The Overlooked Outcome Measure for Spinal Cord Injury: Use of Assistive Devices

Abstract

Although several outcome measures are used to assess various areas of interest regarding spinal cord injuries (SCIs), little is known about the frequency of their use, and the ways in which they transform shared knowledge into implemented practices. Herein, 800 professionals from the International Spinal Cord Society, especially trained for caring in patients with SCI, were invited to respond to an Internet survey collecting information on the use of standardized measures in daily clinical practices. We asked both clinicians and researchers with different areas of interest about their use of functional outcome measures, and, in particular, which scales they habitually use to assess various aspects of clinical practice and rehabilitation. We selected a set of rating scales, which were validated for measuring SCIs (http://www.scireproject.com/outcome-measures). The results show that the areas of interest assessed by most of the participants were neurological status, upper limb, lower limb gait, pain, spasticity, self-care, and daily living. The most widely used rating scales were the spinal cord independence measure, the functional independence measure and the International Standards for Neurological Classification of Spinal Cord Injury. Instead, the majority of respondents did not evaluate the use of assistive technology. Despite the availability of several outcome scales, the practice of evaluating SCIs with standardized measures for assistive technologies and wheelchair mobility is still not widespread, even though it is a high priority in the rehabilitation of SCI patients. The results emphasize the need for a more thorough knowledge and use of outcome scales, thus improving the quality of assistive device evaluation.

Keywords: embodiment; outcome measures; rehabilitative tools; spinal cord injury; survey.

Figure 1

Dendrogram indicating the greatest difference between the responses of using those outcome measures identified by SCIRE. A single-linkage hierarchical clustering algorithm was used. The x-axis shows Euclidean distances that provide a measure of similarity in the distribution of responses. The types of measures are reported along the y-axis. Measures with the most similar performance are closer to each other. Three main clusters are apparent with relatively homogeneous measures. Pain and Assistive Technology clustered separately and seem to have a different profile.

Figure 2

Means of the responses were sorted according to their adhesion to the following responses: (i) “I do not assess this area,” (ii) “I assess with measures identified by SCIRE,” and (iii) “I assess with other measures for the five different clusters”.