A Model of Trust in Online COVID-19 Information and Advice: Cross-Sectional Questionnaire Study.

Publication date: Feb 13, 2025

During the COVID-19 pandemic, many people sought information from websites and social media. Understanding the extent to which these sources were trusted is important in relation to health communication. This study aims to identify the key factors influencing UK citizens’ trust and intention to act on advice about COVID-19 found via digital resources and to test whether an existing model of trust in eHealth provided a good fit for COVID-19-related information seeking online. We also wished to identify any differences between the evaluation of general information and information relating specifically to COVID-19 vaccines. In total, 525 people completed an online survey in January 2022 encompassing a general web trust questionnaire, measures of information corroboration, coping perceptions, and intention to act. Data were analyzed using principal component analysis and structural equation modeling. The evaluation responses of general information and COVID-19 vaccine information were also compared. The principal component analysis revealed 5 trust factors: (1) credibility and impartiality, (2) familiarity, (3) privacy, (4) usability, and (5) personal experiences. In the final structural equation modeling model, trust had a significant direct effect on intention to act (β=. 65; P

Concepts Keywords
Impartiality Adolescent
January Adult
Online Aged
Pandemic Consumer Health Information
Vaccine COVID-19
COVID-19
COVID-19 Vaccines
COVID-19 Vaccines
Cross-Sectional Studies
digital intervention
digital resources
eHealth
electronic health
Female
global health
health information
Humans
infectious
Information Seeking Behavior
Intention
Internet
Male
Middle Aged
online information seeking
pandemic
Pandemics
public health
pulmonary
respiratory
SARS-CoV-2
SARS-CoV-2
scientific credibility
Social Media
social media
surveys
Surveys and Questionnaires
Telemedicine
Trust
trust
United Kingdom
Young Adult

Semantics

Type Source Name
disease MESH COVID-19
disease MESH privacy
disease IDO intervention

Original Article

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