been consistent with previous research.

The analyses comparing participants who drove for work and those who do not drive for work were exploratory, and thus our conclusions are also limited. The utility of the attributes in the DCE scenarios were significantly different for those who drove for work compared to those who did not drive for work based on the significant interactions between Drive for Work and the levels of the attributes. Compared to those who did not drive for work, participants who drove for work derived less utility from the relationship of the sender (Family Member and Significant Other) and the importance of the message (Very Important and Moderately Important) and derived greater utility from the road conditions (City/Heavy Traffic and Highway/Moderate Traffic). Although the difference in the coefficients between the two groups were statistically significant, the reasons for these differences are unknown. Future studies could ask about the rules concerning distracted driving at their jobs because the policies and practices within organizations related to TWD may affect workers’ driving behavior at work and outside of work. Perhaps stricter policies around cellphone use while driving within workplaces would encourage those who drive for work to behave more safely during non-work driving. Additionally, including the amount of a potential fine for being caught TWD as an attribute could have helped to differentiate the groups. It is possible that those who drive for work are less risk averse while driving than those who do not, and there is evidence that those who drive for work in a company vehicle are involved in more car accidents than those who use a personal vehicle ( Clarke et al., 2005 ; Downs et al., 1999 ). The DCE in the present study only asked about decision making associated with TWD during non-work activities (e.g., personal errands), whereas decision making may differ depending on whose car is being driven or whether the driver is currently working.

Although the present study was primarily a demonstration of the DCE methodology with drivers’ decision making, there may be some implications for public policy and guidance. The results indicate that the factor with the greatest effect on the decision to read a text message while driving was the importance of the message, and message importance has been a focus of some insurance campaigns. For example, in 2018, many Allstate Insurance slogans included the phrase, “No text is important enough to risk a life,” in their social media advertisements for that company’s Drivewise program ( Kevin Olp: Allstate Insurance, 2018 ). In relation to texting while driving for work, a study of a cohort of individuals who drive for work found that one of the predictors of safety performance was management commitment to fleet and driver safety ( Wills et al., 2006 ). Therefore, adherence to company texting while driving policies by managers and supervisors (e.g., not sending drivers text messages while they are known to be driving) may help ensure a safer climate for their driving workers.

4.2. Study limitations and future directions

There are several limitations to the present study. First, the amount of information that could be extracted from the DCE design was somewhat limited given that only three attributes were included in the study design. In any well-designed DCE, there is a tradeoff between the number of attributes and levels in the study design and the amount of cognitive burden imposed on the participants. If there are too many attributes, then the quality of the data may suffer because the participants are not attending to all of the attributes ( Alemu et al., 2013 ). Future research could investigate a greater number of attributes, perhaps by using a partial profile design in which only a select number of attributes are presented to each participant ( Kessels et al., 2011 ). Although these designs do require a relatively large number of participants, the design decreases the potential cognitive burden on the participants while still allowing the researchers to examine a larger number of attributes.

A second limitation was that all of the attributes studied were categorical variables. Including a continuous variable, like cost of a driving citation, permits the computation of equivalence calculations, such as maximum acceptable risk ( Bridges et al., 2011 ). In the present study, inclusion of a variable like a monetary fine or penalty for TWD could have expanded the present analysis beyond only ranking the importance of the attributes and levels. Future research could incorporate continuous variables, such as risk of a crash or the amount of a fine, into a discrete choice experiment to assess how much risk would be tolerated under different texting scenarios.

Third, there was no “opt out” option in which the participant could select neither scenario. In the present study participants were forced to make a choice between texting in two different scenarios. It is quite possible that some participants would not have responded to a text message under any condition in a more naturalistic or real-life situation. This may have limited the realism of the DCE choice sets because, in real life, drivers can always choose to not engage in cellphone use while driving. Future studies could expand the DCE methodology to include writing text messages and other types of cellphone use while driving and include continuous variables and opt-out options to increase both the potential implications of the findings and the realism of the DCE, respectively.

Additionally, our sample was relatively young (the mean age was 36.2) and was primarily composed of non-Hispanic whites who had at least some college education. Although the demographic characteristics of drivers were not a focus of the present study, future research could examine differences in decision making across diverse groups.

DCEs can further expand avenues of research on distracted driving. In addition to assessing driver decision making and behavior, DCEs can also be used to assess preferences among different driver monitoring technologies, such as smartphone applications that block calls and screen notifications of email and text messages while driving. For example, a DCE could evaluate the acceptability of attributes of potential new technologies, such as the ease of use and cost of a new smartphone application, related to decreasing or preventing cellphone use while driving, especially considering that some current technologies (e. g., software that blocks phone use while driving) have not been adopted by drivers outside of research study protocols ( Creaser et al., 2015 ; Funkhouser and Sayer, 2013 ). Similarly, DCEs can be used with relevant driver populations to evaluate the potential effectiveness of new public service campaigns in changing driver behavior (cf. Hayashi et al. (2019) ). The aspects of a potential campaign, such as the tagline, included statistics (e.g., X number of drivers crash due to texting), and message framing (e.g., negative or positive), could be manipulated and shown to samples of drivers to assess under which combination of attributes they would be more compelled to alter their texting-while-driving behavior.

4.3. Conclusions

The present study demonstrated the use of a DCE to examine decision making of drivers related to reading text messages while driving. When choosing between two hypothetical scenarios in which the relevant factors were evaluated simultaneously, participants were more likely to read a text message while driving if the sender of the message was a significant other, the message was perceived to be very important, and the participant was driving on rural roads. DCEs offer a promising approach to studying decision making in drivers and other populations because they allow for an analysis of multiple factors simultaneously and the trade-offs among different choices. DCE methods provide safety researchers with additional survey designs and analytical tools to more effectively assess factors that directly influence safety-related decisions and behavior, which would contribute to the development of effective prevention and intervention strategies for the problem.

This work was supported by a Research Development Grant, Office of Academic Affairs, Pennsylvania State University, Hazleton.

Publisher's Disclaimer: Disclaimer

The findings and conclusions in this report have not been formally disseminated by the National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention and should not be construed to represent any agency determination or policy.

Declaration of Competing Interest

The authors have no conflicts of interest to declare. All co-authors have seen and agree with the contents of the manuscript and there is no financial interest to report. The submission is original work and is not under review at any other publication.

Appendix B. Supplementary data

Supplementary material related to this article can be found, in the online version, at doi: https://doi.org/10.1016/j.aap.2020.105823 .

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Trump on Trial

Trump’s ‘eyes and ears’ for scandal.

A tabloid publisher testified how he helped Trump’s 2016 campaign.

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Donald Trump speaks to a crowd while flipping through a large stack of paper.

By Jesse McKinley

If last week’s process of selecting jurors was a kind of prologue to the criminal trial of Donald Trump, today marked the robust beginning of the first act, complete with introduction of the plot and foreshadowing of future drama.

The government’s first witness, David Pecker, the former publisher of The National Enquirer, had laid out the basics of his résumé and his style of “checkbook journalism” in about 30 minutes of testimony yesterday.

But today was a longer, more in-depth session, running about two and a half hours. Pecker set the stage for future testimony by other witnesses and plunged into a crucial element in the state’s case: that Trump worked with allies like Pecker on “catch-and-kill,” shorthand for buying and then burying potentially unflattering stories.

It was a fascinating dive, including Pecker’s narrative of agreeing during a meeting at Trump Tower in August 2015 — not long after Trump had descended his building’s golden escalator and launched his presidential campaign — to be the “eyes and ears” of the Trump campaign , keeping a lookout for rumors in what he called “the marketplace,” where salacious tales are bought and sold.

Pecker’s main contact in many of these dealings was Michael Cohen, Trump’s former lawyer and fixer, who is now expected to be a key witness against him.

In particular, Pecker said that he was to alert Cohen for stories involving women in Trump’s life, noting that the then-candidate was “well known as the most eligible bachelor” who “dated the most beautiful women.”

“I was the person who thought there would be a lot of women to come out to sell their stories,” Pecker said.

Pecker said that his arrangement with Trump also extended to writing negative stories about Republican opponents, including suggesting that Senator Ted Cruz was unfaithful to his wife and that Ben Carson had committed malpractice by leaving a sponge in a patient’s brain.

Pecker called the arrangement mutually beneficial, with Trump feeding him scoops about his show “The Apprentice” and driving reader interest: Trump was “a tremendous help” for his publications. “We followed him religiously,” he said.

Burying stories

Pecker’s testimony is apparently aimed at establishing Trump’s pattern of buying up unsavory stories, in line with the $130,000 payment Cohen made to Stormy Daniels, a porn star, in the weeks before the 2016 election. That payment, for which Cohen was later reimbursed, lies at the heart of the charges of falsification of business records that Trump faces. Trump denies the encounter with Daniels and the charges, calling them politically motivated.

Pecker also gave an example in which The National Enquirer paid off a doorman who previously worked at a Trump building, Dino Sajudin, who was looking to sell a story about an illegitimate child Trump was rumored to have fathered . The story turned out to be unfounded, but Pecker’s company, AMI, still paid $30,000 to shut it down.

And, in a potentially telling detail, after Trump won election in November 2016, a lawyer for Pecker’s company wrote the doorman and said he was free to shop the story — a detail supported by an email the prosecution introduced this afternoon.

Prosecutors also began to unspool the story of the Playboy model Karen McDougal, who said she had an affair with Trump, something he denies. In June 2016, Pecker sent his editor Dylan Howard to Los Angeles to interview McDougal to find out “what the details are.” Cohen repeatedly called Pecker, apparently worried about what McDougal intended to do, Pecker said.

“It looked like he was getting a lot of pressure to get the answer right away,” he said.

Trump has seemed largely unfazed: He listened to some legal proceedings today with his eyes closed, though his body language changed when Pecker started spilling details about the McDougal catch-and-kill deal. He began to move his head, squint and cross his arms over his chest.

And after leaving court, Trump vented — as he has before — that the trial is keeping him off the campaign trail, while President Biden is free to hold events across the country.

“This is all Biden,” the presumptive Republican nominee said, adding, “He’s out campaigning and I’m here in a courtroom, sitting up as straight as I can all day long.”

Trump’s grievances extend to a gag order, which forbids him from attacking prosecutors, jurors, witnesses and court staff, as well as their relatives and relatives of the judge in the case, Juan Merchan. This morning, prosecutors laid out 11 instances of what they saw as Trump violating that order, as recently as yesterday afternoon, when he spoke about Cohen in a statement he made in the hallway after court.

The judge did not immediately rule on those violations, though that decision is likely to land soon. And indications are that he will not favor the defense’s arguments that Trump is merely defending himself from political attacks.

In a memorable, and unpleasant, moment for the defense, Merchan told Todd Blanche, Trump’s lead attorney, that he was “losing all credibility with the court.”

With only a week or so in the books, and many weeks — and twists — yet to come, such an assertion cannot have been good news for Trump’s legal team.

Here’s the team we have reporting on the trial . During the proceedings, we’ll be sending you updates more frequently, including breaking news alerts and our weekly analysis on Thursdays.

Your questions

We’re asking readers what they’d like to know about the Trump cases: the charges, the procedure, the important players or anything else. You can send us your question by filling out this form.

How many reporters fit in the overflow room? Are they permitted to live-tweet, text or email from the courtroom or only the overflow room? Are any members of the public in attendance in either room? — Sonia Jacobsen, Seattle, Washington

Jesse: The media overflow room — a courtroom down the hall from the 15th-floor courtroom where Trump is being tried — sits about 150 people. During most of the trial days, it has been packed, particularly during jury selection when most of the seats in the actual courtroom were filled by prospective jurors. Since testimony began on Monday, that crush has been alleviated. About 50 news organizations have designated seats in courtroom. Posting on social media and texting on your phone is allowed in overflow, but phones can’t be used in the courtroom, except as hotspots. Photography, phone calls or recording are all strictly forbidden in both rooms. The public is also welcome, and people have been showing up to watch the trial, though space in the actual courtroom is limited.

What else to watch

On Thursday, the Supreme Court will hear arguments about Trump’s claim to be immune from prosecution in the election interference case in Washington.

Where does each criminal case stand?

Trump is at the center of at least four separate criminal investigations, at both the state and federal levels, into matters related to his business and political careers. Here is where each case stands .

Jesse McKinley is a Times reporter covering upstate New York, courts and politics. More about Jesse McKinley

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Ultimately, the thesis statement for this essay is that texting and driving is a dangerous and irresponsible behavior that must be addressed through a combination of education, legislation, and technological solutions in order to prevent further harm on the roadways. The impact of texting and driving is significant, as it has led to a high ...
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Introduction. Hook: Anyone can be a distracted driver, even those who are supposed to protect the public from harm. Texting while driving causes 3,000 teen traffic fatalities every year. Thesis Statement: In order to save lives and millions of dollars in property damage, drivers need to leave their phones out of sight. Body Paragraph #1. Define and call out to your audience
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texting is now ubiquitous, there remain gaps in the literature on texting and driving. A Deadly Wandering (2014), by Matt Richtel, examines texting and driving from both a behavioral and legal standpoint. Richtel's book introduces the topic of texting and driving, as well as studies relating to brain activity and attention, to a lay audience.
Texting while driving: the development and validation of the distracted
Background. Texting and other cell phone use while driving has emerged as a major contribution to teenage and young adult injury and death in motor vehicle collisions over the past several years (Bingham 2014; Wilson and Stimpson 2010).Young adults have been found to have higher rates of texting and driving than older drivers (Braitman and McCartt 2010; Hoff et al. 2013).
Distracted Driving
Texting or emailing while driving was more common among older students than younger students (see figure below) and more common among White students (44%) than Black (30%) or Hispanic students (35%). 4; Texting or emailing while driving was as common among students whose grades were mostly As or Bs as among students with mostly Cs, Ds, or Fs. 4
117 Distracted Driving Essay Topic Ideas & Examples
Banning Phone Use While Driving Will Save Lives. For instance, a driver may receive a phone call or make one, and while tending to the call, takes his mind of the road and increasing the chances of causing an accident. We will write. a custom essay specifically for you by our professional experts.
Should Texting While Driving Be Treated Like Drunken Driving?
Their lives collided with devastating speed in the coastal town of Keansburg just before 8:20 on a Wednesday morning, leaving the woman out for a walk fatally injured and the driver facing a ...
Texting While Driving: A Literature Review on Driving ...
Driving simulators (DSs) are powerful tools for identifying drivers' responses to different distracting factors in a safe manner. This paper aims to systematically review simulator-based studies to investigate what types of distractions are introduced when using the phone for texting while driving (TWD), what hardware and measures are used to ...
Texting While Driving: A Literature Review on Driving Simulator Studies
1. Introduction. Road safety is increasingly threatened by distracted driving. One of the highest-risk forms of distracted driving is texting while driving (TWD) [1,2] alongside talking on the phone while driving (TPWD) [3,4].After decades of research, the statistics show that the risks associated with TWD are very high [].According to the United Nations Road Safety statistical data [], car ...
Thesis Statement For Texting And Driving
1. Your life could end because someone made an unwise decision. 2. As a driver, you were doing everything right. You used your blinker, you went the speed limit and your phone did not distract you. 3.The individual, who was texting and driving, swerved into your lane and hit you doing 70 miles per.
Texting And Driving Essay Sample
Thesis Statements of Texting And Driving Essay. Texting and driving is a grave threat to our world today, but by taking the necessary precautions as drivers we can better ensure that it does not affect us or those close to us. Introduction of Texting And Driving Essay.
Texting While Driving Essay Examples
Browse our top essays on texting while driving and find tips to break the bad habit of texting while driving. Read more. The Information Resource For Accident Victims In Pennsylvania. 610-834-6030. 215-738-1791. Home; Practice Areas. ... The following four Texting and Driving Essay essays are the best entries:
Texting while driving: the development and validation of the distracted
Texting while driving and other cell-phone reading and writing activities are high-risk activities associated with motor vehicle collisions and mortality. This paper describes the development and preliminary evaluation of the Distracted Driving Survey (DDS) and score. Survey questions were developed by a research team using semi-structured interviews, pilot-tested, and evaluated in young ...
Texting and driving
C. Establishment of Ethos: I have credibility in talking about this subject because I am guilty of doing this, and have seen many friends, text while driving. D. Thesis Statement: Texting while driving is taking unnecessary lives of young ones throughout the nation, becoming one of the leading cause of preventable death in America.
Texting while driving: A discrete choice experiment
One of the most pernicious forms of distracted driving is texting while driving (TWD) because it involves visual, manual, and cognitive distractions ( Alosco et al., 2012 ). During a simulated driving task, 66 % of drivers exhibited lane excursions while texting ( Rumschlag et al., 2015 ), and in another simulation study, TWD led to five times ...
First Witness in Trump Trial Sets Stage for Future Testimonies
Posting on social media and texting on your phone is allowed in overflow, but phones can't be used in the courtroom, except as hotspots. Photography, phone calls or recording are all strictly ...