Qualitative feasibility study of the mobile app Destroke for clinical stroke monitoring based on the NIH stroke scale
Background: Stroke is a leading cause of severe disability in the United States, but there is no effective method for patients to accurately detect the signs of stroke at home. We developed a mobile app, Destroke, that allows remote performance of a modified NIH stroke scale (NIHSS) by patients. Aim...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-08-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023056013 |
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| author | Evan K. Noch Dan Pham Tomoko Kitago Marissa Wuennemann Susan Wortman-Jutt M. Cristina Falo |
| author_facet | Evan K. Noch Dan Pham Tomoko Kitago Marissa Wuennemann Susan Wortman-Jutt M. Cristina Falo |
| author_sort | Evan K. Noch |
| collection | DOAJ |
| description | Background: Stroke is a leading cause of severe disability in the United States, but there is no effective method for patients to accurately detect the signs of stroke at home. We developed a mobile app, Destroke, that allows remote performance of a modified NIH stroke scale (NIHSS) by patients. Aims: To assess the feasibility of a mobile app for stroke monitoring and education by patients with a history of stroke. Materials and methods: We enrolled 25 patients with a history of stroke in a prospective open-label study to evaluate the feasibility of the Destroke app in patients with stroke. Nineteen patients completed all study assessments, with a median time from stroke onset to enrollment of 5.6 years (range 0.1–12 years). We designed a modified NIHSS that assessed 12 out of 16 tasks on the NIHSS. Patients completed this test eight times over a 28-day period. We conducted pre-study surveys that assessed demographic information, stroke and cardiovascular history, baseline NIHSS, and experience using mobile technologies, and mid- and post-study surveys that assessed patient satisfaction on app usage and confidence in stroke detection. Results: Ten men and nine women participated in this study (median age of 64 (33–76)), representing ten US states and Washington D.C. Median baseline NIHSS was 0 (0–4). 15 patients reported using health apps. On a 5-point Likert scale, patients rated the app as 4.2 on being able to understand and use the app and 4.3 on using the app when instructed by their doctor. For eight patients with poor confidence in detecting the signs of a stroke before the study, six showed higher confidence after the study. Conclusions: The use of an at-home stroke monitoring app is feasible by patients with a history of stroke and improves confidence in detecting the signs of stroke. |
| first_indexed | 2024-03-12T12:23:09Z |
| format | Article |
| id | doaj.art-e83e517e2a42488daee5e5bd538fb84b |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-12T12:23:09Z |
| publishDate | 2023-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-e83e517e2a42488daee5e5bd538fb84b2023-08-30T05:51:10ZengElsevierHeliyon2405-84402023-08-0198e18393Qualitative feasibility study of the mobile app Destroke for clinical stroke monitoring based on the NIH stroke scaleEvan K. Noch0Dan Pham1Tomoko Kitago2Marissa Wuennemann3Susan Wortman-Jutt4M. Cristina Falo5Department of Neurology, Weill Cornell Medicine, New York, NY, USA; Destroke, Inc., USADestroke, Inc., USAWestchester Medical Center, Valhalla, NY, USABurke Neurological Institute, White Plains, NY, USABurke Neurological Institute, White Plains, NY, USAWestchester Medical Center, Valhalla, NY, USA; Corresponding author. Westchester Medical Center, Valhalla, NY, USABackground: Stroke is a leading cause of severe disability in the United States, but there is no effective method for patients to accurately detect the signs of stroke at home. We developed a mobile app, Destroke, that allows remote performance of a modified NIH stroke scale (NIHSS) by patients. Aims: To assess the feasibility of a mobile app for stroke monitoring and education by patients with a history of stroke. Materials and methods: We enrolled 25 patients with a history of stroke in a prospective open-label study to evaluate the feasibility of the Destroke app in patients with stroke. Nineteen patients completed all study assessments, with a median time from stroke onset to enrollment of 5.6 years (range 0.1–12 years). We designed a modified NIHSS that assessed 12 out of 16 tasks on the NIHSS. Patients completed this test eight times over a 28-day period. We conducted pre-study surveys that assessed demographic information, stroke and cardiovascular history, baseline NIHSS, and experience using mobile technologies, and mid- and post-study surveys that assessed patient satisfaction on app usage and confidence in stroke detection. Results: Ten men and nine women participated in this study (median age of 64 (33–76)), representing ten US states and Washington D.C. Median baseline NIHSS was 0 (0–4). 15 patients reported using health apps. On a 5-point Likert scale, patients rated the app as 4.2 on being able to understand and use the app and 4.3 on using the app when instructed by their doctor. For eight patients with poor confidence in detecting the signs of a stroke before the study, six showed higher confidence after the study. Conclusions: The use of an at-home stroke monitoring app is feasible by patients with a history of stroke and improves confidence in detecting the signs of stroke.http://www.sciencedirect.com/science/article/pii/S2405844023056013Stroke detectionStroke educationMobile appDigital health |
| spellingShingle | Evan K. Noch Dan Pham Tomoko Kitago Marissa Wuennemann Susan Wortman-Jutt M. Cristina Falo Qualitative feasibility study of the mobile app Destroke for clinical stroke monitoring based on the NIH stroke scale Heliyon Stroke detection Stroke education Mobile app Digital health |
| title | Qualitative feasibility study of the mobile app Destroke for clinical stroke monitoring based on the NIH stroke scale |
| title_full | Qualitative feasibility study of the mobile app Destroke for clinical stroke monitoring based on the NIH stroke scale |
| title_fullStr | Qualitative feasibility study of the mobile app Destroke for clinical stroke monitoring based on the NIH stroke scale |
| title_full_unstemmed | Qualitative feasibility study of the mobile app Destroke for clinical stroke monitoring based on the NIH stroke scale |
| title_short | Qualitative feasibility study of the mobile app Destroke for clinical stroke monitoring based on the NIH stroke scale |
| title_sort | qualitative feasibility study of the mobile app destroke for clinical stroke monitoring based on the nih stroke scale |
| topic | Stroke detection Stroke education Mobile app Digital health |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023056013 |
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