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Merging the Traditional with the New: CME-accredited Twitter Journal Clubs

Desai, T.

2020-04-27 medical education
10.1101/2020.04.22.20075606 medRxiv
Show abstract

Twitter journal clubs are increasingly popular amongst healthcare providers. Most journal clubs rely on voluntary physician participation. Offering continuing medical education credit may incentivize and improve these journal clubs. In this investigation a series of 5 consecutive publication-sponsored Twitter journal clubs were analyzed in calendar year 2016, in which the latter 3 journal clubs offered CME credit. Various quality metrics were measured and analyzed to identify sustainable improvements in those journal clubs that offered CME credit. Overall, Twitter journal clubs that offered CME credit performed better in certain quality metrics, to wit activity, originality, and evidence-based tweeting, but fared poorly in number of and type of participant interactions. Twitter journal clubs are in their infancy and physician participation remains steady. Offering CME credit improves certain quality metrics within these journal clubs. This investigation should encourage more publications to sponsor CME-accredited Twitter journal clubs.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
PLOS ONE
● 5266 papers in training set
Top 6%
26.4%
Similar papers in this journal
2
BMC Medical Education
○ 21 papers in training set
Top 0.1%
11.8%
Similar papers in this journal
3
BMJ Open
● 601 papers in training set
Top 3%
6.7%
Similar papers in this journal
4
Journal of Medical Internet Research
◐ 87 papers in training set
Top 0.3%
6.2%
Similar papers in this journal
50% of probability mass above
5
JMIR Formative Research
◐ 33 papers in training set
Top 0.2%
6.2%
Similar papers in this journal
6
Medicine
○ 31 papers in training set
Top 0.2%
5.4%
7
Frontiers in Medicine
○ 120 papers in training set
Top 0.5%
4.3%
8
Cureus
○ 68 papers in training set
Top 1%
3.5%
9
npj Digital Medicine
○ 118 papers in training set
Top 1%
3.4%
10
BMC Medicine
○ 176 papers in training set
Top 1%
3.2%
11
PLOS Digital Health
● 106 papers in training set
Top 2%
2.8%
12
BMC Research Notes
○ 33 papers in training set
Top 0.1%
2.6%
13
Journal of Clinical and Translational Science
◐ 14 papers in training set
Top 0.1%
2.6%
14
Frontiers in Digital Health
○ 24 papers in training set
Top 0.6%
1.7%
15
International Journal of Medical Informatics
○ 26 papers in training set
Top 0.8%
1.5%
16
Scientific Reports
○ 3612 papers in training set
Top 60%
1.3%
17
Heliyon
○ 152 papers in training set
Top 8%
0.8%
18
eLife
● 5828 papers in training set
Top 67%
0.8%
19
Critical Care Medicine
○ 12 papers in training set
Top 0.3%
0.6%
20
Neurosurgery
○ 11 papers in training set
Top 0.4%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.