Evidence map›Paper›PMID 37695666›Full record

ArticleJournal of medical Internet research2023

Appraising Unmet Needs and Misinformation Spread About Polycystic Ovary Syndrome in 85,872 YouTube Comments Over 12 Years: Big Data Infodemiology Study.

Kashish Malhotra, Punith Kempegowda

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
12.1field-weighted citation impact, top 2% 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

13 citing papers in PubMed, 21 citations in OpenAlex.

  1. Observational
  2. Review
  3. Article
  4. Article
  5. Article
  6. Network analysis of core symptom changes in lung cancer survivors: a longitudinal study.Journal of cancer survivorship : research and practice · 2025
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. 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

2 authors at 2 institutions in 2 countries.

Kashish MalhotraDepartment of Surgery, Dayanand Medical College and Hospital, Ludhiana, India.ORCID 0000-0002-6985-5731
Punith KempegowdaInstitute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom.ORCID 0000-0003-0954-6512
Dayanand Medical College & Hospital · INUniversity Hospitals Birmingham NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPolycystic ovary syndrome (PCOS) is the most common endocrinopathy in women, resulting in substantial burden related to metabolic, reproductive, and psychological complications. While attempts have been made to understand the themes and sentiments of the public regarding PCOS at the local and regional levels, no study has explored worldwide views, mainly due to financial and logistical limitations. YouTube is one of the largest sources of health-related information, where many visitors share their views as questions or comments. These can be used as a surrogate to understand the public's perceptions.

objectiveWe analyzed the comments of all videos related to PCOS published on YouTube from May 2011 to April 2023 and identified trends over time in the comments, their context, associated themes, gender-based differences, and underlying sentiments.

methodsAfter extracting all the comments using the YouTube application programming interface, we contextually studied the keywords and analyzed gender differences using the Benjamini-Hochberg procedure. We applied a multidimensional approach to analyzing the content via association mining using Mozdeh. We performed network analysis to study associated themes using the Fruchterman-Reingold algorithm and then manually screened the comments for content analysis. The sentiments associated with YouTube comments were analyzed using SentiStrength.

resultsA total of 85,872 comments from 940 PCOS videos on YouTube were extracted. We identified a specific gender for 13,106 comments. Of these, 1506 were matched to male users (11.5%), and 11,601 comments to female users (88.5%). Keywords including diagnosing PCOS, symptoms of PCOS, pills for PCOS (medication), and pregnancy were significantly associated with female users. Keywords such as herbal treatment, natural treatment, curing PCOS, and online searches were significantly associated with male users. The key themes associated with female users were symptoms of PCOS, positive personal experiences (themes such as helpful and love), negative personal experiences (fatigue and pain), motherhood (infertility and trying to conceive), self-diagnosis, and use of professional terminology detailing their journey. The key themes associated with male users were misinformation regarding the "cure" for PCOS, using natural and herbal remedies to cure PCOS, fake testimonies from spammers selling their courses and consultations, finding treatment for PCOS, and sharing perspectives of female family members. The overall average positive sentiment was 1.6651 (95% CI 1.6593-1.6709), and the average negative sentiment was 1.4742 (95% CI 1.4683-1.4802) with a net positive difference of 0.1909.

conclusionsThere may be a disparity in views on PCOS between women and men, with the latter associated with non-evidence-based approaches and misinformation. The improving sentiment noticed with YouTube comments may reflect better health care services. Prioritizing and promoting evidence-based care and disseminating pragmatic online coverage is warranted to improve public sentiment and limit misinformation spread.

Indexed as

Polycystic Ovary SyndromeSocial MediaAlgorithmsBig DataFemaleHumansInfodemiologyMalePregnancybig datacommentscontextualizationendocrinopathyfatiguegenderglobal equityglobal healthinfodemiologymisinformationmotherhoodnetwork analysisonline trendspainPCOSpolycystic ovary syndromepublicsentimenttreatmentuserswomenword associationYouTube

Identifiers

PMID37695666
PMCPMC10520765
OpenAlexW4386593061

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.