| Autor: |
Clay-Warner J; Jody Clay-Warner and Tenshi Kawashima are with the Department of Sociology, University of Georgia, Athens. Timothy G. Edgemon is with the Department of Sociology, Anthropology, and Social Work, Auburn University, Auburn, AL., Kawashima T; Jody Clay-Warner and Tenshi Kawashima are with the Department of Sociology, University of Georgia, Athens. Timothy G. Edgemon is with the Department of Sociology, Anthropology, and Social Work, Auburn University, Auburn, AL., Edgemon TG; Jody Clay-Warner and Tenshi Kawashima are with the Department of Sociology, University of Georgia, Athens. Timothy G. Edgemon is with the Department of Sociology, Anthropology, and Social Work, Auburn University, Auburn, AL. |
| Abstrakt: |
The network scale-up method (NSUM) has shown promise in measuring the prevalence of hidden public health problems and at-risk populations. The technique involves asking survey respondents how many people they know with the health problem or characteristic of interest and extrapolating this information to the population level. An important component of the NSUM estimate is the size of each respondent's network, which is determined by asking respondents about the number of people they know who belong to populations of known size. There is little systematic discussion, however, to guide selection of these questions. Furthermore, many of the most commonly used known population questions are appropriate only in countries with a robust data infrastructure. Here, we draw from the NSUM literature to present a set of best practices in the selection of NSUM known population questions. Throughout, we address the unique situations that many researchers face in collecting prevalence data in the developing world, where innovative prevalence estimation techniques, such as NSUM, are most needed. ( Am J Public Health . 2022;112(5):747-753. https://doi.org/10.2105/AJPH.2022.306731). |
