Working Memory Development and Motor Vehicle Crashes in Young Drivers

Abstract

Key PointsQuestionIs variability in working memory development associated with motor vehicle crashes in young drivers?FindingsIn this cohort study of 84 community youth drivers, relative variation in working memory growth (slope)—but not the baseline (intercept)—was inversely associated with reporting a crash when controlling for other crash risk factors.MeaningRoutine assessment of working memory development across adolescence may help identify teens with a relatively divergent trajectory of working memory growth who may be more likely to be involved in a motor vehicle crash.

Rethinking Cell Phone Use While Driving: Isolated Risk Behavior or a Pattern of Risk-Taking Associated with Impulsivity in Young Drivers?

“…We used a binary crash outcome that collapsed multiple-crash drivers into one group of “at least 1 crash” (described above in our results). This allows us to replicate our prior work and that of others [ 11 , 24 , 38 ], but future work should explore multiple crashes as an alternative outcome because these drivers may be more at risk. Furthermore, while the measures of personality traits were taken after the driver’s had a crash, these traits are largely stable across age in young adulthood [ 39 ], allowing us to examine the pattern of risk taking.…”

“…However, the risk of social desirability bias may have been reduced by the anonymous recruitment of participants and online survey. Furthermore, prior work has also relied on self-reported crashes (which can be over- or under-reported) [ 35 , 36 , 37 ], including models with a history of crashes as the outcome [ 24 , 38 ]. While naturalistic studies and in-vehicle monitoring can offer prospective crash monitoring, and provide richer information about crashes (e.g., if the driver was at fault), these approaches are not without limitations (e.g., recruitment bias and crashes are often a rare outcome of such studies).…”

“…History of crashes was recorded as in our prior work (response options: “none”, “one”, “two”, “more than two”) [ 11 ]. Additionally, replicating our prior studies [ 11 , 24 ], a subset of DBQ survey items that were deemed to pose “definite risk to others’’ was included from the Driver Behavior Questionnaire (from the two most commonly reported latent constructs: deliberate behavioral violations and driving errors) [ 27 ] with two additional items that asked about answering a text while driving and talking on a cell phone while driving. For all driving behavior items, participants indicated how often they engaged in each on a 6-point scale (1 = never, to 6 = nearly all the time).…”

“…In particular, the ongoing maturation of the prefrontal cortex and the associated executive control system that supports self-regulation and cognitive control over behavior may explain weaker impulse control, while rising dopaminergic activity in the brain’s reward circuit may also explain increased sensation seeking [ 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. However, there is also evidence for substantial individual variability in these traits and the underlying neural and cognitive development, which may explain variable risk-taking in young drivers [ 24 ]. If impulsive personality differences underlie tendencies to engage in risky driving practices, including cell phone use, then interventions that discourage the use of cell phones with respect to underlying personality differences may be more effective.…”

Reward-Sensitive Basal Ganglia Stabilize the Maintenance of Goal-Relevant Neural Patterns in Adolescents

“…During adolescence, developmental processes shape and refine this critical cognitive ability (Simmonds et al, 2017;Ullman et al, 2014;Brockmole & Logie, 2013;Satterthwaite et al, 2012Satterthwaite et al, , 2013Crone et al, 2006;Cowan et al, 2005;Gathercole et al, 2004;Barrouillet & Camos, 2001;Towse et al, 1998; see also Davidow et al, 2018;Crone & Steinbeis, 2017;Luna et al, 2015). Because of the relevance of adolescent WM to important outcomes such as scholastic achievement (Finn et al, 2016;Cowan et al, 2005;Gathercole et al, 2004;Gathercole & Pickering, 2000), mental illness (Diwadkar et al, 2011;Ross, Wagner, Heinlein, & Zerbe, 2007;Smith et al, 2006;Martinussen, Hayden, Gohh-Johnson, & Tannock, 2005), and more general adaptive behaviors ( Walshe et al, 2019), understanding the combined roles of reward and cognitive-control circuitry on WM may prove important for gaining insights into broader typical and atypical neurocognitive development. Future research employing longitudinal designs and contrasting adolescent pattern stability phenomenon with adult samples are needed to understand the exact nature of how this phenomenon might change through development.…”