Citation

Nelson AL, Groer S, Palacios P, Mitchell D, Sabharwal S, Kirby RL, Gavin-Dreschnack D, Powell-Cope G. Arch. Phys. Med. Rehabil. 2010; 91(8): 1166-1173.

Affiliation

Health Services Research & Development/Rehabilitation Research & Development Research Center of Excellence: Maximizing Rehabilitation Outcomes, James A. Haley Veterans Hospital, Tampa, FL.

Copyright

(Copyright © 2010, Elsevier Publishing)

DOI

10.1016/j.apmr.2010.05.008

PMID

20684896

Abstract

OBJECTIVES: (1) To determine the incidence of wheelchair falls and fall-related injuries in persons with spinal cord injury (SCI) living in the community. (2) To predict wheelchair-related falls and associated injuries from specific parameters including characteristics of the wheelchair user, wheelchair type and features, health care practices, wheelchair activities, and physical environment. DESIGN: This prospective cohort study followed participants monthly over 1 year; data were collected through surveys, interviews, performance testing, observation, and medical records. SETTING: Three Veterans' Administration hospitals. PARTICIPANTS: Convenience sample of community-dwelling persons with SCI who used a wheelchair as their primary means of mobility (N=702). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Self-reports of wheelchair falls and fall-related injuries, Wheelchair User Characteristics Survey, Health Status Checklist, Health-Related Behaviors, Zuckerman Sensation Seeking Scale, Wheelchair and Equipment-Related Behaviors, Wheelchair Characteristics, Wheelchair Skills Test, and Physical Environment Assessment. RESULTS: Of the 659 subjects who completed the study, 204 participants (31%) reported 553 fall events, and 95 subjects (14%) were injured as a result of wheelchair falls. A logistic regression model for predicting wheelchair falls identified 6 significant risk factors: pain in previous 2 months, alcohol abuse, greater motor function, history of previous fall, fewer SCI years, and shorter length of wheelchair. Eighty-two percent of the variance for wheelchair fall events was explained by these 6 variables. A logistic regression model for predicting injurious falls identified 4 significant risk factors: pain in previous 2 months, greater motor function, history of previous fall, and inaccessible home entrance. These 4 factors were able to explain 81% of the variance for injurious falls. CONCLUSIONS: This is the first study to determine the incidence of wheelchair-related falls in community-dwelling people with SCI who use a wheelchair. Results indicate the incidence of falls was 31% and injurious falls was 14%. Those at greatest risk can be predicted from some readily available information regarding their clinical status, wheelchair features, and home environment.

Language: en