Evidence map›Paper›PMID 42813910›Full record

ArticleJournal of medical Internet research2026

Pre-Exposure Prophylaxis-Related Messages Across Facebook, Instagram, and Twitter (Rebranded X): Content Analysis.

Lourdes S Martinez, Nicole Crocker, Sharanya Akkone, Shravani Hariprasad, Rebecca Houghton, Eric R Walsh-Buhi

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

6 authors.

Lourdes S MartinezSchool of Communication, San Diego State University, 5500 Campanile Drive, San Diego, CA, 92182, United States, 1 6572233122.ORCID http://orcid.org/0000-0001-8011-120X
Nicole CrockerDepartment of Applied Health Science, School of Public Health, Indiana University Bloomington, Bloomington, IN, United States.ORCID http://orcid.org/0000-0002-1019-8546
Sharanya AkkoneThe Center for Human Dynamics in the Mobile Age, San Diego State University, San Diego, CA, United States.ORCID http://orcid.org/0009-0006-5227-6465
Shravani HariprasadThe Center for Human Dynamics in the Mobile Age, San Diego State University, San Diego, CA, United States.ORCID http://orcid.org/0009-0009-2683-471X
Rebecca HoughtonDepartment of Applied Health Science, School of Public Health, Indiana University Bloomington, Bloomington, IN, United States.ORCID http://orcid.org/0000-0002-2590-7907
Eric R Walsh-BuhiDepartment of Applied Health Science, School of Public Health, Indiana University Bloomington, Bloomington, IN, United States.ORCID http://orcid.org/0000-0002-1690-5352

Funding

Pre-exposure prophylaxis (PrEP) information on social mediaR21HD108052 · NICHD · TRUSTEES OF INDIANA UNIVERSITY · PI WALSH-BUHI, ERIC RICHARD · 2023 to 2024
$445k
NICHD NIH HHS R21 HD108052
6 · The paper itself

Abstract

Background: Interventions are needed to address the lack of pre-exposure prophylaxis (PrEP) awareness and mitigate barriers related to PrEP use. One such intervention modality is social media, as PrEP awareness and communication on issues, such as access and cost, are easily addressed via clear social media messages on platforms for PrEP-eligible people, and especially young people, who use social media more frequently. Objective: This descriptive study seeks to extend understanding of PrEP awareness and usage by examining PrEP-related communication across 3 popular social media platforms (Facebook [Meta Platforms, Inc], Instagram [Meta Platforms, Inc], and Twitter [rebranded as X]) and identifying message and source characteristics. Methods: In February 2023, we used CrowdTangle (a public insights tool owned by Facebook, now known as Meta) to gather a total of 39,790 Facebook posts and 5628 Instagram posts. We also used Twitter's public API to collect 14,061 Twitter posts during the same time frame. Of these, we drew a random sample of social media posts from each platform (1000 posts from Facebook, 1000 posts from Instagram, and 811 posts from Twitter) in February 2023 and analyzed them using a quantitative content analysis. Results: Our findings showed some differences in the types of text-based content appearing on each platform. We also uncovered similar patterns across all three platforms: (1) definitions of and indications for PrEP were the most common type of text-based content in posts; (2) information about PrEP appearing in social media posts drew from websites other than traditional sources such as public health organizations, health care providers, and government agencies; and (3) men who have sex with men represented the most frequently mentioned target population. Although our study did not detect a large presence of theory-based concepts from behavior change theory, such as the integrative model of behavioral prediction, across all platforms, attitude emerged most frequently, followed by self-efficacy. Conclusions: These findings shed light on the PrEP-related content that may reach and shape the perceptions of young people who could benefit from PrEP use. Such insights can guide the design of future social media-based messages targeting the most influential beliefs to strengthen HIV prevention efforts.

Indexed as

HIV InfectionsPre-Exposure ProphylaxisSocial MediaDigital MediaHumansMedia Exposurecontent analysishealth communicationHIVpre-exposure prophylaxissocial media

Identifiers

PMID42813910
PMCPMC13625616

What OpenQuestion holds

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Registered trials

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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.