title: What drives technology-based distractions? A structural equation model on social-psychological factors of technology-based driver distraction engagement.
abstract: BACKGROUND
  With the proliferation of new mobile and in-vehicle technologies, understanding the motivations behind a driver's voluntary engagement with such technologies is crucial from a safety perspective, yet is complex. Previous literature either surveyed a large number of distractions that may be diverse, or too focuses on one particular activity, such as cell phone use. Further, earlier studies about social-psychological factors underlying driver distraction tend to focus on one or two factors in-depth, and those that examine a more comprehensive set of factors are often limited in their analyses methods.
  
  
  OBJECTIVE
  The present work considers a wide array of social-psychological factors within a structural equation model to predict their influence on a focused set of technology-based distractions. A better understanding of these facilitators can enhance the design of distraction mitigation strategies.
  
  
  METHODS
  We analysed survey responses about three technology-based driver distractions: holding phone conversations, manually interacting with cell phones, and adjusting the settings of in-vehicle technology, as well as responses on five social-psychological factors: attitude, descriptive norm, injunctive norm, technology inclination, and a risk/sensation seeking personality. Using data collected from 525 drivers (ages: 18-80), a structural equation model was built to analyse these social-psychological factors as latent variables influencing self-reported engagement in these three technology-based distractions.
  
  
  RESULTS
  Self-reported engagement in technology-based distractions was found to be largely influenced by attitudes about the distractions. Personality and social norms also played a significant role, but technology inclination did not. A closer look at two age groups (18-30 and 30+) showed that the effect of social norms, especially of injunctive norm (i.e., perceived approvals), was less prominent in the 30+ age group, while personality remained a significant predictor for the 30+ age group but marginally significant for the younger group.
  
  
  CONCLUSIONS
  Findings from this work provide insights into the social-psychological factors behind intentional engagement in technology-based distractions and in particular suggesting that these factors may be sensitive to demographic differences.
authors.affiliation: University of Toronto, Department of Mechanical and Industrial Engineering, Canada.
authors.forename: Huei-Yen Winnie
authors.initials: HY
authors.lastname: Chen
authors.affiliation: University of Toronto, Department of Mechanical and Industrial Engineering, Canada. Electronic address: donmez@mie.utoronto.ca.
authors.forename: Birsen
authors.initials: B
authors.lastname: Donmez
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001288:Attention; D001290:Attitude; D001334:Automobile Driving / Q000523:psychology*; D040421:Cell Phone; D000071826:Distracted Driving / Q000523:psychology*; D005260:Female; D040362:Geographic Information Systems / Q000295:instrumentation; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010551:Personality; D011845:Radio; D012449:Safety; D066262:Social Norms; D011795:Surveys and Questionnaires; D060145:Text Messaging; D055815:Young Adult
keywords: Attitude; Cell phones; Distracted driving; Personality; SEM; Social norms