Implications of Geographic Information Systems (GIS) for targeted recruitment of older adults with dementia and their caregivers in the community: A retrospective analysis

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Article number100338
JournalContemporary Clinical Trials Communications
Volume14
DOIs
StatePublished - Jun 1 2019

Fingerprint

Geographic Information Systems
Caregivers
Dementia
Censuses
Population Density
Education
Health Priorities
Population
Alzheimer Disease
Public Health

ASJC Scopus subject areas

  • Pharmacology

Cite this

@article{e4b34bb9177d4cde987fea030b27eea7,
title = "Implications of Geographic Information Systems (GIS) for targeted recruitment of older adults with dementia and their caregivers in the community: A retrospective analysis",
abstract = "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.",
author = "Scerpella, {Danny L.} and Atif Adam and Katherine Marx and Gitlin, {Laura N}",
year = "2019",
month = "6",
day = "1",
doi = "10.1016/j.conctc.2019.100338",
language = "English (US)",
volume = "14",
journal = "Contemporary Clinical Trials Communications",
issn = "2451-8654",
publisher = "Elsevier Inc.",

}

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

PY - 2019/6/1

Y1 - 2019/6/1

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.

UR - http://www.scopus.com/inward/record.url?scp=85062489429&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85062489429&partnerID=8YFLogxK

U2 - 10.1016/j.conctc.2019.100338

DO - 10.1016/j.conctc.2019.100338

M3 - Article

C2 - 30899836

AN - SCOPUS:85062489429

VL - 14

JO - Contemporary Clinical Trials Communications

JF - Contemporary Clinical Trials Communications

SN - 2451-8654

M1 - 100338

ER -