OBJECTIVE: The design and implementation of a nationally representative probability sample of persons with a low-prevalence disease, HIV/AIDS. DATA SOURCES/STUDY SETTING: One of the most significant roadblocks to the generalizability of primary data collected about persons with a low-prevalence disease is the lack of a complete methodology for efficiently generating and enrolling probability samples. The methodology developed by the HCSUS consortium uses a flexible, provider-based approach to multistage sampling that minimizes the quantity of data necessary for implementation. STUDY DESIGN: To produce a valid national probability sample, we combined a provider-based multistage design with the M.D.-colleague recruitment model often used in non-probability site-specific studies. DATA COLLECTION: Across the contiguous United States, reported AIDS cases for metropolitan areas and rural counties. In selected areas, caseloads for known providers for HIV patients and a random sample of other providers. For selected providers, anonymous patient visit records. PRINCIPAL FINDINGS: It was possible to obtain all data necessary to implement a multistage design for sampling individual HIV-infected persons under medical care with known probabilities. Taking account of both patient and provider nonresponse, we succeeded in obtaining in-person or proxy interviews from subjects representing over 70 percent of the eligible target population. CONCLUSIONS: It is possible to design and implement a national probability sample of persons with a low-prevalence disease, even if it is stigmatized.
OBJECTIVE: The design and implementation of a nationally representative probability sample of persons with a low-prevalence disease, HIV/AIDS. DATA SOURCES/STUDY SETTING: One of the most significant roadblocks to the generalizability of primary data collected about persons with a low-prevalence disease is the lack of a complete methodology for efficiently generating and enrolling probability samples. The methodology developed by the HCSUS consortium uses a flexible, provider-based approach to multistage sampling that minimizes the quantity of data necessary for implementation. STUDY DESIGN: To produce a valid national probability sample, we combined a provider-based multistage design with the M.D.-colleague recruitment model often used in non-probability site-specific studies. DATA COLLECTION: Across the contiguous United States, reported AIDS cases for metropolitan areas and rural counties. In selected areas, caseloads for known providers for HIVpatients and a random sample of other providers. For selected providers, anonymous patient visit records. PRINCIPAL FINDINGS: It was possible to obtain all data necessary to implement a multistage design for sampling individual HIV-infectedpersons under medical care with known probabilities. Taking account of both patient and provider nonresponse, we succeeded in obtaining in-person or proxy interviews from subjects representing over 70 percent of the eligible target population. CONCLUSIONS: It is possible to design and implement a national probability sample of persons with a low-prevalence disease, even if it is stigmatized.
Authors: M F Shapiro; M L Berk; S H Berry; C A Emmons; L A Athey; D C Hsia; A A Leibowitz; C A Maida; M Marcus; J F Perlman; C L Schur; M A Schuster; J W Senterfitt; S A Bozzette Journal: Health Serv Res Date: 1999-12 Impact factor: 3.402
Authors: D S Zingmond; N S Wenger; S Crystal; G F Joyce; H Liu; U Sambamoorthi; L A Lillard; A A Leibowitz; M F Shapiro; S A Bozzette Journal: Am J Public Health Date: 2001-07 Impact factor: 9.308
Authors: M F Shapiro; M L Berk; S H Berry; C A Emmons; L A Athey; D C Hsia; A A Leibowitz; C A Maida; M Marcus; J F Perlman; C L Schur; M A Schuster; J W Senterfitt; S A Bozzette Journal: Health Serv Res Date: 1999-12 Impact factor: 3.402
Authors: Mark A Schuster; Rebecca Collins; William E Cunningham; Sally C Morton; Sally Zierler; Myra Wong; Wenli Tu; David E Kanouse Journal: J Gen Intern Med Date: 2005-09 Impact factor: 5.128
Authors: Patrick S Sullivan; John M Karon; Faye E Malitz; Stephanie Broyles; Eve D Mokotoff; Susan E Buskin; Patricia L Fleming Journal: Public Health Rep Date: 2005 May-Jun Impact factor: 2.792
Authors: Stephanie L Taylor; M Audrey Burnam; Cathy Sherbourne; Ron Andersen; William E Cunningham Journal: J Behav Health Serv Res Date: 2004 Apr-Jun Impact factor: 1.505