Abstract
Objectives: Pedestrian injury is the second leading cause of death and serious injury among children between the ages of 5 and 14. The existing methods for teaching children how to cross the street safely are difficult to transfer to real life situations. The objective of this study was to evaluate the effectiveness of a Virtual Reality (VR) environment in teaching children how to cross a street safely. Method: Eighty-six children (55 girls and 31 boys), aged 7-12 years, participated in the study. The children were observed while crossing a real street and tested on a test in the virtual environment (VE) prior to and following VR training. Results: The children in the training group significantly improved their street crossing abilities in the VR simulation as well as in the real street crossing in comparison to the control group. Street crossing became safer with age however, no differences were found between boys and girls. Conclusions: This low-cost and readily available street crossing simulation had a positive effect on children's street crossing behavior and on their self-reported satisfaction.
| Original language | English |
|---|---|
| Title of host publication | Fifth International Workshop on Virtual Rehabilitation, IWVR 2006 |
| Publisher | IEEE Computer Society |
| Pages | 42-46 |
| Number of pages | 5 |
| ISBN (Print) | 1424402808, 9781424402809 |
| DOIs | |
| State | Published - 2006 |
| Event | 5th International Workshop on Virtual Rehabilitation, IWVR 2006 - New York, NY, United States Duration: 29 Aug 2006 → 30 Aug 2006 |
Publication series
| Name | Fifth International Workshop on Virtual Rehabilitation, IWVR 2006 |
|---|
Conference
| Conference | 5th International Workshop on Virtual Rehabilitation, IWVR 2006 |
|---|---|
| Country/Territory | United States |
| City | New York, NY |
| Period | 29/08/06 → 30/08/06 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Software
- Rehabilitation
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