Evidence map›Paper›PMID 34743039›Full record

ArticleGeriatric nursing (New York, N.Y.)

Working experience of certified nursing assistants in the greater New York City area during the COVID-19 pandemic: Results from a survey Study.

Sarah Ecker, Sanjay Pinto, Madeline Sterling, Faith Wiggins, Chenjuan Ma

Abstract read
In one paragraph

Article in Geriatric nursing (New York, N.Y.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  5. Article
  6. Forgotten Front Line: Understanding the Needs of Unionized Home Health Aides in Downstate New York During the COVID-19 Pandemic.New solutions : a journal of environmental and occupational health policy : NS · 2022
    Article
  7. Article
  8. 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

5 authors.

Sarah EckerNYU Langone Health, 550 First Avenue, New York, New York 10016, USA.
Sanjay PintoThe Worker Institute, Cornell University ILR School, Ithaca, NY 14853, USA; 1199SEIU Training and Employment Funds, New York 10018, USA.
Madeline SterlingDivision of General Internal Medicine, Weill Cornell Medicine, New York, NY 10065, USA.
Faith Wiggins1199SEIU Training and Employment Funds, New York 10018, USA.
Chenjuan MaNew York University Rory Meyers College of Nursing, New York, New York 10010, USA. Electronic address: cm4215@nyu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to examine the challenges and needs of certified nursing assistants (CNAs) working in nursing homes during the COVID-19 pandemic in the greater New York City area. Between September and November of 2020, a telephone survey was administered to and completed by 208 CNAs in the study area about various aspects of their working experience during COVID-19. CNAs reported significant exposure to COVID-19 and experienced additional emotional and financial strain due to the pandemic. CNAs also expressed the influence of COVID-19 on their work schedules and intent to continue working as CNAs, and strong interest in financial support and further training. This study offers empirical insights into the experiences of CNAs working in nursing homes during the pandemic, which are of unique value to inform future efforts to support CNAs and other long-term care providers in general and during public health emergencies in New York and beyond.

Indexed as

COVID-19Nursing AssistantsHumansNew York CityPandemicsSARS-CoV-2Certified nursing assistantsCOVID-19Long-term careNursing homesWorking experiences

Identifiers

PMID34743039
PMCPMC8519779

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.