1 / 100

ICARUS Inter-Cultural Approaches for Road Users Safety

14 Supporter Countries - Meeting in Ljubljana, November 10th and 11th, 2010. ICARUS Inter-Cultural Approaches for Road Users Safety. TREN/SUB/01-2008. Preliminary results of the research on risk factors of young drivers. “Sapienza” University of Rome.

griffith-ward
Télécharger la présentation

ICARUS Inter-Cultural Approaches for Road Users Safety

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 14 Supporter Countries - Meeting in Ljubljana, November 10th and 11th, 2010 ICARUS Inter-Cultural Approaches for Road Users Safety TREN/SUB/01-2008 Preliminary results of the research on risk factors of young drivers “Sapienza” University of Rome

  2. Within the ICARUSProject, it will be developed, for the first time, a training model to be shared with the EU Countries. The training model will be grounded on a research aimed at detecting the main risk factors in road safety.

  3. www.webicarus.eu

  4. Aims of the Project 1.Identifying main Risk Factors involved in road safety. 2. Developing a shared European Training model starting from and taking into account research results.

  5. The main steps: • to identify a European Network of road safety training agencies; • to conduct an analysis on the driving style and habits of young drivers in different EU countries; • to define a set of guidelines to approach the issue “road safety” in relation to young drivers on a European scale; • to prepare a Manual with a CD-ROMto perform the training for prevention of road accidents.

  6. The intervention areas will be developed in 11 steps along a period of 30 months. Step 1.Creation of a network of participants. Step 2.Preliminary study aimed at drawing up and adapting a questionnaire. Step 3.Sample selection. Step 4. First Conference in Rome.

  7. First Conference in Rome Rome - 15/16 October 2009

  8. Step 6.Organization of a database (data coding and input). Step 7.Data analysis. Step 8.Interpretation of results and first intermediate report. Ljubljana Workshop Step 9.Identification of best practices. Step 10.Creation of a manual both in paper and electronic format. Step 11.Final conference in Brussels.

  9. Workshop in Ljubljana in order to discuss: a) common and/or national-specific risk factors. b) individual variables predicting a risk taking behaviour. c) existence of groups of drivers at higher risk of being involved in car crashes and their individual variables.

  10. Total Sample 9611 Respondents 4010 Car Drivers 2556 males - 19.8 yo 1454 females - 19.8 yo 1349 Scooter Drivers 1000 males – 20.1 yo 349 females - 19.8 yo 4252 Non-Drivers 2560 males – 21.3 yo 1692 females - 21.5 yo

  11. Today, results will be discussed about: Latvia Ireland Lithuania Poland Austria Slovenia Bulgaria Italy Cyprus

  12. Work are still in progress for the following Countries: Malta Germany Francia Slovakia Estonia

  13. The Questionnaire • A series of Scales concerning: • General attitude toward road safety (Scale A) • Locus of Control (Scale B) • Driving-related rage (Scale D) • Moral disengagement (Scale E) • Personality (Scale F) • Driving behaviour (Scale I) • Representation of alcohol effects (Scale F) • Questions about driving expertise, habits etc.

  14. Layout of Analyses • Data check • Identification of the dimensions underlying the Scales Factor Analyses, Principal Axis Method, Oblimin Rotation • Identification of the number of groups of respondents Cluster Analyses, Hierarchical Algorhythm, Complete Linkage, Squared Euclidean Distances • Identification of groups of respondents Cluster Analyses, K-Means Method • Identification of profiles and risk factors Multivariate Analyses of Variance and Discriminant Analyses

  15. The general patterns of results are pretty similar across Countries, but specificities do exist. For instance: • A group of “Safe Drivers” exists in all the Countries • A group of “Risky Drivers” exists in all the Countries • However, specific groups exist in some Countries but not in all of them,such as the “Overconfident”, the “Aggressive”, the “Speeding” Drivers, etc.

  16. Safe Drivers He/she has a friendly attitude toward the others, and has a positive attitude toward the moralnorms. He/she doesn’t feel rage against other drivers or obstacles. He/she thinks accidents are mostly dueto factors under his/hercontrol, and that a careful driver could avoid them. He/she has a positive attitude toward the traffic code. He/she is aware of the negative effects of alcohol on general human behaviour.

  17. Risky Drivers He/she has an egocentric attitude, shows moral disengagement, and looks for excitement and strong sensations. He/she feels rage against other drivers and obstacles. He/she thinks accidents are mostly due to factors not under his/her control. He/she has a negative attitude toward the traffic code(sometimes thinks that violations are useful to make traffic going). He/she considers alcohol as having positive effects on the general human behaviour.

  18. Overconfident Drivers He/she has a friendly attitude toward the others, and has a positive attitude toward the moral norms. He/she doesn’t feel rage against otherdrivers or obstacles. He/she thinks accidents are mostly due to factors under his/her control, and that a careful driver could avoid them. He/she has a negative attitude toward the traffic code, and is especially toleranttoward speeding. He/she is aware of the negative effects of alcohol on general human behaviour.

  19. Aggressive Drivers He/she has a friendly attitude toward the others, and has a positive attitude toward the moral norms. He/she feel rage against other drivers and obstacles, has an aggressive way of driving, and is tolerant toward speeding. He/she thinks accidents are mostly due to factors under his/her control, and that a careful driver could avoid them. He/she has a positive attitude toward the traffic code. He/she is aware of the negative effects of alcohol on general human behaviour.

  20. Safe Drivers He/she has a friendlyattitude toward the others, and has a positiveattitude toward the moral norms. He/she doesn’t feel rage against other drivers or obstacles. He/she thinks accidents are mostly due to factors under his/her control, and that a careful driver could avoid them. He/she has a positive attitude toward the traffic code. He/she is aware of the negative effects of alcohol on general human behaviour.

  21. Risky Drivers He/she has an egocentric attitude, shows moral disengagement, and looks for excitement and strong sensations. He/she feels rage against otherdrivers and obstacles. He/she thinks accidents are mostly due to factors not under his/her control. He/she has a negative attitude toward the traffic code(sometimes thinks that violationsare useful to make traffic going). He/she considers alcohol as having positive effects on the general human behaviour.

  22. Speedy Drivers He/she has a friendly attitude toward the others, and has a positive attitude toward the moral norms. He/she doesn’t feel rage against other drivers or obstacles. He/she thinks accidents are mostly due to factors under his/her control. He/she is especially tolerant toward speeding. He/she is aware of the negative effects of alcohol on general human behaviour.

  23. Non drivers • The same groups of safe and risky “potential drivers” • But a specific group exists in all the Countries composed of individuals who do not recognize that alcohol and drugshave negative effects on human behaviour (and driving).

  24. Preliminary results

  25. SLOVENIA

  26. Wilks’ Lambda=0.08, F44,742=43.7, p<.0001 CAR DRIVERS SECTION 1 538 Respondents (57% males) Mean age = 19.0 years (s.d. 1.0)

  27. Wilks’ Lambda=0.08, F22,408=47.6, p<.0001 SCOOTER DRIVERS SECTION 2 188 Respondents (75% males) Mean age = 17.5 years (s.d. 0.9)

  28. Wilks’ Lambda=0.23, F24,580=25.9, p<.0001 NON DRIVERS SECTION 3 304 Respondents (57% males) Mean age = 18.0 years (s.d. 0.7)

  29. AUSTRIA

  30. Wilks’ Lambda=0.08, F40,374=23.3, p<.0001 CAR DRIVERS SECTION 1 302 Respondents (49% males) Mean age = 19.8 years (s.d. 7.6)

  31. * * * *

  32. Wilks’ Lambda=0.08, F22,408=47.6, p<.0001 SCOOTER DRIVERS SECTION 2 151 Respondents (72% males) Mean age = 17.3 years (s.d. 4.3)

  33. Wilks’ Lambda=0.16, F24,476=30.1, p<.0001 NON DRIVERS SECTION 3 252 Respondents (53% males) Mean age = 17.7 years (s.d. 5.7)

  34. BULGARIA

  35. Wilks’ Lambda=0.14, F36,1318=61.7, p<.0001 CAR DRIVERS SECTION 1 791 Respondents (91% males) Mean age = 19.1 years (s.d. 3.1)

  36. * * * * *

  37. Wilks’ Lambda=0.04, F32,242=29.7, p<.0001 SCOOTER DRIVERS SECTION 2 161 Respondents (87% males) Mean age = 18.3 years (s.d. 0.9)

  38. *

  39. Wilks’ Lambda=0.15, F24,3106=209.6, p<.0001 NON DRIVERS SECTION 3 1540 Respondents (82% males) Mean age = 18.5 years (s.d. 1.7)

More Related