Related Experiment Video
Updated: Jun 16, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
Finding needles in a haystack: a methodology for identifying and sampling community-based youth smoking cessation
Sherry Emery1, Jungwha Lee, Susan J Curry
1Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, IL 60608, USA.
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.
More Related Videos
06:39Electroencephalographic, Heart Rate, and Galvanic Skin Response Assessment for an Advertising Perception Study: Application to Antismoking Public Service Announcements
Published on: August 28, 2017
05:52Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Naïve Adolescents at High Risk for Psychosis
Published on: November 21, 2013
Related Concept Videos
Community Based Intervention
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
Cluster Sampling Method
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Convenience Sampling Method
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Sampling Plans
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Statistical Methods for Analyzing Epidemiological Data
Systematic Sampling Method
Systematic sampling is one of the simplest methods...