Evidence map›Paper›PMID 40262177›Full record

ArticleJournal of public health management and practice : JPHMP

Creating a Probability Survey Panel for Population Health Research: The Experience of the NYC Health Panel.

Leigh Reardon, Sharon E Perlman, Sarah E Dumas, Tashema Bholanath, Pui Ying Chan, Aldo Crossa, Shabitri Dasgupta, L Hannah Gould, Nafesa Kanneh, Maria Lejano and 7 more

Abstract read
In one paragraph

Article in Journal of public health management and practice : JPHMP. 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

17 authors.

Leigh ReardonAuthor Affiliations: Center for Population Health Data Science, NYC Department of Health and Mental Hygiene, NY, New York.
Sharon E Perlman
Sarah E Dumas
Tashema Bholanath
Pui Ying Chan
Aldo Crossa
Shabitri Dasgupta
L Hannah Gould
Nafesa Kanneh
Maria Lejano
Amber Levanon Seligson
Sungwoo Lim
Nika Norvila
Kacie Seil
Tanzia Shaheen
Adrienne Solomon
R Charon Gwynn

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextSurvey panels can allow for more efficient data collection than traditional surveillance surveys both in terms of cost and operations. Seeking an alternative way to collect timely, high-quality data, the New York City (NYC) Health Department created a probability-based survey panel. PROGRAM: The NYC Health Panel was launched in April 2020. Over its first 2 years, the Panel recruited adults (ages 18+) in NYC from address-based lists and probabilistic surveys. IMPLEMENTATION: Once enrolled, panelists were invited to participate in up to 10 surveys per year. Surveys could be completed online (self-administered) or via paper or phone (computer assisted telephone interview) and were offered in 5 languages. Panelists were reconsented at the start of each survey and offered an incentive at completion. Panelists were compared to the 2017-2021 5-year American Community Survey data of NYC adults to assess representativeness. Weighting was used to adjust for these differences. EVALUATION: The NYC Health Department was able to successfully launch the Panel and collect survey data. In its first 2 years, the Panel enrolled approximately 13 000 adult NYC residents and conducted 18 surveys. Most surveys were completed online and in English. The Panel's size and probabilistic design allow for the creation of individual survey samples that are representative of adult NYC residents. DISCUSSION: The NYC Health Panel is an invaluable resource in response to the COVID-19 pandemic, in assessing racial inequities, and in measuring the secondary pandemics of food insecurity, delayed primary care, and adverse mental health. It serves as a unique example of how health departments that have the necessary in-house staff resources can collect timely data.

Indexed as

Population HealthAdolescentAdultAgedCOVID-19FemaleHumansMaleMiddle AgedNew York CitySurveys and Questionnairesepidemiologypopulation healthsurvey methodologysurvey panelsurveys

Identifiers

PMID40262177
PMCPMC12527779

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.