This review examined demographic and clinical characteristics of participants from exercise trials in 3 neurologic disability conditions (multiple sclerosis, spinal cord injury, and traumatic brain injury) and compared these data with population-based statistics. The authors included 75 published studies from 2006 to 2016: 53 studies for multiple sclerosis (n = 2,034), 14 for spinal cord injury (n = 302), and 8 for traumatic brain injury (n = 272). Pooled data resembled some heterogeneous aspects of population data sets. However, many characteristics were not reported; samples were small and predominantly White, and 48.1% of the people screened were excluded. Thus, findings from these studies may not be translatable across the range of people with these three conditions, which warrant efforts to target the inclusion of underrepresented subgroups in future exercise trials.

Background Wearable motion sensors are gaining popularity for monitoring free-living physical activity among people with Parkinson disease (PD), but more evidence supporting the accuracy and precision of motion sensors for capturing step counts is required in people with PD. Objective This study aimed to examine the accuracy and precision of 3 common consumer-grade motion sensors for measuring actual steps taken during prolonged periods of overground and treadmill walking in people with PD. Methods A total of 31 ambulatory participants with PD underwent 6-min bouts of overground and treadmill walking at a comfortable speed. Participants wore 3 devices (Garmin Vivosmart 3, Fitbit One, and Fitbit Charge 2 HR), and a single researcher manually counted the actual steps taken. Accuracy and precision were based on absolute and relative metrics, including intraclass correlation coefficients (ICCs) and Bland-Altman plots. Results Participants walked 628 steps over ground based on manual counting, and Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR devices had absolute (relative) error values of 6 (6/628, 1.0%), 8 (8/628, 1.3%), and 30 (30/628, 4.8%) steps, respectively. ICC values demonstrated excellent agreement between manually counted steps and steps counted by both Garmin Vivosmart (0.97) and Fitbit One (0.98) but poor agreement for Fitbit Charge 2 HR (0.47). The absolute (relative) precision values for Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR were 11.1 (11.1/625, 1.8%), 14.7 (14.7/620, 2.4%), and 74.4 (74.4/598, 12.4%) steps, respectively. ICC confidence intervals demonstrated low variability for Garmin Vivosmart (0.96 to 0.99) and Fitbit One (0.93 to 0.99) but high variability for Fitbit Charge 2 HR (–0.57 to 0.74). The Fitbit One device maintained high accuracy and precision values for treadmill walking, but both Garmin Vivosmart and Fitbit Charge 2 HR (the wrist-worn devices) had worse accuracy and precision for treadmill walking. Conclusions The waist-worn sensor (Fitbit One) was accurate and precise in measuring steps with overground and treadmill walking. The wrist-worn sensors were accurate and precise only during overground walking. Similar research should inform the application of these devices in clinical research and practice involving patients with PD.

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The current study examined the validity of scores from the sitting time item on the International Physical Activity Questionnaire-Short Form (IPAQ-SF) in a sample of persons with multiple sclerosis (MS). Method: Persons with MS were recruited through the distribution of printed letters to a random sample of 1,000 persons from the North American Research Committee on MS registry. Two hundred ninety-five persons with MS were interested and volunteered to wear an ActiGraph accelerometer for a 7-day period and complete a battery of questionnaires that included the IPAQ-SF and Godin Leisure-Time Exercise Questionnaire over this period of time. Results: IPAQ-SF sitting time scores were consistently and moderately correlated with all of the sedentary behavior metrics from the accelerometer (range of r between .295 and .431), and the correlations were stronger than those between self-reported physical activity and sedentary metrics from the accelerometer (range of r between Ϫ.087 and .163). The correlations between IPAQ-SF sitting time scores with the accelerometer-derived sedentary behavior metrics were still statistically significant in the analyses controlling for physical activity (range of parametric correlations between .281 and .411). Conclusions:The correlation analysis indicated consistent, moderate correlations between IPAQ-SF sitting time scores and device-measured estimates of both the volume and pattern of sedentary behavior, and the correlations were (a) stronger than those for self-reported physical activity and (b) independent of self-reported physical activity. Such results provide initial evidence for the validity of inferences from IPAQ-SF sitting time scores as an overall measure of sedentary behavior in persons with MS. Impact and ImplicationsThere is an abundance of research on physical activity in multiple sclerosis, but much less is known about sedentary behavior. This study provides evidence for the validity of inferences from the International Physical Activity Questionnaire-Short Form sitting time scores as a measure of sedentary behavior in multiple sclerosis. The evidence provides support for meaningful interpretations from existing and future research on the prevalence, correlates, and interventions focusing on sedentary behavior in multiple sclerosis.

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