BACKGROUND: Surveys of community-based programs are difficult to conduct when there is virtually no information about the number or locations of the programs of interest. This article describes the methodology used by the Helping Young Smokers Quit (HYSQ) initiative to identify and profile community-based youth smoking cessation programs in the absence of a defined sample frame. METHODS: We developed a two-stage sampling design, with counties as the first-stage probability sampling units. The second stage used snowball sampling to saturation, to identify individuals who administered youth smoking cessation programs across three economic sectors in each county. Multivariate analyses modeled the relationship between program screening, eligibility, and response rates and economic sector and stratification criteria. Cumulative logit models analyzed the relationship between the number of contacts in a county and the number of programs screened, eligible, or profiled in a county. RESULTS: The snowball process yielded 9,983 unique and traceable contacts. Urban and high-income counties yielded significantly more screened program administrators; urban counties produced significantly more eligible programs, but there was no significant association between the county characteristics and program response rate. There is a positive relationship between the number of informants initially located and the number of programs screened, eligible, and profiled in a county. DISCUSSION: Our strategy to identify youth tobacco cessation programs could be used to create a sample frame for other nonprofit organizations that are difficult to identify due to a lack of existing directories, lists, or other traditional sample frames.
BACKGROUND: Surveys of community-based programs are difficult to conduct when there is virtually no information about the number or locations of the programs of interest. This article describes the methodology used by the Helping Young Smokers Quit (HYSQ) initiative to identify and profile community-based youth smoking cessation programs in the absence of a defined sample frame. METHODS: We developed a two-stage sampling design, with counties as the first-stage probability sampling units. The second stage used snowball sampling to saturation, to identify individuals who administered youth smoking cessation programs across three economic sectors in each county. Multivariate analyses modeled the relationship between program screening, eligibility, and response rates and economic sector and stratification criteria. Cumulative logit models analyzed the relationship between the number of contacts in a county and the number of programs screened, eligible, or profiled in a county. RESULTS: The snowball process yielded 9,983 unique and traceable contacts. Urban and high-income counties yielded significantly more screened program administrators; urban counties produced significantly more eligible programs, but there was no significant association between the county characteristics and program response rate. There is a positive relationship between the number of informants initially located and the number of programs screened, eligible, and profiled in a county. DISCUSSION: Our strategy to identify youth tobacco cessation programs could be used to create a sample frame for other nonprofit organizations that are difficult to identify due to a lack of existing directories, lists, or other traditional sample frames.
Authors: Stephen Baker; Mohammad Ali; Jessica Fung Deerin; Muna Ahmed Eltayeb; Ligia Maria Cruz Espinoza; Nagla Gasmelseed; Justin Im; Ursula Panzner; Vera V Kalckreuth; Karen H Keddy; Gi Deok Pak; Jin Kyung Park; Se Eun Park; Arvinda Sooka; Amy Gassama Sow; Adama Tall; Stephen Luby; Christian G Meyer; Florian Marks Journal: Clin Infect Dis Date: 2019-10-30 Impact factor: 9.079