Paul Schepers

Dr. Paul Schepers


Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2014 in Accident Analysis & Prevention
Verified
Journal Article
Closed access
PSPaul Schepers
Paul Schepers
EFE. Fishman
E. Fishman
PHP. Den Hertog
P. Den Hertog
KWK. Klein Wolt
K. Klein Wolt
ASArend Schwab
Arend Schwab

1 May 2011 in Accident Analysis & Prevention
Verified
Journal Article
Closed access
PSPaul Schepers
Paul Schepers
PKP.A. Kroeze
P.A. Kroeze
WSW. Sweers
W. Sweers
JWJ.C. Wüst
J.C. Wüst

1 August 2015 in American Journal of Public Health
Verified
Journal Article
Closed access
EFElliot Fishman
Elliot Fishman
PSPaul Schepers
Paul Schepers
CKCarlijn Barbara Maria Kamphuis
Carlijn Barbara Maria Kamphuis
The Netherlands is well known for their high bicycle use. We used the Health Economic Assessment Tool and life table calculations to quantify the population-level health benefits from Dutch cycling levels. Cycling prevents about 6500 deaths each year, and Dutch people have half-a-year-longer life expectancy because of cycling. These health benefits correspond to more than 3% of the Dutch gross domestic product. Our study confirmed that investments in bicycle-promoting policies (e.g., improved bicycle infrastructure and facilities) will likely yield a high cost–benefit ratio in the long term.

21 November 2006 in Journal of Business and Psychology
Verified
Journal Article
Closed access
PDF file
PSPaul Schepers
Paul Schepers
PBPeter T. van Den Berg
Peter T. van Den Berg

12 January 2010 in Ergonomics
Verified
Journal Article
Closed access
DWDick de Waard
Dick de Waard
PSPaul Schepers
Paul Schepers
WOWieke Ormel
Wieke Ormel
KBKarel Brookhuis
Karel Brookhuis
The effects of mobile phone use on cycling behaviour were studied. In study 1, the prevalence of mobile phone use while cycling was assessed. In Groningen 2.2% of cyclists were observed talking on their phone and 0.6% were text messaging or entering a phone number. In study 2, accident-involved cyclists responded to a questionnaire. Only 0.5% stated that they were using their phone at the time of the accident. In study 3, participants used a phone while cycling. The content of the conversation was manipulated and participants also had to enter a text message. Data were compared with just cycling and cycling while listening to music. Telephoning coincided with reduced speed, reduced peripheral vision performance and increased risk and mental effort ratings. Text messaging had the largest negative impact on cycling performance. Higher mental workload and lower speed may account for the relatively low number of people calling involved in accidents. Statement of Relevance: Although perhaps mainly restricted to flat countries with a large proportion of cyclists, mobile phone use while cycling has increased and may be a threat to traffic safety, similar to phone use while driving a car. In this study, the extent of the problem was assessed by observing the proportion of cyclists using mobile phones, sending questionnaires to accident-involved cyclists and an experimental study was conducted on the effects of mobile phone use while cycling.

1 January 2014 in Accident Analysis & Prevention
Verified
Journal Article
Open access
PSPaul Schepers
Paul Schepers
MHMarjan Hagenzieker
Marjan Hagenzieker
RMRob Methorst
Rob Methorst
BWBert van Wee
Bert van Wee
FWFred Wegman
Fred Wegman
Scientific literature lacks a model which combines exposure to risk, risk, and the relationship between them. This paper presents a conceptual road safety framework comprising mutually interacting factors for exposure to risk resulting from travel behaviour (volumes, modal split, and distribution of traffic over time and space) and for risk (crash and injury risk). The framework's three determinants for travel behaviour are locations of activities; resistances (generalized transport costs); needs, opportunities, and abilities. Crash and injury risks are modelled by the three 'safety pillars': infrastructure, road users and the vehicles they use. Creating a link in the framework between risk and exposure is important because of the 'non-linear relationship' between them, i.e. risk tends to decrease as exposure increases. Furthermore, 'perceived' risk (a type of travel resistance) plays a role in mode choice, i.e. the perception that a certain type of vehicle is unsafe can be a deterrent to its use. This paper uses theories to explain how the elements in the model interact. Cycling is an area where governments typically have goals for both mobility and safety. To exemplify application of the model, the paper uses the framework to link research on cycling (safety) to land use and infrastructure. The model's value lies in its ability to identify potential consequences of measures and policies for both exposure and risk. This is important from a scientific perspective and for policy makers who often have objectives for both mobility and safety.