Evidence map›Paper›PMID 34754196›Full record

ArticleJournal of multidisciplinary healthcare2021

A Scoping Review of Telenursing's Potential as a Nursing Care Delivery Model in Lung Cancer During the COVID-19 Pandemic.

Maria Komariah, Sidik Maulana, Hesti Platini, Tuti Pahria

Open access · goldAbstract readScoping Review
In one paragraph

Article in Journal of multidisciplinary healthcare, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 3 pooled it
2.1field-weighted citation impact, top 10% of its field
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

14 citing papers in PubMed, 3 syntheses or guidelines pooled it, 30 citations in OpenAlex.

  1. Pooled it
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  9. Telenursing and artificial intelligence for oncology nursing.Asia-Pacific journal of oncology nursing · 2022
    Article
  10. Review
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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 at 1 institution in 1 country.

Maria KomariahDepartment of Fundamental Nursing, Faculty of Nursing, Universitas Padjadjaran, Bandung, Indonesia.ORCID 0000-0003-1648-4882
Sidik MaulanaFaculty of Nursing, Universitas Padjadjaran, Bandung, Indonesia.ORCID 0000-0003-4520-1650
Hesti PlatiniDepartment of Medical-Surgical Nursing, Faculty of Nursing, Universitas Padjadjaran, Bandung, Indonesia.
Tuti PahriaDepartment of Medical-Surgical Nursing, Faculty of Nursing, Universitas Padjadjaran, Bandung, Indonesia.
Padjadjaran University · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review aims to investigate the potential of telenursing as a nursing care delivery model for lung cancer throughout the COVID-19 pandemic using a scoping review. The Preferred Reporting Item for Systematic Reviews and Meta-analysis for Scoping Review (PRISMA-ScR) were used in this study. The topic was thoroughly researched in PubMed, CINAHL, and Science Direct. Based on the initial search, there were eight relevant studies out of 432. Websites, phone calls, and lifestream were among the telenursing models discovered in the care of lung cancer patients. The delivery care provided includes monitoring vital signs, symptoms, chemotherapy toxicity, support care, education, and postoperative rehabilitation. Telenursing is considered appropriate for lung cancer patients because it has been shown to help with symptom management, functional status, quality of life, and diminishing the demand for care support. Therefore, telenursing can be used to deliver care for lung cancer throughout the COVID-19 pandemic.

Indexed as

COVID-19lung cancernursing delivery caretelenursing

Identifiers

PMID34754196
PMCPMC8572116
OpenAlexW3208292717

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.