Improving skin screening capabilities for Veterans with spinal cord injuries.

J Spinal Cord Med

Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA.

Published: January 2025

Context: Clinical Practice Guidelines from the Consortium for Spinal Cord Injury (SCI) Medicine recommend daily self-screening of at-risk skin surfaces, but many Veterans with SCI describe challenges using the standard issue long-handled self-inspection mirror (LSIM).

Objective: The objective of this project was to compare the LSIM to a recently developed camera-based self-inspection system (CSIS). User feedback guided iterative engineering to improve and develop the new technology in preparation for transfer to industry.

Methods: Five Veterans with spinal cord injury (SCI) volunteered to compare use of a LSIM versus the CSIS to identify purposefully placed stickers with varying letters and colors over their high-risk skin surfaces while lying in bed. Each Veteran also responded to a series of interview questions and completed the QUEST 2.0 questionnaire on satisfaction with assistive technology.

Results: Veterans with SCI were able to correctly identify sticker letters and colors with significantly higher fidelity ( = .001 and  = .001 respectively) using the CSIS compared to using LSIM. Further the CSIS, was significantly ( = .004) preferred over the LSIM on the QUEST 2.0. The Cohen's D effect sizes for these paired comparisons were large (for color: 5.7, for sticker letter: 5.0 and QUEST 2.0: 2.6).

Conclusions: Improved visualization and satisfaction scores using the newly developed CSIS suggest that adoption of this new technology could improve the quality and acceptance of this skin screening strategy for persons with spinal cord injury.

Download full-text PDF

Source
http://dx.doi.org/10.1080/10790268.2024.2430079DOI Listing

Publication Analysis

Top Keywords

spinal cord
16
cord injury
12
skin screening
8
veterans spinal
8
injury sci
8
skin surfaces
8
veterans sci
8
compare lsim
8
letters colors
8
csis
5

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!