Evidence map›Paper›PMID 38655203›Full record

ArticleJournal of applied research in memory and cognition2024

Scenario-Based Messages on Social Media Motivate COVID-19 Information Seeking.

Alyssa H Sinclair, Morgan K Taylor, Audra Davidson, Joshua S Weitz, Stephen J Beckett, Gregory R Samanez-Larkin

Abstract read
In one paragraph

Article in Journal of applied research in memory and cognition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Behavioral interventions motivate action to address climate change.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. 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

6 authors.

Alyssa H SinclairDepartment of Psychology and Neuroscience, Duke University, Durham, NC, USA.
Morgan K TaylorDepartment of Psychology and Neuroscience, Duke University, Durham, NC, USA.
Audra DavidsonSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
Joshua S WeitzSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
Stephen J BeckettSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
Gregory R Samanez-LarkinDepartment of Psychology and Neuroscience, Duke University, Durham, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Communicating information about health risks empowers individuals to make informed decisions. To identify effective communication strategies, we manipulated the specificity, self-relevance, and emotional framing of messages designed to motivate information seeking about COVID-19 exposure risk. In Study 1 (N=221,829), we conducted a large-scale social media field study. Using Facebook advertisements, we targeted users by age and political attitudes. Episodic specificity drove engagement: Advertisements that contextualized risk in specific scenarios produced the highest click-through rates, across all demographic groups. In Study 2, we replicated and extended our findings in an online experiment (N=4,233). Message specificity (but not self-relevance or emotional valence) drove interest in learning about COVID-19 risks. Across both studies, we found that older adults and liberals were more interested in learning about COVID-19 risks. However, message specificity increased engagement across demographic groups. Overall, evoking specific scenarios motivated information seeking about COVID-19, facilitating risk communication to a broad audience.

Indexed as

COVID-19episodic specificityinformation seekingpublic healthrisk communicationsocial media

Identifiers

PMID38655203
PMCPMC11034827

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.