ObjectivesThe objective of the present work was to study the impact of technological and social distraction on cautionary behaviours and crossing times in pedestrians.MethodsPedestrians were observed at 20 high-risk intersections during 1 of 3 randomly assigned time windows in 2012. Observers recorded demographic and behavioural information, including use of a mobile device (talking on the phone, text messaging, or listening to music). We examined the association between distraction and crossing behaviours, adjusting for age and gender. All multivariate analyses were conducted with random effect logistic regression (binary outcomes) and random effect linear regression (continuous outcomes), accounting for clustering by site.ResultsObservers recorded crossing behaviours for 1102 pedestrians. Nearly one-third (29.8%) of all pedestrians performed a distracting activity while crossing. Distractions included listening to music (11.2%), text messaging (7.3%) and using a handheld phone (6.2%). Text messaging, mobile phone use and talking with a companion increased crossing time. Texting pedestrians took 1.87 additional seconds (18.0%) to cross the average intersection (3.4 lanes), compared to undistracted pedestrians. Texting pedestrians were 3.9 times more likely than undistracted pedestrians to display at least 1 unsafe crossing behaviour (disobeying the lights, crossing mid-intersection, or failing to look both ways). Pedestrians listening to music walked more than half a second (0.54) faster across the average intersection than undistracted pedestrians.ConclusionsDistracting activity is common among pedestrians, even while crossing intersections. Technological and social distractions increase crossing times, with text messaging associated with the highest risk. Our findings suggest the need for intervention studies to reduce risk of pedestrian injury.

This study assessed marijuana-related content posted by adolescents on Twitter and examined content variation before and after the 2012 U.S. election legalizing recreational use in two states. For two 3-week periods occurring 6 months before and after the election, a 1% random sample was obtained of all tweets matching a set of marijuana-related queries. Original content was separated from reposted content (retweets), and foreign language tweets and those not related to marijuana were excluded. Using a structured codebook, tweet content was categorized (e.g., mention of personal marijuana use, parents' views, perceived effects.) Self-reported age was extracted from tweet metadata when available. Chi-square tests were used to assess differences in content by whether the user self-identified as an adolescent and to compare content pre- versus post-election. The full sample consisted of 71,901 tweets. After excluding nonrelevant tweets and separating original tweets from retweets, the analytic sample included 36,969 original tweets. A majority (65.6%) of original tweets by adolescents (n=1,928) reflected a positive attitude toward marijuana, and 42.9% indicated personal use. Of adolescents' tweets that mentioned parents, 36.0% of tweets indicated parental support for the adolescent's marijuana use. Tweets about personal marijuana use increased from 2012 to 2013, as did positive perceptions about the drug. Adolescents and others on Twitter are exposed to positive discussion normalizing use. Over the study period, Twitter was increasingly used to disclose marijuana use.