Literature DB >> 28059557

Message Framing in Vaccine Communication: A Systematic Review of Published Literature.

Marcela A Penţa1, Adriana Băban1.   

Abstract

Suboptimal vaccination rates are a significant problem in many countries today, in spite of improved access to vaccine services. As a result, there has been a recent expansion of research on how best to communicate about vaccines. The purpose of the present article is to provide an updated review of published, peer-reviewed empirical studies that examined the effectiveness of gain versus loss framing (i.e., goal framing) in the context of vaccine communication. To locate studies, we examined the reference list from the previous meta-analytic review (O'Keefe & Nan, 2012), and we conducted systematic searches across multiple databases. We included 34 studies in the qualitative synthesis. The relative effectiveness of goal-framed vaccine messages was often shown to depend on characteristics of the message recipient, perceived risk, or situational factors, yet most effects were inconsistent across studies, or simply limited by an insufficient number of studies. Methodological characteristics and variations are noted and discussed. The review points to several directions concerning moderators and mediators of framing effects where additional rigorous studies would be needed.

Entities:  

Mesh:

Year:  2017        PMID: 28059557     DOI: 10.1080/10410236.2016.1266574

Source DB:  PubMed          Journal:  Health Commun        ISSN: 1041-0236


  11 in total

1.  The effects of message framing and healthcare provider recommendation on adult hepatitis B vaccination: A randomized controlled trial.

Authors:  Monica L Kasting; Katharine J Head; Dena Cox; Anthony D Cox; Gregory D Zimet
Journal:  Prev Med       Date:  2019-08-09       Impact factor: 4.018

2.  African American Parents' Perceived Vaccine Efficacy Moderates the Effect of Message Framing on Psychological Reactance to HPV Vaccine Advocacy.

Authors:  Adam S Richards; Yan Qin; Kelly Daily; Xiaoli Nan
Journal:  J Health Commun       Date:  2021-08-24

3.  A randomized controlled trial of a video intervention shows evidence of increasing COVID-19 vaccination intention.

Authors:  Leah S Witus; Erik Larson
Journal:  PLoS One       Date:  2022-05-19       Impact factor: 3.240

Review 4.  Understanding vaccine acceptance and demand-and ways to increase them.

Authors:  Katrine Bach Habersaat; Cath Jackson
Journal:  Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz       Date:  2020-01       Impact factor: 1.513

Review 5.  Rapid review of virus risk communication interventions: Directions for COVID-19.

Authors:  Darren M Winograd; Cara L Fresquez; Madison Egli; Emily K Peterson; Alyssa R Lombardi; Allison Megale; Yajaira A Cabrera Tineo; Michael G Verile; Alison L Phillips; Jessica Y Breland; Susan Santos; Lisa M McAndrew
Journal:  Patient Educ Couns       Date:  2021-01-20

6.  Effect of Information about COVID-19 Vaccine Effectiveness and Side Effects on Behavioural Intentions: Two Online Experiments.

Authors:  John R Kerr; Alexandra L J Freeman; Theresa M Marteau; Sander van der Linden
Journal:  Vaccines (Basel)       Date:  2021-04-13

7.  Finding the facts in an infodemic: framing effective COVID-19 messages to connect people to authoritative content.

Authors:  Andrew B Pattison; Monta Reinfelde; Hyunsoo Chang; Mayukh Chowdhury; Emma Cohen; Sean Malahy; Katie O'Connor; Mehdi Sellami; Karen L Smith; Charlotte Y Stanton; Bram Voets; Henry G Wei
Journal:  BMJ Glob Health       Date:  2022-02

8.  Message framing and COVID-19 vaccine acceptance among millennials in South India.

Authors:  Aslesha Prakash; Robert Jeyakumar Nathan; Sannidhi Kini; Vijay Victor
Journal:  PLoS One       Date:  2022-07-08       Impact factor: 3.752

9.  Using Machine Learning to Compare Provaccine and Antivaccine Discourse Among the Public on Social Media: Algorithm Development Study.

Authors:  Young Anna Argyris; Kafui Monu; Pang-Ning Tan; Colton Aarts; Fan Jiang; Kaleigh Anne Wiseley
Journal:  JMIR Public Health Surveill       Date:  2021-06-24

10.  Using a Machine Learning Approach to Monitor COVID-19 Vaccine Adverse Events (VAE) from Twitter Data.

Authors:  Andrew T Lian; Jingcheng Du; Lu Tang
Journal:  Vaccines (Basel)       Date:  2022-01-11
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