Evidence map›Paper›PMID 37113799›Full record

ArticleJMIR infodemiology

Unsupervised Machine Learning to Detect and Characterize Barriers to Pre-exposure Prophylaxis Therapy: Multiplatform Social Media Study.

Qing Xu, Matthew C Nali, Tiana McMann, Hector Godinez, Jiawei Li, Yifan He, Mingxiang Cai, Christine Lee, Christine Merenda, Richardae Araojo and 1 more

Open access · goldFull text read
In one paragraph

Article in JMIR infodemiology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 20% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
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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

11 authors at 3 institutions in 1 country.

Qing XuS-3 Research San Diego, CA United States.ORCID https://orcid.org/0000-0002-4507-1094
Matthew C NaliS-3 Research San Diego, CA United States.ORCID https://orcid.org/0000-0002-0565-8202
Tiana McMannS-3 Research San Diego, CA United States.ORCID https://orcid.org/0000-0003-1964-5549
Hector GodinezS-3 Research San Diego, CA United States.ORCID https://orcid.org/0000-0003-2420-5951
Jiawei LiS-3 Research San Diego, CA United States.ORCID https://orcid.org/0000-0001-9801-4715
Yifan HeS-3 Research San Diego, CA United States.ORCID https://orcid.org/0000-0002-9002-6495
Mingxiang CaiS-3 Research San Diego, CA United States.ORCID https://orcid.org/0000-0001-6816-5192
Christine LeeOffice of Minority Health and Health Equity, U.S. Food and Drug Administration Silver Spring, MD United States.ORCID https://orcid.org/0000-0001-8953-4823
Christine MerendaOffice of Minority Health and Health Equity, U.S. Food and Drug Administration Silver Spring, MD United States.ORCID https://orcid.org/0000-0002-0849-8013
Richardae AraojoOffice of Minority Health and Health Equity, U.S. Food and Drug Administration Silver Spring, MD United States.ORCID https://orcid.org/0000-0002-4457-9427
Tim Ken MackeyS-3 Research San Diego, CA United States.ORCID https://orcid.org/0000-0002-2191-7833
San Diego Biomedical Research Institute · USUnited States Food and Drug Administration · USUniversity of California System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Among racial and ethnic minority groups, the risk of HIV infection is an ongoing public health challenge. Pre-exposure prophylaxis (PrEP) is highly effective for preventing HIV when taken as prescribed. However, there is a need to understand the experiences, attitudes, and barriers of PrEP for racial and ethnic minority populations and sexual minority groups. Objective: This infodemiology study aimed to leverage big data and unsupervised machine learning to identify, characterize, and elucidate experiences and attitudes regarding perceived barriers associated with the uptake and adherence to PrEP therapy. This study also specifically examined shared experiences from racial or ethnic populations and sexual minority groups. Methods: The study used data mining approaches to collect posts from popular social media platforms such as Twitter, YouTube, Tumblr, Instagram, and Reddit. Posts were selected by filtering for keywords associated with PrEP, HIV, and approved PrEP therapies. We analyzed data using unsupervised machine learning, followed by manual annotation using a deductive coding approach to characterize PrEP and other HIV prevention-related themes discussed by users. Results: We collected 522,430 posts over a 60-day period, including 408,637 (78.22%) tweets, 13,768 (2.63%) YouTube comments, 8728 (1.67%) Tumblr posts, 88,177 (16.88%) Instagram posts, and 3120 (0.6%) Reddit posts. After applying unsupervised machine learning and content analysis, 785 posts were identified that specifically related to barriers to PrEP, and they were grouped into three major thematic domains: provider level (13/785, 1.7%), patient level (570/785, 72.6%), and community level (166/785, 21.1%). The main barriers identified in these categories included those associated with knowledge (lack of knowledge about PrEP), access issues (lack of insurance coverage, no prescription, and impact of COVID-19 pandemic), and adherence (subjective reasons for why users terminated PrEP or decided not to start PrEP, such as side effects, alternative HIV prevention measures, and social stigma). Among the 785 PrEP posts, we identified 320 (40.8%) posts where users self-identified as racial or ethnic minority or as a sexual minority group with their specific PrEP barriers and concerns. Conclusions: Both objective and subjective reasons were identified as barriers reported by social media users when initiating, accessing, and adhering to PrEP. Though ample evidence supports PrEP as an effective HIV prevention strategy, user-generated posts nevertheless provide insights into what barriers are preventing people from broader adoption of PrEP, including topics that are specific to 2 different groups of sexual minority groups and racial and ethnic minority populations. Results have the potential to inform future health promotion and regulatory science approaches that can reach these HIV and AIDS communities that may benefit from PrEP.

Indexed as

HIVinfoveillanceminority healthPrEPsocial media

Identifiers

PMID37113799
PMCPMC10014091
OpenAlexW4226294230

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read50
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.