Posted by Kostas Pantremenos in REHABILITATION on August 18, 2020
Physical activity (PA) is a key health behavior in people with stroke including risk reduction of recurrent stroke. Despite the beneficial effects of PA, many community-dwelling stroke survivors are physically inactive. Information and communication technologies are emerging as a possible method to promote adherence to PA.
The aim of this study is to investigate the effectiveness of a mobile-health (mHealth) App in improving levels of PA.
Forty-one chronic stroke survivors were randomized into an intervention group (IG) n=24 and a control group (CG) n=17. Participants in the IG were engaged in the Multimodal Rehabilitation Program (MMRP) that consisted on supervising adherence to PA through a mHealth app, participating in an 8-week rehabilitation program that included: aerobic, task-oriented, balance and stretching exercises. Participants also performed an ambulation program at home. The CG received a conventional rehabilitation program. Outcome variables were: adherence to PA, (walking and sitting time/day), walking speed (10MWT); walking endurance (6MWT); risk of falling (TUG); ADLs (Barthel); QoL (Eq-5D5L) and participant’s satisfaction.
At the end of the intervention, community ambulation increased more in IG (38.95 min; SD: 20.37) than in the CG (9.47 min; SD: 12.11) (p≤.05). Sitting time was reduced by 2.96 (SD 2.0) hours/day in the IG and by 0.53 (SD 0.24) hours in the CG (p≤.05).
The results suggest that mHealth technology provides a novel way to promote adherence to home exercise programs post stroke. However, frequent support and guidance of caregiver is required to ensure the use of mobile devices.
Source: https://www.tandfonline.com/doi/full/10.1080/10749357.2019.1691816?scroll=top&needAccess=true
Posted by Kostas Pantremenos in REHABILITATION on July 14, 2017
The aim of this study was to describe accelerometer-derived sleep duration, sedentary behavior, physical activity, and quality of life and their association with demographic and clinical factors within the first month after inpatient stroke rehabilitation.
Thirty people with stroke (mean ± standard deviation, age: 63.8 ± 12.3 years, time since stroke: 3.6 ± 1.1 months) wore an activPAL3 Micro accelerometer (PAL Technologies, Glasgow, Scotland) continuously for 7 days to measure whole-day activity behavior. The Stroke Impact Scale and the Functional Independence Measure were used to assess quality of life and function, respectively.
Sleep duration ranged from 6.6 to 11.6 hours/day. Fifteen participants engaged in long sleep greater than 9 hours/day. Participants spent 74.8% of waking hours in sedentary behavior, 17.9% standing, and 7.3% stepping. Of stepping time, only a median of 1.1 (interquartile range: .3-5.8) minutes were spent walking at a moderate-to-vigorous intensity (≥100 steps/minute). The time spent sedentary, the stepping time, and the number of steps differed significantly by the hemiparetic side (P < .05), but not by sex or the type of stroke. There were moderate to strong correlations between the stepping time and the number of steps with gait speed (Spearman r = .49 and .61 respectively, P < .01). Correlations between accelerometer-derived variables and age, time since stroke, and cognition were not significant.
People with stroke sleep for longer than the normal duration, spend about three quarters of their waking hours in sedentary behaviors, and engage in minimal walking following stroke rehabilitation. Our findings provide a rationale for the development of behavior change strategies after stroke.
TBI Rehabilitation 