Evidence map›Paper›PMID 35013706›Full record

ArticleJournal of transport & health2022

Impact of COVID-19 on adolescent travel behavior.

Jianrong Liu, Qiongwen Cao, Mingyang Pei

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
4.1field-weighted citation impact, top 8% 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

3 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
  3. 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 2 institutions in 2 countries.

Jianrong LiuSchool of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China.
Qiongwen CaoSchool of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China.
Mingyang PeiDepartment of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg, SE-412 96, Sweden.
South China University of Technology · CNChalmers University of Technology · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe outbreak of COVID-19 has significantly impacted travel behavior. However, few studies have analyzed the impact of COVID-19 on adolescent travel behavior. This article analyzed the impact of COVID-19 on adolescent travel behavior using questionnaire survey data.

methodsThis paper first used confirmatory factor analysis (CFA) to explore the psychological factors related to the adolescents' perceptions about the severity of COVID-19. The study then established a logit model to study the effects of COVID-19 in different phases (before, during, and after the epidemic peak), demographic characteristics, and the role of psychological factors on their travel behavior.

resultsThe results show that the phase of COVID-19 did not significantly impact the adolescents' choice of short-distance travel. The frequency of outings per week, the number of exercise sessions per week, and willingness to travel by public transportation decreased significantly in the outbreak phase. Meanwhile, the perception of the severity of COVID-19 significantly impacted adolescent travel behavior.

conclusionThis research demonstrates that COVID-19 has led adolescents to reduce their frequency of outings, and they try not to use public transportation. Adolescents appear to be traveling more cautiously in the outbreak phase and the post-epidemic phase.

Indexed as

AdolescentsLogit modelPsychological factorsTravel behaviorUrban traffic

Identifiers

PMID35013706
PMCPMC8730543
OpenAlexW4206780516

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.