Evidence map›Paper›PMID 39285149›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2024

Barriers and Facilitators to Trust in the COVID-19 New York City Test and Trace Program.

Michelle M Chau, Rita Larson, Margaret M Paul, Rachel E Massar, Lorraine Kwok, Carolyn A Berry, Lorna E Thorpe, Stefanie Bendik, Anna Bershteyn, Nadia S Islam

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Michelle M ChauDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA. Michelle.Chau@nyulangone.org.ORCID http://orcid.org/0000-0002-0554-0757
Rita LarsonDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.
Margaret M PaulKern Center for the Science of Health Care Delivery, Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ, 85054, USA.ORCID http://orcid.org/0000-0003-3281-6234
Rachel E MassarDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.ORCID http://orcid.org/0000-0001-5754-3231
Lorraine KwokDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.ORCID http://orcid.org/0000-0002-2626-0324
Carolyn A BerryDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.ORCID http://orcid.org/0000-0003-3671-3080
Lorna E ThorpeDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.ORCID http://orcid.org/0000-0001-7515-0562
Stefanie BendikDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.
Anna BershteynDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.ORCID http://orcid.org/0000-0002-6604-7093
Nadia S IslamDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.

Funding

NYC H+H NYC Health + Hospitals 1007645
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

COVID-19SARS-CoV-2TrustAdultCOVID-19 TestingFemaleHumansMaleMiddle AgedNew York CityCOVID-19Pandemic preparednessTrust

Identifiers

PMID39285149
PMCPMC11461413

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.