Evidence map›Paper›PMID 40566343›Full record

ArticleInternational journal of environmental research and public health2025

Prevalence and Predictors of Posting Health-Related Content Among US Facebook Users: A Cross-Sectional Survey Study.

Richard Bannor, Ran Xu, Jolaade Kalinowski, Tricia Leahey, Caitlin Caspi, Christie I Idiong, Jared Goetz, Sherry Pagoto

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Richard BannorDepartment of Allied Health Sciences, University of Connecticut, Storrs, CT 06269-1101, USA.ORCID 0000-0002-5849-8740
Ran XuDepartment of Allied Health Sciences, University of Connecticut, Storrs, CT 06269-1101, USA.ORCID 0000-0002-5832-9226
Jolaade KalinowskiDepartment of Human Development and Family Sciences, University of Connecticut, Storrs, CT 06269-1058, USA.
Tricia LeaheyDepartment of Allied Health Sciences, University of Connecticut, Storrs, CT 06269-1101, USA.
Caitlin CaspiDepartment of Allied Health Sciences, University of Connecticut, Storrs, CT 06269-1101, USA.
Christie I IdiongDepartment of Allied Health Sciences, University of Connecticut, Storrs, CT 06269-1101, USA.
Jared GoetzDepartment of Allied Health Sciences, University of Connecticut, Storrs, CT 06269-1101, USA.
Sherry PagotoDepartment of Allied Health Sciences, University of Connecticut, Storrs, CT 06269-1101, USA.ORCID 0000-0002-2462-8797

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health-related content is prevalent on Facebook, but we know little about how often the typical user posts about health, the nature of such posts, or the characteristics of users who do so. We conducted a cross-sectional survey of 2508 adult US Facebook users to assess the frequency and predictors of posting about a health condition, health behavior, and health information on Facebook. The findings revealed that 68.7% of participants posted at least one type of health-related content on Facebook in the past year, and 41.6% posted all three types of health-related content. Approximately 47% posted about a health condition, 56.7% posted about health behavior, and 62.7% posted health information in the past year. Male gender, advanced education, greater Facebook engagement, having a greater number of Facebook friends, and having a chronic disease were associated with more frequent posting of all types of health-related posts (all

Indexed as

Social MediaAdolescentAdultAgedCross-Sectional StudiesFemaleHealth BehaviorHumansMaleMiddle AgedPrevalenceSurveys and QuestionnairesUnited StatesYoung AdultFacebook and healthpeer-to-peer healthcareposting health-related contentsocial media

Identifiers

PMID40566343
PMCPMC12193171

What OpenQuestion holds

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LicenceCC BY
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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.