Evidence map›Paper›PMID 35442995›Full record

ArticlePloS one2022

Satisfaction with the walking-related environment during COVID-19 in South Korea.

Hoon Jo, Ho Hee Lee, Dong-Hyun Kim, In Deok Kong

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Hoon JoArtificial Intelligence Big Data Medical Center, Yonsei University Wonju College of Medicine, Wonju, South Korea.ORCID 0000-0003-3762-1540
Ho Hee LeeDepartment of Preventive Medicine, Yonsei University Wonju College of Medicine, Wonju, South Korea.ORCID 0000-0003-3943-890X
Dong-Hyun KimDepartment of Social and Preventive Medicine, Hallym University College of Medicine; ChunCheon, South Korea.
In Deok KongDepartment of Physiology, Yonsei University Wonju College of Medicine, Wonju, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to examine the satisfaction level differences between urban and rural areas with regard to their walking environment during the COVID-19 pandemic in South Korea. This online cross-sectional research was conducted using a mobile health application. Overall, 1,032 local residents who participated in the mobile healthcare program of a public health center were classified as being from either urban (n = 481, 46.6%) or rural areas (n = 551, 53.4%) for the purpose of this study. The Walkability Checklist, which includes sociodemographic information, was employed using a Chi-square test and a multivariate logistic regression to investigate whether or not the participants were satisfied with the environmental factors associated with walking. It was found that both urban and rural areas were more likely to be unsatisfied with walking comfort (adjusted OR: 24.472, 95% CI: 14.937-40.096). Regarding the walking comfort aspects of the walking environment, urban residents chose poor landscape ("needed more grass, flowers, or trees"; aOR: 13.561, 95% CI: 3.619-50.823) as their primary dissatisfaction, and rural residents chose messy streets ("dirty, lots of litter or trash"; aOR: 29.045, 95% CI: 6.202-136.015). Compared with urban residents, rural residents were more discontented with the walking environment. Thus, to promote walking activities at the community level, it is necessary to focus on walking comfort, and implement efforts related to environmental beautification.

Indexed as

COVID-19Cross-Sectional StudiesHumansPandemicsPersonal SatisfactionRepublic of KoreaResidence CharacteristicsRural PopulationUrban PopulationWalking

Identifiers

PMID35442995
PMCPMC9020742

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.