Evidence map›Paper›PMID 36360715›Full record

ArticleInternational journal of environmental research and public health2022

How Has COVID-19 Impacted Our Language Use?

Francesca Pisano, Alessio Manfredini, Daniela Brachi, Luana Landi, Lucia Sorrentino, Marianna Bottone, Chiara Incoccia, Paola Marangolo

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

8 authors.

Francesca PisanoDepartment of Humanities Studies, University Federico II, 80133 Naples, Italy.ORCID 0000-0001-5814-0151
Alessio ManfrediniDepartment of Humanities Studies, University Federico II, 80133 Naples, Italy.ORCID 0000-0002-4350-5362
Daniela BrachiDepartment of Humanities Studies, University Federico II, 80133 Naples, Italy.
Luana LandiDepartment of Humanities Studies, University Federico II, 80133 Naples, Italy.
Lucia SorrentinoDepartment of Humanities Studies, University Federico II, 80133 Naples, Italy.
Marianna BottoneDepartment of Humanities Studies, University Federico II, 80133 Naples, Italy.
Chiara IncocciaIRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Paola MarangoloDepartment of Humanities Studies, University Federico II, 80133 Naples, Italy.ORCID 0000-0002-1516-9832

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has led to severe consequences for people's mental health. The pandemic has also influenced our language use, shaping our word formation habits. The overuse of new metaphorical meanings has received particular attention from the media. Here, we wanted to investigate whether these metaphors have led to the formation of new semantic associations in memory. A sample of 120 university students was asked to decide whether a target word was or was not related to a prime stimulus. Responses for pandemic pairs in which the target referred to the newly acquired metaphorical meaning of the prime (i.e., "trench"-"hospital") were compared to pre-existing semantically related pairs (i.e., "trench"-"soldier") and neutral pairs (i.e., "trench"-"response"). Results revealed greater accuracy and faster response times for pandemic pairs than for semantic pairs and for semantic pairs compared to neutral ones. These findings suggest that the newly learned pandemic associations have created stronger semantic links in our memory compared to the pre-existing ones. Thus, this work confirms the adaptive nature of human language, and it underlines how the overuse of metaphors evoking dramatic images has been, in part, responsible for many psychological disorders still reported among people nowadays.

Indexed as

COVID-19LanguageHumansPandemicsReaction TimeSemanticsCOVID-19 emergencymetaphorsmisinformationpsychological disorderspublic healthsemantic primingsocial communicationsocial media

Identifiers

PMID36360715
PMCPMC9656816

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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.