Evidence map›Paper›PMID 35298281›Full record

ArticleAmerican journal of public health2022

Measure of Personal Network Size Using the Known Population Method: A Methodological Guide.

Jody Clay-Warner, Tenshi Kawashima, Timothy G Edgemon

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jody Clay-WarnerJody 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.
Tenshi KawashimaJody 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.
Timothy G EdgemonJody 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.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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. (

Indexed as

Public HealthHumansRisk FactorsSurveys and Questionnaires

Identifiers

PMID35298281
PMCPMC9010921

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.