Evidence map›Paper›PMID 30328063›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2019

"Starfish Sampling": a Novel, Hybrid Approach to Recruiting Hidden Populations.

H Fisher Raymond, Yea-Hung Chen, Willi McFarland

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
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  9. The Development and the Assessment of Sampling Methods for Hard-to-Reach Populations in HIV Surveillance.Journal of urban health : bulletin of the New York Academy of Medicine · 2024
    Review
  10. Article
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  19. Improving Underestimation of HIV Prevalence in Surveys Using Time-Location Sampling.Journal of urban health : bulletin of the New York Academy of Medicine · 2021
    Article
  20. 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.

H Fisher RaymondSchool of Public Health, Rutgers University, Piscataway, NJ, USA.
Yea-Hung ChenUniversity of California, San Francisco, CA, USA.
Willi McFarlandUniversity of California, San Francisco, CA, USA. willi.mcfarland@sfdph.org.

Funding

Probability-based survey of HIV risk among transmen using a novel sampling methodR21HD071765 · NICHD · SAN FRANCISCO DEPARTMENT OF PUBLIC HEALTH · PI MCFARLAND, WILLIAM · 2013 to 2014
$303k
NICHD NIH HHS R21 HD071765
6 · The paper itself

Abstract

We sought to leverage the strengths of time location sampling (TLS) and respondent-driven sampling (RDS) for surveys of hidden populations by combing elements of both methods in a new approach we call "starfish sampling." Starfish sampling entails random selection of venue-day-time units from a mapping of the locations where the population can be found, combined with short chains of peer referrals from their social networks at the venue or presenting to the study site later. Using the population of transmen in San Francisco as a case example, we recruited 122 eligible participants using starfish sampling: 79 at randomly selected venues, 11 on dating applications, and 32 by referral. Starfish sampling produced one of the largest community-recruited samples specifically for transmen to date. Starfish sampling is a flexibility method to recruit and sample hidden populations for whom conventional TLS and RDS may not work in theory or practice.

Indexed as

Patient SelectionAdolescentAdultAgedAged, 80 and overAnimalsBiomedical ResearchFemaleHIV InfectionsHumansMaleMiddle AgedPeer GroupPopulation SurveillanceResearch DesignSampling StudiesHidden populationsRespondent-driven samplingSampling methodsTime-location sampling

Identifiers

PMID30328063
PMCPMC6391284

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.