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Rehabilitation Dataset Directory: Dataset Profile

Dataset: Wheelchair Tiedown and Occupant Restraint System (WTORS) Activity in Paratransit Vehicles ()

Basic Information
Dataset Full Name Wheelchair Tiedown and Occupant Restraint System (WTORS) Activity in Paratransit Vehicles
Dataset Acronym

The purpose of this study was to characterize wheelchair tiedown and occupant restraint system (WTORS) usage on paratransit vehicles. A retrospective review of 476 on-board video monitoring recordings of trips by passengers seated in Wheeled Mobility Devices (WhMDs) was conducted. Data was collected from March through October, 2012. The study was conducted using two paratransit vehicles within one metropolitan area. Along with general information about the WhMDs and other equipment used by the passengers, details of the passengers' access and use of the vehicle were recorded. Details of WTORS usage including number of tiedowns and restraints used, attachment points to the WhMD and the vehicle floor, and any improper usage were recorded. Instability of the WhMD and incidents observed while the vehicle was in motion, along with contributing factors, were recorded and described.

Key Terms

Wheelchair, Wheelchair tiedown, Occupant restraint system (WTORS), Paratransit

Study Design Cross-Sectional
Data Type(s) Survey
Sponsoring Agency/Entity

 U.S. Department of Education

Office of Special Education and Rehabilitative Services (OSERS)

The National Institute on Disability and Rehabilitation Research (NIDRR)

Health Conditions/Disability Measures
Health Condition(s)

Wheelchair users

Disability Measures

Special equipment use/assistive technology

Measures/Outcomes of Interest

Wheelchair use, Accessibility, Transportation, Paratransit, Wheelchair restraint systems, Tiedowns, Shoulder belt, Lap belt, Public transit, Public transportation, Safety

Sample Population

Passengers of two paratransit vehicles utilizing Wheeled Mobility Devices (powered wheelchairs, manual wheelchairs and scooters)

Sample Size/Notes

476 paratransit trips

Unit of Observation

Paratransit trip


North America


United States

Geographic Coverage


Geographic Specificity


Data Collection
Data Collection Mode

Observational data (coded video)

Years Collected


Data Collection Frequency

476 paratransit trips

Strengths and Limitations

Includes detailed descriptions of each trip documented related to the use of wheelchair restraint system on two Paratransport vehicles. Documents instances of use/misuse and issues with the wheelchair tiedowns and restraint system (lap and shoulder belts). Provides information on wheelchair type and configuration.

ADDEP provides online analysis capability for this dataset.


Data was collected from only two vehicles in one urban location from a single transit agency. Data may not be representative.

Data Details
Primary Website 

Data Access  

Data Access Requirements

Public use

Summary Tables/Reports 

Note: online analysis on ADDEP site is available

Data Components


Similar/Related Dataset(s)

Wheelchair focused datasets:

Selected Papers
Other Papers

Wheelchair tiedown and occupant restraint practices in paratransit vehicles  



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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).

Other CLDR supported resources and collaborative opportunities:

Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.

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