Prevalence and Profiles of Risky Driving Behavior Among US Teenagers.
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ABSTRACT:
SUBMITTER: Ehsani JP
PROVIDER: S-EPMC11292446 | biostudies-literature | 2024 Jul
REPOSITORIES: biostudies-literature
Publications
Prevalence and Profiles of Risky Driving Behavior Among US Teenagers.
Ehsani Johnathon P JP Duren Michelle L ML Grant Brydon J B BJB Sabit Ahmed A Yenokyan Gayane G
JAMA network open 20240701 7
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Project description:Teenage passengers might influence risky driving, particularly in certain mental states. Notably, social exclusion could increase social conformity. Two studies examined simulated intersection management among young drivers after a social exclusion activity (Cyberball). In Study 1 [112 males (mean = 17.3 years)], risky driving was significantly greater among excluded males driving with a risk-accepting vs. passive passenger; no effect of social exclusion. In Study 2 [115 females (mean = 17.1 years)], risky driving was significantly greater among excluded females driving with a risk-accepting vs. a passive passenger, and greater among those included (fair play) vs. excluded when driving with a risk-accepting passenger. Risky driving behavior among male and female teenagers may be influenced uniquely by passenger norms and social exclusion.
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Project description:Risky and aggressive driving maneuvers are considered a significant indicator for traffic accident occurrence as well as they aggravate their severity. Traffic violations caused by such uncivilized driving behavior is a global issue. Studies in existing literature have used statistical analysis methods to explore key contributing factors toward aggressive driving and traffic violations. However, such methods are unable to capture latent correlations among predictor variables, and they also suffer from low prediction accuracies. This study aimed to comprehensively investigate different traffic violations using spatial analysis and machine learning methods in the city of Luzhou, China. Violations committed by taxi drivers are the focus of the current study since they constitute a significant proportion of total violations reported in the city. Georeferenced violation data for the year 2016 was obtained from the traffic police department. Detailed descriptive analysis is presented to summarize key statistics about various violation types. Results revealed that over-speeding was the most prevalent violation type observed in the study area. Frequency-based nearest neighborhood cluster methods in Arc map Geographic Information System (GIS) were used to develop hotspot maps for different violation types that are vital for prioritizing and conducting treatment alternatives efficiently. Finally, different machine learning (ML) methods, including decision tree, AdaBoost with a base estimator decision tree, and stack model, were employed to predict and classify each violation type. The proposed methods were compared based on different evaluation metrics like accuracy, F-1 measure, specificity, and log loss. Prediction results demonstrated the adequacy and robustness of proposed machine learning (ML) methods. However, a detailed comparative analysis showed that the stack model outperformed other models in terms of proposed evaluation metrics.
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Project description:Longstanding theory in behavioral ecology predicts that prey should evolve decreased foraging rates under high predation threat. However, an alternative perspective suggests that growth into a size refuge from gape-limited predation and the future benefits of large size can outweigh the initial survival costs of intense foraging. Here, I evaluate the relative contributions of selection from a gape-limited predator (Ambystoma opacum) and spatial location to explanations of variation in foraging, growth, and survival in 10 populations of salamander larvae (Ambystoma maculatum). Salamander larvae from populations naturally exposed to intense A. opacum predation risk foraged more actively under common garden conditions. Higher foraging rates were associated with low survival in populations exposed to free-ranging A. opacum larvae. Results demonstrate that risky foraging activity can evolve in high predation-risk habitats when the dominant predators are gape-limited. This finding invites the further exploration of diverse patterns of prey foraging behavior that depends on natural variation in predator size-selectivity. In particular, prey should adopt riskier behaviors under predation threat than expected under existing risk allocation models if foraging effort directly reduces the duration of risk by growth into a size refuge. Moreover, evidence from this study suggests that foraging has evolved over microgeographic scales despite substantial modification by regional gene flow. This interaction between local selection and spatial location suggests a joint role for adaptation and maladaptation in shaping species interactions across natural landscapes, which is a finding with implications for dynamics at the population, community, and metacommunity levels.
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Project description:ImportanceHandheld cellphone use while driving is associated with increased motor vehicle crash risk among adolescents.ObjectiveTo examine the association of handheld cellphone use while driving with kinematic risky driving (KRD) events-hard braking and rapid acceleration-in adolescent drivers.Design, setting, participantsAdolescents aged 16.50 to 17.99 years licensed 365 days or less in Pennsylvania were eligible to participate in this cross-sectional study. Enrollment occurred from July 29, 2021, to June 6, 2022. Participants downloaded a smartphone telematics cellphone app to record driving data for 60 days.ExposuresTrip characteristics, including frequency, length, and duration; presence of speeding; frequency and duration of handheld cellphone use; time of day; and presence of precipitation.Main outcomes and measuresKinematic risky driving events per 100 miles driven. Zero-inflated Poisson regression models examined whether individual characteristics and trip characteristics were associated with KRD. Incidence rate ratios were computed.ResultsOf 405 adolescents who responded to recruitment, 151 enrolled, 140 completed study procedures, and 119 with 12 360 trips were included in the analytic sample (60 female participants [50.4%]; mean [SD] age, 17.2 [0.4] years). Adolescents drove a mean (SD) of 103.8 (65.7) trips, 565.0 (487.3) miles, and 25.1 (19.3) hours. Adolescents had minimal night trips (1.5% [192]), and few trips with precipitation present (9.0% [1097]). Speeding occurred in 43.9% (5428) of the trips and handheld cellphone use occurred in 34.1% (4214) of the trips. Kinematic risky driving events occurred in 10.9% (1358) of the trips at a rate of 2.65 per 100 miles. In adjusted models, increased KRD events were associated with handheld cellphone use (incidence rate ratio [IRR], 2.62; 95% CI, 1.53-4.48), speeding (IRR, 2.12; 95% CI, 1.06-4.26), and minutes driving (IRR, 1.02; 95% CI, 1.01-1.02). Trips at night, precipitation presence, licensure for less than 6 months, and sex were not associated with increased KRD events.ConclusionsIn this cross-sectional study of adolescent drivers, trips with handheld cellphone use and speeding were associated with higher rates of KRD, while individual characteristics were not. The findings suggest that smartphone telematics apps provide an opportunity to observe behaviors as well as surveil changes due to intervention efforts.
| S-EPMC11581603 | biostudies-literature
Project description:(1) Background: Research on patterns of risky driving behaviors (RDBs) in adolescents is scarce. This study aims to identify distinctive patterns of RDBs and to explore their characteristics in a representative sample of adolescents. (2) Methods: this is a cross-sectional study of a representative sample of Tuscany Region students aged 14-19 years (n = 2162). The prevalence of 11 RDBs was assessed and a cluster analysis was conducted to identify patterns of RDBs. ANOVA, post hoc pairwise comparisons and multivariate logistic regression models were used to characterize cluster membership. (3) Results: four distinct clusters of drivers were identified based on patterns of RDBs; in particular, two clusters-the Reckless Drivers (11.2%) and the Careless Drivers (21.5%)-showed high-risk patterns of engagement in RDBs. These high-risk clusters exhibited the weakest social bonds, the highest psychological distress, the most frequent participation in health compromising and risky behaviors, and the highest risk of a road traffic accident. (4) Conclusion: findings suggest that it is possible to identify typical profiles of RDBs in adolescents and that risky driving profiles are positively interrelated with other risky behaviors. This clustering suggests the need to develop multicomponent prevention strategies rather than addressing specific RDBs in isolation.
| S-EPMC8296188 | biostudies-literature
Project description:ObjectiveThis study examines predictors of later risky driving behavior in children with attention-deficit/hyperactivity disorder (ADHD).MethodsStepwise logistic regression and receiver operating characteristic (ROC) analysis were used to explore baseline predictors of risky driving behavior for adolescents who completed the 8-year follow-up assessment in the Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder (MTA).ResultsStepwise logistic regression analysis explained 19% of the total variance in risky driving behavior. Increased likelihood of risky driving behavior was associated with parental history of conduct disorder, low parental monitoring and supervision, and increased age. ROC analysis identified discriminative predictors for adolescents older and younger than 16 years of age at follow-up. The most discriminative predictors of later risky driving behavior were parental stress at baseline (for children 16 years or older) and increased child-rated parental protectiveness (for children less than 16 years old).ConclusionRisky driving behavior was significantly predicted by baseline characteristics for the MTA cohort. Aspects of parenting behavior (or the child's perception of them), including parental stress levels, parental protectiveness, and parental levels of monitoring and supervision, were most informative in predicting these outcomes. Our results suggest that interventions to reduce high-risk behaviors in these high-risk children with ADHD might involve targeted parenting interventions.
| S-EPMC5651934 | biostudies-literature
Project description:ObjectiveExamined cross-sectional associations of driving while impaired (DWI) and risky driving with mental and psychosomatic health among U.S. emerging adults.MethodsData were from years 1-4 after high school (waves 4-7) of the NEXT Generation Health Study, a nationally representative study starting with 10th grade (2009-2010). Outcome variables were DWI (dichotomous variable: ≥ 1 day vs. 0 days in the last 30 days) and risky driving Checkpoints Self-Reported Risky Driving Scale (C-RDS). Independent variables included depressive symptoms and psychosomatic symptoms. Multivariate logistic and linear regressions were conducted with complex survey features considered.ResultsHigher depressive and psychosomatic symptoms were associated with modestly higher likelihood of DWI (Adjusted odds ratio [AOR] ranged from 1.02 to 1.03 and from 1.04 to 1.05, respectively) and higher C-RDS scores (b ranged from 0.06 to 0.12 and from 0.08 to 0.23, respectively) in years 1-4 after high school.ConclusionsDepressive and psychosomatic symptoms were associated with greater DWI and risky driving in all 4 years after high school. Negative mental and psychosomatic health should be targeted components of DWI and risky driving prevention to lower fatal motor vehicle crashes among emerging adults.
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Project description:The history of humankind is an epic of cooperation, which is ubiquitous across societies and increasing in scale. Much human cooperation occurs where it is risky to cooperate for mutual benefit because successful cooperation depends on a sufficient level of cooperation by others. Here we show that arginine vasopressin (AVP), a neuropeptide that mediates complex mammalian social behaviors such as pair bonding, social recognition and aggression causally increases humans' willingness to engage in risky, mutually beneficial cooperation. In two double-blind experiments, male participants received either AVP or placebo intranasally and made decisions with financial consequences in the "Stag hunt" cooperation game. AVP increases humans' willingness to cooperate. That increase is not due to an increase in the general willingness to bear risks or to altruistically help others. Using functional brain imaging, we show that, when subjects make the risky Stag choice, AVP down-regulates the BOLD signal in the left dorsolateral prefrontal cortex (dlPFC), a risk-integration region, and increases the left dlPFC functional connectivity with the ventral pallidum, an AVP receptor-rich region previously associated with AVP-mediated social reward processing in mammals. These findings show a previously unidentified causal role for AVP in social approach behavior in humans, as established by animal research.
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