Evidence map›Paper›PMID 37572167›Full record

ArticleInternational ophthalmology2023

Does Twitter improve the dissemination of ophthalmology scientific publications?

Thomas Muecke, Stephen Bacchi, Robert J Casson, WengOnn Chan

Abstract read
In one paragraph

Article in International ophthalmology, 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

4 authors.

Thomas MueckeRoyal Adelaide Hospital, Adelaide, SA, 5000, Australia. a1742509@student.adelaide.edu.au.
Stephen BacchiRoyal Adelaide Hospital, Adelaide, SA, 5000, Australia.
Robert J CassonRoyal Adelaide Hospital, Adelaide, SA, 5000, Australia.
WengOnn ChanRoyal Adelaide Hospital, Adelaide, SA, 5000, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo determine whether Twitter improves dissemination of ophthalmology scientific publications

methodsData were collected on articles published on PubMed between the years 2016 and 2021 (inclusive) and identified with the word "ophthalmology". Twitter performance metrics, including the number of tweets, number of likes, and number of retweets were collected from Twitter using the publicly available scientific API. Machine learning and descriptive statistics were used to outline Twitter performance metrics.

resultsThe number of included articles was 433710. The percentage of articles that were in the top quartile for citation count, which had ≥1 tweet was 34.4% (number 437/1270). Conversely, the percentage of articles that were in the top quartile for citation count, which had 0 tweets was 27.8% (number 12023/43244). When machine learning was used to predict Twitter performance metrics an AUROC of 0.78 was returned. This was associated with an accuracy of 0.97

conclusionThis study has shown preliminary evidence to support that Twitter may improve the dissemination of scientific ophthalmology publications.

Indexed as

OphthalmologySocial MediaHumansAcademic citationsMachine learningPerfomance metricsTwitter

Identifiers

PMID37572167
PMCPMC10724083

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.