Evidence map›Paper›PMID 38742070›Full record

ReviewHeliyon2024

The use of fear appeals for pandemic compliance: A systematic review of empirical measurement, fear appeal strategies and effectiveness.

Syden Mishi, Farai Borden Mushonga, Godfred Anakpo

Abstract readReview
In one paragraph

Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. Article
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

3 authors.

Syden MishiDepartment of Economics, Nelson Mandela University, South Africa.
Farai Borden MushongaDepartment of Economics, Nelson Mandela University, South Africa.
Godfred AnakpoDepartment of Economics, Nelson Mandela University, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interventions to pandemic outbreaks are often associated with the use of fear-appeal to trigger behavioral change, especially in public health issues. However, no systematic review exists in the literature on the effectiveness of fear appeal strategies in the context of pandemic compliance. This paper aims at providing systematic literature review that answers the following thought-provoking research questions: (1) What is the standard measurement of fear in relation to pandemics in the existing literature? (2) What are the fear appeal strategies used in the empirical literature? (3) How effective are fear appeal strategies in changing behavior toward adopting pandemic preventive measures? A total of 22 studies were selected from 455 potential studies, following a comprehensive literature search and assessment in accordance with the PRISMA guidelines. The findings show that nearly all the available studies on fear measurement used the Likert scale (as the standard approach) with different points of degree and fear appeal strategies such as fear triggers in media channels, print advertisements, and verbal descriptions. Furthermore, most studies conclude that fear appeal is effective in making participants adopt pandemic preventive measures; hence, it is effective for positive behavioral change (the degree of effectiveness depends on gender, population group, etc.), especially when combined with self-efficacy and socio-cultural considerations. Very few studies, however, find an insignificant association, arguably due to the kind and intensity of the fear appeal messages and strategies used.

Indexed as

Fear appealFear appeal effectivenessFear measurementInterventionPandemicSelf-efficacyStrategies

Identifiers

PMID38742070
PMCPMC11089312

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.