Evidence map›Paper›PMID 34442159›Full record

ArticleHealthcare (Basel, Switzerland)2021

Characteristics of COVID-19-Related Free Telephone Consultations by Public Health Nurses in Japan: A Retrospective Study.

Yuka Sumikawa, Chikako Honda, Kyoko Yoshioka-Maeda, Noriko Yamamoto-Mitani

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

4 authors.

Yuka SumikawaDepartment of Community Health Nursing, Division of Health Sciences and Nursing, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.ORCID 0000-0003-3852-251X
Chikako HondaDepartment of Community Health Nursing, Division of Health Sciences and Nursing, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
Kyoko Yoshioka-MaedaDepartment of Health Promotion, National Institute of Public Health, Saitama 351-0197, Japan.ORCID 0000-0003-0344-0143
Noriko Yamamoto-MitaniDepartment of Community Health Nursing, Division of Health Sciences and Nursing, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.

Funding

The Daiwa Securities Health Foundation No Number
6 · The paper itself

Abstract

This study aimed to (1) describe the characteristics of community residents who used coronavirus disease 2019 (COVID-19)-related telephone consultation systems by public health nurses (PHNs) and (2) analyze the concerns they had during the first wave of COVID-19 in Japan. Among 1126 telephone consultations, PHNs recorded telephone consultations between 25 March, and 30 April, 2020, in City A, Japan. We analyzed 1017 consultations involving 799 (79%) community residents (resident group) and 218 (21%) organizational representatives (organization group) located in City A. Half of the consultations were made during midmorning, and most of the consultations were regarding COVID-19 symptoms. Among the resident group, visiting a primary care doctor was the most common recommendation by the PHNs; there was no difference in provision of consultation by sex. Health- and welfare-related organizations mainly consulted PHNs about "having COVID-19-related symptoms" and "undergoing PCR testing," and PHNs' recommended them to visit a primary care doctor and coordinate PCR testing. The results suggest that public health centers should provide more helpful information on COVID-19 that accurately reflects the concerns of the population.

Indexed as

communityCOVID-19public health nursetelephone consultation

Identifiers

PMID34442159
PMCPMC8391788

What OpenQuestion holds

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LicenceCC BY
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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.