Evidence map›Paper›PMID 37971606›Full record

ArticleJournal of medical systems2023

Shaping Social Media: Is Twitter an Equitable tool for Professional Development?

Thibacg Sivayoganathan, Amrit Kirpalani

Abstract read
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Article in Journal of medical systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Thibacg SivayoganathanSchulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Amrit KirpalaniDepartment of Paediatrics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada. amrit.kirpalani@lhsc.on.ca.ORCID https://orcid.org/0000-0001-7567-9052

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTwitter has become a powerful tool for professional development in academia. However, studies from the general population suggest that racialized and gender biases disproportionately empower male and white users. We characterized the demographics of Twitter influencers in Canadian healthcare.

methodsWe used the Right Relevance Insight API algorithm to identify Twitter influencers in the healthcare, healthcare research, and health policy domains, and to generated normalized influencer scores based on user connections and engagement. We used facial recognition software to approximate the influencers' race and sex.

resultsThe majority of influencers identified were white (84%) and/or male (60%). Males had significantly higher influencer scores than females (65.1 ± 8.0 vs. 61.2 ± 6.2, P < 0.05) in health policy. We did not identify any sex- or race-associated disparities among influencers in healthcare or healthcare research.

conclusionMale users have significantly higher levels of influence in health policy on Twitter. Given the importance of Twitter as a tool for professional development, it is crucial that institutional leaders and policymakers are aware of potential inequities in user reach. Future studies should evaluate additional factors shaping user influence in healthcare on Twitter, with a focus on equity, diversity, and trustworthiness.

Indexed as

Social MediaCanadaFemaleHumansMaleSoftwareAltmetricsContinuing Medical EducationDiversityEquityInclusivity

Identifiers

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.