Feasibility of Using a Mobile Application for the Monitoring and Management of Stroke-Associated Risk Factors
Initiatives
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The objective of this study was to test the feasibility of using a smartphone software application (app) for the management of vascular risk factors in patients with stroke.
Note: All published information has been collected from the article referenced in the Marker Paper box below. Therefore, there may be variations with more advanced versions of the study.
- Start Year
- 2013
- End Year
- 2014
Design
- Study design
- Clinical trial cohort
Marker Paper
Seo WK, Kang J, Jeon M, et al. Feasibility of using a mobile application for the monitoring and management of stroke-associated risk factors [published correction appears in J Clin Neurol. 2015 Jul;11(3):295]. J Clin Neurol. 2015;11(2):142‐148. doi:10.3988/jcn.2015.11.2.142
PUBMED 25851892
Recruitment
- Sources of Recruitment
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- Individuals
Number of participants
- Number of participants
- 47
- Number of participants with biosamples
Access
Availability of data and biosamples
| Data | |
| Biosamples | |
| Other |
Timeline
Patients with stroke
This prospective clinical trial developed a smartphone app, the 'Korea University Health Monitoring System for Stroke: KUHMS2,' for use by patients with stroke. During a 6-month follow-up period, its feasibility was assessed by measuring the changes in their vascular risk-factor profiles and the number of days per patient with data registration into the app.
Selection Criteria
- Newborns
- Twins
- Countries
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- South Korea
- Ethnic Origin
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- Health Status
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- Patients with stroke
Recruitment
- Sources of recruitment
-
- Clinical patients
Number of participants
- Number of participants
- 48
- Number of participants with biosamples
Data Collection Event
This prospective clinical trial developed a smartphone app, the 'Korea University Health Monitoring System for Stroke: KUHMS2,' for use by patients with stroke.
- Start Date
-
2013-02
- End Date
-
2014-01
- Data sources
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Mobile data collection
- Smartphone apps
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Mobile data collection