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Fraudulent Data Detection and Prevention Within the National Caregiver Survey

The National Caregiver Survey is an online, incentivized survey that aims to gather information about the health and coping strategies used by Black family caregivers of persons with dementia. The survey data will help elucidate the relationships between coping, health, and adaptation to family care...

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Detalles Bibliográficos
Autores principales: Jackson, Jada, Lipchin, Jessica, Zhang, Rachel, Robinson-Lane, Sheria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8970257/
http://dx.doi.org/10.1093/geroni/igab046.2935
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author Jackson, Jada
Lipchin, Jessica
Zhang, Rachel
Robinson-Lane, Sheria
author_facet Jackson, Jada
Lipchin, Jessica
Zhang, Rachel
Robinson-Lane, Sheria
author_sort Jackson, Jada
collection PubMed
description The National Caregiver Survey is an online, incentivized survey that aims to gather information about the health and coping strategies used by Black family caregivers of persons with dementia. The survey data will help elucidate the relationships between coping, health, and adaptation to family caregiving and facilitate the development of culturally responsive caregiver support programming. Virtually distributing this survey made it cost-effective, easily accessible, and quick to produce usable data. The online format also helped the team reach caregivers from across the nation, as well as keep participants safe during the COVID-19 pandemic. Unfortunately, because online surveys are advertised and administered digitally, they become targets for hacking, especially when the surveys are incentivized. The hacking attempts are executed through digital survey bots and threaten the integrity of the collected data. These corrupt responses also increase study costs by falsely rewarding the hackers for their survey responses and research team time in the investigation, detection, and removal of fraudulent responses. To detect potential bots, a reCAPTCHA bot system was incorporated into the survey, and survey questions were formatted specifically to thwart hacking attempts. Finally, data were cleaned to remove illogical, inconsistent, and duplicative surveys. Findings from this work may help researchers improve online survey design and data collection methods to provide greater confidence in conclusions drawn from virtually surveyed data.
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spelling pubmed-89702572022-04-01 Fraudulent Data Detection and Prevention Within the National Caregiver Survey Jackson, Jada Lipchin, Jessica Zhang, Rachel Robinson-Lane, Sheria Innov Aging Abstracts The National Caregiver Survey is an online, incentivized survey that aims to gather information about the health and coping strategies used by Black family caregivers of persons with dementia. The survey data will help elucidate the relationships between coping, health, and adaptation to family caregiving and facilitate the development of culturally responsive caregiver support programming. Virtually distributing this survey made it cost-effective, easily accessible, and quick to produce usable data. The online format also helped the team reach caregivers from across the nation, as well as keep participants safe during the COVID-19 pandemic. Unfortunately, because online surveys are advertised and administered digitally, they become targets for hacking, especially when the surveys are incentivized. The hacking attempts are executed through digital survey bots and threaten the integrity of the collected data. These corrupt responses also increase study costs by falsely rewarding the hackers for their survey responses and research team time in the investigation, detection, and removal of fraudulent responses. To detect potential bots, a reCAPTCHA bot system was incorporated into the survey, and survey questions were formatted specifically to thwart hacking attempts. Finally, data were cleaned to remove illogical, inconsistent, and duplicative surveys. Findings from this work may help researchers improve online survey design and data collection methods to provide greater confidence in conclusions drawn from virtually surveyed data. Oxford University Press 2021-12-17 /pmc/articles/PMC8970257/ http://dx.doi.org/10.1093/geroni/igab046.2935 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Jackson, Jada
Lipchin, Jessica
Zhang, Rachel
Robinson-Lane, Sheria
Fraudulent Data Detection and Prevention Within the National Caregiver Survey
title Fraudulent Data Detection and Prevention Within the National Caregiver Survey
title_full Fraudulent Data Detection and Prevention Within the National Caregiver Survey
title_fullStr Fraudulent Data Detection and Prevention Within the National Caregiver Survey
title_full_unstemmed Fraudulent Data Detection and Prevention Within the National Caregiver Survey
title_short Fraudulent Data Detection and Prevention Within the National Caregiver Survey
title_sort fraudulent data detection and prevention within the national caregiver survey
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8970257/
http://dx.doi.org/10.1093/geroni/igab046.2935
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