Optimized probability sampling of study sites to improve generalizability in a multisite intervention trial.
BACKGROUND
Studies of type 2 translation, the adaption of evidence-based interventions to real-world settings, should include representative study sites and staff to improve external validity. Sites for such studies are, however, often selected by convenience sampling, which limits generalizability. We used an optimized probability sampling protocol to select an unbiased, representative sample of study sites to prepare for a randomized trial of a weight loss intervention.


METHODS
We invited North Carolina health departments within 200 miles of the research center to participate (N = 81). Of the 43 health departments that were eligible, 30 were interested in participating. To select a representative and feasible sample of 6 health departments that met inclusion criteria, we generated all combinations of 6 from the 30 health departments that were eligible and interested. From the subset of combinations that met inclusion criteria, we selected 1 at random.


RESULTS
Of 593,775 possible combinations of 6 counties, 15,177 (3%) met inclusion criteria. Sites in the selected subset were similar to all eligible sites in terms of health department characteristics and county demographics.


CONCLUSIONS
Optimized probability sampling improved generalizability by ensuring an unbiased and representative sample of study sites.
Kraschnewski
Jennifer L
JL
University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Keyserling
Thomas C
TC
Bangdiwala
Shrikant I
SI
Gizlice
Ziya
Z
Garcia
Beverly A
BA
Johnston
Larry F
LF
Gustafson
Alison
A
Petrovic
Lindsay
L
Glasgow
Russell E
RE
Samuel-Hodge
Carmen D
CD
D000328:Adult; D005260:Female; D006077:Government Agencies; D006282:Health Personnel; D006296:Health Services / Q000706:statistics & numerical data; D006302:Health Services Research / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D008875:Middle Aged; D009657:North Carolina / Q000453:epidemiology; D050177:Overweight / Q000453:epidemiology / Q000628:therapy; D011203:Poverty; D012494:Sampling Studies; D013219:State Government; D015431:Weight Loss