Syed Naeem, Tyler Jones, Joseph Daniel, Jordy Mehawej, Andreas Filippaios, Tenes Paul, Ziyue Wang, Sakeina Howard-Wilson, Darleen Lessard, Eric Ding, Edith Mensah Otabil, Kamran Noorishirazi, Apurv Soni, Jane Saczynski, Khanh-Van Tran, David McManus
{"title":"使用智能手表监测心房颤动的脑卒中幸存者的收入与社会心理因素的关系。","authors":"Syed Naeem, Tyler Jones, Joseph Daniel, Jordy Mehawej, Andreas Filippaios, Tenes Paul, Ziyue Wang, Sakeina Howard-Wilson, Darleen Lessard, Eric Ding, Edith Mensah Otabil, Kamran Noorishirazi, Apurv Soni, Jane Saczynski, Khanh-Van Tran, David McManus","doi":"10.26502/fccm.92920404","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Timely detection of atrial fibrillation (AF) is critical for stroke prevention. Smartwatches are FDA-approved devices that can now aide in this detection.</p><p><strong>Objective: </strong>Investigate how socioeconomic status is associated with self-reported psychosocial outcomes, including anxiety, patient activation, and health-related quality of life in stroke survivors using smartwatch for AF detection.</p><p><strong>Methods: </strong>We analyzed data from the Pulsewatch study, a randomized controlled trial (NCT03761394). Participants in the intervention group wore a cardiac patch monitor in addition to a smartwatch for AF detection, whereas the control group wore only the cardiac patch monitor. Generalized anxiety disorder-7 scale, Consumer Health Activation Index and short-form health survey were completed to assess anxiety, patient activation, physical and mental health status at baseline, 14, and 44 days. We used a longitudinal linear regression model to examine changes in psychosocial outcomes in low (<$50K) vs. high (>$50K) income groups.</p><p><strong>Results: </strong>A total of 95 participants (average age 64.9± 9.1 years; 57.9% male; 89.5% non-Hispanic white) were included. History of renal disease (p-value 0.029), statin use (p-value 0.034), depression (p-value 0.004), and anxiety (p-value <0.001), were different between the income groups. In the adjusted model, the low-income group was associated with increased anxiety (β 2.75, p-value 0.0003), and decreased physical health status (β -5.07, p-value 0.02). There was no change identified in self-reported patient engagement and mental health status score.</p><p><strong>Conclusion: </strong>Our findings demonstrate that low SES is associated with worse self-reporting of physical health status, and this may influence psychosocial outcomes in smartwatch users.</p>","PeriodicalId":72523,"journal":{"name":"Cardiology and cardiovascular medicine","volume":"8 5","pages":"433-439"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11529826/pdf/","citationCount":"0","resultStr":"{\"title\":\"Income in Relation to Psychosocial Factors Among Stroke Survivors using Smartwatches for Atrial Fibrillation Monitoring.\",\"authors\":\"Syed Naeem, Tyler Jones, Joseph Daniel, Jordy Mehawej, Andreas Filippaios, Tenes Paul, Ziyue Wang, Sakeina Howard-Wilson, Darleen Lessard, Eric Ding, Edith Mensah Otabil, Kamran Noorishirazi, Apurv Soni, Jane Saczynski, Khanh-Van Tran, David McManus\",\"doi\":\"10.26502/fccm.92920404\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Timely detection of atrial fibrillation (AF) is critical for stroke prevention. Smartwatches are FDA-approved devices that can now aide in this detection.</p><p><strong>Objective: </strong>Investigate how socioeconomic status is associated with self-reported psychosocial outcomes, including anxiety, patient activation, and health-related quality of life in stroke survivors using smartwatch for AF detection.</p><p><strong>Methods: </strong>We analyzed data from the Pulsewatch study, a randomized controlled trial (NCT03761394). Participants in the intervention group wore a cardiac patch monitor in addition to a smartwatch for AF detection, whereas the control group wore only the cardiac patch monitor. Generalized anxiety disorder-7 scale, Consumer Health Activation Index and short-form health survey were completed to assess anxiety, patient activation, physical and mental health status at baseline, 14, and 44 days. We used a longitudinal linear regression model to examine changes in psychosocial outcomes in low (<$50K) vs. high (>$50K) income groups.</p><p><strong>Results: </strong>A total of 95 participants (average age 64.9± 9.1 years; 57.9% male; 89.5% non-Hispanic white) were included. History of renal disease (p-value 0.029), statin use (p-value 0.034), depression (p-value 0.004), and anxiety (p-value <0.001), were different between the income groups. In the adjusted model, the low-income group was associated with increased anxiety (β 2.75, p-value 0.0003), and decreased physical health status (β -5.07, p-value 0.02). There was no change identified in self-reported patient engagement and mental health status score.</p><p><strong>Conclusion: </strong>Our findings demonstrate that low SES is associated with worse self-reporting of physical health status, and this may influence psychosocial outcomes in smartwatch users.</p>\",\"PeriodicalId\":72523,\"journal\":{\"name\":\"Cardiology and cardiovascular medicine\",\"volume\":\"8 5\",\"pages\":\"433-439\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11529826/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cardiology and cardiovascular medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26502/fccm.92920404\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cardiology and cardiovascular medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26502/fccm.92920404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/11 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Income in Relation to Psychosocial Factors Among Stroke Survivors using Smartwatches for Atrial Fibrillation Monitoring.
Background: Timely detection of atrial fibrillation (AF) is critical for stroke prevention. Smartwatches are FDA-approved devices that can now aide in this detection.
Objective: Investigate how socioeconomic status is associated with self-reported psychosocial outcomes, including anxiety, patient activation, and health-related quality of life in stroke survivors using smartwatch for AF detection.
Methods: We analyzed data from the Pulsewatch study, a randomized controlled trial (NCT03761394). Participants in the intervention group wore a cardiac patch monitor in addition to a smartwatch for AF detection, whereas the control group wore only the cardiac patch monitor. Generalized anxiety disorder-7 scale, Consumer Health Activation Index and short-form health survey were completed to assess anxiety, patient activation, physical and mental health status at baseline, 14, and 44 days. We used a longitudinal linear regression model to examine changes in psychosocial outcomes in low (<$50K) vs. high (>$50K) income groups.
Results: A total of 95 participants (average age 64.9± 9.1 years; 57.9% male; 89.5% non-Hispanic white) were included. History of renal disease (p-value 0.029), statin use (p-value 0.034), depression (p-value 0.004), and anxiety (p-value <0.001), were different between the income groups. In the adjusted model, the low-income group was associated with increased anxiety (β 2.75, p-value 0.0003), and decreased physical health status (β -5.07, p-value 0.02). There was no change identified in self-reported patient engagement and mental health status score.
Conclusion: Our findings demonstrate that low SES is associated with worse self-reporting of physical health status, and this may influence psychosocial outcomes in smartwatch users.