Picture of smart phone in human hand

World leading smartphone and mobile technology research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by Strathclyde researchers from the Department of Computer & Information Sciences involved in researching exciting new applications for mobile and smartphone technology. But the transformative application of mobile technologies is also the focus of research within disciplines as diverse as Electronic & Electrical Engineering, Marketing, Human Resource Management and Biomedical Enginering, among others.

Explore Strathclyde's Open Access research on smartphone technology now...

Validity of simple gait related dual task tests in predicting falls in community dwelling older adults

Muhaidat, Jennifer and Kerr, Andrew and Evans, Jonathan J. and Pilling, Mark and Skelton, Dawn A. (2014) Validity of simple gait related dual task tests in predicting falls in community dwelling older adults. Archives of Physical Medicine and Rehabilitation, 95 (1). pp. 58-64. ISSN 0003-9993

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

Objective: To investigate the predictive validity of simple gait-related dual-task (DT) tests in predicting falls in community-dwelling older adults. Design: A validation cohort study with 6 months' follow-up. Setting: General community. Participants: Independently ambulant community-dwelling adults (N=66) aged ≥65 years, with normal cognitive function. Sixty-two completed the follow-up. No participants required frames for walking. Interventions: Not applicable. Main Outcome Measures: Occurrence of falls in the follow-up period and performance on primary and secondary tasks of 8 DT tests and 1 triple-task (TT) test. Results: A random forest classification analysis identified the top 5 predictors of a fall as (1) absolute difference in time between the Timed Up & Go (TUG) as a single task (ST) and while carrying a cup; (2) time required to complete the walking task in the TT test; (3 and 4) walking and avoiding a moving obstacle as an ST and while carrying a cup; and (5) performing the TUG while carrying a cup. Separate bivariate logistic regression analyses showed that performance on these tasks was significantly associated with falling (P<.01). Despite the random forest analysis being a more robust approach than multivariate logistic regression, it was not clinically useful for predicting falls. Conclusions: This study identified the most important outcome measures in predicting falls using simple DT tests. The results showed that measures of change in performance were not useful in a multivariate model when compared with an "allocated all to falls" rule.