Evidence map›Paper›PMID 36776404›Full record

ArticleDigital health

Tiktoking COVID-19 with frontline workers.

Ahmed Al-Rawi, Kiana Zemenchik

Abstract 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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
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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.

Ahmed Al-RawiSchool of Communication, Faculty of Communication, Art and Technology, Simon Fraser University, British Columbia, Canada.ORCID https://orcid.org/0000-0001-7336-1550
Kiana ZemenchikSchool for International Studies, Faculty of Communication, Art and Technology, Simon Fraser University, British Columbia, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction/Objective: During the COVID-19 pandemic, frontline workers have taken to social media platforms to discuss a variety of issues that concern their personal and professional lives. In particular, TikTok's increased prominence as a social media channel has proved significant for enhancing the public presence of healthcare workers and their ability to disseminate content to a wider audience. The ways that healthcare workers use TikTok draws attention to the type of health information disseminated to the public through social media platforms. This provides the public with succinct and often visually entertaining information that may not be otherwise distributed to them directly from elsewhere. This study also provides relevant insights into how social media-TikTok in particular-can be used as a tool for disseminating knowledge about COVID-19 related topics and combatting misinformation by using the credibility of frontline workers. Methods: This study collected a sample of over 2100 TikTok videos posted by healthcare workers that were coded according to the dominant overarching themes. Results: The themes that arose from this sample were: (1) healthcare workers' mental health and working conditions, (2) healthcare heroes/appreciation, (3) criticism against official authorities, (4) countering misinformation, (5) humor/satire, and (6) educational content. Conclusion: Due to the rise in public appreciation for frontline workers, examining the effects of the pandemic through the eyes of frontline workers has drawn attention to their lived realities in various forms. This study provided some insight into how frontline workers use TikTok to disseminate information and education to the public, often relying on their perceived credibility.

Indexed as

COVID-19frontline workerspandemicTikTok

Identifiers

PMID36776404
PMCPMC9912553

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.