TY - JOUR
T1 - Implications of Geographic Information Systems (GIS) for targeted recruitment of older adults with dementia and their caregivers in the community
T2 - A retrospective analysis
AU - Scerpella, Danny L.
AU - Adam, Atif
AU - Marx, Katherine
AU - Gitlin, Laura N.
N1 - Publisher Copyright:
© 2019 The Authors
PY - 2019/6
Y1 - 2019/6
N2 - 5.5 million Americans are living with Alzheimer's dementia (AD) or related dementias. Developing evidence-based interventions for these people and their caregivers (dyads) is a public health priority, and is highly dependent on recruiting representatives from the community. Precision recruitment methodologies are needed to improve the efficiency of this process. Geographic Information Systems (GIS) offer the potential to determine location trends of an older adult population of people living with dementia in the community and their caregivers. American Community Survey (ACS) 2015 5-year estimates were analyzed at the census tract level in ESRI ArcMap v. 10.5.1. Datasets included summarized estimates of age, gender, income, and education in Maryland. Using a two-step process, geographic regions were identified in ArcMap that contained various combinations of available data variables. These areas were compared to participant locations from a previously completed traditional recruitment effort to determine overlap (Dementia Behavior Study - R01AGO41781). The largest number of existing participants were identified in derived regions defined by combining age, education, gender, and income variables; predicting 184 (79%) of 234 participants regardless of the population density within census tracts. 208 (89%) were identified when matching this variable combination to the highest density census tracts (city/urban), and 66 (28%) in regions with the lowest population density (rural). This study successfully defined specific geographic regions in the state of Maryland that overlapped with a large number of known dementia dyad locations obtained via traditional recruitment efforts. Implications for these findings allow for more targeted recruitment efforts of difficult to recruit populations, and less utilization of resources for doing so.
AB - 5.5 million Americans are living with Alzheimer's dementia (AD) or related dementias. Developing evidence-based interventions for these people and their caregivers (dyads) is a public health priority, and is highly dependent on recruiting representatives from the community. Precision recruitment methodologies are needed to improve the efficiency of this process. Geographic Information Systems (GIS) offer the potential to determine location trends of an older adult population of people living with dementia in the community and their caregivers. American Community Survey (ACS) 2015 5-year estimates were analyzed at the census tract level in ESRI ArcMap v. 10.5.1. Datasets included summarized estimates of age, gender, income, and education in Maryland. Using a two-step process, geographic regions were identified in ArcMap that contained various combinations of available data variables. These areas were compared to participant locations from a previously completed traditional recruitment effort to determine overlap (Dementia Behavior Study - R01AGO41781). The largest number of existing participants were identified in derived regions defined by combining age, education, gender, and income variables; predicting 184 (79%) of 234 participants regardless of the population density within census tracts. 208 (89%) were identified when matching this variable combination to the highest density census tracts (city/urban), and 66 (28%) in regions with the lowest population density (rural). This study successfully defined specific geographic regions in the state of Maryland that overlapped with a large number of known dementia dyad locations obtained via traditional recruitment efforts. Implications for these findings allow for more targeted recruitment efforts of difficult to recruit populations, and less utilization of resources for doing so.
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U2 - 10.1016/j.conctc.2019.100338
DO - 10.1016/j.conctc.2019.100338
M3 - Article
C2 - 30899836
AN - SCOPUS:85062489429
SN - 2451-8654
VL - 14
JO - Contemporary Clinical Trials Communications
JF - Contemporary Clinical Trials Communications
M1 - 100338
ER -