Evidence map›Paper›PMID 42062434›Full record

ArticleScientific reports2026

Healthcare professionals' trust in health authorities throughout COVID-19: a social media analysis.

Idan-Chaim Cohen, Noa Tal, Aviad Elyashar, Rami Puzis, Odeya Cohen

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Idan-Chaim CohenDepartment of Nursing, Recanati School of Community Health Professions, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel. idanchai@post.bgu.ac.il.
Noa TalCyber@BGU, Ben-Gurion University of the Negev, Be'er Sheva, Israel.
Aviad ElyasharCyber@BGU, Ben-Gurion University of the Negev, Be'er Sheva, Israel.
Rami Puzis *Cyber@BGU, Ben-Gurion University of the Negev, Be'er Sheva, Israel.
Odeya Cohen *Department of Nursing, Recanati School of Community Health Professions, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare professionals' institutional trust in health authorities is important for effective crisis response, as these professionals serve as both implementers of health directives and trust intermediaries influencing public confidence. Despite extensive research on public trust during COVID-19, studies examining healthcare professionals' trust in health authorities remain limited. Traditional survey methods face declining response rates and provide only cross-sectional snapshots. Social media platforms offer longitudinal data enabling analysis of trust expressions over extended periods. We analyzed 50,308 tweets from 9,442 healthcare professionals mentioning WHO, CDC, and FDA from January 2019 through March 2023. Large language models assessed trust levels using a 5-point scale. WHO showed the highest mean trust score, followed by FDA and CDC. Trust patterns varied by authority: WHO showed a pronounced early-pandemic decline with subsequent recovery, CDC showed sustained trust erosion throughout 2022-2023, and FDA remained relatively stable. Topic modeling identified 10 major themes, with integrity concerns dominating low-trust discourse across all authorities. Social media analysis demonstrates feasibility for continuous monitoring of healthcare professionals' trust dynamics, enabling early detection of authority-specific trust erosion patterns.

Indexed as

COVID-19Health PersonnelSocial MediaTrustDigital MediaHumansPandemicsSARS-CoV-2United StatesCOVID-19Health authoritiesHealthcare professionalsInstitutional trustLarge language modelsSocial media analysis

Identifiers

PMID42062434
PMCPMC13324178

What OpenQuestion holds

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LicenceCC BY
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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.