Evidence map›Paper›PMID 35496728›Full record

ArticleDiscover social science and health2022

An analysis of changes in wellbeing during the COVID-19 pandemic in the UK.

Jen Murphy, Mark Elliot

Abstract read
In one paragraph

Article in Discover social science and 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
–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

1 citing paper in PubMed.

  1. 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

2 authors.

Jen MurphySchool of Social Sciences, University of Manchester, Oxford Road, Manchester, M21 9DN Greater Manchester UK.
Mark ElliotSchool of Social Sciences, University of Manchester, Oxford Road, Manchester, M21 9DN Greater Manchester UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: We investigated the trajectory of wellbeing over the course of the first wave and sought to determine whether the change in wellbeing is distributed equally across the population. Specifically we investigated pre-existing medical conditions, social isolation, financial stress and deprivation as a predictor for wellbeing and whether there were community level characteristics which protect against poorer wellbeing. Methods: Using online survey responses from the COVID-19 modules of Understanding society, we linked 8379 English cases across five waves of data collection to location based deprivation statistics. We used ordinary least squares regression to estimate the association between deprivation, pre-existing conditions and socio-demographic factors and the change in well-being scores over time, as measured by the GHQ-12 questionnaire. Results: A decline in wellbeing was observed at the beginning of the first lock down period at the beginning of March 2020. This was matched with a corresponding recovery between April and July as restrictions were gradually lifted. There was no association between the decline and deprivation, nor between deprivation and recovery. The strongest predictor of wellbeing during the lock down, was the baseline score, with the counterintuitive finding that for those will pre-existing poor wellbeing, the impact of pandemic restrictions on mental health were minimal, but for those who had previously felt well, the restrictions and the impact of the pandemic on well-being were much greater. Conclusions: These data show no evidence of a social gradient in well-being related to the pandemic. In fact, well-being was shown to be highly elastic in this period indicating a national level of resilience which cut across the usually observed health inequalities.

Indexed as

COVID-19ResilienceSocial gradientWell-being

Identifiers

PMID35496728
PMCPMC9036507

What OpenQuestion holds

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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.