Evidence map›Paper›PMID 33026354›Full record

ArticleJournal of medical Internet research2020

Low Testosterone on Social Media: Application of Natural Language Processing to Understand Patients' Perceptions of Hypogonadism and Its Treatment.

Vadim Osadchiy, Tommy Jiang, Jesse Nelson Mills, Sriram Venkata Eleswarapu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Vadim OsadchiyDivision of Andrology, Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0003-0492-9987
Tommy JiangDivision of Andrology, Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-1199-0615
Jesse Nelson MillsDivision of Andrology, Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-7833-7071
Sriram Venkata EleswarapuDivision of Andrology, Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0003-1852-4833
University of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the results of the Testosterone Trials, physicians remain uncomfortable treating men with hypogonadism. Discouraged, men increasingly turn to social media to discuss medical concerns.

objectiveThe goal of the research was to apply natural language processing (NLP) techniques to social media posts for identification of themes of discussion regarding low testosterone and testosterone replacement therapy (TRT) in order to inform how physicians may better evaluate and counsel patients.

methodsWe retrospectively extracted posts from the Reddit community r/Testosterone from December 2015 through May 2019. We applied an NLP technique called the meaning extraction method with principal component analysis (MEM/PCA) to computationally derive discussion themes. We then performed a prospective analysis of Twitter data (tweets) that contained the terms low testosterone, low T, and testosterone replacement from June through September 2019.

resultsA total of 199,335 Reddit posts and 6659 tweets were analyzed. MEM/PCA revealed dominant themes of discussion: symptoms of hypogonadism, seeing a doctor, results of laboratory tests, derogatory comments and insults, TRT medications, and cardiovascular risk. More than 25% of Reddit posts contained the term doctor, and more than 5% urologist.

conclusionsThis study represents the first NLP evaluation of the social media landscape surrounding hypogonadism and TRT. Although physicians traditionally limit their practices to within their clinic walls, the ubiquity of social media demands that physicians understand what patients discuss online. Physicians may do well to bring up online discussions during clinic consultations for low testosterone to pull back the curtain and dispel myths.

Indexed as

Natural Language ProcessingHormone Replacement TherapyHumansHypogonadismMalePerceptionProspective StudiesRetrospective StudiesSocial MediaTestosteroneTestosteronehypogonadismnatural language processingRedditsocial mediatestosterone replacement therapyTwitter

Identifiers

PMID33026354
PMCPMC7578816
OpenAlexW3092289137

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.