Evidence map›Paper›PMID 37167208›Full record

ArticlePloS one2023

Predicting resilience during the COVID-19 Pandemic in the United Kingdom: Cross-sectional and longitudinal results.

Kate M Bennett, Anna Panzeri, Elfriede Derrer-Merk, Sarah Butter, Todd K Hartman, Liam Mason, Orla McBride, Jamie Murphy, Mark Shevlin, Jilly Gibson-Miller and 9 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.7field-weighted citation impact, top 5% 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

13 citing papers in PubMed, 15 citations in OpenAlex.

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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

19 authors at 8 institutions in 2 countries.

Kate M BennettDepartment of Psychology, University of Liverpool, Liverpool, United Kingdom.ORCID 0000-0003-3164-6894
Anna PanzeriDepartment of General Psychology, University of Padova, Padova, Italy.ORCID 0000-0001-5999-858X
Elfriede Derrer-MerkDepartment of Psychology, University of Liverpool, Liverpool, United Kingdom.
Sarah ButterSchool of Psychology, Ulster University, Coleraine, United Kingdom.
Todd K HartmanDepartment of Social Statistics, University of Manchester, Manchester, United Kingdom.
Liam MasonDivision of Psychology and Language Sciences, University College London, London, United Kingdom.
Orla McBrideSchool of Psychology, Ulster University, Coleraine, United Kingdom.
Jamie MurphySchool of Psychology, Ulster University, Coleraine, United Kingdom.
Mark ShevlinSchool of Psychology, Ulster University, Coleraine, United Kingdom.
Jilly Gibson-MillerDepartment of Psychology, University of Sheffield, Sheffield, United Kingdom.
Liat LevitaSchool of Psychology, University of Sussex, Brighton, United Kingdom.
Anton P MartinezDepartment of Psychology, University of Sheffield, Sheffield, United Kingdom.
Ryan McKayDepartment of Psychology, Royal Holloway, University of London, London, United Kingdom.
Alex LloydDivision of Psychology and Language Sciences, University College London, London, United Kingdom.
Thomas V A StocksDepartment of Psychology, University of Sheffield, Sheffield, United Kingdom.
Gioa BottesiDepartment of General Psychology, University of Padova, Padova, Italy.ORCID 0000-0002-8411-8887
Giulo VidottoDepartment of General Psychology, University of Padova, Padova, Italy.
Richard P BentallDepartment of Psychology, University of Sheffield, Sheffield, United Kingdom.
Marco BertaminiDepartment of General Psychology, University of Padova, Padova, Italy.ORCID 0000-0001-8617-6864
University of Padua · ITUniversity of Sheffield · GBUniversity of Ulster · GBUniversity College London · GBUniversity of Liverpool · GBRoyal Holloway University of London · GBUniversity of Manchester · GBUniversity of Sussex · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the COVID-19 pandemic has impacted the psychological wellbeing of some people, there is evidence that many have been much less affected. The Ecological Model of Resilience (EMR) may explain why some individuals are not resilient whilst others are. In this study we test the EMR in a comparison of UK survey data collected from the COVID-19 Psychological Research Consortium (C19PRC) longitudinal study of a representative sample of the United Kingdom (UK) adult population and data from an Italian arm of the study. We first compare data from the third wave of the UK arm of the study, collected in July/August 2020, with data from an equivalent sample and stage of the pandemic in Italy in July 2020. Next, using UK longitudinal data collected from C19PRC Waves 1, 3 and 5, collected between March 2020 and April 2021 we identify the proportion of people who were resilient. Finally, we examine which factors, drawn from the EMR, predict resilient and non-resilient outcomes. We find that the 72% of the UK sample was resilient, in line with the Italian study. In the cross-sectional logistic regression model, age and self-esteem were significantly associated with resilience whilst death anxiety thoughts, neuroticism, loneliness, and Post Traumatic Stress Disorder (PTSD) symptoms related to COVID-19 were significantly associated with Non-Resilient outcomes. In the longitudinal UK analysis, at Wave 5, 80% of the sample was Resilient. Service use, belonging to wider neighbourhood, self-rated health, self-esteem, openness, and externally generated death anxiety were associated with Resilient outcomes. In contrast, PTSD symptoms and loneliness were associated with Non-Resilient outcomes. The EMR effectively explained the results. There were some variables which are amenable to intervention which could increase resilience in the face of similar future challenges.

Indexed as

COVID-19AdultCross-Sectional StudiesHumansLongitudinal StudiesPandemicsUnited Kingdom

Identifiers

PMID37167208
PMCPMC10174573
OpenAlexW4376225589

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.