Police crash reports are often the main source for official data in many countries. However, with the exception of fatal crashes, crashes are often underreported in a biased manner. Consequently, the countermeasures adopted according to them may be inefficient. In the case of bicycle crashes, this bias is most acute and it probably varies across countries, with some of them being more prone to reporting accidents to police than others. Assessing if this bias occurs and the size of it can be of great importance for evaluating the risks associated with bicycling. This study utilized data collected in the COST TU1101 action "Towards safer bicycling through optimization of bicycle helmets and usage". The data came from an online survey that included questions related to bicyclists' attitudes, behaviour, cycling habits, accidents, and patterns of use of helmets. The survey was filled by 8655 bicyclists from 30 different countries. After applying various exclusion factors, 7015 questionnaires filled by adult cyclists from 17 countries, each with at least 100 valid responses, remained in our sample. The results showed that across all countries, an average of only 10% of all crashes were reported to the police, with a wide range among countries: from a minimum of 0.0% (Israel) and 2.6% (Croatia) to a maximum of a 35.0% (Germany). Some factors associated with the reporting levels were type of crash, type of vehicle involved, and injury severity. No relation was found between the likelihood of reporting and the cyclist's gender, age, educational level, marital status, being a parent, use of helmet, and type of bicycle. The significant under-reporting - including injury crashes that do not lead to hospitalization - justifies the use of self-report survey data for assessment of bicycling crash patterns as they relate to (1) crash risk issues such as location, infrastructure, cyclists' characteristics, and use of helmet and (2) strategic approaches to bicycle crash prevention and injury reduction.

Naturalistic driving can generate huge datasets with great potential for research. However, to analyze the collected data in naturalistic driving trials is quite complex and difficult, especially if we consider that these studies are commonly conducted by research groups with somewhat limited resources. It is quite common that these studies implement strategies for thinning and/or reducing the data volumes that have been initially collected. Thus, and unfortunately, the great potential of these datasets is significantly constrained to specific situations, events, and contexts. For this, to implement appropriate strategies for the visualization of these data is becoming increasingly necessary, at any scale. Mapping naturalistic driving data with Geographic Information Systems (GIS) allows for a deeper understanding of our driving behavior, achieving a smarter and broader perspective of the whole datasets. GIS mapping allows for many of the existing drawbacks of the traditional methodologies for the analysis of naturalistic driving data to be overcome. In this article, we analyze which are the main assets related to GIS mapping of such data. These assets are dominated by the powerful interface graphics and the great operational capacity of GIS software.

The following study will explore the link between mindfulness, driver inattention and a number of driving performance variables that were tested using the SIMUVEG driving simulator. 67 subjects between the ages of 19 and 27 completed the mindful attention awareness scale, attention‐related driving errors scale and attention‐related cognitive errors scale questionnaires, and were evaluated in two driving performance measures: time to line‐crossing and mean speed. The results did not show a correlation between driving performance and mindfulness measures; they did show low but significant correlations with driver inattention measures. A regression analysis suggested that the specific measure of driver inattention is a predictor of driving performance, but the more general measures are not. These results are relevant to the assessment of psychological variables associated with driving performance.

The belief in conspiracy theories predicts behaviors related to public health such as the willingness to receive vaccines. This study applies a similar approach to an aspect of road safety: the use of smartphones while driving. A representative sample of 1706 subjects answered a series of questions related to what can be regarded as erroneous or conspiracy beliefs against restricting or banning the use of smartphones while driving. The results show that those having such conspiracy beliefs reported a greater use of smartphones behind the wheel.

The first part of this paper cautions against the injudicious use of citation data to rank journals. The second and main part presents a correspondence analysis of the descriptors assigned by abstractors to papers in five HCI, two human factors and three psychology journals. This analysis makes it possible to position the journals in a space of descriptors. The HCI journals form a cluster distinct from the psychology and human factors journals, suggesting HCI has now separated from its parent disciplines. Further, it is possible to position individual journals, for example, Behaviour & Information Technology is identified as an HCI journal with a leaning towards human factors.

Mothers attending infant children usually experience high levels of fatigue, and fatigue has been shown to be related to car crashes through attentional errors, among other causes. The current study investigates the effects of fatigue on the attentional errors while driving of women attending infant children. A sample of 112 women—67 attending infant children and 45 not attending—filled out self-report questionnaires assessing acute fatigue, chronic fatigue, and attention-related driving errors. A mediational analysis showed that women attending infant children had higher levels of fatigue, and that chronic fatigue, but not acute fatigue, was related to attentional errors while driving.