ArticleTransportation research. Part F, Traffic psychology and behaviour2019
Learning to drive: A reconceptualization.
Article in Transportation research. Part F, Traffic psychology and behaviour, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Promoting transportation safety in adolescence: the drivingly randomized controlled trial.BMC public health · 2023Trial
- Validation of a performance-based driving assessment: Implications for licensing young drivers.Journal of safety research · 2025Article
- Predicting Young Drivers' Time-to-Licensure from Sociodemographic Characteristics and Quality of Adult-Supervised Practice.Transportation research. Part F, Traffic psychology and behaviour · 2025Article
- The effectiveness of behavioural interventions on young, novice drivers' motor vehicle crash risk: A systematic review.Journal of transport & health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Drivers' population-level crash rates incrementally decrease following licensure, which has led to the implicit assumption that an individual driver's crash risk also decreases incrementally after licensure as they accrue experience. However, in the aggregate data an incremental decrease in crash rate can reflect both incremental reductions in crash risk within individuals and an incremental increase in the proportion of drivers who have experienced an abrupt decrease in crash risk. Therefore, while it is true to say that the population of drivers' crash risk reduces in the months following licensure, it is not necessarily true to say that a driver's crash risk reduces in the months following licensure; that is, it cannot be assumed that individual-level changes in crash risk mirror the population-level changes in crash rates. In statistics, this is known as an ecological fallacy and in formal logic it is known as the fallacy of division, a type of category error. Using computational cognitive modeling methods we demonstrate that aggregating individual-level abrupt decreases in crash risk (i.e., non-incremental change trajectories) accurately fits population-level crash rate data from over 1 million adolescents
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.