Evidence map›Paper›PMID 36864419›Full record

ArticleBMC public health2023

A text-mining study on emotional cognition, understanding, and preventative behaviors during the COVID-19 pandemic.

Eunjung Lim, Jieun Shin, Seyeon Park

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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 3 institutions in 1 country.

Eunjung Lim *Department of Nursing, Daejeon Institute of Science and Technology, Daejeon, South Korea.
Jieun Shin *Department of Biomedical Informatics, College of Medicine, Konyang University, Nonsan, South Korea.
Seyeon ParkDepartment of Nursing, College of Nursing, Chungnam National University Hospital, Daejeon, South Korea. park_sy@cnu.ac.kr.
Chungnam National University Hospital · KRDaejeon Institute of Science and Technology · KRKonyang University · KR

Funding

Chungnam National University 2021-0554-0
6 · The paper itself

Abstract

backgroundThis study aimed to look at emotions perceived about the attributes, prevention, diagnosis, and treatment of infectious diseases related to coronavirus disease (COVID-19) that were widespread across the world and identify their relevance to knowledge about infectious diseases and preventative behaviors.

methodsTexts to measure emotional cognition were selected through a pre-test, and 282 people were chosen as participants based on the survey conducted for 20 days from August 19 to August 29, 2020, created with Google Forms. IBM SPSS Statistics 25.0 was used for the primary analysis, and the SNA package in R (version 4.0.2) was utilized to conduct the network analysis.

resultsIt was found that universal negative emotions such as feeling "anxious" (65.5%), "afraid" (46.1%), and "scared" (32.7%) commonly appeared among most people. Also, they were found to be feeling both positive ("caring" [42.3%] and "strict" [28.2%]) and negative ("frustrating" [39.1%] and "isolated" [31.0%]) emotions about efforts to prevent and curb the spread of COVID-19. In terms of emotional cognition for the diagnosis and treatment of such diseases, "reliable" (43.3%) took the biggest ratio among the replies. The level of understanding about infectious diseases showed differences in emotional cognition, thereby affecting people's emotions. However, no differences were found in the practice of preventative behaviors.

conclusionsEmotions associated with cognition in the context of pandemic infectious diseases have been found to be mixed. Furthermore, it can be seen that feelings vary depending on the degree of understanding of the infectious disease.

Indexed as

COVID-19PandemicsCognitionData MiningEmotionsHumansCovid 19Emotional cognitionPreventative behavioursText-mining

Identifiers

PMID36864419
PMCPMC9981253
OpenAlexW4322762431

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.