scholarly journals STARR - Decision SupporT and self-mAnagement system for stRoke survivoRs Vision based Rehabilitation System

2017 ◽  
Author(s):  
Abd El Rahman Shabayek ◽  
Renato Baptista ◽  
Konstantinos Papadopoulos ◽  
Girum Demisse ◽  
Oyebade Oyedotun ◽  
...  
Keyword(s):  
Decision Support ◽  
Management System ◽  
Self Management ◽  
Stroke Survivors ◽  
Rehabilitation System

scholarly journals A Personalized Self-Management Rehabilitation System with an Intelligent Shoe for Stroke Survivors: A Realist Evaluation

2016 ◽  
Vol 3 (1) ◽  
pp. e1 ◽  
Author(s):  
Susan Mawson ◽  
Nasrin Nasr ◽  
Jack Parker ◽  
Richard Davies ◽  
Huiru Zheng ◽  
...  
Keyword(s):  
Realist Evaluation ◽  
Self Management ◽  
Stroke Survivors ◽  
Rehabilitation System

scholarly journals A Personalized Self-Management Rehabilitation System for Stroke Survivors: A Quantitative Gait Analysis Using a Smart Insole

2016 ◽  
Vol 3 (2) ◽  
pp. e11 ◽  
Author(s):  
Richard John Davies ◽  
Jack Parker ◽  
Paul McCullagh ◽  
Huiru Zheng ◽  
Chris Nugent ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Self Management ◽  
Stroke Survivors ◽  
Rehabilitation System ◽  
Smart Insole ◽  
Quantitative Gait Analysis

PP316 Efficacy And Usability Of eHealth Technologies In Stroke Survivors For Improvement Of Self-Management: Clinical Trial

2020 ◽  
Vol 36 (S1) ◽  
pp. 28-28
Author(s):  
Eunate Arana Arri ◽  
Leire Ortiz-Fernández ◽  
Janire Orcajo ◽  
Rubén García Fernández ◽  
Joana Sagastagoya ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Decision Support ◽  
Conventional Treatment ◽  
Intervention Group ◽  
Self Management ◽  
Control Group ◽  
Stroke Survivors ◽  
Patient Profile ◽  
System Usability Scale

IntroductionStroke is a leading cause of severe and long-term disability in developed countries. Around 15 million people suffer a stroke each year, most due to modifiable risk factors. Several reviews have shown that interventions mediating eHealth technologies can reduce the risk of suffering a stroke episode, improving the control of risk factors; nevertheless, all of them conclude that new and well-designed studies are needed.MethodsWe performed a prospective, randomized, parallel group and open, pilot trial. The study was carried out based on an initial sample of forty-three patients between 18 and 80 years old who have had an ischemic stroke. The control group got conventional treatment and the intervention group got conventional treatment and the assistance of STARR (the Decision SupporT and self-mAnagement system for stRoke survivoRs), as well as commercial wearables. The principal variable of the study was to evaluate the usability of the decision support system.ResultsAt month nine, the average score on the System Usability Scale in the intervention group was 64.7 and in month 12, 67.4, exceeding in both cases the margin of acceptability (50) and in the limit of “good” (68). When we analyzed clinical factors (systolic/diastolic blood pressure) as well as the analytical parameters related to prevention of reinfarction, we observed that the intervention group had good control of blood pressure and better analytical parameters, compared to the control group.ConclusionsTechnological support allowed participants to feel comfortable using the devices as well as resolving technical incidences by themselves after a training period. The self-management platform can be efficient in stroke survivors’ management of their disease condition, improving analytical and clinical parameters, which eventually can influence a decrease in associated comorbidities and, therefore, improvement of the disease. However, it should be noted that this type of platform is not useful for every patient profile, and studies in this regard should be expanded.

scholarly journals Efficacy and Usability of eHealth Technologies in Stroke Survivors for Prevention of a New Stroke and Improvement of Self-Management: Phase III Randomized Control Trial

2019 ◽  
Vol 2 (2) ◽  
pp. 50
Author(s):  
Leire Ortiz-Fernández ◽  
Joana Sagastagoya Zabala ◽  
Agustín Gutiérrez-Ruiz ◽  
Natale Imaz-Ayo ◽  
Ander Alava-Menica ◽  
...  
Keyword(s):  
Decision Support ◽  
Pilot Trial ◽  
Standard Of Care ◽  
Developed Countries ◽  
Phase Iii ◽  
Self Management ◽  
Stroke Survivors ◽  
Patient Report Outcome ◽  
Adult Survivor ◽  
Patient Report Outcome Measure

Background: Stroke is a leading cause of severe and long-term disability in developed countries. Around 15 million people suffer a stroke each year, being most of them ischemic due to modifiable risk factors. Adequate self-management abilities may help to manage the consequences of stroke, but it is unknown which specific intervention could be effective to booster these self-management abilities. Objective: To evaluate the improvement of self-management in chronic stroke survivors using decision support and self-management system (STARR). Methods: A randomized, prospective, parallel group, open, and the unicentric pilot trial will be performed. Stroke survivors and their caregivers will be randomly allocated to STARR management or standard of care. Main inclusion criteria are mild to moderate disabled first stroke adult survivor, living at home, able to cope and follow the guidelines and devices, without socio-familial exclusion. All will get a conventional treatment in the acute and subacute phase; however, in the chronic period, cases will use the developed STARR App and Decision Support System. Measurements will be performed at baseline, at 3 months, and at 6 months. Outcome measures are patient-report outcome measure of self-management competency, physical function, risk factor reduction, healthcare resource utilization, knowledge of the condition, mood, and social isolation. Discussion: If effective, the results of this study will enable stroke patients and their caregivers to deal better with the everyday life obstacles of stroke, improve the adherence of the treatment, improve the control of cardiovascular risk, and, in consequence, reduce the recurrence of secondary strokes, the number of complications, the number of consultations, and readmissions; to ultimately reduce the health systems costs. Taking into consideration that the number of stroke survivors is increasing around the world, a large number of individuals could profit from this intervention.

778-P: The Impact of Self-Management Blood Glucose (SMBG) Real-Time Decision Support on Glycemic Control in Adult with T1D in China

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 778-P
Author(s):  
ZIYU LIU ◽  
CHAOFAN WANG ◽  
XUEYING ZHENG ◽  
SIHUI LUO ◽  
DAIZHI YANG ◽  
...  
Keyword(s):  
Decision Support ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Real Time ◽  
Self Management ◽  
The Impact

MINDSET: Clinic-based decision support demonstrates longitudinal efficacy for increased epilepsy self-management adherence among Spanish speaking patients

2020 ◽  
Vol 113 ◽  
pp. 107552
Author(s):  
Ross Shegog ◽  
Charles Begley ◽  
Jenny Chong ◽  
Refugio Sepulveda ◽  
Robert Addy ◽  
...  
Keyword(s):  
Decision Support ◽  
Self Management ◽  
Spanish Speaking

scholarly journals EXPRESS: Telehealth coaching to improve self-management for secondary prevention after stroke: A randomized controlled trial of Stroke Coach

2021 ◽  
pp. 174749302110176
Author(s):  
Brodie M Sakakibara ◽  
Scott A Lear ◽  
Susan I Barr ◽  
Charles Goldsmith ◽  
Amy Schneeberg ◽  
...  
Keyword(s):  
Risk Factors ◽  
Controlled Trial ◽  
Cognitive Status ◽  
Self Management ◽  
Community Living ◽  
Memory Training ◽  
Stroke Survivors ◽  
Post Intervention ◽  
Lifestyle Behaviour ◽  
Mild Stroke

Background: Stroke Coach is a lifestyle coaching telehealth program to improve self-management of stroke risk factors. Aims: To examine the efficacy of Stroke Coach on lifestyle behaviour and risk factor control among community-living stroke survivors within one-year post stroke. Methods: Participants were randomized to Stroke Coach or an attention control Memory Training group. Lifestyle behaviour was measured using the Health Promoting Lifestyle Profile II. Secondary outcomes included specific behavioural and cardiometabolic risk factors, health-related quality of life (HRQoL), cognitive status, and depressive symptoms. Measurements were taken at baseline, post-intervention (6 months), and retention (12 month). Linear mixed-effects models were used to test the study hypotheses (p<0.05). All analyses were intention-to-treat. Results: The mean age of the Stroke Coach (n=64) and Memory Training (n=62) groups was 67.2 and 69.1 years, respectively. The majority of participants (n = 100) had mild stroke (modified Rankin Scale = 1 or 2), were active, with controlled blood pressure (mean = 129/79 mmHg) at baseline. At post-intervention, there were no significant differences in lifestyle (b = -2.87; 95%CI -8.03 to 2.29; p=0.28). Glucose control, as measured by HbA1c (b = 0.17; 95%CI 0.17 to 0.32; p=0.03), and HRQoL, measured using SF-36 Physical Component Summary (b = -3.05; 95%CI -5.88 to -0.21; p=0.04), were significantly improved in Stroke Coach compared to Memory Training, and the improvements were maintained at retention. Conclusion: Stroke Coach did not improve lifestyle behaviour, however, there were improvements to HbA1c and HRQoL among community-living stroke survivors with mild stroke-related disability. (ClinicalTrials.gov identifier: NCT02207023)

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