Evidence map›Paper›PMID 39337186›Full record

ArticleHealthcare (Basel, Switzerland)2024

The Role of Health Belief Model Constructs and Content Creator Characteristics in Social Media Engagement: Insights from COVID-19 Vaccine Tweets.

Xiaofeng Jia, Soyeon Ahn, Michelle I Seelig, Susan E Morgan

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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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

4 authors.

Xiaofeng JiaSchool of Media & Communication, Bowling Green State University, Bowling Green, OH 43403, USA.ORCID 0000-0003-1709-2776
Soyeon AhnDepartment of Educational and Psychological Studies, School of Education and Human Development, University of Miami, Coral Gables, FL 33146, USA.ORCID 0000-0003-2581-306X
Michelle I SeeligDepartment of Interactive Media School of Communication, School of Communication, Coral Gables, FL 33146, USA.ORCID 0000-0003-0462-7452
Susan E MorganDepartment of Communication Studies, School of Communication, University of Miami, Coral Gables, FL 33146, USA.ORCID 0000-0002-8403-9484

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe Health Belief Model (HBM) has been widely studied, but it is unclear how social media post creators use HBM constructs to influence the public's awareness of health topics, particularly for COVID-19 preventative health behaviors. Moreover, there is limited knowledge about how content creators enhance user engagement with COVID-19 vaccine tweets.

methodsA content analysis of COVID-19 vaccine tweets (

findingsContent creators' tweets about COVID-19-related topics generally centered on two HBM constructs-benefits and barriers-while fewer tweets emphasized perceived susceptibility or self-efficacy; tweets containing these constructs were retweeted less often. Findings revealed that tweets from politicians, health experts, and white and Asian sources emphasized the perceived benefits of the COVID-19 vaccine. Individual tweets, especially from Black individuals and celebrities, generated more user engagement.

conclusionsUnderstanding the factors that contribute to social media user engagement with health-related content is important for designing more focused and impactful health communication campaigns and promoting healthier habits and perspectives. Thus, by demonstrating the possible relevance of the HBM to digital communication strategies or health campaigns, our study provides useful guidance for health promoters and policymakers who use social media to raise public health awareness.

Indexed as

content analysiscontent creator characteristicsCOVID-19 vaccinehealth belief modelsocial media engagement

Identifiers

PMID39337186
PMCPMC11431524

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.