Evidence map›Paper›PMID 36341177›Full record

ArticleJournal of transport & health2022

Insight into the nonlinear effect of COVID-19 on well-being in China: Commuting, a vital ingredient.

Yinan Dong, Yilin Sun, E Owen D Waygood, Bobin Wang, Pei Huang, Hamed Naseri

Open access · greenAbstract read
In one paragraph

Article in Journal of transport & health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

1 citing paper in PubMed, 14 citations in OpenAlex.

  1. Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters.International journal of environmental research and public health · 2022
    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

6 authors at 3 institutions in 2 countries.

Yinan DongCollege of Civil Engineering and Architecture, Center for Balanced Architecture, Zhejiang University, 866 Yuhangtang Road, 310058, Hangzhou, China.
Yilin SunCollege of Civil Engineering and Architecture, Center for Balanced Architecture, Zhejiang University, 866 Yuhangtang Road, 310058, Hangzhou, China.
E Owen D WaygoodDepartment of Civil, Geological, and Mining Engineering, Polytechnique Montréal, 2500, Chemin, de Polytechnique Montréal, Canada.
Bobin WangDepartment of Mechanical Engineering, Université Laval, QC, G1V 0A6, Quebec, Canada.
Pei HuangCollege of Civil Engineering and Architecture, Center for Balanced Architecture, Zhejiang University, 866 Yuhangtang Road, 310058, Hangzhou, China.
Hamed NaseriDepartment of Civil, Geological, and Mining Engineering, Polytechnique Montréal, 2500, Chemin, de Polytechnique Montréal, Canada.
Zhejiang University · CNPolytechnique Montréal · CAUniversité Laval · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: COVID-19 had a devastating impact on people's work, travel, and well-being worldwide. As one of the first countries to be affected by the virus and develop relatively well-executed pandemic control, China has witnessed a significant shift in people's well-being and habits, related to both commuting and social interaction. In this context, what factors and the extent to which they contribute to well-being are worth exploring. Methods: Through a questionnaire survey within mainland China, 688 valid sheets were collected, capturing various aspects of individuals' life, including travel, and social status. Focusing on commuting and other factors, a Gradient Boosting Decision Tree (GBDT) model was developed based on 300 sheets reporting working trips, to analyze the effects on well-being. Two indicators, i.e., the Relative Importance (RI) and Partial Dependency Plot (PDP), were used to quantify and visualize the effects of the explanatory factors and the synergy among them. Results: Commuting characteristics are the most critical ingredients, followed by social interactions to explain subjective well-being. Commuting stress poses the most substantial effect. Less stressful commuting trips can solidly improve overall well-being. Better life satisfaction is linked with shorter confinement periods and increased restriction levels. Meanwhile, the switch from in-person to online social interactions had less impact on young people's life satisfaction. Older people were unsatisfied with this change, which had a significant negative impact on their life satisfaction. Conclusions: From the synergy of commuting stress and commuting time on well-being, the effect of commuting time on well-being is mediated by commuting stress in the case of China. Even if one is satisfied with online communication, the extent of enhancement on well-being is minimal, for it still cannot replace face-to-face interaction. The findings can be beneficial in improving the overall well-being of society during the pandemic and after the virus has been eradicated.

Indexed as

Commuting behaviorCOVID-19Machine learningSocial interactionWell-being

Identifiers

PMID36341177
PMCPMC9618422
OpenAlexW4307899078

What OpenQuestion holds

Textmetadata
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.