Dataset Information

Developing the Florida Academic Cancer Center Alliance Health Disparities Common Measure: The Florida Health and Ancestry Survey.

ABSTRACT:

Purpose

Our specific aim was to develop and assess the consensus-based validity of common measures for understanding health behaviors and ancestry in Florida's population subgroups and establish the feasibility of wide-scale implementation of the measures and biospecimen collection within three cancer centers' catchment areas.

Methods

Using the National Cancer Institute's Grid-Enabled Measures web-based platform and an iterative process, we developed the Florida Health and Ancestry Survey (FHAS). We then used three sampling approaches to implement the FHAS: community-engaged, panel respondent, and random digit dialing (RDD). We asked a subset of participants to provide a saliva sample for future validation of subjective ancestry report with DNA-derived ancestry markers.

Results

This process supported the FHAS content validity. As an indicator of feasibility, the goals for completed surveys by sampling approach were met for two of the three cancer centers, yielding a total of 1438 completed surveys. The RDD approach produced the most representative sample. The panel sampling approach produced inadequate representation of older individuals and males. The community-engaged approach along with social media recruitment produced extreme underrepresentation only for males. Two of the cancer centers mailed biospecimen kits, whereas one did not due to resource constraints. On average, the community engaged approach was more productive in obtaining returned biospecimen samples (80%) than the panel approach (48%).

Conclusions

We successfully developed and implemented the FHAS as a common measure to show its feasibility for understanding cancer health disparities in Florida. We identified sampling approach successes and challenges to obtaining biospecimens for ancestry research.

SUBMITTER: Dyal BW

PROVIDER: S-EPMC9244925 | biostudies-literature |

REPOSITORIES: biostudies-literature

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