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Traffic Injury Prevention Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/gcpi20
Prevalence of and Attitudes About Distracted Driving in College Students a
a
a
b
a
Linda Hill , Jill Rybar , Tara Styer , Ethan Fram , Gina Merchant & Amelia Eastman a
a
University of California, San Diego, California
b
Albert Einstein College of Medicine, New York, New York Accepted author version posted online: 18 Aug 2014.
Click for updates To cite this article: Linda Hill, Jill Rybar, Tara Styer, Ethan Fram, Gina Merchant & Amelia Eastman (2015) Prevalence of and Attitudes About Distracted Driving in College Students, Traffic Injury Prevention, 16:4, 362-367, DOI: 10.1080/15389588.2014.949340 To link to this article: http://dx.doi.org/10.1080/15389588.2014.949340
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
Traffic Injury Prevention (2015) 16, 362–367 C Taylor & Francis Group, LLC Copyright ISSN: 1538-9588 print / 1538-957X online DOI: 10.1080/15389588.2014.949340
Prevalence of and Attitudes About Distracted Driving in College Students LINDA HILL1, JILL RYBAR1, TARA STYER1, ETHAN FRAM2, GINA MERCHANT1, and AMELIA EASTMAN1 1
University of California, San Diego, California Albert Einstein College of Medicine, New York, New York
2
Downloaded by [University of Birmingham] at 10:52 26 August 2015
Received 12 December 2013, Accepted 22 July 2014
Objective: To identify current distracted driving (DD) behaviors among college students, primarily those involving cell phone use, and elucidate the opinions of the students on the most effective deterrent or intervention for reducing cell phone use. Methods: Students enrolled at 12 colleges and universities were recruited to participate in an online, anonymous survey. Recruitment was done via school-based list-serves and posters. School sizes ranged from 476 to over 30,000. The validated survey included 38 questions; 17 were specifically related to distracted driving. Results: Four thousand nine hundred sixty-four participants completed the surveys; the average age was 21.8, 66% were female, 82.7% were undergraduates, and 47% were white/non-Hispanic. Additionally, 4,517 (91%) reported phoning and/or texting while driving; 4,467 (90%) of drivers said they talk on the phone while driving; 1,241 (25%) reported using a hands-free device “most of the time”; 4,467 (90%) of drivers reported texting while driving; 2,488 (50%) reported sending texts while driving on the freeway; 2,978 (60%) while in stop-and-go traffic or on city streets; and 4,319 (87%) at traffic lights. Those who drove more often were more likely to drive distracted. When asked about their capability to drive distracted, 46% said they were capable or very capable of talking on a cell phone and driving, but they felt that only 8.5% of other drivers were capable. In a multivariate model, 9 predictors explained 44% of the variance in DD, which was statistically significant, F (17, 4945) = 224.31; P < .0001; R2 = 0.44. The four strongest predictors (excluding driving frequency) were self-efficacy (i.e., confidence) in driving while multitasking (β = 0.37), perception of safety of multitasking while driving (β = 0.19), social norms (i.e., observing others multitasking while driving; β = 0.29), and having a history of crashing due to multitasking while driving (β = 0.11). Conclusions: Distracted driving is a highly prevalent behavior among college students who have higher confidence in their own driving skills and ability to multitask than they have in other drivers’ abilities. Drivers’ self-efficacy for driving and multitasking in the car, coupled with a greater likelihood of having witnessed DD behaviors in others, greatly increased the probability that a student would engage in DD. Most students felt that policies, such as laws impacting driving privilege and insurance rate increases, would influence their behavior. Keywords: distracted driving, injury prevention, college students, cell phones
Introduction Distracted driving (DD) is defined by NHTSA as any activity that takes a driver’s attention away from the task of driving to focus on some other activity instead (NHTSA 2013) and has emerged as a major danger on today’s roadways. It contributes to roughly 17% of all injury crashes and 10% of fatal crashes in the United States (NHTSA 2013). Fatalities due to DD increased 28% from 2005 to 2008 (Wilson and Stimpson 2010) and 1.9% from 2010 to 2011 (NHTSA 2012a), though accurate estimates of DD are hampered by measurement biases, including self-reporting, and changes in surveillance. Associate Editor Joel Stitzel oversaw the review of this article. Address correspondence to Jill Rybar, Department of Family and Preventive Medicine, University of California, San Diego, 9500 Gilman Drive, MC #0811, La Jolla, CA 92093–9550. E-mail: [email protected]
Distractions from secondary in-vehicle activities include visual, manual, and cognitive distraction. Handheld phones and texting can involve all 3 distractions. Estimates of crash risk with distractions have used simulators, phone records, on-road testing, and naturalistic studies (Horrey and Wickens 2006; Ishigami and Klein 2009). Studies using cell phone records have shown that cell phone use while driving increases the risk of a collision by 4-fold when compared to a similar group of drivers not using their cell phones (McEvoy et al. 2005; Redelmeier and Tibshirani 1997). Driving performance studies done in simulators and in naturalistic settings have found hands-free devices to be as dangerous as handheld cell devices (Horrey and Wickens 2006; Ishigami and Klein 2009; Patten et al. 2004; Strayer et al. 2006). Cognitive distractions have been documented in both hands-free and handheld phone use, speaking to passengers, and speech to text in simulation studies (Strayer et al. 2013). Other simulation studies found associations with a decrease in reaction time (Strayer
Downloaded by [University of Birmingham] at 10:52 26 August 2015
Distracted Driving in College Students et al. 2006), a significant decrease in activation of brain regions involved in spatial processing (Just et al. 2007), and visual processing (Borowsky et al. 2014; Strayer and Drews 2007). A recent naturalistic study combining crash and near-crash data found distracted novices at much higher crash and near crash risk than experienced drivers; both groups had lower crash risks with cell phone talking only (hands-free; Fitch et al. 2013). Text messaging impairs driving ability even more significantly (Hosking et al. 2009) and increases the risk of crash or near-crash by at least 2 times (Fitch et al. 2013). As cell phone ownership has increased in the last 10 years, the frequency of cell phone use while driving has also increased (Governor’s Highway Safety Association 2010). Approximately 4 of every 5 Americans now own a cell phone, and 48% of drivers reported that they answer their phone while driving, and 24% report that they initiate calls (AAA Foundation 2008; Schroeder 2013). Distraction is most prevalent in drivers under the age of 20, with ages 20–29 being the second most distracted group (NHTSA 2009). Drivers younger than 30 years old are estimated to be distracted 16% of the time they spend driving (Farmer et al. 2010). The United States has higher DD rates compared to most European countries; a Centers for Disease Control report that found 69% of US drivers aged 18–64 used a cell phone while driving in the last 30 days, and 31% had texted while driving (Naumann et al. 2013). To better characterize the prevalence of and attitudes toward DD, we conducted an exploratory survey of college students in 2011. The survey’s purpose was to identify current DD behaviors among college-age adults, primarily those involving cell phone use, and elucidate the opinions of college students on the most effective deterrent or intervention for reducing cell phone use. A previous study found that whereas 68% of drivers ages 18–20 are willing to answer incoming phone calls, about 4 in 5 of those drivers believe that texting makes a difference to their driving performance (NHTSA 2012b), and another study found that 76.5% of licensed drivers ages 19–24 believe that drivers talking on cell phones pose a somewhat or very serious threat to safety (AAA Foundation 2013).
Methods Survey Design The survey questions were based on a review of the literature pertaining to the identification of DD characteristics, predictors, attitudes, and basic demographic information. We added questions for reliability and social desirability bias to take into account the tendency of subjects to give socially desirable responses instead of responses that reflect their true feelings (Krumpal 2013), for a total of 38 questions. We administered the survey to 10 volunteers, who were University of California, San Diego (UCSD), students and staff working in the same building on campus to assess clarity. This content assessment addressed issues related to clarity and accuracy of the questions. As a result, we made changes to the survey and, based on feedback, added one question. Institutional Review Board approval was obtained from UCSD with
363 permission to recruit the other participating universities and colleges. Creation of the DD Scale To quantify DD behavior, we created a total distracted driving (TDD) scale based on the Department of Transportation (DOT) definition of DD as stated in the Introduction The TDD scale consists of 17 items. Seven questions ask about talking on the phone, 5 questions ask about texting, and 5 questions ask about using specific devices while driving, such as Global Positioning System, apps, computers, etc. Six Likert scale answer choices to the question “What percentage of the time” does the respondent engage in the question-related behavior (texting, talking, etc.), including never, ≤10%, 11–25%, 26–50%, 51–74%, and ≥75% of the time, were used in the TDD scale. These estimates by the respondents were used to reflect the proportion of time they engage in distracted driving behavior on average trips, though not absolute times. The scale constructs and answer choices were consistent with other validated scales where people estimate a percentage of their time (Usdan et al. 2004). Additional Survey Piloting Between September 19, 2011, and September 23, 2011, 134 participants completed a pen-and-paper pilot of the survey. All respondents were prescreened for eligibility based on 4 qualifying questions. These questions were as follows: (1) Are you between the ages of 18–29? (2) Do you drive a vehicle? (3) Do you use a cell phone? and (4) Are you a current student at a San Diego college, university, or trade school? The same inclusion criteria were used in the final study. The inclusion of ages 18 and 29 years was chosen to allow researchers to equate findings within similar demographic studies on distracted driving (Copeland 2012). TREDS (Training, Research, and Education for Driving Safety) interns recruited students on Library Walk, a main campus thoroughfare at UCSD, between the hours of 9 a.m. and noon on days when the university was in session. In return for a 2-GB flash drive, students were asked to complete a paper version of the online survey. Participants were encouraged to ask about any question that they found unclear, but inquiries about the purpose or reason for each question were not answered. The pilot survey feedback allowed for minor changes to be made to the sentence structure to improve clarity of the questions. Cronbach’s alpha was calculated on the full survey (see below) but not on the pilot testing, which focused on content clarity. Recruitment Table 1 lists the schools in order of the time when students were first contacted about the survey by e-mail or flyer distribution. Students at UCSD were the first contacted, and students at Alliant University were the last. The number of undergraduates is intended to serve as a guide to the number of students who potentially could have been exposed to posters (note that UCSD has 5,513 graduate students and San Diego State
364
Hill et al.
Table 1. Number of undergraduate students at participating schools School
Downloaded by [University of Birmingham] at 10:52 26 August 2015
University of California, San Diego San Diego State University University of San Diego Cuyamaca College Grossmont College Coleman University Miramar College Mesa College San Diego City College California State University San Marcos Palomar College Alliant University
Number of undergraduates 22,663 27,537 8,317 9,000 17,359 476 10,000 24000 20,000 10,276 30,000 4,000
University [SDSU] has 6,253 graduate students). A total of 3,800 UCSD students received an e-mail with a link to the survey, and all 27,537 undergraduate and 6,253 graduate students at SDSU received an e-mail. All students had potential access to fliers that listed the web address for the survey.
Table 2. Demographics of respondents Demographic variable Mean age Gender Male Female Student status Undergraduate Graduate Trade Ethnicity American Indian or Alaskan Native Asian Black or African American Hispanic or Latino Native Hawaiian or Other Pacific Islander White Multiethnic Decline to state
N = 4,964 (100%) 21.8 years old 1,642 (34%) 3,291 (66%) 4,107 (83%) 856 (17%) 1 ( Patten C, Kircher A, Ostund J, Nilsson L. Using mobile telephones: cognitive workload and attention resource allocation. Accid Annal Prev. 2004;36:341–350. ¨ Poysti L, Rajalin S, Summala H. Factors influencing the use of cellular (mobile) phone during driving and hazards while using it. Accid Annal Prev. 2005;37:47–51. Redelmeier DA, Tibshirani RJ. Association between cellular-telephone calls and motor vehicle collisions. N Engl J Med. 1997;336: 453–458. Schroeder P, Meyers M, Kostyniuk L. National Survey on Distracted Driving Attitudes and Behaviors—2012. Washington, DC: NHTSA; 2013. Report No. DOT HS 811 729. Strayer D, Cooper J, Turrill J, Coleman J, Medeiros-Ward N, Biondi F. Measuring cognitive distraction in the automobile. 2013. Available at: https://www.aaafoundation.org/sites/default/files/MeasuringCognitiveDistractions.pdf. Accessed April 14, 2014. Strayer D, Drews F. Cell-phone induced driver distraction. Curr Dir Psychol Sci. 2007;16(3):128–131. Strayer D, Drews F, Crouch D. A comparison of the cell phone driver and the drunk driver. Hum Factors. 2006;48:381–389. Tison J, Chaudhary N, Cosgrove L. National Phone Survey on Distracted Driving Attitudes and Behaviors. Washington, DC: NHTSA; 2011. Report No. DOT HS 811 555. Usdan SL, Schumacher JE, Bernhardt JM. Impaired driving behaviors among college students: a comparison of web-based daily assessment and retrospective timeline follow back. J Alcohol Drug Educ. 2004;48:34–50. White MJ, Cunningham LC, Titchener K. Young drivers’ optimism bias for accident risk and driving skill: accountability and insight experience manipulations. Accid Annal Prev. 2011;43:1309– 1315. Wilson FA, Stimpson JP. Trends in fatalities from distracted driving in the United States: 1999–2008. Am J Public Health. 2010; 100:2213–2219.
Traffic Injury Prevention Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/gcpi20
Prevalence of and Attitudes About Distracted Driving in College Students a
a
a
b
a
Linda Hill , Jill Rybar , Tara Styer , Ethan Fram , Gina Merchant & Amelia Eastman a
a
University of California, San Diego, California
b
Albert Einstein College of Medicine, New York, New York Accepted author version posted online: 18 Aug 2014.
Click for updates To cite this article: Linda Hill, Jill Rybar, Tara Styer, Ethan Fram, Gina Merchant & Amelia Eastman (2015) Prevalence of and Attitudes About Distracted Driving in College Students, Traffic Injury Prevention, 16:4, 362-367, DOI: 10.1080/15389588.2014.949340 To link to this article: http://dx.doi.org/10.1080/15389588.2014.949340
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
Traffic Injury Prevention (2015) 16, 362–367 C Taylor & Francis Group, LLC Copyright ISSN: 1538-9588 print / 1538-957X online DOI: 10.1080/15389588.2014.949340
Prevalence of and Attitudes About Distracted Driving in College Students LINDA HILL1, JILL RYBAR1, TARA STYER1, ETHAN FRAM2, GINA MERCHANT1, and AMELIA EASTMAN1 1
University of California, San Diego, California Albert Einstein College of Medicine, New York, New York
2
Downloaded by [University of Birmingham] at 10:52 26 August 2015
Received 12 December 2013, Accepted 22 July 2014
Objective: To identify current distracted driving (DD) behaviors among college students, primarily those involving cell phone use, and elucidate the opinions of the students on the most effective deterrent or intervention for reducing cell phone use. Methods: Students enrolled at 12 colleges and universities were recruited to participate in an online, anonymous survey. Recruitment was done via school-based list-serves and posters. School sizes ranged from 476 to over 30,000. The validated survey included 38 questions; 17 were specifically related to distracted driving. Results: Four thousand nine hundred sixty-four participants completed the surveys; the average age was 21.8, 66% were female, 82.7% were undergraduates, and 47% were white/non-Hispanic. Additionally, 4,517 (91%) reported phoning and/or texting while driving; 4,467 (90%) of drivers said they talk on the phone while driving; 1,241 (25%) reported using a hands-free device “most of the time”; 4,467 (90%) of drivers reported texting while driving; 2,488 (50%) reported sending texts while driving on the freeway; 2,978 (60%) while in stop-and-go traffic or on city streets; and 4,319 (87%) at traffic lights. Those who drove more often were more likely to drive distracted. When asked about their capability to drive distracted, 46% said they were capable or very capable of talking on a cell phone and driving, but they felt that only 8.5% of other drivers were capable. In a multivariate model, 9 predictors explained 44% of the variance in DD, which was statistically significant, F (17, 4945) = 224.31; P < .0001; R2 = 0.44. The four strongest predictors (excluding driving frequency) were self-efficacy (i.e., confidence) in driving while multitasking (β = 0.37), perception of safety of multitasking while driving (β = 0.19), social norms (i.e., observing others multitasking while driving; β = 0.29), and having a history of crashing due to multitasking while driving (β = 0.11). Conclusions: Distracted driving is a highly prevalent behavior among college students who have higher confidence in their own driving skills and ability to multitask than they have in other drivers’ abilities. Drivers’ self-efficacy for driving and multitasking in the car, coupled with a greater likelihood of having witnessed DD behaviors in others, greatly increased the probability that a student would engage in DD. Most students felt that policies, such as laws impacting driving privilege and insurance rate increases, would influence their behavior. Keywords: distracted driving, injury prevention, college students, cell phones
Introduction Distracted driving (DD) is defined by NHTSA as any activity that takes a driver’s attention away from the task of driving to focus on some other activity instead (NHTSA 2013) and has emerged as a major danger on today’s roadways. It contributes to roughly 17% of all injury crashes and 10% of fatal crashes in the United States (NHTSA 2013). Fatalities due to DD increased 28% from 2005 to 2008 (Wilson and Stimpson 2010) and 1.9% from 2010 to 2011 (NHTSA 2012a), though accurate estimates of DD are hampered by measurement biases, including self-reporting, and changes in surveillance. Associate Editor Joel Stitzel oversaw the review of this article. Address correspondence to Jill Rybar, Department of Family and Preventive Medicine, University of California, San Diego, 9500 Gilman Drive, MC #0811, La Jolla, CA 92093–9550. E-mail: [email protected]
Distractions from secondary in-vehicle activities include visual, manual, and cognitive distraction. Handheld phones and texting can involve all 3 distractions. Estimates of crash risk with distractions have used simulators, phone records, on-road testing, and naturalistic studies (Horrey and Wickens 2006; Ishigami and Klein 2009). Studies using cell phone records have shown that cell phone use while driving increases the risk of a collision by 4-fold when compared to a similar group of drivers not using their cell phones (McEvoy et al. 2005; Redelmeier and Tibshirani 1997). Driving performance studies done in simulators and in naturalistic settings have found hands-free devices to be as dangerous as handheld cell devices (Horrey and Wickens 2006; Ishigami and Klein 2009; Patten et al. 2004; Strayer et al. 2006). Cognitive distractions have been documented in both hands-free and handheld phone use, speaking to passengers, and speech to text in simulation studies (Strayer et al. 2013). Other simulation studies found associations with a decrease in reaction time (Strayer
Downloaded by [University of Birmingham] at 10:52 26 August 2015
Distracted Driving in College Students et al. 2006), a significant decrease in activation of brain regions involved in spatial processing (Just et al. 2007), and visual processing (Borowsky et al. 2014; Strayer and Drews 2007). A recent naturalistic study combining crash and near-crash data found distracted novices at much higher crash and near crash risk than experienced drivers; both groups had lower crash risks with cell phone talking only (hands-free; Fitch et al. 2013). Text messaging impairs driving ability even more significantly (Hosking et al. 2009) and increases the risk of crash or near-crash by at least 2 times (Fitch et al. 2013). As cell phone ownership has increased in the last 10 years, the frequency of cell phone use while driving has also increased (Governor’s Highway Safety Association 2010). Approximately 4 of every 5 Americans now own a cell phone, and 48% of drivers reported that they answer their phone while driving, and 24% report that they initiate calls (AAA Foundation 2008; Schroeder 2013). Distraction is most prevalent in drivers under the age of 20, with ages 20–29 being the second most distracted group (NHTSA 2009). Drivers younger than 30 years old are estimated to be distracted 16% of the time they spend driving (Farmer et al. 2010). The United States has higher DD rates compared to most European countries; a Centers for Disease Control report that found 69% of US drivers aged 18–64 used a cell phone while driving in the last 30 days, and 31% had texted while driving (Naumann et al. 2013). To better characterize the prevalence of and attitudes toward DD, we conducted an exploratory survey of college students in 2011. The survey’s purpose was to identify current DD behaviors among college-age adults, primarily those involving cell phone use, and elucidate the opinions of college students on the most effective deterrent or intervention for reducing cell phone use. A previous study found that whereas 68% of drivers ages 18–20 are willing to answer incoming phone calls, about 4 in 5 of those drivers believe that texting makes a difference to their driving performance (NHTSA 2012b), and another study found that 76.5% of licensed drivers ages 19–24 believe that drivers talking on cell phones pose a somewhat or very serious threat to safety (AAA Foundation 2013).
Methods Survey Design The survey questions were based on a review of the literature pertaining to the identification of DD characteristics, predictors, attitudes, and basic demographic information. We added questions for reliability and social desirability bias to take into account the tendency of subjects to give socially desirable responses instead of responses that reflect their true feelings (Krumpal 2013), for a total of 38 questions. We administered the survey to 10 volunteers, who were University of California, San Diego (UCSD), students and staff working in the same building on campus to assess clarity. This content assessment addressed issues related to clarity and accuracy of the questions. As a result, we made changes to the survey and, based on feedback, added one question. Institutional Review Board approval was obtained from UCSD with
363 permission to recruit the other participating universities and colleges. Creation of the DD Scale To quantify DD behavior, we created a total distracted driving (TDD) scale based on the Department of Transportation (DOT) definition of DD as stated in the Introduction The TDD scale consists of 17 items. Seven questions ask about talking on the phone, 5 questions ask about texting, and 5 questions ask about using specific devices while driving, such as Global Positioning System, apps, computers, etc. Six Likert scale answer choices to the question “What percentage of the time” does the respondent engage in the question-related behavior (texting, talking, etc.), including never, ≤10%, 11–25%, 26–50%, 51–74%, and ≥75% of the time, were used in the TDD scale. These estimates by the respondents were used to reflect the proportion of time they engage in distracted driving behavior on average trips, though not absolute times. The scale constructs and answer choices were consistent with other validated scales where people estimate a percentage of their time (Usdan et al. 2004). Additional Survey Piloting Between September 19, 2011, and September 23, 2011, 134 participants completed a pen-and-paper pilot of the survey. All respondents were prescreened for eligibility based on 4 qualifying questions. These questions were as follows: (1) Are you between the ages of 18–29? (2) Do you drive a vehicle? (3) Do you use a cell phone? and (4) Are you a current student at a San Diego college, university, or trade school? The same inclusion criteria were used in the final study. The inclusion of ages 18 and 29 years was chosen to allow researchers to equate findings within similar demographic studies on distracted driving (Copeland 2012). TREDS (Training, Research, and Education for Driving Safety) interns recruited students on Library Walk, a main campus thoroughfare at UCSD, between the hours of 9 a.m. and noon on days when the university was in session. In return for a 2-GB flash drive, students were asked to complete a paper version of the online survey. Participants were encouraged to ask about any question that they found unclear, but inquiries about the purpose or reason for each question were not answered. The pilot survey feedback allowed for minor changes to be made to the sentence structure to improve clarity of the questions. Cronbach’s alpha was calculated on the full survey (see below) but not on the pilot testing, which focused on content clarity. Recruitment Table 1 lists the schools in order of the time when students were first contacted about the survey by e-mail or flyer distribution. Students at UCSD were the first contacted, and students at Alliant University were the last. The number of undergraduates is intended to serve as a guide to the number of students who potentially could have been exposed to posters (note that UCSD has 5,513 graduate students and San Diego State
364
Hill et al.
Table 1. Number of undergraduate students at participating schools School
Downloaded by [University of Birmingham] at 10:52 26 August 2015
University of California, San Diego San Diego State University University of San Diego Cuyamaca College Grossmont College Coleman University Miramar College Mesa College San Diego City College California State University San Marcos Palomar College Alliant University
Number of undergraduates 22,663 27,537 8,317 9,000 17,359 476 10,000 24000 20,000 10,276 30,000 4,000
University [SDSU] has 6,253 graduate students). A total of 3,800 UCSD students received an e-mail with a link to the survey, and all 27,537 undergraduate and 6,253 graduate students at SDSU received an e-mail. All students had potential access to fliers that listed the web address for the survey.
Table 2. Demographics of respondents Demographic variable Mean age Gender Male Female Student status Undergraduate Graduate Trade Ethnicity American Indian or Alaskan Native Asian Black or African American Hispanic or Latino Native Hawaiian or Other Pacific Islander White Multiethnic Decline to state
N = 4,964 (100%) 21.8 years old 1,642 (34%) 3,291 (66%) 4,107 (83%) 856 (17%) 1 ( Patten C, Kircher A, Ostund J, Nilsson L. Using mobile telephones: cognitive workload and attention resource allocation. Accid Annal Prev. 2004;36:341–350. ¨ Poysti L, Rajalin S, Summala H. Factors influencing the use of cellular (mobile) phone during driving and hazards while using it. Accid Annal Prev. 2005;37:47–51. Redelmeier DA, Tibshirani RJ. Association between cellular-telephone calls and motor vehicle collisions. N Engl J Med. 1997;336: 453–458. Schroeder P, Meyers M, Kostyniuk L. National Survey on Distracted Driving Attitudes and Behaviors—2012. Washington, DC: NHTSA; 2013. Report No. DOT HS 811 729. Strayer D, Cooper J, Turrill J, Coleman J, Medeiros-Ward N, Biondi F. Measuring cognitive distraction in the automobile. 2013. Available at: https://www.aaafoundation.org/sites/default/files/MeasuringCognitiveDistractions.pdf. Accessed April 14, 2014. Strayer D, Drews F. Cell-phone induced driver distraction. Curr Dir Psychol Sci. 2007;16(3):128–131. Strayer D, Drews F, Crouch D. A comparison of the cell phone driver and the drunk driver. Hum Factors. 2006;48:381–389. Tison J, Chaudhary N, Cosgrove L. National Phone Survey on Distracted Driving Attitudes and Behaviors. Washington, DC: NHTSA; 2011. Report No. DOT HS 811 555. Usdan SL, Schumacher JE, Bernhardt JM. Impaired driving behaviors among college students: a comparison of web-based daily assessment and retrospective timeline follow back. J Alcohol Drug Educ. 2004;48:34–50. White MJ, Cunningham LC, Titchener K. Young drivers’ optimism bias for accident risk and driving skill: accountability and insight experience manipulations. Accid Annal Prev. 2011;43:1309– 1315. Wilson FA, Stimpson JP. Trends in fatalities from distracted driving in the United States: 1999–2008. Am J Public Health. 2010; 100:2213–2219.
