ArticleAmerican journal of public health2022
Measure of Personal Network Size Using the Known Population Method: A Methodological Guide.
Article in American journal of public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Social Networks and Their Influence on the Choice of Unassisted Smoking Cessation: Cross-Sectional Study in Six Cities in China.JMIR public health and surveillance · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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. (
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