Evidence map›Paper›PMID 34917812›Full record

ArticleHeliyon2021

Rapid discovery of optimal messages for behavioral intervention: the case of Hungary and Covid-19.

Gillie Gabay, Attila Gere, Orsolya Fehér, Nick Bellissimo, Howard Moskowitz

Abstract read
In one paragraph

Article in Heliyon, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Gillie GabayAchva Academic College, Multi-Disciplinary Studies, Arugot, 7980400, Israel.
Attila GereInstitute of Food Technology, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary.
Orsolya FehérInstitute of Agribusiness, Hungarian University of Agriculture and Life Sciences, 2100 Gödöllő, Hungary.
Nick BellissimoSchool of Nutrition, Ryerson University, 350 Victoria Street, Toronto, Canada.
Howard MoskowitzMind Cart AI, White Plains, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The right messaging plays an important role in the fight against the spread of COVID-19. The present study aims at uncovering the way people think about governmental measures against COVID-19. Two hundred and sixteen Hungarians participated in this on-line study. A conjoint-based experimental design was used to reveal the power of messages as drivers of voluntary social distancing based on the perceived risk of COVID-19, the ways to practice social distancing and to assure it, and preferences regarding the communicator of the social distancing policy. Results revealed three major mindsets: Pandemic observers, Order-followers, and Health-conscious. Members of each mindset respond differently to messages. To enhance compliance with social distancing and contain the virus, we suggest using the prediction tool we developed to identify the belonging of people or groups in the population to mindsets in the sample and address people using effective mindset-tailored messaging.

Indexed as

CommunicationConjointCOVID-19Mindset-segmentationRegression

Identifiers

PMID34917812
PMCPMC8668826

What OpenQuestion holds

Textmetadata
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.