The efficacy of respondent-driven sampling for the health assessment of minority populations |
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| Institution: | 1. University of Guam, College of Natural & Applied Sciences, 303 University Drive, Mangilao, Guam 96923, United States;2. University of Guam, Division of Communication and Fine Arts, 303 University Drive, Mangilao, Guam 96923, United States;3. University of Guam, Cancer Research Center, 303 University Drive, Mangilao, Guam 96923, United States;4. University of Hawaii at Manoa, Department of Communicology, 2560 Campus Road, George 329, Honolulu, HI 96822, United States;5. University of Hawaii Cancer Center, 701 Ilalo St., Honolulu, HI 96813, United States;1. Department of Family Medicine and Community Health, JABSOM – University of Hawaii at Manoa, 677 Ala Moana Blvd, Suite 815, Honolulu, HI 96813, United States;2. Yap State Department of Health Services, P.O. Box 1010, Colonia, Yap 96943, Federated States of Micronesia;1. Collaboration for Cancer Outcomes, Research and Evaluation, The Ingham Institute for Applied Medical Research, Liverpool Hospital, UNSW, Sydney, Australia;2. Applied Radiation Biology and Radiotherapy Section, Division of Human Health e Department of Nuclear Sciences and Applications, International Atomic Energy Agency, PO Box 100, 1400 Vienna, Austria;1. Service de Gynécologie-Obstétrique Centre Hospitalier Universitaire de Guadeloupe, Guadeloupe F.W.I. Route de Chauvel, 97159 Pointe-à-Pitre Cedex, France;2. Institut National de la Santé et de la Recherche Médicale Inserm U1085–IRSET, Campus Universitaire de Fouillole, Pointe à Pitre 97157, Guadeloupe, France;3. Service d’Anatomopathologie, Centre Hospitalier Universitaire de Guadeloupe, Guadeloupe F.W. I. Route de Chauvel, 97159 Pointe-à-Pitre Cedex, France;4. Registre Général des Cancers de Guadeloupe, Centre Hospitalier Universitaire de Guadeloupe, Guadeloupe F.W. I. Route de Chauvel, 97159 Pointe-à-Pitre Cedex, France;1. Department of Pediatrics, Chung-Ang University Hospital, Seoul, Republic of Korea;2. Department of Internal Medicine, Nasaret International Hospital, Incheon, Republic of Korea;3. Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea;4. College of Medicine, Chung-Ang University, Seoul, Republic of Korea;5. Department of Pediatrics, Asan Medical Center, Children’s Hospital, University of Ulsan College of Medicine, Seoul, Republic of Korea;1. Centre for Public Health Research, Massey University-Wellington Campus, PO Box 756, Wellington 6140, New Zealand;2. Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC 3010, Australia;3. National Advisor NCD, Head of National Wellness Centre, Ministry of Health & Medical Services, Fiji;4. John A. Burns School of Medicine, University of Hawaii, University of Hawaii Cancer Center,677 Ilalo Street, Honolulu, HI 96813, United States;1. Group of Evaluation of Health Determinants and Health Policies, Department of Basic Sciences, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Spain;2. Tobacco Control Unit, Cancer Prevention and Control Program, Institut Català d’Oncologia, L''Hospitalet de Llobregat, Barcelona, Spain;3. Cancer Prevention and Control Group, Institut d''Investigació Biomèdica de Bellvitge – IDIBELL, L''Hospitalet de Llobregat, Barcelona, Spain;4. Department of Clinical Sciences, School of Medicine, Universitat de Barcelona, Barcelona, Spain;5. Group of Integrative Pharmacology and Systems Neuroscience, Neurosciences Programme, IMIM (Hospital del Mar Medical Research Institute), Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain;6. Catalan Network of Smoke-free Hospitals, L’Hospitalet de Llobregat, Barcelona, Spain;7. Addictions Unit, Institute of Neurosciences, Hospital Clínic de Barcelona, Barcelona, Spain;8. Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain |
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| Abstract: | BackgroundRespondent driven sampling (RDS) is a relatively new network sampling technique typically employed for hard-to-reach populations. Like snowball sampling, initial respondents or “seeds” recruit additional respondents from their network of friends. Under certain assumptions, the method promises to produce a sample independent from the biases that may have been introduced by the non-random choice of “seeds.” We conducted a survey on health communication in Guam’s general population using the RDS method, the first survey that has utilized this methodology in Guam. It was conducted in hopes of identifying a cost-efficient non-probability sampling strategy that could generate reasonable population estimates for both minority and general populations.MethodsRDS data was collected in Guam in 2013 (n = 511) and population estimates were compared with 2012 BRFSS data (n = 2031) and the 2010 census data. The estimates were calculated using the unweighted RDS sample and the weighted sample using RDS inference methods and compared with known population characteristics.ResultsThe sample size was reached in 23 days, providing evidence that the RDS method is a viable, cost-effective data collection method, which can provide reasonable population estimates. However, the results also suggest that the RDS inference methods used to reduce bias, based on self-reported estimates of network sizes, may not always work. Caution is needed when interpreting RDS study findings.ConclusionsFor a more diverse sample, data collection should not be conducted in just one location. Fewer questions about network estimates should be asked, and more careful consideration should be given to the kind of incentives offered to participants. |
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| Keywords: | Respondent-driven sampling Health communication Guam Chamorro Federated States of Micronesia Micronesians Pacific Islanders |
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