Evidence map›Paper›PMID 36628334›Full record

ArticleSocial networks2023

Leadership and contagion by COVID-19 among residence hall students: A social network analysis approach.

Pilar Marqués-Sánchez, María Cristina Martínez-Fernández, Raquel Leirós-Rodríguez, Óscar Rodríguez-Nogueira, Elena Fernández-Martínez, José Alberto Benítez-Andrades

Abstract read
In one paragraph

Article in Social networks, 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
–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

2 citing papers in PubMed.

  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

6 authors.

Pilar Marqués-SánchezSALBIS Research Group, Faculty of Health Sciences, University of León, Campus of Ponferrada, 24401 Ponferrada, Spain.
María Cristina Martínez-FernándezSALBIS Research Group, Faculty of Health Sciences, University of León, Campus of Ponferrada, 24401 Ponferrada, Spain.
Raquel Leirós-RodríguezSALBIS Research Group, Faculty of Health Sciences, University of León, Campus of Ponferrada, 24401 Ponferrada, Spain.
Óscar Rodríguez-NogueiraSALBIS Research Group, Faculty of Health Sciences, University of León, Campus of Ponferrada, 24401 Ponferrada, Spain.
Elena Fernández-MartínezSALBIS Research Group, Faculty of Health Sciences, University of León, Campus of Vegazana s/n, 24071 León, Spain.
José Alberto Benítez-AndradesSALBIS Research Group, Department of Electric, Systems and Automatics Engineering, Universidad de León, Campus of Vegazana s/n, 24071 León, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

University students have changed their behaviour due to the COVID-19 pandemic. In this paper, we describe the characteristics of PCR+ and PCR- nodes, analyse the structure, and relate the structure of student leaders to pandemic contagion as determined by PCR+ in 93 residential university students. Leadership comes from the male students of social science degrees who have PCR +, with an eigenvector centrality structure, β-centrality, and who are part of the bow-tie structure. There was a significant difference in β-centrality between leaders and non-leaders and in β-centrality between PCR+ and non-leaders. Leading nodes were part of the bow-tie structure. MR-QAP results show how residence and scientific branch were the most important factors in network formation. Therefore, university leaders should consider influential leaders, as they are vectors for disseminating both positive and negative outcomes.

Indexed as

COVID-19LeadershipPandemic contagionResidence HallSocial Network AnalysisUniversity students

Identifiers

PMID36628334
PMCPMC9816079

What OpenQuestion holds

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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.