Predictive model based on the WHO-DAS II of the degree of disability in adults with a spinal cord injury in bogotá

Lema, C.P. Henao; Parra, J.E. Pérez; Otalora, M.L. Acosta; Sierra, S.J. Parra; Avila, A.C. Quino

doi:https://doi.org/10.1016/j.rh.2015.01.001

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Predictive model based on the WHO-DAS II of the degree of disability in adults with a spinal cord injury in bogotá

https://repository.urosario.edu.co/handle/10336/22915
https://doi.org/10.1016/j.rh.2015.01.001

Autores

Lema, C.P. Henao

Parra, J.E. Pérez

Otalora, M.L. Acosta

Sierra, S.J. Parra

Avila, A.C. Quino

Fecha

2015

Editor

Ediciones Doyma, S.L.

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Abstract

Introduction Spinal cord injury is a devastating condition associated with a permanent disability. Factors such as medical, social, psychological and economic problems can contribute to its increase. To build a predictive model from WHO- DAS II, the degree of disability in adults with spinal cord injury in Bogota (Colombia) it helps to understand the factors that influence the disability. Materials and methods Descriptive correlational study. It was carry out with a sample of 51 people with spinal cord injury, older than 18 with more than six months of evolution of varied causes, location and extension. The Spanish version of the WHO-DAS II of 36 items and the ASIA impairment scale were used. Tools of descriptive statistics and construction of linear regression models were used for data analysis. Results Significant relationship of global disability with socio- demographic variables (level of education, occupation, economical status and affiliation to the general social security health), clinical variables (duration and neurological level of the injury and clinical complications in the last year), and variables associated with rehabilitation services (access, assistive devices and vocational, job and educational counseling) were found. Conclusion The predictive model of global disability in adults in Bogotá with a spinal cord injury for more than 6 months is composed of the following post-injury variables: neurological level of the injury, number of clinical complications in the last year, and unemployment after the injury. © 2014 Elsevier España, S.L.U. and SERMEF.