Evidence map›Paper›PMID 34769801›Full record

ArticleInternational journal of environmental research and public health2021

Age-Related Digital Divide during the COVID-19 Pandemic in China.

Yu Song, Chenfei Qian, Susan Pickard

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
34.5field-weighted citation impact, top 1% 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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 91 citations in OpenAlex.

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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

3 authors at 2 institutions in 2 countries.

Yu SongXIPU Institution, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China.
Chenfei QianDepartment of China Studies, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China.
Susan PickardDepartment of Sociology, Social Policy and Criminology, University of Liverpool, Liverpool L69 7ZA, UK.
Xi’an Jiaotong-Liverpool University · CNUniversity of Liverpool · GB

Funding

Xi'an Jiaotong-Liverpool University KSF-E-57
6 · The paper itself

Abstract

China has adopted a variety of digital technologies to effectively combat the unprecedented COVID-19 pandemic. The massive utilisation of digital technologies, however, to a great extent, magnifies the age-related digital divide. This paper aims to examine the impacts of the age-related digital divide on older adults in the context of the COVID-19 pandemic. Cases of three age-related digital divide scenarios, including older people taking public transportation, seeking medical care, as well as conducting digital transactions, are collected from Chinese official news outlets. The results indicate that the COVID-19 pandemic accelerates the pace of digital technology utilisation but exacerbates the age-related digital divide. Such an age-related digital divide has largely excluded older adults from both the real society and the virtual society. Older adults' personal attitudes and motivations, as well as education and income, governmental policies, and family and social supports, are all major contributors to the severe impacts of the age-related digital divide on old adults during the pandemic. More measures should be adopted to bridge the age-related digital divide and build a senior-friendly e-society.

Indexed as

COVID-19Digital DivideAgedChinaHumansPandemicsSARS-CoV-2COVID-19 pandemicdigital codedigital divideolder people

Identifiers

PMID34769801
PMCPMC8582816
OpenAlexW3208500312

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.