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Cited by 1,257

The DOI matches its Crossref record.

Research Article: Recruitment of hard-to-reach population subgroups via adaptations of the snowball sampling strategy: Hard-to-reach populations

Open access
Sadler, Georgia Robins, Lee, Hau-Chen, Lim, Rod Seung-Hwan, Fullerton, Judith·2010·Nursing & Health Sciences
DOI 10.1111/j.1442-2018.2010.00541.x
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Abstract

Nurse researchers and educators often engage in outreach to narrowly defined populations. This article offers examples of how variations on the snowball sampling recruitment strategy can be applied in the creation of culturally appropriate, community-based information dissemination efforts related to recruitment to health education programs and research studies. Examples from the primary author's program of research are provided to demonstrate how adaptations of snowball sampling can be used effectively in the recruitment of members of traditionally underserved or vulnerable populations. The adaptation of snowball sampling techniques, as described in this article, helped the authors to gain access to each of the more-vulnerable population groups of interest. The use of culturally sensitive recruitment strategies is both appropriate and effective in enlisting the involvement of members of vulnerable populations. Adaptations of snowball sampling strategies should be considered when recruiting participants for education programs or for research studies when the recruitment of a population-based sample is not essential.

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Metadata

Authors
Sadler, G. R., Lee, H.-C., Lim, R. S.-H., & Fullerton, J.
Venue
Nursing & Health Sciences
Publisher
Wiley
Published
2010-08-03
Volume
12
Issue
3
Pages
369-374
ISSN
1441-0745 (ISSN-L)
DOI
10.1111/j.1442-2018.2010.00541.x
OpenAlex
W1934945143
Cited by
1,257
References
0
FWCI
13.42
Type
journal article
Language
en
Open access
green

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.