Evidence map›Paper›PMID 34868622›Full record

ArticleDigital health

Long Covid: Online patient narratives, public health communication and vaccine hesitancy.

Esperanza Miyake, Sam Martin

Open access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
16.7field-weighted citation impact, top 1% 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

27 citing papers in PubMed, 54 citations in OpenAlex.

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  14. Long COVID quality of life and healthcare experiences in the UK: a mixed method online survey.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
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  19. "Healing Can Be a Very Jagged Line": Reflections on Life as a COVID-19 Long Hauler.Journal of patient-centered research and reviews · 2023
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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

2 authors at 2 institutions in 1 country.

Esperanza MiyakeChancellor's Fellow, Department of Journalism, Media and Communication, University of Strathclyde, Glasgow, Scotland G4 0LT.ORCID https://orcid.org/0000-0001-5504-7648
Sam MartinDigital Sociologist and Big Data Analytics Research Consultant: Ethox Centre, Nuffield Department of Population Health, Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford OX3 7LF, United Kingdom.ORCID https://orcid.org/0000-0002-4466-8374
University of Oxford · GBUniversity of Strathclyde · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThis study combines quantitative and qualitative analyses of social media data collected through three key stages of the pandemic, to highlight the following: 'First wave' (March to May, 2020): negative consequences arising from a disconnect between official health communications, and unofficial Long Covid sufferers' narratives online.'Second wave' (October 2020 to January 2021): closing the 'gap' between official health communications and unofficial patient narratives, leading to a better integration between patient voice, research and services.'Vaccination phase' (January 2021, early stages of the vaccination programme in the UK): continuing and new emerging concerns.

methodsWe adopted a mixed methods approach involving quantitative and qualitative analyses of 1.38 million posts mentioning long-term symptoms of Covid-19, gathered across social media and news platforms between 1 January 2020 and 1 January 2021, on Twitter, Facebook, Blogs, and Forums. Our inductive thematic analysis was informed by our discourse analysis of words, and sentiment analysis of hashtags and emojis.

resultsResults indicate that the negative impacts arise mostly from conflicting definitions of Covid-19 and fears around the Covid-19 vaccine for Long Covid sufferers. Key areas of concern are: time/duration; symptoms/testing; emotional impact; lack of support and resources.

conclusionsWhilst Covid-19 is a global issue, specific sociocultural, political and economic contexts mean patients experience Long Covid at a localised level, needing appropriate localised responses. This can only happen if we build a knowledge base that begins with the patient, ultimately informing treatment and rehabilitation strategies for Long Covid.

Indexed as

Covid-19health communications < generalinternet < generalLong Covidonline < generalself monitoring < personalised medicinesocial media < media

Identifiers

PMID34868622
PMCPMC8638072
OpenAlexW3208501419

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.