Evidence map›Paper›PMID 36894600›Full record

ArticleScientific reports2023

Changes in Internet use patterns among older adults in England from before to after the outbreak of the COVID-19 pandemic.

Claryn S J Kung, Andrew Steptoe

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  7. Changes in well-being among socially isolated older people during the COVID-19 pandemic: An outcome-wide analysis.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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

2 authors.

Claryn S J KungDepartment of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK. claryn.kung@ucl.ac.uk.
Andrew SteptoeDepartment of Behavioural Science and Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.ORCID 0000-0001-7808-4943

Funding

Project-001R01AG017644 · NIA · UNIVERSITY OF LONDON INST OF NEUROLOGY · PI Andrew Steptoe · 2000 to 2026
$56.2M
Department of HealthNIA NIH HHS R01 AG017644NIA NIH HHS R01AG017644
6 · The paper itself

Abstract

The COVID-19 pandemic brought about an increased reliance on the Internet for various daily activities. Given the known digital divide, it is important to understand whether older adults changed their Internet use patterns, but current evidence is limited to cross-sectional studies. This study documents changes in frequency and types of Internet use among older adults from before to shortly after the outbreak of the COVID-19 pandemic (2018/2019 to June/July 2020), and the factors predicting regular use during these early days of the pandemic. Using data on 6,840 adults aged 50 + from the nationally representative English Longitudinal Study of Ageing, we apply longitudinal fixed-effects models to examine within-individual changes in Internet use behaviour. There was no change in the likelihood of daily Internet use between 2018/2019 and June/July 2020, despite the increased digitalisation of services over the pandemic. Daily use in June/July 2020 was negatively related to age, neighbourhood deprivation, and loneliness, and positively related to partnership status, education, employment, income, and organisation membership. Using the Internet for making calls and getting information about Government services increased, which was important given the social restrictions and overall uncertainty. However, Internet use for finding health-related information decreased. As the world moves towards digital alternatives post-pandemic, it is important to continually ensure older adults are not at risk of exclusion.

Indexed as

COVID-19AgedCross-Sectional StudiesDisease OutbreaksHumansInternetInternet UseLongitudinal StudiesPandemics

Identifiers

PMID36894600
PMCPMC9995747

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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.