Sofiya Milman, Aisha Montgomery, Nir Barzilai, Tina Gao, Kara A Wilson, Thomas Perls, Aoife McGovern Leahy, Elizabeth Burgis, Megan Ruxton, Praduman Jain, Alan R Shuldiner
{"title":"为95岁及以上的成年人设计数字研究平台的量身定制方法:超级老人家庭研究。","authors":"Sofiya Milman, Aisha Montgomery, Nir Barzilai, Tina Gao, Kara A Wilson, Thomas Perls, Aoife McGovern Leahy, Elizabeth Burgis, Megan Ruxton, Praduman Jain, Alan R Shuldiner","doi":"10.1093/gerona/glaf016","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The SuperAgers Family study aims to investigate phenotypic and genetic mechanisms related to healthy aging in nonagenarians, centenarians, and their family members. A remote study design was tested to demonstrate the feasibility of using digital technology to conduct health research within this rare population of advanced age. This paper describes key design elements of the digital research platform developed to deliver consent, enrollment, and study data collection in a cohort of older adults.</p><p><strong>Methods: </strong>SuperAgers participants aged 95 years or older, their offspring, and offspring's spouses were invited to join the study via media and community outreach. Participants completed registration, consent, submitted study data, and completed remote biospecimen collection via the web-based study app. Platform design elements and functionality were adapted for use by older-aged adults. Qualitative process evaluation assessed usability and participant data entry completion throughout the study workflow.</p><p><strong>Results: </strong>Preliminary data from SuperAgers (n = 160) of average age 98 years (±3 standard deviation [SD]) and offspring/spouses (n = 127) of average age 69 years (±5 SD) were evaluated. About 97% of participants in both groups successfully used the platform to complete eligibility screening, eConsent, and study surveys.</p><p><strong>Conclusions: </strong>SuperAgers and offspring successfully used the digital research platform to complete eConsent and submit study data. This supports the feasibility of conducting digitally enabled research in older-aged populations using tailored platform design elements that increase usability and minimize entry errors. These findings may contribute to the development of best practices for digitally delivered research studies in aging populations.</p>","PeriodicalId":94243,"journal":{"name":"The journals of gerontology. Series A, Biological sciences and medical sciences","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926979/pdf/","citationCount":"0","resultStr":"{\"title\":\"Tailored Approach to Designing a Digital Research Platform for Adults Aged 95 and Older: SuperAgers Family Study.\",\"authors\":\"Sofiya Milman, Aisha Montgomery, Nir Barzilai, Tina Gao, Kara A Wilson, Thomas Perls, Aoife McGovern Leahy, Elizabeth Burgis, Megan Ruxton, Praduman Jain, Alan R Shuldiner\",\"doi\":\"10.1093/gerona/glaf016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The SuperAgers Family study aims to investigate phenotypic and genetic mechanisms related to healthy aging in nonagenarians, centenarians, and their family members. A remote study design was tested to demonstrate the feasibility of using digital technology to conduct health research within this rare population of advanced age. This paper describes key design elements of the digital research platform developed to deliver consent, enrollment, and study data collection in a cohort of older adults.</p><p><strong>Methods: </strong>SuperAgers participants aged 95 years or older, their offspring, and offspring's spouses were invited to join the study via media and community outreach. Participants completed registration, consent, submitted study data, and completed remote biospecimen collection via the web-based study app. Platform design elements and functionality were adapted for use by older-aged adults. Qualitative process evaluation assessed usability and participant data entry completion throughout the study workflow.</p><p><strong>Results: </strong>Preliminary data from SuperAgers (n = 160) of average age 98 years (±3 standard deviation [SD]) and offspring/spouses (n = 127) of average age 69 years (±5 SD) were evaluated. About 97% of participants in both groups successfully used the platform to complete eligibility screening, eConsent, and study surveys.</p><p><strong>Conclusions: </strong>SuperAgers and offspring successfully used the digital research platform to complete eConsent and submit study data. This supports the feasibility of conducting digitally enabled research in older-aged populations using tailored platform design elements that increase usability and minimize entry errors. These findings may contribute to the development of best practices for digitally delivered research studies in aging populations.</p>\",\"PeriodicalId\":94243,\"journal\":{\"name\":\"The journals of gerontology. Series A, Biological sciences and medical sciences\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926979/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The journals of gerontology. Series A, Biological sciences and medical sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/gerona/glaf016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The journals of gerontology. Series A, Biological sciences and medical sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/gerona/glaf016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tailored Approach to Designing a Digital Research Platform for Adults Aged 95 and Older: SuperAgers Family Study.
Background: The SuperAgers Family study aims to investigate phenotypic and genetic mechanisms related to healthy aging in nonagenarians, centenarians, and their family members. A remote study design was tested to demonstrate the feasibility of using digital technology to conduct health research within this rare population of advanced age. This paper describes key design elements of the digital research platform developed to deliver consent, enrollment, and study data collection in a cohort of older adults.
Methods: SuperAgers participants aged 95 years or older, their offspring, and offspring's spouses were invited to join the study via media and community outreach. Participants completed registration, consent, submitted study data, and completed remote biospecimen collection via the web-based study app. Platform design elements and functionality were adapted for use by older-aged adults. Qualitative process evaluation assessed usability and participant data entry completion throughout the study workflow.
Results: Preliminary data from SuperAgers (n = 160) of average age 98 years (±3 standard deviation [SD]) and offspring/spouses (n = 127) of average age 69 years (±5 SD) were evaluated. About 97% of participants in both groups successfully used the platform to complete eligibility screening, eConsent, and study surveys.
Conclusions: SuperAgers and offspring successfully used the digital research platform to complete eConsent and submit study data. This supports the feasibility of conducting digitally enabled research in older-aged populations using tailored platform design elements that increase usability and minimize entry errors. These findings may contribute to the development of best practices for digitally delivered research studies in aging populations.